It has been well accepted that the folding energy landscape may resemble a funnel according to the theory of protein folding. This theory of ＂folding funnel＂ has been extensively studied and thought to play an impor...It has been well accepted that the folding energy landscape may resemble a funnel according to the theory of protein folding. This theory of ＂folding funnel＂ has been extensively studied and thought to play an important role in guiding the sampling process of the protein folding and refinement in protein structure prediction. Here, we have investigated the relationship between the ＂funnel likeness＂ of protein folding and the size/structure of the proteins based on a set of non-homologous proteins we have recently evaluated using a statistical mechanicsbased scoring function ITScorePro. It was found that larger proteins that consist of more helix/sheet structures tend to have a higher score-Root Mean Square Deviation（RMSD） correlation（or a more funnel like energy landscape）.Another measurement in protein folding, Z-score, has also shown some correlation with the size of the proteins.As expected, proteins with a better ＂olding funnel likeness＂（or score-RMSD correlation） tend to have a betterpredicted conformation with a lower RMSD from their native structures. These findings can be extremely valuable for the development and improvement of sampling and scoring algorithms for protein structure prediction.展开更多
Objective Cachexia occurs in approximately half of hepatocellular carcinoma(HCC)patients as the disease progresses and is correlated with a poor prognosis.Therefore,early identification of HCC patients at risk of deve...Objective Cachexia occurs in approximately half of hepatocellular carcinoma(HCC)patients as the disease progresses and is correlated with a poor prognosis.Therefore,early identification of HCC patients at risk of developing cachexia and their prognosis is crucial.This study investigated the functional liver imaging score(FLIS)derived from gadoxetic acid-enhanced magnetic resonance imaging(MRI)to identify cachexia in HCC patients and their prognosis.Methods Pretreatment clinical and MRI data from 339 HCC patients who underwent gadoxetic acid-enhanced MRI scans were retrospectively collected.Patient weights were recorded for 6 months following the MRI scan to diagnose cachexia.The FLIS was calculated as the sum of the enhancement quality score,the excretion quality score,and the portal vein sign quality score.A Cox proportional hazards model was used to determine the significant factors affecting overall survival(OS).Multivariable logistic regression was then conducted to identify variables predicting cachexia in HCC patients,which were subsequently used to predict OS.Results Cox regression analysis revealed a significant association between cachexia and worse OS.Both FLIS(0–4 vs.5–6 points)(OR,9.20;95%CI:4.68–18.10;P<0.001)andα-fetoprotein>100 ng/mL(OR,4.08;95%CI:2.13–7.83;P<0.001)emerged as significant predictors of cachexia in patients with HCC.Furthermore,FLIS(0–4 vs.5–6 points)(HR,1.73;95%CI:1.19–2.51;P=0.004)was significantly associated with OS.Patients in the FLIS 0–4 points group had shorter OS than those in the FLIS 5–6 points group[20 months(95%CI,14.7–25.3)vs.43 months(95%CI,27.7–58.3);P=0.001].Conclusion Cachexia was associated with worse OS.The functional liver imaging score emerged as a significant predictor of cachexia in HCC patients and their prognosis.展开更多
AIM To develop a new scoring system, nutech functional scores(NFS) for assessing the patients with spinal cord injury(SCI).METHODS The conventional scale, American Spinal Injury Association's(ASIA) impairment scal...AIM To develop a new scoring system, nutech functional scores(NFS) for assessing the patients with spinal cord injury(SCI).METHODS The conventional scale, American Spinal Injury Association's(ASIA) impairment scale is a measure which precisely describes the severity of the SCI.However, it has various limitations which lead to incomplete assessment of SCI patients.We have developed a 63 point scoring system, i.e., NFS for patients suffering with SCI.A list of symptoms either common or rare that were found to be associated with SCI was recorded for each patient.On the basis of these lists, we have developed NFS.RESULTS These lists served as a base to prepare NFS, a 63 point positional(each symptom is sub-graded and get points based on position) and directional(moves in direction BAD → GOOD) scoring system.For non-progressive diseases, 1, 2, 3, 4, 5 denote worst, bad, moderate, good and best(normal), respectively.NFS for SCI has been divided into different groups based on the affected part of the body being assessed, i.e., motor assessment(shoulders, elbow, wrist, fingers-grasp, fingers-release, hip, knee, ankle and toe), sensory assessment, autonomic assessment, bed sore assessment and general assessment.As probability based studies required a range of(-1, 1) or at least the range of(0, 1) to be useful for real world analysis, the grades were converted to respective numeric values.CONCLUSION NFS can be considered as a unique tool to assess the improvement in patients with SCI as it overcomes the limitations of ASIA impairment scale.展开更多
Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective to...Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.展开更多
[Objectives]To explore the effects of electroacupuncture combined with rehabilitation training on knee joint function,three-dimensional(3D)gait,and inflammatory markers in patients with knee osteoarthritis(KOA)of cold...[Objectives]To explore the effects of electroacupuncture combined with rehabilitation training on knee joint function,three-dimensional(3D)gait,and inflammatory markers in patients with knee osteoarthritis(KOA)of cold-dampness obstruction syndrome.[Methods]A total of 162 KOA patients admitted to Huadong Hospital Affiliated to Fudan University from January 2021 to May 2023 were enrolled and randomly divided into an electroacupuncture group and a control group,with 81 patients in each group.The control group received routine rehabilitation training,while the electroacupuncture group received electroacupuncture treatment in addition to the same rehabilitation training,both for 4 weeks.The efficacy,syndrome scores,Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC),Lysholm Knee Score(LKS),3D gait parameters,and levels of inflammatory markers were compared between the two groups.[Results]Following treatment,the total effective rate in the electroacupuncture group was 92.59%,which was significantly higher than 77.78%observed in the control group(P<0.05).Additionally,the electroacupuncture group exhibited lower TCM syndrome scores(P<0.05),reduced WOMAC scores,and elevated LKS scores compared to the control group(P<0.05).Gait parameters,including step frequency,step speed,stride length,initial ground contact flexion angle,maximum swing phase extension angle,and support phase extension angle,were all higher in the electroacupuncture group.Additionally,the sagittal plane maximum abduction moment was lower in the electroacupuncture group.Inflammatory markers showed that interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)were lower in the electroacupuncture group,while transforming growth factor-β1(TGF-β1)was higher(P<0.05).[Conclusions]Electroacupuncture combined with rehabilitation training effectively enhances clinical efficacy,alleviates symptoms,improves knee joint mobility and walking ability,enhances knee function scores,and reduces inflammatory levels,contributing to the rapid recovery of knee joints in KOA patients.展开更多
Objective:To conduct a scoping review on the application status of the Functional Activity Score(FAS)in postoperative active pain management in China,providing a reference for its standardized and normative promotion....Objective:To conduct a scoping review on the application status of the Functional Activity Score(FAS)in postoperative active pain management in China,providing a reference for its standardized and normative promotion.Methods:Computerized searches of Chinese and English databases were performed to collect studies published by Chinese scholars from 2005 to July 2025 on the application of FAS in postoperative active pain management.After strict screening,the basic characteristics,application fields,assessment models,evaluation timing,types of functional activities,and clinical outcomes of the included literature were systematically analyzed.Results:A total of 18 studies were included,involving surgical types such as thoracic surgery,general surgery,and orthopedics.All studies adopted FAS combined with the Numeric Rating Scale(NRS)for assessment,with evaluation timing mostly concentrated within 72 hours postoperatively.The selected functional activities primarily included respiration-related and limb movements.Evaluation indicators covered pain control,functional recovery,complications,adverse events,patient experience,and tool assessment,with most studies reporting positive outcomes.Conclusion:FAS can effectively enhance pain control and promote functional recovery in postoperative active pain management in China,demonstrating high clinical value.However,existing studies exhibit inconsistencies in assessment criteria,selection of activity types,and research quality.展开更多
BACKGROUND Long-term treatment of attention deficit/hyperactivity disorder(ADHD)is associated with adverse events,such as nausea and vomiting,dizziness,and sleep disturbances,and poor maintenance of late ADHD medicati...BACKGROUND Long-term treatment of attention deficit/hyperactivity disorder(ADHD)is associated with adverse events,such as nausea and vomiting,dizziness,and sleep disturbances,and poor maintenance of late ADHD medication compromises treatment outcomes and prolongs the recovery of patients’social functioning.AIM To evaluate the effect of non-pharmacological treatment on the full recovery of social functioning in patients with ADHD.METHODS A total of 90 patients diagnosed with ADHD between May 2019 and August 2020 were included in the study and randomly assigned to either the pharmacological group(methylphenidate hydrochloride and tomoxetine hydrochloride)or the non-pharmacological group(parental training,behavior modification,sensory integration therapy,and sand tray therapy),with 45 cases in each group.Outcome measures included treatment compliance,Swanson,Nolan,and Pelham,Version IV(SNAP-IV)scores,Conners Parent Symptom Questionnaire(PSQ)scores,and Weiss Functional Impairment Rating Scale(WFIRS)scores.RESULTS The non-pharmacological interventions resulted in significantly higher compliance in patients(95.56%)compared with medication(71.11%)(P<0.05).However,no significant differences in SNAP-IV and PSQ scores,in addition to the learning/school,social activities,and adventure activities of the WFIRS scores were observed between the two groups(P>0.05).Patients with non-pharmacological interventions showed higher WFIRS scores for family,daily life skills,and self-concept than those in the pharmacological group(P<0.05).CONCLUSION Non-pharmacological interventions,in contrast to the potential risks of adverse events after longterm medication,improve patient treatment compliance,alleviate patients’behavioral symptoms of attention,impulsivity,and hyperactivity,and improve their cognitive ability,thereby improving family relationships and patient self-evaluation.展开更多
Objective: to discuss the application of TCM hot compress combined with TCM nursing in elderly patients with knee osteoarthritis. Methods: 90 elderly patients with knee osteoarthritis treated in our hospital were rand...Objective: to discuss the application of TCM hot compress combined with TCM nursing in elderly patients with knee osteoarthritis. Methods: 90 elderly patients with knee osteoarthritis treated in our hospital were randomly selected and divided into groups according to the random way. Among them, 45 cases were given routine nursing intervention (control group) and the other 45 cases were given traditional Chinese medicine hot compress combined with traditional Chinese medicine nursing intervention (observation group). Through observation and comparison, the conclusion was drawn. Results: for the comparison of each data, each data of the treatment method in the observation group has more advantages, and the difference is statistically significant (P < 0.05). After treatment, the cure rate of the observation group was higher than that of the control group, and the difference was statistically significant (P < 0.05). Conclusion: traditional Chinese medicine nursing combined with hot compress of traditional Chinese medicine can effectively improve knee joint function and patients' compliance in the treatment of senile knee osteoarthritis, which is worthy of clinical application.展开更多
With the continuous evolution and expanding applications of Large Language Models (LLMs), there has been a noticeable surge in the size of the emerging models. It is not solely the growth in model size, primarily meas...With the continuous evolution and expanding applications of Large Language Models (LLMs), there has been a noticeable surge in the size of the emerging models. It is not solely the growth in model size, primarily measured by the number of parameters, but also the subsequent escalation in computational demands, hardware and software prerequisites for training, all culminating in a substantial financial investment as well. In this paper, we present novel techniques like supervision, parallelization, and scoring functions to get better results out of chains of smaller language models, rather than relying solely on scaling up model size. Firstly, we propose an approach to quantify the performance of a Smaller Language Models (SLM) by introducing a corresponding supervisor model that incrementally corrects the encountered errors. Secondly, we propose an approach to utilize two smaller language models (in a network) performing the same task and retrieving the best relevant output from the two, ensuring peak performance for a specific task. Experimental evaluations establish the quantitative accuracy improvements on financial reasoning and arithmetic calculation tasks from utilizing techniques like supervisor models (in a network of model scenario), threshold scoring and parallel processing over a baseline study.展开更多
The idea of linear Diophantine fuzzy set(LDFS)theory with its control parameters is a strong model for machine learning and optimization under uncertainty.The activity times in the critical path method(CPM)representat...The idea of linear Diophantine fuzzy set(LDFS)theory with its control parameters is a strong model for machine learning and optimization under uncertainty.The activity times in the critical path method(CPM)representation procedures approach are initially static,but in the Project Evaluation and Review Technique(PERT)approach,they are probabilistic.This study proposes a novel way of project review and assessment methodology for a project network in a linear Diophantine fuzzy(LDF)environment.The LDF expected task time,LDF variance,LDF critical path,and LDF total expected time for determining the project network are all computed using LDF numbers as the time of each activity in the project network.The primary premise of the LDF-PERT approach is to address ambiguities in project network activity timesmore simply than other approaches such as conventional PERT,Fuzzy PERT,and so on.The LDF-PERT is an efficient approach to analyzing symmetries in fuzzy control systems to seek an optimal decision.We also present a new approach for locating LDF-CPM in a project network with uncertain and erroneous activity timings.When the available resources and activity times are imprecise and unpredictable,this strategy can help decision-makers make better judgments in a project.A comparison analysis of the proposed technique with the existing techniques has also been discussed.The suggested techniques are demonstrated with two suitable numerical examples.展开更多
Assessing soil quality is essential for crop management and soil temporal changes. The present study aims to evaluate soil quality in the Ferralitic soils context countrywide. This assessment was done using multivaria...Assessing soil quality is essential for crop management and soil temporal changes. The present study aims to evaluate soil quality in the Ferralitic soils context countrywide. This assessment was done using multivariate soil quality indice (SQI) models, such as additive quality index (AQI), weighted quality indexes (WQI<sub>add</sub> and WQI<sub>com</sub>) and Nemoro quality index (NQI), applied to two approaches of indicator selection: total data set (TDS) and minimum data set (MDS). Physical and chemical soil indicators were extracted from the ORSTOM’s reports resulting from a sampling campaign in different provinces of Gabon. The TDS approach shows soil quality status according to eleven soil indicators extracted from the analysis of 1,059 samples from arable soil layer (0 - 30 cm depth). The results indicated that 87% of all provinces presented a very low soil quality (Q5) whatever the model. Among soil indicators, exchangeable K<sup>+</sup> and Mg<sup>2+</sup>, bulk density and C/N ratio were retained in MDS, using principal component analysis (PCA). In the MDS approach, 50 to 63% of provinces had low soil quality grades with AQI, WQI<sub>add</sub> and NQI, whereas the total was observed with WQI<sub>com</sub>. Only 25% of provinces had medium soil quality grades with AQI and NQI models, while 12.5% (NQI) and 25% (AQI) presented high quality grades. Robust statistical analyses confirmed the accuracy and validation (0.80 r P ≤ 0.016) of AQI, WQI<sub>add</sub> and NQI into the TDS and MDS approaches. The same sensitivity index value (1.53) was obtained with AQI and WQI<sub>add</sub>. However, WQI<sub>add</sub> was chosen as the best SQI model, according to its high linear regression value (R<sup>2</sup> = 0.82) between TDS and MDS. This study has important implications in decision-making on monitoring, evaluation and sustainable management of Gabonese soils in a pedoclimatic context unfavorable to plant growth.展开更多
RNAs play crucial and versatile roles in biological processes.Computational prediction approaches can help to understand RNA structures and their stabilizing factors,thus providing information on their functions,and f...RNAs play crucial and versatile roles in biological processes.Computational prediction approaches can help to understand RNA structures and their stabilizing factors,thus providing information on their functions,and facilitating the design of new RNAs.Machine learning(ML)techniques have made tremendous progress in many fields in the past few years.Although their usage in protein-related fields has a long history,the use of ML methods in predicting RNA tertiary structures is new and rare.Here,we review the recent advances of using ML methods on RNA structure predictions and discuss the advantages and limitation,the difficulties and potentials of these approaches when applied in the field.展开更多
The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas...The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas from local learning, constraint- based, and search-and-score techniques in a principled and ef- fective way. It first reconstructs the junction tree of a BN and then performs a K2-scoring greedy search to orientate the local edges in the cliques of junction tree. Theoretical and experimental results show the proposed algorithm is capable of handling networks with a large number of variables. Its comparison with the well-known K2 algorithm is also presented.展开更多
RNAs play crucial and versatile roles in cellular biochemical reactions.Since experimental approaches of determining their three-dimensional(3D)structures are costly and less efficient,it is greatly advantageous to de...RNAs play crucial and versatile roles in cellular biochemical reactions.Since experimental approaches of determining their three-dimensional(3D)structures are costly and less efficient,it is greatly advantageous to develop computational methods to predict RNA 3D structures.For these methods,designing a model or scoring function for structure quality assessment is an essential step but this step poses challenges.In this study,we designed and trained a deep learning model to tackle this problem.The model was based on a graph convolutional network(GCN)and named RNAGCN.The model provided a natural way of representing RNA structures,avoided complex algorithms to preserve atomic rotational equivalence,and was capable of extracting features automatically out of structural patterns.Testing results on two datasets convincingly demonstrated that RNAGCN performs similarly to or better than four leading scoring functions.Our approach provides an alternative way of RNA tertiary structure assessment and may facilitate RNA structure predictions.RNAGCN can be downloaded from https://gitee.com/dcw-RNAGCN/rnagcn.展开更多
The prediction of protein–protein complex structures is crucial for fundamental understanding of celluar processes and drug design. Despite significant progresses in the field, the accuracy of ab initio docking witho...The prediction of protein–protein complex structures is crucial for fundamental understanding of celluar processes and drug design. Despite significant progresses in the field, the accuracy of ab initio docking without using any experimental restraints remains relatively low. With the rapid advancement of structural biology, more and more information about binding can be derived from experimental data such as NMR experiments or chemical cross-linking. In addition, information about the residue contacts between proteins may also be derived from their sequences by using evolutionary analysis or deep learning. Here, we propose an efficient approach to incorporate interface residue restraints into protein–protein docking, which is named as HDOCKsite. Extensive evaluations on the protein–protein docking benchmark 4.0 showed that HDOCKsite significantly improved the docking performance and obtained a much higher success rate in binding mode predictions than original ab initio docking.展开更多
AIM： To compare the efficacy of pentoxifylline and prednisolone in the treatment of severe alcoholic hepatitis, and to evaluate the role of different liver function scores in predicting prognosis.METHODS： Sixty-eigh...AIM： To compare the efficacy of pentoxifylline and prednisolone in the treatment of severe alcoholic hepatitis, and to evaluate the role of different liver function scores in predicting prognosis.METHODS： Sixty-eight patients with severe alcoholic hepatitis （Maddrey score ≥ 32） received pentoxifylline （n = 34, group Ⅰ） or prednisolone （n = 34, group Ⅱ） for 28 d in a randomized double-blind controlled study, and subsequently in an open study （with a tapering dose of prednisolone） for a total of 3 mo, and were followed up over a period of 12 mo.RESULTS： Twelve patients in group Ⅱ died at the end of 3 mo in contrast to five patients in group Ⅰ. The probability of dying at the end of 3 mo was higher in group Ⅱ as compared to group Ⅰ （35.29% vs 14.71%, P = 0.04; log rank test）. Six patients in group I developed hepatorenal syndrome as compared to none in group Ⅰ. Pentoxifylline was associated with a significantly lower model for end-stage liver disease （MELD） score at the end of 28 d of therapy （15.53± 3.63 vs 17.78± 4.56, P=0.04）. Higher baseline Maddrey score was associated with increased mortality.CONCLUSION： Reduced mortality, improved risk-benefit profile and renoprotective effects of pentoxifylline compared with prednisolone suggest that pentoxifylline is superior to prednisolone for treatment of severe alcoholic hepatitis.展开更多
A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans accord...A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan’s supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of sat- isfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valua- tions for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs’ arbitrariness and subjectivity when these values are determined.展开更多
OBJECTIVE:To evaluate the efficacy of bee venom acupuncture in humeroscapularis(PHS)patients.METHODS:One hundred and twenty patients diagnosed with PHS were assigned into four groups:BV1(0.01 mg/kg),BV2(0.005 mg/kg),B...OBJECTIVE:To evaluate the efficacy of bee venom acupuncture in humeroscapularis(PHS)patients.METHODS:One hundred and twenty patients diagnosed with PHS were assigned into four groups:BV1(0.01 mg/kg),BV2(0.005 mg/kg),BV3(0.0025 mg/kg),and control group(vitamin B1 plus novocain 3%injection)with 15 d of treatment.The outcomes of the study including visual analogue scale(VAS)score andβ-endorphin,inflammatory cytokines including interleukin-10(IL-10),IL-1βand tumor necrosis factorα(TNF-α)and shoulder function score were assessed at baseline,after 10 and 15 d of treatment.RESULTS:All four groups reported statistically significant improvement in VAS score,motion range,and shoulder function score(P<0.01),only the BV3 group showed significant increase of anti-inflammatory(IL-10)and decrease of pro-inflammatory(IL-1β,TNF-α)cytokines after treatment(P<0.05).The BV3 group presented a significant difference between all outcomes compared to the control and other groups.CONCLUSION:BV3 groups showed better recovery including reduced pain,improved motor function and normalized inflammatory cytokines than current therapy used in Vietnam and other groups.展开更多
A method is proposed to deal with the uncertain multiple attribute group decision making problems,where 2-dimension uncertain linguistic variables(2DULVs)are used as the reliable way for the experts to express their f...A method is proposed to deal with the uncertain multiple attribute group decision making problems,where 2-dimension uncertain linguistic variables(2DULVs)are used as the reliable way for the experts to express their fuzzy subjective evaluation information.Firstly,in order to measure the 2DULVs more accurately,a new method is proposed to compare two 2DULVs,called a score function,while a new function is defined to measure the distance between two 2DULVs.Secondly,two optimization models are established to determine the weight of experts and attributes based on the new distance formula and a weighted average operator is used to determine the comprehensive evaluation value of each alternative.Then,a score function is used to determine the ranking of the alternatives.Finally,the effectiveness of the proposed method is proved by an illustrated example.展开更多
Objective: To observe the therapeutic effect of Xuesaitong soft capsule(血塞通软胶囊, XST)and its effect on platelet counts, coagulation factor 1 (CF1) as well as hemorrheologic indexes in treating patients with acute...Objective: To observe the therapeutic effect of Xuesaitong soft capsule(血塞通软胶囊, XST)and its effect on platelet counts, coagulation factor 1 (CF1) as well as hemorrheologic indexes in treating patients with acute cerebral infarction (ACI). Methods: Two hundred and four patients with ACI were assigned into two groups, the control group (n=96) and the treated group (n=108). They were all treated with conventional Western medicines, including mannitol, troxerutin, citicoline, piracetam and aspirin, while to the treated group, XST was given additionally through oral intake, twice a day, 2 capsules each time for 8 successive weeks. The clinical efficacy was evaluated according to the nerve function deficits scoring and the changes of platelet count. CF1 and hemorrheological indexes were measured before and after treatment.Results: The total effective rate was 87.0% in the treated group, and 87.5% in the control group, respectively, showing insignificant difference between them. But the markedly effective rate in the treated group ( 66.7%) was significantly higher than that in the control group (27.1%, P<0.01). The count of platelet was not changed significantly in both groups after treatment, while CF1 in them evidently lowered at the end of the 4th and 8th weeks of treatment, but showed insignificant difference between the two groups. The hematocrit, whole blood viscosity and plasma viscosity in both groups were all improved significantly after treatment, but also showed insignificant difference in comparison of the two groups. Conclusion: XST has good efficacy in auxiliary treatment of patients with ACI, though its mechanism remains to be further explored.展开更多
文摘It has been well accepted that the folding energy landscape may resemble a funnel according to the theory of protein folding. This theory of ＂folding funnel＂ has been extensively studied and thought to play an important role in guiding the sampling process of the protein folding and refinement in protein structure prediction. Here, we have investigated the relationship between the ＂funnel likeness＂ of protein folding and the size/structure of the proteins based on a set of non-homologous proteins we have recently evaluated using a statistical mechanicsbased scoring function ITScorePro. It was found that larger proteins that consist of more helix/sheet structures tend to have a higher score-Root Mean Square Deviation（RMSD） correlation（or a more funnel like energy landscape）.Another measurement in protein folding, Z-score, has also shown some correlation with the size of the proteins.As expected, proteins with a better ＂olding funnel likeness＂（or score-RMSD correlation） tend to have a betterpredicted conformation with a lower RMSD from their native structures. These findings can be extremely valuable for the development and improvement of sampling and scoring algorithms for protein structure prediction.
基金supported by grants from National Natural Science Foundation of China(No.82272064)Jiangsu Provincial Science and Technique Program(No.BK20221461)Zhongda Hospital Affiliated to Southeast University,Jiangsu Province High-level Hospital Paring Assistance Construction(No.zdlyg08).
文摘Objective Cachexia occurs in approximately half of hepatocellular carcinoma(HCC)patients as the disease progresses and is correlated with a poor prognosis.Therefore,early identification of HCC patients at risk of developing cachexia and their prognosis is crucial.This study investigated the functional liver imaging score(FLIS)derived from gadoxetic acid-enhanced magnetic resonance imaging(MRI)to identify cachexia in HCC patients and their prognosis.Methods Pretreatment clinical and MRI data from 339 HCC patients who underwent gadoxetic acid-enhanced MRI scans were retrospectively collected.Patient weights were recorded for 6 months following the MRI scan to diagnose cachexia.The FLIS was calculated as the sum of the enhancement quality score,the excretion quality score,and the portal vein sign quality score.A Cox proportional hazards model was used to determine the significant factors affecting overall survival(OS).Multivariable logistic regression was then conducted to identify variables predicting cachexia in HCC patients,which were subsequently used to predict OS.Results Cox regression analysis revealed a significant association between cachexia and worse OS.Both FLIS(0–4 vs.5–6 points)(OR,9.20;95%CI:4.68–18.10;P<0.001)andα-fetoprotein>100 ng/mL(OR,4.08;95%CI:2.13–7.83;P<0.001)emerged as significant predictors of cachexia in patients with HCC.Furthermore,FLIS(0–4 vs.5–6 points)(HR,1.73;95%CI:1.19–2.51;P=0.004)was significantly associated with OS.Patients in the FLIS 0–4 points group had shorter OS than those in the FLIS 5–6 points group[20 months(95%CI,14.7–25.3)vs.43 months(95%CI,27.7–58.3);P=0.001].Conclusion Cachexia was associated with worse OS.The functional liver imaging score emerged as a significant predictor of cachexia in HCC patients and their prognosis.
文摘AIM To develop a new scoring system, nutech functional scores(NFS) for assessing the patients with spinal cord injury(SCI).METHODS The conventional scale, American Spinal Injury Association's(ASIA) impairment scale is a measure which precisely describes the severity of the SCI.However, it has various limitations which lead to incomplete assessment of SCI patients.We have developed a 63 point scoring system, i.e., NFS for patients suffering with SCI.A list of symptoms either common or rare that were found to be associated with SCI was recorded for each patient.On the basis of these lists, we have developed NFS.RESULTS These lists served as a base to prepare NFS, a 63 point positional(each symptom is sub-graded and get points based on position) and directional(moves in direction BAD → GOOD) scoring system.For non-progressive diseases, 1, 2, 3, 4, 5 denote worst, bad, moderate, good and best(normal), respectively.NFS for SCI has been divided into different groups based on the affected part of the body being assessed, i.e., motor assessment(shoulders, elbow, wrist, fingers-grasp, fingers-release, hip, knee, ankle and toe), sensory assessment, autonomic assessment, bed sore assessment and general assessment.As probability based studies required a range of(-1, 1) or at least the range of(0, 1) to be useful for real world analysis, the grades were converted to respective numeric values.CONCLUSION NFS can be considered as a unique tool to assess the improvement in patients with SCI as it overcomes the limitations of ASIA impairment scale.
文摘Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.
基金Supported by General Program of the National Natural Science Foundation of China(81973883)Three-Year Action Plan Project for Enhancing Clinical Skills and Clinical Innovation Capabilities of Municipal Hospitals(SHDC2020CR1010A).
文摘[Objectives]To explore the effects of electroacupuncture combined with rehabilitation training on knee joint function,three-dimensional(3D)gait,and inflammatory markers in patients with knee osteoarthritis(KOA)of cold-dampness obstruction syndrome.[Methods]A total of 162 KOA patients admitted to Huadong Hospital Affiliated to Fudan University from January 2021 to May 2023 were enrolled and randomly divided into an electroacupuncture group and a control group,with 81 patients in each group.The control group received routine rehabilitation training,while the electroacupuncture group received electroacupuncture treatment in addition to the same rehabilitation training,both for 4 weeks.The efficacy,syndrome scores,Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC),Lysholm Knee Score(LKS),3D gait parameters,and levels of inflammatory markers were compared between the two groups.[Results]Following treatment,the total effective rate in the electroacupuncture group was 92.59%,which was significantly higher than 77.78%observed in the control group(P<0.05).Additionally,the electroacupuncture group exhibited lower TCM syndrome scores(P<0.05),reduced WOMAC scores,and elevated LKS scores compared to the control group(P<0.05).Gait parameters,including step frequency,step speed,stride length,initial ground contact flexion angle,maximum swing phase extension angle,and support phase extension angle,were all higher in the electroacupuncture group.Additionally,the sagittal plane maximum abduction moment was lower in the electroacupuncture group.Inflammatory markers showed that interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)were lower in the electroacupuncture group,while transforming growth factor-β1(TGF-β1)was higher(P<0.05).[Conclusions]Electroacupuncture combined with rehabilitation training effectively enhances clinical efficacy,alleviates symptoms,improves knee joint mobility and walking ability,enhances knee function scores,and reduces inflammatory levels,contributing to the rapid recovery of knee joints in KOA patients.
基金School-level Educational Reform Project of Hangzhou Normal University(Project No.:HLXYJG202304)。
文摘Objective:To conduct a scoping review on the application status of the Functional Activity Score(FAS)in postoperative active pain management in China,providing a reference for its standardized and normative promotion.Methods:Computerized searches of Chinese and English databases were performed to collect studies published by Chinese scholars from 2005 to July 2025 on the application of FAS in postoperative active pain management.After strict screening,the basic characteristics,application fields,assessment models,evaluation timing,types of functional activities,and clinical outcomes of the included literature were systematically analyzed.Results:A total of 18 studies were included,involving surgical types such as thoracic surgery,general surgery,and orthopedics.All studies adopted FAS combined with the Numeric Rating Scale(NRS)for assessment,with evaluation timing mostly concentrated within 72 hours postoperatively.The selected functional activities primarily included respiration-related and limb movements.Evaluation indicators covered pain control,functional recovery,complications,adverse events,patient experience,and tool assessment,with most studies reporting positive outcomes.Conclusion:FAS can effectively enhance pain control and promote functional recovery in postoperative active pain management in China,demonstrating high clinical value.However,existing studies exhibit inconsistencies in assessment criteria,selection of activity types,and research quality.
基金Supported by Ningbo Science and Technology Plan Project Public Welfare Plan(Municipal Level),No:2019C50099Ningbo Medical Key Supporting Discipline Child Health Science,No:2022-F26。
文摘BACKGROUND Long-term treatment of attention deficit/hyperactivity disorder(ADHD)is associated with adverse events,such as nausea and vomiting,dizziness,and sleep disturbances,and poor maintenance of late ADHD medication compromises treatment outcomes and prolongs the recovery of patients’social functioning.AIM To evaluate the effect of non-pharmacological treatment on the full recovery of social functioning in patients with ADHD.METHODS A total of 90 patients diagnosed with ADHD between May 2019 and August 2020 were included in the study and randomly assigned to either the pharmacological group(methylphenidate hydrochloride and tomoxetine hydrochloride)or the non-pharmacological group(parental training,behavior modification,sensory integration therapy,and sand tray therapy),with 45 cases in each group.Outcome measures included treatment compliance,Swanson,Nolan,and Pelham,Version IV(SNAP-IV)scores,Conners Parent Symptom Questionnaire(PSQ)scores,and Weiss Functional Impairment Rating Scale(WFIRS)scores.RESULTS The non-pharmacological interventions resulted in significantly higher compliance in patients(95.56%)compared with medication(71.11%)(P<0.05).However,no significant differences in SNAP-IV and PSQ scores,in addition to the learning/school,social activities,and adventure activities of the WFIRS scores were observed between the two groups(P>0.05).Patients with non-pharmacological interventions showed higher WFIRS scores for family,daily life skills,and self-concept than those in the pharmacological group(P<0.05).CONCLUSION Non-pharmacological interventions,in contrast to the potential risks of adverse events after longterm medication,improve patient treatment compliance,alleviate patients’behavioral symptoms of attention,impulsivity,and hyperactivity,and improve their cognitive ability,thereby improving family relationships and patient self-evaluation.
文摘Objective: to discuss the application of TCM hot compress combined with TCM nursing in elderly patients with knee osteoarthritis. Methods: 90 elderly patients with knee osteoarthritis treated in our hospital were randomly selected and divided into groups according to the random way. Among them, 45 cases were given routine nursing intervention (control group) and the other 45 cases were given traditional Chinese medicine hot compress combined with traditional Chinese medicine nursing intervention (observation group). Through observation and comparison, the conclusion was drawn. Results: for the comparison of each data, each data of the treatment method in the observation group has more advantages, and the difference is statistically significant (P < 0.05). After treatment, the cure rate of the observation group was higher than that of the control group, and the difference was statistically significant (P < 0.05). Conclusion: traditional Chinese medicine nursing combined with hot compress of traditional Chinese medicine can effectively improve knee joint function and patients' compliance in the treatment of senile knee osteoarthritis, which is worthy of clinical application.
文摘With the continuous evolution and expanding applications of Large Language Models (LLMs), there has been a noticeable surge in the size of the emerging models. It is not solely the growth in model size, primarily measured by the number of parameters, but also the subsequent escalation in computational demands, hardware and software prerequisites for training, all culminating in a substantial financial investment as well. In this paper, we present novel techniques like supervision, parallelization, and scoring functions to get better results out of chains of smaller language models, rather than relying solely on scaling up model size. Firstly, we propose an approach to quantify the performance of a Smaller Language Models (SLM) by introducing a corresponding supervisor model that incrementally corrects the encountered errors. Secondly, we propose an approach to utilize two smaller language models (in a network) performing the same task and retrieving the best relevant output from the two, ensuring peak performance for a specific task. Experimental evaluations establish the quantitative accuracy improvements on financial reasoning and arithmetic calculation tasks from utilizing techniques like supervisor models (in a network of model scenario), threshold scoring and parallel processing over a baseline study.
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia[Grant No.GRANT3862].
文摘The idea of linear Diophantine fuzzy set(LDFS)theory with its control parameters is a strong model for machine learning and optimization under uncertainty.The activity times in the critical path method(CPM)representation procedures approach are initially static,but in the Project Evaluation and Review Technique(PERT)approach,they are probabilistic.This study proposes a novel way of project review and assessment methodology for a project network in a linear Diophantine fuzzy(LDF)environment.The LDF expected task time,LDF variance,LDF critical path,and LDF total expected time for determining the project network are all computed using LDF numbers as the time of each activity in the project network.The primary premise of the LDF-PERT approach is to address ambiguities in project network activity timesmore simply than other approaches such as conventional PERT,Fuzzy PERT,and so on.The LDF-PERT is an efficient approach to analyzing symmetries in fuzzy control systems to seek an optimal decision.We also present a new approach for locating LDF-CPM in a project network with uncertain and erroneous activity timings.When the available resources and activity times are imprecise and unpredictable,this strategy can help decision-makers make better judgments in a project.A comparison analysis of the proposed technique with the existing techniques has also been discussed.The suggested techniques are demonstrated with two suitable numerical examples.
文摘Assessing soil quality is essential for crop management and soil temporal changes. The present study aims to evaluate soil quality in the Ferralitic soils context countrywide. This assessment was done using multivariate soil quality indice (SQI) models, such as additive quality index (AQI), weighted quality indexes (WQI<sub>add</sub> and WQI<sub>com</sub>) and Nemoro quality index (NQI), applied to two approaches of indicator selection: total data set (TDS) and minimum data set (MDS). Physical and chemical soil indicators were extracted from the ORSTOM’s reports resulting from a sampling campaign in different provinces of Gabon. The TDS approach shows soil quality status according to eleven soil indicators extracted from the analysis of 1,059 samples from arable soil layer (0 - 30 cm depth). The results indicated that 87% of all provinces presented a very low soil quality (Q5) whatever the model. Among soil indicators, exchangeable K<sup>+</sup> and Mg<sup>2+</sup>, bulk density and C/N ratio were retained in MDS, using principal component analysis (PCA). In the MDS approach, 50 to 63% of provinces had low soil quality grades with AQI, WQI<sub>add</sub> and NQI, whereas the total was observed with WQI<sub>com</sub>. Only 25% of provinces had medium soil quality grades with AQI and NQI models, while 12.5% (NQI) and 25% (AQI) presented high quality grades. Robust statistical analyses confirmed the accuracy and validation (0.80 r P ≤ 0.016) of AQI, WQI<sub>add</sub> and NQI into the TDS and MDS approaches. The same sensitivity index value (1.53) was obtained with AQI and WQI<sub>add</sub>. However, WQI<sub>add</sub> was chosen as the best SQI model, according to its high linear regression value (R<sup>2</sup> = 0.82) between TDS and MDS. This study has important implications in decision-making on monitoring, evaluation and sustainable management of Gabonese soils in a pedoclimatic context unfavorable to plant growth.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11774158,11974173,11774157,and 11934008)。
文摘RNAs play crucial and versatile roles in biological processes.Computational prediction approaches can help to understand RNA structures and their stabilizing factors,thus providing information on their functions,and facilitating the design of new RNAs.Machine learning(ML)techniques have made tremendous progress in many fields in the past few years.Although their usage in protein-related fields has a long history,the use of ML methods in predicting RNA tertiary structures is new and rare.Here,we review the recent advances of using ML methods on RNA structure predictions and discuss the advantages and limitation,the difficulties and potentials of these approaches when applied in the field.
基金supported by the National Natural Science Fundation of China (6097408261075055)the Fundamental Research Funds for the Central Universities (K50510700004)
文摘The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas from local learning, constraint- based, and search-and-score techniques in a principled and ef- fective way. It first reconstructs the junction tree of a BN and then performs a K2-scoring greedy search to orientate the local edges in the cliques of junction tree. Theoretical and experimental results show the proposed algorithm is capable of handling networks with a large number of variables. Its comparison with the well-known K2 algorithm is also presented.
基金funded by the National Natural Science Foundation of China(Grant Nos.11774158 to JZ,11934008 to WW,and 11974173 to WFL)。
文摘RNAs play crucial and versatile roles in cellular biochemical reactions.Since experimental approaches of determining their three-dimensional(3D)structures are costly and less efficient,it is greatly advantageous to develop computational methods to predict RNA 3D structures.For these methods,designing a model or scoring function for structure quality assessment is an essential step but this step poses challenges.In this study,we designed and trained a deep learning model to tackle this problem.The model was based on a graph convolutional network(GCN)and named RNAGCN.The model provided a natural way of representing RNA structures,avoided complex algorithms to preserve atomic rotational equivalence,and was capable of extracting features automatically out of structural patterns.Testing results on two datasets convincingly demonstrated that RNAGCN performs similarly to or better than four leading scoring functions.Our approach provides an alternative way of RNA tertiary structure assessment and may facilitate RNA structure predictions.RNAGCN can be downloaded from https://gitee.com/dcw-RNAGCN/rnagcn.
基金Project supported by the National Natural Science Foundation of China(Grant No.31670724)the Startup Grant of Huazhong University of Science and Technology。
文摘The prediction of protein–protein complex structures is crucial for fundamental understanding of celluar processes and drug design. Despite significant progresses in the field, the accuracy of ab initio docking without using any experimental restraints remains relatively low. With the rapid advancement of structural biology, more and more information about binding can be derived from experimental data such as NMR experiments or chemical cross-linking. In addition, information about the residue contacts between proteins may also be derived from their sequences by using evolutionary analysis or deep learning. Here, we propose an efficient approach to incorporate interface residue restraints into protein–protein docking, which is named as HDOCKsite. Extensive evaluations on the protein–protein docking benchmark 4.0 showed that HDOCKsite significantly improved the docking performance and obtained a much higher success rate in binding mode predictions than original ab initio docking.
文摘AIM： To compare the efficacy of pentoxifylline and prednisolone in the treatment of severe alcoholic hepatitis, and to evaluate the role of different liver function scores in predicting prognosis.METHODS： Sixty-eight patients with severe alcoholic hepatitis （Maddrey score ≥ 32） received pentoxifylline （n = 34, group Ⅰ） or prednisolone （n = 34, group Ⅱ） for 28 d in a randomized double-blind controlled study, and subsequently in an open study （with a tapering dose of prednisolone） for a total of 3 mo, and were followed up over a period of 12 mo.RESULTS： Twelve patients in group Ⅱ died at the end of 3 mo in contrast to five patients in group Ⅰ. The probability of dying at the end of 3 mo was higher in group Ⅱ as compared to group Ⅰ （35.29% vs 14.71%, P = 0.04; log rank test）. Six patients in group I developed hepatorenal syndrome as compared to none in group Ⅰ. Pentoxifylline was associated with a significantly lower model for end-stage liver disease （MELD） score at the end of 28 d of therapy （15.53± 3.63 vs 17.78± 4.56, P=0.04）. Higher baseline Maddrey score was associated with increased mortality.CONCLUSION： Reduced mortality, improved risk-benefit profile and renoprotective effects of pentoxifylline compared with prednisolone suggest that pentoxifylline is superior to prednisolone for treatment of severe alcoholic hepatitis.
基金Project (No. K81077) supported by the Department of Automation, Xiamen University, China
文摘A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan’s supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of sat- isfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valua- tions for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs’ arbitrariness and subjectivity when these values are determined.
文摘OBJECTIVE:To evaluate the efficacy of bee venom acupuncture in humeroscapularis(PHS)patients.METHODS:One hundred and twenty patients diagnosed with PHS were assigned into four groups:BV1(0.01 mg/kg),BV2(0.005 mg/kg),BV3(0.0025 mg/kg),and control group(vitamin B1 plus novocain 3%injection)with 15 d of treatment.The outcomes of the study including visual analogue scale(VAS)score andβ-endorphin,inflammatory cytokines including interleukin-10(IL-10),IL-1βand tumor necrosis factorα(TNF-α)and shoulder function score were assessed at baseline,after 10 and 15 d of treatment.RESULTS:All four groups reported statistically significant improvement in VAS score,motion range,and shoulder function score(P<0.01),only the BV3 group showed significant increase of anti-inflammatory(IL-10)and decrease of pro-inflammatory(IL-1β,TNF-α)cytokines after treatment(P<0.05).The BV3 group presented a significant difference between all outcomes compared to the control and other groups.CONCLUSION:BV3 groups showed better recovery including reduced pain,improved motor function and normalized inflammatory cytokines than current therapy used in Vietnam and other groups.
基金This work was supported by the Natural Science Foundation of Liaoning Province(2013020022).
文摘A method is proposed to deal with the uncertain multiple attribute group decision making problems,where 2-dimension uncertain linguistic variables(2DULVs)are used as the reliable way for the experts to express their fuzzy subjective evaluation information.Firstly,in order to measure the 2DULVs more accurately,a new method is proposed to compare two 2DULVs,called a score function,while a new function is defined to measure the distance between two 2DULVs.Secondly,two optimization models are established to determine the weight of experts and attributes based on the new distance formula and a weighted average operator is used to determine the comprehensive evaluation value of each alternative.Then,a score function is used to determine the ranking of the alternatives.Finally,the effectiveness of the proposed method is proved by an illustrated example.
文摘Objective: To observe the therapeutic effect of Xuesaitong soft capsule(血塞通软胶囊, XST)and its effect on platelet counts, coagulation factor 1 (CF1) as well as hemorrheologic indexes in treating patients with acute cerebral infarction (ACI). Methods: Two hundred and four patients with ACI were assigned into two groups, the control group (n=96) and the treated group (n=108). They were all treated with conventional Western medicines, including mannitol, troxerutin, citicoline, piracetam and aspirin, while to the treated group, XST was given additionally through oral intake, twice a day, 2 capsules each time for 8 successive weeks. The clinical efficacy was evaluated according to the nerve function deficits scoring and the changes of platelet count. CF1 and hemorrheological indexes were measured before and after treatment.Results: The total effective rate was 87.0% in the treated group, and 87.5% in the control group, respectively, showing insignificant difference between them. But the markedly effective rate in the treated group ( 66.7%) was significantly higher than that in the control group (27.1%, P<0.01). The count of platelet was not changed significantly in both groups after treatment, while CF1 in them evidently lowered at the end of the 4th and 8th weeks of treatment, but showed insignificant difference between the two groups. The hematocrit, whole blood viscosity and plasma viscosity in both groups were all improved significantly after treatment, but also showed insignificant difference in comparison of the two groups. Conclusion: XST has good efficacy in auxiliary treatment of patients with ACI, though its mechanism remains to be further explored.
