Clinical analysis and literature review of two paediatric cases of anti-IgLON5 antibody-related encephalitis.

Introduction: Anti-IgLON5 antibody-related encephalitis is a rare autoimmune disorder of the central nervous system, predominantly occurring in middle-aged elderly individuals, with paediatric cases being exceptionally rare. This study aims to enhance the understanding of paediatric anti-IgLON5 antibody-related encephalitis by summarising its clinical and therapeutic characteristics. Method: A retrospective analysis was conducted on two paediatric patients diagnosed with anti-IgLON5 antibody-related encephalitis at Hunan Children's Hospital from August 2022 to November 2023. This involved reviewing their medical records and follow-up data, in addition to a literature review. Results: The study involved two patients, one male and one female, aged between 2.5 and 9.6 years, both presenting with an acute/subacute course of illness. Clinically, both exhibited movement disorders (including dystonia, involuntary movements, and ataxia), cognitive impairments, sleep disturbances, and psychiatric symptoms. Patient 1 experienced epileptic seizures, while Patient 2 exhibited brainstem symptoms and abnormal eye movements. Neither patient showed autonomic dysfunction. Patient 1 had normal cerebrospinal fluid (CSF) and Brain MRI findings, whereas Patient 2 showed moderate leukocytosis and mild protein elevation in the CSF, and Brain MRI revealed symmetrical lesions in the basal ganglia and cerebellum. Oligoclonal bands in the CSF were positive in both cases. Both patients tested negative for HLA-DQB*05:01 and HLA-DRB*10:01. They received both first-line and second-line immunotherapies, with Patient 2 showing a poor response to treatment. Discussion: Paediatric cases of anti-IgLON5 antibody-related encephalitis similarly present sleep disturbances as a core symptom, alongside various forms of movement disorders. Immunotherapy is partially effective. Compared to adult patients, these paediatric cases tend to exhibit more pronounced psychiatric symptoms, a more rapid onset, and more evident inflammatory changes in the CSF. The condition appears to have a limited association with HLA-DQB*05:01 and HLA-DRB*10:01 polymorphisms.

Perioperative Hypothermia in Elderly Patients During Pelvic Floor Reconstruction Surgery: An Observational Study.

INTRODUCTION AND HYPOTHESIS: The potential predictors of pelvic floor reconstruction surgery hypothermia remain unclear. This prospective cohort study was aimed at identifying these predictors and evaluating the outcomes associated with perioperative hypothermia. METHODS: Elderly patients undergoing pelvic floor reconstruction surgery were consecutively enrolled from April 2023 to September 2023. Perioperative temperature was measured at preoperative (T1), every 15 min after the start of anesthesia (T2), and 15 min postoperative (T3) using a temperature probe. Perioperative hypothermia was defined as a core temperature below 36°C at any point during the procedure. Multivariate logistic regression analysis was conducted to determine factors associated with perioperative hypothermia. RESULTS: A total of 229 patients were included in the study, with 50.7% experiencing hypothermia. Multivariate analysis revealed that the surgical method involving pelvic floor combined with laparoscopy, preoperative temperature < 36.5°C, anesthesia duration ≥ 120 min, and the high levels of anxiety were significantly associated with perioperative hypothermia. The predictive value of the multivariate model was 0.767 (95% CI, 0.706 to 0.828). CONCLUSIONS: This observational prospective study identified several predictive factors for perioperative hypothermia in elderly patients during pelvic floor reconstruction surgery. Strategies aimed at preventing perioperative hypothermia should target these factors. Further studies are required to assess the effectiveness of these strategies, specifically in elderly patients undergoing pelvic floor reconstruction surgery.

The quality of life after keratinized mucosa augmentation around dental implants using xenogenic collagen matrix with or without stent.

BACKGROUND: The substitution of missing teeth with implants is a dependable and anticipated therapeutic approach. Despite numerous studies affirming long-term success rates, there exists a spectrum of potential biological and aesthetic complications. OBJECTIVE: The primary objective of this study was to assess patient responses subsequent to surgical interventions, with a specific emphasis on the utilization of xenogenic collagen matrix (XCM), both with and without the application of a stent secured over healing abutments, in the context of keratinized gingival mucosa augmentation. The principal aim was to evaluate and draw comparisons between the clinical outcomes resulting from these two procedural approaches, with a particular focus on critical parameters encompassing post-operative complications, patient comfort, and the overall efficacy in achieving successful keratinized tissue augmentation. methods: Sixty patients were selected for this study. The patients were divided into three groups: A, B, and a control group, with each group comprising 20 participants. We used XCM in experimental group A, XCM covered with surgical stent in experimental group B, and free gingival graft (FGG) in the control group. After the surgical procedure, patients were required to complete a visual analogue scale (VAS) questionnaire for post-operative complications, and a quality of life (QOL) questionnaire on days 1, 3, and 7. RESULTS: Patients in the experimental groups A and B demonstrated markedly improved outcomes when compared with the control group. Assessments conducted on days 1, 3, and 7 demonstrated diminished levels of pain, bleeding, and swelling in both experimental groups, with experimental group B showing the least discomfort. The incorporation of XCM, either with or without stents, was associated with a reduction in analgesic consumption, underscoring its favorable influence on post-operative comfort, notwithstanding the exception of halitosis in experimental group B. CONCLUSION: Using XCM with or without a stent for keratinized tissue augmentation has better post-operative outcomes associated with reduced swelling, bleeding, and pain based on the QOL survey. This study provides data to support the clinical application of XCM and stents.

Metabolomics reveals the reasons for the occurrence of Pendulous-comb related to egg production performance.

The chicken comb is an essential secondary sexual characteristic to measure sexual maturity and is closely related to reproductive performance. Pendulous comb (PC) and upright comb (UC) are 2 common comb phenotypes in hens, which have been highly associated with egg production performance. However, the reasons for the formation of PC remain undetermined. In this study, we first characterized the PC and UC chicken at start (at 175 d age), peak (at 217 d age), and postlaying (at 300 d age) and found that PC and UC could transform for each other. Furthermore, we suggested that PC chicken demonstrated better egg production performance than UC chicken, especially characterizing comb type in the start-laying period. Moreover, we performed histological evaluation of PC and UC tissue, which suggested that the low density of collagen fibers and acid mucopolysaccharides might lead to the formation of PC. To further explore the possible reasons for PC formation, we performed an untargeted metabolomic analysis of serum between PC and UC chicken in the start, peak, and postlaying periods. The enrichment analysis of period-unique differentially expressed metabolites (DEMs) between PC and UC showed that the different metabolic pathways and nutritional levels might contribute to the formation of PC in the different laying periods. Our research provided critical insights into the phenotypic diversity of chicken comb, establishing a foundation for early selection of chicken egg production performance.

Association of stress hyperglycemia ratio with left ventricular function and microvascular obstruction in patients with ST-segment elevation myocardial infarction: a 3.0 T cardiac magnetic resonance study.

BACKGROUND: Stress hyperglycemia, which is associated with poor prognosis in patients with acute myocardial infarction (AMI), can be determined using the stress hyperglycemia ratio (SHR). Impaired left ventricular function and microvascular obstruction (MVO) diagnosed using cardiac magnetic resonance (CMR) have also been proven to be linked to poor prognosis in patients with AMI and aid in risk stratification. However, there have been no studies on the correlation between fasting SHR and left ventricular function and MVO in patients with acute ST-segment elevation myocardial infarction (ASTEMI). Therefore, this study aimed to investigate the additive effect of fasting SHR on left ventricular function and global deformation in patients with ASTEMI and to explore the association between fasting SHR and MVO. METHODS: Consecutive patients who underwent CMR at index admission (3-7 days) after primary percutaneous coronary intervention (PPCI) were enrolled in this study. Basic clinical, biochemical, and CMR data were obtained and compared among all patients grouped by fasting SHR tertiles: SHR1: SHR < 0.85; SHR2: 0.85 ≤ SHR < 1.01; and SHR3: SHR ≥ 1.01. Spearman's rho (r) was used to assess the relationship between fasting SHR and left ventricular function, myocardial strain, and the extent of MVO. Multivariable linear regression analysis was performed to evaluate the determinants of left ventricular function and myocardial strain impairment in all patients with AMI. Univariable and multivariable regression analyses were performed to investigate the correlation between fasting SHR and the presence and extent of MVO in patients with AMI and those with AMI and diabetes mellitus (DM). RESULTS: A total of 357 patients with ASTEMI were enrolled in this study. Left ventricular ejection fraction (LVEF) and left ventricular global function index (LVGFI) were significantly lower in SHR2 and SHR3 than in SHR1. Compared with SHR1 and SHR2 groups, left ventricular strain was lower in SHR3, as evidenced by global radial (GRS), global circumferential (GCS), and global longitudinal (GLS) strains. Fasting SHR were negatively correlated with LVEF, LVGFI, and GRS (r = - 0.252; r = - 0.261; and r = - 0.245; all P<0.001) and positively correlated with GCS (r = 0.221) and GLS (r = 0.249; all P <0.001). Multivariable linear regression analysis showed that fasting SHR was an independent determinant of impaired LVEF, LVGFI, GRS, and GLS. Furthermore, multivariable regression analysis after adjusting for covariates signified that fasting SHR was associated with the presence and extent of MVO in patients with AMI and those with AMI and DM. CONCLUSION: Fasting SHR in patients with ASTEMI successfully treated using PPCI is independently associated with impaired cardiac function and MVO. In patients with AMI and DM, fasting SHR is an independent determinant of the presence and extent of MVO.

Quantification of trace heavy metals in environmental water, soil and atmospheric particulates with their bioaccessibility analysis.

In this work, sulfhydryl (SH) functionalized magnetic covalent organic framework (COF) was synthesized by using 4-aldehyde phenyl butadiyne (DEBD) and 1,3,5-tris(4-aminophenyl) benzene (TAPB) as the monomers and ethanedithiol as the modifier, with the aid of thiol-alkyne "click" reaction. The prepared Fe3O4@COFTAPB-DEBD@SH exhibited relatively strong magnetism (32.8 emu g-1), good stability and selectivity to target analytes with a high sulfhydryl content (0.24 mmol g-1). Based on Fe3O4@COFTAPB-DEBD@SH, a method combining magnetic solid phase extraction with inductively coupled plasma mass spectrometry (ICP-MS) was developed for the quantitative analysis of trace metals. Under the optimal conditions, the method merited fast desorption kinetics (<2 min), adsorption kinetics (<20 min), fast phase separation (<1 min), high enrichment factor (100), and the detection limits for Cd, Hg, Pb and Bi were determined to be 1.18, 0.51, 4.91 and 0.39 ng L-1, respectively. A good resistance to complex matrices was demonstrated for the method in the analysis of soil, atmospheric particles and simulated pulmonary fluids samples. Certified reference materials (coal fly ash GBW08401 and soil GBW07427) were employed to validate the accuracy of the method. Four target metals in the range of 12.9-215 ng L-1, 0.06-24.6 µg g-1 and 0.52-33.1 ng m-3 were found in local water, soil and atmospheric particulates (PM), respectively. Additionally, artificial lysosome solution and gamble's solution were used to simulate human pulmonary fluid and the bioaccessibility of Cd, Hg, Pb and Bi in PM2.5 was evaluated to be 58.6-73.1 % and 1.3-7.1 %, respectively.

A Self-supervised Learning-Based Fine-Grained Classification Model for Distinguishing Malignant From Benign Subcentimeter Solid Pulmonary Nodules.

RATIONALE AND OBJECTIVES: Diagnosing subcentimeter solid pulmonary nodules (SSPNs) remains challenging in clinical practice. Deep learning may perform better than conventional methods in differentiating benign and malignant pulmonary nodules. This study aimed to develop and validate a model for differentiating malignant and benign SSPNs using CT images. MATERIALS AND METHODS: This retrospective study included consecutive patients with SSPNs detected between January 2015 and October 2021 as an internal dataset. Malignancy was confirmed pathologically; benignity was confirmed pathologically or via follow-up evaluations. The SSPNs were segmented manually. A self-supervision pre-training-based fine-grained network was developed for predicting SSPN malignancy. The pre-trained model was established using data from the National Lung Screening Trial, Lung Nodule Analysis 2016, and a database of 5478 pulmonary nodules from the previous study, with subsequent fine-tuning using the internal dataset. The model's efficacy was investigated using an external cohort from another center, and its accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were determined. RESULTS: Overall, 1276 patients (mean age, 56 ± 10 years; 497 males) with 1389 SSPNs (mean diameter, 7.5 ± 2.0 mm; 625 benign) were enrolled. The internal dataset was specifically enriched for malignancy. The model's performance in the internal testing set (316 SSPNs) was: AUC, 0.964 (95% confidence interval (95%CI): 0.942-0.986); accuracy, 0.934; sensitivity, 0.965; and specificity, 0.908. The model's performance in the external test set (202 SSPNs) was: AUC, 0.945 (95% CI: 0.910-0.979); accuracy, 0.911; sensitivity, 0.977; and specificity, 0.860. CONCLUSION: This deep learning model was robust and exhibited good performance in predicting the malignancy of SSPNs, which could help optimize patient management.

Predicting the pathways of string-like motions in metallic glasses via path-featurizing graph neural networks.

String-like motions (SLMs)-cooperative, "snake"-like movements of particles-are crucial for dynamics in diverse glass formers. Despite their ubiquity, questions persist: Do SLMs prefer specific paths? If so, can we predict these paths? Here, in Al-Sm glasses, our isoconfigurational ensemble simulations reveal that SLMs do follow certain paths. By designing a graph neural network (GNN) to featurize the environment around directional paths, we achieve a high-fidelity prediction of likely SLM pathways, solely based on the static structure. GNN gauges a structural measure to assess each path's propensity to engage in SLMs, akin to a "softness" metric, but for paths rather than for atoms. Our GNN interpretation reveals the critical role of the bottleneck zone along a path in steering SLMs. By monitoring "path softness," we elucidate that SLM-favored paths transit from fragmented to interconnected upon glass transition. Our findings reveal that, beyond atoms or clusters, glasses have another dimension of structural heterogeneity: "paths."

Anticancer activity of 8-hydroxyquinoline-triphenylphosphine rhodium(III) complexes targeting mitophagy pathways.

Metallodrugs exhibiting distinct mechanisms of action compared with cisplatin hold promise for overcoming cisplatin resistance and improving the efficacy of anticancer drugs. In this study, a new series of rhodium (Rh)(III) complexes containing tris(triphenylphosphine)rhodium(I) chloride [(TPP)3RhCl] (TPP = triphenylphosphine, TPP=O = triphenylphosphine oxide) and 8-hydroxyquinoline derivatives (H-XR1-H-XR4), namely [Rh(XR1)2(TPP)Cl]·(TPP=O) (Yulin Normal University-1a [YNU-1a]), [Rh(XR2)2(TPP)Cl] (YNU-1b), [Rh(XR3)2(TPP)Cl] (YNU-1c), and [Rh(XR4)2(TPP)Cl] (YNU-1d), was synthesized and characterized via X-ray diffraction, mass spectrometry and IR. The cytotoxicity of the compounds YNU-1a-YNU-1d in Hep-G2 and HCC1806 human cancer cell lines and normal HL-7702 cell line was evaluated. YNU-1c exhibited cytotoxicity and selectivity in HCC1806 cells (IC50 = 0.13 ± 0.06 µM, selectivity factor (SF) = 384.6). The compounds YNU-1b and YNU-1c, which were selected for mechanistic studies, induced the activation of apoptotic pathways and mitophagy. In addition, these compounds released cytochrome c, cleaved caspase-3/pro-caspase-3 and downregulated the levels of mitochondrial respiratory chain complexes I/IV (M1 and M4) and ATP. The compound YNU-1c, which was selected for in vivo experiments, exhibited tumor growth inhibition (58.9 %). Importantly, hematoxylin and eosin staining and TUNEL revealed that HCC1806 tumor tissues exhibited significant apoptotic characteristics. YNU-1a-YNU-1d compounds are promising drug candidates that can be used to overcome cisplatin resistance.

Online sequential analysis of volatile and semivolatile organic compounds in water matrices by double robotic sample preparations and dual-channel mono and comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry system.

The monitoring of organic compounds in aquatic matrices poses challenges due to its complexity and time-intensive nature. To address these challenges, we introduce a novel approach utilizing a dual-channel mono (1D) and comprehensive two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) system, integrated with a robotic pretreatment platform, for online monitoring of both volatile organic compounds (VOCs) and semivolatile organic compounds (SVOCs) in water matrices. Employing the robotic platform, we establish a suite of online liquid-liquid extraction (LLE) pretreatment processes for water samples, marking the first instance of such procedures. Leveraging the automatic headspace (HS) module, dual robotic preparations of HS and LLE are sequentially executed to extract VOCs and SVOCs from water matrices. The GC × GC-TOFMS system is distinguished by its dual-channel analytical column configuration, facilitating sequential analysis of VOCs in GC-TOFMS mode and SVOCs in GC × GC-TOFMS mode. Quantitative detection of 55 target VOCs and 104 SVOCs is achieved in a water sample using the instrument system. Our method demonstrates excellent correlation coefficients ranging from 0.990 to 1.000, method detection limits ranging from 0.08 to 4.78 µg L-1, relative standard deviations below 19.3 %, and recovery rates ranging from 50.0 % to 124.0 %. To validate the online monitoring capabilities of our system, we assess target SVOCs at three different concentration levels over a 3-day period. Most compounds exhibit recovery rates ranging from 70.0 % to 130.0 %. Furthermore, we apply our method to analyze a real water sample, successfully identifying over 100 target and nontarget VOCs/SVOCs, including alcohols, aldehydes, ketones, acids, esters, and phenols. These results highlight the efficacy of the proposed analysis system, capable of conducting two distinct analyses in automatic sequence, thereby enhancing the efficiency and accuracy of organic compound analysis in water matrices.

pNet: A toolbox for personalized functional networks modeling.

Personalized functional networks (FNs) derived from functional magnetic resonance imaging (fMRI) data are useful for characterizing individual variations in the brain functional topography associated with the brain development, aging, and disorders. To facilitate applications of the personalized FNs with enhanced reliability and reproducibility, we develop an open-source toolbox that is user-friendly, extendable, and includes rigorous quality control (QC), featuring multiple user interfaces (graphics, command line, and a step-by-step guideline) and job-scheduling for high performance computing (HPC) clusters. Particularly, the toolbox, named personalized functional network modeling (pNet), takes fMRI inputs in either volumetric or surface type, ensuring compatibility with multiple fMRI data formats, and computes personalized FNs using two distinct modeling methods: one method optimizes the functional coherence of FNs, while the other enhances their independence. Additionally, the toolbox provides HTML-based reports for QC and visualization of personalized FNs. The toolbox is developed in both MATLAB and Python platforms with a modular design to facilitate extension and modification by users familiar with either programming language. We have evaluated the toolbox on two fMRI datasets and demonstrated its effectiveness and user-friendliness with interactive and scripting examples. pNet is publicly available at https://github.com/MLDataAnalytics/pNet.

Automated insulin delivery in children with type 1 diabetes during physical activity: a meta-analysis.

OBJECTIVES: The aim of this study was to evaluate the performance of the automated insulin delivery (AID) in adolescents, and children with type 1 diabetes (T1D) during physical activity. METHODS: Relevant studies were searched electronically in the Cochrane Library, PubMed, and Embase utilizing the key words "Child", "Insulin Infusion Systems", and "Diabetes Mellitus" from inception to 17th March 2024 to evaluate the performance of the AID in adolescents, and children with T1D during physical activity. RESULTS: Twelve studies involving 514 patients were identified. AID did not show a beneficial effect on duration of hypoglycemia<70 mg/dL during study period (p>0.05; I2=96 %) and during the physical activity (p>0.99). Percentage of sensor glucose values in TIR was higher in AID than the non-AID pumps during study period (p<0.001; I2=94 %). The duration of hyperglycemic time was significantly decreased in AID group compared to the non-AID pumps group during study period (p<0.05; I2>50 %). CONCLUSIONS: AID improved TIR and decreased the duration of hyperglycemic time, but did not appear to have a significant beneficial effect on the already low post-exercise duration of hypoglycemia achievable by open loop or sensor-augmented pumps in adolescents and children with T1D during physical activity; further research is needed to confirm the beneficial effect of AID on duration of hypoglycemia.

Comparative investigation of neoadjuvant immunotherapy versus adjuvant immunotherapy in perioperative patients with cancer: a global-scale, cross-sectional, large-sample informatics study.

BACKGROUND: Neoadjuvant and adjuvant immunotherapies for cancer have evolved through a series of remarkable and critical research advances; however, addressing their similarities and differences is imperative in clinical practice. Therefore, this study aimed to examine their similarities and differences from the perspective of informatics analysis. METHODS: This cross-sectional study retrospectively analyzed extensive relevant studies published between 2014 and 2023 using stringent search criteria, excluding non-peer-reviewed and non-English documents. The main outcome variables are publication volume, citation volume, connection strength, occurrence frequency, relevance percentage, and development percentage. Furthermore, an integrated comparative analysis was conducted using unsupervised hierarchical clustering, spatiotemporal analysis, regression statistics, and Walktrap algorithm analysis. RESULTS: This analysis included 1,373 relevant studies. Advancements in neoadjuvant and adjuvant immunotherapies have been promising over the last decade, with an annual growth rate of 25.18% vs. 6.52% and global collaboration (International Co-authorships) of 19.93% vs. 19.84%. Respectively, five dominant research clusters were identified through unsupervised hierarchical clustering based on machine learning, among which Cluster 4 (Balance of neoadjuvant immunotherapy efficacy and safety) and Cluster 2 (Adjuvant immunotherapy clinical trials) (Average Publication Year [APY]: 2021.70±0.70 vs. 2017.54±4.59) are emerging research populations. Burst and regression curve analyses uncovered domain pivotal research signatures, including microsatellite instability (R2=0.7500, P=0.0025) and biomarkers (R2=0.6505, P=0.0086) in neoadjuvant scenarios, and the tumor microenvironment (R2=0.5571, P=0.0209) in adjuvant scenarios. The Walktrap algorithm further revealed that "neoadjuvant immunotherapy, non-small cell lung cancer (NSCLC), immune checkpoint inhibitors, melanoma" and "adjuvant immunotherapy, melanoma, hepatocellular carcinoma, dendritic cells" (Relevance Percentage: 100% vs. 100%, Development Percentage: 37.5% vs. 17.1%) are extremely relevant to this field but remain underdeveloped, highlighting the need for further investigation. CONCLUSION: This study identified pivotal research signatures and provided substantial predictions for neoadjuvant and adjuvant cancer immunotherapies. In addition, comprehensive quantitative comparisons revealed a notable shift in focus within this field, with neoadjuvant immunotherapy taking precedence over adjuvant immunotherapy after 2020; such a qualitative finding facilitate proper decision-making for subsequent research and mitigate the wastage of healthcare resources.

Deciphering the Roles of Extracellular Polymeric Substances (EPS) in Shaping Disinfection Kinetics through Permanent Removal via Genetic Disruption.

Extracellular polymeric substances (EPS) ubiquitously encapsulate microbes and play crucial roles in various environmental processes. However, understanding their complex interactions with dynamic bacterial behaviors, especially during the disinfection process, remains very limited. In this work, we investigated the impact of EPS on bacterial disinfection kinetics by developing a permanent EPS removal strategy. We genetically disrupted the synthesis of exopolysaccharides, the structural components of EPS, in Pseudomonas aeruginosa, a well-known EPS-producing opportunistic pathogen found in diverse environments, creating an EPS-deficient strain. This method ensured a lasting absence of EPS while maintaining bacterial integrity and viability, allowing for real-time in situ investigations of the roles of EPS in disinfection. Our findings indicate that removing EPS from bacteria substantially lowered their susceptibility threshold to disinfectants such as ozone, chloramine B, and free chlorine. This removal also substantially accelerated disinfection kinetics, shortened the resistance time, and increased disinfection efficiency, thereby enhancing the overall bactericidal effect. The absence of EPS was found to enhance bacterial motility and increase bacterial cell vulnerability to disinfectants, resulting in greater membrane damage and intensified reactive oxygen species (ROS) production upon exposure to disinfectants. These insights highlight the central role of EPS in bacterial defenses and offer promising implications for developing more effective disinfection strategies.

Deciphering Multidrug-Resistant Plasmids in Disinfection Residual Bacteria from a Wastewater Treatment Plant.

Current disinfection processes pose an emerging environmental risk due to the ineffective removal of antibiotic-resistant bacteria, especially disinfection residual bacteria (DRB) carrying multidrug-resistant plasmids (MRPs). However, the characteristics of DRB-carried MRPs are poorly understood. In this study, qPCR analysis reveals that the total absolute abundance of four plasmids in postdisinfection effluent decreases by 1.15 log units, while their relative abundance increases by 0.11 copies/cell compared to investigated wastewater treatment plant (WWTP) influent. We obtain three distinctive DRB-carried MRPs (pWWTP-01-03) from postdisinfection effluent, each carrying 9-11 antibiotic-resistant genes (ARGs). pWWTP-01 contains all 11 ARGs within an ∼25 Kbp chimeric genomic island showing strong patterns of recombination with MRPs from foodborne outbreaks and hospitals. Antibiotic-, disinfectant-, and heavy-metal-resistant genes on the same plasmid underscore the potential roles of disinfectants and heavy metals in the coselection of ARGs. Additionally, pWWTP-02 harbors an adhesin-type virulence operon, implying risks of both antibiotic resistance and pathogenicity upon entering environments. Furthermore, some MRPs from DRB are capable of transferring and could confer selective advantages to recipients under environmentally relevant antibiotic pressure. Overall, this study advances our understanding of DRB-carried MRPs and highlights the imminent need to monitor and control wastewater MRPs for environmental security.

Global research hotspots, development trends and prospect discoveries of phase separation in cancer: a decade-long informatics investigation.

Liquid-liquid phase separation (LLPS) is a complex and subtle phenomenon whose formation and regulation take essential roles in cancer initiation, growth, progression, invasion, and metastasis. This domain holds a wealth of underutilized unstructured data that needs further excavation for potentially valuable information. Therefore, we retrospectively analyzed the global scientific knowledge in the field over the last decade by using informatics methods (such as hierarchical clustering, regression statistics, hotspot burst, and Walktrap algorithm analysis). Over the past decade, this area enjoyed a favorable development trend (Annual Growth Rate: 34.98%) and global collaboration (International Co-authorship: 27.31%). Through unsupervised hierarchical clustering based on machine learning, the global research hotspots were divided into five dominant research clusters: Cluster 1 (Effects and Mechanisms of Phase Separation in Drug Delivery), Cluster 2 (Phase Separation in Gene Expression Regulation), Cluster 3 (Phase Separation in RNA-Protein Interaction), Cluster 4 (Reference Value of Phase Separation in Neurodegenerative Diseases for Cancer Research), and Cluster 5 (Roles and Mechanisms of Phase Separation). And further time-series analysis revealed that Cluster 5 is the emerging research cluster. In addition, results from the regression curve and hotspot burst analysis point in unison to super-enhancer (a=0.5515, R2=0.6586, p=0.0044) and stress granule (a=0.8000, R2=0.6000, p=0.0085) as the most potential star molecule in this field. More interestingly, the Random-Walk-Strategy-based Walktrap algorithm further revealed that "phase separation, cancer, transcription, super-enhancer, epigenetics"(Relevance Percentage[RP]=100%, Development Percentage[DP]=29.2%), "stress granule, immunotherapy, tumor microenvironment, RNA binding protein"(RP=79.2%, DP=33.3%) and "nanoparticle, apoptosis"(RP=70.8%, DP=25.0%) are closely associated with this field, but are still under-developed and worthy of further exploration. In conclusion, this study profiled the global scientific landscape, discovered a crucial emerging research cluster, identified several pivotal research molecules, and predicted several crucial but still under-developed directions that deserve further research, providing an important reference value for subsequent basic and clinical research of phase separation in cancer.

Cardiac magnetic resonance feature tracking derived left atrial strain in the diagnosis of patients with constrictive pericarditis and restrictive cardiomyopathy.

Objective: To explore the diagnostic value of cardiac magnetic resonance feature tracking (CMR-FT) divided left atrial (LA) strain in differentiating constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM). Methods: Patients with CP (n = 40) and RCM (n = 40), and another 40 normal control group were retrospectively enrolled over a period of 8 years at a tertiary cardiac centre. Left ventricular (LV) and biatrial strain and strain rate (SR) were measured. Atrial strain was used to differentiate between patients with CP and RCM. Then, patients were grouped according to their left ventricular ejection fraction (LVEF), either ≥50% or < 50%. A deeper analysis was done to evaluate the diagnostic value of atrial strain in these subgroups. Receiver operating characteristic curves (ROC) were used to assess the accuracy of myocardial strain based on CMR FT for the differential diagnosis of CP and RCM. Results: LV and LA strain and SR were significantly lower in patients with CP and RCM than those in the normal controls (P < 0.05). LA strain and SR were significantly lower in the RCM group than in the CP group (P < 0.05). In patients with either LVEF≥50% or＜50%, LA strain were lower in the RCM group than in the CP group (P < 0.05). ROC analysis showed that LA stored strain (LA-εs) had a good differential diagnostic value for CP and RCM, with an area under the curve (AUC) of 0.811 and an optimal cutoff value of 6.98%, above this value it tends to develop CP. Further, an excellent differential diagnostic value was found in patients with LVEF＜50%, with an AUC of 0.955. Conclusion: LA strain analysis obtained by CMR-FT provides good differential diagnostic value for distinguishing CP from RCM, especially in patients with LVEF＜50%.

Effect of RARC-ERAS nursing program on clinical outcomes in patients undergoing RARC surgery: a retrospective, propensity matching study.

Currently, there is no specific perioperative nursing standard for RARC based on the ERAS concept. This retrospective study investigates to analyze the effect of RARC-ERAS nursing program on VTE and other clinical outcomes in patients undergoing RARC surgery. This retrospective study included 216 patients undergoing RARC surgery From January 1, 2022 to December 30, 2023, and propensity score adjustment analysis was applied. The study compares a control group receiving traditional nursing and an observation group receiving RARC-ERAS nursing program. Perioperative variables and other postoperative complications were retrieved from the hospital medical records. After propensity score matching, there were no significant differences in the demographic and clinical characteristics between the two groups (p > 0.05). The ERAS group exhibited aa significantly higher rate of postoperative unobstructed venous blood flow in the lower extremities by color Doppler ultrasound as compared to the control group (94.6% VS 80.4%, p = 0.042). Before anesthesia induction, lower preoperative anxiety and surgical information needs scores were observed in the ERAS group than in the control group (p < 0.05). Compared to the control group, the ERAS group demonstrated a shorter surgical duration, a lower incidence of perioperative hypothermia, less time needed for getting out of bed, anal exhaust, and for defecation after returning to the ward (p < 0.05). RARC-ERAS nursing program significantly increased the rate of postoperative unobstructed venous blood flow in the lower extremities by color doppler ultrasound, lower preoperative anxiety and intraoperative hypothermia in patients undergoing RARC. This nursing approach presents a valuable strategy for enhancing patient outcomes and merits further exploration in clinical practice.Trial registration:ChiCTR2400081118; http://www.chictr.org.cn , Principal investigator: Mang-mang He, Date of registration: Feb 22, 2024.

Ubenimex combined with Albendazole for the treatment of Echinococcus multilocularis-induced alveolar echinococcosis in mice.

Introduction: Alveolar echinococcosis (AE) is a parasitic disease caused by E. multilocularis metacestodes and it is highly prevalent in the northern hemisphere. We have previously found that vaccination with E. multilocularis-Leucine aminopeptidase (EM-LAP) could inhibit the growth and invasion of E. multilocularis in host liver, and Ubenimex, a broad-spectrum inhibitor of LAP, could also inhibit E. multilocularis invasion but had a limited effect on the growth and development of E. multilocularis. Methods: In this study, the therapeutic effect of Ubenimex combined with Albendazole on AE was evaluated. Mice were intraperitoneally injected with protoscoleces and imaging examination was performed at week 8 and week 16 to detect cyst change. During this period, mice were intraperitoneally injected with Ubenimex and intragastrically administered with Albendazole suspension. At last, the therapeutic effect was evaluated by morphological and pathological examination and liver function. Results: The results revealed that the combined treatment could inhibit the growth and infiltration of cysts in BALB/c mice infected with E. multilocularis protoscoleces. The weight, number, invasion and fibrosis of cysts were reduced in mice treated with Ubenimex in combination with Albendazole. The same effect was achieved by the single Ubenimex treatment because of its inhibitory effect on LAP activity, but it was less effective in inhibiting the growth of cysts. The levels of ALT, AST, TBIL, DBIL, ALP, and γ-GT were reduced after the combined treatment, indicating that treatment with both Ubenimex and Albendazole could alleviate liver damage. Discussion: This study suggests that the combined treatment with Ubenimex and Albendazole could be a potential therapeutic strategy for E. multilocularis infections.

Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models.

Background Preoperative discrimination of preinvasive, minimally invasive, and invasive adenocarcinoma at CT informs clinical management decisions but may be challenging for classifying pure ground-glass nodules (pGGNs). Deep learning (DL) may improve ternary classification. Purpose To determine whether a strategy that includes an adjudication approach can enhance the performance of DL ternary classification models in predicting the invasiveness of adenocarcinoma at chest CT and maintain performance in classifying pGGNs. Materials and Methods In this retrospective study, six ternary models for classifying preinvasive, minimally invasive, and invasive adenocarcinoma were developed using a multicenter data set of lung nodules. The DL-based models were progressively modified through framework optimization, joint learning, and an adjudication strategy (simulating a multireader approach to resolving discordant nodule classifications), integrating two binary classification models with a ternary classification model to resolve discordant classifications sequentially. The six ternary models were then tested on an external data set of pGGNs imaged between December 2019 and January 2021. Diagnostic performance including accuracy, specificity, and sensitivity was assessed. The χ2 test was used to compare model performance in different subgroups stratified by clinical confounders. Results A total of 4929 nodules from 4483 patients (mean age, 50.1 years ± 9.5 [SD]; 2806 female) were divided into training (n = 3384), validation (n = 579), and internal (n = 966) test sets. A total of 361 pGGNs from 281 patients (mean age, 55.2 years ± 11.1 [SD]; 186 female) formed the external test set. The proposed strategy improved DL model performance in external testing (P < .001). For classifying minimally invasive adenocarcinoma, the accuracy was 85% and 79%, sensitivity was 75% and 63%, and specificity was 89% and 85% for the model with adjudication (model 6) and the model without (model 3), respectively. Model 6 showed a relatively narrow range (maximum minus minimum) across diagnostic indexes (accuracy, 1.7%; sensitivity, 7.3%; specificity, 0.9%) compared with the other models (accuracy, 0.6%-10.8%; sensitivity, 14%-39.1%; specificity, 5.5%-17.9%). Conclusion Combining framework optimization, joint learning, and an adjudication approach improved DL classification of adenocarcinoma invasiveness at chest CT. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Sohn and Fields in this issue.