Objective:To analyze the risk factors for prolonged hospital stay in inpatients based on data from nutritionDay worldwide survey 2020 to 2022 conducted in China and to construct and validate a prediction model for clinical decision-making.Methods:This study was a retrospective study, the data source was the China's multi-centered nutritionalDay worldwide database for nutrition status in inpatients. A total of 2 335 cases registered in the database from 2020 to 2022 were selected for the study, comprising individuals aged 18 and above, with valid response for the 30-day prognosis questionnaires, and with complete clinical data. The demographic characteristics, nutrition-related indicators, disease information, and outcome indicators of the participants were collected. Based on the 75th percentile of hospitalization duration, the participants were divided into the prolonged length of stay group (570 cases) and the normal length of stay group (1 765 cases). A nomogram prediction model was constructed using the least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Logistic regression analysis. Area under the curve ( AUC), calibration curve, Hosmer-Lemeshow test, and clinical decision curve were used to verify discriminative ability, goodness-of-fit, and clinical effectiveness of the model. Results:Seven independent risk factors for prolonged length of stay were identified, namely body mass index (BMI), whether surgery occurred during hospitalization, intensive care unit admission during hospitalization, Nutrition Risk Screening 2002 score, ambulatory independence, previous hospitalization frequency, and weight loss in the past 3 months. A nomogram prediction model was established accordingly. The AUC of training set was 0.783 (95% CI: 0.759 - 0.807), and the AUC of validation set was 0.797 (95% CI: 0.746 - 0.849). Calibration curves and Hosmer-Lemeshow tests ( P=0.735 for training set, P=0.431 for validation set) indicated good model fitting. The clinical decision curve demonstrated the favorable clinical utility of the nomogram. Conclusions:BMI, whether they had surgery during hospitalization, whether they were admitted to the ICU during hospitalization, NRS 2002 score, whether they were able to walk independently, number of previous hospitalizations, and weight loss in the past 3 months were risk factors for longer stay in Chinese hospitalized patients. The nomogram prediction model developed in this study can forecast the risk of prolonged length of stay among Chinese inpatients, providing a basis for early identification and intervenion in high-risk patients.

Objective:To analyze the risk factors for prolonged hospital stay in inpatients based on data from nutritionDay worldwide survey 2020 to 2022 conducted in China and to construct and validate a prediction model for clinical decision-making.Methods:This study was a retrospective study, the data source was the China's multi-centered nutritionalDay worldwide database for nutrition status in inpatients. A total of 2 335 cases registered in the database from 2020 to 2022 were selected for the study, comprising individuals aged 18 and above, with valid response for the 30-day prognosis questionnaires, and with complete clinical data. The demographic characteristics, nutrition-related indicators, disease information, and outcome indicators of the participants were collected. Based on the 75th percentile of hospitalization duration, the participants were divided into the prolonged length of stay group (570 cases) and the normal length of stay group (1 765 cases). A nomogram prediction model was constructed using the least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Logistic regression analysis. Area under the curve ( AUC), calibration curve, Hosmer-Lemeshow test, and clinical decision curve were used to verify discriminative ability, goodness-of-fit, and clinical effectiveness of the model. Results:Seven independent risk factors for prolonged length of stay were identified, namely body mass index (BMI), whether surgery occurred during hospitalization, intensive care unit admission during hospitalization, Nutrition Risk Screening 2002 score, ambulatory independence, previous hospitalization frequency, and weight loss in the past 3 months. A nomogram prediction model was established accordingly. The AUC of training set was 0.783 (95% CI: 0.759 - 0.807), and the AUC of validation set was 0.797 (95% CI: 0.746 - 0.849). Calibration curves and Hosmer-Lemeshow tests ( P=0.735 for training set, P=0.431 for validation set) indicated good model fitting. The clinical decision curve demonstrated the favorable clinical utility of the nomogram. Conclusions:BMI, whether they had surgery during hospitalization, whether they were admitted to the ICU during hospitalization, NRS 2002 score, whether they were able to walk independently, number of previous hospitalizations, and weight loss in the past 3 months were risk factors for longer stay in Chinese hospitalized patients. The nomogram prediction model developed in this study can forecast the risk of prolonged length of stay among Chinese inpatients, providing a basis for early identification and intervenion in high-risk patients.

Objective To systematically evaluate and sequentially analyze the clinical efficacy and safety of Baogong Zhixue Granules for the treatment of abnormal uterine bleeding due to ovulation disorder.Methods The randomized controlled trials(RCTs)of Baogong Zhixue Granules for the treatment of abnormal uterine bleeding due to ovulation disorder were retrieved from the databases of CNKI,Wanfang Data,VIP,China Biology Medicine,PubMed,Embase,and Cochrane Library from the establishment of the databases to January 5th,2023.Literature screening and data extraction were conducted according to Cochrane Handbook for Systematic Reviews of Interventions,and Meta-analysis was performed by RevMan 5.4.Results Totally 15 articles were included,involving 1 425 patients.Meta-analysis results showed that Baogong Zhixue Granules could effectively improve the clinical efficacy of abnormal uterine bleeding due to ovulatory disorder(RR=1.17,95%CI[1.13,1.23],P<0.000 01),shorten hemostasis time[bleeding control time(MD=-6.35,95%CI[-8.89,-3.81],P<0.000 01),complete hemostasis time(MD=-12.56,95%CI[-16.22,-8.89],P<0.000 01)],reduce endometrial thickness(MD=-1.26,95%CI[-1.71,-0.80],P<0.000 01),reduce hemoglobin loss(MD=13.35,95%CI[11.41,15.29],P<0.000 01),improve the score of uterine bleeding(MD=-2.22,95%CI[-2.43,-2.01],P<0.000 01),and reduce the recurrence of disease(RR=0.37,95%CI[0.19,0.72],P=0.004).There was no statistical significance between the test group and the control group in terms of adverse reactions(P=0.82).The trial sequential analysis of the total efficiency was carried out,and the cumulative included research passed the traditional threshold and trail sequential analysis threshold.Conclusion Baogong Zhixue Granules have a certain clinical efficacy in the treatment of abnormal uterine bleeding due to ovulation disorder,but there may be publication bias in the study,and higher quality clinical RCTs need to be carried out.

Objective:To explore the white matter structural characteristics in patients with bipolar disorder(BD)using diffusion tensor imaging(DTI)and investigate their relationship with cognitive function.Methods:A total of 15 patients with BD type Ⅰ and 26 patients with BD type Ⅱ who met the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition(DSM-Ⅳ)diagnostic criteria and 37 normal controls were included.Cognitive function was assessed with the Trail Making Test(TMT)and Repeatable Battery for the Assessment of Neuropsy-chological Status(RBANS).The tract-based spatial statistics(TBSS)method was used to explore the differences in fractional anisotropy(FA)and mean diffusivity(MD)among the three groups and perform correlation analyses with cognitive function.Results:Patients with BD Ⅰ and BD Ⅱ had lower scores in attention(P＜0.001),delayed memory(P＜0.01),and total scores(P＜0.001)on the RBANS compared to the normal control group.They also exhibited lower FA values in the corpus callosum and right superior corona radiata compared to the normal control group(P＜0.05).In the BD Ⅰ group,there was a positive correlation between FA values in the genu of corpus cal-losum and visuospatial/constructional scores(r=0.74,P＜0.05),while in the BD Ⅱ group,a positive correlation was found between FA values in the same region and language function scores(r=0.55,P＜0.05).Conclusion:It suggests that patients with bipolar disorder may have impaired white matter integrity in the corpus callosum and right superior corona radiata,which may be associated with cognitive impairment.

Objective To explore the characteristics of opportunistic infections(OIs)in HIV-infected indi-viduals with suboptimal immune reconstitution after ART treatment so as to provide a reference for preventing and managing HIV infections.Methods The clinical data including opportunistic infections specifically were acquired from 112 HIV-infected individuals with suboptimal immune reconstitution from the outpatient department of Wuming Hospital,Guangxi Medical University.The impact of baseline CD4+T lymphocyte counts on the incidence,type,and mixed infection rates of the opportunistic infections were analyzed.Results The opportunistic infection rate among the 112 HIV-infected individuals with suboptimal immune reconstitution was 42.86%,among which fungal infections were the most commonly seen.The opportunistic infection rate of the patients with a baseline of CD4+T lymphocyte counts≤50/μL was significantly higher than that of the patients with a baseline of CD4+T lymphocyte counts>50/μL,and there was no significant difference in the type of opportunistic infections as well as the rate of mixed infections.Conclusion HIV-infected people with suboptimal immune reconstitution in Guangxi are susceptible to HIV OIs.Among them,the group with a baseline CD4+ T lymphocyte counts≤50/μL has a higher rate of OIs,mainly fungal infections.

Humans ; Parkinson Disease/therapy* ; Phototherapy ; Treatment Outcome

Objective:Using the Taqman low-density array (TLDA) to develop a detection method which can rapidly type influenza A virus and the subtypes of H1-H16 and N1-N9, which is suitable for rapid typing and identification of influenza A in influenza like cases and avian influenza samples.Methods:The primers and probes of influenza A, H1-16 subtypes, N1-9 subtypes were designed and pre-customized on the TLDA reaction chip; Optimize the TLDA annealing temperature; The sensitivity of TLDA was evaluated by 10 fold gradient dilution of influenza A virus nucleic acid of various subtypes and the digital PCR; The specificity of the TLDA was verified by influenza B, adenovirus, respiratory syncytial virus and other respiratory viruses. At the same time, a variety of influenza A viruses that have been clearly typed were selected to evaluate the specificity and effectiveness of TLDA; The TLDA was used to detect 16 samples of influenza like cases and 24 samples of external environment of avian influenza.Results:The best annealing temperature of TLDA was 60 ℃, the detection sensitivity of TLDA was between 1.52 and 8.00 copies/μl for H1N1, H3N2, H5N6, H7N9 and H9N2, there was no specific cross reaction with influenza B, avian influenza, adenovirus, respiratory syncytial virus and other respiratory viruses. A total of 12 influenza positive samples and 24 samples from environmental surveillance of avian influenza were detected by TLDA, all of the result of samples were correct in typing.Conclusions:The high-throughput detection method of influenza A virus based on TLDA has good sensitivity and specificity, and the result of clinical samples show that the TLDA is suitable for rapid detection of influenza like cases and avian influenza samples, especially for rapid subtype screening and identification of new influenza A virus that cannot be identified by conventional commercial kits.

Objective:To explore the associations between perceived built environment attributes and adults’ leisure-time physical activity in four cities of China.Methods:Multistage cluster random sampling method was used to select adults aged 25 to 64 in Hangzhou, Suzhou, Chengdu, and Qingdao. Data were collected from June 2017 to July 2018. The perception of the urban built environment was assessed by the neighborhood environment walkability scale-abbreviated (NEWS-A), and the physical activity was assessed by the International Physical Activity Questionnaire. Generalized linear mixed models were used to explore the relationship between the perceived built environment and leisure-time physical activities.Results:A total of 3 789 participants were included in the analysis. After adjusting for potential confounders, better access to public services ( OR=1.34, 95% CI: 1.02-1.75) and higher aesthetic quality ( OR=1.37, 95% CI: 1.09-1.73) were positively associated with the possibility of engaging in leisure-time physical activity in the past week. Similarly, these two attributes were positively associated with leisure-time walking. Higher scores on the perception of street connectivity were positively associated with leisure-time walking [ exp( β)=1.09, 95% CI: 1.00-1.19]. Higher residential density [ exp( β)=1.000 4, 95% CI:1.000 0-1.000 8], better access to physical activity destinations[ exp( β)=1.09, 95% CI: 1.00-1.19], and better aesthetics [ exp( β)=1.11, 95% CI:1.00-1.22] were associated with higher leisure-time physical activity. Similarly, these three attributes were positively associated with the possibility of meeting the WHO recommendations. Conclusion:Changing some urban built environment attributes may increase leisure-time physical activity.

Objective: To investigate the dynamic changes of copper and iron contents in brain tissue, body fluids and barriers of rats exposed to lead at different periods in order to provide a theoretical basis for the study of the mechanism of lead nerve injury. Methods: Sixty-four healthy adult SPF male SD rats were randomly divided into control group and lead exposure group, after one week of adaptive feeding, rats in the lead exposure group were treated with 250 mg/L lead acetate, and rats in control group were treated with ordinary drinking water, the experimental period was 12 weeks. After exposure for 3, 6, 9 and 12 weeks, the samples including blood, choroid plexus, cerebrospinal fluid, cortex, hippocampus, striatum, hypothalamus, amygdala, substantia nigra and cerebellum were obtained. Lead, copper and iron content in all kinds of samples were detected by Inductively Coupled Plasma Mass Spectrometry(ICP-MS). The measurement data were presented as Mean±SD, Comparison of metal contents in different tissues of rats at different time analyzed using repeated measurement analysis of variance, Two-variable correlation analysis using Spearman correlation test.The relationship between lead exposure experiod and copper and iron in samples was studied by using trend test. Results: After 12 weeks of lead exposure compared with the control group, lead contents in cortex, hippocampus, striatum, hypothalamus, amygdala, substantia nigra and cerebellum of rats were 2.21, 2.44, 2.95, 3.53, 4.01, 1.85 and 2.86 folds of control group, and the differences were statistically significant(P<0.05). At the same time, lead content in blood, cerebrospinal fluid,choroid plexus, brain microvessels and bones increased. The increase rate in the amygdala and cerebrospinal fluid ranked first among brain tissue or barrier,which were 4.01 and 3.0 folds respectively. Compared with the control group, Compared with the control group, copper content in cortex,hippocampus, striatum, hypothalamus,amygdala, cerebellum,blood,cerebrospinal fluid,choroid plexus and cerebral microvasculature showed an increasing trend among rats following 3,6,9,12 weeks of lead exposure. Copper content change in the striatum was highest among all brain tissue. The increase rate of copper content in the striatum was at the top among brain tissues. After 12 weeks of lead exposure,copper content in brain microvessels was 4.98 folds higher than that of the control group (P<0.05). After lead exposure at different periods,the iron content in the cortex, hippocampus, striatum,cerebrospinal fluid,choroid plexus and brain microvessels of experimental rats all increased(P<0.05). And the iron increase rate in the hypothalamus or cerebrospinal fluid increase ranked first among brain tissues or body fluid the most obviously. Conclusion With the increase of exposure time, lead exposure can changes in the contents of copper and iron in different brain tissues,body fluids and barriers in rats,among which, the contents of copper and iron in the amygdala,cerebrospinal fluid and brain microvessels increase significantly. This may be related to nerve damage from lead exposure.

Brain science accelerates the study of intelligence and behavior, contributes fundamental insights into human cognition, and offers prospective treatments for brain disease. Faced with the challenges posed by imaging technologies and deep learning computational models, big data and high-performance computing (HPC) play essential roles in studying brain function, brain diseases, and large-scale brain models or connectomes. We review the driving forces behind big data and HPC methods applied to brain science, including deep learning, powerful data analysis capabilities, and computational performance solutions, each of which can be used to improve diagnostic accuracy and research output. This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible, by improving data standardization and sharing, and by providing new neuromorphic insights.