TiN/anatase/rutile phase junction obtained by in-situ thermal transformation for efficient photothermal-assisted photocatalytic hydrogen generation.

Phase junctions exhibit great potential in photocatalytic energy conversion, yet the narrow light response region and inefficient charge transfer limit their photocatalytic performance. Herein, an anatase/rutile phase junction modified by plasmonic TiN and oxygen vacancies (TiN/(A-R-TiO2-Ov)) is prepared through an in-situ thermal transformation from TiN for efficient photothermal-assisted photocatalytic hydrogen production for the first time. The content of TiN, oxygen vacancies, and phase components in TiN/(A-R-TiO2-Ov) hybrids can be well-adjusted by tuning the heating time. The as-prepared photocatalysts display a large specific area and wide light absorption due to the synergistic effect of plasmonic excitation, oxygen vacancies, and bandgap excitations. Meanwhile, the multi-interfaces between TiN, anatase, and rutile provide built-in electric fields for efficient separation of photoinduced carriers and hot electron injection via ohmic contact and type-Ⅱ band arrangement. As a result, the TiN/(A-R-TiO2-Ov) photocatalyst shows an excellent photocatalytic hydrogen generation rate of 15.07 mmol/g/h, which is 20.6 times higher than that of titanium dioxide P25. Moreover, temperature-dependent photocatalytic tests reveal that the excellent photothermal conversion caused by plasmonic heating and crystal lattice vibrations in TiN/(A-R-TiO2-Ov) has about 25 % enhancement in photocatalysis (18.84 mmol/g/h). This work provides new inspiration for developing high-performance photocatalysts by optimizing charge transfer and photothermal conversion.

Development and validation of an artificial intelligence-based model for detecting urothelial carcinoma using urine cytology images: a multicentre, diagnostic study with prospective validation.

Background: Urine cytology is an important non-invasive examination for urothelial carcinoma (UC) diagnosis and follow-up. We aimed to explore whether artificial intelligence (AI) can enhance the sensitivity of urine cytology and help avoid unnecessary endoscopy. Methods: In this multicentre diagnostic study, consecutive patients who underwent liquid-based urine cytology examinations at four hospitals in China were included for model development and validation. Patients who declined surgery and lacked associated histopathology results, those diagnosed with rare subtype tumours of the urinary tract, or had low-quality images were excluded from the study. All liquid-based cytology slides were scanned into whole-slide images (WSIs) at 40 × magnification and the WSI-labels were derived from the corresponding histopathology results. The Precision Urine Cytology AI Solution (PUCAS) was composed of three distinct stages (patch extraction, features extraction, and classification diagnosis) and was trained to identify important WSI features associated with UC diagnosis. The diagnostic sensitivity was mainly used to validate the performance of PUCAS in retrospective and prospective validation cohorts. This study is registered with the ChiCTR, ChiCTR2300073192. Findings: Between January 1, 2018 and October 31, 2022, 2641 patients were retrospectively recruited in the training cohort, and 2335 in retrospective validation cohorts; 400 eligible patients were enrolled in the prospective validation cohort between July 7, 2023 and September 15, 2023. The sensitivity of PUCAS ranged from 0.922 (95% CI: 0.811-0.978) to 1.000 (0.782-1.000) in retrospective validation cohorts, and was 0.896 (0.837-0.939) in prospective validation cohort. The PUCAS model also exhibited a good performance in detecting malignancy within atypical urothelial cells cases, with a sensitivity of over 0.84. In the recurrence detection scenario, PUCAS could reduce 57.5% of endoscopy use with a negative predictive value of 96.4%. Interpretation: PUCAS may help to improve the sensitivity of urine cytology, reduce misdiagnoses of UC, avoid unnecessary endoscopy, and reduce the clinical burden in resource-limited areas. The further validation in other countries is needed. Funding: National Natural Science Foundation of China; Key Program of the National Natural Science Foundation of China; the National Science Foundation for Distinguished Young Scholars; the Science and Technology Planning Project of Guangdong Province; the National Key Research and Development Programme of China; Guangdong Provincial Clinical Research Centre for Urological Diseases.

Integrative proteomic and transcriptomic analysis in the female goat ovary to explore the onset of puberty.

Puberty is considered a prerequisite for affecting reproductive performance and productivity. Little was known about molecular changes in pubertal goat ovaries. Therefore, we measured and performed a correlation analysis of the mRNA and proteins changes in the pre-pubertal and pubertal goat ovaries. The results showed that only six differentially expressed genes and differentially abundant proteins out of 18,139 genes and 7550 proteins quantified had significant correlations. CNTN2 and THBS1, discovered in the mRNA-mRNA interaction network, probably participated in pubertal and reproductive regulation by influencing GnRH receptor signals, follicular development, and ovulation. The predicted core transcription factors may either promote or inhibit the expression of reproductive genes and act synergistically to maintain normal reproductive function in animals. The interaction between PKM and TIMP3 with other proteins may impact animal puberty through energy metabolism and ovarian hormone secretion. Pathway enrichment analyses revealed that the co-associated key pathways between ovarian genes and proteins at puberty included calcium signalling pathway and olfactory transduction. These pathways were associated with gonadotropin-releasing hormone synthesis and secretion, signal transmission, and cell proliferation. In summary, these results enriched the potential molecules and signalling pathways that affect puberty and provided new insights for regulating and promoting the onset of puberty. SIGNIFICANCE: This study conducted the first transcriptomic and proteomic correlation analysis of pre-pubertal and pubertal goat ovaries and identified six significantly correlated molecules at both the gene and protein levels. Meanwhile, we were drawn to several molecules and signalling pathways that may play a regulatory role in the onset of puberty and reproduction by influencing reproductive-related gene expression, GnRH receptor signals, energy metabolism, ovarian hormone secretion, follicular development, and ovulation. This information contributed to identify potential biomarkers in pubertal goat ovaries, which was vital for predicting the onset of puberty and improving livestock performance.

Developing a clinical decision support system software prototype that assists in the management of patients with self-harm in the emergency department: protocol of the PERMANENS project.

BACKGROUND: Self-harm presents a significant public health challenge. Emergency departments (EDs) are crucial healthcare settings in managing self-harm, but clinician uncertainty in risk assessment may contribute to ineffective care. Clinical Decision Support Systems (CDSSs) show promise in enhancing care processes, but their effective implementation in self-harm management remains unexplored. METHODS: PERMANENS comprises a combination of methodologies and study designs aimed at developing a CDSS prototype that assists clinicians in the personalized assessment and management of ED patients presenting with self-harm. Ensemble prediction models will be constructed by applying machine learning techniques on electronic registry data from four sites, i.e., Catalonia (Spain), Ireland, Norway, and Sweden. These models will predict key adverse outcomes including self-harm repetition, suicide, premature death, and lack of post-discharge care. Available registry data include routinely collected electronic health record data, mortality data, and administrative data, and will be harmonized using the OMOP Common Data Model, ensuring consistency in terminologies, vocabularies and coding schemes. A clinical knowledge base of effective suicide prevention interventions will be developed rooted in a systematic review of clinical practice guidelines, including quality assessment of guidelines using the AGREE II tool. The CDSS software prototype will include a backend that integrates the prediction models and the clinical knowledge base to enable accurate patient risk stratification and subsequent intervention allocation. The CDSS frontend will enable personalized risk assessment and will provide tailored treatment plans, following a tiered evidence-based approach. Implementation research will ensure the CDSS' practical functionality and feasibility, and will include periodic meetings with user-advisory groups, mixed-methods research to identify currently unmet needs in self-harm risk assessment, and small-scale usability testing of the CDSS prototype software. DISCUSSION: Through the development of the proposed CDSS software prototype, PERMANENS aims to standardize care, enhance clinician confidence, improve patient satisfaction, and increase treatment compliance. The routine integration of CDSS for self-harm risk assessment within healthcare systems holds significant potential in effectively reducing suicide mortality rates by facilitating personalized and timely delivery of effective interventions on a large scale for individuals at risk of suicide.

Suicide attempt risk predicts inconsistent self-reported suicide attempts: A machine learning approach using longitudinal data.

INTRODUCTION: Inconsistent self-reports of lifetime suicide attempts (LSAs) are a major obstacle for accurate assessment of suicidal behavior. This study is the first to posit that adolescents at higher risk report LSAs more consistently than those at lower risk, revealing a link between suicide attempt risk and consistent reporting. METHODS: A machine learning model was trained with 70 % of the baseline assessment data of a longitudinal sample of Norwegian adolescents (n = 10,739). The model was used to estimate the LSA risk score for the remaining 30 % of the testing dataset. The relationship between these baseline risk scores and the consistency of reporting LSAs was assessed using a 2-year follow-up reassessment of the testing dataset. RESULTS: Internalizing problems, optimism about the future, conduct problems, substance use, and disordered eating were important factors associated with suicide attempt risk. Of the participants, 63.41 % had inconsistent self-reports at the two-year follow-up. Adolescents who consistently reported LSAs had significantly higher scores of suicide attempt risk at baseline. Two logistic regression analyses confirmed an association between suicide attempt risk and inconsistent self-reported LSAs and showed that sex (being male), and lower levels of depression and conduct problems significantly predicted such inconsistencies. Those who inconsistently reported LSAs were more likely than the others to be classified by the model as false negatives at the baseline risk assessment due to their lower estimated risk scores. LIMITATIONS: Suicide attempts were measured with a single item in this study. CONCLUSION: These risk factors support the theory of adolescent suicidality (TAS) and could improve suicide attempt risk assessment. Inconsistent self-reported LSAs signal lower suicide attempt risk.

Vitamin E biofortification: enhancement of seed tocopherol concentrations by altered chlorophyll metabolism.

Homogentisate Phytyltransferase (HPT) catalyzes condensation of homogentisate (HGA) and phytyl diphosphate (PDP) to produce tocopherols, but can also synthesize tocotrienols using geranylgeranyl diphosphate (GGDP) in plants engineered for deregulated HGA synthesis. In contrast to prior tocotrienol biofortification efforts, engineering enhanced tocopherol concentrations in green oilseeds has proven more challenging due to the integral role of chlorophyll metabolism in supplying the PDP substrate. This study show that RNAi suppression of CHLSYN coupled with HPT overexpression increases tocopherol concentrations by >two-fold in Arabidopsis seeds. We obtained additional increases in seed tocopherol concentrations by engineering increased HGA production via overexpression of bacterial TyrA that encodes chorismate mutase/prephenate dehydrogenase activities. In overexpression lines, seed tocopherol concentrations increased nearly three-fold, and resulted in modest tocotrienol accumulation. We further increased total tocochromanol concentrations by enhancing production of HGA and GGDP by overexpression of the gene for hydroxyphenylpyruvate dioxygenase (HPPD). This shifted metabolism towards increased amounts of tocotrienols relative to tocopherols, which was reflected in corresponding increases in ratios of GGDP/PDP in these seeds. Overall, our results provide a theoretical basis for genetic improvement of total tocopherol concentrations in green oilseeds (e.g., rapeseed, soybean) through strategies that include seed-suppression of CHLSYN coupled with increased HGA production.

Grid1 regulates the onset of puberty in female rats.

The study aimed to investigate the effect of Grid1, encoding the glutamate ionotropic receptor delta type subunit 1 (GluD1), on puberty onset in female rats. Grid1 mRNA and protein expression was detected in the hypothalamus of female rats at prepuberty and puberty. The levels of Grid1 mRNA in the hypothalamus, the fluorescence intensity in the arcuate nucleus and paraventricular nucleus of the prepubertal rats was significantly lower than pubertal. Additionally, the expression of Grid1 was suppressed in primary hypothalamus cells and prepubertal rat. Finally, investigated the effect of Grid1 knockdown on puberty onset and reproductive performance. Treatment of hypothalamic neurons with LV-Grid1 decreased the level of Grid1 and Rfrp-3 (encoding RFamide-related peptide 3) mRNA expression, but increased the Gnrh (encoding gonadotropin-releasing hormone) mRNA levels. After an ICV injection, the time for the rat vaginal opening occurred earlier. Moreover, Gnrh mRNA expression was increased, whereas Rfrp-3 mRNA expression was decreased in the hypothalamus. The concentration of progesterone (P4) in the serum was significantly decreased compare with control group. Ovary hematoxylin-eosin staining revealed that the LV-Grid1 group mainly contained primary and secondary follicles. The reproductive performance of the rats was not affected by the Grid1 knockdown. Therefore, Grid1 may affect the onset of puberty in female rats by regulating the levels of Gnrh, and Rfrp-3 in the hypothalamus, as well as the concentrations of P4, but not reproduction performance.

Interpersonal violent injury and subsequent risk of suicide and deliberate self-harm: a register-based national cohort study from Norway, 2010-2018.

Background: Interpersonal violence is a leading cause of morbidity, with potentially severe adverse consequences for the mental health of the injured persons. The extent to which violent injury is associated with subsequent suicidal behavior, however, remains unclear. This study aimed to examine how violent injury was associated with subsequent deliberate self-harm and death by suicide. Methods: This retrospective cohort study used nationwide longitudinal registry data from Norway to identify all individuals presenting to emergency services in 2010-2018 with a violence-related injury, along with sex- and age-matched control individuals from the general population. The primary outcomes were any emergency visit for deliberate self-harm (DSH) and suicide death, observed through 31 December 2018. Rates of each outcome were compared between violence-injured patients and comparison individuals using stratified multivariable Cox regression models, controlling for sociodemographic characteristics as well as history of psychiatric treatment and DSH. Secondary analyses tested for moderation by sex, age, and prior psychiatric treatment. Findings: Violence-injured patients (n = 28,276) had substantially higher rates of DSH (946.7 per 100,000 person-years) and suicide death (74.5 per 100,000) when compared to controls (n = 282,760; 90.0 and 15.2 per 100,000, respectively). The hazard ratios (HRs) remained significantly higher even after accounting for covariates (HRadj for DSH: 5.11; 95% CI: 4.62, 5.66; HRadj for suicide: 2.40; 95% CI: 1.78, 3.24). Sex differences in this association were negligible, but the association between violence injury and DSH increased with age. Violence-injured patients with prior psychiatric treatment had the highest risk of suicidal behavior. Interpretation: Violence-injured patients experience significantly excess rates of suicidal behavior, a finding with potential to inform both clinical intervention and population-level suicide prevention strategies. Funding: Fulbright Norway Scholarship.

PAX2 is regulated by estrogen/progesterone through promoter methylation in endometrioid adenocarcinoma and has an important role in carcinogenesis via the AKT/mTOR signaling pathway.

Endometrioid adenocarcinoma (EEC) is one of the most common cancers of the female reproductive system. In recent years, much emphasis has been placed on early diagnosis and treatment. PAX2 (Paired box 2) inactivation is reportedly an important biomarker for endometrioid intraepithelial neoplasia (EIN) and EEC. However, the role of PAX2 in EEC carcinogenesis remains unclear. PAX2 expression and associated clinical characteristics were analyzed via The Cancer Genome Atlas, Gene Expression Omnibus, and Cancer Cell Line Encyclopedia databases and clinical paired EIN/EEC tissue samples. Bioinformatic analysis was conducted to identify the putative molecular function and mechanism of PAX2. Cell proliferation, colony formation, cell migration, and invasion assays in vitro, and mouse xenograft models were utilized to study the biological functions of PAX2 in vivo. Pyrosequencing and the demethylating drug 5-Aza-dc were used to verify promoter methylation in clinical tissues and cell lines, respectively. The mechanism underlying the regulatory effect of estrogen (E2) and progesterone (P4) on PAX2 expression was investigated by receptor block assay and double luciferase reporter assay. PAX2 expression was found to be significantly downregulated in EIN and EEC tissues, its overexpression inhibited EEC cell malignant behaviors in vivo and in vitro and inhibited the AKT/mTOR signaling pathway. PAX2 inactivation in EEC was related to promoter methylation, and its expression was regulated by E2 and P4 through their receptors via promoter methylation. Our findings elucidated the expression and function of PAX2 in EEC and have provided hitherto undocumented evidence of the underlying molecular mechanisms. PAX2 expression is suppressed by estrogen prompting its methylation through estrogen receptor. Furthermore, PAX2 regulates the AKT/mTOR signaling pathway to influence EEC progression. © 2024 The Pathological Society of Great Britain and Ireland.

Unveiling Adolescent Suicidality: Holistic Analysis of Protective and Risk Factors Using Multiple Machine Learning Algorithms.

Adolescent suicide attempts are on the rise, presenting a significant public health concern. Recent research aimed at improving risk assessment for adolescent suicide attempts has turned to machine learning. But no studies to date have examined the performance of stacked ensemble algorithms, which are more suitable for low-prevalence conditions. The existing machine learning-based research also lacks population-representative samples, overlooks protective factors and their interplay with risk factors, and neglects established theories on suicidal behavior in favor of purely algorithmic risk estimation. The present study overcomes these shortcomings by comparing the performance of a stacked ensemble algorithm with a diverse set of algorithms, performing a holistic item analysis to identify both risk and protective factors on a comprehensive data, and addressing the compatibility of these factors with two competing theories of suicide, namely, The Interpersonal Theory of Suicide and The Strain Theory of Suicide. A population-representative dataset of 173,664 Norwegian adolescents aged 13 to 18 years (mean = 15.14, SD = 1.58, 50.5% female) with a 4.65% rate of reported suicide attempt during the past 12 months was analyzed. Five machine learning algorithms were trained for suicide attempt risk assessment. The stacked ensemble model significantly outperformed other algorithms, achieving equal sensitivity and a specificity of 90.1%, AUC of 96.4%, and AUCPR of 67.5%. All algorithms found recent self-harm to be the most important indicator of adolescent suicide attempt. Exploratory factor analysis suggested five additional risk domains, which we labeled internalizing problems, sleep disturbance, disordered eating, lack of optimism regarding future education and career, and victimization. The identified factors provided stronger support for The Interpersonal Theory of Suicide than for The Strain Theory of Suicide. An enhancement to The Interpersonal Theory based on the risk and protective factors identified by holistic item analysis is presented.

Anti-Ulcerative Colitis Effects and Active Ingredients in Ethyl Acetate Extract from Decoction of Sargentodoxa cuneata.

Ulcerative colitis (UC) is an intractable disease prevalent worldwide. While ethyl acetate extract from decoction of Sargentodoxa cuneata (EAdSc) has potential anti-inflammatory activity, its effects on UC remain unknown. In this study, the constituent compounds discussed in the literature and identified by gas chromatography and mass spectrometry (GC-MS) were collected, and the blood-soluble components of EAdSc were identified by liquid chromatography-mass spectrometry. The network pharmacology analysis and molecular docking analysis were performed to explore the potential underlying mechanism and active ingredients of EAdSc against UC. Furthermore, mice with dextran sulfate sodium (DSS)-induced UC were used to study the therapeutic effects and validate the mechanism of EAdSc against UC. A total of 53 compounds from EAdSc were identified in the literature and by GC-MS, and 22 blood-soluble EAdSc components were recognized. Network pharmacology analysis revealed that multiple inflammatory signaling pathways are involved in EAdSc's anti-UC activity. Furthermore, molecular docking analysis showed that the eleutheroside A, liriodendrin, epicatechin, 2-methoxy-4-vinylphenol, catechin, androsin, coumaroyltyramine, and catechol may be active against UC through the TLR4/NF-κB/NLRP3 pathway. EAdSc reduced the disease activity, macroscopic colon damage, and histological damage indices, as well as inhibiting DSS-induced spleen enlargement and colon shortening. In addition, EAdSc decreased the levels of tumor necrosis factor-α (TNF-α), interleukin (IL)-1ß, IL-6, and IL-17, as well as the expression of TLR4, NF-κB p65, NLRP3, and Caspase-1 mRNA in colon tissues. These results provide insights into the anti-UC effects and underlying mechanisms of EAdSc and help elucidate the active ingredients of EAdSc in the treatment of UC.

Situation Analysis of Suicide and Self-Harm in the WHO Eastern Mediterranean Region.

OBJECTIVE: An estimated 41,000 lives are lost to suicide each year in World Health Organization Eastern Mediterranean Region Office (WHO EMRO) countries. The objective of this study was to conduct a situation analysis for suicide and self-harm in the WHO EMRO region. METHODS: Data on suicide were obtained from the WHO Global Health Estimates for the years 2000-2019. Information on risk groups efforts to prevent self-harm and suicide in the EMRO region were retrieved through scientific studies, grey literature, and public websites. RESULTS: During 2000-2019, the age-standardized suicide rate was 6.7 per 100,000 inhabitants, albeit there are concerns regarding data quality. Self-harm and suicide remain criminal acts in more than half of the countries. Few countries have a national plan for prevention of suicide. Toxic agents, such as pesticides and black henna, are easily available and frequently used for suicide in some areas, as are firearms and self-immolation. Successful prevention measures include means restriction and psychosocial interventions after self-harm. CONCLUSION: Many WHO EMRO countries remain underserved in terms of mental health care. Decriminalization of suicide and means restriction might be further promoted. Online-based tools for mental health literacy and psychosocial therapy are other options to explore.

Suicidal behavior remains a criminal act in more than half of the WHO EMRO countries.Easily available toxic agents, such as pesticides and black henna, and firearms are common methods used for suicidal behavior in the WHO EMRO countries.Access to mental health care is limited in many of the WHO EMRO countries.Online-based psychoeducation and psychosocial intervention programs might be further explored as preventive efforts.

Integrative proteomic and phosphoproteomic analysis in the female goat hypothalamus to study the onset of puberty.

BACKGROUND: Puberty marks the end of childhood and achieve sexual maturation and fertility. The role of hypothalamic proteins in regulating puberty onset is unclear. We performed a comprehensive differential proteomics and phosphoproteomics analysis in prepubertal and pubertal goats to determine the roles of hypothalamic proteins and phosphoproteins during the onset of puberty. RESULTS: We used peptide and posttranslational modifications peptide quantification and statistical analyses, and identified 69 differentially expressed proteins from 5,057 proteins and 576 differentially expressed phosphopeptides from 1574 phosphorylated proteins. Combined proteomic and phosphoproteomics, 759 correlated proteins were identified, of which 5 were differentially expressed only at the protein level, and 201 were only differentially expressed at the phosphoprotein level. Pathway enrichment analyses revealed that the majority of correlated proteins were associated with glycolysis/gluconeogenesis, Fc gamma R-mediated phagocytosis, focal adhesion, GABAergic synapse, and Rap1 signaling pathway. These pathways are related to cell proliferation, neurocyte migration, and promoting the release of gonadotropin-releasing hormone in the hypothalamus. CTNNB1 occupied important locations in the protein-protein interaction network and is involved in focal adhesion. CONCLUSION: The results demonstrate that the proteins differentially expression only at the protein level or only differentially expressed at the phosphoprotein level and their related signalling pathways are crucial in regulating puberty in goats. These differentially expressed proteins and phosphorylated proteins may constitute the proteomic backgrounds between the two different stages.

Significant Enhancement of Circular Polarization in Light Emission through Controlling Helical Pitches of Semiconductor Nanohelices.

Circularly polarized light emission (CPLE) can be potentially applied to three-dimensional displays, information storage, and biometry. However, these applications are practically limited by a low purity of circular polarization, i.e., the small optical dissymmetry factor gCPLE. Herein, glancing angle deposition (GLAD) is performed to produce inorganic nanohelices (NHs) to generate CPLE with large gCPLE values. CdSe NHs emit red CPLE with gCPLE = 0.15 at a helical pitch (P) ≈ 570 nm, having a 40-fold amplification of gCPLE compared to that at P ≈ 160 nm. Ceria NHs emit ultraviolet-blue CPLE with gCPLE ≈ 0.06 at P ≈ 830 nm, with a 103-fold amplification compared to that at P ≈ 110 nm. Both the photoluminescence and scattering among the close-packed NHs complicatedly account for the large gCPLE values, as revealed by the numerical simulations. The GLAD-based NH-fabrication platform is devised to generate CPLE with engineerable color and large gCPLE = 10-2-10-1, shedding light on the commercialization of CPLE devices.

Prognostic Predicting Model of Pancreatic Body Tail Carcinoma Using Clinical and CT Radiomic Data.

Objective: To collect the clinical, pathological, and computed tomography (CT) data of 143 accepted surgical cases of pancreatic body tail cancer (PBTC) and to model and predict its prognosis. Methods: The clinical, pathological, and CT data of 143 PBTC patients who underwent surgical resection or endoscopic ultrasound biopsy and were pathologically diagnosed in Xiangyang No.1 People's Hospital Hospital from December 2012 to December 2022 were retrospectively analyzed. The Kaplan-Meier method was adopted to make survival curves based on the 1 to 5 years' follow-up data, and then the log-rank was employed to analyze the survival. According to the median survival of 6 months, the PBTC patients were divided into a group with a good prognosis (survival time ≥ 6 months) and a group with a poor prognosis (survival time < 6 months), and further the training set and test set were set at a ratio of 7/3. Then logistic regression was conducted to find independent risk factors, establish predictive models, and further the models were validated. Results: The Kaplan-Meier analysis showed that age, diabetes, tumor, node, and metastasis stage, CT enhancement mode, peripancreatic lymph node swelling, nerve invasion, surgery in a top hospital, tumor size, carbohydrate antigen 19-9, carcinoembryonic antigen, Radscore 1/2/3 were the influencing factors of PBTC recurrence. The overall average survival was 7.4 months in this study. The multivariate logistic analysis confirmed that nerve invasion, surgery in top hospital, dilation of the main pancreatic duct, and Radscore 2 were independent factors affecting the mortality of PBTC (P < .05). In the test set, the combined model achieved the best predictive performance [AUC 0.944, 95% CI (0.826-0.991)], significantly superior to the clinicopathological model [AUC 0.770, 95% CI (0.615-0.886), P = .0145], and the CT radiomics model [AUC 0.883, 95% CI (0.746-0.961), P = .1311], with a good clinical net benefit confirmed by decision curve. The same results were subsequently validated on the test set. Conclusion: The diagnosis and treatment of PBTC are challenging, and survival is poor. Nevertheless, the combined model benefits the clinical management and prognosis of PBTC.

Psychiatric disorders among adult deliberate self-harm patients and subsequent risk of dying by suicide, mental and behavioural disorders and other external causes.

INTRODUCTION: Deliberate self-harm (DSH) treated in general hospital is a well-established risk factor for suicide and other cause mortality. However, few studies have used population data to investigate the differential impact of specific psychiatric disorders on the risk of subsequent suicide, by sex and age of the patient in the context of previous DSH episodes. METHOD: All patients aged 18 and older treated for DSH in general hospitals during the period 2008-2018 were identified through national registers. Cox proportional hazards regression was used to ascertain the associated risk of death by suicide, mental and behavioural disorder and other external causes. RESULTS: The cohort consisted of 39 479 patients of which 878 died by suicide, 461 by mental and behavioural disorders and 1037 by other external causes. Overall, schizophrenia spectrum disorders, affective disorders and personality disorders increased the risk of suicide. Large gender and age differences were identified in the risk of suicide associated with personality disorders and affective disorders. Alcohol use disorders and dementia increased the risk of dying by mental and behavioural disorders and alcohol use disorders and other substance use disorders increased the risk of death by external causes. CONCLUSION: Schizophrenia spectrum disorders, affective disorders and personality disorders increased the risk of suicide among DSH patients, but the effect varied by gender, age and history of previous DSH. Psychiatric evaluation of all DSH patients and treatment tailored to the patient's specific needs is essential to reduce the risk of premature death.

Clinical Features and Computed Tomography Radiomics-Based Model for Predicting Pancreatic Ductal Adenocarcinoma and Focal Mass-Forming Pancreatitis.

Objective: To establish a predictive model distinguishing focal mass-forming pancreatitis (FMFP) from pancreatic ductal adenocarcinoma (PDAC) based on computed tomography (CT) radiomics and clinical data. Methods: A total of 78 FMFP patients (FMFP group) and 120 PDAC patients (PDAC group) who were admitted to Xiangyang No.1 People's Hospital and Xiangyang Central Hospital from February 2012 to May 2021 and were pathologically diagnosed were included in this study, and were input to set up the training set and test set at a ratio of 7:3. The 3Dslicer software was used to extract the radiomic features and radiomic scores (Radscores) of the 2 groups, and the clinical data (age, gender, etc), CT imaging features (lesion location, size, enhancement degree, vascular wrapping, etc) and CT radiomic features of the 2 groups were compared. Logistic regression was used to screen the independent risk factors of the 2 groups, and multiple prediction models (clinical imaging model, radiomics model, and combined model) were established. Then the receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) were conducted to compare the prediction performance and net benefit of the models. Results: The multivariate logistic regression results indicated that dilation of the main pancreatic duct, vascular wrapping, Radscore1 and Radscore2 were independent influencing factors for distinguishing FMFP from PDAC. In the training set, the combined model showed the best predictive performance (area under the ROC curve [AUC] 0.857, 95% CI [0.787-0.910]), significantly higher than the clinical imaging model (AUC 0.650, 95% CI [0.565-0.729]) and the radiomics model (AUC 0.812, 95% CI [0.759-0.890]). DCA confirmed that the combined model had the highest net benefit. These results were further validated by the test set. Conclusion: The combined model based on clinical-CT radiomics data can effectively identify FMFP and PDAC, providing a reference for clinical decision-making.

Knockdown of lncRNA Meg3 delays the onset of puberty in female rats.

This study investigated how lncRNA Meg3 affects the onset of puberty in female rats. We determined Meg3 expression in the hypothalamus-pituitary-ovary axis of female rats at the infancy, prepubertal, pubertal, and adult life stages, using quantitative reverse transcription polymerase chain reaction (qRT-PCR). We also assessed the effects of Meg3 knockdown on the expression levels of puberty-related genes and Wnt/ß-catenin proteins in the hypothalamus, time of puberty onset, levels of reproductive genes and hormones, and ovarian morphology in female rats. Meg3 expression in the ovary varied significantly between prepuberty and puberty (P < 0.01). Meg3 knockdown decreased the expression of Gnrh, and Kiss1 mRNA (P < 0.05) and increased the expression of Wnt (P < 0.01) and ß-catenin proteins (P < 0.05) in the hypothalamic cells. Onset of puberty in Meg3 knockdown rats was delayed compared to the control group (P < 0.05). Meg3 knockdown decreased Gnrh mRNA levels (P < 0.05) and increased Rfrp-3 mRNA levels (P < 0.05) in the hypothalamus. The serum concentrations of progesterone (P4) and estradiol (E2) of Meg3 knockdown rats were lower than those in the control animals (P < 0.05). Higher longitudinal diameter and ovary weight were found in Meg3 knockdown rats (P < 0.05). These findings suggest that Meg3 regulates the expression of Gnrh, Kiss-1 mRNA and Wnt/ß-catenin proteins in the hypothalamic cells, and Gnrh, Rfrp-3 mRNA of the hypothalamus and the serum concentration of P4 and E2, and its knockdown delays the onset of puberty in female rats.

Predicting model of mild and severe types of COVID-19 patients using Thymus CT radiomics model: A preliminary study.

OBJECTIVE: To predict COVID-19 severity by building a prediction model based on the clinical manifestations and radiomic features of the thymus in COVID-19 patients. METHOD: We retrospectively analyzed the clinical and radiological data from 217 confirmed cases of COVID-19 admitted to Xiangyang NO.1 People's Hospital and Jiangsu Hospital of Chinese Medicine from December 2019 to April 2022 (including 118 mild cases and 99 severe cases). The data were split into the training and test sets at a 7:3 ratio. The cases in the training set were compared in terms of clinical data and radiomic parameters of the lasso regression model. Several models for severity prediction were established based on the clinical and radiomic features of the COVID-19 patients. The DeLong test and decision curve analysis (DCA) were used to compare the performances of several models. Finally, the prediction results were verified on the test set. RESULT: For the training set, the univariate analysis showed that BMI, diarrhea, thymic steatosis, anorexia, headache, findings on the chest CT scan, platelets, LDH, AST and radiomic features of the thymus were significantly different between the two groups of patients (P < 0.05). The combination model based on the clinical and radiomic features of COVID-19 patients had the highest predictive value for COVID-19 severity [AUC: 0.967 (OR 0.0115, 95%CI: 0.925-0.989)] vs. the clinical feature-based model [AUC: 0.772 (OR 0.0387, 95%CI: 0.697-0.836), P < 0.05], laboratory-based model [AUC: 0.687 (OR 0.0423, 95%CI: 0.608-0.760), P < 0.05] and model based on CT radiomics [AUC: 0.895 (OR 0.0261, 95%CI: 0.835-0.938), P < 0.05]. DCA also confirmed the high clinical net benefits of the combination model. The nomogram drawn based on the combination model could help differentiate between the mild and severe cases of COVID-19 at an early stage. The predictions from different models were verified on the test set. CONCLUSION: Severe cases of COVID-19 had a higher level of thymic involution. The thymic differentiation in radiomic features was related to disease progression. The combination model based on the radiomic features of the thymus could better promote early clinical intervention of COVID-19 and increase the cure rate.

Predicting Model of Biochemical Recurrence of Prostate Carcinoma (PCa-BCR) Using MR Perfusion-Weighted Imaging-Based Radiomics.

OBJECTIVE: To build a combined model that integrates clinical data, contrast-enhanced ultrasound, and magnetic resonance perfusion-weighted imaging-based radiomics for predicting the possibility of biochemical recurrence of prostate carcinoma and develop a nomogram tool. METHOD: We retrospectively analyzed the clinical, ultrasound, and magnetic resonance imaging data of 206 patients pathologically confirmed with prostate carcinoma and receiving radical prostatectomy at Xiangyang No. 1 People's Hospital from February 2015 to August 2021. Based on one to 7 years of follow-up (prostate specific antigen [PSA] level≥0.2 ng/mL, indicative of prostate carcinoma-biochemical recurrence), the patients were divided into biochemical recurrence group (n = 77) and normal group (n = 129). The training and testing sets were formed by dividing the patients at a 7:3 ratio. In training set, The magnetic resonance perfusion-weighted imaging-based radiomics radscore was generated using lasso regression. Several predictive models were built based on the patients' clinical imaging data. The predictive efficacy (area under the curve) of these models was compared using the MedCalc software. The decision curve analysis was conducted using the R to compare the net benefit. Finally, an external validation was carried out on the testing set, and the nomogram tool was developed for predicting prostate carcinoma-biochemical recurrence. RESULT: The univariate analysis confirmed that Tumor diameter, tumor node metastasis classification stage of tumor, lymph node metastasis or distance metastasis, Gleason grade, preoperative PSA, ultrasound (peak intensity, arrival time, and elastography grade), and magnetic resonance imaging-radscore1/2 were predictors of prostate carcinoma-biochemical recurrence. On the training set, the combined model based on the above factors had the highest predictive efficacy for prostate carcinoma-biochemical recurrence (area under the curve: 0.91; odds ratio 0.02, 95% confidence interval: 0.85-0.95). The predictive performance of the combined model was significantly higher than that of the model based on general clinical data (area under the curve: 0.74; odds ratio 0.04, 95% confidence interval: 0.67-0.81, P < .05), contrast-enhanced ultrasound (area under the curve: 0.61; odds ratio 0.05 95% confidence interval: 0.53-0.69, P < .05), and the magnetic resonance imaging-based radiomics model (area under the curve: 0.85; odds ratio 0.03, 95% confidence interval: 0.78-0.91, P = .01). The decision curve analysis also indicated the maximum net benefit derived from the combined model, which agreed with the validation results on the testing set. The nomogram tool developed based on the combined model achieved a good performance in clinical applications. CONCLUSION: The magnetic resonance imaging texture parameters extracted by magnetic resonance perfusion-weighted imaging Lasso regression could help increase the accuracy of the predictive model. The combined model and the nomogram tool provide support for the clinical screening of the populations at a risk for biochemical recurrence.