Yale Journal of Biology and Medicine最新文献

Chronic obstructive pulmonary disease (COPD) is a significant respiratory disease and is globally ranked as the third leading cause of death. In Canada, the direct healthcare costs associated with COPD are estimated to be $1.5 billion annually. This study utilized quantitative analyses to examine the impact of specific dimensions of social support, namely, guidance, reliable alliance, reassurance of worth, attachment, and social integration within a clinically identified population of individuals with COPD who exhibit symptoms of depression and anxiety. The study was based on the Social Provisions Theory and stress-buffering hypothesis, utilizing large-scale population data from Statistics Canada's 2012 Canadian Community Health Survey (CCHS) Mental Health component. On a national scale, individuals were more likely to report a decreased sense of belonging to a group of friends (social integration) and struggle to depend on others in stressful times (reliable alliance) while experiencing symptoms of anxiety and depression. These findings underscore the potential benefits of integrating peer support, socialization initiatives, and caregiver training into clinical programs designed for individuals with COPD.

Background: Chronic rhinosinusitis (CRS) is an inflammatory condition classified into chronic rhinosinusitis with nasal polyps (CRSwNP) and chronic rhinosinusitis without nasal polyps (CRSsNP). Th cells manage inflammatory cells in CRS. Suppressor of Cytokine Signaling (SOCS) proteins regulate Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway in Th cells by polarizing toward Th1, Th2, and Th17 cells. This study evaluated the levels of SOCS1,3,5 in CRS patients to find associations with Th cells. Methods: In this cross-sectional study, 20 CRSwNP patients, 12 CRSsNP patients, and 12 controls participated. The infiltration of CD4⁺ T cells was determined using immunohistochemistry. The expression of specific transcription factors and SOCS proteins was assessed using real-time PCR. Cytokine levels were evaluated using ELISA. SOCS protein levels were investigated using western blot analysis. Results: The expression of SOCS3 increased in the CRSwNP group compared to CRSsNP and control groups (p <0.001). SOCS3 protein levels increased in the CRSwNP group compared to CRSsNP (p <0.05) and control (p <0.001) groups. Although there was a significant difference in SOCS5 expression between CRSsNP and control groups, SOCS5 protein levels were significantly different between CRSsNP and control (p <0.001) and CRSwNP (p <0.05) groups. Conclusions: Targeted therapies may be suggested for CRS by modulating SOCS3 and SOCS5 proteins that are responsible for polarization of Th cells toward Th2 or Th1 cells, respectively. JAK-STAT pathway targeting, which encompasses numerous cells, can be limited to SOCS proteins to more effectively orchestrate Th cell differentiation.

Aldo-keto reductases (AKRs) are a superfamily of promiscuous enzymes that have been chiseled by evolution to act as catalysts for numerous regulatory pathways in humans. However, they have not lost their promiscuity in the process, essentially making them a double-edged sword. The superfamily is involved in multiple metabolic pathways and are linked to chronic diseases such as cataracts, diabetes, and various cancers. Unlike other detoxifying enzymes such as cytochrome P450s (CYP450s), short-chain dehydrogenases (SDRs), and medium-chain dehydrogenases (MDRs), that participate in essential pathways, AKRs are more widely distributed and have members with interchangeable functions. Moreover, their promiscuity is ubiquitous across all species and participates in the resistance of pathogenic microbes. Moreover, the introduction of synthetic substrates, such as synthetic molecules and processed foods, results in unwanted "toxification" due to enzyme promiscuity, leading to chronic diseases.

Populations identified to be severely affected by COVID-19, such as pregnant patients, require special consideration in vaccine counseling, access, and provider education. Maternal infection with COVID-19 poses a significant risk to the maternal-fetal dyad with known adverse placenta destruction [1-5]. Despite the widespread access and availability of vaccinations, vaccine hesitancy continues to persist and is highly prevalent in pregnant populations [6-9]. Addressing the multitude of social ecological factors surrounding vaccine hesitancy can aid in providing holistic counseling [10]. However, such factors are foremost shaped by maternal concern over possible fetal effects from vaccination. While changes in policy can help foster vaccine access and acceptance, increasing global provider education and incorporation of motivational interviewing skills are the first steps towards increasing maternal acceptance.

Objective: to evaluate the effect of prenatal care (PC) on perinatal outcomes of pregnant women with diabetes mellitus (DM). Methods: systematic review developed according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines and conducted through the population, intervention, control, and outcomes (PICO) strategy. Clinical trials and observational studies were selected, with adult pregnant women, single-fetus pregnancy, diagnosis of DM, or gestational DM and who had received PC and/or nutritional therapy (NT). The search was carried out in PubMed, Scopus, and BIREME databases. The quality of the studies was evaluated using the tools of the National Heart, Lung and Blood Institute-National Institutes of Health (NHLBI-NIH). Results: We identified 5972 records, of which 15 (n=47 420 pregnant women) met the eligibility criteria. The most recurrent outcomes were glycemic control (14 studies; n=9096 participants), hypertensive disorders of pregnancy (2; n=39 282), prematurity (6; n=40 163), large for gestational age newborns (4; n=1556), fetal macrosomia (birth weight >4kg) (6; n=2980) and intensive care unit admission (4; n=2022). Conclusions: The findings suggest that PC interferes with the perinatal outcome, being able to reduce the risks of complications associated with this comorbidity through early intervention, especially when the NT is an integral part of this assistance.

The intricate steps of human ocular embryology are impacted by cellular and genetic signaling pathways and a myriad of external elements that can affect pregnancy, such as environmental, metabolic, hormonal factors, medications, and intrauterine infections. This review focuses on presenting some of these factors to recognize the multifactorial nature of ocular development and highlight their clinical significance. This review is based on English-language articles sourced from PubMed, Web of Science, and Google Scholar; keywords searched included "ocular development in pregnancy," "ocular embryology," "maternal nutrition," "ophthalmic change," and "visual system development." While some animal models show the disruption of ocular embryology from these external factors, there are limited post-birth assessments in human studies. Much remains unknown about the precise mechanisms of how these external factors can disrupt normal ocular development in utero, and more significant research is needed to understand the pathophysiology of these disruptive effects further. Findings in this review emphasize the importance of additional research in understanding the dynamic association between factors impacting gestation and neonatal ocular development, particularly in the setting of limited resources.

Background: Adverse outcomes from gestational diabetes mellitus (GDM) in the mother and newborn are well established. Genetic variants may predict GDM and Artificial Intelligence (AI) can potentially assist with improved screening and early identification in lower resource settings. There is limited information on genetic variants associated with GDM in sub-Saharan Africa and the implementation of AI in GDM screening in sub-Saharan Africa is largely unknown. Methods: We reviewed the literature on what is known about genetic predictors of GDM in sub-Saharan African women. We searched PubMed and Google Scholar for single nucleotide polymorphisms (SNPs) involved in GDM predisposition in a sub-Saharan African population. We report on barriers that limit the implementation of AI that could assist with GDM screening and offer possible solutions. Results: In a Black South African cohort, the minor allele of the SNP rs4581569 existing in the PDX1 gene was significantly associated with GDM. We were not able to find any published literature on the implementation of AI to identify women at risk of GDM before second trimester of pregnancy in sub-Saharan Africa. Barriers to successful integration of AI into healthcare systems are broad but solutions exist. Conclusions: More research is needed to identify SNPs associated with GDM in sub-Saharan Africa. The implementation of AI and its applications in the field of healthcare in the sub-Saharan African region is a significant opportunity to positively impact early identification of GDM.

Postpartum psychosis is a mental illness that is often misunderstood and stigmatized and can have a devastating impact on the women affected and their families, particularly when not identified and treated early on. The first-person perspective of experiencing a mental illness such as postpartum psychosis is remarkably powerful and can shed light on some of the hidden or misunderstood aspects of diagnosis, treatment, recovery, and getting support. With this in mind, we have prepared this interview from both an academic and lived experience perspective of postpartum psychosis, for clinicians, academics, mental health professionals, and members of the public.

Pregnancy causes physiological changes that support the growing fetus and get the mother ready for labor and delivery. Some of these modifications affect biochemical levels; they are normally stable, while others could imitate symptoms of illness. It is critical to distinguish between pathology associated with disease and typical physiological changes. This review article focuses on the significant changes that occur throughout a typical pregnancy.

Enhanced health literacy in children has been empirically linked to better health outcomes over the long term; however, few interventions have been shown to improve health literacy. In this context, we investigate whether large language models (LLMs) can serve as a medium to improve health literacy in children. We tested pediatric conditions using 26 different prompts in ChatGPT-3.5, ChatGPT-4, Microsoft Bing, and Google Bard (now known as Google Gemini). The primary outcome measurement was the reading grade level (RGL) of output as assessed by Gunning Fog, Flesch-Kincaid Grade Level, Automated Readability Index, and Coleman-Liau indices. Word counts were also assessed. Across all models, output for basic prompts such as "Explain" and "What is (are)," were at, or exceeded, the tenth-grade RGL. When prompts were specified to explain conditions from the first- to twelfth-grade level, we found that LLMs had varying abilities to tailor responses based on grade level. ChatGPT-3.5 provided responses that ranged from the seventh-grade to college freshmen RGL while ChatGPT-4 outputted responses from the tenth-grade to the college senior RGL. Microsoft Bing provided responses from the ninth- to eleventh-grade RGL while Google Bard provided responses from the seventh- to tenth-grade RGL. LLMs face challenges in crafting outputs below a sixth-grade RGL. However, their capability to modify outputs above this threshold, provides a potential mechanism for adolescents to explore, understand, and engage with information regarding their health conditions, spanning from simple to complex terms. Future studies are needed to verify the accuracy and efficacy of these tools.