Explore the vast range of titles available.

Background Technology is essential for advancing healthcare services by enhancing information availability and access. This is especially relevant to Singapore's rapidly ageing population. However, despite widespread smartphone ownership, usage of health-related applications remains low among older Singaporeans. Therefore, this study sought to investigate and understand key factors influencing older adults’ attitudes towards technology, namely in health, communication, productivity, and entertainment. Methods This cross-sectional study was conducted in Singapore through a self-administered face-to-face questionnaire. Data were collected from 380 adults aged 40 and above regarding attitudes towards different technologies in four domains: health, communication, productivity, and entertainment in July 2023. Participants' responses were then re-coded as having a positive or negative attitude, and chi-square tests were used to analyse across categorical variables. Multivariable logistic regression examined the association between attitude and age groups, adjusting for confounders. Results Overall, respondents exhibited positive attitudes toward health technology (69.5%), communication (94.5%), entertainment (85.8%), and productivity (79.7%). Participants aged 75 and above exhibited lower positive attitudes, although they demonstrated notable positivity toward communication (74.6%) and entertainment (56.7%), as opposed to health (35.8%) and productivity (38.8%). Younger age groups (40–54 years) exhibited higher odds of positive attitude toward health technology (OR 7.69, 95% CI: 2.42–25.5), similarly for those with higher education (OR 6.0, 95% CI: 2.64–14.1) and larger families (OR 4.77, 95% CI: 1.54–17.2) after multivariable adjustment. Notably, positive attitudes toward health technology were consistently lower across all age groups compared to other domains. Within health technology, younger adults were more inclined to use medical services and health apps compared to older adults. Although younger adults utilised technology more for time-saving purposes (53% vs. 18%, P  < 0.001), no age differences were observed for health monitoring (44% vs. 37%, P  = 0.228). Conclusion More older Singaporeans were less positive towards health technology compared to technologies for communication, productivity, and entertainment. Increasing age remains the predominant variable, even after adjusting for confounders. Efforts to improve accessibility, usability, and perceived usefulness of health technologies may help enhance adoption among older adults.

Heavy, bingelike patterns of exposure to ethanol during a portion of the early postnatal period in the rat, a time of rodent brain development corresponding to the human third trimester, has been shown to deplete cerebellar neurons and to produce deficits in cerebellar-dependent tasks. In the current study, we examined the impact of more moderate ethanol exposure, during an extended portion of the rat third trimester equivalent, on cerebellar-dependent learning (eyeblink conditioning) and deep cerebellar nuclei neuron numbers. Neonatal rats received 0, 1, 2, or 3 g/kg/day of ethanol in milk formula via a single intragastric intubation each day across postnatal days 2–11, or were left untreated. Peak BACs for ethanol-exposed rats were 50, 150, and 225 mg/dl, respectively. Rats underwent eyeblink conditioning as young adults (70 days of age) and deep cerebellar nuclei neuron numbers were assessed at 100 days of age. In Experiment 1, all rats showed normal responsiveness to periorbital stimulation prior to conditioning. The 3-g/kg/day group was impaired in eyeblink conditioning and possessed fewer deep cerebellar nuclei neurons. A trend toward impairment was observed in the 2-g/kg/day group. However, the 0-g/kg/day group was also impaired in eyeblink conditioning. In Experiment 2, the unconditioned stimulus pretest phase was eliminated, the 0-g/kg/day group learned normally, and both the 2- and 3-g/kg/day groups were again impaired. These results suggest that more moderate doses of ethanol during the rat third-trimester equivalent can produce long-term effects on the cerebellum.

Several studies have documented periodic and quasi-periodic signals from the time series of dMe flare stars and other stellar sources. Such periodic signals, observed within quiescent phases (i.e., devoid of larger-scale microflare or flare activity), range in period from \\(1-1000\\) seconds and hence have been tentatively linked to ubiquitous \\(p\\)-mode oscillations generated in the convective layers of the star. As such, most interpretations for the observed periodicities have been framed in terms of magneto-hydrodynamic wave behavior. However, we propose that a series of continuous nanoflares, based upon a power-law distribution, can provide a similar periodic signal in the associated time series. Adapting previous statistical analyses of solar nanoflare signals, we find the first statistical evidence for stellar nanoflare signals embedded within the noise envelope of M-type stellar lightcurves. Employing data collected by the Next Generation Transit Survey (NGTS), we find evidence for stellar nanoflare activity demonstrating a flaring power-law index of \\(3.25 \\pm 0.20 \\), alongside a decay timescale of \\(200 \\pm 100\\) s. We also find that synthetic time series, consistent with the observations of dMe flare star lightcurves, are capable of producing quasi-periodic signals in the same frequency range as \\(p\\)-mode signals, despite being purely comprised of impulsive signatures. Phenomena traditionally considered a consequence of wave behaviour may be described by a number of high frequency but discrete nanoflare energy events. This new physical interpretation presents a novel diagnostic capability, by linking observed periodic signals to given nanoflare model conditions.

Large disparities in mortality exist across racial–ethnic groups and by location in the USA, but the extent to which racial–ethnic disparities vary by location, or how these patterns vary by cause of death, is not well understood. We aimed to estimate age-standardised mortality by racial–ethnic group, county, and cause of death and describe the intersection between racial–ethnic and place-based disparities in mortality in the USA, comparing patterns across health conditions. We applied small-area estimation models to death certificate data from the US National Vital Statistics system and population data from the US National Center for Health Statistics to estimate mortality by age, sex, county, and racial–ethnic group annually from 2000 to 2019 for 19 broad causes of death. Race and ethnicity were categorised as non-Latino and non-Hispanic American Indian or Alaska Native (AIAN), non-Latino and non-Hispanic Asian or Pacific Islander (Asian), non-Latino and non-Hispanic Black (Black), Latino or Hispanic (Latino), and non-Latino and non-Hispanic White (White). We adjusted these mortality rates to correct for misreporting of race and ethnicity on death certificates and generated age-standardised results using direct standardisation to the 2010 US census population. From 2000 to 2019, across 3110 US counties, racial–ethnic disparities in age-standardised mortality were noted for all causes of death considered. Mortality was substantially higher in the AIAN population (all-cause mortality 1028·2 [95% uncertainty interval 922·2–1142·3] per 100 000 population in 2019) and Black population (953·5 [947·5–958·8] per 100 000) than in the White population (802·5 [800·3–804·7] per 100 000), but substantially lower in the Asian population (442·3 [429·3–455·0] per 100 000) and Latino population (595·6 [583·7–606·8] per 100 000), and this pattern was found for most causes of death. However, there were exceptions to this pattern, and the exact order among racial–ethnic groups, magnitude of the disparity in both absolute and relative terms, and change over time in this magnitude varied considerably by cause of death. Similarly, substantial geographical variation in mortality was observed for all causes of death, both overall and within each racial–ethnic group. Racial–ethnic disparities observed at the national level reflect widespread disparities at the county level, although the magnitude of these disparities varied widely among counties. Certain patterns of disparity were nearly universal among counties; for example, in 2019, mortality was higher among the AIAN population than the White population in at least 95% of counties for skin and subcutaneous diseases (455 [97·8%] of 465 counties with unmasked estimates) and HIV/AIDS and sexually transmitted infections (458 [98·5%] counties), and mortality was higher among the Black population than the White population in nearly all counties for skin and subcutaneous diseases (1436 [96·6%] of 1486 counties), diabetes and kidney diseases (1473 [99·1%]), maternal and neonatal disorders (1486 [100·0%] counties), and HIV/AIDS and sexually transmitted infections (1486 [100·0%] counties). Disparities in mortality among racial–ethnic groups are ubiquitous, occurring across locations in the USA and for a wide range of health conditions. There is an urgent need to address the shared structural factors driving these widespread disparities. National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research, US National Institutes of Health.

Study reproducibility is essential to corroborate, build on, and learn from the results of scientific research but is notoriously challenging in bioinformatics, which often involves large data sets and complex analytic workflows involving many different tools. Additionally, many biologists are not trained in how to effectively record their bioinformatics analysis steps to ensure reproducibility, so critical information is often missing. Software tools used in bioinformatics can automate provenance tracking of the results they generate, removing most barriers to bioinformatics reproducibility. Here we present an implementation of that idea, Provenance Replay, a tool for generating new executable code from results generated with the QIIME 2 bioinformatics platform, and discuss considerations for bioinformatics developers who wish to implement similar functionality in their software.

BackgroundFalls can lead to severe health loss including death. Past research has shown that falls are an important cause of death and disability worldwide. The Global Burden of Disease Study 2017 (GBD 2017) provides a comprehensive assessment of morbidity and mortality from falls.MethodsEstimates for mortality, years of life lost (YLLs), incidence, prevalence, years lived with disability (YLDs) and disability-adjusted life years (DALYs) were produced for 195 countries and territories from 1990 to 2017 for all ages using the GBD 2017 framework. Distributions of the bodily injury (eg, hip fracture) were estimated using hospital records.ResultsGlobally, the age-standardised incidence of falls was 2238 (1990–2532) per 100 000 in 2017, representing a decline of 3.7% (7.4 to 0.3) from 1990 to 2017. Age-standardised prevalence was 5186 (4622–5849) per 100 000 in 2017, representing a decline of 6.5% (7.6 to 5.4) from 1990 to 2017. Age-standardised mortality rate was 9.2 (8.5–9.8) per 100 000 which equated to 695 771 (644 927–741 720) deaths in 2017. Globally, falls resulted in 16 688 088 (15 101 897–17 636 830) YLLs, 19 252 699 (13 725 429–26 140 433) YLDs and 35 940 787 (30 185 695–42 903 289) DALYs across all ages. The most common injury sustained by fall victims is fracture of patella, tibia or fibula, or ankle. Globally, age-specific YLD rates increased with age.ConclusionsThis study shows that the burden of falls is substantial. Investing in further research, fall prevention strategies and access to care is critical.

Metabolic dysfunction associated steatotic liver disease (MASLD) increases the risk of incident chronic kidney disease (CKD). However, the relative risk of CKD associated with increasing hepatic fibrosis, and consequent mortality risk, remains underexplored in real-world cohorts. In this study, we sought to establish whether hepatic fibrosis is associated with increased CKD risk and explore differences in mortality risk in a cohort of people living with MASLD, contingent on liver fibrosis and CKD status. This was an observational study of people who underwent routine liver function testing in Tayside, Scotland. MASLD was defined as: elevated ALT (>30 U/L) or GGT (>73 U/L); presence of diabetes, and/or hypertension, and/or obesity; weekly alcohol consumption <14 units (112g (+/-8g) alcohol); and negative screen for other aetiologies. Data was collected from digital health records. We used log-binomial models to quantify the risk of CKD among those with and without fibrosis, and Cox regression models to estimate differences in mortality risk dependent on fibrosis and CKD. In our cohort (n = 2,046), 1,448 (70.8%) people had MASLD without fibrosis and 598 (29.2%) with fibrosis; 161 (11.1%) and 117 (19.6%) respectively also had CKD. After excluding individuals with structural, autoimmune, or malignant CKD (n = 22), liver fibrosis (n = 593; 18.9% with CKD) was associated with increased CKD risk (aRR = 1.31, 1.04-1.64, p = 0.021). Increased mortality risk was observed for those with liver fibrosis (aHR = 2.30, 1.49-3.56, p = <0.001) and was higher again among people with both fibrosis and CKD (aHR = 5.07, 3.07-8.39, p = <0.014). Liver fibrosis was an independent risk factor for CKD in this cohort of people living with MASLD. Furthermore, those with MASLD with liver fibrosis had higher risk for mortality and this risk was further elevated among those with co-morbid CKD. Given the increased risk of CKD, and consequent mortality risk, among people living with MASLD fibrosis, renal function screening should be considered within liver health surveillance programmes and guidelines.

Patients with chronic traumatic brain injury (TBI) requiring long-term, permanent care suffer a myriad of clinical symptoms (i.e., impaired cognition, fatigue, and other conditions) that persist for years beyond the acute brain injury. In addition to these comorbid clinical symptoms, chronic TBI patients exhibit altered amino acid and hormonal profiles with distinct cytokine patterns suggesting chronic inflammation. This metabolic link suggests a role of the gut-brain axis in chronic TBI. Thus, we utilized a two-site trial to investigate the role of the gut-brain axis in comorbidities of chronic TBI. The fecal microbiome profile of 22 moderate/severe TBI patients residing in permanent care facilities in Texas and California was compared to 18 healthy age-matched control subjects working within the participating facilities. Each fecal microbiome was characterized by 16S(V4) ribosomal RNA (rRNA) gene sequencing and metagenomic genome sequencing approaches followed by confirmatory full 16S rRNA gene sequencing or focused tuf gene speciation and specific quantitative polymerase chain reaction evaluation of selected genera or species. The average chronic TBI patient fecal microbiome structure was significantly different compared to the control cohort, and these differences persisted after group stratification analysis to identify any unexpected confounders. Notably, the fecal microbiome of the chronic TBI cohort had absent or reduced Prevotella spp. and Bacteroidies spp. Conversely, bacteria in the Ruminococcaceae family were higher in abundance in TBI compared to control profiles. Previously reported hypoaminoacidemia, including significantly reduced levels of l-tryptophan, l-sarcosine, ß-alanine, and alanine, positively correlated with the reduced levels of Prevotella spp. in the TBI cohort samples compared to controls. Although the sequelae of gut-brain axis disruption after TBI is not fully understood, characterizing TBI-related alterations in the fecal microbiome may provide biomarkers and therapeutic targets to address patient morbidity.

Cancer therapy: stop PARP The discovery that BRCA1/2 mutant cells (defective in the homologous recombination pathway of DNA repair) are spectacularly sensitive to inhibition of the enzyme PARP (involved in base excision repair) suggests a new, low toxicity, approach to the treatment of women with breast cancers caused by BRCA mutations. As the PARP inhibitors have no effect on cells with functional homologous recombination, the hope is that the treatment will be specific for breast cancer cells. PARP-inhibiting chemotherapeutics may be able to make use of a ‘synthetic lethal’ effect as an alternative to conventional nonspecific cytotoxic anticancer treatments. BRCA1 and BRCA2 are important for DNA double-strand break repair by homologous recombination 1 , and mutations in these genes predispose to breast and other cancers 2 . Poly(ADP-ribose) polymerase (PARP) is an enzyme involved in base excision repair, a key pathway in the repair of DNA single-strand breaks 3 . We show here that BRCA1 or BRCA2 dysfunction unexpectedly and profoundly sensitizes cells to the inhibition of PARP enzymatic activity, resulting in chromosomal instability, cell cycle arrest and subsequent apoptosis. This seems to be because the inhibition of PARP leads to the persistence of DNA lesions normally repaired by homologous recombination. These results illustrate how different pathways cooperate to repair damage, and suggest that the targeted inhibition of particular DNA repair pathways may allow the design of specific and less toxic therapies for cancer.

Upon stimulation, B cells assume heterogeneous cell fates, with only a fraction differentiating into antibody-secreting cells (ASC). Here we investigate B cell fate programming and heterogeneity during ASC differentiation using T cell-independent models. We find that maximal ASC induction requires at least eight cell divisions in vivo, with BLIMP-1 being required for differentiation at division eight. Single cell RNA-sequencing of activated B cells and construction of differentiation trajectories reveal an early cell fate bifurcation. The ASC-destined branch requires induction of IRF4, MYC-target genes, and oxidative phosphorylation, with the loss of CD62L expression serving as a potential early marker of ASC fate commitment. Meanwhile, the non-ASC branch expresses an inflammatory signature, and maintains B cell fate programming. Finally, ASC can be further subseted based on their differential responses to ER-stress, indicating multiple development branch points. Our data thus define the cell division kinetics of B cell differentiation in vivo, and identify the molecular trajectories of B cell fate and ASC formation. The development of activated B cells into antibody-secreting cells (ASC) is a critical step for humoral immunity. Here the authors show, using adoptive transfers and single cell RNA sequencing, that commitment to ASC occurs soon following B cell activation, and is coordinated by specific transcriptome programs and proliferation kinetics.