Dysregulation of immune response is currently recognized as one of the important pathological factors in ulcerative colitis (UC). Based on the confirmation that the Sini San (SNS) can significantly improve the colon inflammation induced by dextran sulfate sodium sulfate (DSS) in mice, the present work systematically studied the xenobiotics in the colon and mesenteric lymph nodes, spleen, and thymus of UC mice after administration of SNS by high-performance liquid chromatography-ion trap time-of-flight mass spectrometry (HPLC-IT-TOF-MS). The results showed that, in addition to the colon, some components and their metabolites in SNS could be distributed in immune tissues, and it was found that the quality of relatively low-abundance and weakly responsive components such as saikosaponin a, paeoniflorin, and glycyrrhizic acid had the characteristics of efficient transmission to the colon and lymphoid organs. These components were very likely to be the source of pharmacodynamic substances of SNS. The findings of this study lay a foundation for the study of the efficacy and molecular mechanism of the components against ulcerative colitis, and also provide a scientific basis for the rational clinical application of SNS, which is expected to promote the secondary development of its preparations.

BACKGROUND: Circadian syndrome (CircS) may be closely linked to lifestyle, psychological, and occupational factors, but evidence is lacking. This study aimed to explore complex associations between lifestyle, psychological and occupational factors and CircS among employed people in southwestern China. METHODS: In this study, network analysis was used to identify complex associations between lifestyle, psychological and occupational factors and CircS in employed people from the Chinese Cohort of Working Adults (CCWA). The centrality of each variable was estimated by strength centrality index, which was calculated by the sum of edge weights connected to the variable. Bridge in the network was identified as the variables in the top 80 th percentile of overall bridge strength, which was defined as the most strongly connected variables across lifestyle, psychological and occupational factors and CircS. The differences were assessed in network structures between subgroups divided by the median score of the variable with the strongest bridge strengthen. RESULTS: Among 31,105 participants from CCWA, 5213 (16.76%) had CircS. In the constructed network, anxiety (edge weights: 0.28), smoking (edge weights: 0.15), drinking (edge weights: 0.10), perceived noise at work (edge weights: 0.08), and implicit health attitude (edge weights: -0.02) were directly related to CircS, with 83.31% of the variance for CircS explained by these neighboring factors. Anxiety was the most central variable (strength centrality: 1.20) in the network and the strongest bridge (bridge strength: 0.84) connecting all domains of variables. A stronger association between anxiety and CircS was observed in the network of participants with more severe anxiety (edge weight: 0.23) than those with less severe anxiety (edge weight: 0.03). CONCLUSION Anxiety had the strongest association with CircS and was the central factor with the highest strength centrality, also the bridge with the highest bridge strength in the network.
Humans ; Male ; Female ; Adult ; China ; Middle Aged ; Life Style ; Chronobiology Disorders/epidemiology*

Objective:To investigate the relationship between symptoms of vertigo and vestibular functions and short-term hearing outcomes in patients with flat descending sudden sensorineural hearing loss （SSNHL）. Methods:A retrospective review was conducted of the vestibular symptoms observed in 48 patients with unilateral flat-down sudden sensorineural hearing loss treated at the Department of Otolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine. Symptoms of vertigo and the results of cervical vestibular-evoked myogenic potentials （cVEMP）, ocular VEMP （oVEMP）, caloric test and video head-impulse test （vHIT） were collected to determine whether these factors could predict therapeutic efficacy. Results:The symptoms of vertigo was not correlated with prognosis （P>0.05） or with abnormal vestibular functions （P>0.05）. Patients with abnormal cVEMP, oVEMP, caloric test or vHIT showed significantly lower effective rates （32.0%, 44.0%, 32.0%, and 24.0%, respectively）; the greater the number of abnormal tests, the poorer the outcome. Patients with all four tests abnormal gained only （3.13±15.97） dB HL in hearing recovery, whereas those with normal cVEMP, oVEMP, caloric test or vHIT showed better chances of hearing improvements by （29.22±20.31）, （31.18±21.59）, （26.17±21.31）, and （26.38±24.05） dB HL, respectively. Conclusion:Vestibular function effectively predicts prognosis in flat descending SSNHL. Patients with abnormal vestibular tests, regardless of symptoms of vertigo, responded poorly to treatment, whereas those with normal cVEMP, oVEMP, caloric test and vHIT results achieved better hearing recovery. Abnormal vestibular function implies more extensive and severe inner-ear lesions in patients with SSNHL.
Humans ; Male ; Female ; Retrospective Studies ; Prognosis ; Adult ; Middle Aged ; Vertigo/diagnosis* ; Hearing Loss, Sensorineural/diagnosis* ; Young Adult ; Hearing Loss, Sudden/diagnosis* ; Adolescent ; Aged ; Vestibular Evoked Myogenic Potentials

The rapid screening of bioactive constituents within traditional Chinese medicine (TCM) presents a significant challenge to researchers. Prevailing strategies for the screening of active components in TCM often overlook trace components owing to their concealment by more abundant constituents. To address this limitation, a fishing strategy based on offline two-dimensional liquid chromatography (2D-LC) combined with surface plasmon resonance (SPR) was utilized to screen bioactive trace components targeting peroxiredoxin 3 (PRDX3), using Uncaria alkaloids (UAs) as a case study. Initially, an orthogonal preparative offline 2D-LC system combining a positively charged C₁₈ column and a conventional C₁₈ column under disparate mobile phase conditions was constructed. To fully reveal the trace alkaloids, 13 2D fractions of UAs were prepared, and their components were characterized using mass spectrometry (MS). Subsequently, employing PRDX3 as the targeting protein, a SPR-based screening approach was established and rigorously validated with geissoschizine methyl ether (GSM) serving as a positive control for binding. Employing this refined strategy, 29 candidate binding alkaloids were fished from the 13 2D fractions. Notably, combining offline 2D-LC with SPR increased the yield of candidate binding components from 10 to 29 when compared to SPR-based screening alone. Subsequent binding affinity assays confirmed that PRDX3 was a direct binding target for the 12 fished alkaloids, with isovallesiachotamine (IV), corynoxeine N-oxide (CO-N), and cadambine (CAD) demonstrating the highest affinity for PRDX3. Their interactions were further validated through molecular docking analysis. Subsequent intracellular H₂O₂ measurement assays and transfection experiments confirmed that these three trace alkaloids enhanced PRDX3-mediated H₂O₂ clearance. In conclusion, this study introduced an innovative strategy for the identification of active trace components in TCM. This approach holds promise for accelerating research on medicinal components within this field.

Objective To summarise and analyse the qualitative studies on the factors that influence patient involvement in decision-making for the initial administration of insulin for the patients with Type II diabetes,from the perspectives of patients and healthcare staff in order to provide a reference to promote patient involvement in decision-making.Methods Systematic searches were conducted across databases,such as CINAHL,Cochrane Library,EMBASE,PubMed,Web of Science,PsycINFO,China National Knowledge Infrastructure(CNKI),Wanfang Data,VIP,and SinoMed,for qualitative studies on the factors that affect patient involvement in initial insulin decision-making for the patients with Type II diabetes.The search was limited to articles from the inception of the databases to 30th September,2023.Quality of the included studies was assessed using the Joanna Briggs Institute(JBI)evidence-based healthcare centre for qualitative research quality assessment tool.The results were integrated using a synthesising integration method.Results A total of 19 articles were included,yielding 20 study results,which were categorised into 7 themes of patient decision-making related values,patient role preferences in decision-making,condition of patient,the role of healthcare staff in patient participation in decision-making,professional quality of healthcare staff,relationship between patient and healthcare staff,and the support from a medical institution.The data were ultimately integrated into 4 overarching themes of patient personal factors,healthcare staff factors,patient-staff interaction factors and medical institution factors.Conclusion The involvement of the patients with Type II diabetes in the decision-making for the initial administration of insulin is influenced by patients themselves,healthcare staff and medical institutions.It requires efforts of multiple parties:not only with the patients actively participate in decision-making,but also with the healthcare staff and institutions who provide effective decision supports.

The role of photoplethysmography(PPG)in the functional assessment of the cardiovascular system at home and abroad was summarized to provide theoretical references and lessons for the medical application of PPG and innovative research.Currently,functional assessment indices such as heart rate,heart rhythm,blood pressure,and volume can be analyzed from PPG signals,which can also assist in identifying and diagnosing abnormal blood pressure,diabetes mellitus,cardiac arrhythmia,sleep apnea syndrome,early ischemic shock,and other diseases.However,the accuracy and precision of PPG,data interpretation and standardization,waveform analysis,and clinical applications remain controversial.PPG has been widely used in medical and scientific research to effectively assess the functional status of the cardiovascular system and assist in diagnosing various diseases.In the future,PPG is expected to show a multipath development trend in high-precision,multi-parameter,noncontact,remote monitoring,and medical treatment.

Alzheimer''s disease (AD) has brought to us huge medical and economic burdens, and so discovery of its therapeutic drugs is of great significance.In this paper, we utilized knowledge graph embedding (KGE) models to explore drug repurposing for AD on the publicly available drug repurposing knowledge graph (DRKG).Specifically, we applied four KGE models, namely TransE, DistMult, ComplEx, and RotatE, to learn the embedding vectors of entities and relations on DRKG.By using three classical knowledge graph evaluation metrics, we then evaluated and compared the performance of these models as well as the quality of the learned embedded vectors.Based on our results, we selected the RotatE model for link prediction and identified 16 drugs that might be repurposed for the treatment of AD.Previous studies have confirmed the potential therapeutic effects of 12 drugs against AD, i.e., glutathione, haloperidol, capsaicin, quercetin, estradiol, glucose, disulfire, adenosine, paroxetine, paclitaxel, glybride and amitriptyline.Our study demonstrates that drug repurposing based on KGE may provide new ideas and methods for AD drug discovery.Moreover, the RotatE model effectively integrates multi-source information of DRKG, enabling promising AD drug repurposing.The source code of this paper is available at https://github.com/LuYF-Lemon-love/AD-KGE.

BACKGROUND/OBJECTIVES: Weight loss via a mobile application (App) or a paper-based diary (Paper) may confer favorable metabolic and anthropometric changes. SUBJECTS/METHODS: A randomized parallel trial was conducted among 57 adults whose body mass indices (BMIs) were 25 kg/m 2 or greater. Participants randomly assigned to either the App group (n = 30) or the Paper group (n = 27) were advised to record their foods and supplements through App or Paper during the 12-week intervention period. Relative changes of anthropometries and biomarker levels were compared between the 2 intervention groups.Untargeted metabolic profiling was identified to discriminate metabolic profiles. RESULTS: Out of the 57 participants, 54 participants completed the trial. Changes in body weight and BMI were not significantly different between the 2 groups (P = 0.11). However, body fat and low-density lipoprotein (LDL)-cholesterol levels increased in the App group but decreased in the Paper group, and the difference was statistically significant (P = 0.03 for body fat and 0.02 for LDL-cholesterol). In the metabolomics analysis, decreases in methylglyoxal and (S)-malate in pyruvate metabolism and phosphatidylcholine (lecithin) in linoleic acid metabolism from pre- to post-intervention were observed in the Paper group. CONCLUSIONS In the 12-week randomized parallel trial of weight loss through a App or a Paper, we found no significant difference in change in BMI or weight between the App and Paper groups, but improvement in body fatness and LDL-cholesterol levels only in the Paper group under the circumstances with minimal contact by dietitians or health care providers.Trial Registration: Clinical Research Information Service Identifier: KCT0004226

Purpose To preliminarily establish a predictive model for assessing preterm birth in the first trimester via clinical history and multiple ultrasound parameters.Materials and Methods This study included 200 women in the first trimester of pregnancy from 6 to 8 weeks in the Affiliated Renhe Hospital of Three Gorges University from September 2020 to September 2021,and their clinical history,two-dimensional imaging data and cervical elastography data were collected.Logistic regression analysis,screening and assignment were performed to initially establish a clinical prediction model for evaluating preterm birth during the first trimester.Results Finally,41 pregnant women developed preterm birth(preterm birth group),and 159 pregnant women did not develop preterm birth(term group).History of miscarriage,history of preterm birth,uterocervical angle(UCA),A,and A1 were the independent risk factors for preterm birth via univariate analysis,and multivariate analysis was carried out to obtain the formula:Logit(P)=1.495×abortion history+1.060×A1+0.795×UCA+1.354×A-14.951,which had a good fit via Hosmer-Lemeshow goodness-of-fit test,and the diagnostic efficiency was 96.9%.Conclusion The early pregnancy prediction model can effectively predict the occurrence of preterm birth in pregnant women with singleton pregnancy.

Adult ; Atherosclerosis ; Cardiovascular Diseases ; China ; Habits ; Humans ; Lipids