A fundamental objective of public health is to identify the causes of diseases and associated risk factors to develop effective prevention strategies. In this regard, the population attributable fraction (PAF) has become a key epidemiological measure for quantifying the proportion of disease incidence in a population attributable to specific risk factors.Current Concepts: The concept of PAF is widely applied in epidemiological and public health research, playing a crucial role in prioritizing disease prevention and management strategies. Estimating the PAF of cancer risk factors based on national data provides essential evidence for the formulation of government-led cancer control policies and prevention strategies. In particular, these estimates serve as critical indicators for evaluating cancer control programs and informing policy decisions. Given the variations in risk factor prevalence across different populations, it is crucial to estimate PAF using country-specific data to ensure the development of tailored and effective public health interventions.Discussion and Conclusion: This study underscores the importance of PAF as a foundational tool for evidencebased policymaking and highlights the need for periodic reassessment to enhance the effectiveness of cancer prevention and control efforts.

Single-cell omics technologies have transformed our investigation of genomic, transcriptomic, and proteomic landscapes at the individual cell level. In particular, the application of single-cell RNA sequencing has unveiled the complex transcriptional variations inherent in cardiac cells, offering valuable perspectives into their dynamics. This review focuses on the integration of single-cell omics with induced pluripotent stem cells (iPSCs) in the context of cardiovascular research, offering a unique avenue to deepen our understanding of cardiac biology. By synthesizing insights from various single-cell technologies, we aim to elucidate the molecular intricacies of heart health and diseases. Beyond current methodologies, we explore the potential of emerging paradigms such as single-cell/spatial omics, delving into their capacity to reveal the spatial organization of cellular components within cardiac tissues. Furthermore, we anticipate their transformative role in shaping the future of cardiovascular research. This review aims to contribute to the advancement of knowledge in the field, offering a comprehensive perspective on the synergistic potential of transcriptomic analyses, iPSC applications, and the evolving frontier of spatial omics.

A fundamental objective of public health is to identify the causes of diseases and associated risk factors to develop effective prevention strategies. In this regard, the population attributable fraction (PAF) has become a key epidemiological measure for quantifying the proportion of disease incidence in a population attributable to specific risk factors.Current Concepts: The concept of PAF is widely applied in epidemiological and public health research, playing a crucial role in prioritizing disease prevention and management strategies. Estimating the PAF of cancer risk factors based on national data provides essential evidence for the formulation of government-led cancer control policies and prevention strategies. In particular, these estimates serve as critical indicators for evaluating cancer control programs and informing policy decisions. Given the variations in risk factor prevalence across different populations, it is crucial to estimate PAF using country-specific data to ensure the development of tailored and effective public health interventions.Discussion and Conclusion: This study underscores the importance of PAF as a foundational tool for evidencebased policymaking and highlights the need for periodic reassessment to enhance the effectiveness of cancer prevention and control efforts.

Single-cell omics technologies have transformed our investigation of genomic, transcriptomic, and proteomic landscapes at the individual cell level. In particular, the application of single-cell RNA sequencing has unveiled the complex transcriptional variations inherent in cardiac cells, offering valuable perspectives into their dynamics. This review focuses on the integration of single-cell omics with induced pluripotent stem cells (iPSCs) in the context of cardiovascular research, offering a unique avenue to deepen our understanding of cardiac biology. By synthesizing insights from various single-cell technologies, we aim to elucidate the molecular intricacies of heart health and diseases. Beyond current methodologies, we explore the potential of emerging paradigms such as single-cell/spatial omics, delving into their capacity to reveal the spatial organization of cellular components within cardiac tissues. Furthermore, we anticipate their transformative role in shaping the future of cardiovascular research. This review aims to contribute to the advancement of knowledge in the field, offering a comprehensive perspective on the synergistic potential of transcriptomic analyses, iPSC applications, and the evolving frontier of spatial omics.

A fundamental objective of public health is to identify the causes of diseases and associated risk factors to develop effective prevention strategies. In this regard, the population attributable fraction (PAF) has become a key epidemiological measure for quantifying the proportion of disease incidence in a population attributable to specific risk factors.Current Concepts: The concept of PAF is widely applied in epidemiological and public health research, playing a crucial role in prioritizing disease prevention and management strategies. Estimating the PAF of cancer risk factors based on national data provides essential evidence for the formulation of government-led cancer control policies and prevention strategies. In particular, these estimates serve as critical indicators for evaluating cancer control programs and informing policy decisions. Given the variations in risk factor prevalence across different populations, it is crucial to estimate PAF using country-specific data to ensure the development of tailored and effective public health interventions.Discussion and Conclusion: This study underscores the importance of PAF as a foundational tool for evidencebased policymaking and highlights the need for periodic reassessment to enhance the effectiveness of cancer prevention and control efforts.

Single-cell omics technologies have transformed our investigation of genomic, transcriptomic, and proteomic landscapes at the individual cell level. In particular, the application of single-cell RNA sequencing has unveiled the complex transcriptional variations inherent in cardiac cells, offering valuable perspectives into their dynamics. This review focuses on the integration of single-cell omics with induced pluripotent stem cells (iPSCs) in the context of cardiovascular research, offering a unique avenue to deepen our understanding of cardiac biology. By synthesizing insights from various single-cell technologies, we aim to elucidate the molecular intricacies of heart health and diseases. Beyond current methodologies, we explore the potential of emerging paradigms such as single-cell/spatial omics, delving into their capacity to reveal the spatial organization of cellular components within cardiac tissues. Furthermore, we anticipate their transformative role in shaping the future of cardiovascular research. This review aims to contribute to the advancement of knowledge in the field, offering a comprehensive perspective on the synergistic potential of transcriptomic analyses, iPSC applications, and the evolving frontier of spatial omics.

Objective: This study compared the effects of preperitoneal pelvic packing (PPP) versus resuscitation alone, angioembolization, PPP with pelvic stabilization, resuscitative endovascular balloon occlusion of the aorta (REBOA) with PPP, pelvic stabilization, and REBOA. Methods: A comprehensive search was performed using multiple databases, trial registries, grey literature, and conference proceedings from inception until March 10, 2022. The risk of bias in non-randomized studies of intervention (ROBINS-I) and ROB 2.0 tools were used to assess the risk of bias for non-randomized studies and randomized controlled trials, respectively. The certainty of evidence was rated using the GRADE approach. Results: Twenty-two studies, including 1,762 participants, were retrieved. Based on randomized controlled trials, there was a high uncertainty regarding the effects of PPP versus angioembolization on improving the mortality rate (risk ratio [RR]=0.74; 95% confidence interval [CI] 0.22-2.49; very low certainty of evidence) and improving the hemorrhagic mortality rate (RR=0.19; 95% CI 0.01-3.72; very low certainty of evidence). Based on non-randomized studies, there was a high uncertainty regarding the effects of PPP versus angioembolization on improving the mortality rate (RR=0.76; 95% CI 0.48-1.21; I2=54%; very low certainty of evidence), improving the hemorrhagic mortality rate (RR=0.66; 95% CI 0.18-2.46; I2=75%; very low certainty of evidence), and reducing the post procedural complications (RR=0.76; 95% CI 0.39-1.48; I2=66%; very low certainty of evidence). Conclusion There is high uncertainty regarding the effects of PPP compared to resuscitation only, angioembolization, PPP with pelvic stabilization, REBOA following PPP, pelvic stabilization, and REBOA. (Registration No. CRD42022311628)

Objective: The coronavirus disease-2019 (COVID-19) pandemic’s social isolation has significantly impacted mental health, increasing depression and anxiety. This study explores the effects of social isolation on both humans and mice, focusing on behavioral changes and hippocampal protein expression. It also investigates genetic alterations through single-cell RNA and whole-genome sequencing (WGS). Methods: Here we conducted behavioral studies, protein expression studies, single-nucleus sequencing (snRNAseq), and WGS of the hippocampus of mice that underwent early maternal separation and social isolation, and a demographic study of community populations who had been self-quarantined owing to COVID-19 exposure to investigate the link between somatic mutations and stress due to social isolation. Results: The demographic study demonstrated more negative mental health findings among individuals who live alone or are single. Mice subjected to early maternal separation and social isolation demonstrated increased anxiety-like behaviors and stress-related corticotropin-releasing hormone receptor 1, and neurogenesis-related sex-determining region Y-box 2 and doublecortin expression. In snRNA-seq, differences, such as transthyretin increase, were observed in the maternal separation group, and somatic mutations, including insertion in the intron site of Tmem267, were observed in the social isolation group on WGS. Conclusion The results of this study suggest that stress, such as social isolation, can cause changes at the genetic level, as well as behavioral and brain protein changes.

Background: Papillary renal cell carcinoma (pRCC) is the second most common histological subtype of renal cell carcinoma and is considered a morphologically and molecularly heterogeneous tumor. Accurate classification and assessment of the immunohistochemical features of possible therapeutic targets are needed for precise patient care. We aimed to evaluate immunohistochemical features and possible therapeutic targets of papillary renal neoplasms Methods: We collected 140 papillary renal neoplasms from three different hospitals and conducted immunohistochemical studies on tissue microarray slides. We performed succinate dehydrogenase B, fumarate hydratase, and transcription factor E3 immunohistochemical studies for differential diagnosis and re-classified five cases (3.6%) of papillary renal neoplasms. In addition, we conducted c-MET, p16, c-Myc, Ki-67, p53, and stimulator of interferon genes (STING) immunohistochemical studies to evaluate their pathogenesis and value for therapeutic targets. Results: We found that c-MET expression was more common in pRCC (classic) (p = .021) among papillary renal neoplasms and Ki-67 proliferation index was higher in pRCC (not otherwise specified, NOS) compared to that of pRCC (classic) and papillary neoplasm with reverse polarity (marginal significance, p = .080). Small subsets of cases with p16 block positivity (4.5%) (pRCC [NOS] only) and c-Myc expression (7.1%) (pRCC [classic] only) were found. Also, there were some cases showing STING expression and those cases were associated with increased Ki-67 proliferation index (marginal significance, p = .063). Conclusions Our findings suggested that there are subsets of pRCC with c-MET, p16, c-MYC, and STING expression and those cases could be potential candidates for targeted therapy.

Objective: The coronavirus disease-2019 (COVID-19) pandemic’s social isolation has significantly impacted mental health, increasing depression and anxiety. This study explores the effects of social isolation on both humans and mice, focusing on behavioral changes and hippocampal protein expression. It also investigates genetic alterations through single-cell RNA and whole-genome sequencing (WGS). Methods: Here we conducted behavioral studies, protein expression studies, single-nucleus sequencing (snRNAseq), and WGS of the hippocampus of mice that underwent early maternal separation and social isolation, and a demographic study of community populations who had been self-quarantined owing to COVID-19 exposure to investigate the link between somatic mutations and stress due to social isolation. Results: The demographic study demonstrated more negative mental health findings among individuals who live alone or are single. Mice subjected to early maternal separation and social isolation demonstrated increased anxiety-like behaviors and stress-related corticotropin-releasing hormone receptor 1, and neurogenesis-related sex-determining region Y-box 2 and doublecortin expression. In snRNA-seq, differences, such as transthyretin increase, were observed in the maternal separation group, and somatic mutations, including insertion in the intron site of Tmem267, were observed in the social isolation group on WGS. Conclusion The results of this study suggest that stress, such as social isolation, can cause changes at the genetic level, as well as behavioral and brain protein changes.