In this paper,we have calculated the structural,electronic,and optical properties of chalcogenide stannite Cu_(2)CdSnX4(X=S,Se,Te) materials.The calculations are based on the density functional theory (DFT) method and...In this paper,we have calculated the structural,electronic,and optical properties of chalcogenide stannite Cu_(2)CdSnX4(X=S,Se,Te) materials.The calculations are based on the density functional theory (DFT) method and are performed using the Cambridge sequential total energy package (CASTEP) code included in the Biovia Material Studio 20 software.All optical properties have been studied in a domain that extends energetically from 10 meV to 40 eV.Our results show that Cu_(2)CdSnX4(X=S,Se,Te) stannite exhibits absorption in the visible region,the refractive index decreases with increasing energy,and the refractive index values are n=3.2,3.73 and 3.75 for Cu_(2)CdSnS_(4),Cu_(2)CdSnSe_(4)and Cu_(2)CdSnTe_(4),respectively.They show also high conductivity,which implies that this material is promising for solar cells.These results argue in favor of the use of these materials in various potential applications.The density of state,band structures,and structural properties of Cu_(2)CdSnX4(X=S,Se,and Te) stannite are also studied in this work.展开更多
This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temp...This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.展开更多
Osteoclasts are essential for maintaining healthy bone.Pathological elevation of os-teoclastogenesis or osteoclast activity can cause osteoporosis and increase the risk of bone fracture.However,a few options are avail...Osteoclasts are essential for maintaining healthy bone.Pathological elevation of os-teoclastogenesis or osteoclast activity can cause osteoporosis and increase the risk of bone fracture.However,a few options are available for directly measuring osteoclast activity in vivo to test interventions that may affect osteoclasts.Here,we describe an in vivo method to measure osteoclast-mediated bone loss targeted at normal mouse calvaria.The method employs a novel procedure for measuring osteoclast resorption pits using micro-computed tomography.The potential utility of this mouse calvaria model to assess therapies targeting osteoclasts was validated using zoledronic acid,which is a nitrogen-containing bisphosphonate drug used to treat osteoporosis.展开更多
The convergence of Software Defined Networking(SDN)in Internet of Vehicles(IoV)enables a flexible,programmable,and globally visible network control architecture across Road Side Units(RSUs),cloud servers,and automobil...The convergence of Software Defined Networking(SDN)in Internet of Vehicles(IoV)enables a flexible,programmable,and globally visible network control architecture across Road Side Units(RSUs),cloud servers,and automobiles.While this integration enhances scalability and safety,it also raises sophisticated cyberthreats,particularly Distributed Denial of Service(DDoS)attacks.Traditional rule-based anomaly detection methods often struggle to detectmodern low-and-slowDDoS patterns,thereby leading to higher false positives.To this end,this study proposes an explainable hybrid framework to detect DDoS attacks in SDN-enabled IoV(SDN-IoV).The hybrid framework utilizes a Residual Network(ResNet)to capture spatial correlations and a Bi-Long Short-Term Memory(BiLSTM)to capture both forward and backward temporal dependencies in high-dimensional input patterns.To ensure transparency and trustworthiness,themodel integrates the Explainable AI(XAI)technique,i.e.,SHapley Additive exPlanations(SHAP).SHAP highlights the contribution of each feature during the decision-making process,facilitating security analysts to understand the rationale behind the attack classification decision.The SDN-IoV environment is created in Mininet-WiFi and SUMO,and the hybrid model is trained on the CICDDoS2019 security dataset.The simulation results reveal the efficacy of the proposed model in terms of standard performance metrics compared to similar baseline methods.展开更多
CaS phosphor activated with Dy ions is prepared by the solid-state diffusion method. The phosphor is characterized by x-ray powder diffraction, thermogravimetric analysis and photoiuminescence. Defect centres formed i...CaS phosphor activated with Dy ions is prepared by the solid-state diffusion method. The phosphor is characterized by x-ray powder diffraction, thermogravimetric analysis and photoiuminescence. Defect centres formed in CaS：Dy are studied using the technique of electron spin resonance. The thermoluminescence glow curve shows peaks at around 117℃ and 345℃. Irradiated CaS：Dy exhibits ESR lines due to defect centres. The thermal annealing behaviour of one of the defect centres appears to correlate with the TL peaks at 117℃ and 345℃. This centre is characterized by an isotropic g-value of 2.0035 and is assigned to an F^＋ centre.展开更多
Background:Routinely collected health data are increasingly used in clinical research.No study has systematically reviewed the temporal trends in the number of publications and analyzed different aspects of local rese...Background:Routinely collected health data are increasingly used in clinical research.No study has systematically reviewed the temporal trends in the number of publications and analyzed different aspects of local research practices and their variations in Hong Kong,China,with a specific focus on research ethics governance and approval.Methods:PubMed was systematically searched from its inception to March 28,2023,for studies using routinely col-lected healthcare data from Hong Kong.Results:A total of 454 studies were included.Between 2000 and 2009,32 studies were identified.The number of pub-lications increased from 5 to 120 between 2010 and 2022.Of the investigator-led studies using the Hospital Authority(HA)’s cross-cluster data(n=393),327(83.2%)reported receiving ethics approval from a single cluster/university-based REC,whereas 50 studies(12.7%)did not report approval from a REC.For use of the HA Data Collaboration Lab,approval by a single hospital-based or University-based REC is accepted.Repeated submission of identical ethics applications to different RECs is estimated to cost HK$4.2 million yearly.Conclusions:Most studies reported gaining approval from a single cluster REC before retrieval of cross-cluster HA data.Substantial cost savings would result if repeated review of identical ethics applications were not required.展开更多
Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of suc...Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.展开更多
BACKGROUND Pancreaticobiliary maljunction(PBM)is a rare congenital abnormality in pancreaticobiliary duct development.PBM is commonly found in children,and it often leads to acute pancreatitis and other diseases as a ...BACKGROUND Pancreaticobiliary maljunction(PBM)is a rare congenital abnormality in pancreaticobiliary duct development.PBM is commonly found in children,and it often leads to acute pancreatitis and other diseases as a result of pancreaticobiliary reflux.Roux-en-Y choledochojejunostomy is a common surgical method for the treatment of PBM,but there are several associated complications that may occur after this operation.CASE SUMMARY The patient,a 12-year-old female,was hospitalized nearly 20 times in 2021 for recurrent acute pancreatitis.In 2022,she was diagnosed with PBM and underwent laparoscopic common bile duct resection and Roux-en-Y choledochojejunostomy in a tertiary hospital.In the first year after surgery,the patient had more than 10 recurrent acute pancreatitis episodes.After undergoing abdominal computed tomography and other examinations,she was diagnosed with“residual bile duct stones and recurrent acute pancreatitis”.On January 30,2024,the patient was admitted to our hospital due to recurrent upper abdominal pain and was cured through endoscopic retrograde cholangiopancreatography.CONCLUSION This article reports a case of a child with distal residual common bile duct stones and recurrent acute pancreatitis after Roux-en-Y choledochojejunostomy for PBM.The patient was cured through endoscopic retrograde cholangiopancreatography.展开更多
Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics,advancing precision medicine by enabling integration and learning from diverse data sources.The exponential growth of high-dim...Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics,advancing precision medicine by enabling integration and learning from diverse data sources.The exponential growth of high-dimensional healthcare data,encompassing genomic,transcriptomic,and other omics profiles,as well as radiological imaging and histopathological slides,makes this approach increasingly important because,when examined separately,these data sources only offer a fragmented picture of intricate disease processes.Multimodal deep learning leverages the complementary properties of multiple data modalities to enable more accurate prognostic modeling,more robust disease characterization,and improved treatment decision-making.This review provides a comprehensive overview of the current state of multimodal deep learning approaches in medical diagnosis.We classify and examine important application domains,such as(1)radiology,where automated report generation and lesion detection are facilitated by image-text integration;(2)histopathology,where fusion models improve tumor classification and grading;and(3)multi-omics,where molecular subtypes and latent biomarkers are revealed through cross-modal learning.We provide an overview of representative research,methodological advancements,and clinical consequences for each domain.Additionally,we critically analyzed the fundamental issues preventing wider adoption,including computational complexity(particularly in training scalable,multi-branch networks),data heterogeneity(resulting from modality-specific noise,resolution variations,and inconsistent annotations),and the challenge of maintaining significant cross-modal correlations during fusion.These problems impede interpretability,which is crucial for clinical trust and use,in addition to performance and generalizability.Lastly,we outline important areas for future research,including the development of standardized protocols for harmonizing data,the creation of lightweight and interpretable fusion architectures,the integration of real-time clinical decision support systems,and the promotion of cooperation for federated multimodal learning.Our goal is to provide researchers and clinicians with a concise overview of the field’s present state,enduring constraints,and exciting directions for further research through this review.展开更多
Hierarchical porous carbon(HPC)materials exhibit superior performance profiles in various applications due to their well-developed multiscale interconnected pore structures.The synthesis of HPC from natural biomass pr...Hierarchical porous carbon(HPC)materials exhibit superior performance profiles in various applications due to their well-developed multiscale interconnected pore structures.The synthesis of HPC from natural biomass precursors instead of fossil fuel-based precursors has gained considerable attention in recent decades.Rice husk,a globally abundant agricultural waste,offers a sustainable and cost-effective precursor for HPC production.The structural components and inherent silica content of rice husk act as a natural self-template for forming hierarchical pore structures with superior characteristics.In this review,recent studies on preparing rice husk-based HPC are summarized,and synthesis techniques are evaluated.In addition,recent advancements in activation methods and the effect of silica templates are reviewed while comparing these with traditional activated carbon production methods.Potential future directions for research and development activities are also discussed.Rice husk is a highly promising candidate for producing high-performance HPC materials.展开更多
This study evaluated the effectiveness of Chinese herbal foot bath therapy in improving sleep quality among postpartum women of advanced maternal age.A quasi-experimental design was used,involving 60 participants with...This study evaluated the effectiveness of Chinese herbal foot bath therapy in improving sleep quality among postpartum women of advanced maternal age.A quasi-experimental design was used,involving 60 participants with sleep disturbances recruited from Zouping County Traditional Chinese Medicine Hospital.Participants were divided into control and experimental groups,and sleep quality was assessed using the Pittsburgh Sleep Quality Index(PSQI)before and after the intervention.The experimental group received Chinese herbal foot bath therapy,while the control group did not.Post-intervention results showed a significant improvement in sleep quality for the experimental group,with a mean PSQI score of 7.79(SD=2.90),compared to 13.45(SD=2.57)in the control group,indicating continued poor sleep.Statistical analysis confirmed that the therapy led to significant improvements across overall and component PSQI scores.The study concludes that Chinese herbal foot bath therapy is a safe,non-invasive,and cost-effective method to enhance sleep quality among postpartum women,especially those of advanced maternal age.It holds promise as a complementary treatment option and could be integrated into standard postpartum care practices to address sleep disturbances without relying on pharmacological interventions.展开更多
This study presents an enhanced convolutional neural network(CNN)model integrated with Explainable Artificial Intelligence(XAI)techniques for accurate prediction and interpretation of wheat crop diseases.The aim is to...This study presents an enhanced convolutional neural network(CNN)model integrated with Explainable Artificial Intelligence(XAI)techniques for accurate prediction and interpretation of wheat crop diseases.The aim is to streamline the detection process while offering transparent insights into the model’s decision-making to support effective disease management.To evaluate the model,a dataset was collected from wheat fields in Kotli,Azad Kashmir,Pakistan,and tested across multiple data splits.The proposed model demonstrates improved stability,faster conver-gence,and higher classification accuracy.The results show significant improvements in prediction accuracy and stability compared to prior works,achieving up to 100%accuracy in certain configurations.In addition,XAI methods such as Local Interpretable Model-agnostic Explanations(LIME)and Shapley Additive Explanations(SHAP)were employed to explain the model’s predictions,highlighting the most influential features contributing to classification decisions.The combined use of CNN and XAI offers a dual benefit:strong predictive performance and clear interpretability of outcomes,which is especially critical in real-world agricultural applications.These findings underscore the potential of integrating deep learning models with XAI to advance automated plant disease detection.The study offers a precise,reliable,and interpretable solution for improving wheat production and promoting agricultural sustainability.Future extensions of this work may include scaling the dataset across broader regions and incorporating additional modalities such as environmental data to enhance model robustness and generalization.展开更多
Diagnosing dental disorders using routine photographs can significantly reduce chair-side workload and expand access to care.However,most AI-based image analysis systems suffer from limited interpretability and are tr...Diagnosing dental disorders using routine photographs can significantly reduce chair-side workload and expand access to care.However,most AI-based image analysis systems suffer from limited interpretability and are trained on class-imbalanced datasets.In this study,we developed a balanced,transformer-based pipeline to detect three common dental disorders:tooth discoloration,calculus,and hypodontia,from standard color images.After applying a color-standardized preprocessing pipeline and performing stratified data splitting,the proposed vision transformer model was fine-tuned and subsequently evaluated using standard classification benchmarks.The model achieved an impressive accuracy of 98.94%,with precision,recall and F1 scores all greater than or equal to 98%for the three classes.To ensure interpretability,three complementary saliency methods,attention roll-out,layer-wise relevance propagation,and LIME,verified that predictions rely on clinically meaningful cues such as stained enamel,supragingival deposits,and edentulous gaps.The proposed method addresses class imbalance through dataset balancing,enhances interpretability using multiple explanation methods,and demonstrates the effectiveness of transformers over CNNs in dental imaging.This method offers a transparent,real-time screening tool suitable for both clinical and tele-dentistry frameworks,providing accessible,clarity-guided care pathways.展开更多
Background:Long-term exposure to light has emerged as a novel risk factor for metabolic diseases.The whitening of brown adipose tissue(BAT)may play an important role in metabolic disorders caused by long-term continuo...Background:Long-term exposure to light has emerged as a novel risk factor for metabolic diseases.The whitening of brown adipose tissue(BAT)may play an important role in metabolic disorders caused by long-term continuous light exposure.This study aimed to investigate the morphological and functional alterations in BAT under continuous light conditions and to identify traditional Chinese medicine compounds capable of reversing these changes.Methods:A metabolic disorder model was established by subjecting mice to continuous light exposure for 5 weeks.During this period,body weight,food intake,and body fat percentage were monitored.Serum levels of triglyceride(TG),total cholesterol(TC),high density lipoprotein cholesterol(HDL-C),and low density lipoprotein cholesterol(LDL-C)were measured to assess lipid metabolism.Histological changes in BAT were examined using H&E staining.The expression of the thermogenic marker uncoupling protein 1(UCP1)in BAT was determined by RT-qPCR and Western blot to evaluate thermogenic function.RNA sequencing(RNA-seq)was employed to identify differentially expressed genes(DEGs)involved in BAT whitening induced by prolonged continuous light exposure.DEGs were analyzed using the connectivity map(CMap)database to identify potential preventive and therapeutic compounds.The therapeutic efficacy of the selected compounds was subsequently evaluated using the above indicators,and key pathways were validated through western blot analysis.Results:After 5 weeks of continuous light exposure,mice exhibited increased body fat percentage and serum levels of TG,impaired mitochondrial function,reduced thermogenic capacity,and whitening of BAT.Gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analyses indicated that BAT whitening was primarily associated with the adenosine 5'-monophosphate-activated protein kinase(AMPK)signaling pathway,fatty acid metabolism,and circadian rhythm.Ten hub genes identified using Cytoscape were mainly related to AMPK signaling and heat shock proteins.In vivo experiments showed that cordycepin significantly attenuated the increase in body fat percentage caused by prolonged light exposure.This effect was mediated by activation of the AMPK/PGC-1α/UCP1 signaling pathway,which restored the multilocular morphology and thermogenic function of BAT.Conclusion:Cordycepin mitigates continuous light-induced BAT whitening and metabolic disturbances by activating the AMPK signaling pathway.展开更多
Not always climate and cultural contexts are discussed at the forefront of architectural discussions on traditional or vernacular architecture,nevertheless,the construction material also plays a significant part in de...Not always climate and cultural contexts are discussed at the forefront of architectural discussions on traditional or vernacular architecture,nevertheless,the construction material also plays a significant part in defining places’architectural languages.Building from the local materials is an essential ingredient of the local distinctiveness,whilst forming the architectural grand gesture in its context.In Siwa oasis,salt architecture has formed that architectural grand gesture.The vernacular vocabularies adopted by old Bedouins using salt bricks generated Siwa’s unique spirit.In this paper,some examples are illustrated based on a series of site visits to three main sites in Siwa,namely:Old Shali,Abu Shuruf,and Aghourmy.This shows the evolution of Siwa’s vernacular architecture and the role of the architectural language or detrimental effect on the overall quality of architecture.From the site visits,it was observed that building with the traditional technique is now becoming abandoned in Siwa,explained by the local builders to be due to the huge costs required;forcing them to shifting to modern architecture.The influx to building using modern techniques has led to a significant transformation in the urban morphology and spirit of Siwa.Herein lies the scope of this paper:to discuss the impact of the evolution of vernacular architecture on the overall quality of architecture in Siwa and thus identifying the problems which will lead to policy formulation and guidelines for the redevelopment of Siwa in order to“revitalize/resuscitate”its vernacular style accordingly.展开更多
Dear Editor,This letter studies finite-time stability (FTS) of impulsive and switched hybrid systems with delay-dependent impulses. Some conditions, based on Lyapunov method, are proposed for ensuring FTS and estimati...Dear Editor,This letter studies finite-time stability (FTS) of impulsive and switched hybrid systems with delay-dependent impulses. Some conditions, based on Lyapunov method, are proposed for ensuring FTS and estimating settling-time function (STF) of the hybrid systems.When switching dynamics are FTS and impulsive dynamics involve destabilizing delay-dependent impulses, the FTS is retained if the impulses occur infrequently.展开更多
OBJECTIVE:To explore the clinical efficacy and potential mechanisms of Huoxue Jiedu prescription(活血解毒方)in the treatment of polycythemia vera and provide objective basis for the treatment of polycythemia vera by u...OBJECTIVE:To explore the clinical efficacy and potential mechanisms of Huoxue Jiedu prescription(活血解毒方)in the treatment of polycythemia vera and provide objective basis for the treatment of polycythemia vera by using network pharmacology,molecular docking technology,and clinical trials.METHODS:First,network pharmacology and molecular docking analysis methods were used to screen the main targets of Huoxue Jiedu prescription in the treatment of polycythemia vera.Patients who were first diagnosed with polycythemia vera in the Hematology Department of Langfang Hospital of Traditional Chinese Medicine from September 2022 to January 2024 were enrolled,and a clinical randomized controlled study was conducted.Sixty patients with primary polycythemia who met the inclusion criteria were randomly divided into the treatment group and the control group,with 30 cases in each group.The control group received oral Western Medicine treatment,whereas the treatment group received oral Western Medicine combined with Huoxue Jiedu prescription treatment,and three courses were observed.The differences in the efficacy of Traditional Chinese and Western Medicine,hematological indicators,coagulation function,and expression of related targets before and after treatment were observed between the two groups.SPSS 26.0 statistical software was used for data analysis,and the treatment results of the two groups were compared to observe their clinical efficacy and mechanisms.RESULTS:Network pharmacology results identified the phosphatidyqinositol-3 kinase(PI3K-Akt)pathway as an important pathway of Huoxue Jiedu prescription in the treatment of polycythemia vera PV,which was closely related to thrombosis.Clinical trial results showed that Huoxue Jiedu prescription improved efficacy and hematological indicators,reduced patients'coagulation indicators such as D-dimer and fibrinogen,reduced activated partial thromboplastin time and prothrombin time,and decreased the expression of PI3K and Serine/threonine-protein kinase AKT1(AKT1)m RNA in peripheral blood.CONCLUSION:Network pharmacology predicted the corresponding targets of traditional Chinese medicine to a certain extent.Huoxue Jiedu prescription could enhance clinical efficacy,improve hematological indicators,and reduce coagulation indicators through antithrombotic effect by inhibiting the expression of PI3K and AKT1.展开更多
The prevalence of autism and attention deficit/hyperactivity disorders is increasing worldwide.Recent studies suggest the excessive intake of ultra-processed food plays a role in the inheritance of these disorders via...The prevalence of autism and attention deficit/hyperactivity disorders is increasing worldwide.Recent studies suggest the excessive intake of ultra-processed food plays a role in the inheritance of these disorders via heavy metal exposures and nutritional deficits that impact the expression of genes.In the case of the metallothionein(MT)gene,biomarker studies show dietary zinc(Zn)deficits impact MT protein levels in children with autism and are associated with the bioaccumulation of lead and/or mercury in children exhibiting autism/attention deficit/hyperactivity disorders symptomology.The impact of dietary changes on lead and mercury exposures and MT gene behavior could be determined using a randomized test and control group design.Pregnant women serving in the testgroup would participate in a nutritional epigenetics education intervention/course designed to reduce ultra-processed food intake and heavy metal levels in blood while increasing whole food intake and MT and Zn levels.Changes in maternal diet would be measured using data derived from an online diet survey administered to the test and control groups pre-post intervention.Changes in maternal lead,mercury,Zn,and MT levels would be measured via blood sample analyses prior to the intervention and after childbirth via cord blood analyses to determine infant risk factors.展开更多
Honey, an apicultural product with a complex chemical composition, contains numerous bioactive compounds with potential antimicrobial effects. This study investigated the effect of Apis mellifera honey from Brazil’s ...Honey, an apicultural product with a complex chemical composition, contains numerous bioactive compounds with potential antimicrobial effects. This study investigated the effect of Apis mellifera honey from Brazil’s Central-West Region, combined with antibiotics, on bacterial membrane permeability, exploring the contributions of bioactive compounds and the botanical origin of honey. Six fresh Apis mellifera honey samples and their fractions (hexane and ethyl acetate) were analyzed, for a total of 18 samples. The bacteria Staphylococcus epidermidis, Helicobacter pylori and Enterococcus faecalis were used for antibacterial activity tests, which included minimum inhibitory concentration (MIC) determination and synergistic effect (checkerboard) assays. The total polyphenol and flavonoid contents were quantified, and the botanical origin was determined based on pollen analysis. The tested honey samples significantly affected bacterial membrane permeability when combined with rifampicin and clarithromycin. Although many honey-derived bioactive compounds, when isolated, did not exhibit significant activity against these bacteria, the additive or synergistic effect of multiple compounds acting on different targets appears to potentiate the antibacterial action. Descriptive statistical analysis, including means and 95% confidence intervals, confirmed the relevance of the findings. This study has provided an important discovery: Honey has an effect on bacterial membrane permeability, although the specific mechanisms involved in this process require further investigation.展开更多
This paper presents a thermophysical study approach for a pure environmental control system(ECS),incorporating the geometric dimensions of heat exchangers,ram air duct,and air cycle machine(ACM)blades of the Sabreline...This paper presents a thermophysical study approach for a pure environmental control system(ECS),incorporating the geometric dimensions of heat exchangers,ram air duct,and air cycle machine(ACM)blades of the Sabreliner’s environmental control system.Real flight scenarios are simulated by considering flight input variables such as altitude,aircraft speed,compression ratio of the air cycle machine,and the mass flow rate of bleed air.The study evaluates the coefficient of performance(COP)of the environmental control system,the heat exchanger efficiencies,and the work distribution of the air cycle machine based on five flight scenarios,with a particular focus on considering the effects of humidity on environmental control system performance.The results demonstrate that at cruising altitude(11,000 m),air humidity conditions allow an increase in the COP of around 9.28%compared to dry conditions.Conversely,on land,humidity conditions reduce the performance by 4.26%compared to dry conditions.It was also found that the effects of humidity at high aircraft speeds become negligible.In general terms,the humidity conditions in the air proved to have positive effects on the environmental control system’s performance but negative effects on the heat exchanger efficiencies,reducing them by 0.22%.Additionally,land conditions reflect significant improvements in performance when the compression ratio of the air cycle machine is varied.Furthermore,in the work distribution of the air cycle machine,humidity conditions were demonstrated to consume 2.91%less work fromthe turbine compared to dry conditions.展开更多
基金supported by the University Sultan Moulay Slimane,Beni Mellal,Morocco。
文摘In this paper,we have calculated the structural,electronic,and optical properties of chalcogenide stannite Cu_(2)CdSnX4(X=S,Se,Te) materials.The calculations are based on the density functional theory (DFT) method and are performed using the Cambridge sequential total energy package (CASTEP) code included in the Biovia Material Studio 20 software.All optical properties have been studied in a domain that extends energetically from 10 meV to 40 eV.Our results show that Cu_(2)CdSnX4(X=S,Se,Te) stannite exhibits absorption in the visible region,the refractive index decreases with increasing energy,and the refractive index values are n=3.2,3.73 and 3.75 for Cu_(2)CdSnS_(4),Cu_(2)CdSnSe_(4)and Cu_(2)CdSnTe_(4),respectively.They show also high conductivity,which implies that this material is promising for solar cells.These results argue in favor of the use of these materials in various potential applications.The density of state,band structures,and structural properties of Cu_(2)CdSnX4(X=S,Se,and Te) stannite are also studied in this work.
文摘This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.
基金National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health,Grant/Award Number:R01AR069044Rutgers-New Jersey Medical School Department of Orthopaedics。
文摘Osteoclasts are essential for maintaining healthy bone.Pathological elevation of os-teoclastogenesis or osteoclast activity can cause osteoporosis and increase the risk of bone fracture.However,a few options are available for directly measuring osteoclast activity in vivo to test interventions that may affect osteoclasts.Here,we describe an in vivo method to measure osteoclast-mediated bone loss targeted at normal mouse calvaria.The method employs a novel procedure for measuring osteoclast resorption pits using micro-computed tomography.The potential utility of this mouse calvaria model to assess therapies targeting osteoclasts was validated using zoledronic acid,which is a nitrogen-containing bisphosphonate drug used to treat osteoporosis.
基金extend their appreciation to the Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R760)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors also extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through small group research under grant number RGP2/714/46.
文摘The convergence of Software Defined Networking(SDN)in Internet of Vehicles(IoV)enables a flexible,programmable,and globally visible network control architecture across Road Side Units(RSUs),cloud servers,and automobiles.While this integration enhances scalability and safety,it also raises sophisticated cyberthreats,particularly Distributed Denial of Service(DDoS)attacks.Traditional rule-based anomaly detection methods often struggle to detectmodern low-and-slowDDoS patterns,thereby leading to higher false positives.To this end,this study proposes an explainable hybrid framework to detect DDoS attacks in SDN-enabled IoV(SDN-IoV).The hybrid framework utilizes a Residual Network(ResNet)to capture spatial correlations and a Bi-Long Short-Term Memory(BiLSTM)to capture both forward and backward temporal dependencies in high-dimensional input patterns.To ensure transparency and trustworthiness,themodel integrates the Explainable AI(XAI)technique,i.e.,SHapley Additive exPlanations(SHAP).SHAP highlights the contribution of each feature during the decision-making process,facilitating security analysts to understand the rationale behind the attack classification decision.The SDN-IoV environment is created in Mininet-WiFi and SUMO,and the hybrid model is trained on the CICDDoS2019 security dataset.The simulation results reveal the efficacy of the proposed model in terms of standard performance metrics compared to similar baseline methods.
基金Supported by the National Natural Science Foundation of China under Grant No 20325516, and the Fund of National Grade Key laboratory of Tunable Laser Technology under Grant No 51472040JW1101.
文摘CaS phosphor activated with Dy ions is prepared by the solid-state diffusion method. The phosphor is characterized by x-ray powder diffraction, thermogravimetric analysis and photoiuminescence. Defect centres formed in CaS：Dy are studied using the technique of electron spin resonance. The thermoluminescence glow curve shows peaks at around 117℃ and 345℃. Irradiated CaS：Dy exhibits ESR lines due to defect centres. The thermal annealing behaviour of one of the defect centres appears to correlate with the TL peaks at 117℃ and 345℃. This centre is characterized by an isotropic g-value of 2.0035 and is assigned to an F^＋ centre.
文摘Background:Routinely collected health data are increasingly used in clinical research.No study has systematically reviewed the temporal trends in the number of publications and analyzed different aspects of local research practices and their variations in Hong Kong,China,with a specific focus on research ethics governance and approval.Methods:PubMed was systematically searched from its inception to March 28,2023,for studies using routinely col-lected healthcare data from Hong Kong.Results:A total of 454 studies were included.Between 2000 and 2009,32 studies were identified.The number of pub-lications increased from 5 to 120 between 2010 and 2022.Of the investigator-led studies using the Hospital Authority(HA)’s cross-cluster data(n=393),327(83.2%)reported receiving ethics approval from a single cluster/university-based REC,whereas 50 studies(12.7%)did not report approval from a REC.For use of the HA Data Collaboration Lab,approval by a single hospital-based or University-based REC is accepted.Repeated submission of identical ethics applications to different RECs is estimated to cost HK$4.2 million yearly.Conclusions:Most studies reported gaining approval from a single cluster REC before retrieval of cross-cluster HA data.Substantial cost savings would result if repeated review of identical ethics applications were not required.
文摘Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.
文摘BACKGROUND Pancreaticobiliary maljunction(PBM)is a rare congenital abnormality in pancreaticobiliary duct development.PBM is commonly found in children,and it often leads to acute pancreatitis and other diseases as a result of pancreaticobiliary reflux.Roux-en-Y choledochojejunostomy is a common surgical method for the treatment of PBM,but there are several associated complications that may occur after this operation.CASE SUMMARY The patient,a 12-year-old female,was hospitalized nearly 20 times in 2021 for recurrent acute pancreatitis.In 2022,she was diagnosed with PBM and underwent laparoscopic common bile duct resection and Roux-en-Y choledochojejunostomy in a tertiary hospital.In the first year after surgery,the patient had more than 10 recurrent acute pancreatitis episodes.After undergoing abdominal computed tomography and other examinations,she was diagnosed with“residual bile duct stones and recurrent acute pancreatitis”.On January 30,2024,the patient was admitted to our hospital due to recurrent upper abdominal pain and was cured through endoscopic retrograde cholangiopancreatography.CONCLUSION This article reports a case of a child with distal residual common bile duct stones and recurrent acute pancreatitis after Roux-en-Y choledochojejunostomy for PBM.The patient was cured through endoscopic retrograde cholangiopancreatography.
文摘Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics,advancing precision medicine by enabling integration and learning from diverse data sources.The exponential growth of high-dimensional healthcare data,encompassing genomic,transcriptomic,and other omics profiles,as well as radiological imaging and histopathological slides,makes this approach increasingly important because,when examined separately,these data sources only offer a fragmented picture of intricate disease processes.Multimodal deep learning leverages the complementary properties of multiple data modalities to enable more accurate prognostic modeling,more robust disease characterization,and improved treatment decision-making.This review provides a comprehensive overview of the current state of multimodal deep learning approaches in medical diagnosis.We classify and examine important application domains,such as(1)radiology,where automated report generation and lesion detection are facilitated by image-text integration;(2)histopathology,where fusion models improve tumor classification and grading;and(3)multi-omics,where molecular subtypes and latent biomarkers are revealed through cross-modal learning.We provide an overview of representative research,methodological advancements,and clinical consequences for each domain.Additionally,we critically analyzed the fundamental issues preventing wider adoption,including computational complexity(particularly in training scalable,multi-branch networks),data heterogeneity(resulting from modality-specific noise,resolution variations,and inconsistent annotations),and the challenge of maintaining significant cross-modal correlations during fusion.These problems impede interpretability,which is crucial for clinical trust and use,in addition to performance and generalizability.Lastly,we outline important areas for future research,including the development of standardized protocols for harmonizing data,the creation of lightweight and interpretable fusion architectures,the integration of real-time clinical decision support systems,and the promotion of cooperation for federated multimodal learning.Our goal is to provide researchers and clinicians with a concise overview of the field’s present state,enduring constraints,and exciting directions for further research through this review.
文摘Hierarchical porous carbon(HPC)materials exhibit superior performance profiles in various applications due to their well-developed multiscale interconnected pore structures.The synthesis of HPC from natural biomass precursors instead of fossil fuel-based precursors has gained considerable attention in recent decades.Rice husk,a globally abundant agricultural waste,offers a sustainable and cost-effective precursor for HPC production.The structural components and inherent silica content of rice husk act as a natural self-template for forming hierarchical pore structures with superior characteristics.In this review,recent studies on preparing rice husk-based HPC are summarized,and synthesis techniques are evaluated.In addition,recent advancements in activation methods and the effect of silica templates are reviewed while comparing these with traditional activated carbon production methods.Potential future directions for research and development activities are also discussed.Rice husk is a highly promising candidate for producing high-performance HPC materials.
文摘This study evaluated the effectiveness of Chinese herbal foot bath therapy in improving sleep quality among postpartum women of advanced maternal age.A quasi-experimental design was used,involving 60 participants with sleep disturbances recruited from Zouping County Traditional Chinese Medicine Hospital.Participants were divided into control and experimental groups,and sleep quality was assessed using the Pittsburgh Sleep Quality Index(PSQI)before and after the intervention.The experimental group received Chinese herbal foot bath therapy,while the control group did not.Post-intervention results showed a significant improvement in sleep quality for the experimental group,with a mean PSQI score of 7.79(SD=2.90),compared to 13.45(SD=2.57)in the control group,indicating continued poor sleep.Statistical analysis confirmed that the therapy led to significant improvements across overall and component PSQI scores.The study concludes that Chinese herbal foot bath therapy is a safe,non-invasive,and cost-effective method to enhance sleep quality among postpartum women,especially those of advanced maternal age.It holds promise as a complementary treatment option and could be integrated into standard postpartum care practices to address sleep disturbances without relying on pharmacological interventions.
文摘This study presents an enhanced convolutional neural network(CNN)model integrated with Explainable Artificial Intelligence(XAI)techniques for accurate prediction and interpretation of wheat crop diseases.The aim is to streamline the detection process while offering transparent insights into the model’s decision-making to support effective disease management.To evaluate the model,a dataset was collected from wheat fields in Kotli,Azad Kashmir,Pakistan,and tested across multiple data splits.The proposed model demonstrates improved stability,faster conver-gence,and higher classification accuracy.The results show significant improvements in prediction accuracy and stability compared to prior works,achieving up to 100%accuracy in certain configurations.In addition,XAI methods such as Local Interpretable Model-agnostic Explanations(LIME)and Shapley Additive Explanations(SHAP)were employed to explain the model’s predictions,highlighting the most influential features contributing to classification decisions.The combined use of CNN and XAI offers a dual benefit:strong predictive performance and clear interpretability of outcomes,which is especially critical in real-world agricultural applications.These findings underscore the potential of integrating deep learning models with XAI to advance automated plant disease detection.The study offers a precise,reliable,and interpretable solution for improving wheat production and promoting agricultural sustainability.Future extensions of this work may include scaling the dataset across broader regions and incorporating additional modalities such as environmental data to enhance model robustness and generalization.
文摘Diagnosing dental disorders using routine photographs can significantly reduce chair-side workload and expand access to care.However,most AI-based image analysis systems suffer from limited interpretability and are trained on class-imbalanced datasets.In this study,we developed a balanced,transformer-based pipeline to detect three common dental disorders:tooth discoloration,calculus,and hypodontia,from standard color images.After applying a color-standardized preprocessing pipeline and performing stratified data splitting,the proposed vision transformer model was fine-tuned and subsequently evaluated using standard classification benchmarks.The model achieved an impressive accuracy of 98.94%,with precision,recall and F1 scores all greater than or equal to 98%for the three classes.To ensure interpretability,three complementary saliency methods,attention roll-out,layer-wise relevance propagation,and LIME,verified that predictions rely on clinically meaningful cues such as stained enamel,supragingival deposits,and edentulous gaps.The proposed method addresses class imbalance through dataset balancing,enhances interpretability using multiple explanation methods,and demonstrates the effectiveness of transformers over CNNs in dental imaging.This method offers a transparent,real-time screening tool suitable for both clinical and tele-dentistry frameworks,providing accessible,clarity-guided care pathways.
文摘Background:Long-term exposure to light has emerged as a novel risk factor for metabolic diseases.The whitening of brown adipose tissue(BAT)may play an important role in metabolic disorders caused by long-term continuous light exposure.This study aimed to investigate the morphological and functional alterations in BAT under continuous light conditions and to identify traditional Chinese medicine compounds capable of reversing these changes.Methods:A metabolic disorder model was established by subjecting mice to continuous light exposure for 5 weeks.During this period,body weight,food intake,and body fat percentage were monitored.Serum levels of triglyceride(TG),total cholesterol(TC),high density lipoprotein cholesterol(HDL-C),and low density lipoprotein cholesterol(LDL-C)were measured to assess lipid metabolism.Histological changes in BAT were examined using H&E staining.The expression of the thermogenic marker uncoupling protein 1(UCP1)in BAT was determined by RT-qPCR and Western blot to evaluate thermogenic function.RNA sequencing(RNA-seq)was employed to identify differentially expressed genes(DEGs)involved in BAT whitening induced by prolonged continuous light exposure.DEGs were analyzed using the connectivity map(CMap)database to identify potential preventive and therapeutic compounds.The therapeutic efficacy of the selected compounds was subsequently evaluated using the above indicators,and key pathways were validated through western blot analysis.Results:After 5 weeks of continuous light exposure,mice exhibited increased body fat percentage and serum levels of TG,impaired mitochondrial function,reduced thermogenic capacity,and whitening of BAT.Gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analyses indicated that BAT whitening was primarily associated with the adenosine 5'-monophosphate-activated protein kinase(AMPK)signaling pathway,fatty acid metabolism,and circadian rhythm.Ten hub genes identified using Cytoscape were mainly related to AMPK signaling and heat shock proteins.In vivo experiments showed that cordycepin significantly attenuated the increase in body fat percentage caused by prolonged light exposure.This effect was mediated by activation of the AMPK/PGC-1α/UCP1 signaling pathway,which restored the multilocular morphology and thermogenic function of BAT.Conclusion:Cordycepin mitigates continuous light-induced BAT whitening and metabolic disturbances by activating the AMPK signaling pathway.
文摘Not always climate and cultural contexts are discussed at the forefront of architectural discussions on traditional or vernacular architecture,nevertheless,the construction material also plays a significant part in defining places’architectural languages.Building from the local materials is an essential ingredient of the local distinctiveness,whilst forming the architectural grand gesture in its context.In Siwa oasis,salt architecture has formed that architectural grand gesture.The vernacular vocabularies adopted by old Bedouins using salt bricks generated Siwa’s unique spirit.In this paper,some examples are illustrated based on a series of site visits to three main sites in Siwa,namely:Old Shali,Abu Shuruf,and Aghourmy.This shows the evolution of Siwa’s vernacular architecture and the role of the architectural language or detrimental effect on the overall quality of architecture.From the site visits,it was observed that building with the traditional technique is now becoming abandoned in Siwa,explained by the local builders to be due to the huge costs required;forcing them to shifting to modern architecture.The influx to building using modern techniques has led to a significant transformation in the urban morphology and spirit of Siwa.Herein lies the scope of this paper:to discuss the impact of the evolution of vernacular architecture on the overall quality of architecture in Siwa and thus identifying the problems which will lead to policy formulation and guidelines for the redevelopment of Siwa in order to“revitalize/resuscitate”its vernacular style accordingly.
基金supported by the National Natural Science Foundation of China(61833005)
文摘Dear Editor,This letter studies finite-time stability (FTS) of impulsive and switched hybrid systems with delay-dependent impulses. Some conditions, based on Lyapunov method, are proposed for ensuring FTS and estimating settling-time function (STF) of the hybrid systems.When switching dynamics are FTS and impulsive dynamics involve destabilizing delay-dependent impulses, the FTS is retained if the impulses occur infrequently.
基金Scientific Research Project of the Chinese Society of Ethnographic Medicine:A Feasibility Study on the Treatment of Polycythemia Vera with Stasis-Expelling Decoctions Based on the Theory of Activating Blood and Resolving Stasis(2020,2020ZY175-440801)Scientific Research Project of the Chinese Society of Traditional Chinese Medicine:a Real-World Prospective Study on the Use of Stasis-Expelling Decoctions in Treating Polycythemia Vera(2021,202169-003)+2 种基金National Administration of Traditional Chinese Medicine Yang Shulian’s National Famous Traditional Chinese Medicine Expert Inheritance Studio Construction Project(State Administration of Traditional Chinese Medicine Jiaohan[2022]No.75)Hebei Province Graduate Innovation Funding Project(2023,PX-19221895)Beijing-Tianjin-Hebei Traditional Chinese Medicine Collaborative Specialty Alliance(Hebei Traditional Chinese Medicine[2024]No.11)。
文摘OBJECTIVE:To explore the clinical efficacy and potential mechanisms of Huoxue Jiedu prescription(活血解毒方)in the treatment of polycythemia vera and provide objective basis for the treatment of polycythemia vera by using network pharmacology,molecular docking technology,and clinical trials.METHODS:First,network pharmacology and molecular docking analysis methods were used to screen the main targets of Huoxue Jiedu prescription in the treatment of polycythemia vera.Patients who were first diagnosed with polycythemia vera in the Hematology Department of Langfang Hospital of Traditional Chinese Medicine from September 2022 to January 2024 were enrolled,and a clinical randomized controlled study was conducted.Sixty patients with primary polycythemia who met the inclusion criteria were randomly divided into the treatment group and the control group,with 30 cases in each group.The control group received oral Western Medicine treatment,whereas the treatment group received oral Western Medicine combined with Huoxue Jiedu prescription treatment,and three courses were observed.The differences in the efficacy of Traditional Chinese and Western Medicine,hematological indicators,coagulation function,and expression of related targets before and after treatment were observed between the two groups.SPSS 26.0 statistical software was used for data analysis,and the treatment results of the two groups were compared to observe their clinical efficacy and mechanisms.RESULTS:Network pharmacology results identified the phosphatidyqinositol-3 kinase(PI3K-Akt)pathway as an important pathway of Huoxue Jiedu prescription in the treatment of polycythemia vera PV,which was closely related to thrombosis.Clinical trial results showed that Huoxue Jiedu prescription improved efficacy and hematological indicators,reduced patients'coagulation indicators such as D-dimer and fibrinogen,reduced activated partial thromboplastin time and prothrombin time,and decreased the expression of PI3K and Serine/threonine-protein kinase AKT1(AKT1)m RNA in peripheral blood.CONCLUSION:Network pharmacology predicted the corresponding targets of traditional Chinese medicine to a certain extent.Huoxue Jiedu prescription could enhance clinical efficacy,improve hematological indicators,and reduce coagulation indicators through antithrombotic effect by inhibiting the expression of PI3K and AKT1.
文摘The prevalence of autism and attention deficit/hyperactivity disorders is increasing worldwide.Recent studies suggest the excessive intake of ultra-processed food plays a role in the inheritance of these disorders via heavy metal exposures and nutritional deficits that impact the expression of genes.In the case of the metallothionein(MT)gene,biomarker studies show dietary zinc(Zn)deficits impact MT protein levels in children with autism and are associated with the bioaccumulation of lead and/or mercury in children exhibiting autism/attention deficit/hyperactivity disorders symptomology.The impact of dietary changes on lead and mercury exposures and MT gene behavior could be determined using a randomized test and control group design.Pregnant women serving in the testgroup would participate in a nutritional epigenetics education intervention/course designed to reduce ultra-processed food intake and heavy metal levels in blood while increasing whole food intake and MT and Zn levels.Changes in maternal diet would be measured using data derived from an online diet survey administered to the test and control groups pre-post intervention.Changes in maternal lead,mercury,Zn,and MT levels would be measured via blood sample analyses prior to the intervention and after childbirth via cord blood analyses to determine infant risk factors.
文摘Honey, an apicultural product with a complex chemical composition, contains numerous bioactive compounds with potential antimicrobial effects. This study investigated the effect of Apis mellifera honey from Brazil’s Central-West Region, combined with antibiotics, on bacterial membrane permeability, exploring the contributions of bioactive compounds and the botanical origin of honey. Six fresh Apis mellifera honey samples and their fractions (hexane and ethyl acetate) were analyzed, for a total of 18 samples. The bacteria Staphylococcus epidermidis, Helicobacter pylori and Enterococcus faecalis were used for antibacterial activity tests, which included minimum inhibitory concentration (MIC) determination and synergistic effect (checkerboard) assays. The total polyphenol and flavonoid contents were quantified, and the botanical origin was determined based on pollen analysis. The tested honey samples significantly affected bacterial membrane permeability when combined with rifampicin and clarithromycin. Although many honey-derived bioactive compounds, when isolated, did not exhibit significant activity against these bacteria, the additive or synergistic effect of multiple compounds acting on different targets appears to potentiate the antibacterial action. Descriptive statistical analysis, including means and 95% confidence intervals, confirmed the relevance of the findings. This study has provided an important discovery: Honey has an effect on bacterial membrane permeability, although the specific mechanisms involved in this process require further investigation.
文摘This paper presents a thermophysical study approach for a pure environmental control system(ECS),incorporating the geometric dimensions of heat exchangers,ram air duct,and air cycle machine(ACM)blades of the Sabreliner’s environmental control system.Real flight scenarios are simulated by considering flight input variables such as altitude,aircraft speed,compression ratio of the air cycle machine,and the mass flow rate of bleed air.The study evaluates the coefficient of performance(COP)of the environmental control system,the heat exchanger efficiencies,and the work distribution of the air cycle machine based on five flight scenarios,with a particular focus on considering the effects of humidity on environmental control system performance.The results demonstrate that at cruising altitude(11,000 m),air humidity conditions allow an increase in the COP of around 9.28%compared to dry conditions.Conversely,on land,humidity conditions reduce the performance by 4.26%compared to dry conditions.It was also found that the effects of humidity at high aircraft speeds become negligible.In general terms,the humidity conditions in the air proved to have positive effects on the environmental control system’s performance but negative effects on the heat exchanger efficiencies,reducing them by 0.22%.Additionally,land conditions reflect significant improvements in performance when the compression ratio of the air cycle machine is varied.Furthermore,in the work distribution of the air cycle machine,humidity conditions were demonstrated to consume 2.91%less work fromthe turbine compared to dry conditions.
