miR-605-3p may affect caerulein-induced ductal cell injury and pyroptosis in acute pancreatitis by targeting the DUOX2/NLRP3/NF-κB pathway.

Acute pancreatitis (AP) is a sudden-onset disease of the digestive system caused by abnormal activation of pancreatic enzymes. Dual oxidase 2 (DUOX2) has been found to be elevated in the progression of a variety of inflammatory diseases. Therefore, we analyzed the specific roles of DUOX2 in AP development. Blood samples were collected from of AP patients and healthy people, and the caerulein- stimulated human pancreatic duct cells (H6C7) were utilized to establish an AP cell model. Cell growth and apoptosis were measured using an MTT assay and TUNEL staining. Additionally, RT-qPCR and western blot assays were conducted to assess the RNA and protein expressions of the cells. ELISA kits were used to determine TNF-α, IL-6, IL-8, and IL-1ß levels. The interaction between DUOX2 and miR-605-3p was predicted using the Targetscan database and confirmed by dual-luciferase report assay. We found that DUOX2 increased while miR-605-3p decreased in the blood of AP patients and caerulein-stimulated H6C7 cells. DUOX2 was targeted by miR-605-3p. Furthermore, DUOX2 knockdown or miR-605-3p overexpression promoted cell viability, decreased the TNF-α, IL-6, IL-8, and IL-1ß levels, and inhibited apoptosis rate in caerulein-stimulated H6C7 cells. DUOX2 knockdown or miR-605-3p overexpression also increased the Bcl-2 protein levels and down-regulated Bax, cleaved-caspase-1, NLRP3 and p-p65. Interestingly, DUOX2 overexpression reversed the miR-605-3p mimic function in the caerulein-treated H6C7 cells. In conclusion, our research demonstrated that DUOX2 knockdown relieved the injury and inflammation in caerulein-stimulated H6C7 cells.

Unveiling a Potent Small Molecule Disruptor for RNA G-Quadruplexes Tougher Than DNA G-Quadruplex Disruption.

This research presents a unique small molecule characterized by its ability to effectively disrupt RNA G-quadruplexes (G4s), which are notably more stable than their DNA counterparts. We conducted a comprehensive series of in vitro experiments to thoroughly assess the disruptive capabilities of this molecule on RNA G4s. These experiments included comparisons with established G4 stabilizers and DNA G4 disruptors, providing a multifaceted evaluation of the molecule's efficacy. Our extensive in vitro analyses demonstrated that this molecule effectively alters G4 structures and interactions with the BG4 protein, a well-recognized G4-specific antibody. These findings underscore the molecule's potential to modulate G4-protein interactions, indicating promising applications for manipulating cellular functions associated with G4 dynamics in future research.

Distinct Immune Homeostasis Remodeling Patterns after HLA-Matched and Haploidentical Transplantation.

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a widely used treatment for a variety of hematopoietic disorders, and also provides a valuable platform for investigating the development of donor-derived immune cells in recipients post-HSCT. The immune system remodels from the donor to the recipient during allo-HSCT. However, little is known about the cell profile alterations as donor homeostasis rebalances to recipient homeostasis following HSCT. Here, multi-omics technology is applied at both the single cell and bulk sample levels, as well as spectrum flow cytometry and fluorescent transgenic mouse models, to dissect the dynamics of the rebalanced homeostatic immune system in recipients after allo-HSCT. The data reveal that all immune subpopulations observed in donors are successfully restored in recipients, though with varying levels of abundance. The remodeling of immune homeostasis exhibits different patterns in HLA-matched and haploidentical HSCT, highlighting distinct biases in T cell reconstitution from the central and peripheral pathways. Furthermore, ZNF683 is critical for maintaining the persistence and quiescence of CD8 T-cell in haploidentical HSCT. The research can serve as a foundation for developing novel strategies to induce immune tolerance.

Regular Mobile Phone Use and Incident Cardiovascular Diseases: Mediating Effects of Sleep Patterns, Psychological Distress, and Neuroticism.

BACKGROUND: The relationship between mobile phone use and incident cardiovascular disease (CVD) is uncertain. We aimed to examine the association of regular mobile phone use with incident CVD and explore the mediating effects of sleep and mental health. METHODS: A total of 444,027 individuals from the UK Biobank without a history of CVD were included. Regular mobile phone use was defined as at least 1 call per week. Weekly mobile phone usage time was self-reported as the average time of calls per week over the previous 3 months. The primary outcome was incident CVD. The secondary outcomes included each component of CVD and increased carotid intima-media thickness (CIMT). We applied Cox proportional hazard models to assess the association between mobile phone use and incident CVD, and mediation analyses to investigate the role of sleep patterns, psychologic distress, and neuroticism. RESULTS: In a median follow-up period of 12.3 years, 56,181 individuals developed incident CVD. Compared with nonregular mobile phone users, regular mobile phone users had a significantly higher risk of incident CVD (hazard ratio 1.04, 95% confidence interval 1.02-1.06) and increased CIMT (odds ratio 1.11, 95% CI 1.04-1.18). Among regular mobile phone users, weekly mobile phone usage time was positively associated with the risk of incident CVD, especially in current smokers (P for interaction = 0.001) and diabetic individuals (P for interaction = 0.037). Of the relationship between weekly mobile phone usage time and incident CVD, 5.11% was mediated by sleep patterns, 11.5% by psychological distress, and 2.25% by neuroticism. CONCLUSIONS: Weekly mobile phone usage time was positively associated with incident CVD risk, which was partly explained by poor sleep, psychologic distress, and neuroticism.

Progressive gray matter atrophy in parkinsonian variant of multiple system atrophy assessed by using causal structural covariance network.

INTRODUCTION: Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown. METHODS: In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T1-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P. RESULTS: With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL. CONCLUSION: MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.

Enhanced prediction of atrial fibrillation risk using proteomic markers: a comparative analysis with clinical and polygenic risk scores.

BACKGROUND: Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank. METHODS: We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS2-AF risk model and a polygenic risk score. RESULTS: Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS2-AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively). CONCLUSIONS: A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.

A genome-scale deep learning model to predict gene expression changes of genetic perturbations from multiplex biological networks.

Systematic characterization of biological effects to genetic perturbation is essential to the application of molecular biology and biomedicine. However, the experimental exhaustion of genetic perturbations on the genome-wide scale is challenging. Here, we show TranscriptionNet, a deep learning model that integrates multiple biological networks to systematically predict transcriptional profiles to three types of genetic perturbations based on transcriptional profiles induced by genetic perturbations in the L1000 project: RNA interference, clustered regularly interspaced short palindromic repeat, and overexpression. TranscriptionNet performs better than existing approaches in predicting inducible gene expression changes for all three types of genetic perturbations. TranscriptionNet can predict transcriptional profiles for all genes in existing biological networks and increases perturbational gene expression changes for each type of genetic perturbation from a few thousand to 26 945 genes. TranscriptionNet demonstrates strong generalization ability when comparing predicted and true gene expression changes on different external tasks. Overall, TranscriptionNet can systemically predict transcriptional consequences induced by perturbing genes on a genome-wide scale and thus holds promise to systemically detect gene function and enhance drug development and target discovery.

Comparison of Injury Severity Score (ISS) and New Injury Severity Score (NISS) in the Evaluation of Thoracic Trauma Patients: A Retrospective Cohort Study.

Objective: To explore the value of the injury severity score (ISS) and the new injury severity score (NISS) for evaluating injuries and predicting complications (pneumonia and respiratory failure) and poor prognoses (in-hospital tracheal intubation, extended length of hospital stay, ICU admission, prolonged ICU stay, and death) in patients with thoracic trauma. Methods: The data of consecutive patients with thoracic trauma who were admitted to the department of cardiothoracic surgery of a tertiary hospital between January 2018 and December 2021 were retrospectively collected. ISS and NISS were calculated for each patient. The study outcomes were complications and poor prognoses. The differences in ISS and NISS between patients with complications and poor prognoses and patients without the abovementioned conditions were compared using the Mann‒Whitney U test. Discrimination and calibration of ISS and NISS in predicting outcomes were compared using the area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer‒Lemeshow (H-L) statistic. Results: A total of 310 patients were included. ISS and NISS of patients with complications and poor prognoses were greater than those of patients without complications and poor prognoses, respectively. The discrimination of ISS in predicting pneumonia, respiratory failure, in-hospital tracheal intubation, extended length of hospital stay, ICU admission, prolonged ICU stay, and death (AUCs: 0.609, 0.721, 0.848, 0.784, 0.763, 0.716, and 0.804, respectively) was not statistically significantly different from that of NISS in predicting the corresponding outcomes (AUCs: 0.628, 0.712, 0.795, 0.767, 0.750, 0.750, and 0.818, respectively). ISS showed better calibration than NISS for predicting pneumonia, respiratory failure, in-hospital tracheal intubation, extended length of hospital stay, and ICU admission but worse calibration for predicting prolonged ICU stay and death. Conclusion: ISS and NISS are both suitable for injury evaluation. There was no statistically significant difference in discrimination between ISS and NISS, but they had different calibrations when predicting different outcomes.

Nanoreactors with Cascade Catalytic Activity Reprogram the Tumor Microenvironment for Enhanced Immunotherapy by Synchronously Regulating Treg and Macrophage Cells.

Immunotherapy has been extensively utilized and studied as a prominent therapeutic strategy for tumors. However, the presence of a hypoxic immunosuppressive tumor microenvironment significantly reduces the efficacy of the treatment, thus impeding its application. In addition, the hypoxic microenvironment can also lead to the enrichment of immunosuppressive cells and reduce the effectiveness of tumor immunotherapy; nanoparticles with biocatalytic activity have the ability to relieve hypoxia in tumor tissues and deliver drugs to target cells and have been widely concerned and applied in the field of tumor therapy. The present study involved the development of a dual nanodelivery system that effectively targets the immune system to modify the tumor microenvironment (TME). The nanodelivery system was developed by incorporating R848 and Imatinib (IMT) into Pt nanozyme loaded hollow polydopamine (P@HP) nanocarriers. Subsequently, their surface was modified with specifically targeted peptides that bind to M2-like macrophages and regulatory T (Treg) cells, thereby facilitating the precise targeting of these cells. When introduced into the tumor model, the nanocarriers were able to selectively target immune cells in tumor tissue, causing M2-type macrophages to change into the M1 phenotype and reducing Treg activation within the tumor microenvironment. In addition, the carriers demonstrated exceptional biocatalytic activity, effectively converting H2O2 into oxygen and water at the tumor site while the drug was active, thereby alleviating the hypoxic inhibitory conditions present in the tumor microenvironment. Additionally, this further enhanced the infiltration of M1-type macrophages and cytotoxic T lymphocytes. Moreover, when used in conjunction with immune checkpoint therapy, the proposed approach demonstrated enhanced antitumor immunotherapeutic effects. The bimodal targeted immunotherapeutic strategy developed in the present study overcomes the drawbacks of traditional immunotherapy approaches while offering novel avenues for the treatment of cancer.

Effect of controlled release of HGF on extracellular vesicle secretion by urine-derived stem cells.

Introduction: The hepatic growth factor (HGF) stimulates DNA synthesis and cell proliferation and plays a role in tissue protection and regeneration. In this study, we have examined the effect of incubation of HGF with urine-derived stem cells (USCs) on the secretion of small extracellular vesicles (sEV) by the cells. Materials and Methods: HGF in the incubation medium was either a bolus administration or a controlled release of an equivalent amount from microbeads within the size range of 50-200 µm made with ultrapurified low-viscosity high-guluronic acid (UP-LVG) alginate. USCs were incubated with or without HGF for 3 days or 7 days before removal of the incubation media, followed by harvesting sEV by the precipitation method. The protein content of isolated sEV was measured by bicinchoninic acid assay (BCA) for these three groups: control (no HGF beads), bolus HGF, and HGF beads. We also performed nanoparticle tracking analysis (NTA), Western blot assay, and ELISA for the HGF content of samples. Results: We found a significantly higher concentration of proteins in the HGF microbead group (control release group) compared to the bolus group and the control group after 7 days (p < 0.0017). The NTA data aligned with the BCA; they showed a significantly higher concentration of particles within the size range of sEV (<200 nm) in the group treated with HGF beads compared to the two other groups on day 7 (p < 0.0001). Conclusion: We found that administration of HGF to USCs by controlled release of the growth factor significantly enhances the levels of sEV secretion during 7 days of incubation.

Mitochondrial dysfunction in sepsis: mechanisms and therapeutic perspectives.

Sepsis is a severe medical condition characterized by a systemic inflammatory response, often culminating in multiple organ dysfunction and high mortality rates. In recent years, there has been a growing recognition of the pivotal role played by mitochondrial damage in driving the progression of sepsis. Various factors contribute to mitochondrial impairment during sepsis, encompassing mechanisms such as reactive nitrogen/oxygen species generation, mitophagy inhibition, mitochondrial dynamics change, and mitochondrial membrane permeabilization. Damaged mitochondria actively participate in shaping the inflammatory milieu by triggering key signaling pathways, including those mediated by Toll-like receptors, NOD-like receptors, and cyclic GMP-AMP synthase. Consequently, there has been a surge of interest in developing therapeutic strategies targeting mitochondria to mitigate septic pathogenesis. This review aims to delve into the intricate mechanisms underpinning mitochondrial dysfunction during sepsis and its significant impact on immune dysregulation. Moreover, we spotlight promising mitochondria-targeted interventions that have demonstrated therapeutic efficacy in preclinical sepsis models.

Application of Novel Wearable Self-Balancing Exoskeleton Robot Capable for Complete Self-Support in Post-stroke Rehabilitation: A Case Study.

Early weight-bearing and trunk control training are essential components for promoting lower limb motor recovery in individuals with stroke. In this case study, we presented the successful implementation of a three-week wearable self-balancing exoskeleton robot training program for a 57-year-old male patient who had suffered from a stroke. After carefully reviewing the patient's previous medical records, conducting a thorough assessment, and excluding other potential contraindications, we introduced wearable self-balancing exoskeleton robot training to complement conventional rehabilitation in managing balance and lower limb function. The training program included early initiation of weight bearing and trunk control training following an ischemic stroke, aimed at promoting motor recovery and improving functional independence. The findings indicated that training with a wearable self-balancing exoskeleton robot enhanced the balance and motor function of the hemiplegic patient, with commendable adherence. Furthermore, the participants consistently reported increased satisfaction and confidence during the training sessions. This case report not only provided preliminary evidence of the effectiveness of the wearable self-balancing exoskeleton robot in promoting functional recovery following a stroke but also outlined a comprehensive training program that may hold value for future clinical application.

Interfacial study and modulation of high-voltage layered cathode based all-solid-state batteries.

Employing layered materials as the cathodes for solid-state batteries (SSBs) is vital in enhancing the batteries' energy density, whereas numerous issues are present regarding the compatibilities between cathode electrode and modified solid electrolyte (ME) in this battery configuration. By investigating the electrochemical performance and interfacial properties of SSBs using various cathodes, the fundamental reason for the poor compatibility between layered cathodes, especially LiCoO2 with ME is revealed. Because of the Li(solvent)+ intercalation environments formed in the ME, the resultant weak-interacted TFSI- could be adsorbed and destabilized by Co ions on the surface. Besides, the high energy level offsets between LiCoO2 and ME lead to Li-ion transferring from the bulk electrode to the electrolyte, resulting in a pre-formed interface on the cathode particles before the electric current is applied, affects the formation of effective cathode-electrolyte interface (CEI) film during electrochemical process and deteriorated overall battery performance. From this view, an interlayer is pre-added on the LiCoO2 surface through an electrostatic adsorption method, to adjust the energy level offsets between the cathode and ME, as well as isolate the direct contact of surface Co ions to TFSI-. The cycling properties of the SSB using modified LiCoO2 are greatly enhanced, and a capacity retention of 68.72 % after 100 cycles could be achieved, against 8.28 % previously, certifying the rationality of the understanding and the effectiveness of the proposed modification method. We believe this research could provide basic knowledge of the compatibility between layered cathodes and MEs, shedding light on designing more effective strategies for achieving SSBs with high energy density.

Research on mental fatigue during long-term motor imagery: a pilot study.

Mental fatigue during long-term motor imagery (MI) may affect intention recognition in MI applications. However, the current research lacks the monitoring of mental fatigue during MI and the definition of robust biomarkers. The present study aims to reveal the effects of mental fatigue on motor imagery recognition at the brain region level and explore biomarkers of mental fatigue. To achieve this, we recruited 10 healthy participants and asked them to complete a long-term motor imagery task involving both right- and left-handed movements. During the experiment, we recorded 32-channel EEG data and carried out a fatigue questionnaire for each participant. As a result, we found that mental fatigue significantly decreased the subjects' motor imagery recognition rate during MI. Additionally the theta power of frontal, central, parietal, and occipital clusters significantly increased after the presence of mental fatigue. Furthermore, the phase synchronization between the central cluster and the frontal and occipital lobes was significantly weakened. To summarize, the theta bands of frontal, central, and parieto-occipital clusters may serve as powerful biomarkers for monitoring mental fatigue during motor imagery. Additionally, changes in functional connectivity between the central cluster and the prefrontal and occipital lobes during motor imagery could be investigated as potential biomarkers.

Cooperation dynamics of prisoner's dilemma games on an evolutionary weighted network with heterogeneous preferences.

Relationships between people in real life are dynamically changed with the interaction process, and due to the heterogeneous preferences, this change is different from person to person. Based on this observation, we propose a new spatial and weighted prisoner's dilemma game model with heterogeneous individuals. Two types of tags, namely, tag-F (concerned about social fairness) and tag-W (concerned about personal well-being), are introduced to describe individuals' different preferences. The link weights indicating the interaction strength between individuals are updated based on different rules that depend on their tags. Through simulations, we verify that a large link weight control factor and a high proportion of tag-F individuals favor the emergence and persistence of cooperation. In addition, an increase in the link weight sensitivity factor favors the evolution of cooperation when the link weight control factor is small. Moreover, while the level of cooperation increases with the proportion of tag-F type in the population, contrary to our intuition, when the population consists entirely of tag-F individuals, in some cases, cooperation cannot reach a higher level compared with the situation when they are mixed with tag-W type. However, at high dilemma intensities, cooperators emerge only when the entire population consists of tag-F type. These results may provide some new insights into the impact of the evolutionary weighted network with heterogeneous preferences on collective cooperative behavior.

Essential and multifunctional mpox virus E5 helicase-primase in double and single hexamer.

An outbreak of mpox virus in May 2022 has spread over 110 nonpandemic regions in the world, posing a great threat to global health. Mpox virus E5, a helicase-primase, plays an essential role in DNA replication, but the molecular mechanisms are elusive. Here, we report seven structures of mpox virus E5 in a double hexamer (DH) and six in single hexamer in different conformations, indicating a rotation mechanism for helicase and a coupling action for primase. The DH is formed through the interface of zinc-binding domains, and the central channel density indicates potential double-stranded DNA (dsDNA), which helps to identify dsDNA binding residues Arg249, Lys286, Lys315, and Lys317. Our work is important not only for understanding poxviral DNA replication but also for the development of novel therapeutics for serious poxviral infections including smallpox virus and mpox virus.

Advancements in understanding substantia nigra hyperechogenicity via transcranial sonography in Parkinson's disease and its clinical implications.

Amidst rising Parkinson's disease (PD) incidence in an aging global population, the need for non-invasive and reliable diagnostic methods is increasingly critical. This review evaluates the strategic role of transcranial sonography (TCS) in the early detection and monitoring of PD. TCS's ability to detect substantia nigra hyperechogenicity offers profound insights into its correlation with essential neuropathological alterations-namely, iron accumulation, neuromelanin depletion, and glial proliferation-fundamental to PD's pathophysiology. Our analysis highlights TCS's advantages, including its non-invasiveness, cost-effectiveness, and ease of use, positioning it as an invaluable tool for early diagnosis and continual disease progression monitoring. Moreover, TCS assists in identifying potential risk and protective factors, facilitating tailored therapeutic strategies to enhance clinical outcomes. This review advocates expanding TCS utilization and further research to maximize its diagnostic and prognostic potential in PD management, contributing to a more nuanced understanding of the disease.

A multifunctional near-infrared fluorescent probe based on benzothiazole structure for fluoride-ion detection.

Fluoride ions (F-) are one of the essential trace elements for the human body and are widely existed in nature. In this study, we present a novel fluorescent probe (YF-SZ-F) designed and synthesized for the specific detection of F-. The probe exhibits high sensitivity, excellent selectivity, and low cytotoxicity, making it a promising tool for biomedical applications. Imaging experiments conducted on zebrafish and Arabidopsis roots demonstrate the probe's remarkable cellular permeability and biocompatibility, laying a solid foundation for its potential biomedical utility. Furthermore, the probe holds potential for practical applications in environmental monitoring and public health through its capability to detect fluoride ions in water samples and via mobile phone software. This multifaceted functionality underscores the broad applicability and significance of the fluorescent probe, not only in scientific research but also in real-world scenarios, contributing to the development of more convenient and precise methods for fluoride detection.

Development and application of a population pharmacokinetic model repository for caffeine dose tailoring in preterm infants.

BACKGROUND: Considerable interindividual variability for the pharmacokinetics of caffeine in preterm infants has been demonstrated, emphasizing the importance of personalized dosing. This study aimed to develop and apply a repository of currently published population pharmacokinetic (PopPK) models of caffeine in preterm infants to facilitate model-informed precision dosing (MIPD). RESEARCH DESIGN AND METHODS: Literature search was conducted using PubMed, Embase, Scopus, and Web of Science databases. Relevant publications were screened, and their quality was assessed. PopPK models were reestablished to develop the model repository. Covariate effects were evaluated and the concentration-time profiles were simulated. An online simulation and calculation tool was developed as an instance. RESULTS: Twelve PopPK models were finally included in the repository. Preterm infants' age and body size, especially the postnatal age and current weight, were identified as the most clinically critical covariates. Simulated blood concentration-time profiles across these models were comparable. Caffeine citrate-dose regimen should be adjusted according to the age and body size of preterm infants. The developed online tool can be used to facilitate clinical decision-making. CONCLUSIONS: The first developed repository of PopPK models for caffeine in preterm infants has a wide range of potential applications in the MIPD of caffeine.