Rapid detection of the irinotecan-related UGT1A1 & 5-fluorouracil related DPYD polymorphism by asymmetric polymerase chain reaction melting curve analysis.

BACKGROUND: Determination of DPYD and UGT1A1 polymorphisms prior to 5-fluorouracil and irinotecan therapy is crucial for avoiding severe adverse drug effects. Hence, there is a pressing need for accurate and reliable genotyping methods for the most common DPYD and UGT1A1 polymorphisms. In this study, we introduce a novel polymerase chain reaction (PCR) melting curve analysis method for discriminating DPYD c.1236G > A, c.1679 T > G, c.2846A > T, IVS14 + 1G > A and UGT1A1*1, *28, *6 (G71R) genotypes. METHODS: Following protocol optimization, this technique was employed to genotype 28 patients, recruited between March 2023 and October 2023, at the First Affiliated Hospital of Xiamen University. These patients included 20 with UGT1A1 *1/*1, 8 with UGT1A1 *1/*28, 4 with UGT1A1 *28/*28, 22 with UGT1A1*6 G/G, 6 with UGT1A1*6 G/A, 4 with UGT1A1*6 A/A, 27 with DPYD(c.1236) G/G, 3 with DPYD(c.1236) G/A, 2 with DPYD(c.1236) A/A, 27 with DPYD(c.1679) T/T, 2 with DPYD(c.1679) T/G, 3 with DPYD(c.1679) G/G, 28 with DPYD(c.2846A/T) A/A, 2 with DPYD(c.2846A/T) A/T, 2 with DPYD(c.2846A/T) T/T, 28 with DPYD(c.IVS14 + 1) G/G, 2 with DPYD(c.IVS14 + 1) G/G, and 2 with DPYD(c.IVS14 + 1) G/G, as well as 3 plasmid standards. Method accuracy was assessed by comparing results with those from Sanger sequencing or Multiplex quantitative PCR(qPCR). Intra- and inter-run precision of melting temperatures (Tms) were calculated to evaluate reliability, and sensitivity was assessed through limit of detection examination. RESULTS: The new method accurately identified all genotypes and exhibited higher accuracy than Multiplex qPCR. Intra- and inter-run coefficients of variation for Tms were both ≤1.97 %, with standard deviations ≤0.95 °C. The limit of detection was 0.09 ng/µL of input genomic DNA. CONCLUSION: Our developed PCR melting curve analysis offers accurate, reliable, rapid, simple, and cost-effective detection of DPYD and UGT1A1 polymorphisms. Its application can be easily extended to clinical laboratories equipped with a fluorescent PCR platform.

Comparative analysis of dexmedetomidine, midazolam, and propofol impact on epilepsy-related mortality in the ICU: insights from the MIMIC-IV database.

BACKGROUND: Dexmedetomidine (Dex), midazolam, and propofol are three distinct sedatives characterized by varying pharmacological properties. Previous literature has indicated the positive impact of each of these sedatives on ICU patients. However, there is a scarcity of clinical evidence comparing the efficacy of Dex, midazolam, and propofol in reducing mortality among people with epilepsy (PWE). This study aimed to assess the impact of Dex, midazolam, and propofol on the survival of PWE. METHODS: The data were retrospectively retrieved from the Medical Information Mart for Intensive Care (MIMIC)-IV database (version 2.0). PWE were categorized into Dex, midazolam, and propofol groups based on the intravenously administered sedatives. PWE without standard drug therapy were included in the control group. Comparative analyses were performed on the data among the groups. RESULTS: The Dex group exhibited a significantly lower proportion of in-hospital deaths and a markedly higher in-hospital survival time compared to the midazolam and propofol groups (p < 0.01) after propensity score matching. Kaplan-Meier curves demonstrated a significant improvement in survival rates for the Dex group compared to the control group (p = 0.025). Analysis of Variance (ANOVA) revealed no significant differences in survival rates among the Dex, midazolam, and propofol groups (F = 1.949, p = 0.143). The nomogram indicated that compared to midazolam and propofol groups, Dex was more effective in improving the survival rate of PWE. CONCLUSION: Dex might improve the survival rate of PWE in the ICU compared to no standard drug intervention. However, Dex did not exhibit superiority in improving survival rates compared to midazolam and propofol.

Examining the role of resilience in the relationship between social support and fear of recurrence among patients with gastric cancer on chemotherapy: a cross-sectional study in Jiangsu, China.

OBJECTIVES: The objective of this study is to investigate the relationships between fear of cancer recurrence (FCR), social support and resilience, and further determine whether resilience mediates social support and FCR among Chinese patients with gastric cancer undergoing chemotherapy. DESIGN: Multicentre cross-sectional survey. SETTING: Four hospitals in Jiangsu Province, China, with grade-A tertiary hospital settings. PARTICIPANTS: 755 patients with gastric cancer on chemotherapy across four hospitals in China were included from March 2021 to September 2022. OUTCOME MEASURES: The Fear of Progression Questionnaire-Short Form (FoP-Q-SF), Connor-Davidson Resilience Scale (CD-RISC) and Social Support Rating Scale (SSRS) were used to test the model's constructs. Statistical analyses were conducted by using IBM SPSS V.26.0 software. PROCESS V.3.4 macro was used to analyse the mediating role of resilience in the relationship between social support and FCR. RESULTS: The mean scores for SSRS, CD-RISC and FoP-Q-SF in patients with gastric cancer receiving chemotherapy were 41.55±7.79, 54.83±18.46 and 30.91±10.11, respectively. 43.3% (n=327) had psychological dysfunction, 56.8% (n=429) had low to medium resilience and 99.1% (n=748) had medium to robust social support. Significant differences exist among three variables, resilience positively correlated with social support, while FCR negatively correlated with resilience and social support (p<0.001). Resilience fully mediated the relationship between social support and FCR (a*b-path=-0.126, 95% CI -0.169 to -0.086). CONCLUSIONS: Mediation analysis shows resilience mediates social support and FCR in patients with gastric cancer as the negative effect of social support on FCR was fully mediated by resilience. Interventions targeting these variables may reduce FCR in patients with gastric cancer undergoing chemotherapy.

Selenium restored mitophagic flux to alleviate cadmium-induced hepatotoxicity by inhibiting excessive GPER1-mediated mitophagy activation.

Cadmium (Cd) is a common environmental pollutant, while selenium (Se) can ameliorate heavy metal toxicity. Consequently, this study aimed to investigate the protective effects of Se against Cd-induced hepatocyte injury and its underlying mechanisms. To achieve this, we utilized the Dongdagou-Xinglong cohort, BRL3A cell models, and a rat model exposed to Cd and/or Se. The results showed that Se counteracted liver function injury and the decrease in GPER1 levels caused by environmental Cd exposure, and various methods confirmed that Se could protect against Cd-induced hepatotoxicity both in vivo and in vitro. Mechanistically, Cd caused excessive mitophagy activation, evidenced by the colocalization of LC3B, PINK1, Parkin, P62, and TOMM20. Transfection of BRL3A cells with mt-keima adenovirus indicated that Cd inhibited autophagosome-lysosome fusion, thereby impeding mitophagic flux. Importantly, G1, a specific agonist of GPER1, mitigated Cd-induced mitophagy overactivation and hepatocyte toxicity, whereas G15 exacerbates these effects. Notably, Se supplementation attenuated Cd-induced GPER1 protein reduction and excessive mitophagy activation while facilitating autophagosome-lysosome fusion, thereby restoring mitophagic flux. In conclusion, this study proposed a novel mechanism whereby Se alleviated GPER1-mediated mitophagy and promoted autophagosome-lysosome fusion, thus restoring Cd-induced mitophagic flux damage, and preventing hepatocyte injury.

Exploring laser-induced acute and chronic retinal vein occlusion mouse models: Development, temporal in vivo imaging, and application perspectives.

Photodynamic venous occlusion is a commonly accepted method for establishing mouse models of retinal vein occlusion (RVO). However, existing model parameters do not distinguish between acute and chronic RVO subtypes. Large variations in laser energy seem to correlate with fluctuating retinopathy severity and high rates of venous recanalization during the acute phase, along with the variable levels of retinal perfusion during the chronic phase. After optimizing the modeling procedure and defining success and exclusion criteria, laser energy groups of 80mW, 100mW, and 120mW were established. Multimodal imaging confirmed that higher energy levels increased the incidence of retinal cystoid edema and intraretinal hemorrhage, exacerbated the severity of exudative retinal detachment, and reduced the venous recanalization rate. For the acute model, 100mW was considered an appropriate parameter for balancing moderate retinopathy and venous recanalization. Continuous imaging follow-up revealed that day 1 after RVO was the optimal observation point for peaking of retinal thickness and intensive occurrence of retinal cystic edema and intraretinal hemorrhage. After excluding the influence of venous recanalization on retinal thickness, acute retinal edema demonstrated a positive response to standard anti-vascular endothelial growth factor therapy, validating the clinical relevance of the acute RVO model for further study in pathogenic mechanisms and therapeutic efficacy. For the chronic model, the 120mW parameter with the lowest venous recanalization rate was applied, accompanied by an increase in both photocoagulation shots and range to ensure sustained vein occlusion. Imaging follow-up clarified non-ischemic retinopathy characterized by tortuosity and dilation of the distal end, branches, and adjacent veins of the occluded vein. These morphological changes are quantifiable and could be combined with electrophysiological functional assessment for treatment effectiveness evaluation. Moreover, the stable state of venous occlusion may facilitate investigations into response and compensation mechanisms under conditions of chronic retinal hypoperfusion.

Transfer RNA-derived fragment tRF-23-Q99P9P9NDD promotes progression of gastric cancer by targeting ACADSB. / 转移RNA衍生片段tRF-23-Q99P9P9NDD通过靶向ACADSB促进胃癌进展.

Gastric cancer (GC) is one of the most common gastrointestinal tumors. As a newly discovered type of non-coding RNAs, transfer RNA (tRNA)|-derived small RNAs (tsRNAs) play a dual biological role in cancer. Our previous studies have demonstrated the potential of tRF-23-Q99P9P9NDD as a diagnostic and prognostic biomarker for GC. In this work, we confirmed for the first time that tRF-23-Q99P9P9NDD can promote the proliferation, migration, and invasion of GC cells in vitro. The dual luciferase reporter gene assay confirmed that tRF-23-Q99P9P9NDD could bind to the 3' untranslated region (UTR) site of acyl-coenzyme A dehydrogenase short/branched chain (ACADSB). In addition, ACADSB could rescue the effect of tRF-23-Q99P9P9NDD on GC cells. Next, we used Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) to find that downregulated ACADSB in GC may promote lipid accumulation by inhibiting fatty acid catabolism and ferroptosis. Finally, we verified the correlation between ACADSB and 12 ferroptosis genes at the transcriptional level, as well as the changes in reactive oxygen species (ROS) levels by flow cytometry. In summary, this study proposes that tRF-23-Q99P9P9NDD may affect GC lipid metabolism and ferroptosis by targeting ACADSB, thereby promoting GC progression. It provides a theoretical basis for the diagnostic and prognostic monitoring value of GC and opens up new possibilities for treatment.

Berbamine ameliorates DSS-induced colitis by inhibiting peptidyl-arginine deiminase 4-dependent neutrophil extracellular traps formation.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease with immune dysregulation affecting colon inflammatory response. Recent studies have highlighted that neutrophil extracellular traps (NETs) play an important role in the pathogenesis of UC. Berbamine (BBM), one of the bioactive ingredients extracted from Chinese herbal medicine Berberis vulgaris L, has attracted intensive attentions due to its significant anti-inflammatory activity and a marketing drug for treating leukemia in China. However, the exact role and potential molecular mechanism of BBM against UC remains elusive. In the present study, our results showed that BBM could markedly improve the pathological phenotype and the colon inflammation in mice with dextran sulfate sodium (DSS)-induced colitis. Then, comprehensive approaches combining network pharmacology and molecular docking analyses were employed to predict the therapeutic potential of BBM in treating UC by peptidyl-arginine deiminase 4 (PAD4), a crucial molecule involved in NETs formation. The molecular docking results showed BBM had a high affinity for PAD4 with a binding energy of -9.3 kcal/mol Moreover, PAD4 expression and NETs productions, including citrullination of histone H3 (Cit-H3), neutrophil elastase (NE), myeloperoxidase (MPO) in both neutrophils and colonic tissue were reduced after BBM administration. However, in the mice with DSS-induced colitis pretreated with GSK484, a PAD4-specific inhibitor, BBM could not further reduce disease related indexes, expression of PAD4 and NETs productions. Above all, the identification of PAD4 as a potential target for BBM to inhibit NETs formation in colitis provides novel insights into the development of BBM-derived drugs for the clinical management of UC.

An exploration on the machine-learning-based stroke prediction model.

Introduction: With the rapid development of artificial intelligence technology, machine learning algorithms have been widely applied at various stages of stroke diagnosis, treatment, and prognosis, demonstrating significant potential. A correlation between stroke and cytokine levels in the human body has recently been reported. Our study aimed to establish machine-learning models based on cytokine features to enhance the decision-making capabilities of clinical physicians. Methods: This study recruited 2346 stroke patients and 2128 healthy control subjects from Chongqing University Central Hospital. A predictive model was established through clinical experiments and collection of clinical laboratory tests and demographic variables at admission. Three classification algorithms, namely Random Forest, Gradient Boosting, and Support Vector Machine, were employed. The models were evaluated using methods such as ROC curves, AUC values, and calibration curves. Results: Through univariate feature selection, we selected 14 features and constructed three machine-learning models: Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Machine (GBM). Our results indicated that in the training set, the RF model outperformed the GBM and SVM models in terms of both the AUC value and sensitivity. We ranked the features using the RF algorithm, and the results showed that IL-6, IL-5, IL-10, and IL-2 had high importance scores and ranked at the top. In the test set, the stroke model demonstrated a good generalization ability, as evidenced by the ROC curve, confusion matrix, and calibration curve, confirming its reliability as a predictive model for stroke. Discussion: We focused on utilizing cytokines as features to establish stroke prediction models. Analyses of the ROC curve, confusion matrix, and calibration curve of the test set demonstrated that our models exhibited a strong generalization ability, which could be applied in stroke prediction.

Effects of Cadmium and Lead Co-exposure on Sleep Status in Rural Areas Northwestern China.

In this study, we explored how cadmium and lead co-exposure affects sleep status among residents of a polluted area and nature reserve in rural northwestern China. Cadmium and lead levels were measured using blood samples, and sleep status was evaluated using sleep questionnaires, with the main sleep indicators including sleep duration, sleep quality, bedtime, and staying up. Furthermore, cadmium-lead co-exposure levels were divided into three groups: high exposure, medium exposure, and low exposure. Subjects in the contaminated area had significantly higher exposure levels (p < 0.001) and more negative sleep indicators (p < 0.01). Significant differences were found for all four sleep indicators in the high exposure group compared to the low exposure group (p < 0.01). Moreover, the overall evaluation of sleep status with high cadmium-lead co-exposure had a negative impact. Our data suggest that cadmium-lead co-exposure has a negative effect on sleep status and may have a synergistic effect on sleep.

Narrowband Organic/Inorganic Hybrid Afterglow Materials.

Narrowband afterglow materials display interesting functions in high-quality anti-counterfeiting and multiplexed bioimaging. However, there is still a limited exploration of these afterglow materials, especially for those with a full width at half maxima (FWHM) around 30 nm. Here, we report the fabrication of narrowband organic/inorganic hybrid afterglow materials via energy transfer technology. Coronene (Cor) with a long phosphorescence feature and broad phosphorescence band is selected as the donor for energy transfer, and inorganic quantum dots (QDs) of CdSe/ZnS with a narrowband emission are used as acceptors. Upon doping into the organic matrix, the resultant three-component materials exhibit a narrowband afterglow with an afterglow lifetime of approximately 3.4 s and an FWHM of 31 nm. The afterglow wavelength of the afterglow materials can be controlled by the QDs. This work based on organic/inorganic hybrids provides a facile approach for developing multicolor and narrowband afterglow materials, as well as opens a new way for expanding the features of organic afterglow for multifunctional applications. It is expected to rely on narrowband afterglow emitters to solve the "spectrum congestion" problem of high-density information storage in optical anti-counterfeiting and information encryption.

Microstructure and Texture Evolution in Cold-Rolled and Annealed Oxygen-Free Copper Sheets.

Commercial oxygen-free copper sheets were cold-rolled with reduction rates ranging from 20% to 87% and annealed at 400, 500 and 600 °C. The microstructure and texture evolution during the cold-rolling and annealing processes were studied using optical microscopy (OM), scanning electron microscopy (SEM) and electron back-scattered diffraction (EBSD). The results show that the deformation textures of {123}<634> (S), {112}<111> (Copper) and {110}<112> (Brass) were continuously enhanced with the increase in cold-rolling reduction. The orientations along the α-oriented fiber converged towards Brass, and the orientation density of ß fiber obviously increased when the rolling reduction exceeded 60%. The recrystallization texture was significantly affected by the cold-rolling reduction. After 60% cold-rolling reduction, Copper and S texture components gradually decreased, and the {011}<511> recrystallization texture component formed with the increase in annealing temperature. After 87% cold-rolling reduction, a strong Cube texture formed, and other textures were inhibited with the increase in annealing temperature. The strong Brass and S deformation texture was conducive to the formation of a strong Cube annealing texture. The density of the annealing twin boundary decreased with the increase in annealing temperature, and more annealing twin boundaries formed in the oxygen-free copper sheets with the increase in cold-rolling reduction.

Enhancing Methane Gas Sensing through Defect Engineering in Ag-Ru Co-doped ZnO Nanorods.

Detection of leaks of flammable methane (CH4) gas in a timely manner can mitigate health, safety, and environmental risks. Zinc oxide (ZnO), a polar semiconductor with controllable surface defects, is a promising material for gas sensing. In this study, Ag-Ru co-doped into self-assembled ZnO nanorod arrays (ZnO NRs) was prepared by a one-step hydrothermal method. The Ag-Ru co-doped sample shows a good hydrophobic property as a result of its particular microstructure, which results in high humidity resistance. In addition, oxygen vacancy density significantly increased after Ag-Ru co-doping. Density functional theory (DFT) calculations revealed an exceptionally high charge density accumulated at the Ru sites and the formation of a localized strong electric field, which provides additional energy for the CH4 reaction with •O2- at the surface at room temperature. Optimized AgRu0.025-ZnO demonstrated an outstanding CH4 sensing performance, with a limit of detection (LOD) as low as 2.24 ppm under free-heat and free-light conditions. These findings suggest that introducing defects into the ZnO lattice, such as oxygen vacancies and localized ions, offers a promising approach to improving the gas sensing performance.

The possibly role of GnIH in stress and gut dysfunction in chicken.

Stress is known to disrupt the intestinal barrier and induce intestinal dysfunction. A critical role for gonadotropin inhibitory hormone (GnIH) in stress has emerged. However, whether GnIH mediates stress-induced intestinal dysfunction remains unknown. The present study explored this question through in vivo and in vitro experiments in hens. Our in vivo experiments showed that continuous intraperitoneal injection of GnIH not only significantly increased the concentration of stress hormones in serum, but also significantly elevated the mRNA expression of glucocorticoid receptor (GR) in the duodenum and jejunum. Moreover, morphological and molecular analyses revealed that GnIH disrupted the physical and chemical barriers of the intestine and dramatically increased inflammatory factor levels in the intestine and serum of hens. Interestingly, the microbiomics results showed that GnIH altered the structure and composition of the gut flora in the cecum, revealing an increased abundance of harmful intestinal bacteria such as Desulfovibrionaceae. Similar results were found in in vitro studies in which the GnIH-induced intestinal mucosal barrier was disrupted, and inflammation increased in jejunal explants, although no significant difference was found in the expression of GR between the control and GnIH groups. Our results demonstrated that GnIH not only directly damaged intestinal barriers and elevated intestinal inflammation but also mediated stress and microflora imbalance-induced intestinal function disorder, suggesting that GnIH is a potential therapeutic target for gut dysfunction, stress-induced intestinal function disorder, and inflammatory bowel disease in animals and humans.

Peripheral 5-HT Mediates Gonadotropin-Inhibitory Hormone-Induced Feeding Behavior and Energy Metabolism Disorder in Chickens via the 5-HT2C Receptor.

INTRODUCTION: Since the discovery of gonadotropin-inhibitory hormone (GnIH), it has been found to play a critical role in reproduction in vertebrates. Recently, a regulatory role of GnIH in appetite and energy metabolism has emerged, although its precise physiological mechanisms remain unknown. METHODS: Thus, the present study evaluated the effects of a single or long-term intraperitoneal GnIH treatment on the food intake, weight, and glucolipid metabolism of chickens, as well as investigating the possible neuroendocrinology factors and mechanisms involved in GnIH-induced obesity and glucolipid metabolism disorder. RESULTS: Our results show that the intraperitoneal administration of GnIH to chickens resulted in a marked body mass increase, hyperlipidemia, hyperglycemia, and glucose intolerance. Subsequently, the results of metabolomics studies and the pharmacological inhibition of the 5-HT2C receptor revealed that blocking the 5-HT2C receptor reinforced the effects of GnIH on food intake, body weight, and blood glucose and lipid levels, resulting in even worse cases of GnIH-induced hyperglycemia, hyperlipidemia, and hepatic lipid deposition. This suggests that, via the 5-HT2C receptor, peripheral 5-HT may act as a negative feedback regulator to interplay with GnIH and jointly control energy balance homeostasis in chickens. DISCUSSION: Our present study provides evidence of cross-talk between GnIH and 5-HT in food intake and energy metabolism at the in vivo pharmacological level, and it proposes a molecular basis for these interactions, suggesting that functional interactions between GnIH and 5-HT may open new avenues for understanding the mechanism of the neuroendocrine network involved in appetite and energy metabolism, as well as providing a new therapeutic strategy to prevent obesity, diabetes, and metabolic disorders.

CBX7 silencing promoted liver regeneration by interacting with BMI1 and activating the Nrf2/ARE signaling pathway.

Multiple studies have shown knockdown of chromobox 7 (CBX7) promotes the regenerative capacity of various cells or tissues. We examined the effect of CBX7 on hepatocyte proliferation and liver regeneration after 2/3 hepatectomy in a mouse model. For in vitro experiments, NCTC 1469 and BNL CL.2 hepatocytes were co-transfected with siRNA-CBX7-1 (si-CBX7-1), siRNA-CBX7-2 (si-CBX7-2), pcDNA-CBX7, si-BMI1-1, si-BMI1-2, pcDNA-BMI1, or their negative control. For in vivo experiments, mice were injected intraperitoneally with lentivirus-packaged shRNA and shRNA CBX7 before hepatectomy. Our results showed that CBX7 was rapidly induced in the early stage of liver regeneration. CBX7 regulated hepatocyte proliferation, cell cycle, and apoptosis of NCTC 1469 and BNL CL.2 hepatocytes. CBX7 interacted with BMI1 and inhibited BMI1 expression in hepatocytes. Silencing BMI1 aggregated the inhibitory effect of CBX7 overexpression on hepatocyte viability and the promotion of apoptosis. Furthermore, silencing BMI1 enhanced the regulatory effect of CBX7 on Nrf2/ARE signaling in HGF-induced hepatocytes. In vivo, CBX7 silencing enhanced liver/body weight ratio in PH mice. CBX7 silencing promoted the Ki67-positive cell count and decreased the Tunel-positive cell count after hepatectomy, and also increased the expression of nuclear Nrf2, HO-1, and NQO-1. Our results suggest that CBX7 silencing may increase survival following hepatectomy by promoting liver regeneration.

Assessment of the role of false-positive alerts in computer-aided polyp detection for assistance capabilities.

BACKGROUND AND AIM: False positives (FPs) pose a significant challenge in the application of artificial intelligence (AI) for polyp detection during colonoscopy. The study aimed to quantitatively evaluate the impact of computer-aided polyp detection (CADe) systems' FPs on endoscopists. METHODS: The model's FPs were categorized into four gradients: 0-5, 5-10, 10-15, and 15-20 FPs per minute (FPPM). Fifty-six colonoscopy videos were collected for a crossover study involving 10 endoscopists. Polyp missed rate (PMR) was set as primary outcome. Subsequently, to further verify the impact of FPPM on the assistance capability of AI in clinical environments, a secondary analysis was conducted on a prospective randomized controlled trial (RCT) from Renmin Hospital of Wuhan University in China from July 1 to October 15, 2020, with the adenoma detection rate (ADR) as primary outcome. RESULTS: Compared with routine group, CADe reduced PMR when FPPM was less than 5. However, with the continuous increase of FPPM, the beneficial effect of CADe gradually weakens. For secondary analysis of RCT, a total of 956 patients were enrolled. In AI-assisted group, ADR is higher when FPPM ≤ 5 compared with FPPM > 5 (CADe group: 27.78% vs 11.90%; P = 0.014; odds ratio [OR], 0.351; 95% confidence interval [CI], 0.152-0.812; COMBO group: 38.40% vs 23.46%, P = 0.029; OR, 0.427; 95% CI, 0.199-0.916). After AI intervention, ADR increased when FPPM ≤ 5 (27.78% vs 14.76%; P = 0.001; OR, 0.399; 95% CI, 0.231-0.690), but no statistically significant difference was found when FPPM > 5 (11.90% vs 14.76%, P = 0.788; OR, 1.111; 95% CI, 0.514-2.403). CONCLUSION: The level of FPs of CADe does affect its effectiveness as an aid to endoscopists, with its best effect when FPPM is less than 5.

A latent profile analysis of psychological resilience in gastric cancer survivors: A cross-sectional study.

PURPOSE: To characterize patterns of psychological resilience in gastric cancer survivors using latent profile analyses and to explore the factors influencing these latent profiles based on Kumpfer's resilience framework. METHODS: Five hundred eighty-six gastric cancer survivors were recruited between July 30, 2021, and May 1, 2023. A demographic and clinical characteristics questionnaire, Connor and Davidson's Resilience Scale (CD-RISC), Fear of Progression Questionnaire Short Form (FoP-Q-SF), General Self-efficacy Scale (GSES), Medical Coping Modes Questionnaire (MCMQ), and Social Support Rating Scale (SSRS) were used for the investigation. Latent profile analysis of the resilience of gastric cancer survivors was conducted, and the factors influencing the latent profiles were explored by multivariate logistic regression analysis. RESULTS: A total of 586 questionnaires were collected, and 572 were valid, with an effective recovery rate of 97.61%. The results of latent profile analysis showed that the resilience of gastric cancer survivors was divided into four subgroups, namely, the low-resilience group (18.4%), moderate-resilience group (43.2%), medium-high-resilience group (30.2%), and high-resilience group (8.2%). Multivariate logistic regression analysis showed that fear of disease progression, self-efficacy, medical coping mode and social support were influencing factors of subgroups. CONCLUSIONS: Psychological resilience in gastric cancer survivors is individualized. Nurses should assess risk and protective factors for survivor resilience based on Kumpfer's resilience framework, identify unique needs, and develop new approaches and interventions.

Bayesian analysis of physiologically based toxicokinetic (PBTK) modeling for pentachlorophenol exposure in pregnant women.

Pentachlorophenol (PCP) is a persistent organic compound that is widely present in the environment. The estimation of internal exposure levels for a given external exposure using toxicokinetic models is key to the human health risk assessment of PCP. The present study developed a physiologically based multicompartmental pharmacokinetic (PBTK) model to describe and predict the behavior of pentachlorophenol (PCP) in an organism. The model consists of stomach, intestines, adipose tissue, kidneys and fast- and poorly perfused tissues that are interconnected via blood circulation. We constructed a PBTK model of PCP in rats and extrapolated it to human dietary PCP exposure. The toxicokinetic data of PCP in human tissues and excreta were obtained from the published literature. Based on the collected PCP dietary survey and internal exposure data of pregnant women in Shanghai, Bayesian statistical analysis was performed for the model using Markov chain Monte Carlo (MCMC) simulation. The posterior distributions of the sensitive parameters were estimated, and the model was parameter optimized and validated using the pregnant women's test dataset. The results showed that the root mean square error (RMSE) improved 37.3% compared to the original model, and a systematic literature search revealed that the optimized model achieved acceptable prediction results for other datasets in China. A PCP metabolism model based on the exposure characteristics of pregnant women in China was constructed in the present study. The model provides a theoretical basis for the study of PCP toxicity and risk assessment.

Development and validation of an early mortality risk model for pediatric hemophagocytic lymphohistiocytosis: a comparison with HScore, PELOD-2, P-MODS, and pSOFA.

There has been no severity evaluation model for pediatric patients with hemophagocytic lymphohistiocytosis (HLH) that uses readily available parameters. This study aimed to develop a novel model for predicting the early mortality risk in pediatric patients with HLH using easily obtained parameters whatever etiologic subtype. Patients from one center were divided into training and validation sets for model derivation. The developed model was validated using an independent validation cohort from the second center. The prediction model with nomogram was developed based on logistic regression. The model performance underwent internal and external evaluation and validation using the area under the receiver operating characteristic curve (AUC), calibration curve with 1000 bootstrap resampling, and decision curve analysis (DCA). Model performance was compared with the most prevalent severity evaluation scores, including the PELOD-2, P-MODS, and pSOFA scores. The prediction model included nine variables: glutamic-pyruvic transaminase, albumin, globulin, myohemoglobin, creatine kinase, serum potassium, procalcitonin, serum ferritin, and interval between onset and diagnosis. The AUC of the model for predicting the 28-day mortality was 0.933 and 0.932 in the training and validation sets, respectively. The AUC values of the HScore, PELOD-2, P-MODS and pSOFA were 0.815, 0.745, 0.659 and 0.788, respectively. The DCA of the 28-day mortality prediction exhibited a greater net benefit than the HScore, PELOD-2, P-MODS and pSOFA. Subgroup analyses demonstrated good model performance across HLH subtypes. The novel mortality prediction model in this study can contribute to the rapid assessment of early mortality risk after diagnosis with readily available parameters.