Conectar
by Min Wang, Yushun Yan, Wanqiu Yang, Ruini He, Lingdan Zhao, Yikai Dou, Yuanmei Tao, Xiao Yang, Qingqing Xiang, Xiaohong Ma
Psychiatric nurses represent a high-stress occupational group that experiences elevated levels of suicidal ideation (SI), emphasizing the need for focused mental health interventions. The main purpose of this study was to examine the prevalence of SI among psychiatric nurses and to identify the psychological and occupational factors associated with SI. A total of 1,835 psychiatric nurses completed questionnaires on depressive symptoms (PHQ-9), SI, quality of work-related life (QWL), and burnout. Multivariate logistic regression and phenotypic network analyses were conducted to identify factors associated with SI and the potential pathways linking depressive symptoms, burnout, and QWL to SI. The results indicated that 11.33% of the participants had SI in the past two weeks. Multivariate logistic regression revealed that emotional exhaustion, depersonalization, personal accomplishment, stress at work, general well-being, and the home-work interface were significant predictors of SI. Network analysis further revealed that psychomotor changes, guilt, sad mood, low energy, and appetite changes were the symptoms most directly associated with SI. In addition, sad mood, general well-being, and work-home interface were linked to job and career satisfaction, whereas sad mood and low energy were associated with emotional exhaustion and SI. These findings contribute valuable large-scale evidence on the mental health challenges faced by psychiatric nurses and highlight the importance of addressing mood disturbances, energy loss, and work-related stress in SI prevention efforts for this vulnerable group.by Florence L. Meier, Levy Jäger, Oliver Senn, Stefan Markun, Jakob M. Burgstaller
RegistrationProspero (CRD42024506727).
by Jiangfa Li, Wenxiang Song, Jixue Li, Lv Cai, Zhao Jiang, Mengxiao Wei, Boming Nong, Meiyu Lai, Yiyi Jiang, Erbo Zhao, Liping Lei
ObjectiveTo develop a predictive model for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) through radiomics analysis, integrating data from both enhanced computed tomography (CT) and magnetic resonance imaging (MRI).
MethodsA retrospective analysis was conducted on 93 HCC patients who underwent partial hepatectomy. The gold standard for MVI was based on the histopathological diagnosis of the tissue. The 93 patients were randomly divided into training and validation groups in 7:3 ratio. The imaging data of patients, including CT and MRI, were collected and processed using 3D Slicer to delineate the region of interest (ROI) for each tumor. Radiomics features were extracted from CT and MRI of patients using Python. Lasso regression analysis was used to select optimal radiomics features for MVI in the training group. The optimal radiomics features of CT and MRI were selected to establish the prediction model. The predictive performance of the model was evaluated using the receiver operator characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).
ResultsAfter univariate and multivariate analyses, it was found that tumor diameter was significantly different between the MVI positive and negative groups. After extracting 2153 imaging phenotyping features from the CT and MRI images of the 93 patients using Python, ten standardized coefficient non-zero imaging phenotyping features were finally determined by Lasso regression analysis in the CT and MRI images. A comprehensive predictive model with clinical variable and optimal radiomics features was established. The area under the curve (AUC) of the training group was 0.916 (95%CI: 0.843–1.000), sensitivity: 95.2%, specificity: 79.2%. In the validation group, the predictive model diagnosed MVI with AUC = 0.816 (95%CI: 0.642–0.990), sensitivity: 84.2%, and specificity: 75.0%.
ConclusionThe joint model that integrated the optimal radiomics features with clinical variables has good diagnostic performance for MVI of HCC and specific clinical applicability.
by Bin Li, Jinjin Wang, Jianlong Ge, Meijie Liao, Xiaojun Rong, Jinyan Wang, Yingeng Wang, Zheng Zhang, Chunyuan Wang, Yongxiang Yu
In order to study the optimal use of Lactobacillus plantarum in sea cucumber (Apostichopus japonicus), 49 days feeding trial was conducted to determine the influence of immersion bathing in different concentrations of Lactobacillus plantarum CLY-05 on body weight gain rate and non-specific immune activities. The potential effect of CLY-05 on gut microbiota was also analyzed during the immersion bathing at the optimum concentration. The results showed that the body weight growth rate of all bathing groups was higher than that of control. The highest specific growth rate (4.58%) and weight gain rate (25.35%) was achieved at the bacterial concentration of 1×103 CFU/mL. The activities of non-specific immune enzymes (ACP, AKP, SOD and LZM) of all bathing groups increased after immersion bathing, and the enzyme activities of groups bathed with the bacterium at 1×103 and 1×104 CFU/mL reached the highest. Therefore, 1×103 CFU/mL was considered as the optimum concentration of L. plantarum CLY-05 for A. japonicus pond culture. The results of gut microbiota analysis showed that the gut microbiota changed with the addition of L. plantarum CLY-05, and the richness and diversity of the gut microbiota peaked on day 14 and day 21, respectively. The correlation analysis revealed that the non-specific immune enzyme activities were significantly correlated to some gut bacteria (in the phyla Proteobacteria, Firmicutes) after immersion bathing in L. plantarum CLY-05. These findings provide the theoretical foundation for probiotic application in sea cucumber farming.by Hossein Mansourizadeh, Mohammad Reza Bakhtiarizadeh, Luciana Correia de Almeida Regitano, Jennifer Jessica Bruscadin
Different sheep breeds show distinct phenotypic plasticity in fat deposition in the tails. The genetic background underlying fat deposition in the tail of sheep is complex, multifactorial, and may involve allele-specific expression (ASE) mechanism to modulate allelic expression. ASE is a common phenomenon in mammals and refers to allelic imbalanced expression modified by cis-regulatory genetic variants that can be observed at heterozygous loci. Therefore, regulatory processes behind the fat-tail formation in sheep may be to some extent explained by cis- regulatory variants, through ASE mechanism, which was investigated in the present study. An RNA-Seq-based variant calling was applied to perform genome-wide survey of ASE genes using 45 samples from seven independent studies comparing the transcriptome of fat-tail tissue between fat- and thin-tailed sheep breeds. Using a rigorous computational pipeline, 115 differential ASE genes were identified, which were narrowed down to four genes (LPL, SOD3, TCP1 and LRPAP1) for being detected in at least two studies. Functional analysis revealed that the ASE genes were mainly involved in fat metabolism. Of these, LPL was of greater importance, as 1) observed in five studies, 2) reported as ASE gene in the previous studies and 3) with a known role in fat deposition. Our findings implied that complex physiological traits, like fat-tail formation, can be better explained by considering various genetic mechanisms, which can be more finely mapped through ASE analyses. The insights gained in this study indicate that biallelic expression may not be a common mechanism in sheep fat-tail development. Hence, allelic imbalance of the fat deposition-related genes can be considered a novel layer of information for future research on genetic improvement and increased efficiency in sheep breeding programs.by Miao Cheng, Siqi Xiao, Shaer Kayi, Yujie Guan, Yingxin Liu, Jianmei Chen, Hua Chen, Lei Wang, Xiaojin He
ObjectiveAnkylosing spondylitis (AS) patients often present with microscopic signs of gut inflammation. We used proteomic techniques to identify the differentially expressed proteins (DEPs) in the colon tissues of patients with AS and patients with gut inflammation, and then used investigated the influence of NMRAL1 protein on inflammatory cytokines to explore its potential role in the pathogenesis of AS and gut inflammation.
MethodsColonic mucosal tissues were collected from four different groups: healthy individuals (group A), patients with gut inflammation only (group B), patients with AS only (group C), and patients with AS combined with gut inflammation (group D). A total of 20 samples were processed for proteomic analysis, wherein proteins were extracted using SDT lysis, followed by separation via sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE). The proteins were digested using the filter-aided sample preparation (FASP) method and then analyzed using a timsTOF Pro mass spectrometer. The resulting peptide data were used to identify differentially expressed proteins (DEPs) across the different groups. To further explore the inflammation-related function of NMRAL1 protein, the murine monocyte/macrophage cell line RAW264.7 was used. NMRAL1 mRNA expression levels were assessed via RT-qPCR, and inflammatory cytokine levels (TNF-α, IL-1β, IL-17 and IL-23) were measured using ELISA following NMRAL1 siRNA transfection in LPS-treated macrophages.
ResultsWe collected colonic mucosa specimens from 20 patients, including groups A,B, C and D with 5 patients in each group. We established a database of DEPs and identified 107 (63 upregulated and 44 downregulated) between group B and group A, 78 (16 upregulated and 62 downregulated) between group D and group C, 45 (8 upregulated and 37 downregulated) between group D and group B, and 57 (33 upregulated and 24 downregulated) between group C and group A. Further analysis revealed that the NmrA-like family domain containing 1 (NMRAL1) protein was identified as a DEP specifically associated with group D. The results of in vitro results showed a significant decrease in NMRAL1 mRNA expression in LPS-treated cells (PPPPPPP Conclusion
NMRAL1 is identified as a key differentially expressed protein in AS patients with gut inflammation. Knockdown of NMRAL1 significantly reduced the levels of inflammatory cytokines, suggesting its potential role in the pathogenesis of AS and gut inflammation, and as a possible therapeutic target.
by Wensi Ouyang, Guimei Guo, Jie Xia, Changwei Zhao, Xiaoling Zhou
BackgroundMinimally invasive treatment options for osteonecrosis of the femoral head (ONFH) have been a prominent area of research in recent years. Arthroscopic-assisted treatments have been applied in the clinical management of ONFH; however, high-quality evidence verifying their effectiveness and safety is still lacking.
ObjectiveTo systematically assess the clinical efficacy and safety of arthroscopic-assisted core decompression (AACD) in treating ONFH.
MethodsA comprehensive literature search was conducted in PubMed, Web of Science, EMBASE, Cochrane Library, Chinese National Knowledge Infrastructure, China Science and Technology Journal Database, WanFang, and the Chinese BioMedical Literature Database, from inception to June 25, 2024. We identified randomized controlled trials and non-randomized controlled studies on AACD for the treatment of ONFH based on predefined inclusion and exclusion criteria. A meta-analysis was performed using Review Manager 5.4.1 and Stata 17.0 software. The analyzed outcomes included operative time, intraoperative blood loss, length of hospital stay, postoperative femoral head collapse rate, Harris hip score, and postoperative complication rate. The Grades of Recommendations, Assessment, Development, and Evaluations (GRADE) system was used to assess the quality of evidence for the outcome indicators.
ResultsA total of fourteen studies were included in this meta-analysis, comprising 1,063 patients-541 in the core decompression (CD) group and 522 in the AACD group. The meta-analysis revealed no significant differences between the two groups in terms of intraoperative blood loss, length of hospital stay, 12-month postoperative Harris hip score, or overall postoperative complication rate (P > 0.05). However, the AACD group had a longer operative time (MD = 31.19, 95% Cl: 5.32 to 57.07, P = 0.02) and a lower overall postoperative femoral head collapse rate (RR = 0.49, 95% Cl: 0.27 to 0.89, P = 0.02) compared with the CD group. Additionally, the AACD group showed significant improvements in Harris hip scores at 3 months (MD = 6.39, 95% Cl: 5.44 to 7.33, P P P P Conclusion
This meta-analysis suggests that AACD is an effective and safe treatment for patients with ONFH. However, due to the limited quantity and quality of the included studies, these results should be interpreted with caution. Further high-quality studies are recommended to confirm these findings.
by Shunmei Chen, Cihan Ruan, Yutong Guo, Jia Chang, Haohao Yan, Liang Chen, Yongzhong Duan, Guangyou Duan, Jinlong Bei, Xin Li, Shan Gao
Since the emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), its genetic and geographical origins remain unclear, resulting in suspicions about its natural origin. In one of our previous studies, we reported the presence of a furin cleavage site RRAR in the junction region between S1 and S2 subunits of the spike protein, which was discovered as the first crucial clue for the origin tracing of SARS-CoV-2. In the present study, we conducted an integrative analysis of new genome data from bat Sarbecovirus strains reported after the COVID-19 outbreak. The primary results included the identification of BANAL-20-52, Rp22DB159, and S18CXBatR24 as three close relatives of SARS-CoV-2 and the successful detection of seven out of nine key genomic features (designated as RC0-7 and ORF8) observed in wild types of SARS-CoV-2 in the three close relatives from Laos, Vietnam, and Yunnan province of China, respectively. The most significant contribution of the present study lies in the detection of RC1 in wild genotype in a bat Sarbecovirus population BANAL-20-52 belonging to. Encoding a segment of the NSP3 protein, RC1 was discovered as the second crucial clue for the origin tracing of SARS-CoV-2. Although RC0, encoding the junction furin cleavage site, remains undetected outside of the SARS-CoV-2 genome, Feuang of Laos is the sole place where eight of the nine wild-type features (RC1-7 and ORF8) have been detected.by Ana Paula Serafini Poeta Silva, Guilherme Arruda Cezar, Edison Sousa Magalhães, Kinath Rupasinghe, Srijita Chandra, Gustavo S. Silva, Marcelo Almeida, Bret Crim, Eric Burrough, Phillip Gauger, Christopher Siepker, Marta Mainenti, Michael Zeller, Rodger G. Main, Mary Thurn, Paulo Fioravante, Cesar Corzo, Albert Rovira, Hemant Naikare, Rob McGaughey, Franco Matias Ferreyra, Jamie Retallick, Jordan Gebhardt, Angela Pillatzki, Jon Greseth, Darren Kersey, Travis Clement, Jane Christopher-Hennings, Melanie Prarat, Ashley Johnson, Dennis Summers, Craig Bowen, Kenitra Hendrix, Joseph Boyle, Daniel Correia Lima Linhares, Giovani Trevisan
This study evaluated the use of endemic enteric coronaviruses polymerase chain reaction (PCR)-negative testing results as an alternative approach to detect the emergence of animal health threats with similar clinical diseases presentation. This retrospective study, conducted in the United States, used PCR-negative testing results from porcine samples tested at six veterinary diagnostic laboratories. As a proof of concept, the database was first searched for transmissible gastroenteritis virus (TGEV) negative submissions between January 1st, 2010, through April 29th, 2013, when the first porcine epidemic diarrhea virus (PEDV) case was diagnosed. Secondly, TGEV- and PEDV-negative submissions were used to detect the porcine delta coronavirus (PDCoV) emergence in 2014. Lastly, encountered best detection algorithms were implemented to prospectively monitor the 2023 enteric coronavirus-negative submissions. Time series (weekly TGEV-negative counts) and Seasonal Autoregressive-Integrated Moving-Average (SARIMA) were used to control for outliers, trends, and seasonality. The SARIMA’s fitted and residuals were then subjected to anomaly detection algorithms (EARS, EWMA, CUSUM, Farrington) to identify alarms, defined as weeks of higher TGEV-negativity than what was predicted by models preceding the PEDV emergence. The best-performing detection algorithms had the lowest false alarms (number of alarms detected during the baseline) and highest time to detect (number of weeks between the first alarm and PEDV emergence). The best-performing detection algorithms were CUSUM, EWMA, and Farrington flexible using SARIMA fitted values, having a lower false alarm rate and identified alarms 4 to 17 weeks before PEDV and PDCoV emergences. No alarms were identified in the 2023 enteric negative testing results. The negative-based monitoring system functioned in the case of PEDV propagating epidemic and in the presence of a concurrent propagating epidemic with the PDCoV emergence. It demonstrated its applicability as an additional tool for diagnostic data monitoring of emergent pathogens having similar clinical disease as the monitored endemic pathogens.
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