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Remimazolam (CNS7056) is a novel benzodiazepine for intravenous sedation; it has an ultra-short duration of action and was recently approved for use in procedural sedation and general anaesthesia. It acts on [gamma]-aminobutyric acid type A receptors and is rapidly converted into an inactive metabolite by tissue esterase enzymes. Remimazolam has been successfully used in endoscopic inspection or surgery and general anaesthesia induction and maintenance with fast and predictable onset and recovery times, high procedure success rates, and minor respiratory and hemodynamic fuctuations and without serious drug-related adverse reactions. If needed, the effects of remimazolam can be reversed by fumazenil, which allows prompt termination of sedation. Although remimazolam has great potential for sedation in patients admitted to intensive care units, future studies are needed to evaluate its efficacy and safety in patients requiring sedation for a long period, and numerous studies are warranted to explore the optimal dose in different application scenarios. The review aimed to provide an introduction to the process of remimazolam synthesis and its current clinical uses and future clinical developments. Keywords: sedation, endoscopy, general anaesthesia, ICU

Chemokine (C–C motif) ligand 19 (CCL19) is a critical regulator of the induction of T cell activation, immune tolerance, and inflammatory responses during continuous immune surveillance, homeostasis, and development. Migration of CC-chemokine receptor 7 (CCR7)-expressing cells to secondary lymphoid organs is a crucial step in the onset of adaptive immunity, which is initiated by a complex interaction between CCR7 and its cognate ligands. Recent advances in knowledge regarding the response of the CCL19-CCR7 axis to viral infections have elucidated the complex network of interplay among the invading virus, target cells and host immune responses. Viruses use various strategies to evade or delay the cytokine response, gaining additional time to replicate in the host. In this review, we summarize the impacts of CCL19 and CCR7 expression on the regulation of viral pathogenesis with an emphasis on the corresponding signaling pathways and adjuvant mechanisms. We present and discuss the expression, signaling adaptor proteins and effects of CCL19 and CCR7 as these molecules differentially impact different viral infections and viral life cycles in host homeostatic strategies. The underlying mechanisms discussed in this review may assist in the design of novel agents to modulate chemokine activity for viral prevention.

HSV-2 is the main pathogen causing genital herpes, and its infection increases the infection and transmission of HIV-1. Currently, there are no vaccines to prevent HSV-2 infection or treatment that can fully cure it. Mining key host factors that regulate HSV-2 replication and elucidating their specific regulatory mechanisms are crucial for understanding virus–host interactions and discovering new antiviral targets. In the current study, we identified DDX43 as a cellular factor involved in the suppression of HSV-2 replication through comparative transcriptomic analyses of HSV-2-infected epithelial cells, followed by experimental validation. Comprehensive transcriptomic profiling revealed distinct host cellular gene expression patterns in HeLa and ARPE-19 cell lines post HSV-2 infection. Subsequent orthogonal partial least-squares discriminant analysis (OPLS-DA) pinpointed DDX43 as one of the principal mediators distinguishing the host response between HSV-2-infected HeLa and ARPE-19 cells. Furthermore, overexpression of DDX43 inhibited HSV-2 replication, whereas knockdown of endogenous DDX43 enhanced HSV-2 replication. Additional experiments revealed that human DDX43 inhibits HSV-2 replication in an interferon-independent manner. This study demonstrates that DDX43 serves as a host regulator against HSV-2 infection, underscoring the power of comparative transcriptomics in identifying novel host proteins that modulate viral replications.

Sepsis-Associated Liver Injury (SALI) is an independent risk factor for death from sepsis. The aim of this study was to develop an interpretable machine learning model for early prediction of 28-day mortality in patients with SALI. Data from the Medical Information Mart for Intensive Care (MIMIC-IV, v2.2, MIMIC-III, v1.4) were used in this study. The study cohort from MIMIC-IV was randomized to the training set (0.7) and the internal validation set (0.3), with MIMIC-III (2001 to 2008) as external validation. The features with more than 20% missing values were deleted and the remaining features were multiple interpolated. Lasso-CV that lasso linear model with iterative fitting along a regularization path in which the best model is selected by cross-validation was used to select important features for model development. Eight machine learning models including Random Forest (RF), Logistic Regression, Decision Tree, Extreme Gradient Boost (XGBoost), K Nearest Neighbor, Support Vector Machine, Generalized Linear Models in which the best model is selected by cross-validation (CV_glmnet), and Linear Discriminant Analysis (LDA) were developed. Shapley additive interpretation (SHAP) was used to improve the interpretability of the optimal model. At last, a total of 1043 patients were included, of whom 710 were from MIMIC-IV and 333 from MIMIC-III. Twenty-four clinically relevant parameters were selected for model construction. For the prediction of 28-day mortality of SALI in the internal validation set, the area under the curve (AUC (95% CI)) of RF was 0.79 (95% CI: 0.73–0.86), and which performed the best. Compared with the traditional disease severity scores including Oxford Acute Severity of Illness Score (OASIS), Sequential Organ Failure Assessment (SOFA), Simplified Acute Physiology Score II (SAPS II), Logistic Organ Dysfunction Score (LODS), Systemic Inflammatory Response Syndrome (SIRS), and Acute Physiology Score III (APS III), RF also had the best performance. SHAP analysis found that Urine output, Charlson Comorbidity Index (CCI), minimal Glasgow Coma Scale (GCS_min), blood urea nitrogen (BUN) and admission_age were the five most important features affecting RF model. Therefore, RF has good predictive ability for 28-day mortality prediction in SALI. Urine output, CCI, GCS_min, BUN and age at admission(admission_age) within 24 h after intensive care unit(ICU) admission contribute significantly to model prediction.

In the intensive care unit (ICU), septic patients frequently require endotracheal intubation followed by invasive mechanical ventilation. Nonetheless, the optimal sedation-analgesia regimen for these critically ill patients remains undetermined. This retrospective observational study analyzed data from the Medical Information Mart for Intensive Care IV (MIMIC-IV version 3.0) database to examine septic patients who underwent endotracheal intubation and subsequent invasive mechanical ventilation in the intensive care unit. Initially, Kaplan-Meier survival analysis and Cox proportional hazards models were employed to evaluate the prognostic impact of different sedation-analgesia regimens. Subsequently, the least absolute shrinkage and selection operator (LASSO) regression was utilized to identify key prognostic factors. Multiple machine learning algorithms were then implemented to develop predictive models, and the SHapley Additive exPlanations (SHAP) method was used to interpret the model outputs and determine the most influential predictors. Following the initial screening process, seven distinct sedation-analgesia regimens with sample sizes greater than 100 were incorporated into the final analysis. Utilizing Kaplan-Meier estimates and Cox regression models, the combination of fentanyl and midazolam was identified as the most advantageous regimen. This association remained statistically significant after adjusting for confounding variables, demonstrating a reduction in the length of stay in the intensive care unit (length of stay in ICU, HR [95% CI]: 0.66 [0.52-0.85]) and a decrease in ICU mortality (OR [95% CI]: 0.62 [0.46-0.85]). Subsequently, LASSO regression analysis identified seven key prognostic factors associated with outcomes in this patient subgroup. Among the machine learning models developed for outcome prediction, the LightGBM model exhibited superior performance (AUC = 0.838). SHAP analysis indicated that the top three predictors of 28-day mortality were the Acute Physiology Score III (APS III), patient age, and the presence of acute renal failure. The concurrent administration of fentanyl and midazolam was associated with lower ICU mortality and shorter length of ICU stay among septic patients necessitating endotracheal intubation and invasive mechanical ventilation, suggesting potential clinical benefit. Furthermore, the LightGBM algorithm exhibited superior predictive accuracy for ICU mortality within this cohort, suggesting its potential utility as a tool for supporting data-driven clinical decision-making.

Pentagalloyl glucose (PGG) is a natural hydrolyzable gallotannin abundant in various plants and herbs. It has a broad range of biological activities, specifically anticancer activities, and numerous molecular targets. Despite multiple studies available on the pharmacological action of PGG, the molecular mechanisms underlying the anticancer effects of PGG are unclear. Here, we have critically reviewed the natural sources of PGG, its anticancer properties, and underlying mechanisms of action. We found that multiple natural sources of PGG are available, and the existing production technology is sufficient to produce large quantities of the required product. Three plants (or their parts) with maximum PGG content were Rhus chinensis Mill, Bouea macrophylla seed, and Mangifera indica kernel. PGG acts on multiple molecular targets and signaling pathways associated with the hallmarks of cancer to inhibit growth, angiogenesis, and metastasis of several cancers. Moreover, PGG can enhance the efficacy of chemotherapy and radiotherapy by modulating various cancer-associated pathways. Therefore, PGG can be used for treating different human cancers; nevertheless, the data on the pharmacokinetics and safety profile of PGG are limited, and further studies are essential to define the clinical use of PGG in cancer therapies.

Sepsis is a high-incidence disease and demands intensive care. Finding effective treatment is the key to cure sepsis. Studies have shown a lower level of vitamin C in patients with sepsis. Therefore, vitamin C supplementation has become one of the measures to treat sepsis. However, the clinical studies of vitamin C in the treatment of sepsis have been controversial. We performed a meta-analysis to evaluate vitamin C’s efficacy and safety in the treatment of sepsis. We searched four electronic databases: PubMed, Embase, Web of Science, and the Cochrane Library, and two researchers independently screened 24 eligible RCTs published in English. Our review demonstrates that intravenous (IV) vitamin C might improve short-term mortality (RR, 0.82; 95% CI, 0.65–1.02; P=0.07; and I2 = 45%) and overall mortality (RR, 0.86; 95% CI, 0.74–1.01; P=0.06; and I2 = 51%) of patients with sepsis. Moreover, the SOFA score of patients with sepsis improved significantly after treatment with vitamin C for over 72 hours (RR, 0.26; 95% CI, 0.09–0.42; P=0.002; and I2 = 0%). The main results of our study were moderate-quality evidence. More high-quality, multicenter RCTs are needed to provide more substantial evidence on the efficacy and safety of IV vitamin C for sepsis.

Human norovirus (HuNoV) is the leading cause of acute gastroenteritis (AGE) worldwide, which is highly stable and contagious, with a few virus particles being sufficient to establish infection. Although the World Health Organization in 2016 stated that it should be an absolute priority to develop a HuNoV vaccine, unfortunately, there is currently no licensed HuNoV vaccine available. The major barrier to the development of an effective HuNoV vaccine is the lack of a robust and reproducible in vitro cultivation system. To develop a HuNoV vaccine, HuNoV immunogen alone or in combination with other viral immunogens have been designed to assess whether they can simultaneously induce protective immune responses against different viruses. Additionally, monovalent and multivalent vaccines from different HuNoV genotypes, including GI and GII HuNoV virus-like particles (VLPs), have been assessed in order to induce broad protection. Although there are several HuNoV vaccine candidates based on VLPs that are being tested in clinical trials, the challenges to develop effective HuNoV vaccines remain largely unresolved. In this review, we summarize the advances of the HuNoV cultivation system and HuNoV vaccine research and discuss current challenges and future perspectives in HuNoV vaccine development.

Background Sleep disturbances (SD) exhibit a high prevalence among older adults and exert considerable influence on cardiovascular health, quality of life, and other facets of well-being. α-Klotho, an anti-aging factor that diminishes with advancing age, has been implicated in a multitude of age-related conditions. However, the relationship between SD and α-klotho levels in the elderly remains inadequately investigated, and potential sex-specific differences in this association warrant further exploration. Methods This study utilized data from the National Health and Nutrition Examination Survey (NHANES) to initially investigate the association between α-klotho levels and SD, with analyses conducted separately for both sexes. In addition, the relationship was further delineated using restricted cubic spline (RCS) curves. Results A total of 5,957 elderly adults participated in this study, revealing a prevalence of SD at 29.5%. Notably, females exhibited a higher prevalence of SD compared to men (33.6% for females vs. 25.3% for males). After adjusting for covariates, higher α-klotho levels were hypothesized to be associated with a decreased incidence of SD. Differences also existed between sexes, as demonstrated by a significant correlation between serum α-klotho and SD in females, but not in males. Results from the RCS analysis indicated a negative and nonlinear relationship between α-klotho levels and SD, consistent across both sexes and the general population. Conclusions The findings of the current study revealed a negative association between α-klotho levels and the development of SD in the elderly population, with notable sex-specific differences.

Although conventional vaccine approaches have proven to be successful in preventing infectious diseases in past decades, for vaccine development against emerging/re-emerging viruses, one of the main challenges is rapid response in terms of design and manufacture. mRNA vaccines can be designed and produced within days, representing a powerful approach for developing vaccines. Furthermore, mRNA vaccines can be scaled up and may not have the risk of integration. mRNA vaccines are roughly divided into non-replicating mRNA vaccines and self-amplifying RNA (saRNA) vaccines. In this review, we provide an overview of saRNA vaccines, and discuss future directions and challenges in advancing this promising vaccine platform to combat emerging/re-emerging viruses.