Tissue Kallikrein supplementation in ischemic phase protects the neurovascular unit and attenuates reperfusion-induced injury in ischemic stroke.

Tissue kallikrein (TK) has emerged as a potential neuroprotective agent in ischemic stroke (IS), yet the optimal timing and mechanisms of TK therapy remain unclear. Here, we established a causal link between lower baseline TK levels and an increased risk of stroke through a retrospective, multicenter cohort study involving 2115 initially non-stroke subjects monitored for 5 years. Sequentially, we observed a notable increase in bradykinin receptor 2 (B2R) levels during the ischemic phase of the IS model, while levels of TK and bradykinin receptor 1 (B1R) remained stable. Intriguingly, both B1R and B2R exhibited a significant elevation 24 h after reperfusion. Further investigations in preclinical models demonstrated that TK supplementation activates the PI3K/AKT signaling pathway via enhanced B2R expression during the ischemic phase, leading to nuclear translocation of Hif-1α. This activation enhances the expression of VEGF and eNOS, thereby fortifying the neurovascular unit. Moreover, it suppresses the activation of the kallikrein-kinin system induced by reperfusion injury, effectively reducing inflammation, ROS production, apoptosis, and endothelial barrier dysfunction. Thus, our findings highlight the significance of TK supplementation during the ischemic phase in attenuating reperfusion-induced injury in IS, providing a mechanistic rationale for determining the optimal timing for TK supplementation therapy.

Nucleated red blood cell distribution in critically ill patients with acute pancreatitis: a retrospective cohort study.

OBJECTIVES: This study examined the potential association between nucleated red blood cell (NRBC) levels and mortality in critically ill patients with acute pancreatitis (AP) in the intensive care unit, due to limited existing research on this correlation. METHODS: This retrospective cohort study utilized data from the MIMIC-IV v2.0 and MIMIC-III v1.4 databases to investigate the potential relationship between NRBC levels and patient outcomes. The study employed restricted cubic splines (RCS) regression analysis to explore non-linear associations. The impact of NRBC on prognosis was assessed using a generalized linear model (GLM) with a logit link, adjusted for potential confounders. Furthermore, four machine learning models, including Gradient Boosting Classifier (GBC), Random Forest, Gaussian Naive Bayes, and Decision Tree Classifier model, were constructed using NRBC data to generate risk scores and evaluate the potential of NRBC in predicting patient prognosis. RESULTS: A total of 354 patients were enrolled in the study, with 162 (45.8%) individuals aged 60 years or older and 204 (57.6%) males. RCS regression analysis demonstrated a non-linear relationship between NRBC levels and 90-day mortality. Receiver Operating Characteristic (ROC) analysis identified a 1.7% NRBC cutoff to distinguish survivor from non-survivor patients for 90-day mortality, yielding an Area Under the Curve (AUC) of 0.599, with a sensitivity of 0.475 and specificity of 0.711. Elevated NRBC levels were associated with increased risks of 90-day mortality in both unadjusted and adjusted models (all Odds Ratios > 1, P < 0.05). Assessment of various machine learning models with nine variables, including NRBC, Sex, Age, Simplified Acute Physiology Score II, Acute Physiology Score III, Congestive Heart Failure, Vasopressin, Norepinephrine, and Mean Arterial Pressure, indicated that the GBC model displayed the highest predictive accuracy for 90-day mortality, with an AUC of 0.982 (95% CI 0.970-0.994). Post hoc power analysis showed a statistical power of 0.880 in the study. CONCLUSIONS: Elevated levels of NRBC are linked to an increased mortality risk in critically ill patients with AP, suggesting its potential for predicting mortality.

Unraveling the role of HIF-1α in sepsis: from pathophysiology to potential therapeutics-a narrative review.

Sepsis is characterized by organ dysfunction resulting from a dysregulated inflammatory response triggered by infection, involving multifactorial and intricate molecular mechanisms. Hypoxia-inducible factor-1α (HIF-1α), a notable transcription factor, assumes a pivotal role in the onset and progression of sepsis. This review aims to furnish a comprehensive overview of HIF-1α's mechanism of action in sepsis, scrutinizing its involvement in inflammatory regulation, hypoxia adaptation, immune response, and organ dysfunction. The review encompasses an analysis of the structural features, regulatory activation, and downstream signaling pathways of HIF-1α, alongside its mechanism of action in the pathophysiological processes of sepsis. Furthermore, it will delve into the roles of HIF-1α in modulating the inflammatory response, including its association with inflammatory mediators, immune cell activation, and vasodilation. Additionally, attention will be directed toward the regulatory function of HIF-1α in hypoxic environments and its linkage with intracellular signaling, oxidative stress, and mitochondrial damage. Finally, the potential therapeutic value of HIF-1α as a targeted therapy and its significance in the clinical management of sepsis will be discussed, aiming to serve as a significant reference for an in-depth understanding of sepsis pathogenesis and potential therapeutic targets, as well as to establish a theoretical foundation for clinical applications.

Dyslipidemia versus obesity as predictors of ischemic stroke prognosis: a multi-center study in China.

BACKGROUND: This multicenter observational study aimed to determine whether dyslipidemia or obesity contributes more significantly to unfavorable clinical outcomes in patients experiencing a first-ever ischemic stroke (IS). METHODS: The study employed a machine learning predictive model to investigate associations among body mass index (BMI), body fat percentage (BFP), high-density lipoprotein (HDL), triglycerides (TG), and total cholesterol (TC) with adverse outcomes in IS patients. Extensive real-world clinical data was utilized, and risk factors significantly linked to adverse outcomes were identified through multivariate analysis, propensity score matching (PSM), and regression discontinuity design (RDD) techniques. Furthermore, these findings were validated via a nationwide multicenter prospective cohort study. RESULTS: In the derived cohort, a total of 45,162 patients diagnosed with IS were assessed, with 522 experiencing adverse outcomes. A multifactorial analysis incorporating PSM and RDD methods identified TG (adjusted odds ratio (OR) = 1.110; 95% confidence interval (CI): 1.041-1.183; P <  0.01) and TC (adjusted OR = 1.139; 95%CI: 1.039-1.248; P <  0.01) as risk factors. However, BMI, BFP, and HDL showed no significant effect. In the validation cohort, 1410 controls and 941 patients were enrolled, confirming that lipid levels are more strongly correlated with the prognosis of IS patients compared to obesity (TC, OR = 1.369; 95%CI: 1.069-1.754; P <  0.05; TG, OR = 1.332; 95%CI: 1.097-1.618; P <  0.01). CONCLUSION: This study suggests that dyslipidemia has a more substantial impact on the prognosis of IS patients compared to obesity. This highlights the importance of prioritizing dyslipidemia management in the treatment and prevention of adverse outcomes in IS patients.

GPEdit: the genetic and pharmacogenomic landscape of A-to-I RNA editing in cancers.

Altered A-to-I RNA editing has been widely observed in many human cancers and some editing sites are associated with drug sensitivity, implicating its therapeutic potential. Increasing evidence has demonstrated that a quantitative trait loci mapping approach is effective to understanding the genetic basis of RNA editing. We systematically performed RNA editing quantitative trait loci (edQTL) analysis in 33 human cancer types for >10 000 cancer samples and identified 320 029 edQTLs. We also identified 1688 ed-QTLs associated with patient overall survival and 4672 ed-QTLs associated with GWAS risk loci. Furthermore, we demonstrated the associations between RNA editing and >1000 anti-cancer drug response with ∼3.5 million significant associations. We developed GPEdit (https://hanlab.uth.edu/GPEdit/) to facilitate a global map of the genetic and pharmacogenomic landscape of RNA editing. GPEdit is a user-friendly and comprehensive database that provides an opportunity for a better understanding of the genetic impact and the effects on drug response of RNA editing in cancers.

Dual-Use Strain Sensors for Acoustic Emission and Quasi-Static Bending Measurements.

In this paper, a MEMS piezoresistive ultrathin silicon membrane-based strain sensor is presented. The sensor's ability to capture an acoustic emission signal is demonstrated using a Hsu-Nielsen source, and shows comparable frequency content to a commercial piezoceramic ultrasonic transducer. To the authors' knowledge, this makes the developed sensor the first known piezoresistive strain sensor which is capable of recording low-energy acoustic emissions. The improvements to the nondestructive evaluation and structural health monitoring arise from the sensor's low minimum detectable strain and wide-frequency bandwidth, which are generated from the improved fabrication process that permits crystalline semiconductor membranes and advanced polymers to be co-processed, thus enabling a dual-use application of both acoustic emission and static strain sensing. The sensor's ability to document quasi-static bending is also demonstrated and compared with an ultrasonic transducer, which provides no significant response. This dual-use application is proposed to effectively combine the uses of both strain and ultrasonic transducer sensor types within one sensor, making it a novel and useful method for nondestructive evaluations. The potential benefits include an enhanced sensitivity, a reduced sensor size, a lower cost, and a reduced instrumentation complexity.

Elevated MMP-8 levels, inversely associated with BMI, predict mortality in mechanically ventilated patients: an observational multicenter study.

BACKGROUND: The present study aimed to investigate the correlation between weight status and mortality in mechanically ventilated patients and explore the potential mediators. METHODS: Three medical centers encompassing 3301 critically ill patients receiving mechanical ventilation were assembled for retrospective analysis to compare mortality across various weight categories of patients using machine learning algorithms. Bioinformatics analysis identified genes exhibiting differential expression among distinct weight categories. A prospective study was then conducted on a distinct cohort of 50 healthy individuals and 193 other mechanically ventilated patients. The expression levels of the genes identified through bioinformatics analysis were quantified through enzyme-linked immunosorbent assay (ELISA). RESULTS: The retrospective analysis revealed that overweight individuals had a lower mortality rate than underweight individuals, and body mass index (BMI) was an independent protective factor. Bioinformatics analysis identified matrix metalloproteinase 8 (MMP-8) as a differentially expressed gene between overweight and underweight populations. The results of further prospective studies showed that overweight patients had significantly lower MMP-8 levels than underweight patients ((3.717 (2.628, 4.191) vs. 2.763 (1.923, 3.753), ng/ml, P = 0.002). High MMP-8 levels were associated with increased mortality risk (OR = 4.249, P = 0.005), indicating that elevated level of MMP-8 predicts the mortality risk of underweight patients receiving mechanical ventilation. CONCLUSIONS: This study provides evidence for a protective effect of obesity in mechanically ventilated patients and highlights the potential role of MMP-8 level as a biomarker for predicting mortality risk in this population.

HeRA: an atlas of enhancer RNAs across human tissues.

Enhancer RNA (eRNA) is a type of long non-coding RNA transcribed from DNA enhancer regions. Despite critical roles of eRNA in gene regulation, the expression landscape of eRNAs in normal human tissue remains unexplored. Using numerous samples from the Genotype-Tissue Expression project, we characterized 45 411 detectable eRNAs and identified tens of thousands of associations between eRNAs and traits, including gender, race, and age. We constructed a co-expression network to identify millions of putative eRNA regulators and target genes across different tissues. We further constructed a user-friendly data portal, Human enhancer RNA Atlas (HeRA, https://hanlab.uth.edu/HeRA/). In HeRA, users can search, browse, and download the eRNA expression profile, trait-related eRNAs, and eRNA co-expression network by searching the eRNA ID, gene symbol, and genomic region in one or multiple tissues. HeRA is the first data portal to characterize eRNAs from 9577 samples across 54 human tissues and facilitates functional and mechanistic investigations of eRNAs.

Harnessing ADAR-Mediated Site-Specific RNA Editing in Immune-Related Disease: Prediction and Therapeutic Implications.

ADAR (Adenosine Deaminases Acting on RNA) proteins are a group of enzymes that play a vital role in RNA editing by converting adenosine to inosine in RNAs. This process is a frequent post-transcriptional event observed in metazoan transcripts. Recent studies indicate widespread dysregulation of ADAR-mediated RNA editing across many immune-related diseases, such as human cancer. We comprehensively review ADARs' function as pattern recognizers and their capability to contribute to mediating immune-related pathways. We also highlight the potential role of site-specific RNA editing in maintaining homeostasis and its relationship to various diseases, such as human cancers. More importantly, we summarize the latest cutting-edge computational approaches and data resources for predicting and analyzing RNA editing sites. Lastly, we cover the recent advancement in site-directed ADAR editing tool development. This review presents an up-to-date overview of ADAR-mediated RNA editing, how site-specific RNA editing could potentially impact disease pathology, and how they could be harnessed for therapeutic applications.

APAatlas: decoding alternative polyadenylation across human tissues.

Alternative polyadenylation (APA) is an RNA-processing mechanism on the 3' terminus that generates distinct isoforms of mRNAs and/or other RNA polymerase II transcripts with different 3'UTR lengths. Widespread APA affects post-transcriptional gene regulation in mRNA translation, stability, and localization, and exhibits strong tissue specificity. However, no existing database provides comprehensive information about APA events in a large number of human normal tissues. Using the RNA-seq data from the Genotype-Tissue Expression project, we systematically identified APA events from 9475 samples across 53 human tissues and examined their associations with multiple traits and gene expression across tissues. We further developed APAatlas, a user-friendly database (https://hanlab.uth.edu/apa/) for searching, browsing and downloading related information. APAatlas will help the biomedical research community elucidate the functions and mechanisms of APA events in human tissues.

Development of a Flexible Integrated Self-Calibrating MEMS Pressure Sensor Using a Liquid-to-Vapor Phase Change.

Self-calibration capabilities for flexible pressure sensors are greatly needed for fluid dynamic analysis, structure health monitoring and wearable sensing applications to compensate, in situ and in real time, for sensor drifts, nonlinearity effects, and hysteresis. Currently, very few self-calibrating pressure sensors can be found in the literature, let alone in flexible formats. This paper presents a flexible self-calibrating pressure sensor fabricated from a silicon-on-insulator wafer and bonded on a polyimide substrate. The sensor chip is made of four piezoresistors arranged in a Wheatstone bridge configuration on a pressure-sensitive membrane, integrated with a gold thin film-based reference cavity heater, and two thermistors. With a liquid-to-vapor thermopneumatic actuation system, the sensor can create precise in-cavity pressure for self-calibration. Compared with the previous work related to the single-phase air-only counterpart, testing of this two-phase sensor demonstrated that adding the water liquid-to-vapor phase change can improve the effective range of self-calibration from 3 psi to 9.5 psi without increasing the power consumption of the cavity micro-heater. The calibration time can be further improved to a few seconds with a pulsed heating power.

Numerical Study of the Thermal Performance of a Mems Pressure Sensor with Self-Calibration Capabilities.

Recent industry trends toward more complex and interconnected systems have increased the demand for more reliable pressure sensors. By integrating a microactuator with a pressure sensor, the sensor can self-calibrate, eliminating the complexities and costs associated with traditional sensor calibration methods to ensure reliability. The present work is focused on furthering understanding and improving the thermal performance of a thermopneumatic actuated self-calibrating pressure sensor. A transient numerical model was developed in ANSYS and was calibrated using experimental testing data. The numerical model provided insights into the sensor's performance not previously observed in experimental testing. Furthermore, the model was utilized for two design studies. First, it was found that a substrate with low thermal conductivity and high thermal diffusivity is ideal for both the sensor's efficiency and a faster transient response time. The second design study showed that decreasing the size of the sealed reference cavity lowers power consumption and transient response time. The study also showed that reducing the cavity base dimension has a greater effect on lowering power consumption and response time. Overall, the present work increases understanding of the self-calibrating pressure sensor and provides insight into potential design improvements, moving closer to optimized self-calibrating pressure sensors.

Genomic landscape of T-cell lymphoblastic lymphoma.

Objective: T-cell lymphoblastic lymphoma (T-LBL) is an aggressive neoplasm of precursor T cells, however, detailed genome-wide sequencing of large T-LBL cohorts has not been performed due to its rarity. The purpose of this study was to identify putative driver genes in T-LBL. Methods: To gain insight into the genetic mechanisms of T-LBL development, we performed whole-exome sequencing on 41 paired tumor-normal DNA samples from patients with T-LBL. Results: We identified 32 putative driver genes using whole-exome sequencing in 41 T-LBL cases, many of which have not previously been described in T-LBL, such as Janus kinase 3 (JAK3), Janus kinase 1 (JAK1), Runt-related transcription factor 1 (RUNX1) and Wilms' tumor suppressor gene 1 (WT1). When comparing the genetic alterations of T-LBL to T-cell acute lymphoblastic leukemia (T-ALL), we found that JAK-STAT and RAS pathway mutations were predominantly observed in T-LBL (58.5% and 34.1%, respectively), whereas Notch and cell cycle signaling pathways mutations were more prevalent in T-ALL. Notably, besides notch receptor 1 (NOTCH1), mutational status of plant homeodomain (PHD)-like finger protein 6 (PHF6) was identified as another independent factor for good prognosis. Of utmost interest is that co-existence of PHF6 and NOTCH1 mutation status might provide an alternative for early therapeutic stratification in T-LBL. Conclusions: Together, our findings will not only provide new insights into the molecular and genetic mechanisms of T-LBL, but also have tangible implications for clinical practice.

Structure and Optical Properties of Hybrid-Layered-Double Perovskites (C8H20N2)2AgMBr8 (M = In, Sb, and Bi).

The Pb-free hybrid-layered-double perovskites (HLDPs) have been proposed as green and stable semiconducting materials for optoelectronic devices, but the synthesized members are still limited. Here, we report the synthesis of three new HLDPs, (C8H20N2)2AgMBr8 (M = In, Sb, and Bi), by a solution method using 1,4-bis(ammoniomethyl)cyclohexane (C8H20N22+) as the organic spacing cation. All three of these HLDPs show ⟨100⟩-oriented layered structures with Ag and In/Sb/Bi order arranged in corner-sharing octahedral layers. The first-principle calculations indicate the indirect-gap nature of (C8H20N2)2AgInBr8 and (C8H20N2)2AgSbBr8, while their Bi counterpart shows a direct band gap after considering spin-orbit coupling. The band gaps obtained by diffuse-reflectance spectroscopy are 3.11, 2.60, and 2.70 eV for M = In, Sb, and Bi, respectively. (C8H20N2)2AgInBr8 shows a broadband red emission centered at 690 nm, and it is mainly attributed to the self-trapped-excitons mechanism. Our results not only provide a series of new "Pb-free" HLDPs with chemical diversity but also help us to further understand the structure-property relationships of HLDP materials.

Ancestral transcriptome inference based on RNA-Seq and ChIP-seq data.

With the help of high-throughput NGS (next-generation sequencing) technologies, ancestral transcriptome reconstruction is helpful to understand the complexity of transcriptional regulatory systems that underlies the evolution of multiple cellular metazoans with sophisticated functions and distinctive morphologies. To this end, we report a new method of ancestral state inference. The new method used Ornstein-Uhlenbeck (OU) model, which is more biologically realistic, to replace the Brownian motion (BM) model and is suitable for multi-transcriptome data. Implemented in the free R package, AnceTran is specially designed for RNA-seq and ChIP-seq data, which is feasible. It should be noticed that our work will be integrated to a unified, statistically-sound phylogenetic framework to study the evolution of many other molecular phenomes such as proteomics, chromatin accessibility, methylation status, and metabolomics. We exemplify our method by a case study, using the ChIP-seq binding data of three liver-specific transcription factors and the RNA-seq liver expression data in four closely related mice species, and some technical issues are discussed.

Pancan-meQTL: a database to systematically evaluate the effects of genetic variants on methylation in human cancer.

DNA methylation is an important epigenetic mechanism for regulating gene expression. Aberrant DNA methylation has been observed in various human diseases, including cancer. Single-nucleotide polymorphisms can contribute to tumor initiation, progression and prognosis by influencing DNA methylation, and DNA methylation quantitative trait loci (meQTL) have been identified in physiological and pathological contexts. However, no database has been developed to systematically analyze meQTLs across multiple cancer types. Here, we present Pancan-meQTL, a database to comprehensively provide meQTLs across 23 cancer types from The Cancer Genome Atlas by integrating genome-wide genotype and DNA methylation data. In total, we identified 8 028 964 cis-meQTLs and 965 050 trans-meQTLs. Among these, 23 432 meQTLs are associated with patient overall survival times. Furthermore, we identified 2 214 458 meQTLs that overlap with known loci identified through genome-wide association studies. Pancan-meQTL provides a user-friendly web interface (http://bioinfo.life.hust.edu.cn/Pancan-meQTL/) that is convenient for browsing, searching and downloading data of interest. This database is a valuable resource for investigating the roles of genetics and epigenetics in cancer.

Actinomycin V Induces Apoptosis Associated with Mitochondrial and PI3K/AKT Pathways in Human CRC Cells.

Actinomycin (Act) V, an analogue of Act D, presented stronger antitumor activity and less hepatorenal toxicity than Act D in our previous studies, which is worthy of further investigation. We hereby report that Act V induces apoptosis via mitochondrial and PI3K/AKT pathways in colorectal cancer (CRC) cells. Act V-induced apoptosis was characterized by mitochondrial dysfunction, with loss of mitochondria membrane potential (MMP) and cytochrome c release, which then activated cleaved caspase-9, cleaved caspase-3, and cleaved PARP, revealing that it was related to the mitochondrial pathway, and the apoptotic trendency can be reversed by caspase inhibitor Z-VAD-FMK. Furthermore, we proved that Act V significantly inhibited PI3K/AKT signalling in HCT-116 cells using cell experiments in vitro, and it also presented a potential targeted PI3Kα inhibition using computer docking models. Further elucidation revealed that it exhibited a 28-fold greater potency than the PI3K inhibitor LY294002 on PI3K inhibition efficacy. Taken together, Act V, as a superior potential replacement of Act D, is a potential candidate for inhibiting the PI3K/AKT pathway and is worthy of more pre-clinical studies in the therapy of CRC.

The genetic and pharmacogenomic landscape of snoRNAs in human cancer.

Emerging evidence has revealed significant roles for small nucleolar RNAs (snoRNAs) in tumorigenesis. However, the genetic and pharmacogenomic landscape of snoRNAs has not been characterized. Using the genotype and snoRNA expression data from The Cancer Genome Atlas, we characterized the effects of genetic variants on snoRNAs across 29 cancer types and further linked related alleles with patient survival as well as genome-wide association study risk loci. Furthermore, we characterized the impact of snoRNA expression on drug response in patients to facilitate the clinical utility of snoRNAs in cancer. We also developed a user-friendly data resource, GPSno (http://hanlab.uth.edu/GPSno), with multiple modules for researchers to visualize, browse, and download multi-dimensional data. Our study provides a comprehensive genetic and pharmacogenomic landscape of snoRNAs, which will shed light on future clinical considerations for the development of snoRNA-based targeted therapies.

Immunogenic cell death in colon cancer prevention and therapy.

Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide. The colonic mucosa constitutes a critical barrier and a major site of immune regulation. The immune system plays important roles in cancer development and treatment, and immune activation caused by chronic infection or inflammation is well-known to increase cancer risk. During tumor development, neoplastic cells continuously interact with and shape the tumor microenvironment (TME), which becomes progressively immunosuppressive. The clinical success of immune checkpoint blockade therapies is limited to a small set of CRCs with high tumor mutational load and tumor-infiltrating T cells. Induction of immunogenic cell death (ICD), a type of cell death eliciting an immune response, can therefore help break the immunosuppressive TME, engage the innate components, and prime T cell-mediated adaptive immunity for long-term tumor control. In this review, we discuss the current understanding of ICD induced by antineoplastic agents, the influence of driver mutations, and recent developments to harness ICD in colon cancer. Mechanism-guided combinations of ICD-inducing agents with immunotherapy and actionable biomarkers will likely offer more tailored and durable benefits to patients with colon cancer.

Estimating the strength of expression conservation from high throughput RNA-seq data.

MOTIVATION: Evolution of gene across species is usually subject to the stabilizing selection to maintain the optimal expression level. While it is generally accepted that the resulting expression conservation may vary considerably among genes, statistically reliable estimation remains challenging, due to few species included in current comparative RNA-seq data with high number of unknown parameters. RESULTS: In this paper, we develop a gamma distribution model to describe how the strength of expression conservation (denoted by W) varies among genes. Given the high throughput RNA-seq datasets from multiple species, we then formulate an empirical Bayesian procedure to estimate W for each gene. Our case studies showed that those W-estimates are useful to study the evolutionary pattern of expression conservation. AVAILABILITY AND IMPLEMENTATION: Our method has been implemented in the R-package software, TreeExp, which is publically available at Github develop site https://github.com/hr1912/TreeExp. It involves three functions: estParaGamma, estParaQ and estParaWBayesian. The manual for software TreeExp is available at https://github.com/hr1912/TreeExp/tree/master/vignettes. For any question, one may contact Dr Hang Ruan (Hang.Ruan@uth.tmc.edu).