PEX3 promotes regenerative repair after myocardial injury in mice through facilitating plasma membrane localization of ITGB3.

The peroxisome is a versatile organelle that performs diverse metabolic functions. PEX3, a critical regulator of the peroxisome, participates in various biological processes associated with the peroxisome. Whether PEX3 is involved in peroxisome-related redox homeostasis and myocardial regenerative repair remains elusive. We investigate that cardiomyocyte-specific PEX3 knockout (Pex3-KO) results in an imbalance of redox homeostasis and disrupts the endogenous proliferation/development at different times and spatial locations. Using Pex3-KO mice and myocardium-targeted intervention approaches, the effects of PEX3 on myocardial regenerative repair during both physiological and pathological stages are explored. Mechanistically, lipid metabolomics reveals that PEX3 promotes myocardial regenerative repair by affecting plasmalogen metabolism. Further, we find that PEX3-regulated plasmalogen activates the AKT/GSK3ß signaling pathway via the plasma membrane localization of ITGB3. Our study indicates that PEX3 may represent a novel therapeutic target for myocardial regenerative repair following injury.

BF3·OEt2 Catalyzed Cascade [4 + 2] Benzannulation of Vinyloxiranes with Coumarins to Construct Benzocoumarin Derivatives.

A BF3·OEt2-catalyzed cascade cyclization reaction of vinyloxirane with coumarin is described, affording the benzocoumarin derivatives with moderate to excellent yields (72-92%). The reaction demonstrates exceptional substrate tolerance and has been extensively explored for its potential in drug development, including scale-up experiments, functional group transformations, and screening of the products for anticancer activity. Moreover, the reaction mechanism has been rigorously validated through intermediate trapping and control experiments. Additionally, this reaction represents the uncommon nonmetal catalyzed intermolecular cyclization of vinyloxiranes.

Checkpoint Kinase 1 Stimulates Endogenous Cardiomyocyte Renewal and Cardiac Repair by Binding to Pyruvate Kinase Isoform M2 C-Domain and Activating Cardiac Metabolic Reprogramming in a Porcine Model of Myocardial Ischemia/Reperfusion Injury.

BACKGROUND: The regenerative capacity of the adult mammalian hearts is limited. Numerous studies have explored mechanisms of adult cardiomyocyte cell-cycle withdrawal. This translational study evaluated the effects and underlying mechanism of rhCHK1 (recombinant human checkpoint kinase 1) on the survival and proliferation of cardiomyocyte and myocardial repair after ischemia/reperfusion injury in swine. METHODS AND RESULTS: Intramyocardial injection of rhCHK1 protein (1 mg/kg) encapsulated in hydrogel stimulated cardiomyocyte proliferation and reduced cardiac inflammation response at 3 days after ischemia/reperfusion injury, improved cardiac function and attenuated ventricular remodeling, and reduced the infarct area at 28 days after ischemia/reperfusion injury. Mechanistically, multiomics sequencing analysis demonstrated enrichment of glycolysis and mTOR (mammalian target of rapamycin) pathways after rhCHK1 treatment. Co-Immunoprecipitation (Co-IP) experiments and protein docking prediction showed that CHK1 (checkpoint kinase 1) directly bound to and activated the Serine 37 (S37) and Tyrosine 105 (Y105) sites of PKM2 (pyruvate kinase isoform M2) to promote metabolic reprogramming. We further constructed plasmids that knocked out different CHK1 and PKM2 amino acid domains and transfected them into Human Embryonic Kidney 293T (HEK293T) cells for CO-IP experiments. Results showed that the 1-265 domain of CHK1 directly binds to the 157-400 amino acids of PKM2. Furthermore, hiPSC-CM (human iPS cell-derived cardiomyocyte) in vitro and in vivo experiments both demonstrated that CHK1 stimulated cardiomyocytes renewal and cardiac repair by activating PKM2 C-domain-mediated cardiac metabolic reprogramming. CONCLUSIONS: This study demonstrates that the 1-265 amino acid domain of CHK1 binds to the 157-400 domain of PKM2 and activates PKM2-mediated metabolic reprogramming to promote cardiomyocyte proliferation and myocardial repair after ischemia/reperfusion injury in adult pigs.

Clinical study of 400mg efavirenz treatment in newly diagnosed patients with HIV/AIDS.

The efficacy of 400mg efavirenz (EFV) once daily is reported to be similar to that of 600mg EFV. However, EFV-related toxic and side effects of 400mg EFV are significantly reduced. Here, the feasibility of reducing EFV to 400mg once a day in HIV-infected/AIDS patients was evaluated. Fifty patients were included. Patients were given 3TC+TDF+400mg EFV (n=25) or 3TC+TDF+600mg EFV (n=25). The proportion of patients with HIV RNA < 40 copies/mL and the adverse events served as the primary and secondary outcomes, respectively. HIV inhibition rates of the 3TC+TDF+400mg EFV group and 3TC+TDF+600mg EFV group were both 56.52% at week 24 and respectively 100%, 91.3% at week 48. During 48 weeks, 27 cases of adverse events were reported in the 3TC+TDF+400mg EFV group, lower than those in the 3TC+TDF+600mg EFV group, which had 39 cases. Compared with the 3TC+TDF+400mg EFV group, the incidence of transaminase, dizziness, hyperlipidemia and rashes all increased in the 3TC+TDF+600mg EFV group (P>0.05). No serious adverse events of the central nervous system occurred. The incidence of depression, sleep disturbance, and vertigo were similar (P>0.05). The efficacy of 400mg EFV is comparable to 600mg EFV. However, patients receiving 400mg EFV have fewer adverse events.

Genetic background of hematological parameters in Holstein cattle based on genome-wide association and RNA sequencing analyses.

Hematological parameters refer to the assessment of changes in the number and distribution of blood cells, including leukocytes (LES), erythrocytes (ERS), and platelets (PLS), which are essential for the early diagnosis of hematological system disorders and other systemic diseases in livestock. In this context, the primary objectives of this study were to investigate the genomic background of 19 hematological parameters in Holstein cattle, focusing on LES, ERS, and PLS blood components. Genetic and phenotypic (co)variances of hematological parameters were calculated based on the average information restricted maximum likelihood method and 1,610 genotyped individuals and 5,499 hematological parameter records from 4,543 cows. Furthermore, we assessed the genetic relationship between these hematological parameters and other economically important traits in dairy cattle breeding programs. We also carried out genome-wide association studies and candidate gene analyses. Blood samples from 21 primiparous cows were used to identify candidate genes further through RNA sequencing (RNA-seq) analyses. Hematological parameters generally exhibited low-to-moderate heritabilities ranging from 0.01 to 0.29, with genetic correlations between them ranging from -0.88 ± 0.09 (between mononuclear cell ratio and lymphocyte cell ratio) to 0.99 ± 0.01 (between white blood cell count and granulocyte cell count). Furthermore, low-to-moderate approximate genetic correlations between hematological parameters with one longevity, 4 fertility, and 5 health traits were observed. One hundred ninety-nine significant SNP located primarily on the Bos taurus autosomes (BTA) BTA4, BTA6, and BTA8 were associated with 16 hematological parameters. Based on the RNA-seq analyses, 6,687 genes were significantly downregulated and 4,119 genes were upregulated when comparing 2 groups of cows with high and low phenotypic values. By integrating genome-wide association studies (GWAS), RNA-seq, and previously published results, the main candidate genes associated with hematological parameters in Holstein cattle were ACRBP, ADAMTS3, CANT1, CCM2L, CNN3, CPLANE1, GPAT3, GRIP2, PLAGL2, RTL6, SOX4, WDFY3, and ZNF614. Hematological parameters are heritable and moderately to highly genetically correlated among themselves. The large number of candidate genes identified based on GWAS and RNA-seq indicate the polygenic nature and complex genetic determinism of hematological parameters in Holstein cattle.

Cellular nucleic acid binding protein facilitates cardiac repair after myocardial infarction by activating ß-catenin signaling.

The regenerative capacity of the adult mammalian heart is limited, while the neonatal heart is an organ with regenerative and proliferative ability. Activating adult cardiomyocytes (CMs) to re-enter the cell cycle is an effective therapeutic method for ischemic heart disease such as myocardial infarction (MI) and heart failure. Here, we aimed to reveal the role and potential mechanisms of cellular nucleic acid binding protein (CNBP) in cardiac regeneration and repair after heart injury. CNBP is highly expressed within 7 days post-birth while decreases significantly with the loss of regenerative ability. In vitro, overexpression of CNBP promoted CM proliferation and survival, whereas knockdown of CNBP inhibited these processes. In vivo, knockdown of CNBP in CMs robustly hindered myocardial regeneration after apical resection in neonatal mice. In adult MI mice, CM-specific CNBP overexpression in the infarct border zone ameliorated myocardial injury in acute stage and facilitated CM proliferation and functional recovery in the long term. Quantitative proteomic analysis with TMT labeling showed that CNBP overexpression promoted the DNA replication, cell cycle progression, and cell division. Mechanically, CNBP overexpression increased the expression of ß-catenin and its downstream target genes CCND1 and c-myc; Furthermore, Luciferase reporter and Chromatin immunoprecipitation (ChIP) assays showed that CNBP could directly bind to the ß-catenin promoter and promote its transcription. CNBP also upregulated the expression of G1/S-related cell cycle genes CCNE1, CDK2, and CDK4. Collectively, our study reveals the positive role of CNBP in promoting cardiac repair after injury, providing a new therapeutic option for the treatment of MI.

Organization of microtubule plus-end dynamics by phase separation in mitosis.

In eukaryotes, microtubule polymers are essential for cellular plasticity and fate decisions. End-binding (EB) proteins serve as scaffolds for orchestrating microtubule polymer dynamics and are essential for cellular dynamics and chromosome segregation in mitosis. Here, we show that EB1 forms molecular condensates with TIP150 and MCAK through liquid-liquid phase separation to compartmentalize the kinetochore-microtubule plus-end machinery, ensuring accurate kinetochore-microtubule interactions during chromosome segregation in mitosis. Perturbation of EB1-TIP150 polymer formation by a competing peptide prevents phase separation of the EB1-mediated complex and chromosome alignment at the metaphase equator in both cultured cells and Drosophila embryos. Lys220 of EB1 is dynamically acetylated by p300/CBP-associated factor in early mitosis, and persistent acetylation at Lys220 attenuates the phase separation of the EB1-mediated complex, dissolves droplets in vitro, and harnesses accurate chromosome segregation. Our data suggest a novel framework for understanding the organization and regulation of eukaryotic spindle for accurate chromosome segregation in mitosis.

Combination of histological and metabolomic assessments to evaluate the potential pharmacological efficacy of saikosaponin D.

Saikosaponin D (SsD), a natural triterpenoid saponin compound, exhibits notable potential in suppressing tumor growth and inhibiting metastasis, particularly in breast cancer. However, its underlying mechanism of action for SsD remains unclear. In this study, a combination strategy to reveal the metabolism modulation of SsD on breast cancer was performed by integration of histopathological assessments and untargeted metabolomics analysis. Pathological evaluation of the efficacy of SsD from a visual and intuitive perspective. Accordingly, a non-targeted metabolomics study was used to investigate the pharmacological efficacy using a set of serum samples from mice before and after (0-30 days) modulated with SsD based on ultra-high performance liquid chromatography tandem orbitrap mass spectrometry to discover metabolite biomarkers for finding the key metabolic mechanism in a molecular perspective. As a result, 20 metabolites were selected as potential biomarkers for SsD efficacy evaluation with high sensitivity and specificity. These metabolites changes were involved in sphingolipid metabolism, glycerophospholipid metabolism, phenylalanine and tryptophan metabolism, and phenylalanine, tyrosine and tryptophan biosynthesis pathways, suggesting that SsD exerted anti-breast cancer effects through the regulation of the underlying metabolism. In conclusion, we developed a new analysis strategy that effectively discovers tumor-progressing related metabolite biomarkers in serum for pharmacological efficacy evaluation.

Using machine learning to predict the bleeding risk for patients with cardiac valve replacement treated with warfarin in hospitalized.

BACKGROUND: Distinguishing warfarin-related bleeding risk at the bedside remains challenging. Studies indicate that warfarin therapy should be suspended when international normalized ratio (INR) ≥ 4.5, or it may sharply increase the risk of bleeding. We aim to develop and validate a model to predict the high bleeding risk in valve replacement patients during hospitalization. METHOD: Cardiac valve replacement patients from January 2016 to December 2021 across Nanjing First Hospital were collected. Five different machine-learning (ML) models were used to establish the prediction model. High bleeding risk was an INR ≥4.5. The area under the receiver operating characteristic curve (AUC) was used for evaluating the prediction performance of different models. The SHapley Additive exPlanations (SHAP) was used for interpreting the model. We also compared ML with ATRIA score and ORBIT score. RESULTS: A total of 2376 patients were finally enrolled in this model, 131 (5.5%) of whom experienced the high bleeding risk after anticoagulation therapy of warfarin during hospitalization. The extreme gradient boosting (XGBoost) exhibited the best overall prediction performance (AUC: 0.882, confidence interval [CI] 0.817-0.946, Brier score, 0.158) compared to other prediction models. It also shows superior performance compared with ATRIA score and ORBIT score. The top 5 most influential features in XGBoost model were platelet, thyroid stimulation hormone, body surface area, serum creatinine and white blood cell. CONCLUSION: A model for predicting high bleeding risk in valve replacement patients who treated with warfarin during hospitalization was successfully developed by using machine learning, which may well assist clinicians to identify patients at high risk of bleeding and allow timely adjust therapeutic strategies in evaluating individual patient.

Catalytic Structure Design by AI Generating with Spectroscopic Descriptors.

Generative artificial intelligence has depicted a beautiful blueprint for on-demand design in chemical research. However, the few successful chemical generations have only been able to implement a few special property values because most chemical descriptors are mathematically discrete or discontinuously adjustable. Herein, we use spectroscopic descriptors with machine learning to establish a quantitative spectral structure-property relationship for adsorbed molecules on metal monatomic catalysts. Besides catalytic properties such as adsorption energy and charge transfer, the complete spatial relative coordinates of the adsorbed molecule were successfully inverted. The spectroscopic descriptors and prediction models are generalized, allowing them to be transferred to several different systems. Due to the continuous tunability of the spectroscopic descriptors, the design of catalytic structures with continuous adsorption states generated by AI in the catalytic process has been achieved. This work paves the way for using spectroscopy to enable real-time monitoring of the catalytic process and continuous customization of catalytic performance, which will lead to profound changes in catalytic research.

Tolerability and effectiveness of albuvirtide combined with dolutegravir for hospitalized people living with HIV/AIDS.

Treatment options for hospitalized people living with HIV/AIDS (PLWHA) with opportunistic infections and comorbidities are limited in China. Albuvirtide (ABT), a new peptide drug, is a long-acting HIV fusion inhibitor with limited drug-drug interactions and fast onset time. This single-center, retrospective cohort study investigated the effectiveness and safety of ABT plus dolutegravir (DTG) therapy in a real-world setting. We performed a chart review on the electronic patient records for hospitalized PLWHA using ABT plus DTG between April and December 2020. The clinical outcomes were retrospectively analyzed. Among 151 PLWHA (mean age 47.6 ± 15.9 years), 140 (93%) had at least 1 episode of bacterial and/or fungal infections and 64 (42%) had other comorbidities including syphilis, hepatitis B, and/or hypertension. ABT plus DTG was given to 87 treatment-naïve (TN) and 64 treatment-experienced (TE) PLWHA. Regardless of treatment history, mean HIV-1 RNA levels significantly decreased from 4.32 log10copies/mL to 2.24 log10copies/mL, 2.10 log10copies/mL and 1.89 log10copies/mL after 2, 4 and 8 weeks of treatment, respectively (P < .0001). Compared with baseline mean CD4 + T-cell counts of 122.72 cells/µL, it increased to 207.87 cells/µL (P = .0067) and 218.69 cells/µL (P = .0812) after 4 and 8 weeks of treatment. Except for limited laboratory abnormalities such as hyperuricemia, increased creatinine level, and hyperglycemia observed after treatment, no other clinical adverse events were considered related to ABT plus DTG. Data suggests that ABT plus DTG is safe and effective for critically-ill hospitalized PLWHA. In view of the rapid viral load suppression and restoration of CD4 + count within 8 weeks of treatment, its clinical application warrants further investigation.

SIRT3-dependent mitochondrial redox homeostasis mitigates CHK1 inhibition combined with gemcitabine treatment induced cardiotoxicity in hiPSC-CMs and mice.

Administration of CHK1-targeted anticancer therapies is associated with an increased cumulative risk of cardiac complications, which is further amplified when combined with gemcitabine. However, the underlying mechanisms remain elusive. In this study, we generated hiPSC-CMs and murine models to elucidate the mechanisms underlying CHK1 inhibition combined with gemcitabine-induced cardiotoxicity and identify potential targets for cardioprotection. Mice were intraperitoneally injected with 25 mg/kg CHK1 inhibitor AZD7762 and 20 mg/kg gemcitabine for 3 weeks. hiPSC-CMs and NMCMs were incubated with 0.5 uM AZD7762 and 0.1 uM gemcitabine for 24 h. Both pharmacological inhibition or genetic deletion of CHK1 and administration of gemcitabine induced mtROS overproduction and pyroptosis in cardiomyocytes by disrupting mitochondrial respiration, ultimately causing heart atrophy and cardiac dysfunction in mice. These toxic effects were further exacerbated with combination administration. Using mitochondria-targeting sequence-directed vectors to overexpress CHK1 in cardiomyocyte (CM) mitochondria, we identified the localization of CHK1 in CM mitochondria and its crucial role in maintaining mitochondrial redox homeostasis for the first time. Mitochondrial CHK1 function loss mediated the cardiotoxicity induced by AZD7762 and CHK1-knockout. Mechanistically, mitochondrial CHK1 directly phosphorylates SIRT3 and promotes its expression within mitochondria. On the contrary, both AZD7762 or CHK1-knockout and gemcitabine decreased mitochondrial SIRT3 abundance, thus resulting in respiration dysfunction. Further hiPSC-CMs and mice experiments demonstrated that SIRT3 overexpression maintained mitochondrial function while alleviating CM pyroptosis, and thereby improving mice cardiac function. In summary, our results suggest that targeting SIRT3 could represent a novel therapeutic approach for clinical prevention and treatment of cardiotoxicity induced by CHK1 inhibition and gemcitabine.

Air quality prediction model based on mRMR-RF feature selection and ISSA-LSTM.

Severe air pollution poses a significant threat to public safety and human health. Predicting future air quality conditions is crucial for implementing pollution control measures and guiding residents' activity choices. However, traditional single-module machine learning models suffer from long training times and low prediction accuracy. To improve the accuracy of air quality forecasting, this paper proposes a ISSA-LSTM model-based approach for predicting the air quality index (AQI). The model consists of three main components: random forest (RF) and mRMR, improved sparrow search algorithm (ISSA), and long short-term memory network (LSTM). Firstly, RF-mRMR is used to select the influential variables affecting AQI, thereby enhancing the model's performance. Next, ISSA algorithm is employed to optimize the hyperparameters of LSTM, further improving the model's performance. Finally, LSTM model is utilized to predict AQI concentrations. Through comparative experiments, it is demonstrated that the ISSA-LSTM model outperforms other models in terms of RMSE and R2, exhibiting higher prediction accuracy. The model's predictive performance is validated across different time steps, demonstrating minimal prediction errors. Therefore, the ISSA-LSTM model is a viable and effective approach for accurately predicting AQI.

Interpretable Machine Learning Model Predicting Early Neurological Deterioration in Ischemic Stroke Patients Treated with Mechanical Thrombectomy: A Retrospective Study.

Early neurologic deterioration (END) is a common and feared complication for acute ischemic stroke (AIS) patients treated with mechanical thrombectomy (MT). This study aimed to develop an interpretable machine learning (ML) model for individualized prediction to predict END in AIS patients treated with MT. The retrospective cohort of AIS patients who underwent MT was from two hospitals. ML methods applied include logistic regression (LR), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBoost). The area under the receiver operating characteristic curve (AUC) was the main evaluation metric used. We also used Shapley Additive Explanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) to interpret the result of the prediction model. A total of 985 patients were enrolled in this study, and the development of END was noted in 157 patients (15.9%). Among the used models, XGBoost had the highest prediction power (AUC = 0.826, 95% CI 0.781-0.871). The Delong test and calibration curve indicated that XGBoost significantly surpassed those of the other models in prediction. In addition, the AUC in the validating set was 0.846, which showed a good performance of the XGBoost. The SHAP method revealed that blood glucose was the most important predictor variable. The constructed interpretable ML model can be used to predict the risk probability of END after MT in AIS patients. It may help clinical decision making in the perioperative period of AIS patients treated with MT.

Association of glycation gap with all-cause and cardiovascular mortality in US adults: A nationwide cohort study.

AIM: To investigate the relationship of the glycation gap (GGap) with all-cause and cardiovascular (CV) mortality in US adults. METHODS: This was a retrospective cohort study comprising 12 909 individual participant data from the National Health and Nutrition Examination Survey from 1999 to 2004 and their mortality data through 31 December 2019. Weighted Cox proportional hazards regression models and restricted cubic splines were used to investigate the associations between GGap and mortality. RESULTS: During a median follow-up of 16.8 years, 3528 deaths occurred, including 1140 CV deaths. The associations of GGap with risk of all-cause and CV mortality were U-shaped (both P for non-linearity < .001). Compared with individuals with a GGap of 0.09%-0.38% (61st-80th centiles), the multivariable-adjusted HRs and 95% CIs for individuals with a GGap less than -0.83% (first-fifth centiles) and individuals with a GGap greater than 0.90% (96th-100th centiles) were 1.36 (1.10, 1.69) and 1.21 (1.00, 1.45) for all-cause mortality, and 1.77 (1.16, 2.71) and 1.43 (1.04, 1.95) for CV mortality. The GGap value associated with the lowest risk of all-cause and CV mortality was 0.38% in the general population and 0.78% among individuals with diabetes. CONCLUSIONS: We found a U-shaped association between GGap and all-cause and CV mortality, with significant positive or negative GGap values associated with increased mortality risk, probably because of glycaemic variability and fructosamine-3-kinase activity.

Improved methodology for efficient establishment of the myocardial ischemia-reperfusion model in pigs through the median thoracic incision.

To investigate the feasibility and effectiveness of establishing porcine ischemia-reperfusion models by ligating the left anterior descending (LAD) coronary artery, we first randomly divided 16 male Bama pigs into a sham group and a model group. After anesthesia, we separated the arteries and veins. Subsequently, we rapidly located the LAD coronary artery at the beginning of its first diagonal branch through a mid-chest incision. Then, we loosened and released the ligation line after five minutes of pre-occlusion. Finally, we ligated the LAD coronary artery in situ two minutes later and loosened the ligature 60 min after ischemia. Compared with the sham group, electrocardiogram showed multiple continuous lead ST-segment elevations, and ultrasound cardiogram showed significantly lower ejection fraction and left ventricular fractional shortening at one hour and seven days post-operation in the model group. Twenty-four hours after the operation, cardiac troponin T and creatine kinase-MB isoenzyme levels significantly increased in the model group, compared with the sham group. Hematoxylin and eosin staining showed the presence of many inflammatory cells infiltrating the interstitium of the myocardium in the model group but not in the sham group. Masson staining revealed a significant increase in infarct size in the ischemia/reperfusion group. All eight pigs in the model group recovered with normal sinus heart rates, and the survival rate was 100%. In conclusion, the method can provide an accurate and stable large animal model for preclinical research on ischemia/reperfusion with a high success rate and homogeneity of the myocardial infarction area.

P16INK4a Regulates ROS-Related Autophagy and CDK4/6-Mediated Proliferation: A New Target of Myocardial Regeneration Therapy.

Neonatal mice achieve complete cardiac repair through endogenous myocardial regeneration after apical resection (AR), but this capacity is rapidly lost 7 days after birth. As an upstream inhibitor of cyclin-dependent kinase 4/6- (CDK4/6-) mediated cell cycle activity, p16INK4a is widely involved in regulating tumor and senescence. Given that p16INK4a had a significant negative regulation on cell proliferation, targeting cardiomyocytes (CMs) to inhibit p16INK4a seems to be a promising attempt at myocardial regeneration therapy. The p16INK4a expression was upregulated during perimyocardial regeneration time. Knockdown of p16INK4a stimulated CM proliferation, while p16INK4a overexpression had the opposite effect. In addition, p16INK4a knockdown prolonged the proliferation time window of newborn myocardium. And p16INK4a overexpression inhibited cell cycle activity and deteriorated myocardial regeneration after AR. The quantitative proteomic analysis showed that p16INK4a knockdown mediated the cell cycle progression and intervened in energy metabolism homeostasis. Mechanistically, overexpression of p16INK4a causes abnormal accumulation of reactive oxygen species (ROS) to induce autophagy, while scavenging ROS with N-acetylcysteine can alleviate autophagy and regulate p16INK4a, CDK4/6, and CyclinD1 in a covering manner. And the effect of inhibiting the proliferation of p16INK4a-activated CMs was significantly blocked by the CDK4/6 inhibitor Palbociclib. In summary, p16INK4a regulated CM proliferation progression through CDK4/6 and ROS-related autophagy to jointly affect myocardial regeneration repair. Our study revealed that p16INK4a might be a potential therapeutic target for myocardial regeneration after injury.

Association of serum osmolality with all-cause and cardiovascular mortality in US adults: A prospective cohort study.

BACKGROUND AND AIMS: The association between serum osmolality, an effective indicator of body hydration status, and long-term mortality in the general population remains undetermined. The present study aimed to investigate the association of serum osmolality with long-term all-cause and cardiovascular mortality among adults in the United States. METHODS AND RESULTS: This cohort study used data from the National Health and Nutrition Examination Survey (NHANES) 2007-2014. Participants were linked to National Death Index mortality data from the survey date through December 31, 2019. Cox proportional hazards regression model was used to calculate hazard ratios (HRs) and 95% CIs, and restricted cubic spline (RCS) regression was conducted. A total of 18312 US adults were included. During a median follow-up of 8.7 years, 1353 total deaths occurred, including 379 cardiovascular deaths. After multivariable adjustments, compared with the 3rd quartile (Q3) of serum osmolality, participants in the 1st (Q1) and 4th (Q4) quartiles were at a significantly higher risk of all-cause mortality (HR 1.41 [95% CI, 1.14-1.75] and 1.29 [95% CI, 1.04-1.61], respectively). RCS revealed a nonlinear relationship of serum osmolality to all-cause and cardiovascular mortality, with an inflection point of 278 mmol/kg. CONCLUSION: In the nationally representative cohort of US adults, serum osmolality was nonlinearly associated with all-cause and cardiovascular mortality. The risk of mortality was lowest around an osmolality of 278 mmol/kg. These findings suggest the importance of serum osmolality management for long-term health outcomes.

Prognostic costimulatory molecule-related signature risk model correlates with immunotherapy response in colon cancer.

Costimulatory molecules can promote the activation and proliferation of T cells and play an essential role in immunotherapy. However, their role in the prognosis of colon adenocarcinoma remains elusive. In this study, the expression data of costimulatory molecules and clinicopathological information of 429 patients with colon adenocarcinoma were obtained from The Cancer Genome Atlas database. The patients were divided into training and verification cohorts. Correlation, Cox regression, and Lasso regression analyses were performed to identify costimulatory molecules related to prognosis. After mentioning the construction of the risk mode, a nomogram integrating the clinical characteristics and risk scores of patients was constructed to predict prognosis. Eventually, three prognostic costimulatory molecules were identified and used for constructing a risk model. High expression of these three molecules indicated a poor prognosis. The predictive accuracy of the risk model was verified in the GSE17536 dataset. Subsequently, multivariate regression analysis showed that the signature based on the three costimulatory molecules was an independent risk factor in the training cohort (HR = 2.12; 95% CI = 1.26, 3.56). Based on the risk model and clinicopathological data, the AUC values for predicting the 1-, 3-, and 5-year survival probability of patients with colon adenocarcinoma were 0.77, 0.77, and 0.71, respectively. To the best of our knowledge, this study is the first to report a risk signature constructed based on the costimulatory molecules TNFRSF10c, TNFRSF13c, and TNFRSF11a. This risk signature can serve as a prognostic biomarker for colon adenocarcinoma and is related to the immunotherapeutic response of patients.