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BACKGROUND: Behavioral and emotional problems are common and often co-occur during childhood and adolescence. The aim of this study was to assess gender differences in the network structures of behavioral and emotional problems of children and adolescents in China based on a national survey. METHODS: The Parent version of Achenbach's Child Behavior Checklist (CBCL) was used to assess behavioral and emotional problems. To account for potential confounding factors between boys and girls, propensity score matching was utilized. Network model differences were assessed with a Network Comparison Test (NCT). RESULTS: Data from 60,715 children and adolescents were included for analyses. Boys exhibited more severe total behavioral and emotional problems compared to girls. While several edges showed significant differences between boys and girls, the strongest association was consistently found between "Attention problems" (CBCL6) and "Aggressive behavior"(CBCL8) in both boys and girls, regardless of age. Network centrality was higher among adolescents compared to children. The most central problems commonly found across different genders and age groups were "Aggressive behavior" (CBCL8) (centrality values were 1.142 for boys aged 6-11 years, 1.051 for boys aged 12-16 years, 1.148 for girls aged 6-11 years, and 1.028 for girls aged 12-16 years), "Anxious/depressed" (CBCL1) (centrality values of 0.892 for boys aged between 6 and 11 years, 1.031 for boys aged 12-16 years, 0.951 for girls aged 6-11 years, and 1.099 for girls aged 12-16 years) and "Social problems" (CBCL4) (centrality values of 1.080 for boys aged 6-11 years, 0.978 for boys aged 12-16 years, 1.086 for girls aged between 6 and 11 years, and 0.929 for girls aged 12-16 years). CONCLUSION: Development of interventions that address aggressive behavior, anxiety/depression, and social problems may be beneficial for reducing risk of psychopathology among children and adolescents.

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BACKGROUND: Ambient air pollution might serve as a prognostic factor for ovarian cancer (OC) survival, yet the relationships between plant-based diet indices (PDIs) and OC survival remain unclear. We aimed to investigate the associations of comprehensive air pollution and PDIs with OC survival and explored the effects of air pollution-diet interactions. METHODS: The present study encompassed 658 patients diagnosed with OC. The overall plant-based diet index (PDI), the healthful PDI (hPDI), and the unhealthful PDI (uPDI) were evaluated by a self-reported validated food frequency questionnaire. In addition, an air pollution score (APS) was formulated by summing the concentrations of particulate matter with a diameter of 2.5 microns or less, ozone, and nitrogen dioxide. Cox proportional hazard models were applied to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs). The potential interactions of APS with PDIs in relation to overall survival (OS) were assessed on both multiplicative and additive scales. RESULTS: Throughout a median follow-up of 37.60 (interquartile: 24.77-50.70) months, 123 deaths were confirmed. Comparing to the lowest tertiles, highest uPDI was associated with lower OS of OC (HR = 2.06, 95 % CI = 1.30, 3.28; P-trend < 0.01), whereas no significant associations were found between either overall PDI or hPDI and OC survival. Higher APS (HR for per interquartile range = 1.27, 95 % CI = 1.01, 1.60) was significantly associated with worse OC survival, and the association was exacerbated by adherence to uPDI. Notably, an additive interaction was identified between combined air pollution and uPDI (P < 0.005 for high APS and high uPDI). We also found that adherence to overall PDI aggravated associations of air pollution with OC survival (P-interaction = 0.006). CONCLUSIONS: Joint exposure to various ambient air pollutants was significantly associated with lower survival among patients with OC, particularly for those who predominantly consumed unhealthy plant-based foods.

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Background: Previous studies on the association between diet quality and ovarian cancer (OC) survival are limited and inconsistent. We evaluated the relationship between pre- and post-diagnosis diet quality based on the Healthy Eating Index-2020 (HEI-2020), as well as their changes and OC survival. Methods: This prospective cohort study involved 1082 patients with OC aged 18-79 years, enrolled between 2015 and 2022. Detailed dietary intake before and after diagnosis was recorded using a validated food frequency questionnaire. Deaths were ascertained until February 16th, 2023 via medical records and active follow-up. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI). Results: We included 549 OC cases with a median follow-up of 44.9 months, representing 206 total deaths. Higher HEI scores were associated with better OS (pre-diagnosis: HRT3 vs. T1 0.66, 95%CI: 0.46-0.93, HR1-SD 0.84, 95%CI: 0.73-0.96; post-diagnosis: HRT3 vs. T1 0.68, 95%CI: 0.49-0.96, HR1-SD 0.80, 95%CI: 0.69-0.92). Compared to the stable group, the group with decreased HEI scores (>3%) from pre- to post-diagnosis had worse OS (HR 1.93, 95%CI: 1.26-2.97). Conclusion: High pre- and post-diagnosis diet quality was associated with improved OC survival, whereas deterioration in diet quality after diagnosis was associated with decreased OC survival.

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BACKGROUND: Numerous meta-analyses have explored the association between the triglyceride-glucose (TyG) index and diverse health outcomes, yet the comprehensive assessment of the scope, validity, and quality of this evidence remains incomplete. Our aim was to systematically review and synthesise existing meta-analyses of TyG index and health outcomes and to assess the quality of the evidence. METHODS: A thorough search of PubMed, EMBASE, and Web of Science databases was conducted from their inception through to 8 April 2024. We assessed the quality of reviews using A Measurement Tool to Assess Systematic Reviews (AMSTAR) and the certainty of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system. This study was registered with PROSPERO (CRD: 42024518587). RESULTS: Overall, a total of 95 associations from 29 meta-analyses were included, investigating associations between TyG index and 30 health outcomes. Of these, 83 (87.4%) associations were statistically significant (P < 0.05) according to the random effects model. Based on the AMSTAR tool, 16 (55.2%) meta-analyses were high quality and none was low quality. The certainty of the evidence, assessed by the GRADE framework, showed that 6 (6.3%) associations were supported by moderate-quality evidence. When compared with the lowest category of the TyG index, the risk of contrast-induced nephropathy (CIN) [relative risk (RR) = 2.25, 95%CI 1.82, 2.77], the risk of stroke in patients with diabetes mellitus (RR = 1.26, 95%CI 1.18, 1.33) or with acute coronary syndrome disease (RR = 1.56, 95%CI 1.06, 2.28), the prognosis of coronary artery disease (CAD)-non-fatal MI (RR = 2.02, 95%CI 1.32, 3.10), and the severity of CAD including coronary artery stenosis (RR = 3.49, 95%CI 1.71, 7.12) and multi-vessel CAD (RR = 2.33, 95%CI 1.59, 3.42) increased with high TyG index. CONCLUSION: We found that the TyG index was positively associated with many diseases including the risk of CIN and stroke, the prognosis of CAD, and the severity of CAD which were supported by moderate-quality evidence. TyG index might be useful to identify people at high-risk for developing these diseases.

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BACKGROUND: Although evidence on the association between per- and polyfluoroalkyl substances (PFASs) and human health outcomes has grown exponentially, specific health outcomes and their potential associations with PFASs have not been conclusively evaluated. METHODS: We conducted a comprehensive search through the databases of PubMed, Embase, and Web of Science from inception to February 29, 2024, to identify systematic reviews with meta-analyses of observational studies examining the associations between the PFASs and multiple health outcomes. The quality of included studies was evaluated using the A Measurement Tool to Assess Systematic Reviews (AMSTAR) tool, and credibility of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. The protocol of this umbrella review (UR) had been registered in PROSPERO (CRD 42023480817). RESULTS: The UR identified 157 meta-analyses from 29 articles. Using the AMSTAR measurement tool, all articles were categorized as of moderate-to-high quality. Based on the GRADE assessment, significant associations between specific types of PFASs and low birth weight, tetanus vaccine response, and triglyceride levels showed high certainty of evidence. Moreover, moderate certainty of evidence with statistical significance was observed between PFASs and health outcomes including lower BMI z-score in infancy, poor sperm progressive motility, and decreased risk of preterm birth as well as preeclampsia. Fifty-two (33%) associations (e.g., PFASs and gestational hypertension, cardiovascular disease, etc) presented low certainty evidence. Additionally, eighty-five (55%) associations (e.g., PFASs with infertility, lipid metabolism, etc) presented very low certainty evidence. CONCLUSION: High certainty of evidence supported that certain PFASs were associated with the incidence of low birth weight, low efficiency of the tetanus vaccine, and low triglyceride levels.

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Psychiatric syndromes are common following recovery from Coronavirus Disease 2019 (COVID-19) infection. This study investigated the prevalence and the network structure of depression, insomnia, and suicidality among mental health professionals (MHPs) who recovered from COVID-19. Depression and insomnia were assessed with the Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index questionnaire (ISI7) respectively. Suicidality items comprising suicidal ideation, suicidal plan and suicidal attempt were evaluated with binary response (no/yes) items. Network analyses with Ising model were conducted to identify the central symptoms of the network and their links to suicidality. A total of 9858 COVID-19 survivors were enrolled in a survey of MHPs. The prevalence of depression and insomnia were 47.10% (95% confidence interval (CI) = 46.09-48.06%) and 36.2% (95%CI = 35.35-37.21%), respectively, while the overall prevalence of suicidality was 7.8% (95%CI = 7.31-8.37%). The key central nodes included "Distress caused by the sleep difficulties" (ISI7) (EI = 1.34), "Interference with daytime functioning" (ISI5) (EI = 1.08), and "Sleep dissatisfaction" (ISI4) (EI = 0.74). "Fatigue" (PHQ4) (Bridge EI = 1.98), "Distress caused by sleep difficulties" (ISI7) (Bridge EI = 1.71), and "Motor Disturbances" (PHQ8) (Bridge EI = 1.67) were important bridge symptoms. The flow network indicated that the edge between the nodes of "Suicidality" (SU) and "Guilt" (PHQ6) showed the strongest connection (Edge Weight= 1.17, followed by "Suicidality" (SU) - "Sad mood" (PHQ2) (Edge Weight = 0.68)). The network analysis results suggest that insomnia symptoms play a critical role in the activation of the insomnia-depression-suicidality network model of COVID-19 survivors, while suicidality is more susceptible to the influence of depressive symptoms. These findings may have implications for developing prevention and intervention strategies for mental health conditions following recovery from COVID-19.

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BACKGROUND: Depression and insomnia are common co-occurring psychiatric problems among older adults who have had strokes. Nevertheless, symptom-level relationships between these disorders remain unclear. OBJECTIVES: In this study, we compared inter-relationships of depression and insomnia symptoms with life satisfaction among older stroke patients and stroke-free peers in the United States. METHODS: The study included 1026 older adults with a history of stroke and 3074 matched controls. Data were derived from the US Health and Retirement Study. Depression, insomnia and life satisfaction were assessed. Propensity score matching was employed to identify demographically-similar groups of stroke patients and controls. Central and bridge symptoms were assessed using Expected influence (EI) and bridge EI, respectively. RESULTS: The prevalence of depression in the stroke group (25.0 %) was higher than that of controls (14.3 %, P < 0.001). In stroke group, "Feeling depressed" (CESD1; EI: 5.80), "Feeling sad" (CESD7; EI: 4.67) and "Not enjoying life" (CESD6; EI: 4.51) were the most central symptoms, while "Feeling tired in the morning" (JSS4; BEI: 1.60), "Everything was an effort" (CESD2; BEI: 1.21) and "Waking up during the night" (JSS2; BEI: 0.98) were key bridge symptoms. In controls, the most central symptoms were "Lack of happiness" (CESD4; EI: 6.45), "Feeling depressed" (CESD1; EI: 6.17), and "Feeling sad" (CESD7; EI: 6.12). Furthermore, "Feeling tired in the morning" (JSS4; BEI: 1.93), "Everything was an effort" (CESD2; BEI: 1.30), and "Waking up too early" (JSS3; BEI: 1.12) were key bridge symptoms. Life satisfaction had the most direct associations with "Not enjoying life" (CESD6) and "Feeling lonely" (CESD5) in the two groups, respectively. CONCLUSION: Older adults with stroke exhibited more severe depression and insomnia symptoms. Interventions targeting central and bridge symptoms may help to mitigate the co-occurrence of these symptoms.

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BACKGROUND: Few studies have examined the associations between pain trajectories and cognitive function in older adults. This study explored the associations between pain trajectories and different cognitive domains in older adults from a network perspective. METHODS: Data on pain trajectories were derived from the Health and Retirement Study between 2010 and 2020 using latent class growth analyses. Measurements of key cognition domains, including memory, attention, calculation, orientation and language, were included. Linear regression and network analysis were performed to evaluate the associations between different pain trajectories and cognition. RESULTS: A total of 9,551 older adults were included in this study and three trajectories of pain were identified. After controlling for the covariates, persistent severe pain trajectory was associated with poorer overall cognition, memory and calculation ability when compared to mild or non-persistent pain trajectory. In the pain and cognition network model, memory (expected influence (EI) = 0.62), language (EI = 0.58) and calculation (EI = 0.41) were the most central domains. CONCLUSIONS: Pain trajectories appeared stable over time among older adults in this study. Severity of persistent pain was an important risk factor for poor cognition, especially in relation to memory and calculation domains. Interventions targeting memory, language and calculation domains might be useful in addressing cognitive decline in older adults with persistent pain.

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OBJECTIVE: Airline pilots are members of a unique occupational group that is often confronted with sleep routine disruptions, yet relatively few studies have examined their mental health status. This study assessed the prevalence and network structure of internet addiction, depression and sleep quality problems in commercial airline pilots. METHOD: A total of 7055 airline pilots were included in analyses. Internet addiction and depression were measured with the Internet Addiction Test (IAT) and 9-item Patient Health Questionnaire (PHQ-9), respectively. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). The network model was constructed based on an Ising model and its association with sleep quality was evaluated using a flow procedure. RESULTS: Internet addiction, depression and sleep quality were common among airline pilots. The prevalence of internet addiction was 8.0 % (95 % CI: 7.3-8.6 %), while the rates of depression and poor sleep quality were 23.3 % (95 % CI: 22.3-24.2 %) and 33.0 % (95 % CI: 31.9-34.1 %), respectively. In the depression and internet addiction network model, "Fatigue" (PHQ4; Expected Influence (EI): 2.04) and "Depressed/moody/nervous only while being offline" (IAT20; EI: 1.76) were most central symptoms while "Fatigue" (PHQ4; Bridge EI: 1.30) was also the most important bridge symptom. The flow network model of sleep quality with internet addiction and depression showed that "Appetite" (PHQ5) had the strongest positive association with poor sleep quality. CONCLUSION: Internet addiction, depression and sleep quality were common among airline pilots and warrant regular screening and timely treatment. Strategies to improve sleep hygiene may be useful in preventing onsets or exacerbations in depression and internet addiction among airline pilots.

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OBJECTIVES: Depression and loneliness co-occur frequently. This study examined interactive changes between depression and loneliness among older adults prior to and during the COVID-19 pandemic from a longitudinal network perspective. METHODS: This network study was based on data from three waves (2016-2017, 2018-2019, and 2020) of the English Longitudinal Study of Ageing (ELSA). Depression and loneliness were measured with the eight-item version of the Center for Epidemiologic Studies Depression Scale (CESD-8) and three item version of the University of California Los Angeles (UCLA) Loneliness Scale, respectively. A network model was constructed using an Ising Model while network differences were assessed using a Network Comparison Test. Central symptoms were identified via Expected Influence (EI). RESULTS: A total of 4,293 older adults were included in this study. The prevalence and network of depression and loneliness did not change significantly between the baseline and pre-pandemic assessments but increased significantly from the pre-pandemic assessment to during COVID-19 assessment. The central symptom with the strongest increase from pre-pandemic to pandemic assessments was "Inability to get going" (CESD8) and the edge with the highest increase across depression-loneliness symptom communities was "Lack companionship" (UCLA1) - "Inability to get going" (CESD8). Finally, "Feeling depressed" (CESD1) and "Everything was an effort" (CESD2) were the most central symptoms over the three assessment periods. CONCLUSIONS: The COVID-19 pandemic was associated with significant changes in the depression-loneliness network model. The most changed symptoms and edges could be treatment targets for reducing the risk of depression and loneliness in older adults.

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Platinum-based chemotherapy remains one of the major choices for treatment of ovarian cancer (OC). However, primary or acquired drug resistance severely impairs their efficiency, thereby causing chemotherapy failure and poor prognosis. SH3 domain containing ring finger 2 (SH3RF2) has been linked to the development of cancer. Here we find higher levels of SH3RF2 in the tumor tissues from cisplatin-resistant OC patients when compared to those from cisplatin-sensitive patients. Similarly, cisplatin-resistant OC cells also express higher levels of SH3RF2 than normal OC cells. Through in vitro and in vivo loss-of-function experiments, SH3RF2 is identified as a driver of cisplatin resistance, as evidenced by increases in cisplatin-induced cell apoptosis and DNA damage and decreases in cell proliferation induced by SH3RF2 depletion. Mechanistically, SH3RF2 can directly bind to the RNA-binding protein mRNA processing factor (RBPMS). RBPMS has been reported as an inhibitor of cisplatin resistance in OC. As a E3 ligase, SH3RF2 promotes the K48-linked ubiquitination of RBPMS to increase its proteasomal degradation and activator protein 1 (AP-1) transactivation. Impairments in RBPMS function reverse the inhibitory effect of SH3RF2 depletion on cisplatin resistance. Collectively, the SH3RF2-RBPMS-AP-1 axis is an important regulator in cisplatin resistance and inhibition of SH3RF2 may be a potential target in preventing cisplatin resistance.

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The unique properties of ionic liquids (ILs), such as structural tunability, good solubility, chemical/thermal stability, favorable biocompatibility, and simplicity of preparation, have led to a wide range of applications in the pharmaceutical and biomedical fields. ILs can not only speed up the chemical reaction process, improve the yield, and reduce environmental pollution but also improve many problems in the field of medicine, such as the poor drug solubility, product crystal instability, poor biological activity, and low drug delivery efficiency. This paper presents a systematic and concise analysis of the recent advancements and further applications of ILs in the pharmaceutical field from the aspects of drug synthesis, drug analysis, drug solubilization, and drug crystal engineering. Additionally, it explores the biomedical field, covering aspects such as drug carriers, stabilization of proteins, antimicrobials, and bioactive ionic liquids.

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OBJECTIVES: The Coronavirus Disease 2019 (COVID-19) pandemic and the containment measures for COVID-19 have affected sleep quality in the population. This study explored sleep-related research from a bibliometric perspective to provide an overview of the research outputs in this field. METHODS: Original and review articles were retrieved from the Web of Science Core Collection (WOSCC) database from December 2019 to 7 Aug 2023. R package "bibliometrix" was used to summarize the number of articles of authors, institutions, and countries; count the citations of the articles, and generate a Three-Fields Plot. VOSviewer software was applied to visualize the collaboration network among authors and institutions, and to conduct a co-occurrence analysis of keywords. RESULTS: A total of 4,499 articles on COVID-19 and sleep, and 25,883 articles on non-COVID-19 and sleep were included. Sleep related articles were mainly published by authors from China, the USA, and Italy. For COVID-19 and sleep research, Huazhong University of Science was the most productive institution. The Psychiatry Research was the most influential journal across the different subject categories of this field. "Mental health", "anxiety", and "depression" were the most common keywords, while "sleep quality" and "quality of life" were the likely topic areas in terms of future research directions. CONCLUSIONS: Our findings provide a comprehensive perspective for researchers to understand the wider landscape of both COVID-19 and non-COVID-19 sleep-related research area.

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SCOPE: The study aims to investigate the role of the sulfur microbial diet in the survival of ovarian cancer (OC). METHODS AND RESULTS: A prospective cohort study is conducted with 703 patients diagnosed with OC between 2015 and 2020. Diet information is collected using a validated food frequency questionnaire. Deaths are ascertained up to March 31, 2021, via the death registry linkage. During the follow-up period (median: 37.2 months, interquartile range: 24.7-50.2 months), 130 deaths are observed. A higher sulfur microbial diet score is significantly associated with an increased risk of all-cause mortality among OC patients (tertile 3 vs tertile 1: HR = 1.93, 95% CI = 1.11-3.35). Each 1-standard deviation increment in the sulfur microbial diet score increases the all-cause mortality risk by 33% (95% CI = 1.04-1.71). Stratified analysis shows that significant associations are found in OC patients diagnosed over 50 years of age, with body mass index ≥24  kg m-2 , who changed their diet after diagnosis, or without residual lesions. CONCLUSIONS: Adherence to the sulfur microbial diet, characterized by high intakes of red meats and processed meats, and low intakes of fruits, vegetables, and whole grains, is associated with poor survival in OC patients.

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Post-infection sequelae of COVID-19 (PISC) have raised public health concerns. However, it is not clear whether infected mental health professionals (MHPs) with PISC have experienced more psychiatric symptoms than MHPs without PISC do. This study examined differences in the prevalence of self-reported depression, anxiety, insomnia and suicidality as well as the network structures of these symptoms between these two groups. Participants completed questionnaire measures of psychiatric symptoms and demographics. Expected influence was used to measure centrality of symptoms and network comparison tests were adopted to compare differences in the two network models. The sample comprised 2,596 participants without PISC and 2,573 matched participants with PISC. MHPs with PISC had comparatively higher symptom levels related to depression (55.2% vs. 23.5 %), anxiety (32.0% vs. 14.9 %), insomnia (43.3% vs. 17.3 %), and suicidality (9.6% vs. 5.3 %). PHQ4 ("Fatigue"), PHQ6 ("Guilt"), and GAD2 ("Uncontrollable Worrying") were the most central symptoms in the "without PISC" network model. Conversely, GAD3 ("Worry too much"), GAD5 ("Restlessness"), and GAD4 ("Trouble relaxing") were more central in the "with PISC" network model. In sum, MHPs with PISC experienced comparatively more psychiatric symptoms and related disturbances. Network results provide foundations for the expectation that MHPs with PISC may benefit from interventions that address anxiety-related symptoms, while those without PISC may benefit from interventions targeting depression-related symptoms.

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Clear cell carcinoma (CCC), endometrioid carcinoma (EC), and serous carcinoma (SC) are the major histological subtypes of epithelial ovarian cancer (EOC), whose differences in carcinogenesis are still unclear. Here, we undertake comprehensive proteomic profiling of 80 CCC, 79 EC, 80 SC, and 30 control samples. Our analysis reveals the prognostic or diagnostic value of dysregulated proteins and phosphorylation sites in important pathways. Moreover, protein co-expression network not only provides comprehensive view of biological features of each histological subtype, but also indicates potential prognostic biomarkers and progression landmarks. Notably, EOC have strong inter-tumor heterogeneity, with significantly different clinical characteristics, proteomic patterns and signaling pathway disorders in CCC, EC, and SC. Finally, we infer MPP7 protein as potential therapeutic target for SC, whose biological functions are confirmed in SC cells. Our proteomic cohort provides valuable resources for understanding molecular mechanisms and developing treatment strategies of distinct histological subtypes.

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BACKGROUND AND AIMS: It is still controversial whether deep learning (DL) systems add accuracy to thyroid nodule imaging classification based on the recent available evidence. We conducted this study to analyze the current evidence of DL in thyroid nodule imaging diagnosis in both internal and external test sets. METHODS: Until the end of December 2022, PubMed, IEEE, Embase, Web of Science, and the Cochrane Library were searched. We included primary epidemiological studies using externally validated DL techniques in image-based thyroid nodule appraisal. This systematic review was registered on PROSPERO (CRD42022362892). RESULTS: We evaluated evidence from 17 primary epidemiological studies using externally validated DL techniques in image-based thyroid nodule appraisal. Fourteen studies were deemed eligible for meta-analysis. The pooled sensitivity, specificity, and area under the curve (AUC) of these DL algorithms were 0.89 (95% confidence interval 0.87-0.90), 0.84 (0.82-0.86), and 0.93 (0.91-0.95), respectively. For the internal validation set, the pooled sensitivity, specificity, and AUC were 0.91 (0.89-0.93), 0.88 (0.85-0.91), and 0.96 (0.93-0.97), respectively. In the external validation set, the pooled sensitivity, specificity, and AUC were 0.87 (0.85-0.89), 0.81 (0.77-0.83), and 0.91 (0.88-0.93), respectively. Notably, in subgroup analyses, DL algorithms still demonstrated exceptional diagnostic validity. CONCLUSIONS: Current evidence suggests DL-based imaging shows diagnostic performances comparable to clinicians for differentiating thyroid nodules in both the internal and external test sets.

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BACKGROUND: The ratio of lymphocytes to monocytes (LMR) has been shown to be an effective predictor of gastric cancer prognosis. However, its predictive accuracy for signet ring gastric cancer is currently not well understood. AIM: To evaluate the prognosis predictive accuracy of preoperative LMR in signet ring gastric cancer. METHODS: A total of 212 signet ring gastric cancer patients admitted at the Xiangya Hospital of Central South University, Department of Gastrointestinal Surgery, from January 2012 to December 2016 were enrolled in the study. The prognosis predictive accuracy of preoperative LMR was explored based on the area under the receiver operating characteristic. Factors that significantly affect the survival of patients were identified using single factor analysis, and those that were independently associated with signet ring gastric cancer were identified through multivariate analysis. RESULTS: The results of the single factor analysis revealed a strong correlation between the survival of signet ring gastric cancer patients and several factors, including tumor invasion (χ2 = 49.726; P < 0.001), lymph node metastasis (χ2 = 30.269; P < 0.001), pTNM stage (χ2 = 49.322; P < 0.001), surgical approach (χ2 = 8.489; P = 0.004), age (t = -2.213; P < 0.028), carcinoembryonic antigen (CEA) (Z = -3.265; P = 0.001), platelet-to-lymphocyte ratio (Z = -2.196; P = 0.028), LMR (Z = -2.226; P = 0.026), ALB (t = 3.284; P = 0.001), prognostic nutritional index (t = -3.789; P < 0.001) and FIB (Z = -3.065; P = 0.002). Furthermore, the multivariate analysis further demonstrated that age (HR: 0.563, 95%CI: 0.363-0.873), tumor invasion depth (HR: 0.226, 95%CI: 0.098-0.520), pTNM stage (HR: 0.444, 95%CI: 0.255-0.771), preoperative CEA level (HR: 0.597, 95%CI: 0.386-8.790), and preoperative LMR level (HR: 1.776, 95%CI: 1.150-2.741) were independent factors influencing the prognosis of signet ring gastric cancer. CONCLUSION: In signet ring gastric cancer patients, a low preoperative LMR level predicts poor prognosis. The death risk ratio of the low LMR group compared to the high LMR group is 1.776.

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Background: The colors of fruits and vegetables (FV) reflect the presence of pigmented bioactive compounds. The evidence of pre-diagnosis specific FV color group intake contributing to ovarian cancer (OC) survival is limited and inconsistent. Methods: A prospective cohort study was conducted between 2015 and 2020 with 700 newly diagnosed OC patients. Pre-diagnosis dietary information was assessed by a validated food frequency questionnaire. We classified FV into five groups based on the color of their edible parts (e.g., green, red/purple, orange/yellow, white, and uncategorized groups). Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of specific color groups of FV before diagnosis with OC survival. Potential multiplicative and additive interactions were assessed. Results: 130 patients died during a median follow-up of 37.57 (interquartile: 24.77-50.20) months. We observed the improved survival with a higher pre-diagnosis intake of total FV (HRtertile 3 vs. tertile 1 = 0.63, 95%CI = 0.40-0.99), total vegetables (HRtertile 3 vs. tertile 1 = 0.57, 95%CI = 0.36-0.90), and red/purple FV (HRtertile 3 vs. tertile 1 = 0.52, 95%CI = 0.33-0.82). In addition, we observed significant dose-response relationships for per standard deviation increment between total vegetable intake (HR = 0.79, 95%CI = 0.65-0.96) and red/purple group intake (HR = 0.77, 95%CI = 0.60-0.99) before diagnosis with OC survival. Additionally, pre-diagnosis green FV intake was borderline associated with better OC survival (HRper standard deviation increment = 0.83; 95%CI = 0.69-1.00). In contrast, we did not observe significant associations between pre-diagnosis intake of total fruits, orange/yellow, white, and uncategorized groups and OC survival. Conclusion: Pre-diagnosis FV intake from various color groups, especially the green and red/purple ones, may improve OC survival. Further studies are needed to validate our findings.

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Many people suffer from hair loss and abnormal skin pigmentation, highlighting the need for simple assays to support drug discovery research. Current assays have various limitations, such as being in vitro only, not sensitive enough, or unquantifiable. We took advantage of the bilateral symmetry and large size of mouse whisker follicles to develop a novel in vivo assay called "whisker follicle microinjection assay". In this assay, we plucked mouse whiskers and then injected molecules directly into one side of the whisker follicles using microneedles that were a similar size to the whiskers, and we injected solvent on the other side as a control. Once the whiskers grew out again, we quantitatively measured their length and color intensity to evaluate the effects of the molecules on hair growth and coloring. Several chemicals and proteins were used to test this assay. The chemicals minoxidil and ruxolitinib, as well as the protein RSPO1, promoted hair growth. The effect of the clinical drug minoxidil could be detected at a concentration as low as 0.001%. The chemical deoxyarbutin inhibited melanin production. The protein Nbl1 was identified as a novel hair-growth inhibitor. In conclusion, we successfully established a sensitive and quantitative in vivo assay to evaluate the effects of chemicals and proteins on hair growth and coloring and identified a novel regulator by using this assay. This whisker follicle microinjection assay will be useful when investigating protein functions and when developing drugs to treat hair loss and abnormal skin pigmentation.

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