Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases,child mortality and morbidity.Expanded Program on Immunization(EPI)is a nation-wide program in Pakistan to implement immun...Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases,child mortality and morbidity.Expanded Program on Immunization(EPI)is a nation-wide program in Pakistan to implement immunization activities,however the coverage is quite low despite the accessibility of free vaccination.This study proposes a defaulter prediction model for accurate identification of defaulters.Our proposed framework classifies defaulters at five different stages:defaulter,partially high,partially medium,partially low,and unvaccinated to reinforce targeted interventions by accurately predicting children at high risk of defaulting from the immunization schedule.Different machine learning algorithms are applied on Pakistan Demographic and Health Survey(2017–18)dataset.Multilayer Perceptron yielded 98.5%accuracy for correctly identifying children who are likely to default from immunization series at different risk stages of being defaulter.In this paper,the proposed defaulters’prediction framework is a step forward towards a data-driven approach and provides a set of machine learning techniques to take advantage of predictive analytics.Hence,predictive analytics can reinforce immunization programs by expediting targeted action to reduce dropouts.Specially,the accurate predictions support targeted messages sent to at-risk parents’and caretakers’consumer devices(e.g.,smartphones)to maximize healthcare outcomes.展开更多
Background: Tuberculosis is second only to HIV/AIDS as the greatest killer worldwide, due to a single infectious agent. Directly Observed Treatment Short-Course (DOTS) is presently the WHO recommended programme to fig...Background: Tuberculosis is second only to HIV/AIDS as the greatest killer worldwide, due to a single infectious agent. Directly Observed Treatment Short-Course (DOTS) is presently the WHO recommended programme to fight tuberculosis worldwide. There is a need to understand the characteristics of patients who default from treatment for tuberculosis. This will help modify the strategies to reduce such default to the barest minimum and achieve higher levels of adherence. Objective: The aim of this study was to describe the characteristics of patients that defaulted from treatment for TB at Nnamdi Azikiwe University Teaching Hospital (NAUTH) Nnewi DOTS clinic for the period 1st January 2011 to 31st December 2012. Materials and Methods: This was a retrospective study conducted at the DOTS clinic at Nnamdi Azikiwe University Teaching Hospital Nnewi, Anambra State, Nigeria. The records of patients who received treatment from the clinic from 1st January 2011 to 31st December 2012 (2 years) were reviewed. The data collected include patients’ demographic characteristics, treatment category, patient type, baseline sputum smear result, and retroviral status. From the data, default rate was calculated and its relationship with other variables noted. Associations between patients’ characteristics were determined using chi square test of independence. The significance level was set at p = 0.05. Results: A total of 765 patients enrolled for TB treatment in the DOTS clinic of the study area within the study period of 1<sup>st</sup> January 2011 and December 31st 2012. The mean age at commencement of the treatment was 33.14 years (±18.09). The outcome of treatment showed that 260 (34%) had treatment completed, 230 (30.1%) cured, 120 (15.7%) defaulted, 103 (13.5%) died, 40 (5.2%) were transferred-out, and 12 (1.6%) failed in the treatment, giving a treatment success rate of 64.1%. Among the 120 (15.7%) patients that defaulted from treatment, majority 80 (66.7%) were males, and most 30 (25.0%) were in the 30 - 39 years age group. Conclusion: Defaulting starts with treatment interruption hence prompt management of interruption of treatment and default will largely help in preventing drug-resistant TB.展开更多
Between 2005 and 2007,the China Development Bank offered 1.66 billion yuan($237 million) worth of loans to 243,000 stu- dents from poor families in central China’s Henan Province.
Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the u...Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.展开更多
Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network con...Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.展开更多
Microfinance institutions in Kenya play a unique role in promoting financial inclusion,loans,and savings provision,especially to low-income individuals and small-scale entrepreneurs.However,despite their benefits,most...Microfinance institutions in Kenya play a unique role in promoting financial inclusion,loans,and savings provision,especially to low-income individuals and small-scale entrepreneurs.However,despite their benefits,most of their products and programs in Machakos County have been reducing due to re-payment challenges,threatening their financial ability to extend further credit.This could be attributed to ineffective credit scoring models which are not able to establish the nuanced non-linear repayment behavior and patterns of the loan applicants.The research objective was to enhance credit risk scoring for microfinance institutions in Machakos County using supervised machine learning algorithms.The study adopted a mixed research design under supervised machine learning approach.It randomly sampled 6771 loan application ac-count records and repayment history.Rstudio and Python programming lan-guages were deployed for data pre-processing and analysis.Logistic regression algorithm,XG Boosting and the random forest ensemble method were used.Metric evaluations used included the performance accuracy,Area under the Curve and F1-Score.Based on the study findings:XG Boosting was the best performer with 83.3%accuracy and 0.202 Brier score.Development of legal framework to govern ethical and open use of machine learning assessment was recommended.A similar research but using different machine learning al-gorithms,locations,and institutions,to ascertain the validity,reliability and the generalizability of the study findings was recommended for further re-search.展开更多
BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological s...BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological substrates underlying depression,the intricate patterns of disrupted brain network connectivity in adolescents warrant further exploration.AIM To elucidate the neural correlates of adolescent depression by examining brain network connectivity using resting-state functional magnetic resonance imaging(rs-fMRI).METHODS The study cohort comprised 74 depressed adolescents and 59 healthy controls aged 12 to 17 years.Participants underwent rs-fMRI to evaluate functional connectivity within and across critical brain networks,including the visual,default mode network(DMN),dorsal attention,salience,somatomotor,and frontoparietal control networks.RESULTS Analyses revealed pronounced functional disparities within key neural circuits among adolescents with depression.The results demonstrated existence of hemispheric asymmetries characterized by enhanced activity in the left visual network,which contrasted the diminished activity in the right hemisphere.The DMN facilitated increased activity within the left prefrontal cortex and reduced engagement in the right hemisphere,implicating disrupted self-referential and emotional processing mechanisms.Additionally,an overactive right dorsal attention network and a hypoactive salience network were identified,underscoring significant abnormalities in attentional and emotional regulation in adolescent depression.CONCLUSION The findings from this study underscore distinct neural connectivity disruptions in adolescent depression,underscoring the critical role of specific neurobiological markers for precise early diagnosis of adolescent depression.The observed functional asymmetries and network-specific deviations elucidate the complex neurobiological architecture of adolescent depression,supporting the development of targeted therapeutic strategies.展开更多
BACKGROUND Group cognitive behavioral therapy(GCBT)is increasingly being used to treat obsessive-compulsive disorder(OCD)because of its high efficiency,economy,and interaction among group members.However,the changes i...BACKGROUND Group cognitive behavioral therapy(GCBT)is increasingly being used to treat obsessive-compulsive disorder(OCD)because of its high efficiency,economy,and interaction among group members.However,the changes in network functional connectivity(FC)in patients with OCD with GCBT remain unclear.AIM To investigate inter-and intra-network resting-state FC(rs-FC)abnormalities before and after GCBT in unmedicated patients with OCD and validate the efficacy of GCBT.METHODS Overall,33 individuals with OCD and 26 healthy controls underwent resting-state functional magnetic resonance imaging.The patients were rescanned 12 weeks after GCBT.Four cognition-related networks-default mode network(DMN),dorsal attention network(DAN),salience network(SAN),and frontoparietal network(FPN)-were selected to examine FC abnormalities within and between OCD networks before and after GCBT.Neuropsychological assessments including memory,executive function,speech,attention,and visuospatial ability were reassessed following GCBT.Pearson’s correlations were used to analyze the relationship between aberrant FC in cognition-related networks and altered neuropsychological assessments in patients.RESULTS Rs-FC within the DMN and DAN decreased significantly.Additionally,rs-FC between the DMN-DAN,DMNFPN,DMN-SAN,and DAN-SAN also decreased.Significant improvements were observed in cognitive functions,such as memory,executive function,attention,and visuospatial ability.Furthermore,reduced rs-FC within the DMN correlated with visuospatial ability and executive function;DAN positively correlated with Shape Trails Test(STT)-A test elapsed time;DMN-DAN negatively correlated with Rey-Osterrieth Complex Figure(Rey-O)mimicry time and the three elapsed times of the tower of Hanoi;DMN-SAN negatively correlated with Rey-O imitation time and positively correlated with STT-A test elapsed time;and DMN-FPN negatively correlated with Auditory Word Learning Test N1 and N4 scores.CONCLUSION Decreased rs-FC within the DMN and DAN,which correlated with executive function post-treatment,has potential as a neuroimaging marker to predict treatment response to GCBT in patients with OCD.展开更多
presented The conceptions of abstract default reasoning frameworks （ADRFs） and D-consequence relations are Based on representation properties of D-consequence relations, it proves that any cumulative nonmonotonic co...presented The conceptions of abstract default reasoning frameworks （ADRFs） and D-consequence relations are Based on representation properties of D-consequence relations, it proves that any cumulative nonmonotonic consequence relation with the connective-free form can be represented by ADRFs.展开更多
In the relevance-theoretic framework,translation is an act of communication carried out between two cultures through the medium of language,which involves the cognition of three parts;the original writer,the translato...In the relevance-theoretic framework,translation is an act of communication carried out between two cultures through the medium of language,which involves the cognition of three parts;the original writer,the translator,and the target reader.Since it is a culture-specific phenomenon and the cognitive environment of the original writer and the target reader are different,cultural default often results in misreading or incoherent understanding in cross-cultural communication.展开更多
Schizophrenia is a severe mental disorder characterized by impaired perception, delusions, thought disorder, abnormal emotion regulation, altered motor function, and impaired drive. The default mode network （DMN）, s...Schizophrenia is a severe mental disorder characterized by impaired perception, delusions, thought disorder, abnormal emotion regulation, altered motor function, and impaired drive. The default mode network （DMN）, since it was first proposed in 2001, has become a central research theme in neuropsychiatric disorders, including schizophrenia. In this review, first we define the DMN and describe its functional activity, functional and anatomical connectivity, heritability, and inverse correlation with the task positive network. Second, we review empirical studies of the anatomical and functional DMN, and anti-correlation between DMN and the task positive network in schizophrenia. Finally, we review preliminary evidence about the relationship between antipsychotic medications and regulation of the DMN, review the role of DMN as a treatment biomarker for this disease, and consider the DMN effects of individualized therapies for schizophrenia.展开更多
Mood disorders/psychosis have been associated with dysfunctions in the default mode network(DMN).However,the relative contributions of DMN regions to state and trait disturbances in pediatric bipolar disorder(PBD)rema...Mood disorders/psychosis have been associated with dysfunctions in the default mode network(DMN).However,the relative contributions of DMN regions to state and trait disturbances in pediatric bipolar disorder(PBD)remain unclear.The aim of this study was to investigate the possible mechanisms of PBD through brain imaging and explore the influence of psychotic symptoms on functional alterations in PBD patients.Twenty-nine psychotic and 26 non-psychotic PBD patients,as well as 19 age-and sex-matched healthy controls underwent a restingstate functional MRI scan and the data were analyzed by independent component analysis.The DMN component from the fMRI data was extracted for each participant.Spearman's rank correlation analysis was performed between aberrant connectivity and clinical measurements.The results demonstrated that psychotic PBD was characterized by aberrant DMN connectivity in the anterior cingulate cortex/medial prefrontal cortex,bilateral caudate nucleus,bilateral angular gyri,and left middle temporal gyrus,while non-psychotic PBD was not,suggesting further impairment with the development of psychosis.In summary,we demonstrated unique impairment in DMN functional connectivity in the psychotic PBD group.These specific neuroanatomical abnormalities may shed light on the underlying pathophysiology and presentation of PBD.展开更多
Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer’s disease(AD)or amnestic mild cognitive impairment(aMCI).However,most studies examined traditional resting state functi...Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer’s disease(AD)or amnestic mild cognitive impairment(aMCI).However,most studies examined traditional resting state functional connections,ignoring the instantaneous connection mode of the whole brain.In this case-control study,we used a new method called dynamic functional connectivity(DFC)to look for abnormalities in patients with AD and aMCI.We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant,and then used a support vector machine to classify AD patients and normal controls.Finally,we highlighted brain regions and brain networks that made the largest contributions to the classification.We found differences in dynamic function connectivity strength in the left precuneus,default mode network,and dorsal attention network among normal controls,aMCI patients,and AD patients.These abnormalities are potential imaging markers for the early diagnosis of AD.展开更多
Neuroimaging techniques such as functional magnetic resonance imaging and positron emission tomography have provided an unprecedented neurobiological perspective for research on personality traits. Evidence from task-...Neuroimaging techniques such as functional magnetic resonance imaging and positron emission tomography have provided an unprecedented neurobiological perspective for research on personality traits. Evidence from task-related neuroimaging has shown that extraversion is associated with activations in regions of the anterior cingulate cortex, dorsolateral prefrontal cortex, middle temporal gyrus and the amygdala. Currently, resting-state neuroimaging is being widely used in cognitive neuroscience. Initial exploration of extraversion has revealed correlations with the medial prefrontal cortex, anterior cingulate cortex, insular cortex, and the precuneus. Recent research work has indicated that the long-range temporal dependence of the resting-state spontaneous oscillation has high test-retest reliability. Moreover, the long-range temporal dependence of the resting-state networks is highly correlated with personality traits, and this can be used for the prediction of extraversion. As the long-range temporal dependence reflects real-time information updating in individuals, this method may provide a new approach to research on personality traits.展开更多
Although organellar genomes(including chloroplast and mitochondrial genomes)are smaller than nuclear genomes in size and gene number,organellar genomes are very important for the investigation of plant evolution and m...Although organellar genomes(including chloroplast and mitochondrial genomes)are smaller than nuclear genomes in size and gene number,organellar genomes are very important for the investigation of plant evolution and molecular ecology mechanisms.Few studies have focused on the organellar genomes of horticultural plants.Approximately 1193 chloroplast genomes and 199 mitochondrial genomes of land plants are available in the National Center for Biotechnology Information(NCBI),of which only 39 are from horticultural plants.In this paper,we report an innovative and efficient method for high-quality horticultural organellar genome assembly from next-generation sequencing(NGS)data.Sequencing reads were first assembled by Newbler,Amos,and Minimus software with default parameters.The remaining gaps were then filled through BLASTN search and PCR.The complete DNA sequence was corrected based on Illumina sequencing data using BWA(Burrows–Wheeler Alignment tool)software.The advantage of this approach is that there is no need to isolate organellar DNA from total DNA during sample preparation.Using this procedure,the complete mitochondrial and chloroplast genomes of an ornamental plant,Salix suchowensis,and a fruit tree,Ziziphus jujuba,were identified.This study shows that horticultural plants have similar mitochondrial and chloroplast sequence organization to other seed plants.Most horticultural plants demonstrate a slight bias toward A+T rich features in the mitochondrial genome.In addition,a phylogenetic analysis of 39 horticultural plants based on 15 protein-coding genes showed that some mitochondrial genes are horizontally transferred from chloroplast DNA.Our study will provide an important reference for organellar genome assembly in other horticultural plants.Furthermore,phylogenetic analysis of the organellar genomes of horticultural plants could accurately clarify the unanticipated relationships among these plants.展开更多
基金This research was supported by Korea Institute for Advancement of Technology(KIAT)grant funded by the Korea Government(MOTIE)(P0012724,The Competency DevelopmentProgram for Industry Specialist)the Soonchunhyang University Research Fund.
文摘Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases,child mortality and morbidity.Expanded Program on Immunization(EPI)is a nation-wide program in Pakistan to implement immunization activities,however the coverage is quite low despite the accessibility of free vaccination.This study proposes a defaulter prediction model for accurate identification of defaulters.Our proposed framework classifies defaulters at five different stages:defaulter,partially high,partially medium,partially low,and unvaccinated to reinforce targeted interventions by accurately predicting children at high risk of defaulting from the immunization schedule.Different machine learning algorithms are applied on Pakistan Demographic and Health Survey(2017–18)dataset.Multilayer Perceptron yielded 98.5%accuracy for correctly identifying children who are likely to default from immunization series at different risk stages of being defaulter.In this paper,the proposed defaulters’prediction framework is a step forward towards a data-driven approach and provides a set of machine learning techniques to take advantage of predictive analytics.Hence,predictive analytics can reinforce immunization programs by expediting targeted action to reduce dropouts.Specially,the accurate predictions support targeted messages sent to at-risk parents’and caretakers’consumer devices(e.g.,smartphones)to maximize healthcare outcomes.
文摘Background: Tuberculosis is second only to HIV/AIDS as the greatest killer worldwide, due to a single infectious agent. Directly Observed Treatment Short-Course (DOTS) is presently the WHO recommended programme to fight tuberculosis worldwide. There is a need to understand the characteristics of patients who default from treatment for tuberculosis. This will help modify the strategies to reduce such default to the barest minimum and achieve higher levels of adherence. Objective: The aim of this study was to describe the characteristics of patients that defaulted from treatment for TB at Nnamdi Azikiwe University Teaching Hospital (NAUTH) Nnewi DOTS clinic for the period 1st January 2011 to 31st December 2012. Materials and Methods: This was a retrospective study conducted at the DOTS clinic at Nnamdi Azikiwe University Teaching Hospital Nnewi, Anambra State, Nigeria. The records of patients who received treatment from the clinic from 1st January 2011 to 31st December 2012 (2 years) were reviewed. The data collected include patients’ demographic characteristics, treatment category, patient type, baseline sputum smear result, and retroviral status. From the data, default rate was calculated and its relationship with other variables noted. Associations between patients’ characteristics were determined using chi square test of independence. The significance level was set at p = 0.05. Results: A total of 765 patients enrolled for TB treatment in the DOTS clinic of the study area within the study period of 1<sup>st</sup> January 2011 and December 31st 2012. The mean age at commencement of the treatment was 33.14 years (±18.09). The outcome of treatment showed that 260 (34%) had treatment completed, 230 (30.1%) cured, 120 (15.7%) defaulted, 103 (13.5%) died, 40 (5.2%) were transferred-out, and 12 (1.6%) failed in the treatment, giving a treatment success rate of 64.1%. Among the 120 (15.7%) patients that defaulted from treatment, majority 80 (66.7%) were males, and most 30 (25.0%) were in the 30 - 39 years age group. Conclusion: Defaulting starts with treatment interruption hence prompt management of interruption of treatment and default will largely help in preventing drug-resistant TB.
文摘Between 2005 and 2007,the China Development Bank offered 1.66 billion yuan($237 million) worth of loans to 243,000 stu- dents from poor families in central China’s Henan Province.
文摘Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.
基金supported by the Guangzhou Municipal Key Discipline in Medicine(2021-2023)the Guangzhou High-level Clinical Key Specialty,the Guangzhou Research-oriented Hospital,the Innovative Clinical Technique of Guangzhou(2024-2026)+6 种基金the Guangdong Basic and Applied Basic Research Foundation(grant number 2022A1515011567,2020A1515110565)the Guangzhou Science,Technology Planning Project(grant number 202201010714,202103000032)the National Natural Science Foundation of China(grant number 82471546)the Guangdong College Students Innovation and Entrepreneurship Training Project(grant number S202310570038)the Guangzhou Health Science and Technology Project(grant number 20231A010038)the Guangzhou Traditional Chinese Medicine and Integrated Traditional Chinese and Western Medicine Technology Project(grant number:20232A010013)the Science and Technology Plan Project of Guangzhou(2023A03J0842).
文摘Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.
文摘Microfinance institutions in Kenya play a unique role in promoting financial inclusion,loans,and savings provision,especially to low-income individuals and small-scale entrepreneurs.However,despite their benefits,most of their products and programs in Machakos County have been reducing due to re-payment challenges,threatening their financial ability to extend further credit.This could be attributed to ineffective credit scoring models which are not able to establish the nuanced non-linear repayment behavior and patterns of the loan applicants.The research objective was to enhance credit risk scoring for microfinance institutions in Machakos County using supervised machine learning algorithms.The study adopted a mixed research design under supervised machine learning approach.It randomly sampled 6771 loan application ac-count records and repayment history.Rstudio and Python programming lan-guages were deployed for data pre-processing and analysis.Logistic regression algorithm,XG Boosting and the random forest ensemble method were used.Metric evaluations used included the performance accuracy,Area under the Curve and F1-Score.Based on the study findings:XG Boosting was the best performer with 83.3%accuracy and 0.202 Brier score.Development of legal framework to govern ethical and open use of machine learning assessment was recommended.A similar research but using different machine learning al-gorithms,locations,and institutions,to ascertain the validity,reliability and the generalizability of the study findings was recommended for further re-search.
基金Supported by the Medical Research Project of the Chongqing Municipal Health Commission,No.2024WSJK110.
文摘BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological substrates underlying depression,the intricate patterns of disrupted brain network connectivity in adolescents warrant further exploration.AIM To elucidate the neural correlates of adolescent depression by examining brain network connectivity using resting-state functional magnetic resonance imaging(rs-fMRI).METHODS The study cohort comprised 74 depressed adolescents and 59 healthy controls aged 12 to 17 years.Participants underwent rs-fMRI to evaluate functional connectivity within and across critical brain networks,including the visual,default mode network(DMN),dorsal attention,salience,somatomotor,and frontoparietal control networks.RESULTS Analyses revealed pronounced functional disparities within key neural circuits among adolescents with depression.The results demonstrated existence of hemispheric asymmetries characterized by enhanced activity in the left visual network,which contrasted the diminished activity in the right hemisphere.The DMN facilitated increased activity within the left prefrontal cortex and reduced engagement in the right hemisphere,implicating disrupted self-referential and emotional processing mechanisms.Additionally,an overactive right dorsal attention network and a hypoactive salience network were identified,underscoring significant abnormalities in attentional and emotional regulation in adolescent depression.CONCLUSION The findings from this study underscore distinct neural connectivity disruptions in adolescent depression,underscoring the critical role of specific neurobiological markers for precise early diagnosis of adolescent depression.The observed functional asymmetries and network-specific deviations elucidate the complex neurobiological architecture of adolescent depression,supporting the development of targeted therapeutic strategies.
基金Supported by the Pharmaceutical Science and Technology Project of Zhejiang Province,No.2023RC266the Natural Science Foundation of Ningbo,No.202003N4266.
文摘BACKGROUND Group cognitive behavioral therapy(GCBT)is increasingly being used to treat obsessive-compulsive disorder(OCD)because of its high efficiency,economy,and interaction among group members.However,the changes in network functional connectivity(FC)in patients with OCD with GCBT remain unclear.AIM To investigate inter-and intra-network resting-state FC(rs-FC)abnormalities before and after GCBT in unmedicated patients with OCD and validate the efficacy of GCBT.METHODS Overall,33 individuals with OCD and 26 healthy controls underwent resting-state functional magnetic resonance imaging.The patients were rescanned 12 weeks after GCBT.Four cognition-related networks-default mode network(DMN),dorsal attention network(DAN),salience network(SAN),and frontoparietal network(FPN)-were selected to examine FC abnormalities within and between OCD networks before and after GCBT.Neuropsychological assessments including memory,executive function,speech,attention,and visuospatial ability were reassessed following GCBT.Pearson’s correlations were used to analyze the relationship between aberrant FC in cognition-related networks and altered neuropsychological assessments in patients.RESULTS Rs-FC within the DMN and DAN decreased significantly.Additionally,rs-FC between the DMN-DAN,DMNFPN,DMN-SAN,and DAN-SAN also decreased.Significant improvements were observed in cognitive functions,such as memory,executive function,attention,and visuospatial ability.Furthermore,reduced rs-FC within the DMN correlated with visuospatial ability and executive function;DAN positively correlated with Shape Trails Test(STT)-A test elapsed time;DMN-DAN negatively correlated with Rey-Osterrieth Complex Figure(Rey-O)mimicry time and the three elapsed times of the tower of Hanoi;DMN-SAN negatively correlated with Rey-O imitation time and positively correlated with STT-A test elapsed time;and DMN-FPN negatively correlated with Auditory Word Learning Test N1 and N4 scores.CONCLUSION Decreased rs-FC within the DMN and DAN,which correlated with executive function post-treatment,has potential as a neuroimaging marker to predict treatment response to GCBT in patients with OCD.
文摘presented The conceptions of abstract default reasoning frameworks （ADRFs） and D-consequence relations are Based on representation properties of D-consequence relations, it proves that any cumulative nonmonotonic consequence relation with the connective-free form can be represented by ADRFs.
文摘In the relevance-theoretic framework,translation is an act of communication carried out between two cultures through the medium of language,which involves the cognition of three parts;the original writer,the translator,and the target reader.Since it is a culture-specific phenomenon and the cognitive environment of the original writer and the target reader are different,cultural default often results in misreading or incoherent understanding in cross-cultural communication.
基金supported by the National Natural Science Foundation of China(81271484,81471361,30900486,and 81371480)the National Basic Research Development Program(973 Program)of China(2012CB517904)the Nation Sponsored Study Abroad Program from China Scholarship Council(201506370095)
文摘Schizophrenia is a severe mental disorder characterized by impaired perception, delusions, thought disorder, abnormal emotion regulation, altered motor function, and impaired drive. The default mode network （DMN）, since it was first proposed in 2001, has become a central research theme in neuropsychiatric disorders, including schizophrenia. In this review, first we define the DMN and describe its functional activity, functional and anatomical connectivity, heritability, and inverse correlation with the task positive network. Second, we review empirical studies of the anatomical and functional DMN, and anti-correlation between DMN and the task positive network in schizophrenia. Finally, we review preliminary evidence about the relationship between antipsychotic medications and regulation of the DMN, review the role of DMN as a treatment biomarker for this disease, and consider the DMN effects of individualized therapies for schizophrenia.
基金supported by National Natural Science Foundation of China (81171291, 81371531, 81571344, 81871344)the Natural Science Foundation of Jiangsu Province, China (BK20161109)+2 种基金the Key Program for Guangming Lu (BWS11J063, and 10z026)the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China (18KJB190003)the Postdoctoral Science Foundation of China (2014M552700)
文摘Mood disorders/psychosis have been associated with dysfunctions in the default mode network(DMN).However,the relative contributions of DMN regions to state and trait disturbances in pediatric bipolar disorder(PBD)remain unclear.The aim of this study was to investigate the possible mechanisms of PBD through brain imaging and explore the influence of psychotic symptoms on functional alterations in PBD patients.Twenty-nine psychotic and 26 non-psychotic PBD patients,as well as 19 age-and sex-matched healthy controls underwent a restingstate functional MRI scan and the data were analyzed by independent component analysis.The DMN component from the fMRI data was extracted for each participant.Spearman's rank correlation analysis was performed between aberrant connectivity and clinical measurements.The results demonstrated that psychotic PBD was characterized by aberrant DMN connectivity in the anterior cingulate cortex/medial prefrontal cortex,bilateral caudate nucleus,bilateral angular gyri,and left middle temporal gyrus,while non-psychotic PBD was not,suggesting further impairment with the development of psychosis.In summary,we demonstrated unique impairment in DMN functional connectivity in the psychotic PBD group.These specific neuroanatomical abnormalities may shed light on the underlying pathophysiology and presentation of PBD.
基金supported by the National Natural Science Foundation of China,No.81471120Fund Projects in Technology of the Foundation Strengthening Program of China,No.2019-JCJQ-JJ-151(both to XZ).
文摘Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer’s disease(AD)or amnestic mild cognitive impairment(aMCI).However,most studies examined traditional resting state functional connections,ignoring the instantaneous connection mode of the whole brain.In this case-control study,we used a new method called dynamic functional connectivity(DFC)to look for abnormalities in patients with AD and aMCI.We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant,and then used a support vector machine to classify AD patients and normal controls.Finally,we highlighted brain regions and brain networks that made the largest contributions to the classification.We found differences in dynamic function connectivity strength in the left precuneus,default mode network,and dorsal attention network among normal controls,aMCI patients,and AD patients.These abnormalities are potential imaging markers for the early diagnosis of AD.
基金supported by grants from the National High Technology Research Development Project (863 Project) of China (2015AA020504)the National Natural Science Foundation of China (31571111 and 31200857)the Fundamental Research Funds for the Central Universities of China (SW1509113)
文摘Neuroimaging techniques such as functional magnetic resonance imaging and positron emission tomography have provided an unprecedented neurobiological perspective for research on personality traits. Evidence from task-related neuroimaging has shown that extraversion is associated with activations in regions of the anterior cingulate cortex, dorsolateral prefrontal cortex, middle temporal gyrus and the amygdala. Currently, resting-state neuroimaging is being widely used in cognitive neuroscience. Initial exploration of extraversion has revealed correlations with the medial prefrontal cortex, anterior cingulate cortex, insular cortex, and the precuneus. Recent research work has indicated that the long-range temporal dependence of the resting-state spontaneous oscillation has high test-retest reliability. Moreover, the long-range temporal dependence of the resting-state networks is highly correlated with personality traits, and this can be used for the prediction of extraversion. As the long-range temporal dependence reflects real-time information updating in individuals, this method may provide a new approach to research on personality traits.
基金This study was supported by the National Key Research and Development Plan of China(2016YFD0600101)2017 Graduate Research and Innovation Program Projects in Jiangsu Province(KYCY17_0827)+3 种基金the Fundamental Research Funds for the Central Non-Profit Research Institution of CAF(CAFYBB2014QB015)the National Natural Science Foundation of China(31570662,31500533,and 61401214)the Jiangsu Provincial Department of Housing and Urban-Rural Development(2016ZD44)the PAPD(Priority Academic Program Development)program at Nanjing Forestry University.
文摘Although organellar genomes(including chloroplast and mitochondrial genomes)are smaller than nuclear genomes in size and gene number,organellar genomes are very important for the investigation of plant evolution and molecular ecology mechanisms.Few studies have focused on the organellar genomes of horticultural plants.Approximately 1193 chloroplast genomes and 199 mitochondrial genomes of land plants are available in the National Center for Biotechnology Information(NCBI),of which only 39 are from horticultural plants.In this paper,we report an innovative and efficient method for high-quality horticultural organellar genome assembly from next-generation sequencing(NGS)data.Sequencing reads were first assembled by Newbler,Amos,and Minimus software with default parameters.The remaining gaps were then filled through BLASTN search and PCR.The complete DNA sequence was corrected based on Illumina sequencing data using BWA(Burrows–Wheeler Alignment tool)software.The advantage of this approach is that there is no need to isolate organellar DNA from total DNA during sample preparation.Using this procedure,the complete mitochondrial and chloroplast genomes of an ornamental plant,Salix suchowensis,and a fruit tree,Ziziphus jujuba,were identified.This study shows that horticultural plants have similar mitochondrial and chloroplast sequence organization to other seed plants.Most horticultural plants demonstrate a slight bias toward A+T rich features in the mitochondrial genome.In addition,a phylogenetic analysis of 39 horticultural plants based on 15 protein-coding genes showed that some mitochondrial genes are horizontally transferred from chloroplast DNA.Our study will provide an important reference for organellar genome assembly in other horticultural plants.Furthermore,phylogenetic analysis of the organellar genomes of horticultural plants could accurately clarify the unanticipated relationships among these plants.
