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Background This study aims to evaluate the relative efficacy and safety of sodium‐glucose cotransporter 2 (SGLT2) inhibitors in patients with Type 2 diabetes mellitus (T2DM) and established cardiovascular disease (CVD) or at risk for CVD. Primary efficacy outcomes were cardiovascular (CV) death and hospitalization for heart failure (HFH); primary safety outcomes were major hypoglycemic events and genital mycotic infections. Methods We performed a targeted literature search on PubMed through December 2023 to identify randomized controlled trials (RCTs) assessing the efficacy and safety of sotagliflozin, empagliflozin, canagliflozin, and dapagliflozin in patients with T2DM and established CVD or at risk for CVD. Subsequently, we used a random‐effects network meta‐analysis for an indirect treatment comparison of 4 relevant RCTs, to estimate the relative hazard ratio ([HR], for efficacy outcomes), odds ratio ([OR], for safety outcomes), and 95% confidence interval (CI). Results This study showed key differences in the efficacy and safety among SGLT2 inhibitors. Dapagliflozin (HR, 1.58; 95% CI, 1.19–2.11) and canagliflozin (HR, 1.40; 95% CI, 1.04–1.89) were associated with a higher rate of CV death compared to empagliflozin. Dapagliflozin and empagliflozin decreased the odds of major hypoglycemic events when compared to sotagliflozin (OR, 0.15; 95% CI, 0.03–0.72) and (OR, 0.21; 95% CI, 0.04–0.95), respectively. Canagliflozin increased the odds of major hypoglycemic events when compared to dapagliflozin (OR, 1.55; 95% CI 1.06–2.27). Patients treated with dapagliflozin were more likely to develop genital mycotic infections than with empagliflozin (OR, 2.37; 95% CI, 1.15–5.06). Conversely, canagliflozin reduced the odds of developing genital mycotic infections compared to empagliflozin (OR, 0.48; 95% CI, 0.23–0.99). Conclusions This study revealed notable differences among SGLT2 inhibitors in the likelihood of CV death, major hypoglycemic events, and genital mycotic infections. It provides evidence of comparable efficacy and safety across several other outcomes. These findings underscore the importance of personalizing therapy based on individual patient risk factors.

BackgroundDiabetes-related multi-morbidity and cultural factors place Latinas with diabetes at increased risk for stress, which can threaten illness management. Families provide an ideal focus for interventions that seek to strengthen interpersonal resources for illness management and, in the process, to reduce stress. The current study sought to examine whether participating in a dyadic intervention was associated with reduced perceived stress and, furthermore, whether this association was mediated by persuasion and pressure, two forms of health-related social control.MethodLatina mothers with diabetes and their at-risk adult daughters participated in either (1) a dyadic intervention that encouraged constructive collaboration to improve health behaviors and reduce stress, or (2) a usual-care minimal control condition. Actor-partner interdependence model analysis was used to estimate the effect of the intervention on dyads’ perceived stress, and mother-daughter ratings of health-related social control as potential mediators.ResultsResults revealed that participating in the intervention was associated with significantly reduced perceived stress for daughters, but not for mothers (β =  − 3.00, p = 0.02; β =  − 0.57, p = 0.67, respectively). Analyses also indicated that the association between the intervention and perceived stress was mediated by persuasion, such that mothers’ who experienced more health-related persuasion exhibited significantly less post-intervention perceived stress (indirect effect =  − 1.52, 95% CI = [− 3.12, − 0.39]). Pressure exerted by others, however, did not evidence a mediating mechanism for either mothers or daughters.ConclusionThese findings buttress existing research suggesting that persuasion, or others’ attempts to increase participants’ healthy behaviors in an uncritical way, may be a driving force in reducing perceived stress levels.

We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thousands of complete mitochondrial genomes. An \"image distance\" is computed for each pair of graphical representations of DNA sequences, and the distances are visualized as a Molecular Distance Map: Each point on the map represents a DNA sequence, and the spatial proximity between any two points reflects the degree of structural similarity between the corresponding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a genomic signature. Consequently, Molecular Distance Maps could inform species identification, taxonomic classifications and, to a certain extent, evolutionary history. The image distance employed, Structural Dissimilarity Index (DSSIM), implicitly compares the occurrences of oligomers of length up to k (herein k = 9) in DNA sequences. We computed DSSIM distances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Dimensional Scaling (MDS) to obtain Molecular Distance Maps that visually display the sequence relatedness in various subsets, at different taxonomic levels. This general-purpose method does not require DNA sequence alignment and can thus be used to compare similar or vastly different DNA sequences, genomic or computer-generated, of the same or different lengths. We illustrate potential uses of this approach by applying it to several taxonomic subsets: phylum Vertebrata, (super)kingdom Protista, classes Amphibia-Insecta-Mammalia, class Amphibia, and order Primates. This analysis of an extensive dataset confirms that the oligomer composition of full mtDNA sequences can be a source of taxonomic information. This method also correctly finds the mtDNA sequences most closely related to that of the anatomically modern human (the Neanderthal, the Denisovan, and the chimp), and that the sequence most different from it in this dataset belongs to a cucumber.

Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically. The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health. We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects. Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types. Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy.

Assistant principals exist in most school contexts and, although instructional leadership has been a frequent topic of educational research, most studies have focused specifically on the role of principals. The present improvement initiative analyzed the instructional leadership capacity of assistant principals and the impact of targeted professional development on assistant principals’ instructional leadership capacity. Assistant principals were asked to participate in a 6-week, all-virtual professional development series emphasizing high-impact instructional strategies based on John Hattie’s (2009) work. Assistant principal participant feedback and survey data were analyzed using a mixed-methods approach. Findings indicated assistant principals view instructional leadership as an important function of their role yet struggle to find time to address the instructional needs associated with that role. Additionally, assistant principals experienced increased confidence and frequency of engagement in instructional leadership activities after participating in professional development focused on actionable learning that can be implemented immediately as part of their professional practice. This study provides guidance for school districts seeking to implement professional development activities, including how school districts can use existing expertise from district leaders to improve the instructional leadership capacity of their assistant principals.

Assistant principals exist in most school contexts and, although instructional leadership has been a frequent topic of educational research, most studies have focused specifically on the role of principals. The present improvement initiative analyzed the instructional leadership capacity of assistant principals and the impact of targeted professional development on assistant principals’ instructional leadership capacity. Assistant principals were asked to participate in a 6-week, all-virtual professional development series emphasizing high-impact instructional strategies based on John Hattie’s (2009) work. Assistant principal participant feedback and survey data were analyzed using a mixed-methods approach. Findings indicated assistant principals view instructional leadership as an important function of their role yet struggle to find time to address the instructional needs associated with that role. Additionally, assistant principals experienced increased confidence and frequency of engagement in instructional leadership activities after participating in professional development focused on actionable learning that can be implemented immediately as part of their professional practice. This study provides guidance for school districts seeking to implement professional development activities, including how school districts can use existing expertise from district leaders to improve the instructional leadership capacity of their assistant principals.

Prolonged heat and sea salt aerosols pose a challenge for the mammalian airway, placing the protective airway surface liquid (ASL) at risk for desiccation. Thus, mammals inhabiting salt marshes might have acquired adaptations for ASL regulation. We studied the airways of the rice rat, a rodent that inhabits salt marshes. We discovered negligible Na+ transport through the epithelial sodium channel (ENaC). In contrast, carbachol induced a large Cl- secretory current that was blocked by the calcium-activated chloride channel (CaCC) inhibitor CaCCinh-A01. Decreased mRNA expression of α, β and γ ENaC, and increased mRNA expression of the CaCC transmembrane member 16A distinguished the rice rat airway. Rice rat airway cultures also secreted fluid in response to carbachol and displayed an exaggerated expansion of the ASL volume when challenged with 3.5% NaCl. These data suggest that the rice rat airway might possess unique ion transport adaptations to facilitate survival in the salt marsh environment.

We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thousands of complete mitochondrial genomes. An \"image distance\" is computed for each pair of graphical representations of DNA sequences, and the distances are visualized as a Molecular Distance Map: Each point on the map represents a DNA sequence, and the spatial proximity between any two points reflects the degree of structural similarity between the corresponding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a genomic signature. Consequently, Molecular Distance Maps could inform species identification, taxonomic classifications and, to a certain extent, evolutionary history. The image distance employed, Structural Dissimilarity Index (DSSIM), implicitly compares the occurrences of oligomers of length up to k (herein k = 9) in DNA sequences. We computed DSSIM distances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Dimensional Scaling (MDS) to obtain Molecular Distance Maps that visually display the sequence relatedness in various subsets, at different taxonomic levels. This general-purpose method does not require DNA sequence alignment and can thus be used to compare similar or vastly different DNA sequences, genomic or computer-generated, of the same or different lengths. We illustrate potential uses of this approach by applying it to several taxonomic subsets: phylum Vertebrata, (super)kingdom Protista, classes Amphibia-Insecta-Mammalia, class Amphibia, and order Primates. This analysis of an extensive dataset confirms that the oligomer composition of full mtDNA sequences can be a source of taxonomic information. This method also correctly finds the mtDNA sequences most closely related to that of the anatomically modern human (the Neanderthal, the Denisovan, and the chimp), and that the sequence most different from it in this dataset belongs to a cucumber.