White matter integrity of right frontostriatal circuit predicts internet addiction severity among internet gamers.

Excessive use of the internet, which is a typical scenario of self-control failure, could lead to potential consequences such as anxiety, depression, and diminished academic performance. However, the underlying neuropsychological mechanisms remain poorly understood. This study aims to investigate the structural basis of self-control and internet addiction. In a cohort of 96 internet gamers, we examined the relationships among grey matter volume and white matter integrity within the frontostriatal circuits and internet addiction severity, as well as self-control measures. The results showed a significant and negative correlation between dACC grey matter volume and internet addiction severity (p < 0.001), but not with self-control. Subsequent tractography from the dACC to the bilateral ventral striatum (VS) was conducted. The fractional anisotropy (FA) and radial diffusivity of dACC-right VS pathway was negatively (p = 0.011) and positively (p = 0.020) correlated with internet addiction severity, respectively, and the FA was also positively correlated with self-control (p = 0.036). These associations were not observed for the dACC-left VS pathway. Further mediation analysis demonstrated a significant complete mediation effect of self-control on the relationship between FA of the dACC-right VS pathway and internet addiction severity. Our findings suggest that the dACC-right VS pathway is a critical neural substrate for both internet addiction and self-control. Deficits in this pathway may lead to impaired self-regulation over internet usage, exacerbating the severity of internet addiction.

Mental Health and Quality of Life in Chronic Kidney Disease Patients with Mild-to-Moderate Depression: A Retrospective Cohort Study of Mindfulness-Based Stress Reduction Therapy.

BACKGROUND: Chronic kidney disease (CKD) patients may experience pessimism, and even despair, due to long-term nature of the condition, which increases the risk of depression. Mindfulness-based stress reduction (MBSR) can relieve depression. This retrospective cohort study aimed to investigate the effects of MBSR on mental health and quality of life in CKD patients with mild-to-moderate depression, so as to provide guidance for clinical nursing programs. METHODS: The clinical data of 100 CKD patients with mild-to-moderate depression who were treated in Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences from January 2021 to March 2023 were retrospectively analyzed. Based on nursing method received, the patients were divided into the conventional group (conventional management) and the MBSR group (MBSR therapy was implemented in addition to conventional management). After matching, there were 35 cases in each group. The scores for the self-rating depression scale (SDS), Connor-Davidson Resilience Scale (CD-RISC), Five-factor Mindfulness Questionnaire (FFMQ), Pittsburgh Sleep Quality Index (PSQI), and 36-item Short Form Health Survey (SF-36) were compared between the two groups. RESULTS: After management, the SDS and PSQI scores of the MBSR group were lower than those of the conventional group, and the CD-RISC, FFMQ and SF-36 scores were higher than those of the conventional group (p < 0.05). CONCLUSION: MBSR can improve the mental health, sleep quality, and quality of life of CKD patients with mild-to-moderate depression, and improve psychological resilience and mindfulness.

Effects of Designed Herbal Formula on Growth Performance, Blood Indices, Organ Traits, and Cecum Microbiology in Broilers.

The objective of this study was to investigate the effect of the designed herbal formula (DHF) on growth performance, blood indices, organ traits, and cecum microbiology in broilers. A total of 96 male broilers of 1 d were selected and randomly assigned to two groups with six replicates of eight broilers each. The control (CON) and the basal diet containing 1.0% DHF (Astragali radix, Atractylodes macrocephala Koidz., Isatis tinctoria Linnaeus, and Citri reticulatae pericarpium, 2:1:1:2) were fed separately. The experiment was conducted for 35 days. The results showed that the DHF diet increased body weight and decreased the feed conversion ratio (FCR) (p < 0.05). At 21 days, the spleen, thymus, lymphocytes, and thrombocytes were increased (p < 0.05), and pancreas, duodenum, heterophils, and mean corpuscular hemoglobin (MCH) were decreased (p < 0.05). At 35 days, the heart, pancreas, white blood cell, heterophils, hemoglobin, MCH and mean corpuscular hemoglobin concentration (MCHC) were decreased, while lymphocytes and middle cells were increased (p < 0.05). The results of microbial diversity analysis showed that the DHF diet decreased the microbial diversity of the cecum. Firmicutes and Bacteroidetes were the dominant phyla, where the DHF diet increased the relative abundances of Bacteroides uniformis, Bacteroides vulgatus, and Faecalibacterium prausnitzii, and then decreased the relative abundance of Shigella sonnei. In conclusion, DHF played a positive role in improving the growth performance, immune performance, and relative abundance of Bacteroides uniformis, Bacteroides vulgatus, and Faecalibacterium prausnitzii in cecum microbiology in broilers, and has the potential to be used as a novel feed additive.

The Critical Role of Leadership in Patient Safety Culture: A Mediation Analysis of Management Influence on Safety Factors.

Purpose: This research aims to investigate the role of management leadership in promoting a culture of patient safety within healthcare organizations. Through a comprehensive mediation analysis of the Chinese version of the safety attitudes questionnaire (CSAQ) and patient safety culture, the study examines the interplay between these critical factors and their combined influence on healthcare outcomes. Patients and Methods: In a medical center located in Taiwan, a cross-sectional survey was carried out utilizing the CSAQ. Among the 1500 distributed surveys, 1037 were returned and deemed valid, resulting in a return rate of 69.13%. To investigate the main measures, Structural Equation Modeling with mediation analysis was employed to scrutinize the direct and indirect effects of factors including teamwork climate, job satisfaction, stress recognition, perceptions of management, working conditions, and emotional exhaustion on safety climate. Results: The findings reveal that effective management leadership plays a pivotal role in shaping safety attitudes and fostering a robust patient safety culture. The study identifies three critical facets of patient safety that are entirely mediated by management perceptions: teamwork climate, working conditions, and stress recognition. The results highlight the importance of enhancing these dimensions to advance the patient safety culture within healthcare organizations. Moreover, stress recognition is identified as a critical factor influencing the organizational culture of patient safety. Conclusion: This research offers valuable insights for healthcare organizations seeking to prioritize patient safety and improve overall quality of care. By enhancing our understanding of the critical factors that shape safety attitudes and patient safety culture, this study provides a roadmap for effective management leadership and a culture of patient safety within healthcare organizations. The study underscores the significance of management leadership in promoting patient safety culture and highlights the importance of enhancing teamwork climate, working conditions, and stress recognition to advance patient safety culture.

NASP gene contributes to autism by epigenetic dysregulation of neural and immune pathways.

BACKGROUND: Epigenetics makes substantial contribution to the aetiology of autism spectrum disorder (ASD) and may harbour a unique opportunity to prevent the development of ASD. We aimed to identify novel epigenetic genes involved in ASD aetiology. METHODS: Trio-based whole exome sequencing was conducted on ASD families. Genome editing technique was used to knock out the candidate causal gene in a relevant cell line. ATAC-seq, ChIP-seq and RNA-seq were performed to investigate the functional impact of knockout (KO) or mutation in the candidate gene. RESULTS: We identified a novel candidate gene NASP (nuclear autoantigenic sperm protein) for epigenetic dysregulation in ASD in a Chinese nuclear family including one proband with autism and comorbid atopic disease. The de novo likely gene disruptive variant tNASP(Q289X) subjects the expression of tNASP to nonsense-mediated decay. tNASP KO increases chromatin accessibility, promotes the active promoter state of genes enriched in synaptic signalling and leads to upregulated expression of genes in the neural signalling and immune signalling pathways. Compared with wild-type tNASP, tNASP(Q289X) enhances chromatin accessibility of the genes with enriched expression in the brain. RNA-seq revealed that genes involved in neural and immune signalling are affected by the tNASP mutation, consistent with the phenotypic impact and molecular effects of nasp-1 mutations in Caenorhabditis elegans. Two additional patients with ASD were found carrying deletion or deleterious mutation in the NASP gene. CONCLUSION: We identified novel epigenetic mechanisms mediated by tNASP which may contribute to the pathogenesis of ASD and its immune comorbidity.

Revealing Novel Genomic Insights and Therapeutic Targets for Juvenile Idiopathic Arthritis through Omics.

BACKGROUND: The genetic architecture of juvenile idiopathic arthritis (JIA) remains only partially comprehended. There is a clear imperative for continued endeavors to uncover insights into the underlying causes of JIA. METHODS: This study encompassed a comprehensive spectrum of endeavors, including conducting a JIA GWAS meta-analysis that incorporated data from 4,550 JIA cases and 18 446 controls. We employed in silico and genome-editing approaches to prioritize target genes. To investigate pleiotropic effects, we conducted phenome-wide association studies. Cell-type enrichment analyses were performed by integrating bulk and single-cell sequencing data. Finally, we delved into potential druggable targets for JIA. RESULTS: Fourteen genome-wide significant non-HLA loci were identified including four novel loci, each exhibiting pleiotropic associations with other autoimmune diseases or musculoskeletal traits. We uncovered strong genetic correlation between JIA and bone mineral density (BMD) traits at 52 genomic regions, including three GWAS loci for JIA. Candidate genes with immune functions were captured by in silico analyses at each novel locus, with additional findings identified through our experimental approach. Cell-type enrichment analysis revealed 21 specific immune cell types crucial for affected organs in JIA, indicating their potential contribution to the disease. Finally, 24 known or candidate druggable target genes were prioritized. CONCLUSIONS: Our identification of four novel JIA associated genes, CD247, RHOH, COLEC10 and IRF8, broadens novel potential drug repositioning opportunities. We established a new genetic link between COLEC10, TNFRSF11B and JIA/BMD. Additionally, the identification of RHOH underscores its role in positive thymocyte selection, thereby illuminating a critical facet of JIA's underlying biological mechanisms.

Effects of Heat Stress on Breast Muscle Metabolomics and Lipid Metabolism Related Genes in Growing Broilers.

With global warming and worsening climatic conditions, heat stress (HS) has become a significant challenge affecting the development of poultry production. In this study, we aimed to determine the effects of HS on breast muscle metabolomics and lipid metabolism-related genes in growing broilers. One hundred twenty 29-day-old Arbor Acres broilers were randomly divided into normal temperature (NT; 21 ± 1 °C) and heat stress (HS; 31 ± 1 °C) groups, with six replicates (ten birds in each replicate) in each group, raised for 14 days in two environment chambers at 60 ± 7% relative humidity. Compared with the broilers in the NT group, the average daily food intake, average daily gain and breast muscle yield in the HS group were significantly lower (p < 0.05). The feed conversion ratio was significantly higher in the HS group (p < 0.05). The concentrations of serum corticosterone, free fatty acids and cholesterol and the percentage of abdominal fat of broilers in the HS group were significantly higher (p < 0.05) than the values of the broilers in the NT group. Untargeted breast muscle metabolome analysis revealed 14 upregulated differential metabolites, including glycerophosphocholine, and 27 downregulated differential metabolites, including taurine, in the HS group compared to the NT group; the HS group also displayed significant effects on six metabolic pathways compared to the NT group (p < 0.05). The mRNA expression levels of peroxisome proliferator-activated receptor gamma coactivator-1-alpha, peroxisome proliferator-activated receptor alpha (PPARα) and ATP-binding cassette transporter A1 in the liver and breast muscles were significantly decreased in the HS group compared with the NT group (p < 0.05). The collective findings reveal that HS can cause disorders in breast muscle lipid metabolism in broilers. The PPARα gene might be the key gene in the mechanism of the lipid metabolism that is induced by HS in breast muscle of broilers. These findings provide novel insights into the effects of HS on chicken growth.

Target genes regulated by CLEC16A intronic region associated with common variable immunodeficiency.

BACKGROUND: CLEC16A intron 19 has been identified as a candidate locus for common variable immunodeficiency (CVID). OBJECTIVES: This study sought to elucidate the molecular mechanism by which variants at the CLEC16A intronic locus may contribute to the pathogenesis of CVID. METHODS: The investigators performed fine-mapping of the CLEC16A locus in a CVID cohort, then deleted the candidate functional SNP in T-cell lines by the CRISPR-Cas9 technique and conducted RNA-sequencing to identify target gene(s). The interactions between the CLEC16A locus and its target genes were identified using circular chromosome conformation capture. The transcription factor complexes mediating the chromatin interactions were determined by proteomic approach. The molecular pathways regulated by the CLEC16A locus were examined by RNA-sequencing and reverse phase protein array. RESULTS: This study showed that the CLEC16A locus is an enhancer regulating expression of multiple target genes including a distant gene ATF7IP2 through chromatin interactions. Distinct transcription factor complexes mediate the chromatin interactions in an allele-specific manner. Disruption of the CLEC16A locus affects the AKT signaling pathway, as well as the molecular response of CD4+ T cells to immune stimulation. CONCLUSIONS: Through multiomics and targeted experimental approaches, this study elucidated the underlying target genes and signaling pathways involved in the genetic association of CLEC16A with CVID, and highlighted plausible molecular targets for developing novel therapeutics.

Long Non-Coding RNAs: Discoveries, Mechanisms, and Research Strategies in Seeds.

Seeds provide nutrients for the embryo and allow for dormancy in stressed environments to better adapt the plant to its environment. In addition, seeds are an essential source of food for human survival and are the basis for the formation of food production and quality. Therefore, the research on the genetic mechanism of seed development and germination will provide a theoretical basis and technical support for the improvement of crop yield and quality. Recent studies have shown that long non-coding RNAs (lncRNAs) occupy a pivotal position in seed development and germination. In this review, we describe the key processes in seed biology and examine discoveries and insights made in seed lncRNA, with emphasis on lncRNAs that regulate seed biology through multiple mechanisms. Given that thousands of lncRNAs are present in the seed transcriptome, characterization has lagged far behind identification. We provide an overview of research strategies and approaches including some exciting new techniques that may uncover the function of lncRNAs in seed. Finally, we discuss the challenges facing the field and the opening questions. All in all, we hope to provide a clear perspective on discoveries of seed lncRNA by linking discoveries, mechanisms, and technologies.

The Effect of Preventing Oxidative Stress and Its Mechanisms in the Extract from Sonchus brachyotus DC. Based on the Nrf2-Keap1-ARE Signaling Pathway.

As the organ with the largest contact area with the outside world, the intestine is home to a large number of microorganisms and carries out the main functions of food digestion, absorption, and metabolism. Therefore, there is a very active metabolism of substances and energy in the gut, which is easily attacked by oxygen free radicals. What is more, oxidative stress can gradually and slowly cause very serious damage to the gut. Hence, maintaining redox balance is essential for maintaining environmental balance in the gut. Our previous studies have demonstrated that the extract of Sonchus brachyotus DC. (SBE) has been shown to be capable of repairing oxidative damage, while it has not been demonstrated that it can prevent oxidative stress or how it develops. In this work, we investigated the prevention of oxidative stress and its mechanism in SBE based on the H2O2-induced oxidative damage model in Caco-2 cells; the results indicate that SBE can reduce the contents of ROS and MDA and increase the activities of SOD and CAT in preventing oxidative stress. Then, at the mRNA and protein level, SBE can up-regulate and down-regulate the expression of related genes (NFE2L2, KEAP1, HMOX1, NQO1, SOD1, CAT, and GPX1) and proteins involved in the Nrf2-Keap1-ARE signaling pathway. In conclusion, SBE plays a preventive role in oxidative stress through the Nrf2-Keap1-ARE signaling pathway.

Benefits of Combining Sonchus brachyotus DC. Extracts and Synbiotics in Alleviating Non-Alcoholic Fatty Liver Disease.

Non-alcoholic fatty liver disease, commonly abbreviated to NAFLD, is a pervasive ailment within the digestive system, exhibiting a rising prevalence, and impacting individuals at increasingly younger ages. Those afflicted by NAFLD face a heightened vulnerability to the onset of profound liver fibrosis, cardiovascular complications, and malignancies. Currently, NAFLD poses a significant threat to human health, and there is no approved therapeutic treatment for it. Recent studies have shown that synbiotics, which regulate intestinal microecology, can positively impact glucolipid metabolism, and improve NAFLD-related indicators. Sonchus brachyotus DC., a Chinese herb, exhibits hepatoprotective and potent antioxidant properties, suggesting its potential therapeutic use in NAFLD. Our preclinical animal model investigation suggests that the synergy between Sonchus brachyotus DC. extracts and synbiotics is significantly more effective in preventing and treating NAFLD, compared to the isolated use of either component. As a result, this combination holds the potential to introduce a fresh and encouraging therapeutic approach to addressing NAFLD.

Early acquired resistance to EGFR-TKIs in lung adenocarcinomas before radiographic advanced identified by CT radiomic delta model based on two central studies.

Early acquired resistance (EAR) to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in lung adenocarcinomas before radiographic advance cannot be perceived by the naked eye. This study aimed to discover and validate a CT radiomic model to precisely identify the EAR. Training cohort (n = 67) and internal test cohort (n = 29) were from the First Affiliated Hospital of Fujian Medical University, and external test cohort (n = 29) was from the Second Affiliated Hospital of Xiamen Medical College. Follow-up CT images at three different times of each patient were collected: (1) baseline images before EGFR-TKIs therapy; (2) first follow-up images after EGFR-TKIs therapy (FFT); (3) EAR images, which were the last follow-up images before radiographic advance. The features extracted from FFT and EAR were used to construct the classic radiomic model. The delta features which were calculated by subtracting the baseline from either FFT or EAR were used to construct the delta radiomic model. The classic radiomic model achieved AUC 0.682 and 0.641 in training and internal test cohorts, respectively. The delta radiomic model achieved AUC 0.730 and 0.704 in training and internal test cohorts, respectively. Over the external test cohort, the delta radiomic model achieved AUC 0.661. The decision curve analysis showed that when threshold of the probability of the EAR to the EGFR-TKIs was between 0.3 and 0.82, the proposed model was more benefit than treating all patients. Based on two central studies, the delta radiomic model derived from the follow-up non-enhanced CT images can help clinicians to identify the EAR to EGFR-TKIs in lung adenocarcinomas before radiographic advance and optimize clinical outcomes.

Application value of CT radiomic nomogram in predicting T790M mutation of lung adenocarcinoma.

BACKGROUND: The purpose of this study was to develop a radiomic nomogram to predict T790M mutation of lung adenocarcinoma base on non-enhanced CT lung images. METHODS: This retrospective study reviewed demographic data and lung CT images of 215 lung adenocarcinoma patients with T790M gene test results. 215 patients (including 52 positive) were divided into a training set (n = 150, 36 positive) and an independent test set (n = 65, 16 positive). Multivariate logistic regression was used to select demographic data and CT semantic features to build clinical model. We extracted quantitative features from the volume of interest (VOI) of the lesion, and developed the radiomic model with different feature selection algorithms and classifiers. The models were trained by a 5-fold cross validation strategy on the training set and assessed on the test set. ROC was used to estimate the performance of the clinical model, radiomic model, and merged nomogram. RESULTS: Three demographic features (gender, smoking, emphysema) and ten radiomic features (Kruskal-Wallis as selection algorithm, LASSO Logistic Regression as classifier) were determined to build the models. The AUC of the clinical model, radiomic model, and nomogram in the test set were 0.742(95%CI, 0.619-0.843), 0.810(95%CI, 0.696-0.907), 0.841(95%CI, 0.743-0.938), respectively. The predictive efficacy of the nomogram was better than the clinical model (p = 0.042). The nomogram predicted T790M mutation with cutoff value was 0.69 and the score was above 130. CONCLUSION: The nomogram developed in this study is a non-invasive, convenient, and economical method for predicting T790M mutation of lung adenocarcinoma, which has a good prospect for clinical application.

DARMF-UNet: A dual-branch attention-guided refinement network with multi-scale features fusion U-Net for gland segmentation.

Accurate gland segmentation is critical in determining adenocarcinoma. Automatic gland segmentation methods currently suffer from challenges such as less accurate edge segmentation, easy mis-segmentation, and incomplete segmentation. To solve these problems, this paper proposes a novel gland segmentation network Dual-branch Attention-guided Refinement and Multi-scale Features Fusion U-Net (DARMF-UNet), which fuses multi-scale features using deep supervision. At the first three layers of feature concatenation, a Coordinate Parallel Attention (CPA) is proposed to guide the network to focus on the key regions. A Dense Atrous Convolution (DAC) block is used in the fourth layer of feature concatenation to perform multi-scale features extraction and obtain global information. A hybrid loss function is adopted to calculate the loss of each segmentation result of the network to achieve deep supervision and improve the accuracy of segmentation. Finally, the segmentation results at different scales in each part of the network are fused to obtain the final gland segmentation result. The experimental results on the gland datasets Warwick-QU and Crag show that the network improves in terms of the evaluation metrics of F1 Score, Object Dice, Object Hausdorff, and the segmentation effect is better than the state-of-the-art network models.

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.

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.

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.

Amifostine-Loaded Nanocarrier Traverses the Blood-Brain Barrier and Prevents Radiation-Induced Brain Injury.

Radiation-induced brain injury (RIBI) is a severe, irreversible, or even life-threatening cerebral complication of radiotherapy in patients with head and neck tumors, and there is no satisfying prevention and effective treatment available for these patients. Amifostine (AMF) is a well-known free radical scavenger with demonstrated effectiveness in preventing radiation-induced toxicity. However, the limited permeability of AMF across the blood-brain barrier (BBB) when administered intravenously reduces the effectiveness of AMF in preventing RIBI. Herein, we construct a nanoparticle (NP) platform for BBB delivery of AMF. AMF is conjugated with 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine-n-[poly(ethylene glycol)]-hydroxy succinamide [DSPE-PEG-NHS, PEG M 2000], and the product is DSPE-PEG-AMF. Then, the nanoparticles (DAPP NPs) were formed by self-assembly of poly(lactic-co-glycolic acid) (PLGA), DSPE-PEG-AMF, and polysorbate 80 (PS 80). PEG shields the nanoparticles from blood clearance by the reticuloendothelial system and lengthens the drug circulation time. PS 80 is used to encapsulate nanoparticles for medication delivery to the brain. The results of our study showed that DAPP NPs were able to effectively penetrate the blood-brain barrier (BBB) in healthy C57BL/6 mice. Furthermore, in a well-established mouse model of X-knife-induced brain injury, treatment with DAPP NPs (corresponding to 250 mg/kg AMF) was found to significantly reduce the volume of brain necrosis compared to mice treated with AMF (250 mg/kg). Importantly, the use of DAPP NPs was also shown to significantly mitigate the effects of radiation-induced neuronal damage and glial activation. This work presents a convenient brain-targeted AMF delivery system to achieve effective radioprotection for the brain, providing a promising strategy with tremendous clinical translation potential.

The Interaction between Oxidative Stress Biomarkers and Gut Microbiota in the Antioxidant Effects of Extracts from Sonchus brachyotus DC. in Oxazolone-Induced Intestinal Oxidative Stress in Adult Zebrafish.

Oxidative stress is a phenomenon caused by an imbalance between the production and accumulation of reactive oxygen species in cells and tissues that eventually leads to the production of various diseases. Here, we investigated the antioxidant effects of the extract from Sonchus brachyotus DC. (SBE) based on the 0.2% oxazolone-induced intestinal oxidative stress model of zebrafish. Compared to the model group, the treatment group alleviated oxazolone-induced intestinal tissue damage and reduced the contents of malondialdehyde, reactive oxygen species, IL-1ß, and TNF-α and then increased the contents of superoxide dismutase, glutathione peroxidase, and IL-10. The 16s rDNA gene sequencing findings demonstrated that SBE could increase the relative abundance of Fusobacteriota, Actinobacteriota, and Firmicutes and decrease the relative abundance of Proteobacteria. Based on the correlation analysis between the oxidative stress biomarkers and intestinal flora, we found that the trends of oxidative stress biomarkers were significantly correlated with intestinal microorganisms, especially at the genus level. The correlations of MDA, IL-1ß, and TNF-α were significantly negative with Shewanella, while SOD, GSH-Px, and IL-10 were significantly positive with Cetobacterium, Gemmobacter, and Flavobacterium. Consequently, we concluded that the antioxidant effect of SBE was realized through the interaction between oxidative stress biomarkers and gut microbiota.