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It is noticeable how the novel coronavirus has spread from the Wuhan region of China to the whole world, devastating the lives of people worldwide. All the data related to the precautionary measures, diagnosis, treatment, and even the epidemiological data are being made freely accessible and reachable in a very little time as well as being rapidly published to save humankind from this pandemic. There might be neurological complications of COVID-19 and patients suffering from neurodegenerative conditions like Alzheimer’s disease and Parkinson’s disease might have repercussions as a result of the pandemic. In this review article, we have discussed the effect of SARS-CoV-2 viral infection on the people affected with neurodegenerative disorders such as Parkinson’s and Alzheimer’s. It primarily emphasizes two issues, i.e., vulnerability to infection and modifications of course of the disease concerning the clinical neurological manifestations, the advancement of the disease and novel approaches to support health care professionals in disease management, the susceptibility to these diseases, and impact on the severity of disease and management.

Background We evaluated community health volunteer (CHV) strategies to prevent non-communicable disease (NCD) care disruption and promote coronavirus disease 2019 (COVID-19) detection among Syrian refugees and vulnerable Jordanians, as the pandemic started. Methods Alongside medication delivery, CHVs called patients monthly to assess stockouts and adherence, provide self-management and psychosocial support, and screen and refer for complications and COVID-19 testing. Cohort analysis was undertaken of stockouts, adherence, complications and suspected COVID-19. Multivariable models of disease control assessed predictors and non-inferiority of the strategy pre-/post-initiation. Cost-efficiency and patient/staff interviews assessed implementation. Results Overall, 1119 patients were monitored over 8 mo. The mean monthly proportion of stockouts was 4.9%. The monthly proportion non-adherent (past 5/30 d) remained below 5%; 204 (18.1%) patients had complications, with 63 requiring secondary care. Mean systolic blood pressure and random blood glucose remained stable. For hypertensive disease control, age 41–65 y (OR 0.46, 95% CI 0.2 to 0.78) and with diabetes (OR 0.73, 95% CI 0.54 to 0.98) had decreased odds, and with baseline control had increased odds (OR 3.08, 95% CI 2.31 to 4.13). Cumulative suspected COVID-19 incidence (2.3/1000 population) was suggestive of ongoing transmission. While cost-efficient (108 US${\$}$/patient/year), funding secondary care was challenging. Conclusions During multiple crises, CHVs prevented care disruption and reinforced COVID-19 detection.

Objectives: Toward common methods for system monitoring and evaluation, we proposed a key performance indicator framework and discussed lessons learned while implementing a statewide exposure notification (EN) system in California during the COVID-19 epidemic. Materials and Methods: California deployed the Google Apple Exposure Notification framework, branded CA Notify, on December 10, 2020, to supplement traditional COVID-19 contact tracing programs. For system evaluation, we defined 6 key performance indicators: adoption, retention, sharing of unique codes, identification of potential contacts, behavior change, and impact. We aggregated and analyzed data from December 10, 2020, to July 1, 2021, in compliance with the CA Notify privacy policy. Results: We estimated CA Notify adoption at nearly 11 million smartphone activations during the study period. Among 1 654 201 CA Notify users who received a positive test result for SARS-CoV-2, 446 634 (27%) shared their unique code, leading to ENs for other CA Notify users who were in close proximity to the SARS-CoV-2–positive individual. We identified at least 122 970 CA Notify users as contacts through this process. Contact identification occurred a median of 4 days after symptom onset or specimen collection date of the user who received a positive test result for SARS-CoV-2. Practice Implications: Smartphone-based EN systems are promising new tools to supplement traditional contact tracing and public health interventions, particularly when efficient scaling is not feasible for other approaches. Methods to collect and interpret appropriate measures of system performance must be refined while maintaining trust and privacy.

Schizophrenia is a serious psychiatric disorder leading to cognitive impairment and has higher rates of morbidity and mortality. There is a need to understand the mechanisms underlying the onset and progression of the disease as the clinical presentation may vary in patients and inadequate knowledge of neurochemical alterations can lead to decreased efficacy in treatment which makes it necessary to identify new potent biomarkers. Identification of biomarkers in schizophrenia offers significant benefits to the well-being of patients, including better prognosis, diagnosis, detection, screening, enhancement in treatment efficacy, prevention of relapse, and better clinical results. Incorporation of advanced technological techniques is necessary to provide an approach for the diagnosis and treatment of psychiatric disorders and to permit specific therapeutic interventions. This review highlights the particulars about the current use and application of various biomarkers such as proteomics, miRNAs, language techniques, antibodies, blood biomarkers, gut microbiota, such as analysis, neuroimaging techniques, and inflammatory biomarkers in effective prognosis, detection, and treatment of schizophrenia and which would contribute as an additional tool for a psychiatrist in cases where an appropriate diagnosis is lacking clarity.

Background: Interventions designed to reduce the risk for head impacts and concussion in youth football have increased over the past decade; however, understanding of the role of regular game play on head impact exposure among youth tackle and flag football athletes is currently limited. Purpose: To explore head impact exposure among youth tackle and flag football athletes (age range, 6-14 years) during both practices and games. Study Design: Cohort study; Level of evidence, 2. Methods: Using the Vector MouthGuard sensor, the authors collected head impact data from 524 tackle and flag youth football athletes over the course of a football season. Quantities of interest were estimated from regression models using Bayesian methods. Results: For impacts ≥10 g, a tackle football athlete had an estimated 17.55 (95% CI, 10.78-28.96) times more head impacts per practice compared with a flag football athlete (6.85 [95% CI, 6.05-7.76] and 0.39 [95% CI, 0.24-0.62] head impacts, respectively). Additionally, a tackle football athlete had an estimated 19.48 (95% CI, 12.74-29.98) times more head impacts per game compared with a flag football athlete (13.59 [95% CI, 11.97-15.41] and 0.70 [95% CI, 0.46-1.05] head impacts, respectively). Among tackle football athletes, the estimated average impact rate was 6.51 (95% CI, 5.75-7.37) head impacts during a practice and 12.97 (95% CI, 11.36-14.73) impacts during a game, resulting in 2.00 (95% CI, 1.74-2.29) times more ≥10 g head impacts in games versus practices. Tackle football athletes had 2.06 (95% CI, 1.80-2.34) times more high-magnitude head impacts (≥40 g) during a game than during a practice. On average, flag football athletes experienced an estimated 0.37 (95% CI, 0.20-0.60) head impacts during a practice and 0.77 (95% CI, 0.53-1.06) impacts during a game, resulting in 2.06 (95% CI, 1.29-3.58) times more ≥10 g head impacts in games versus practices. Because of model instability caused by a large number of zero impacts for flag football athletes, a comparison of high-magnitude head impacts is not reported for practices or games. Conclusion: This study provides a characterization of the head impact exposure of practices and games among a large population of youth tackle and flag football athletes aged 6 to 14 years. These findings suggest that a greater focus on game-based interventions, such as fair play interventions and strict officiating, may be beneficial to reduce head impact exposures for youth football athletes.

Network science methods can be useful in design, monitoring, and analysis of randomized trials for control of spread of infections. Their usefulness arises from the role of statistical network models in molecular epidemiology and in study design. Computational models, such as agent-based models that propagate disease on simulated contact networks, can be used to investigate the properties of different study designs and analysis plans. Particularly valuable is the use of these methods to assess how magnitude and detectability of intervention effects depend on both individual-level and network-level characteristics of the enrolled populations. Such investigation also provides an important approach to assessing consequences of study data being incomplete or measured with error. To address these goals, we consider two statistical network models: exponential random graph models and the more flexible congruence class models. We focus first on an historical use of these methods in design and monitoring of a cluster randomized trial in Botswana to evaluate the effect of combination HIV prevention modalities compared to standard of care on HIV incidence. We then present a framework for the design of a study of booster vaccine effects on infection with, and forward transmission of, SARS-CoV-2 variants. Motivation for the study is driven in part by guidance from the United Kingdom to base approval of booster vaccines with “strain changes” that target variants on results of neutralizing antibody tests and information about safety, but without requiring evidence of clinical efficacy. Using designs informed by our agent-based network models, we show it may be feasible to conduct a trial of novel SARS-CoV-2 vaccines in a single large campus to obtain useful information regarding vaccine efficacy against susceptibility and infectiousness. If needed, the sample size could be increased by extending the study to a small number of campuses. Novel network methods may be useful in developing pragmatic SARS-CoV-2 vaccine trials that can leverage existing infrastructure to reduce costs and hasten the development of results.

Background: Promoted as a safer alternative to tackle football, there has been an increase in flag football participation in recent years. However, examinations of head impact exposure in flag football as compared with tackle football are currently limited. Hypothesis: Tackle football athletes will have a greater number and magnitude of head impacts compared with flag football athletes. Study Design: Cohort study. Level of Evidence: Level 4. Methods: Using mouthguard sensors, this observational, prospective cohort study captured data on the number and magnitude of head impacts among 524 male tackle and flag football athletes (6-14 years old) over the course of a single football season. Estimates of interest based on regression models used Bayesian methods to estimate differences between tackle and flag athletes. Results: There were 186,239 head impacts recorded during the study. Tackle football athletes sustained 14.67 (95% CI 9.75-21.95) times more head impacts during an athletic exposure (game or practice) compared with flag football athletes. Magnitude of impact for the 50th and 95th percentile was 18.15 g (17.95-18.34) and 52.55 g (51.06-54.09) for a tackle football athlete and 16.84 g (15.57-18.21) and 33.51 g (28.23-39.08) for a flag football athlete, respectively. A tackle football athlete sustained 23.00 (13.59-39.55) times more high-magnitude impacts (≥40 g) per athletic exposure compared with a flag football athlete. Conclusion: This study demonstrates that youth athletes who play tackle football are more likely to experience a greater number of head impacts and are at a markedly increased risk for high-magnitude impacts compared with flag football athletes. Clinical Relevance: These results suggest that flag football has fewer head impact exposures, which potentially minimizes concussion risk, making it a safer alternative for 6- to 14-year-old youth football athletes.

BACKGROUND The Health Resources and Services Administration's Ryan White HIV/AIDS Program provides services to more than half of all people diagnosed with HIV in the United States. We present and validate a mathematical model that can be used to estimate the long-term public health and cost impact of the federal program. METHODS We developed a stochastic, agent-based model that reflects the current HIV epidemic in the United States. The model simulates everyone's progression along the HIV care continuum, using 2 network-based mechanisms for HIV transmission: injection drug use and sexual contact. To test the validity of the model, we calculated HIV incidence, mortality, life expectancy, and lifetime care costs and compared the results with external benchmarks. RESULTS The estimated HIV incidence rate for men who have sex with men (502 per 100,000 person years), mortality rate of all people diagnosed with HIV (1663 per 100,000 person years), average life expectancy for individuals with low CD4 counts not on antiretroviral therapy (1.52-3.78 years), and lifetime costs ($362,385) all met our validity criterion of within 15% of external benchmarks. CONCLUSIONS The model represents a complex HIV care delivery system rather than a single intervention, which required developing solutions to several challenges, such as calculating need for and receipt of multiple services and estimating their impact on care retention and viral suppression. Our strategies to address these methodological challenges produced a valid model for assessing the cost-effectiveness of the Ryan White HIV/AIDS Program.

Islet function is critical for normal glucose homeostasis. Unlike adult β cells, fetal and neonatal islets are more proliferative and have decreased insulin secretion in response to stimuli. However, the underlying mechanisms governing functional maturity of islets have not been completely elucidated. Pancreatic islets comprise different cell types. The microenvironment of islets and interactions between these cell types are critical for β-cell development and maturation. Thus, the study of intact islets is optimal to identify novel molecular mechanisms controlling islet functional development. Transcriptomes and genome-wide histone landscapes of H3K4me3, H3K27me3, and H3K27Ac from intact islets isolated from 2- and 10-week-old Sprague-Dawley rats were integrated to elucidate genes and pathways modulating islet development, as well as the contribution of epigenetic regulation. A total of 4489 differentially expressed genes were identified; 2289 and 2200 of them were up- and down-regulated in 10-week islets, respectively. Ingenuity Pathway Analysis revealed critical pathways regulating functional maturation of islets, including nutrient sensing, neuronal function, immune function, cell replication, and extracellular matrix. Furthermore, we identified significant changes in enrichment of H3K4me3, H3K27me3, and H3K27Ac marks, which correlated with expression changes of genes critical for islet function. These histone marks were enriched at critical transcription factor-binding motifs, such as Hoxa9, C/EBP-β, Gata1, Foxo1, E2f1, E2f3, and Mafb. In addition, our chromatin immunoprecipitation sequencing data revealed multiple potential bivalent genes whose poised states changed with maturation. Collectively, our current study identified critical novel pathways for mature islet function and suggested a role for histone modifications in regulating islet development and maturation.

Maternal and paternal factors influence offspring development and program its genome for successful postnatal life. Based on the stressors during gestation, the pregnant female prepares the fetus for the outside environment. This preparation is achieved by changing the epigenome of the fetus and is referred to as ‘developmental programming’. For instance, nutritional insufficiency in utero will lead to programming events that prepare the fetus to cope up with nutrient scarcity following birth; however, offspring may not face nutrient scarcity following birth. This discrepancy between predicted and exposed postnatal environments are perceived as ‘stress’ by the offspring and may result in cardiovascular and metabolic disorders. Thus, this developmental programming may be both beneficial as well as harmful depending on the prenatal vs postnatal environment. Over the past three decades, accumulating evidence supports the hypothesis of Developmental Origin of Health and Disease (DOHaD) by the programming of the fetal phenotype without altering the genotype per se. These heritable modifications in gene expression occur through DNA methylation, histone modification and noncoding RNA-associated gene activation or silencing, and all are defined as epigenetic modifications. In the present review, we will summarize the evidence supporting epigenetic regulation as a significant component in DOHaD.

Traumatic brain injury (TBI) is a major health concern in the United States resulting in a substantial number of hospitalizations and in a broad spectrum of symptoms and disabilities. In the clinical setting, neurological responsiveness and structural imaging are used to classify mild, moderate and severe TBI. To evaluate the complex secondary and severity-specific injury response, investigators have relied on pre-clinical rodent models. The controlled cortical impact (CCI) model in mice is a widely used to study TBI. The CCI method has demonstrated consistent intra-laboratory outcomes due to precise control of cortical depth penetration, dwell time and speed of impact. While the CCI method results in control of injury severity, there is no consensus regarding the injury parameters or behavioral and histological endpoints that constitute a mild, moderate or severe TBI in this model. This discrepancy has resulted in considerable variability across laboratories in the outcomes of CCI-induced mild, moderate, and severe TBI. Inconsistent with clinical evaluation, injury severity in the CCI model has predominately relied on the extent of tissue damage. In the present review, we discuss variations in surgical parameters for injury induction as well as the criteria used to determine injury severity. Additionally, we propose guiding principles for the induction and defining of mild, moderate and severe TBI in the craniectomy-dependent experimental mouse CCI model.

The liver acts as a manufacturing unit for the production of fetuin-A, which is essential for various physiological characteristics. Scientific research has shown that a moderate upward push in fetuin-A serum levels is associated with a confirmed non-alcoholic fatty liver disease (NAFLD) diagnosis. Fetuin-A modulation is associated with a number of pathophysiological variables that cause liver problems, including insulin receptor signaling deficiencies, adipocyte dysfunction, hepatic inflammation, fibrosis, triacylglycerol production, macrophage invasion, and TLR4 activation. The focus of the present review is on the various molecular pathways, and genetic relevance of mRNA expression of fetuin-A which is correlated with progression of NAFLD. The other major area of exploration in the present review is based on the new targets for the modulation of fetuin-A, like calorie restriction and novel pharmacological agents, such as rosuvastatin, metformin, and pioglitazone which are successfully implicated in the management of various liver-related complications.

Universities are faced with decisions on how to resume campus activities while mitigating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) risk. To provide guidance for these decisions, we developed an agent-based network model of SARS-CoV-2 transmission to assess the potential impact of strategies to reduce outbreaks. The model incorporates important features related to risk at the University of California San Diego. We found that structural interventions for housing (singles only) and instructional changes (from in-person to hybrid with class size caps) can substantially reduce the basic reproduction number, but masking and social distancing are required to reduce this to at or below 1. Within a risk mitigation scenario, increased frequency of asymptomatic testing from monthly to twice weekly has minimal impact on average outbreak size (1.1–1.9), but substantially reduces the maximum outbreak size and cumulative number of cases. We conclude that an interdependent approach incorporating risk mitigation, viral detection, and public health intervention is required to mitigate risk.

World is facing a critical situation this time. A pandemic declared by World Health Organization; COVID-19 caused by new corona virus. It is an infectious disease caused by a newly discovered virus. Most people infected with the Covid-19 virus will experiences mild to moderate respiratory illness and some cases have caused death. This virus can be spread from person to person. There is no corona virus vaccine yet. Prevention involves frequent hand washing, coughing into the bend of your elbow, staying home, wear face mask and practice social distancing.India is not untouched by this. The character of the rule of a nation is reflected only in times of calamity and disaster. The Corona virus disaster has also told what the character of a person, society and nation can be. Now it is time for tragedy, it will pass definitely. The marks that will remain after the passing of time, they will tell how world dealt with this time. Then perhaps this confusion will break who is the most powerful country in the world.In India, there were different dimensions of government activism and society's sensitivity. The society got involved in discharging its role with the government. Community sets out to show excitement, solidarity, on a call in a time of calamity. &nbsp

A Bayesian approach to conduct network model selection is presented for a general class of network models referred to as the congruence class models (CCMs). CCMs form a broad class that includes as special cases several common network models, such as the Erd\H{o}s-R\'{e}nyi-Gilbert model, stochastic block model and many exponential random graph models. Due to the range of models able to be specified as a CCM, investigators are better able to select a model consistent with generative mechanisms associated with the observed network compared to current approaches. In addition, the approach allows for incorporation of prior information. We utilize the proposed Bayesian network model selection approach for CCMs to investigate several mechanisms that may be responsible for the structure of patient-sharing networks, which are associated with the cost and quality of medical care. We found evidence in support of heterogeneity in sociality but not selective mixing by provider type nor degree., Comment: 12 pages, 2 figures

Background With an annual budget of more than $2 billion, the Health Resources and Services Administration's Ryan White HIV/AIDS Program (RWHAP) is the third largest source of public funding for HIV care and treatment in the United States, yet little analysis has been done to quantify the long-term public health and economic impacts of the federal program. Methods Using an agent-based, stochastic model, we estimated health care costs and outcomes over a 50-year period in the presence of the RWHAP relative to those expected to prevail if the comprehensive and integrated system of medical and support services funded by the RWHAP were not available. We made a conservative assumption that, in the absence of the RWHAP, only uninsured clients would lose access to these medical and support services. Results The model predicts that the proportion of people with HIV who are virally suppressed would be 25.2 percentage points higher in the presence of the RWHAP (82.6 percent versus 57.4 percent without the RWHAP). The number of new HIV infections would be 18 percent (190,197) lower, the number of deaths among people with HIV would be 31 percent (267,886) lower, the number of quality-adjusted life years would be 2.7 percent (5.6 million) higher, and the cumulative health care costs would be 25 percent ($165 billion) higher in the presence of the RWHAP relative to the counterfactual. Based on these results, the RWHAP has an incremental cost-effectiveness ratio of $29,573 per quality-adjusted life year gained compared with the non-RWHAP scenario. Sensitivity analysis indicates that the probability of transmitting HIV via male-to-male sexual contact and the cost of antiretroviral medications have the largest effect on the cost-effectiveness of the program. Conclusions The RWHAP would be considered very cost-effective when using standard guidelines of less than the per capita gross domestic product of the United States. The results suggest that the RWHAP plays a critical and cost-effective role in the United States' public health response to the HIV epidemic.

The Alpha Adrenergic Signaling Pathway is one of the chief regulators of cerebrovascular tone and cerebral blood flow (CBF), mediating its effects in the arteries through alpha1-adrenergic receptors (Alpha1AR). In the ovine middle cerebral artery (MCA), with development from a fetus to an adult, others and we have shown that Alpha1AR play a key role in contractile responses, vascular development, remodeling, and angiogenesis. Importantly, Alpha1AR play a significant role in CBF autoregulation, which is incompletely developed in a premature fetus as compared to a near-term fetus. However, the mechanistic pathways are not completely known. Thus, we tested the hypothesis that as a function of maturation and in response to Alpha1AR stimulation there is a differential gene expression in the ovine MCA. We conducted microarray analysis on transcripts from MCAs of premature fetuses (96-day), near-term fetuses (145-day), newborn lambs, and non-pregnant adult sheep (2-year) following stimulation of Alpha1AR with phenylephrine (a specific agonist). We observed several genes which belonged to pro-inflammatory and vascular development/angiogenesis pathway significantly altered in all of the four age groups. We also observed age-specific changes in gene expression–mediated by Alpha1AR stimulation in the different developmental age groups. These findings imply complex regulatory mechanisms of cerebrovascular development.

Analysis of sexual history data intended to describe sexual networks presents many challenges arising from the fact that most surveys collect information on only a very small fraction of the population of interest. In addition, partners are rarely identified and responses are subject to reporting biases. Typically, each network statistic of interest, such as mean number of sexual partners for men or women, is estimated independently of other network statistics. There is, however, a complex relationship among networks statistics; and knowledge of these relationships can aid in addressing concerns mentioned earlier. We develop a novel method that constrains a posterior predictive distribution of a collection of network statistics in order to leverage the relationships among network statistics in making inference about network properties of interest. The method ensures that inference on network properties is compatible with an actual network. Through extensive simulation studies, we also demonstrate that use of this method can improve estimates in settings where there is uncertainty that arises both from sampling and from systematic reporting bias compared with currently available approaches to estimation. To illustrate the method, we apply it to estimate network statistics using data from the Chicago Health and Social Life Survey. Copyright © 2017 John Wiley & Sons, Ltd.

Background: Out of 3 billion base pairs in human genome only ~2% code for proteins; and out of 180,000 transcripts in human cells, about 20,000 code for protein, remaining 160,000 are non-coding transcripts. Most of these transcripts are more than 200 base pairs and constitute a group of long non-coding RNA (lncRNA). Many of the lncRNA have its own promoter, and are well conserved in mammals. Accumulating evidence indicates that lncRNAs act as molecular switches in cellular differentiation, movement, apoptosis, and in the reprogramming of cell states by altering gene expression patterns. However, the role of this important group of molecules in angiogenesis is not well understood. Angiogenesis is a complex process and depends on precise regulation of gene expression. Conclusion: Dysregulation of transcription during this process may lead to several diseases including various cancers. As angiogenesis is an important process in cancer pathogenesis and treatment, lncRNA may be playing an important role in angiogenesis. In support of this, lncRNA microvascular invasion in hepatocellular carcinoma (MVIH) has been shown to activate angiogenesis. Furthermore, lncRNA-Meg3-knockout mouse showed increased expression of vascular endothelial growth factor pathway genes and increased cortical microvessel density. Overall, there is strong evidence that lncRNA is an important class of regulatory molecule, and a number of studies have demonstrated that these can be targeted to change cellular physiology and functions. In this review, we have attempted to summarize these studies and elucidate the potential of this novel regulatory molecule as a therapeutic target.

Hydrogen sulfide (H 2 S), a byproduct of homocysteine (Hcy) transsulfuration, protects against adverse cardiac remodeling in diabetic cardiomyopathy, hyperhomocysteinemia (HHcy), and other cardiomyopathies. However, the underlying molecular mechanisms are unclear. Pyroptosis is a caspase 1-mediated cell death mechanism that promotes remodeling. It is inhibited by autophagy, a lysosomal degradation process that maintains cellular homeostasis. We hypothesized that H 2 S supplementation inhibits Hcy-induced pyroptosis by increasing autophagy in the heart. We treated CBS +/- mice (a model of HHcy) and WT mice with SG1002 (slow-releasing H 2 S donor) or control diet for 14 weeks and performed deep sequencing of their hearts (LV tissue). Ingenuity Pathway Analysis revealed SG1002 downregulated cardiac hypertrophy genes, plausibly by altering upstream regulators involved in pyroptosis and autophagy (IL-1β and mTOR). Western blot results showed that SG1002 suppresses mTOR in CBS +/- hearts (WT: 2.1±0.83, CBS: 10±2.4, CBS+SG: 3.8±2.3, WT+SG: 0.96±0.39) to induce autophagy. SG1002 decreases IL-1β (WT: 0.61±0.08, CBS: 0.88±0.07, CBS+SG: 0.32±0.01, WT+SG: 0.38±0.03) and inhibits caspase-1 activity to suppress Hcy-induced pyroptosis. NF-kB p65, which activates pyroptosis, is also downregulated by SG1002. We conclude that H 2 S could alleviate cardiac remodeling by inducing autophagy and inhibiting NF-kB-mediated pyroptosis. This is the first report that H 2 S controls cross-talk of cardiac pyroptosis and autophagy.