The involvement of SigmaR1K142 degradation mediated by ERAD in neural senescence linked with CdCl2 exposure.

Alzheimer's disease (AD) is the most common cause of dementia worldwide. Due to its uncertain pathogenesis, there is currently no treatment available for AD. Increasing evidences have linked cellular senescence to AD, although the mechanism triggering cellular senescence in AD requires further exploration. To investigate the involvement of cellular senescence in AD, we explored the effects of cadmium chloride (CdCl2) exposure, one of the potential environmental risk factors for AD, on neuron senescence in vivo and in vitro. ß-amyloid (Aß) and tubulin-associated protein (tau) pathologies were found to be enhanced by CdCl2 exposure in the in vitro models, while p53/p21/Rb cascade-related neuronal senescence pathways were activated. Conversely, the use of melatonin, a cellular senescence inhibitor, or a cadmium ion chelator suppressed CdCl2-induced neuron senescence, along with the Aß and tau pathologies. Mechanistically, CdCl2 exposure activated the suppressor enhancer Lin-12/Notch 1-like (SEL1L)/HMG-CoA reductase degradation 1 (HRD1)-regulated endoplasmic reticulum-associated degradation (ERAD), which enhanced the ubiquitin degradation of sigma-1 receptor (SigmaR1) by specifically recognizing its K142 site, resulting in the activation of the p53/p21/Rb pathway via the induction of Ca2+ dyshomeostasis and mitochondrial dysfunction. In the in vivo models, the administration of the SigmaR1 agonist ANAVEX2-73 rescues neurobehavioral inhibition and alleviates cellular senescence and AD-like pathology in the brain tissue of CdCl2-exposed mice. Consequently, the present study revealed a novel senescence-associated regulatory route for the SEL1L/HRD1/SigmaR1 axis that affects the pathological progression of CdCl2 exposure-associated AD. CdCl2 exposure activated SEL1L/HRD1-mediated ERAD and promoted the ubiquitinated degradation of SigmaR1, activating p53/p21/Rb pathway-regulated neuronal senescence. The results of the present study suggest that SigmaR1 may function as a neuroprotective biomarker of neuronal senescence, and pharmacological activation of SigmaR1 could be a promising intervention strategy for AD therapy.

Enhanced versus standard hydration in acute ischaemic stroke: REVIVE - a randomised clinical trial.

RATIONALE: Early neurological deterioration (END) within 72 hours of stroke onset is associated with poor prognosis. Optimising hydration might reduce the risk of END. AIMS: To determine in acute ischaemic stroke patients if enhanced hydration versus standard hydration reduced the incidence of major (primary) and minor (secondary) END, as whether it increased the incidence of early neurological improvement (secondary), at 72 hours after admissionSample Size Estimate: 244 participants per arm. METHODS AND DESIGN: A prospective, double-blinded, multicentre, parallel-group, randomised controlled trial conducted at 4 hospitals from April 2014 to July 2020, with data analysed in August 2020. The sample size estimated was 488 participants (244 per arm). Ischaemic stroke patients with measurable neurological deficits of onset within 12 hours of emergency department presentation and blood urea nitrogen/creatinine (BUN/Cr) ratio ≥15 at point of admission were enrolled and randomised to 0.9% sodium chloride infusions of varying rates - enhanced hydration (20 mL/kg body weight, one-third given via bolus and remainder over 8 hours) versus standard hydration (60 mL/hour for 8 hours), followed by maintenance infusion of 40-80 mL/hour for the subsequent 64 hours. The primary outcome measure was the incidence of major early neurological deterioration at 72 hours after admission, defined as an increase in National Institutes of Health Stroke Scale of ≥4 points from baseline. RESULTS: 487 participants were randomised (median age 67 years; 287 females). At 72 hours: 7 (2.9%) in the enhanced-hydration arm and 5(2.0%) in the standard-hydration developed major early neurological deterioration (p=0.54). The incidence of minor early neurological deterioration and early neurological improvement did not differ between treatment arms. CONCLUSIONS AND RELEVANCE: Enhanced hydration ratio did not reduce END or improve short term outcomes in acute ischaemic stroke. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02099383, https://clinicaltrials.gov/study/NCT02099383).

3D visualization technology for Learning human anatomy among medical students and residents: a meta- and regression analysis.

BACKGROUND: 3D visualization technology applies computers and other devices to create a realistic virtual world for individuals with various sensory experiences such as 3D vision, touch, and smell to gain a more effective understanding of the relationships between real spatial structures and organizations. The purpose of this study was to comprehensively evaluate the effectiveness of 3D visualization technology in human anatomy teaching/training and explore the potential factors that affect the training effects to better guide the teaching of classroom/laboratory anatomy. METHODS: We conducted a meta-analysis of randomized controlled studies on teaching human anatomy using 3D visualization technology. We extensively searched three authoritative databases, PubMed, Web of Science, and Embase; the main outcomes were the participants' test scores and satisfaction, while the secondary outcomes were time consumption and enjoyment. Heterogeneity by I² was statistically determined because I²> 50%; therefore, a random-effects model was employed, using data processing software such as RevMan, Stata, and VOSviewer to process data, apply standardized mean difference and 95% confidence interval, and subgroup analysis to evaluate test results, and then conduct research through sensitivity analysis and meta-regression analysis. RESULTS: Thirty-nine randomized controlled trials (2,959 participants) were screened and included in this study. The system analysis of the main results showed that compared with other methods, including data from all regions 3D visualization technology moderately improved test scores as well as satisfaction and enjoyment; however, the time that students took to complete the test was not significantly reduced. Meta-regression analysis also showed that regional factorsaffected test scores, whereas other factors had no significant impact. When the literature from China was excluded, the satisfaction and happiness of the 3D virtual-reality group were statistically significant compared to those of the traditional group; however, the test results and time consumption were not statistically significant. CONCLUSION: 3D visualization technology is an effective way to improve learners' satisfaction with and enjoyment of human anatomical learning, but it cannot reduce the time required for testers to complete the test. 3D visualization technology may struggle to improve the testers' scores. The literature test results from China are more prone to positive results and affected by regional bias.

Aflatoxin B1-exposed hepatocyte-derived extracellular vesicles: Initiating hepatic stellate cell-mediated liver fibrosis through a p53-Parkin-dependent mitophagy pathway.

Environmental aflatoxin B1 (AFB1) exposure has been proposed to contribute to hepatocellular carcinoma by promoting liver fibrosis, but the potential mechanisms remain to be further elucidated. Extracellular vesicles (EVs) were recognized as crucial traffickers for hepatic intercellular communication and play a vital role in the pathological process of liver fibrosis. The AFB1-exposed hepatocyte-derived EVs (AFB1-EVs) were extracted, and the functional effects of AFB1-EVs on the activation of hepatic stellate cells (HSCs) were explored to investigate the molecular mechanism of AFB1 exposure-induced liver fibrogenesis. Our results revealed that an environment-level AFB1 exposure induced liver fibrosis via HSCs activation in mice, while the AFB1-EVs mediated hepatotoxicity and liver fibrogenesis in vitro and in vivo. AFB1 exposure in vitro increased PINK1/Parkin-dependent mitophagy in hepatocytes, where upregulated transcription of the PARK2 gene via p53 nuclear translocation and mitochondrial recruitment of Parkin, and promoted AFB1-EVs-mediated mitochondria-trafficking communication between hepatocytes and HSCs. The knockdown of Parkin in HepaRG cells reversed HSCs activation by blocking the mitophagy-related AFB1-EVs trafficking. This study further revealed that the hepatic fibrogenesis of AFB1 exposure was rescued by genetic intervention with siPARK2 or p53's Pifithrin-α (PFTα) inhibitors. Furthermore, AFB1-EVs-induced HSCs activation was relieved by GW4869 pharmaceutic inhibition of EVs secretion. These results revealed a novel mechanism that AFB1 exposure-induced p53-Parkin signal axis regulated mitophagy-dependent hepatocyte-derived EVs to mediate the mitochondria-trafficking intercellular communication between hepatocytes and HSCs in the local hepatotoxic microenvironment to promote the activated HSCs-associated liver fibrogenesis. Our study provided insight into p53-Parkin-dependent pathway regulation and promised an advanced strategy targeting intervention to EVs-mediated mitochondria trafficking for preventing xenobiotics-induced liver fibrosis.

Never-Ending Learning for Explainable Brain Computing.

Exploring the nature of human intelligence and behavior is a longstanding pursuit in cognitive neuroscience, driven by the accumulation of knowledge, information, and data across various studies. However, achieving a unified and transparent interpretation of findings presents formidable challenges. In response, an explainable brain computing framework is proposed that employs the never-ending learning paradigm, integrating evidence combination and fusion computing within a Knowledge-Information-Data (KID) architecture. The framework supports continuous brain cognition investigation, utilizing joint knowledge-driven forward inference and data-driven reverse inference, bolstered by the pre-trained language modeling techniques and the human-in-the-loop mechanisms. In particular, it incorporates internal evidence learning through multi-task functional neuroimaging analyses and external evidence learning via topic modeling of published neuroimaging studies, all of which involve human interactions at different stages. Based on two case studies, the intricate uncertainty surrounding brain localization in human reasoning is revealed. The present study also highlights the potential of systematization to advance explainable brain computing, offering a finer-grained understanding of brain activity patterns related to human intelligence.

Outcomes of endoscopic sclerotherapy for jejunal varices at the site of choledochojejunostomy (with video): Three case reports.

BACKGROUND: Hemorrhage associated with varices at the site of choledochojejunostomy is an unusual, difficult to treat, and often fatal manifestation of portal hypertension. So far, no treatment guidelines have been established. CASE SUMMARY: We reported three patients with jejunal varices at the site of choledochojejunostomy managed by endoscopic sclerotherapy with lauromacrogol/α-butyl cyanoacrylate injection at our institution between June 2021 and August 2023. We reviewed all patient records, clinical presentation, endoscopic findings and treatment, outcomes and follow-up. Three patients who underwent pancreaticoduodenectomy with a Whipple anastomosis were examined using conventional upper gastrointestinal endoscopy for suspected hemorrhage from the afferent jejunal loop. Varices with stigmata of recent hemorrhage or active hemorrhage were observed around the choledochojejunostomy site in all three patients. Endoscopic injection of lauromacrogol/α-butyl cyanoacrylate was carried out at jejunal varices for all three patients. The bleeding ceased and patency was observed for 26 and 2 months in two patients. In one patient with multiorgan failure and internal environment disturbance, rebleeding occurred 1 month after endoscopic sclerotherapy, and despite a second endoscopic sclerotherapy, repeated episodes of bleeding and multiorgan failure resulted in eventual death. CONCLUSION: We conclude that endoscopic sclerotherapy with lauromacrogol/α-butyl cyanoacrylate injection can be an easy, effective, safe and low-cost treatment option for jejunal varicose bleeding at the site of choledochojejunostomy.

Biomedical Applications of Sulfonylcalix[4]arene-Based Metal-Organic Supercontainers.

Coordination cages sustained by metal-ligand interactions feature polyhedral architectures and well-defined hollow structures, which have attracted significant attention in recent years due to a variety of structure-guided promising applications. Sulfonylcalix[4]arenes-based coordination cages, termed metal-organic supercontainers (MOSCs), that possess unique multi-pore architectures containing an endo cavity and multiple exo cavities, are emerging as a new family of coordination cages. The well-defined built-in multiple binding domains of MOSCs allow the efficient encapsulation of guest molecules, especially for drug delivery. Here, we critically discuss the design strategy, and, most importantly, the recent advances in research surrounding cavity-specified host-guest chemistry and biomedical applications of MOSCs.

Effectively Enhancing the Conductance of Asymmetric Molecular Wires by Aligning the Energy Level and Symmetrizing the Coupling.

An asymmetric structure is an important strategy for designing highly conductive molecular wires for a gap-fixed molecular circuit. As the conductance enhancement in the current strategy is still limited to about 2 times, we inserted a methylene group as a spacer in a conjugated structure to modulate the structural symmetry. We found that the conductance drastically enhanced in the asymmetric molecular wire to 1.5 orders of magnitude as high as that in the symmetric molecular wire. First-principles quantum transport studies attributed the effective enhancement to the synchronization of improved energy alignment and nearly symmetric coupling between the frontier orbitals and the electrodes.

Identification of Immune Infiltration and Iron Metabolism-Related Subgroups in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with a broad spectrum of symptoms and prognoses. Effective therapy requires understanding this variability. ASD children's cognitive and immunological development may depend on iron homoeostasis. This study employs a machine learning model that focuses on iron metabolism hub genes to identify ASD subgroups and describe immune infiltration patterns. A total of 97 control and 148 ASD samples were obtained from the GEO database. Differentially expressed genes (DEGs) and an iron metabolism gene collection achieved the intersection of 25 genes. Unsupervised cluster analysis determined molecular subgroups in individuals with ASD based on 25 genes related to iron metabolism. We assessed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, gene set variation analysis (GSVA), and immune infiltration analysis to compare iron metabolism subtype effects. We employed machine learning to identify subtype-predicting hub genes and utilized both training and validation sets to assess gene subtype prediction accuracy. ASD can be classified into two iron-metabolizing molecular clusters. Metabolic enrichment pathways differed between clusters. Immune infiltration showed that clusters differed immunologically. Cluster 2 had better immunological scores and more immune cells, indicating a stronger immune response. Machine learning screening identified SELENBP1 and CAND1 as important genes in ASD's iron metabolism signaling pathway. These genes express in the brain and have AUC values over 0.8, implying significant predictive power. The present study introduces iron metabolism signaling pathway indicators to predict ASD subtypes. ASD is linked to immune cell infiltration and iron metabolism disorders.

Interventing mitochondrial PD-L1 suppressed IFN-γ-induced cancer stemness in hepatocellular carcinoma by sensitizing sorafenib-induced ferroptosis.

Evidence recently showed that pleiotropic cytokine interferon-gamma (IFN-γ) in the tumor microenvironment (TME) plays a positive role in hepatocellular carcinoma (HCC) progression through the regulation of liver cancer stem cells (LCSCs) in HCC. The present study explored the role and potential mechanism of mitochondrial programmed cell death-ligand 1 (PD-L1) and its regulation of ferroptosis in modulating the cancer stemness of LCSCs. It was shown that mimicking TME IFN-γ exposure increased the LCSCs ratio and cancer stemness phenotypes in HCC cells. IFN-γ exposure inhibited sorafenib (Sora)-induced ferroptosis by enhancing glutathione peroxidase 4 (GPX4) expression as well reactive oxygen species (ROS) and lipid peroxidation (LPO) generation in LCSCs. Furthermore, IFN-γ exposure upregulated PD-L1 expression and its mitochondrial translocation, inducing dynamin-related protein 1 (Drp1)-dependent mitochondrial fission and correlating with glycolytic metabolism reprogramming in LCSCs. The genetic intervention of PD-L1 promoted ferroptosis-dependent anti-tumor effects of Sora, reduced glycolytic metabolism reprogramming, and inhibited cancer stemness of HCC in vitro and in vivo. Our results revealed a novel mechanism that IFN-γ exposure-induced mitochondrial translocation of PD-L1 enhanced glycolytic reprogramming to mediate the GPX4-dependent ferroptosis resistance and cancer stemness in LCSCs. This study provided new insights into the role of mitochondrial PD-L1-Drp1-GPX4 signal axis in regulating IFN-γ exposure-associated cancer stemness in LCSCs and verified that PD-L1-targeted intervention in combination with Sora might achieve promising synergistic anti-HCC effects.

Endoscopic ultrasound-based application system for predicting endoscopic resection-related outcomes and diagnosing subepithelial lesions: Multicenter prospective study.

OBJECTIVES: Subepithelial lesions (SELs) are associated with various endoscopic resection (ER) outcomes and diagnostic challenges. We aimed to establish a tool for predicting ER-related outcomes and diagnosing SELs and to investigate the predictive value of endoscopic ultrasound (EUS). METHODS: Phase 1 (system development) was performed in a retrospective cohort (n = 837) who underwent EUS before ER for SELs at eight hospitals. Prediction models for five key outcomes were developed using logistic regression. Models with satisfactory internal validation performance were included in a mobile application system, SEL endoscopic resection predictor (SELERP). In Phase 2, the models were externally validated in a prospective cohort of 200 patients. RESULTS: An SELERP was developed using EUS characteristics, which included 10 models for five key outcomes: post-ER ulcer management, short procedure time, long hospital stay, high medication costs, and diagnosis of SELs. In Phase 1, 10 models were derived and validated (C-statistics, 0.67-0.99; calibration-in-the-large, -0.14-0.10; calibration slopes, 0.92-1.08). In Phase 2, the derived risk prediction models showed convincing discrimination (C-statistics, 0.64-0.73) and calibration (calibration-in-the-large, -0.02-0.05; calibration slopes, 1.01-1.09) in the prospective cohort. The sensitivities and specificities of the five diagnostic models were 68.3-95.7% and 64.1-83.3%, respectively. CONCLUSION: We developed and prospectively validated an application system for the prediction of ER outcomes and diagnosis of SELs, which could aid clinical decision-making and facilitate patient-physician consultation. EUS features significantly contributed to the prediction. TRIAL REGISTRATION: Chinese Clinical Trial Registry, http://www.chictr.org.cn (ChiCTR2000040118).

Attaining Exceptional Stable Copper(I) Metallacyclopentadiene Diradicaloids through Ligand Engineering.

Diradicaloids are generally high-energy molecules with open-shell configuration and are quite reactive. In this work, we report a feasible synthetic approach to attaining exceptionally stable copper(I) metallacyclopentadiene diradicaloids through ligand engineering. Copper(I)-hybrid cyclopentadiene diradicaloids 1c-6c that absorb intensely in visible regions were successfully prepared in stoichiometrical yields under UV light irradiation. The diradicaloids originate from the C-C bonding coupling of two side-by-side-arranged ethynyl groups in complexes 1-6 upon photocyclization. By rational selection of substituents in triphosphine ligands, we systematically modulate the kinetic behavior of diradicaloids 1c-6c in the thermal decoloration process. With precise ligand design, we are able to obtain exceptionally stable copper(I)-hybrid cyclopentadiene diradicaloids with a half-life as long as ca. 40 h in CH2Cl2 solution at ambient temperature. As demonstrated by electron paramagnetic resonance (EPR) and variable-temperature magnetic studies, the diradicaloids manifest a singlet ground state, but they are readily populated to a triplet excited state through thermal activation in view of a small singlet-triplet energy gap of -0.39 kcal mol-1. The diradicaloids show two-step quasi-reversible reduction waves at about -0.5 and -1.0 V ascribed to successive one-electron-accepting processes, coinciding perfectly with the characteristics of diradicals.

An Unusual Case of LGI1 (Leucine-Rich Glioma-Inactivated Protein 1) Limbic Encephalitis With Anti-acetylcholine Receptor and Anti-striational Autoantibodies.

Autoimmune encephalitis (AE) results from immune-mediated damage to the central nervous system (CNS) with varying clinical manifestations depending on autoimmune antibodies present and the antigens they target. Leucine-rich glioma-inactivated protein 1 (LGI1) has been recognized as one of the leading causes of limbic encephalitis (LE), presenting with seizures, memory loss, and faciobrachial dystonic seizures. A better understanding of the unique presentations of these AE allows for quick and effective diagnosis and treatment. We are presenting a very unusual case of LGI1 autoimmune LE with two additional autoantibodies, anti-acetylcholine receptor (AChR) and anti-striational, in a patient with an underlying thymoma. We will discuss the pathophysiology and common clinical presentation of anti-LGI1 autoimmune LE.

Alzheimer's Disease Prediction via Brain Structural-Functional Deep Fusing Network.

Fusing structural-functional images of the brain has shown great potential to analyze the deterioration of Alzheimer's disease (AD). However, it is a big challenge to effectively fuse the correlated and complementary information from multimodal neuroimages. In this work, a novel model termed cross-modal transformer generative adversarial network (CT-GAN) is proposed to effectively fuse the functional and structural information contained in functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). The CT-GAN can learn topological features and generate multimodal connectivity from multimodal imaging data in an efficient end-to-end manner. Moreover, the swapping bi-attention mechanism is designed to gradually align common features and effectively enhance the complementary features between modalities. By analyzing the generated connectivity features, the proposed model can identify AD-related brain connections. Evaluations on the public ADNI dataset show that the proposed CT-GAN can dramatically improve prediction performance and detect AD-related brain regions effectively. The proposed model also provides new insights into detecting AD-related abnormal neural circuits.

Regulation of T cells by myeloid-derived suppressor cells: emerging immunosuppressor in lung cancer.

Myeloid-derived suppressor cells (MDSCs), major components maintaining the immune suppressive microenvironment in lung cancer, are relevant to the invasion, metastasis, and poor prognosis of lung cancer, through the regulation of epithelial-mesenchymal transition, remodeling of the immune microenvironment, and regulation of angiogenesis. MDSCs regulate T-cell immune functions by maintaining a strong immunosuppressive microenvironment and promoting tumor invasion. This raises the question of whether reversing the immunosuppressive effect of MDSCs on T cells can improve lung cancer treatment. To understand this further, this review explores the interactions and specific mechanisms of different MDSCs subsets, including regulatory T cells, T helper cells, CD8 + T cells, natural killer T cells, and exhausted T cells, as part of the lung cancer immune microenvironment. Second, it focuses on the guiding significance confirmed via clinical liquid biopsy and tissue biopsy that different MDSC subsets improve the prognosis of lung cancer. Finally, we conclude that targeting MDSCs through action targets or signaling pathways can help regulate T-cell immune functions and suppress T-cell exhaustion. In addition, immune checkpoint inhibitors targeting MDSCs may serve as a new approach for enhancing the efficiency of immunotherapy and targeted therapy for lung cancer in the future, providing better comprehensive options for lung cancer treatment.

Brain Structure-Function Fusing Representation Learning Using Adversarial Decomposed-VAE for Analyzing MCI.

Integrating the brain structural and functional connectivity features is of great significance in both exploring brain science and analyzing cognitive impairment clinically. However, it remains a challenge to effectively fuse structural and functional features in exploring the complex brain network. In this paper, a novel brain structure-function fusing-representation learning (BSFL) model is proposed to effectively learn fused representation from diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) for mild cognitive impairment (MCI) analysis. Specifically, the decomposition-fusion framework is developed to first decompose the feature space into the union of the uniform and unique spaces for each modality, and then adaptively fuse the decomposed features to learn MCI-related representation. Moreover, a knowledge-aware transformer module is designed to automatically capture local and global connectivity features throughout the brain. Also, a uniform-unique contrastive loss is further devised to make the decomposition more effective and enhance the complementarity of structural and functional features. The extensive experiments demonstrate that the proposed model achieves better performance than other competitive methods in predicting and analyzing MCI. More importantly, the proposed model could be a potential tool for reconstructing unified brain networks and predicting abnormal connections during the degenerative processes in MCI.

Exploring a Linear Combination Feature for Predicting the Conductance of Parallel Molecular Circuits.

An accurate rule for predicting conductance is the cornerstone of developing molecular circuits and provides a promising solution for miniaturizing electric circuits. The successful prediction of series molecular circuits has proven the possibility of establishing a rule for molecular circuits under quantum mechanics. However, the quantitatively accurate prediction has not been validated by experiments for parallel molecular circuits. Here we used 1,3-dihydrobenzothiophene (DBT) to build the parallel molecular circuits. The theoretical simulation and single-molecule conductance measurements demonstrated that the conductance of the molecule containing one DBT is the unprecedented linear combination of the conductance of the two individual channels with respective contribution weights of 0.37 and 0.63. With these weights, the conductance of the molecule containing two DBTs is predicted as 1.81 nS, matching perfectly with the measured conductance (1.82 nS). This feature offers a potential rule for quantitatively predicting the conductance of parallel molecular circuits.

An Enhanced Food Digestion Algorithm for Mobile Sensor Localization.

Mobile sensors can extend the range of monitoring and overcome static sensors' limitations and are increasingly used in real-life applications. Since there can be significant errors in mobile sensor localization using the Monte Carlo Localization (MCL), this paper improves the food digestion algorithm (FDA). This paper applies the improved algorithm to the mobile sensor localization problem to reduce localization errors and improve localization accuracy. Firstly, this paper proposes three inter-group communication strategies to speed up the convergence of the algorithm based on the topology that exists between groups. Finally, the improved algorithm is applied to the mobile sensor localization problem, reducing the localization error and achieving good localization results.