Implementation of gas chromatography tandem mass spectrometry for the analysis of six high boiling point polyhydric alcohols in cosmetics and toothpaste based on precolumn derivatization.

Based on precolumn derivatization, an analytical method has been developed for the determination of six high boiling point polyhydric alcohols (HBPAs, b.p. > 300 ℃) in cosmetics and toothpaste, including erythritol, xylitol, Pro-Xylane-S, inositol, mannitol, and sorbitol. The water dispersion and oil in water samples were extracted by distilled water. The water in oil sample was firstly pre-dispersed with acetone, and then extracted by distilled water. The extract was concentrated to dry under nitrogen, and derivatized with acetic anhydride under the dispersion and catalysis of anhydrous pyridine. The derivatives were detected by gas chromatography-tandem mass spectrometry in the selected reaction monitoring mode, and quantified using arabinitol as internal standard. The experimental conditions such as the selection of columns, extraction procedures, and derivative conditions were optimized. This method was properly validated under the optimized conditions, and obtained excellent analytical features. Specifically, the correlation coefficients in the range of 0.02 ∼ 0.5 mg/L all exceed 0.992. The method limits of detection and quantification were 0.25 and 0.8 mg/kg, respectively. The average recoveries in toothpaste, cosmetics with oil in water and water in oil were 81.8 ∼ 107.1 %, with the relative standard deviation were 3.1 ∼ 7.2 %. The established method was successfully applied to commercial samples of different matrices, showing the advantages of simplicity, sensitivity, and good reproducibility, and can be used for the determination of HBPAs in cosmetics and toothpaste. The proposed methodology solves the problem that there is no detection method for HBPAs in cosmetics.

Advances in the transport of oral nanoparticles in gastrointestinal tract.

Biological barriers in the gastrointestinal tract (GIT) prevent oral absorption of insoluble drugs. Recently, significant progress has been made in the development of various nanoparticles (NPs) designed to enhance the efficacy of oral drugs. However, the mechanism underlying the intracellular transport of NPs remains unclear, and there are still limitations to improving the oral bioavailability of drugs. This article reviews the challenges faced in the absorption of oral NPs, proposes strategies to overcome these barriers, and discusses the future prospects.

Tryptophan Metabolism Disorder-Triggered Diseases, Mechanisms, and Therapeutic Strategies: A Scientometric Review.

BACKGROUND: Tryptophan is widely present in foods such as peanuts, milk, and bananas, playing a crucial role in maintaining metabolic homeostasis in health and disease. Tryptophan metabolism is involved in the development and progression of immune, nervous, and digestive system diseases. Although some excellent reviews on tryptophan metabolism exist, there has been no systematic scientometric study as of yet. METHODS: This review provides and summarizes research hotspots and potential future directions by analyzing annual publications, topics, keywords, and highly cited papers sourced from Web of Science spanning 1964 to 2022. RESULTS: This review provides a scientometric overview of tryptophan metabolism disorder-triggered diseases, mechanisms, and therapeutic strategies. CONCLUSIONS: The gut microbiota regulates gut permeability, inflammation, and host immunity by directly converting tryptophan to indole and its derivatives. Gut microbial metabolites regulate tryptophan metabolism by activating specific receptors or enzymes. Additionally, the kynurenine (KYN) pathway, activated by indoleamine-2, 3-dioxygenase (IDO) and tryptophan 2, 3-dioxygenase, affects the migration and invasion of glioma cells and the development of COVID-19 and depression. The research and development of IDO inhibitors help to improve the effectiveness of immunotherapy. Tryptophan metabolites as potential markers are used for disease therapy, guiding clinical decision-making. Tryptophan metabolites serve as targets to provide a new promising strategy for neuroprotective/neurotoxic imbalance affecting brain structure and function. In summary, this review provides valuable guidance for the basic research and clinical application of tryptophan metabolism.

Gender differences in the mental symptom network of high school students in Shanghai, China: a network analysis.

BACKGROUND: Adolescence is a critical period for the onset of mental health issues. In China, high school students face significant academic and social pressures, leading to high rates of mental health challenges. Gender differences in the manifestation of these symptoms have been observed, with boys and girls exhibiting distinct psychological profiles. OBJECTIVE: This study aims to explore the structure of psychological symptoms among Chinese high school students using network analysis, focusing on identifying core symptoms and gender differences in symptom networks. The key objectives are to: 1) identify the central psychological symptoms for boys and girls, and 2) uncover the interactions between symptoms to inform targeted interventions. METHODS: A cluster sampling method was used to recruit 3,769 high school students (2,206 males and 1,563 females) in Shanghai. The Middle School Students Mental Health Scale (MSSMHS) was administered, and network analysis was conducted using the R packages bootnet and qgraph to assess symptom network edges, centrality, and network strength. Comparisons between male and female networks were made. RESULTS: Network analysis showed tightly connected symptom networks for both genders, with 43 non-zero edges for boys (sparsity 0.04) and 39 for girls (sparsity 0.13). Depression was the core symptom for boys (centrality 1.20), while anxiety was central for girls (centrality 1.46). Boys showed a stronger link between interpersonal sensitivity and depression (edge value 0.20), while girls exhibited a stronger connection between anxiety and obsessive-compulsive symptoms (edge value 0.16). Network comparison tests revealed no significant differences in overall network strength between boys (4.625) and girls (4.660), with P-values greater than 0.05 across all comparisons. CONCLUSION: This study highlights significant gender differences in the psychological symptom networks of Chinese high school students. Depression and anxiety emerged as core symptoms for boys and girls, respectively. These findings provide a foundation for developing gender-sensitive mental health interventions, emphasizing the need for tailored approaches based on gender-specific symptom profiles.

Enhancing laboratory biosafety management: a comprehensive strategy from theory to practice.

Objective: This study examines biosafety management practices in a psychiatric hospital's laboratory in China, focusing on how outdated information technology impacts the hospital's ability to respond to public health emergencies. The goal is to enhance the hospital's emergency response capabilities by updating risk assessments, biosafety manuals, and implementing a comprehensive quality management system alongside a specialized infection control system for significant respiratory diseases. Methods: We utilized an integrated research approach, expanding the scope of risk assessments, updating the biosafety manual according to the latest international standards, and implementing a quality management system. A specialized infection control system for significant respiratory diseases was introduced to improve emergency response capabilities. Results: Updated risk assessments and a new biosafety manual have significantly improved the identification and management of biosafety threats. Implementing new quality management and infection control systems has enhanced response efficiency and operational standardization. Conclusion: The measures taken have strengthened the biosafety management and emergency response capabilities of the laboratory department, highlighting the importance of information technology in biosafety management and recommending similar strategies for other institutions.

Cimicifuga heracleifolia kom. Attenuates ulcerative colitis through the PI3K/AKT/NF-κB signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Cimicifuga heracleifolia Kom. (C. heracleifolia) has demonstrated efficacy in treating gastrointestinal disorders, including splenasthenic diarrhea. Ulcerative colitis (UC), a chronic inflammatory bowel disease, shares similarities with splenasthenic diarrhea. However, the pharmacological effects of C. heracleifolia on UC and the underlying mechanisms remain unexplored. AIM OF THE STUDY: The present study investigates the therapeutic potential and mechanisms of C. heracleifolia in UC. METHODS: Initially, network pharmacology analysis, encompassing ingredient screening, target prediction, protein-protein interaction (PPI) network analysis, and enrichment analysis, was employed to predict the mechanisms of C. heracleifolia. The findings were further validated using transcriptomics and functional assays in a dextran sulfate sodium (DSS)-induced UC model. Additionally, bioactive compounds were identified through surface plasmon resonance (SPR) analysis, molecular docking, and cell-based assays. RESULTS: A total of 52 ingredients of C. heracleifolia were screened, and 32 key targets were identified within a PPI network comprising 285 potential therapeutic targets. Enrichment analysis indicated that the anti-UC effects of C. heracleifolia are mediated through immune response modulation and the inhibition of inflammatory signaling pathways. In vivo experiments showed that C. heracleifolia mitigated histological damage in the colon, reduced the expression of phosphorylated Akt1, nuclear factor-kappa B (NF-κB) p65, and inhibitor of Kappa B kinase α/ß (IKKα/ß), suppressed the content of interleukin-1ß (IL-1ß), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α), and enhanced the expression of tight junction proteins. Moreover, cimigenoside, caffeic acid, and methyl caffeate were identified as the bioactive constituents responsible for the UC treatment effects of C. heracleifolia. CONCLUSIONS: In summary, this study is the first to demonstrate that C. heracleifolia exerts therapeutic effects on UC by enhancing the intestinal mucosal barrier and inhibiting the phosphatidylinositol 3-kinase (PI3K)/AKT/NF-κB signaling pathway. These findings offer valuable insights into the clinical application of C. heracleifolia for UC management.

An indirect treatment comparison meta-analysis of digital versus face-to-face cognitive behavior therapy for headache.

Cognitive behavioral therapy (CBT) is effective for headache disorders. However, it is unclear whether the emerging digital CBT is noninferior to face-to-face CBT. An indirect treatment comparison (ITC) meta-analysis was conducted to assess the relative effects between them using standard mean differences (SMDs). Effective sample size (ESS) and required sample size (RSS) were calculated to demonstrate the robustness of the results. Our study found that digital CBT had a similar effect on headache frequency reduction (SMD, 0.12; 95%CI, -2.45 to 2.63) compared with face-to-face CBT. The ESS had 84 participants, while the RSS had 466 participants to achieve the same power as a non-inferior head-to-head trial. Digital CBT is as effective as face-to-face CBT in preventing headache disorders. Due to the heterogeneity (I2 = 94.5%, τ2 = 1.83) and the fact that most of the included studies were on migraine prevention, further head-to-head trials are warranted.

Analysis of international publication trends in artificial intelligence in skin cancer.

Bibliometric methods were used to analyze publications on artificial intelligence in skin cancer from 2010 to 2022, aiming to explore current publication trends and future directions. A comprehensive search using four terms - "artificial intelligence," "machine learning," "deep learning," and "skin cancer" was performed in the Web of Science database for original English-language publications on artificial intelligence in skin cancer from 2010 to 2022. We visually analyzed publication, citation, and coupling information, focusing on authors, countries and regions, publishing journals, institutions, and core keywords. The analysis of 989 publications revealed a consistent year-on-year increase in publications from 2010 to 2022 (0.51% vs. 33.57%). The USA, India, and China emerged as the leading contributors. IEEE Access was identified as the most prolific journal in this area. Key journals and influential authors were highlighted. Examination of the top 10 most cited publications highlights the significant potential of AI in oncology. Co-citation network analysis identified four primary categories of classical literature on AI in skin tumors. Keyword analysis indicated that "melanoma," "classification," and "deep learning" were the most prevalent keywords, suggesting that deep learning for melanoma diagnosis and grading is the current research focus. The term "pigmented skin lesions" showed the strongest burst and longest duration, while "texture" was the latest emerging keyword. AI represents a rapidly growing area of research in skin cancer with the potential to significantly improve skin cancer management. Future research is likely to focus on machine learning and deep learning technologies for screening and diagnostic purposes.

Biomedical potentials of alginate via physical, chemical, and biological modifications.

Alginate is a linear polysaccharide with a modifiable structure and abundant functional groups, offers immense potential for tailoring diverse alginate-based materials to meet the demands of biomedical applications. Given the advancements in modification techniques, it is significant to analyze and summarize the modification of alginate by physical, chemical and biological methods. These approaches provide plentiful information on the preparation, characterization and application of alginate-based materials. Physical modification generally involves blending and physical crosslinking, while chemical modification relies on chemical reactions, mainly including acylation, sulfation, phosphorylation, carbodiimide coupling, nucleophilic substitution, graft copolymerization, terminal modification, and degradation. Chemical modified alginate contains chemically crosslinked alginate, grafted alginate and oligo-alginate. Biological modification associated with various enzymes to realize the hydrolysis or grafting. These diverse modifications hold great promise in fully harnessing the potential of alginate for its burgeoning biomedical applications in the future. In summary, this review provides a comprehensive discussion and summary of different modification methods applied to improve the properties of alginate while expanding its biomedical potentials.

Genetic Characterization, Antibiotic Resistance, and Virulence Genes Profiling of Bacillus cereus Strains from Various Foods in Japan.

Bacillus cereus sensu stricto is a foodborne pathogen that causes food poisoning. Their spore and biofilm-forming abilities persist in various environments and foods. This study investigated the prevalence, virulence, antibiotic resistance, and genetic diversity of B. cereus s. s. strains isolated from various food samples. Of 179 samples, 22.34% were positive for B. cereus s. s., with significantly high detection rates in milk products and raw chicken meat. Forty strains were isolated from positive samples. Matrix-assisted laser desorption ionization/time of flight mass spectrometry analysis revealed nine distinct clusters and multi-locus sequence typing revealed 34 sequence types including 23 novel sequences, demonstrating high genetic diversity among the isolates. PCR analysis revealed that all the strains contained at least one toxin gene, but none contained the cytK gene. Antibiotic resistance tests revealed that all isolates were classified as multidrug-resistant, with high resistance levels, particularly to ß-lactam antibiotics and vancomycin, but were susceptible to gentamicin. All isolates showed variations in biofilm formation. This study highlights the significant public health risk due to B. cereus s. s. and underscores the need for stringent monitoring and control measures in food production to manage antimicrobial resistance and ensure food safety.

Use of vaginal dinoprostone for women with term prelabor rupture of membranes and an unfavorable cervix within 6 h versus within 6-24 h.

BACKGROUND: Most guidelines propose inducing labor within 24 h following term (37 or more weeks of gestation) prelabor rupture of membranes (PROM). However, the exact timing for initiating induction within the 24 h period remains unknown. This study aims to comparatively assess the efficacy and safety of the use of vaginal dinoprostone within 6 h versus within 6-24 h for singleton pregnancies with PROM and an unfavorable cervix (Bishop score < 6). METHODS: This was a retrospective cohort study including singleton pregnancies with PROM and an unfavorable cervix (Bishop score < 6) in which labor was induced using vaginal dinoprostone. Women were divided into two groups according to the timing of the use of induction (within 6 h versus within 6-24 h after PROM). Baseline maternal data, maternal and neonatal outcomes were recorded for statistical analysis. RESULTS: 450 women were included, 146 (32.4%) of whom were induced within 6 h of PROM and 304 (67.6%) were induced within 6-24 h. Cesarean delivery rate (15.8% versus 29.3%, p = 0.002) and nonreassuring fetal heart rate tracing (4.8% versus 10.5%, p = 0.043) in group with vaginal dinoprostone within 6 h were significantly lower than those in group with vaginal dinoprostone within 6-24 h. There was no significant differences in terms of duration from IOL to vaginal delivery. CONCLUSION: Induction of labor within 6 h with vaginal dinoprostone after PROM for singleton pregnancies with an unfavorable cervix (Bishop score < 6) significantly associated with less cesarean section, less nonreassuring fetal heart rate tracing, compared to induction of labor within 6-24 h after PROM.

Content Determination and Chemical Clustering Analysis of Tanshinone and Salvianolic Acid in Salvia spp.

Salvia miltiorrhiza is one of the famous traditional Chinese medicines for treating cardiovascular and cerebrovascular diseases. Tanshinone and phenolic acids are the main active compounds of Salvia miltiorrhiza, whereas the distribution patterns of the two kinds of components are still unclear among Salvia spp. In this work, high-performance liquid chromatography was applied to analyze the distribution patterns of major components in the roots and leaves of 58 Salvia spp. The results showed that the distribution patterns of tanshinone and phenolic acids in Salvia spp. varied significantly. Phenolic acid components such as rosmarinus acid, caffeic acid, and danshensu are widely distributed in the roots and leaves, and phenolic acids in the leaves of Salvia spp. are generally higher than that in roots. Tanshinones are mainly detected in the roots of Salvia przewalskii, Salvia trijuga, Salvia castanea, and Salvia yunnanensis. The content of major components of the different species varied significantly. The content of phenolic acids in most Salvia spp. generally followed the pattern of salvianolic acid B > rosmarinic acid > danshensu > caffeic acid both in the roots and leaves. Tanshinone IIA and cryptotanshinone were the main lipophilic components of Salvia spp. distributed in southwest China. A correlation between the distribution pattern of tanshinone and the genetic relationship of species was indicated in the work. This research systematically reveals the distribution patterns of tanshinone and phenolic acids in Salvia spp., providing a theoretical basis for the development and utilization of medicinal resources of Salvia.

Preparation and Evaluation of Clarithromycin Taste-Masking Dry Suspension Using Hot Melt Extrusion Based on Solid Dispersion Technology.

Clarithromycin (CLA) is the preferred drug for treating respiratory infections in pediatric patients, but it has the drawbacks of extreme bitterness and poor water solubility. The purpose of this study was to improve solubility and mask the extreme bitterness of CLA. We use Hot Melt Extrusion (HME) to convert CLA and Eudragit® E100 into Solid Dispersion (SD). Differential scanning calorimetry (DSC) and Powder X-ray diffraction (PXRD) were used to identify the crystalline form of the prepared SDs, which showed that the crystalline CLA was converted to an amorphous form. At the same time, an increase in dissolution rate was observed, which is one of the properties of SD. The results showed that the prepared SD significantly increased the dissolution rate of crystalline CLA. Subsequently, the SD of CLA was prepared into a dry suspension with excellent suspending properties and a taste-masking effect. The bitterness bubble chart and taste radar chart showed that the SD achieved the bitter taste masking of CLA. Principal components analysis (PCA) of the data generated by the electronic tongue showed that the bitter taste of CLA was significantly suppressed using the polymer Eudragit® E100. Subsequently, a dry suspension was prepared from the SD of CLA. In conclusion, this work illustrated the importance of HME for preparing amorphous SD of CLA, which can solve the problems of bitterness-masking and poor solubility. It is also significant for the development of compliant pediatric formulations.

A risk prediction model of gestational diabetes mellitus based on traditional and genetic factors.

BACKGROUND: Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication during pregnancy. We aimed to evaluate a risk prediction model of GDM based on traditional and genetic factors. METHODS: A total of 2744 eligible pregnant women were included. Face-to-face questionnaire surveys were conducted to gather general data. Serum test results were collected from the laboratory information system. Independent risk factors for GDM were identified using univariate and multivariate logistic regression analyses. A GDM risk prediction model was constructed and evaluated with the Hosmer-Lemeshow goodness-of-fit test, goodness-of-fit calibration plot, receiver operating characteristic curve and area under the curve. RESULTS: Among traditional factors, age ≥30 years, family history, GDM history, impaired glucose tolerance history, systolic blood pressure ≥116.22 mmHg, diastolic blood pressure ≥74.52 mmHg, fasting plasma glucose ≥5.0 mmol/L, 1-hour postprandial blood glucose ≥8.8 mmol/L, 2-h postprandial blood glucose ≥7.9 mmol/L, total cholesterol ≥4.50 mmol/L, low-density lipoprotein ≥2.09 mmol/L and insulin ≥11.5 mIU/L were independent risk factors for GDM. Among genetic factors, 11 single nucleotide polymorphisms (SNPs) (rs2779116, rs5215, rs11605924, rs7072268, rs7172432, rs10811661, rs2191349, rs10830963, rs174550, rs13266634 and rs11071657) were identified as potential predictors of the risk of postpartum DM among women with GDM history, collectively accounting for 3.6% of the genetic risk. CONCLUSIONS: Both genetic and traditional factors contribute to the risk of GDM in women, operating through diverse mechanisms. Strengthening the risk prediction of SNPs for postpartum DM among women with GDM history is crucial for maternal and child health protection.

We aimed to evaluate a risk prediction model of gestational diabetes mellitus (GDM) based on traditional and genetic factors. A total of 2744 eligible pregnant women were included. Face-to-face questionnaire surveys were conducted to collect general data. Among traditional factors, age ≥30 years old, family history, GDM history, impaired glucose tolerance history, systolic blood pressure ≥116.22 mmHg, diastolic blood pressure ≥74.52 mmHg, fasting plasma glucose ≥5.0 mmol/L, 1-hour postprandial blood glucose ≥8.8 mmol/L, 2-h postprandial blood glucose ≥7.9 mmol/L, total cholesterol ≥4.50 mmol/L, low-density lipoprotein ≥2.09 mmol/L and insulin ≥11.5 mIU/L were independent risk factors for GDM. Among genetic factors, 11 single nucleotide polymorphisms were identified as potential predictors of the risk of postpartum DM among women with GDM history, collectively accounting for 3.6% of the genetic risk. Both genetic and traditional factors increase the risk of GDM in women.

CCDC189 depletion leads to oligo-astheno-teratozoospermia and male infertility in mice†.

In male reproductive system, proteins containing the coiled-coil domain (CCDC) are predominantly expressed in specific regions including the testis, epididymis, seminal vesicle, and prostate. They play a vital role in centriole formation, sperm motility and flagellar development in male gametes. Despite being highly expressed in the testis, the exact physiological function of the coiled-coil domain-containing 189 (Ccdc189) gene remain largely unclear. Our research provides a comprehensive and detailed investigation into the localization of CCDC189 protein within the testis seminiferous tubules. CCDC189 specifically expressed in spermatocytes, round spermatids, and elongating spermatids in mouse testis. The deletion of Ccdc189 in mouse leads to male infertility, characterized by significantly reduced sperm counts and motility. Abnormally shaped spermatozoa with irregular tails, exhibiting shortened and twisted morphology, were observed in the seminiferous tubules. Electron microscopy revealed disordered and missing peripheral microtubule doublets (MTD) and outer dense fibers (ODF) in the sperm flagella, accompanied by a consistent absence of central pairs (CP). The knockout of Ccdc189 resulted in oligo-astheno-teratozoospermia, which is characterized by low sperm count and reduced sperm motility and abnormal morphology. Furthermore, we identified poly(A)-binding protein cytoplasmic 1 (PABPC1) and PABPC2 as interacting proteins with CCDC189. These proteins belong to the PABP family and are involved in regulating mRNA translational activity in spermatogenic cells by specifically binding to poly(A) tails at the 3' ends of mRNAs.

Tuber quality enhancement via grafting potato onto a wooden goji rootstock through vitalizing multi-pathways.

Grafting is applied in Solanaceae to improve growth and quality traits. However, grafting potato onto a wooden goji rootstock is rare. Our study introduces a novel distant grafting technique to investigate potato scion responses, specifically regarding photosynthetic and tuber nutritional quality. The physiological and transcriptomic findings reveal an increase in photosynthesis ratio and carbon fixation in potato leaves after 45 days of grafting due to the upregulation of pivotal genes (PsbA, PPC1, rbcl, and GAPDH). After 95 days of long-term growth, the leaf redox balance was maintained with intensified chlorophyll synthesis, facilitated by the enrichment of crucial genes (GUN4, CHLH, CHLP, CAO) and several light-harvesting proteins (Lhca and Lhcb) in potato leaves. The tubers of grafted plants showed a 6.5% increase in crude protein, 51% in anthocyanin, and lower carbohydrate content. Goji altered the expression of tubers genes involved in assimilatory sulfate reduction, which subsequently affects cysteine-methionine biosynthesis. Furthermore, the tuber transcriptome shows ABA signaling and transcription factors regulate the expression of key biosynthetic genes involved in inducing the secondary metabolites, such as scopoletin and anthocyanin accumulation, which are primary polyphenols in goji. Our innovative grafting approach offers valuable insights into the interactions between woody and herbaceous plants for developing future strategies to modulate growth efficiency and tuber quality in the face of climate challenges and to meet the demand for nutritious food.

Recurrent COVID-19-related psychotic disorder with neuro-immuno-endocrine dysfunction as a possible underlying mechanism: A case report from China.

Background: SARS-CoV-2, first identified in Wuhan, China, in December 2019, has been gradually spreading worldwide since 2020. The relationship between SARS-CoV-2 infection and psychotic disorders has received much attention, and several studies have described the direct/indirect mechanisms of its effects on the brain, but no mechanism has been found to explain recurrent episodes of COVID-19-related psychotic symptoms. Case: We report the case of an 18-year-old female patient with no family or personal psychotic disorder history with multiple hospital admissions with symptoms such as disorganized speech and behavior, hyperactivity, restlessness, and impulsive aggression during the COVID-19 recovery period. Relevant tests revealed longitudinal changes such as persistent IL-6 and IL-10 elevation, abnormal discharges on EEG, and brain and hippocampal MRI abnormal signals. The patient was treated with antipsychotics, MECT, combination therapy of hormones and antivirals, then discharged after multiple treatment rounds. Conclusion: The case presented here outlines the possibility that the COVID-19 recovery period may be a critical period for acute psychotic episodes and that the patient's recurrent psychotic symptoms may be associated with neuro-immuno-endocrine dysfunction mediated by sustained cytokine synthesis, further causing structural and functional brain damage. Routine psychiatric evaluation and related screening should be performed at all stages of the illness to better identify, prevent, and effectively intervene in psychiatric disorders following COVID-19. Because many outcomes require long-term assessment, a clearer understanding of the impact of the COVID-19 epidemic on mental health is likely to emerge in the future.

[Construction of a Predictive Model for Diabetes Mellitus Type 2 in Middle-Aged and Elderly Populations Based on the Medical Checkup Data of National Basic Public Health Service]. / åŸºäºŽå›½å®¶åŸºæœ¬å ¬å ±å«ç”ŸæœåŠ¡ä½“æ£€çš„ä¸­è€å¹´äºº2åž‹ç³–å°¿ç— é£Žé™©é¢„æµ‹æ¨¡åž‹æž„å»º.

Objective: To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2 (T2DM) in the middle-aged and elderly populations based on the results of a Meta-analysis, and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service. Methods: Cohort studies evaluating T2DM risks were identified in Chinese and English databases. The logistic model utilized Meta-combined effect values such as the odds ratio (OR) to derive ß, the partial regression coefficient, of the logistic model. The Meta-combined incidence rate of T2DM was used to obtain the parameter α of the logistic model. Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service. The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7602 individuals who did not have T2DM at their baseline medical checkups done at the community health center. This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people. Results: A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM, including age, central obesity, smoking, physical inactivity, impaired fasting glucose, a reduced level of high-density lipoprotein cholesterol (HDL-C), hypertension, body mass index (BMI), triglyceride glucose (TYG) index, and a family history of diabetes, with the OR values and 95% confidence interval (CI) being 1.04 (1.03, 1.05), 1.55 (1.29, 1.88), 1.36 (1.11, 1.66), 1.26 (1.07, 1.49), 3.93 (2.94, 5.24), 1.14 (1.06, 1.23), 1.47 (1.34, 1.61), 1.11 (1.05, 1.18), 2.15 (1.75, 2.62), and 1.66 (1.55, 1.78), respectively, and the combined ß values being 0.039, 0.438, 0.307, 0.231, 1.369, 0.131, 0.385, 0.104, 0.765, and 0.507, respectively. A total of 37 studies reported the incidence rate, with the combined incidence being 0.08 (0.07, 0.09) and the parameter α being -2.442 for the logistic model. The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7602 individuals who had medical checkups and were followed up for at least once. External validation results showed that the predictive model had an area under curve (AUC) of 0.794 (0.771, 0.816), accuracy of 74.5%, sensitivity of 71.0%, and specificity of 74.7% in the 7602 individuals. Conclusion: The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.

Effectiveness of electroacupuncture on postoperative ileus prevention after abdominal surgery: A systematic review and trial sequential analysis of randomized controlled trials.

BACKGROUND: We aimed to verify the effectiveness of electroacupuncture on postoperative ileus prevention after abdominal surgery by meta-analysis and trial sequential analysis (TSA). METHODS: From inception to May 14, 2024, PubMed, the Cochrane Library, Web of Science, and Embase databases were searched. TSA was used to determine an optimal sample size and control false-positive findings. The primary outcome was the time to first defecation (hours). RESULTS: Fourteen studies were included, with 1105 participants. Meta-analysis and TSA revealed firm evidence for benefits that electroacupuncture shorted the time to first defecation (mean difference [MD] -12.73 h, I2 = 22%, P < 0.01), the time to first flatus (MD -7.03 h, I2 = 25%, P < 0.01), the time to start of sips of water (MD -12.02 h, I2 = 0%, P < 0.01), and the time to start of liquid diet (MD -12.97 h, I2 = 0%, P < 0.01) compared with usual care. While compared with sham electroacupuncture, meta-analysis and TSA also confirmed that electroacupuncture shortened the time to first defecation (MD -10.81 h, I2 = 31%, P = 0.02) and the time to first flatus (MD -10.81 h, I2 = 0%, P < 0.01). However, TSA revealed that firm evidence for benefit or futility was not reached for the length of hospital stay and the rates of postoperative prolonged ileus. CONCLUSIONS: Electroacupuncture shortened the duration of postoperative ileus in patients undergoing abdominal surgery, and the adverse events related to electroacupuncture were minor. Further investigation of the effect of electroacupuncture on the risk of prolonged postoperative ileus is warranted in the future.

A Beginner's Guide to Artificial Intelligence for Ophthalmologists.

The integration of artificial intelligence (AI) in ophthalmology has promoted the development of the discipline, offering opportunities for enhancing diagnostic accuracy, patient care, and treatment outcomes. This paper aims to provide a foundational understanding of AI applications in ophthalmology, with a focus on interpreting studies related to AI-driven diagnostics. The core of our discussion is to explore various AI methods, including deep learning (DL) frameworks for detecting and quantifying ophthalmic features in imaging data, as well as using transfer learning for effective model training in limited datasets. The paper highlights the importance of high-quality, diverse datasets for training AI models and the need for transparent reporting of methodologies to ensure reproducibility and reliability in AI studies. Furthermore, we address the clinical implications of AI diagnostics, emphasizing the balance between minimizing false negatives to avoid missed diagnoses and reducing false positives to prevent unnecessary interventions. The paper also discusses the ethical considerations and potential biases in AI models, underscoring the importance of continuous monitoring and improvement of AI systems in clinical settings. In conclusion, this paper serves as a primer for ophthalmologists seeking to understand the basics of AI in their field, guiding them through the critical aspects of interpreting AI studies and the practical considerations for integrating AI into clinical practice.