Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy.

BACKGROUND: Epilepsy is a serious complication after an ischemic stroke. Although two studies have developed prediction model for post-stroke epilepsy (PSE), their accuracy remains insufficient, and their applicability to different populations is uncertain. With the rapid advancement of computer technology, machine learning (ML) offers new opportunities for creating more accurate prediction models. However, the potential of ML in predicting PSE is still not well understood. The purpose of this study was to develop prediction models for PSE among ischemic stroke patients. METHODS: Patients with ischemic stroke from two stroke centers were included in this retrospective cohort study. At the baseline level, 33 input variables were considered candidate features. The 2-year PSE prediction models in the derivation cohort were built using six ML algorithms. The predictive performance of these machine learning models required further appraisal and comparison with the reference model using the conventional triage classification information. The Shapley additive explanation (SHAP), based on fair profit allocation among many stakeholders according to their contributions, is used to interpret the predicted outcomes of the naive Bayes (NB) model. RESULTS: A total of 1977 patients were included to build the predictive model for PSE. The Boruta method identified NIHSS score, hospital length of stay, D-dimer level, and cortical involvement as the optimal features, with the receiver operating characteristic curves ranging from 0.709 to 0.849. An additional 870 patients were used to validate the ML and reference models. The NB model achieved the best performance among the PSE prediction models with an area under the receiver operating curve of 0.757. At the 20 % absolute risk threshold, the NB model also provided a sensitivity of 0.739 and a specificity of 0.720. The reference model had poor sensitivities of only 0.15 despite achieving a helpful AUC of 0.732. Furthermore, the SHAP method analysis demonstrated that a higher NIHSS score, longer hospital length of stay, higher D-dimer level, and cortical involvement were positive predictors of epilepsy after ischemic stroke. CONCLUSIONS: Our study confirmed the feasibility of applying the ML method to use easy-to-obtain variables for accurate prediction of PSE and provided improved strategies and effective resource allocation for high-risk patients. In addition, the SHAP method could improve model transparency and make it easier for clinicians to grasp the prediction model's reliability.

Phase separation provides a mechanism to drive phenotype switching.

Phenotypic switching plays a crucial role in cell fate determination across various organisms. Recent experimental findings highlight the significance of protein compartmentalization via liquid-liquid phase separation in influencing such decisions. However, the precise mechanism through which phase separation regulates phenotypic switching remains elusive. To investigate this, we established a mathematical model that couples a phase separation process and a gene expression process with feedback. We used the chemical master equation theory and mean-field approximation to study the effects of phase separation on the gene expression products. We found that phase separation can cause bistability and bimodality. Furthermore, phase separation can control the bistable properties of the system, such as bifurcation points and bistable ranges. On the other hand, in stochastic dynamics, the droplet phase exhibits double peaks within a more extensive phase separation threshold range than the dilute phase, indicating the pivotal role of the droplet phase in cell fate decisions. These findings propose an alternative mechanism that influences cell fate decisions through the phase separation process. As phase separation is increasingly discovered in gene regulatory networks, related modeling research can help build biomolecular systems with desired properties and offer insights into explaining cell fate decisions.

Tumor-informed deep sequencing of ctDNA detects minimal residual disease and predicts relapse in osteosarcoma.

Background: Current surveillance modalities of osteosarcoma relapse exhibit limited sensitivity and specificity. Although circulating tumor DNA (ctDNA) has been established as a biomarker of minimal residual disease (MRD) in many solid tumors, a sensitive ctDNA detection technique has not been thoroughly explored for longitudinal MRD detection in osteosarcoma. Methods: From August 2019 to June 2023, 59 patients diagnosed with osteosarcoma at the First Affiliated Hospital of Sun Yat-sen University were evaluated in this study. Tumor-informed MRD panels were developed through whole exome sequencing (WES) of tumor tissues. Longitudinal blood samples were collected during treatment and subjected to multiplex PCR-based next-generation sequencing (NGS). Kaplan-Meier curves and Log-rank tests were used to compare outcomes, and Cox regression analysis was performed to identify prognostic factors. Findings: WES analysis of 83 patients revealed substantial mutational heterogeneity, with non-recurrent mutated genes accounting for 58.1%. Tumor-informed MRD panels were successfully obtained for 85.5% of patients (71/83). Among 59 patients with successful MRD panel customization and available blood samples, 13 patients exhibited positive ctDNA detection after surgery. Patients with negative post-operative ctDNA had better event-free survival (EFS) compared to those with positive ctDNA, at 1-6 months after surgery, after adjuvant chemotherapy, and more than 6 months after surgery (p < 0.05). In both univariate and multivariate Cox regression analysis, ctDNA results emerged as a significant predictor of EFS (p < 0.05). ctDNA detection preceded positive imaging in 5 patients, with an average lead time of 92.6 days. Thirty-nine patients remained disease-free, with ctDNA results consistently negative or turning negative during follow-up. Interpretation: Our study underscores the applicability of tumor-informed deep sequencing of ctDNA in osteosarcoma MRD surveillance and, to our knowledge, represents the largest cohort to date. ctDNA detection is a significant prognostic factor, enabling the early identification of tumor relapse and progression compared to standard imaging, thus offering valuable insights in guiding osteosarcoma patient management. Funding: The Grants of National Natural Science Foundation of China (No. 82072964, 82072965, 82203798, 82203026), the Natural Science Foundation of Guangdong (No. 2023A1515012659, 2023A1515010302), and the Regional Combination Project of Basic and Applied Basic Research Foundation of Guangdong (No. 2020A1515110010).

Association between phthalates exposure and myocardial damage in the general population: a cross-sectional study.

BACKGROUND: Cardiovascular consequences of phthalates exposure have been given increasing attention, but the association of phthalates with subclinical cardiovascular disease (CVD) was unknown. Accordingly, this study aimed to investigate the association between phthalates exposure and high-sensitivity cardiac troponin I (hs-cTnI), a marker of myocardial injury, which was detectable in the subclinical stage of CVD. METHODS: Participants aged 6 years or older with available urinary phthalates metabolites and serum hs-cTnI concentrations were included in the National Health and Nutrition Examination Survey 2003-2004 cycle. Multivariable linear regression and weighted quantiles sum (WQS) regression were used to assess the association of hs-cTnI with individual phthalates and their co-exposure. Di-2-ethylhexylphthalate (ΣDEHP), high-molecular-weight phthalate (ΣHMWP), and low-molecular-weight phthalate (ΣLMWP) were defined as the molecular sum of phthalates metabolites in urine. RESULTS: 2241 participants were finally included. The percent change of serum hs-cTnI concentrations related to per 1-standard deviation increase of logarithmic urinary phthalates concentrations was 3.4% (0.1 to 6.7, P = 0.04) for ΣDEHP, 3.6% (0.3 to 6.9, P = 0.03) for ΣHMWP, and 3.5% (0.2 to 6.8, P = 0.04) for ΣLMWP. Co-exposure to phthalates metabolites expressed as the WQS index also demonstrated a positive association with hs-cTnI. A similar association pattern was found in the population with no prior CVD. CONCLUSIONS: This study indicated the potential of phthalates to myocardial injury which may occur even before clinically apparent CVD was identified, emphasizing the significance of reducing phthalates in the prevention of CVD.

Determinants of Maximum Magnetic Anomaly Detection Distance.

The maximum detection distance is usually the primary concern of magnetic anomaly detection (MAD). Intuition tells us that larger object size, stronger magnetization and finer measurement resolution guarantee a further detectable distance. However, the quantitative relationship between detection distance and the above determinants is seldom studied. In this work, unmanned aerial vehicle-based MAD field experiments are conducted on cargo vessels and NdFeB magnets as typical magnetic objects to give a set of visualized magnetic field flux density images. Isometric finite element models are established, calibrated and analyzed according to the experiment configuration. A maximum detectable distance map as a function of target size and measurement resolution is then obtained from parametric sweeping on an experimentally calibrated finite element analysis model. We find that the logarithm of detectable distance is positively proportional to the logarithm of object size while negatively proportional to the logarithm of resolution, within the ranges of 1 m~500 m and 1 pT~1 µT, respectively. A three-parameter empirical formula (namely distance-size-resolution logarithmic relationship) is firstly developed to determine the most economic sensor configuration for a given detection task, to estimate the maximum detection distance for a given magnetic sensor and object, or to evaluate minimum detectable object size at a given magnetic anomaly detection scenario.

Tumor-Derived Exosomal miR-143-3p Induces Macrophage M2 Polarization to Cause Radiation Resistance in Locally Advanced Esophageal Squamous Cell Carcinoma.

We aimed to determine whether monitoring tumor-derived exosomal microRNAs (miRNAs) could be used to assess radiotherapeutic sensitivity in patients with locally advanced esophageal squamous cell carcinoma (ESCC). RNA sequencing was employed to conduct a comparative analysis of miRNA expression levels during radiotherapy, focusing on identifying miRNAs associated with progression. Electron microscopy confirmed the existence of exosomes, and co-cultivation assays and immunofluorescence validated their capacity to infiltrate macrophages. To determine the mechanism by which exosomal miR-143-3p regulates the interplay between ESCC cells and M2 macrophages, ESCC cell-derived exosomes were co-cultured with macrophages. Serum miR-143-3p and miR-223-3p were elevated during radiotherapy, suggesting resistance to radiation and an unfavorable prognosis for ESCC. Increased levels of both miRNAs independently predicted shorter progression-free survival (p = 0.015). We developed a diagnostic model for ESCC using serum microRNAs, resulting in an area under the curve of 0.751. Radiotherapy enhanced the release of miR-143-3p from ESCC cell-derived exosomes. Immune cell infiltration analysis at the Cancer Genome Atlas (TCGA) database revealed that ESCC cell-derived miR-143-3p triggered M2 macrophage polarization. Mechanistically, miR-143-3p upregulation affected chemokine activity and cytokine signaling pathways. Furthermore, ESCC cell exosomal miR-143-3p could be transferred to macrophages, thereby promoting their polarization. Serum miR-143-3p and miR-223-3p could represent diagnostic and prognostic markers for patients with ESCC undergoing radiotherapy. Unfavorable prognosis could be linked to the increased levels of ESCC cell-derived exosomal miR-143-3p, which might promote tumor progression by interacting with macrophages.

An analysis of AURKB's prognostic and immunological roles across various cancers.

Aurora kinase B (AURKB), an essential regulator in the process of mitosis, has been revealed through various studies to have a significant role in cancer development and progression. However, the specific mechanisms remain poorly understood. This study, therefore, seeks to elucidate the multifaceted role of AURKB in diverse cancer types. This study utilized bioinformatics techniques to examine the transcript, protein, promoter methylation and mutation levels of AURKB. The study further analysed associations between AURKB and factors such as prognosis, pathological stage, biological function, immune infiltration, tumour mutational burden (TMB) and microsatellite instability (MSI). In addition, immunohistochemical staining data of 50 cases of renal clear cell carcinoma and its adjacent normal tissues were collected to verify the difference in protein expression of AURKB in the two tissues. The results show that AURKB is highly expressed in most cancers, and the protein level of AURKB and the methylation level of its promoter vary among cancer types. Survival analysis showed that AURKB was associated with overall survival in 12 cancer types and progression-free survival in 11 cancer types. Elevated levels of AURKB were detected in the advanced stages of 10 different cancers. AURKB has a potential impact on cancer progression through its effects on cell cycle regulation as well as inflammatory and immune-related pathways. We observed a strong association between AURKB and immune cell infiltration, immunomodulatory factors, TMB and MSI. Importantly, we confirmed that the AURKB protein is highly expressed in kidney renal clear cell carcinoma (KIRC). Our study reveals that AURKB may be a potential biomarker for pan-cancer and KIRC.

Evaluating the Causal Effects of Low Density Lipoprotein Cholesterol Levels on Ischemic Stroke: A Mendelian Randomization Study.

Background: Ischemic stroke (IS) is the leading cause of disability and mortality worldwide. Low-density lipoprotein cholesterol (LDL-C) levels hadno potential risk on ischemic stroke. However, higher LDL-C levels were closely related to IS. Based on two antagonistic viewpoints, a Mendelian randomization (MR) study was designed to evaluate the causal effects of LDL-C levels on IS. Methods: Datasets of LDL-C levels and ischemic stroke were acquired from genome-wide association studies (GWAS). Weighted median method was conducted for main analysis, and MR-Egger and inverse-variance weighted (IVW) methods were performed for auxiliary analyses. Heterogeneity and pleiotropic tests were utilized to confirm the reliability of this study. Results: A total of 359 single nucleotide polymorphisms (SNPs) were associated with LDL-C levels (P < 5 × 10-8) and 337 SNPs were available in ischemic stroke with eliminating outliers. LDL-C levels were significantly associated with ischemic stroke (OR = 1.104, 95%CI = 1.019 - 1.195, P = 1.52 × 10-2). MR-Egger and IVW showed directionally similar estimates (MR-Egger: OR = 1.120, 95%CI = 1.040 - 1.207, P = 3.12 × 10-3; IVW: OR = 1.120, 95%CI = 1.064 - 1.178, P = 1.17 × 10-5). Conclusion: LDL-C levels had causal effects on IS, providing insights into the design of future interventions to reduce the burden of ischemic stroke.

A multi-omic single-cell landscape of cellular diversification in the developing human cerebral cortex.

The vast neuronal diversity in the human neocortex is vital for high-order brain functions, necessitating elucidation of the regulatory mechanisms underlying such unparalleled diversity. However, recent studies have yet to comprehensively reveal the diversity of neurons and the molecular logic of neocortical origin in humans at single-cell resolution through profiling transcriptomic or epigenomic landscapes, owing to the application of unimodal data alone to depict exceedingly heterogeneous populations of neurons. In this study, we generated a comprehensive compendium of the developing human neocortex by simultaneously profiling gene expression and open chromatin from the same cell. We computationally reconstructed the differentiation trajectories of excitatory projection neurons of cortical origin and inferred the regulatory logic governing lineage bifurcation decisions for neuronal diversification. We demonstrated that neuronal diversity arises from progenitor cell lineage specificity and postmitotic differentiation at distinct stages. Our data paves the way for understanding the primarily coordinated regulatory logic for neuronal diversification in the neocortex.

The cumulative antitumor effects of regorafenib and radiotherapy in hepatocellular carcinoma.

Regorafenib is a second-line standard treatment for hepatocellular carcinoma (HCC). However, the efficacy of regorafenib is often limited due to drug resistance, individual differences among patients, and irrational drug use. Radiotherapy (RT) is an important method of localized HCC treatment, and combining RT with other therapies may exert a synergetic antitumor effect. Platelet-derived growth factor receptor-like (PDGFRL) is a tumor suppressor in various solid tumors. However, the function of PDGFRL in HCC is still unknown. In this study, we explored whether regorafenib and RT exert a synergetic effect on the treatment of HCC. The antitumor effect and mechanisms of the combination of regorafenib and RT were verified in a xenograft mouse model in vivo and in HCC cells in vitro. The combination treatment significantly inhibited cell proliferation and promoted apoptosis both in vitro and in vivo. PDGFRL, a potential target of regorafenib, was increased after cumulative treatment in HCC cells, and PDGFRL suppressed HCC cell proliferation and promoted apoptosis by inhibiting STAT3 pathway activation. Furthermore, the cumulative antitumor effect was dependent on the upregulated expression of PDGFRL and inhibition of STAT3 signaling pathway activation in HCC cells. This study increased the understanding of the molecular mechanism underlying the effect of regorafenib plus RT on HCC and provided a theoretical basis for the clinical practice of HCC.

Materials Advances in Photocatalytic Solar Hydrogen Production: Integrating Systems and Economics for a Sustainable Future.

Photocatalytic solar hydrogen generation, encompassing both overall water splitting and organic reforming, presents a promising avenue for green hydrogen production. This technology holds the potential for reduced capital costs in comparison to competing methods like photovoltaic-electrocatalysis and photoelectrocatalysis, owing to its simplicity and fewer auxiliary components. However, the current solar-to-hydrogen efficiency of photocatalytic solar hydrogen production has predominantly remained low at ≈1-2% or lower, mainly due to curtailed access to the entire solar spectrum, thus impeding practical application of photocatalytic solar hydrogen production. This review offers an integrated, multidisciplinary perspective on photocatalytic solar hydrogen production. Specifically, the review presents the existing approaches in photocatalyst and system designs aimed at significantly boosting the solar-to-hydrogen efficiency, while also considering factors of cost and scalability of each approach. In-depth discussions extending beyond the efficacy of material and system design strategies are particularly vital to identify potential hurdles in translating photocatalysis research to large-scale applications. Ultimately, this review aims to provide understanding and perspective of feasible pathways for commercializing photocatalytic solar hydrogen production technology, considering both engineering and economic standpoints.

Serine protease Rv2569c facilitates transmission of Mycobacterium tuberculosis via disrupting the epithelial barrier by cleaving E-cadherin.

Epithelial cells function as the primary line of defense against invading pathogens. However, bacterial pathogens possess the ability to compromise this barrier and facilitate the transmigration of bacteria. Nonetheless, the specific molecular mechanism employed by Mycobacterium tuberculosis (M.tb) in this process is not fully understood. Here, we investigated the role of Rv2569c in M.tb translocation by assessing its ability to cleave E-cadherin, a crucial component of cell-cell adhesion junctions that are disrupted during bacterial invasion. By utilizing recombinant Rv2569c expressed in Escherichia coli and subsequently purified through affinity chromatography, we demonstrated that Rv2569c exhibited cell wall-associated serine protease activity. Furthermore, Rv2569c was capable of degrading a range of protein substrates, including casein, fibrinogen, fibronectin, and E-cadherin. We also determined that the optimal conditions for the protease activity of Rv2569c occurred at a temperature of 37°C and a pH of 9.0, in the presence of MgCl2. To investigate the function of Rv2569c in M.tb, a deletion mutant of Rv2569c and its complemented strains were generated and used to infect A549 cells and mice. The results of the A549-cell infection experiments revealed that Rv2569c had the ability to cleave E-cadherin and facilitate the transmigration of M.tb through polarized A549 epithelial cell layers. Furthermore, in vivo infection assays demonstrated that Rv2569c could disrupt E-cadherin, enhance the colonization of M.tb, and induce pathological damage in the lungs of C57BL/6 mice. Collectively, these results strongly suggest that M.tb employs the serine protease Rv2569c to disrupt epithelial defenses and facilitate its systemic dissemination by crossing the epithelial barrier.

Autoimmune diseases and the risk of bladder cancer: A Mendelian randomization analysis.

OBJECTIVE: To investigate the association between autoimmune diseases (AIDs) and bladder cancer (BC) at the genetic level using Mendelian randomization (MR). METHODS: Single nucleotide polymorphisms (SNPs) associated with the seven AIDs were extracted from the IEU GWAS database, and the SNPs were quality-controlled using strict screening criteria. The association between AIDs and BC risk was assessed by inverse-variance weighted (IVW), MR-Egger regression and Weighted median method. The heterogeneity of SNPs was evaluated by Cochran Q test. MR-Egger intercept test and MR-PRESSO global test were used to test the horizontal pleiotropy of SNPs. Both sides with potential causal associations were validated using the validation set. RESULTS: Our result showed that genetically predicted RA was significantly associated with an increased risk of BC (IVW OR = 1.214, 95 % CI = 1.062-1.388, P = 0.005). MS nominally increased the risk of BC (IVW OR = 1.095, 95 % CI = 1.005-1.193, P = 0.037), consistent with the results of the MR analysis of the BC validation cohort. However SLE, T1D, UC, CD, and MG were not causally associated with BC risk (P > 0.05). The sensitivity analyses showed that there was no heterogeneity or horizontal pleiotropy in our findings. CONCLUSION: This study provides evidence of a causal relationship between AIDs and BC risk at the genetic level, confirming a causal relationship between RA and MS in increasing the risk of BC.

A deep learning based multi-model approach for predicting drug-like chemical compound's toxicity.

Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate prediction of compound toxicity using deep learning models offers a promising solution to mitigate these risks during drug discovery. In this study, we present the development of several deep-learning models aimed at evaluating different types of compound toxicity, including acute toxicity, carcinogenicity, hERG_cardiotoxicity (the human ether-a-go-go related gene caused cardiotoxicity), hepatotoxicity, and mutagenicity. To address the inherent variations in data size, label type, and distribution across different types of toxicity, we employed diverse training strategies. Our first approach involved utilizing a graph convolutional network (GCN) regression model to predict acute toxicity, which achieved notable performance with Pearson R 0.76, 0.74, and 0.65 for intraperitoneal, intravenous, and oral administration routes, respectively. Furthermore, we trained multiple GCN binary classification models, each tailored to a specific type of toxicity. These models exhibited high area under the curve (AUC) scores, with an impressive AUC of 0.69, 0.77, 0.88, and 0.79 for predicting carcinogenicity, hERG_cardiotoxicity, mutagenicity, and hepatotoxicity, respectively. Additionally, we have used the approved drug dataset to determine the appropriate threshold value for the prediction score in model usage. We integrated these models into a virtual screening pipeline to assess their effectiveness in identifying potential low-toxicity drug candidates. Our findings indicate that this deep learning approach has the potential to significantly reduce the cost and risk associated with drug development by expediting the selection of compounds with low toxicity profiles. Therefore, the models developed in this study hold promise as critical tools for early drug candidate screening and selection.

Spatial variability and source analysis of soil heavy metals: A case study of the key planting area of special agricultural products in Cangxi County, China.

Heavy metal pollution in farmland soil represents a considerable risk to ecosystems and human health, constituting a global concern. Focusing on a key area for the cultivation of special agricultural products in Cangxi County, we collected 228 surface soil samples. We analyzed the concentration, spatial distribution, and pollution levels of six heavy metals (Cr, Cu, Pb, Ni, Zn, and Hg) in the soil. Moreover, we investigated the sources and contribution rates of these heavy metals using Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS) and Positive Matrix Factorization (PMF) models. Our findings indicate that none of the six metals exceeded the pollution thresholds for farmland soils. However, the mean concentrations of Cr and Ni surpassed the background levels of Sichuan Province. A moderate spatial correlation existed between Pb and Ni, attributable to both natural and anthropogenic factors, whereas Zn, Cu, Hg, and Cr displayed a strong spatial correlation, mainly due to natural factors. The spatial patterns of Cr, Cu, Zn, Pb, and Ni were similar, with higher concentrations in the northern and eastern regions and lower concentrations centrally. Hg's spatial distribution differed, exhibiting a broader range of lower values. The single pollution index evaluation showed that Cr and Ni were low pollution, and the other elements were no pollution. The average value of comprehensive pollution index is 0.994, and the degree of pollution is close to light pollution. Predominantly, higher pollution levels in the northern and eastern regions, lower around reservoirs. The PCA/APCS model identified two main pollution sources: agricultural traffic mixed source (65.2%) and natural parent source (17.2%). The PMF model delineated three sources: agricultural activities (32.59%), transportation (30.64%), and natural parent sources (36.77%). Comparatively, the PMF model proved more accurate and reliable, yielding findings more aligned with the study area's actual conditions.

Alterations of Myocardial Mitochondrial Morphology and Function in a Canine Model of Premature Ventricular Contractions-Induced Cardiomyopathy.

AIMS: Changes in myocardial mitochondrial morphology and function in premature ventricular contractions (PVCs)-induced cardiomyopathy (PVCCM) remain poorly studied. Here, we investigated the effects of PVCs with different coupling intervals (CIs) on myocardial mitochondrial remodelling in a canine model of PVCCM. METHODS AND RESULTS: Twenty-one beagles underwent pacemaker implantation and were randomised into the sham (n = 7), short-coupled PVCs (SCP, n = 7), and long-coupled PVCs (LCP, n = 7) groups. Right ventricular (RV) apical bigeminy was produced for 12-week to induce PVCCM in the SCP (CI, 250 ms) and LCP (CI, 350 ms) groups. Echocardiography was performed at baseline and biweekly thereafter to evaluate cardiac function. Masson's trichrome staining measured ventricular interstitial fibrosis. The ultrastructural morphology of the myocardial mitochondria was analysed using transmission electron microscopy. Mitochondrial Ca2+ concentration, reactive oxygen species (ROS) levels, adenosine triphosphate (ATP) content, membrane potential, and electron transport chain (ETC) complex activity were measured to assess myocardial mitochondrial function. Twelve-week-PVCs led to left ventricular (LV) enlargement with systolic dysfunction, disrupted mitochondrial morphology, increased mitochondrial Ca2+ concentration and ROS levels, decreased mitochondrial ATP content and membrane potential, and impaired ETC complex activity in both the SCP and LCP groups (all p < 0.01 vs the sham group). Ventricular fibrosis was observed only in canines with LCP. Worse cardiac function and more pronounced abnormalities in mitochondrial morphology and function were observed in the LCP group than to the SCP group (all p < 0.05). CONCLUSION: We demonstrated myocardial mitochondrial abnormalities in dogs with PVCCM, characterised by abnormal mitochondrial morphology, mitochondrial Ca2+ overload, oxidative stress, and impaired mitochondrial energy metabolism. Compared to SCP, long-term LCP exposure resulted in more severe mitochondrial remodelling and cardiac dysfunction in dogs.

Durable and Robust Antibacterial Polypropylene Hernia Mesh for Abdominal Wall Defect Repair.

Polypropylene (PP) mesh is commonly used in repairing abdominal wall hernia (AWH). However, the use of synthetic prosthesis comes with the risk of developing a prosthetic infection, resulting in delayed healing, secondary surgery, and potentially increased mortality. To address these issues, a facile surface functionalization strategy for PP mesh based on phytic acid (PA) and polyhexamethylene guanidine (PHMG) was constructed through a one-step co-deposition process, referred to as the PA/PHMG coating. The development of PA/PHMG coating is mainly attributed to the surface affinity of PA and the electrostatic interactions between PA and PHMG. The PA/PHMG coating could be completed within 4 h under mild conditions. The prepared PA/PHMG coatings on PP mesh surfaces exhibited desirable biocompatibility toward mammalian cells and excellent antibacterial properties against the notorious "superbug" methicillin-resistant Staphylococcus aureus (MRSA) and tetracycline-resistant Escherichia coli (TRE). The PA/PHMG-coated PP meshes showed killing ratios of over 99% against MRSA in an infected abdominal wall hernia repair model. Furthermore, histological and immunohistochemical analysis revealed a significantly attenuated degree of neutrophil infiltration in the PA/PHMG coating group, attributed to the decreased bacterial numbers alleviating the inflammatory response at the implant sites. Meanwhile, the pristine PP and PA/PHMG-coated meshes showed effective tissue repair, with the PA/PHMG coating group exhibiting enhanced angiogenesis compared with pristine PP meshes, suggesting superior tissue restoration. Additionally, PP meshes with the highest PHMG weight ratio (PA/PHMG(3)) exhibited excellent long-term robustness under phosphate-buffered saline (PBS) immersion with a killing ratio against MRSA still exceeding 95% after 60 days of PBS immersion. The present work provides a facile and promising approach for developing antibacterial implants.

Trends and disparities in the prevalence of physical activity among US adults with epilepsy, 2010-2022.

BACKGROUND: Physical activity may be associated with health benefits for people with epilepsy. It remains unclear how the prevalence of physical activity has changed at a national level over the years and whether this prevalence varies between subgroups. METHODS: The National Health and Interview Survey, which was conducted from 2010 to 2017 and again in 2022, was used for our nationally representative study. This study explored the trends and disparities in meeting physical activity guidelines among US individuals with epilepsy and non-epilepsy adults. RESULTS: The prevalence of adults with epilepsy meeting physical activity guidelines was consistently lower and remained unchanged compared to those without epilepsy. Among the population with epilepsy, the prevalence of aerobic physical activity was 38.1 % (95 % CI, 32.6 %-43.5 %) in 2010 and 39.0 % (95 % CI, 33.4 %-44.7 %) in 2017 (P for trend = 0.84), and remained unchanged in 2022 (39.1 %). For muscle-strength training, the prevalence was 17.5 % (95 % CI, 13.3 %-21.7 %) in 2010 and 18.8 % (95 % CI, 14.8 %-22.8 %) in 2017 (P for trend = 0.82). The prevalence for both activities combined was 12.4 % (95 % CI, 8.7 %-16.2 %) in 2010 and 16.6 % (95 % CI, 12.8 %-20.5 %) in 2017 (P for trend = 0.26). The prevalence of aerobic physical activity varied by educational attainment, body mass index, comorbid conditions, alcohol-drinking status, and epilepsy status. CONCLUSION: This study suggests that the adherence rate to meeting physical activity guidelines among US adults with epilepsy was at a low level and had not improved over time. This finding highlights the need for additional nationwide efforts to promote physical activity in the US population with epilepsy.

Frailty as an Effect Modifier in Randomized Controlled Trials: A Systematic Review.

BACKGROUND: The effect of clinical interventions may vary by patients' frailty status. Understanding treatment effect heterogeneity by frailty could lead to frailty-guided treatment strategies and reduce overtreatment and undertreatment. This systematic review aimed to examine the effect modification by frailty in randomized controlled trials (RCTs) that evaluate pharmacological, non-pharmacological, and multicomponent interventions. METHODS: We searched PubMed, Web of Science, EMBASE, and ClinicalTrial.gov, from their inception to 8 December 2023. Two reviewers independently extracted trial data and examined the study quality with senior authors. RESULTS: Sixty-one RCTs that evaluated the interaction between frailty and treatment effects in older adults were included. Frailty was evaluated using different tools such as the deficit accumulation frailty index, frailty phenotype, and other methods. The effect of several pharmacological interventions (e.g., edoxaban, sacubitril/valsartan, prasugrel, and chemotherapy) varied according to the degree of frailty, whereas other treatments (e.g., antihypertensives, vaccinations, osteoporosis medications, and androgen medications) demonstrated consistent benefits across different frailty levels. Some non-pharmacological interventions had greater benefits in patients with higher (e.g., chair yoga, functional walking, physical rehabilitation, and higher dose exercise program) or lower (e.g., intensive lifestyle intervention, psychosocial intervention) levels of frailty, while others (e.g., resistance-type exercise training, moderate-intensive physical activity, walking and nutrition or walking) produced similar intervention effects. Specific combined interventions (e.g., hospital-based disease management programs) demonstrated inconsistent effects across different frailty levels. DISCUSSION: The efficacy of clinical interventions often varied by frailty levels, suggesting that frailty is an important factor to consider in recommending clinical interventions in older adults. REGISTRATION: PROSPERO registration number CRD42021283051.

Swift Covalent Gelation Coupled with Robust Wet Adhesive Powder: A Novel Approach for Acute Massive Hemorrhage Control in Dynamic and High-Pressure Wound Environments.

The quest for efficient hemostatic agents in emergency medicine is critical, particularly for managing massive hemorrhages in dynamic and high-pressure wound environments. Traditional self-gelling powders, while beneficial due to their ease of application and rapid action, fall short in such challenging conditions. To bridge this gap, the research introduces a novel self-gelling powder that combines ultrafast covalent gelation and robust wet adhesion, presenting a significant advancement in acute hemorrhage control. This ternary system comprises ε-polylysine (ε-PLL) and 4-arm polyethylene glycol succinyl succinate (4-arm-PEG-NHS) forming the hydrogel framework. Na2HPO4 functions as the "H+ sucker" to expedite the amidation reaction, slashing gelation time to under 10 s, crucial for immediate blood loss restriction. Moreover, PEG chains' hydrophilicity facilitates efficient absorption of interfacial blood, increasing the generated hydrogel's cross-linking density and strengthens its tissue bonding, thereby resulting in excellent mechanical and wet adhesion properties. In vitro experiments reveal the optimized formulation's exceptional tissue compliance, procoagulant activity, biocompatibility and antibacterial efficacy. In porcine models of heart injuries and arterial punctures, it outperforms commercial hemostatic agent Celox, confirming its rapid and effective hemostasis. Conclusively, this study presents a transformative approach to hemostasis, offering a reliable and potent solution for the emergency management of massive hemorrhage.