IntroductionIncreasing demand for colonoscopy continues to strain healthcare systems worldwide. Colon capsule endoscopy (CCE) offers a minimally invasive alternative, but its adoption is limited by high re-investigation rates. The aim of this study is to develop and evaluate clinical prediction models for selecting faecal immunochemical test (FIT) positive patients most suitable for CCE versus colonoscopy.MethodsWe conducted a secondary analysis of data from CareForColon2015 randomized controlled trial (2020-2022), including individuals aged 50-74 years with a positive FIT. Logistic regression models were developed to predict CCE transit, bowel cleansing, completeness, and colonoscopy indication. Sixty candidate predictors were assessed, including demographics, lifestyle factors, FIT values, medications, perceived stress, and health literacy. Models were validated using repeated random subsampling and evaluated on a 10% hold-out set using the area under the receiver-operating-characteristic curve (AUC), Cohen's K, and accuracy. Decision curve analysis (DCA) was performed to assess clinical utility.ResultsCCE achieved complete transit in 92.1% and acceptable bowel cleansing in 71.3% of participants, with 69.6% of investigations deemed complete. Colonoscopy was indicated in 68.0% of cases, based on broad inclusion criteria, and 55.9%, based on more stringent criteria. Models predicting colonoscopy indication showed moderate performance (AUC 0.69-0.71; accuracy 65-67%; Cohen's K 0.28-0.30). DCA indicated positive net benefit for both models within threshold probabilities of 0.5-0.75, supporting their potential to identify FIT-positive patients unlikely to benefit from immediate colonoscopy.ConclusionsClinical prediction models may assist in post-FIT triage between CCE and colonoscopy. DCA suggests potential to reduce unnecessary colonoscopies by identifying low-risk patients suitable for initial CCE. External validation is needed before clinical implementation.
The scarcity of safe and timely caesarean sections in much of Africa contrasts with SA's paradox of having one of the world's highest rates of caesarean section in the private sector - approaching 80% - yet persistently high maternal and perinatal mortality in rural public hospitals. This article addresses three challenges: (i) inequitable access to safe caesarean sections; (ii) high and rising caesarean section rates without evidence of better outcomes, raising concerns about overservicing, costs and respectful care; and (iii) research and data gaps. Closing these gaps requires action from all stakeholders to ensure equitable, high-quality and life-saving care for all.
Clostridioides difficile infection (CDI) causes the majority of identifiable antibiotic-associated diarrhea. Epidemiological studies have shown that biological human females are more susceptible to CDI than males. In this study, we show that female mice developed more severe CDI than males under all conditions tested. We found time-delayed effects of the female estrus cycle on CDI. Indeed, animals in proestrus at any time during CDI progression developed severe signs 1-2 days later. In contrast, animals that were in the estrus stage were protected. Consistent with the delayed effect of the estrous cycle on CDI, we found that pre-infection levels of the sexual hormone prolactin (PRL), immunoglobulin IgG2b, cytokine IL-1β, cytokine G-CSF, and chemokine KC (CXCL1) were the primary nodes of a complex network that correlated with CDI symptomatology on the day after spore challenge. Similarly, we found that the pre-infection levels of sex hormone progesterone, sex hormone luteinizing hormone (LH), immunoglobulin IgG1, chemokine eotaxin, and chemokine IP-10 (CXCL10) were the primary network nodes that affected CDI severity, but with a 2-day delay. As expected, early post-infection levels of immunoglobulins, cytokines, and chemokines formed a hormone-independent network that concurrently correlated with CDI severity. Interestingly, early post-infection levels of FSH, together with cytokine IL-1β and chemokine KC (CXL1), were the main nodes of a network that affected CDI 2 days later, during the recovery phase of the infection. In summary, we show that murine female sexual hormones affect CDI progression, probably by affecting the immune system both before infection and during disease development.
Large-scale multiancestry genome-wide association studies have identified hundreds of loci associated with type 2 diabetes (T2D) and glycemic traits, yet imputed genotyping arrays limit the detection of low-frequency and rare variants. Whole-genome sequencing (WGS) offers a more complete view of genetic variation, especially across diverse populations. We analyzed high-coverage (38×) WGS data from 21,913 T2D case subjects, 61,036 control subjects, and up to 50,011 individuals with no diabetes with fasting glucose, fasting insulin, and HbA1c from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine Program. We performed single-variant association testing, conditional analysis, fine-mapping, and Bayesian colocalization to identify genetic signals and assess regulatory relevance in diabetes-related tissues. We identified 76 distinct association signals across 34 loci, including novel variants at DUSP9 for T2D, and ROBO1, NDN, and MYT1 for HbA1c. Fine-mapping narrowed credible sets and improved causal variant resolution. Colocalization highlighted 80 expression signals in diabetes-related tissues, linking genetic associations to functional regulatory mechanisms. Our findings demonstrate the utility of WGS to uncover novel variants in diverse populations, enhance locus resolution, and link regulatory variation to disease-relevant tissues. This work refines the genetic architecture of T2D and glycemic traits and supports precision medicine efforts targeting diverse populations. We aimed to improve understanding of the genetic architecture of type 2 diabetes and glycemic traits by leveraging whole-genome sequencing in diverse populations. Our goal was to identify novel variants, refine known loci, and link genetic signals to regulatory mechanisms through colocalization with expression quantitative trait loci. We discovered novel variants, significantly improved fine-mapping resolution, and identified 80 regulatory colocalization signals in diabetes-relevant tissues. These findings support precision medicine approaches by connecting genetic variation to functional biology in type 2 diabetes.
To explore parent/caregivers' perceptions of procedures in which their child was held still and the reported impact of these experiences on both the child and parent. Qualitative descriptive study using an online survey. Three research teams (United Kingdom (UK), New Zealand (NZ), and Australia) administered a qualitative survey to parents/caregivers of a child who had been held for a procedure in the last 2 years. Data were analysed using inductive thematic analysis. One hundred and twenty parents and three caregivers described 215 clinical procedures during which their child had been held. Four themes, conceptualised as procedural journeys, captured how parents described experiences unfolding over time: (1) Unravelling restraint, (2) Inevitable restraint led by professionals, (3) Inevitable restraint led by parents/caregivers, and (4) Child-centred holding. Parent/caregivers'accounts highlighted how procedures characterised by limited planning, rapid escalation, reduced responsiveness to child distress and restraint were experienced as particularly challenging and linked to feelings of guilt, regret and trauma. Procedures involving preparation, communication, flexibility and supportive comfort holds were described more positively and as less traumatic. The use of restraint was described as distressing for both the child and the parent/caregiver, particularly when procedures unfolded without adequate planning. Approaches that prioritised preparation and collaboration were perceived to support more positive experiences. There is a need to move away from default or reactive restraint practices towards more deliberate, rights-based, trauma-informed procedural care. The Consolidated Criteria for Reporting Qualitative Research (COREQ) were utilised when reporting findings. To ensure that study materials and survey questions were clear and relevant, consultation occurred with two parents in the UK and three parents in NZ. The study design and questions were also presented to the New Zealand Mātauranga Māori Committee for feedback to ensure cultural appropriateness.
Energy expenditure (EE) is the dynamic physiological process that balances energy intake to maintain body weight and body temperature. Environmental changes induce EE adaptations that limit fluctuations in body weight or body temperature by balancing between body temperature defense and energy conservation. The central nervous system (CNS) orchestrates these adaptations by integrating multiple external and internal cues to coordinate thermogenesis together with other behavioral and metabolic processes. Key hypothalamic and brainstem nuclei form a distributed network that modulates autonomic output to peripheral organs, including sympathetic tone to brown and white adipose tissues. Here, we review known neural circuits and neurotransmitter systems, their integration with sensory pathways and functionally opposing output discrepancies that reveal knowledge gaps how the CNS switches between body temperature defense and energy preservation.
The Latarjet procedure is widely used for anterior shoulder instability with glenoid bone loss, yet its influence on glenohumeral joint (GHJ) kinematics during functional movement remains unclear. This study evaluated GHJ kinematics during active external rotation compared with the contralateral shoulder preoperatively and at 1- and 2-year follow-up using dynamic radiostereometry (RSA) and CT-derived 3D bone models registered to the radiographs. Patient-reported outcomes were assessed using the Western Ontario Shoulder Instability Index (WOSI). Preoperatively, the injured shoulder showed a tendency toward a more anterior (up to 1.5 mm, CI -0.3-3.3) and inferior (up to 1.1 mm, CI -0.3-2.5) humeral head position. At 1 year postoperatively, the humeral head was more posterior (up to 1.8 mm, CI 0.8-2.9) and superior (4.0 mm, CI -4.1-12.1) compared with preoperatively, with an additional posterior shift at 2 years (1.5 mm, CI 0.4-2.6). Postoperative kinematics did not differ from the healthy shoulder. Contact area decreased preoperatively by up to 121.7 mm2 (CI 57.1-186.3) and increased by up to 110.8 mm2 (CI 42.3-179.3) at 2 years. WOSI improved from 55% (CI 49-61) preoperatively to 36% (CI 25-48) at 1 year and 27% (CI 17-36) at 2 years. The Latarjet procedure resulted in GHJ kinematics comparable to the healthy shoulder during external rotation. Postoperatively, kinematics shifted posteriorly and superiorly with improved WOSI scores over 2 years. Clinical Significance: Near-normal GHJ kinematics during external rotation are achieved within 2 years, supporting improved shoulder function in anterior instability following the Latarjet procedure.
Oral squamous cell carcinoma (OSCC) is the most common head and neck cancer and is associated with high recurrence and poor prognosis. This study investigated the effects of Sweet Apple e-cigarette vapor extract (Apple EVE), with and without nicotine, on mTOR pathway activation in OSCC cell lines Ca9-22 and Cal 27. Cells were exposed for 6 hours to 10% Apple EVE generated from "Reds Apple Juice" in the presence or absence of nicotine (6 mg), with untreated cells as controls. Phosphorylation levels of mTOR pathway components (p-mTOR, p-p70S6K, p-4EBP1, and p-AKT) were assessed by Western blot and quantified by densitometry normalized to β-actin. Cell invasion was evaluated using a Matrigel-coated real-time xCELLigence assay. Data were analyzed using the Mann-Whitney U test (p < 0.05). Nicotine-containing Apple EVE significantly increased p-mTOR in both cell lines. In Ca9-22 cells, it decreased p-p70S6K and p-4EBP1, whereas in Cal 27 cells it increased p-AKT. Apple EVE without nicotine induced more modest and variable effects. No significant changes in cell invasion were observed in either cell line. Apple EVE, particularly when combined with nicotine, differentially modulates mTOR signaling in a cell line-specific manner in OSCC cells. These findings highlight the complex effects of flavored e-cigarette aerosols on cancer-related pathways and warrant further investigation into the functional consequences of these early signaling changes.
Sleep disturbance is a well-established risk factor for suicide, though few studies to date have examined whether sleep disturbance contributes to suicide risk among individuals at clinical high risk for psychosis (CHR). The current study addressed this gap in the literature. We hypothesized that sleep disturbance would have a unique relationship with suicidal ideation/attempts when accounting for other variables in the model. We also hypothesized that the interaction between sleep disturbance/attenuated positive symptoms and sleep disturbance/stress would be related to suicidal ideation/attempts in CHR. The current study used data generated by the Accelerating Medicines Partnership® Schizophrenia Observational Study. The total sample included 1,048 participants (827 CHR and 221 community controls). Participants completed measures of suicidal ideation/attempts, attenuated positive symptoms, depressive symptoms, perceived stress, and sleep disturbance. Results supported a relationship between sleep disturbance and suicidal ideation/attempts in CHR, with participants who had lifetime ideation and attempts experiencing more sleep disturbance than those with no ideation or attempts. We also found small, but significant positive correlations between sleep disturbance and suicide risk in CHR. When accounting for other variables in the model, the effect of sleep disturbance remained significant for past month ideation, but not lifetime ideation or attempts. Both interaction models were non-significant. Our findings highlight the potential value of sleep measures in early identification and treatment of suicide risk in CHR. Further research in this area is warranted.
To evaluate the agreement of an artificial intelligence (AI) model with human expert raters in assessing greyscale synovitis, Doppler activity, and osteophytes in hand joints. Ultrasound images of the wrist, metacarpophalangeal, proximal interphalangeal, distal interphalangeal, and interphalangeal joints were collected. Five experienced rheumatologists, all ultrasound instructors, scored images for synovial hypertrophy (SH), Doppler activity, and osteophyte severity on a 0 to 3 scale using established scoring systems. The AI model was trained, validated, and tested on 7314 images, then compared against raters on 1280 images for SH, 840 videos for Doppler, and 351 images for osteophytes. Agreement was calculated as the AI's average agreement with all raters. For SH, the AI vs expert raters showed a kappa value of 0.39 (95% CI, 0.35-0.44), a percent exact agreement (PEA) value of 51.77% (95% CI, 48.83-54.70), and a percent close agreement (PCA) value of 91.03% (95% CI, 89.21-92.63). For Doppler activity, the kappa value was 0.61 (95% CI, 0.54-0.67), the PEA value was 80.49% (95% CI, 77.51-83.22), and the PCA value was 97.13% (95% CI, 95.69-98.18). For osteophyte grading, the kappa value was 0.56 (95% CI, 0.48-0.64), the PEA value was 70.69% (95% CI, 65.57-75.45), and the PCA value was 96.28% (95% CI, 93.70-98.01). Interrater reliability among the human experts showed comparable kappa value ranges: 0.36 to 0.47 for SH, 0.69 to 0.74 for Doppler, and 0.42 to 0.64 for osteophytes. The AI model demonstrated agreement with expert raters comparable with interrater agreement for SH and osteophyte grading, whereas it was slightly lower for Doppler activity. The lower-than-expected human interrater reliability, particularly for SH, may reflect the absence of prereading alignment sessions, which provide a more realistic picture of variability in expert scoring. These findings support the potential of AI-assisted ultrasound interpretation, while underscoring the need for continued model refinement.
Demographic bias in AI-driven clinical decision support systems (CDSS) represents one of the most consequential and least-addressed risks in healthcare AI. Large Language Models (LLMs) applied to emergency triage can silently perpetuate or amplify existing health disparities across thousands of patient decisions. This paper introduces FairGuard, a continuous bias detection and governance framework that embeds demographic fairness auditing directly into the LLM inference pipeline using four integrated mechanisms: (1) an equity-enforcing consent gate that applies demographic-blind access control; (2) a RAG corpus bias analyzer that traces class-directional misclassification to retrieval layer composition; (3) per-subgroup confusion matrix stratification computing ΔF1 across demographic groups; and (4) a blockchain-anchored continuous monitoring layer that enforces a ΔF1 ≤ 0.05 governance threshold across every inference batch. Evaluated on the MIMIC-IV Full Emergency dataset (N=300-1,000), FairGuard achieves a gender ΔF1 of 0.020, well within threshold, while identifying RAG corpus composition as the root cause of conservative triage bias (50.9% Urgent → Non-Urgent misclassification), establishing that the observed bias is class-directional rather than demographically concentrated. FairGuard provides the first continuous, blockchain-enforced fairness governance mechanism for LLM-based emergency triage CDSS.
First, to describe the development of a novel postconcussive symptom (PCS) code set for identifying symptoms via medical records. Second, to apply it to a population-based cohort of service members with a history of mild traumatic brain injury (mTBI) per Military Health System (MHS) records, to identify distinct subgroups based on patterns of risk for specific PCS. MHS. Population-based sample of service members with mTBI who served in the Army, Air Force, Navy, and Marine Corps and received a diagnosis within the MHS (n = 148 293). Retrospective cohort study using medical record data from the MHS spanning 2002 to 2021. In collaboration with clinical experts, we iteratively refined a novel PCS code set comprised of ICD-9/10 codes based on Neurobehavioral Symptom Inventory categories, when possible. We used latent class analysis (LCA) with a split-sample cross-validation procedure to identify subgroups of service members with mTBI based on probability of receiving each PCS diagnosis. The final PCS code set included 20 symptoms, spanning vestibular, sensory, cognitive, and mood/behavioral-related symptoms. The LCA supported 5 distinct subgroups, the most prevalent being the Minimal subgroup (59%), characterized by low probability of all PCS. The next most common class was the Headache class (16%), followed by the Mood-Behavioral (15%), Headache-Sleep (6%), and Headache-Mood-Sleep (5%) classes. Using a novel PCS code set leveraging routinely collected data, we identified 5 clinically meaningful and statistically distinct subgroups based on symptom patterns in a population-based cohort of service members with a history of mTBI. These subgroups provide a nuanced, person-centered understanding of symptoms among those with a history of TBI and can inform targeted interventions and policies aimed at meeting the needs of these service members. Further, findings establish a foundation for investigating risk factors and outcomes across subgroups, informing prognostication.
Evaluate changes in subjective-objective sleep discrepancies among participants with insomnia and a history of moderate-to-severe traumatic brain injury (TBI) following computerized cognitive behavioral therapy for insomnia (cCBT-I). An outpatient setting at a Department of Veterans Affairs medical center. United States veterans between the ages of 18 and 60 years with current insomnia and a history of moderate-to-severe TBI ( N = 36). A secondary analysis of intervention-arm data from a randomized controlled trial. Participants completed an online cCBT-I program called SleepEZ. The program was primarily self-guided, with adjunctive assistance provided by a study clinician. Subjective sleep outcomes were measured using the Consensus Sleep Diary, which were collected nightly throughout the entire intervention. Objective sleep outcomes were measured using wrist-based actigraphy, which were collected during the initial and final weeks of the program. Subjective-objective sleep discrepancies were calculated for total sleep time (TST), sleep onset latency (SOL), waking after sleep onset (WASO), early morning awakening (EMA), and sleep efficiency. Measure agreement was estimated with Bland-Altman plots. Changes in subjective-objective sleep discrepancies were estimated through multilevel modeling. Poor agreement was observed for all 4 sleep outcomes. At baseline, participants overreported SOL and EMA on sleep diaries. However, WASO was greatly underreported, resulting in higher TST values calculated using sleep diaries compared with actigraphy. Following cCBT-I, overreporting of SOL decreased and sleep efficiency discrepancies grew larger, driven by improvements in subjective, but not objective, sleep measures. The concurrent use of subjective and objective measures is recommended to fully capture sleep health when treating insomnia after moderate-to-severe TBI. Further research is needed to elucidate mechanisms contributing to subjective-objective sleep discrepancies-potentially including specific aspects of cognitive impairment, striatal hyperactivity, or sleep pressure homeostasis-which may inform novel targets for post-TBI insomnia treatments among those with more severe injuries.
Physician wellness discussions often center on burnout and negative aspects of clinical practice. Less is known about what brings professional satisfaction to physicians, particularly among emergency medicine (EM) residents. Understanding drivers of professional satisfaction is important for the future of the specialty as they may influence residents' career decisions. This study aimed to identify drivers of professional satisfaction among a national cohort of EM residents. We conducted a mixed methods study using a survey administered following the 2024 ABEM In-Training Examination to EM residents in ACGME-accredited programs. The single-item, free-text survey question asked: "List the top 3 drivers of your professional satisfaction in EM." Responses were linked to resident demographics, year in training, and program length. Using an exploratory, sequential mixed methods design, we developed a codebook via team-based thematic analysis. We subsequently quantified theme prevalence, summarized the top 10 themes, and compared the top 5 themes across strata by demographics and program characteristics. 3914 of 9820 eligible residents (39.9%) responded. Our team identified 41 unique themes from these responses. The top 10 drivers of professional satisfaction by frequency were: (1) EM community/team culture, (2) positive impact on patients, (3) work-life balance, (4) bedside patient interactions, (5) clinical variety, (6) shift work flexibility, (7) financial compensation, (8) opportunities for procedures, (9) EM clinical skill set, and (10) critical care opportunities. The most prevalent themes did not vary by resident demographics. In a national cohort of EM residents, we identified a list of key drivers of professional satisfaction that clustered into a small number of highly prevalent themes. The most important factors were related to the people and culture of the program and making a positive impact on patients. These findings may inform strategies to strengthen EM resident professional fulfillment and support the future of the specialty.
The Harmattan season (approximately December to March) in Western Africa is characterized by dry, dusty trade winds blowing from the Sahara Desert toward the Gulf of Guinea and is associated with marked increases in fine particulate matter and other air pollutants, cooler temperatures, and crop reductions. The season has been linked with several negative health effects, though impacts on pregnancy outcomes are unknown. We leveraged data from the Ghana Randomized Air Pollution and Health Study (GRAPHS) to determine whether prenatal exposure to the Harmattan season impacts newborn size and whether there are critical windows of exposure. GRAPHS enrolled 1,414 pregnant women from Kintampo, Ghana from 2013 to 2015. We employed distributed lag models (DLMs) to examine time-varying associations between prenatal exposure to the Harmattan season (yes/no) for each week of gestation and birth weight, length, and head circumference among infants liveborn ≥ 37 weeks. Analyses included n = 1,261 mother-infant pairs. Harmattan exposure was associated with smaller head circumference across gestation and DLMs identified sensitive windows in weeks 1-11 and 15-34. These effects were only significant among infant males. No impact of Harmattan on birth weight or birth length was identified. Our analyses suggest prenatal exposure to the Harmattan season is associated with negative impacts on newborn size and specifically head circumference; exposure during certain gestational windows appears to have a greater impact than others. Climate change threatens to make Harmattan more severe secondary to increased desertification; we therefore need a better understanding of its health effects during pregnancy.
Additive fitness landscapes-also called Mount Fuji landscapes-are the simplest and most widely used models of sequence-function relationships. As such, they play essential roles across multiple areas of biology, including evolutionary theory, quantitative genetics, gene regulation, and protein science. One of the most basic properties of any fitness landscape is its genotypic density-the number of sequences near a given fitness value. Understanding this density is especially important near fitness peaks, as it quantifies the supply of high-fitness genotypes. Here I study the genotypic density of additive landscapes near fitness peaks. Although this density is well known to be approximately Gaussian near the middle of the fitness range, its behavior near maximal fitness has not been reported. I begin by deriving a saddle-point approximation that accurately describes the genotypic density of additive landscapes over virtually the entire fitness range. I then show that the log of this density follows a power law near maximal fitness, with the exponent determined by how much the best allele at each position outperforms its nearest competitor. This power-law behavior holds over a substantial fraction of fitness values, besting the Gaussian approximation on both simulated and empirical landscapes across roughly a quarter to a third of the fitness range. Under certain conditions this behavior also extends to globally epistatic landscapes (defined as nonlinear functions of one or more additive traits), though with a reduced range of validity. These findings advance our understanding of one of the most fundamental models of sequence-function relationships. In particular, they reveal that the uppermost reaches of Mount Fuji landscapes, rather than being sharply peaked, are actually quite stubby.
China launched ambitious air pollution regulations in 2013 that have resulted in substantial reductions in concentrations of particulate matter with aerodynamic diameters of 2.5 micrometers or less (PM2.5). The main objective of this project is to analyze whether regulations to control PM2.5 have been associated with declining mortality rates, especially in locations where the regulations caused larger reductions in PM2.5 concentrations. In addressing this main objective, we control for ozone (O3) concentrations. In addition, we examine and analyze available PM2.5 components (that is, the subspecies that make up PM2.5) and related air pollutants in secondary analyses that focused on understanding the influence of specific source sectors and emission control policies on PM2.5 trends. We used both observations and model outputs to characterize observed and counterfactual spatiotemporal trends in air quality from 2008 to 2019 across China. We characterized observed PM2.5 and O3 concentrations from 2008 to 2019 across China using published gridded datasets that incorporate observations along with remote sensing and other data to estimate surface concentrations that are spatially and temporally complete. We used the Community Multiscale Air Quality (CMAQ) model to both reproduce observed pollution and to simulate concentrations of PM2.5 and O3 that would have occurred absent regulations from 2008 to 2019. Additional CMAQ scenarios quantified the impacts of a range of source-specific emission control policies on ambient concentrations. In a secondary, supporting analysis, we analyzed observed speciated particulate matter data from three cities using source apportionment methods to infer changes in pollution source influences over time. We analyzed mortality data from two large, representative cohorts maintained by the Chinese Center for Disease Control and Prevention in relation to spatial and temporal variations in PM2.5 and O3 concentrations using two methods. We first analyzed the health data using a traditional Cox proportional hazards model to estimate conventional hazard ratios (HR) for PM2.5 risk. Next, we implemented novel causal methods based on principal stratification to analyze the extent to which regulatory policies implemented starting in 2013 were associated with reduced mortality across China. From 2013 to 2019, we estimate there was a ~45% reduction in PM2.5 as compared to a no-control scenario, but with considerable regional heterogeneity. Associations were observed between PM2.5 and mortality rates in all cohorts, though results were sensitive to model specification in a cohort of elderly subjects. Results of causal models suggested that improvements in PM2.5 since 2013 were associated with increased survival probability in both cohorts. The scope of air pollution regulations and resulting PM2.5 improvements in China since 2013 provided a unique opportunity for accountability research. Our study provides evidence supporting the health benefits of those policies.
Vitamin A is an essential micronutrient with broad physiological roles. The liver is of central importance in whole-body vitamin A homeostasis, with hepatocytes distributing retinol to the rest of the body by secreting it in complex with Retinol-binding protein 4 (RBP4). The goal of this study was to elucidate homeostatic mechanisms regulating hepatic vitamin A metabolism by specifically blocking retinoic acid (RA) signaling in hepatocytes. Herein, we used Albumin-Cre (AlbCre) mice to conditionally express a dominant negative retinoic acid receptor (Rardn) in hepatocytes, generating AlbCre:Rardn mice. These mice experience a functional block in hepatocyte RA signaling, as evidenced by the suppression of Cyp26a1, a gene that is highly responsive to RA and is exclusively expressed in hepatocytes within the liver. Unexpectedly, we observed increased circulating levels of retinol and RBP4 in AlbCre:Rardn mice, accompanied by increased hepatic expression of RBP4 at the gene and protein level. We then compared the effect of blocking RA signaling in AlbCre:Rardn mice with a more physiological depletion of hepatic retinoid content, using a mouse model of diet-induced vitamin A deficiency. Similar to AlbCre:Rardn mice, hepatic RBP4 protein expression was higher in vitamin A deficient mice. However, this was instead accompanied by no transcriptional change in hepatic Rbp4 and reduced retinol-RBP4 in the plasma, indicating an overall reduction in hepatic retinol-RBP4 secretion. Together, these data provide new insight into factors that modulate circulating retinol-RBP4 levels, and how the liver supplies the rest of the body with vitamin A.
General practitioners manage most opioid tapering. This process requires time-consuming, individualised planning accounting for patient preferences, dose options and costs. Consequently, clinicians need tools to support tapering. This review explores existing international digital decision support systems for opioid tapering. We conducted a scoping review following the JBI methodology. Five databases (PubMed, Embase, CINAHL, Cochrane and Web of Science) were searched in January 2026. Title/abstract and full-text screening were performed independently by two reviewers based on predefined eligibility criteria. Disagreements were resolved by a third reviewer. Data were extracted and summarised both descriptively and narratively. The search identified 2340 studies, of which four met the eligibility criteria. The studies included described four different technology-driven decision support tools for opioid tapering. The tools varied in format and clinical context (primary and secondary care), but they all aimed to support clinicians in planning and managing opioid tapering. Evidence on clinical effectiveness and real-world implementation was limited across the studies. Only few studies have investigated technology-driven decision support for opioid tapering, and only one is set within a European context. While tools exist in different formats and clinical settings, evidence on their effectiveness and real-world implementation remains limited, highlighting a need for further development and evaluation. General practitioners manage most opioid tapering, which requires individualised plans based on patient preferences, doses, and costs. To identify digital decision support systems assisting clinicians, we conducted a scoping review in January 2026. After screening 2340 studies across five databases, we identified four relevant studies. These described four distinct technological tools used in primary and secondary care to plan opioid tapering. However, we found limited evidence regarding their clinical effectiveness or real‐world implementation, and only one study was European. While tapering tools exist, researchers must further evaluate their effectiveness and practical use in clinical settings.
Surgical care is critical for addressing universal access to healthcare, but access to safe and timely surgery is limited, especially in poorly resourced settings. To determine the surgical experiences of individuals in a peri-urban community in Cape Town, South Africa. A cross-sectional household survey of individuals in a peri-urban Cape Town community was conducted with door-to door interviews by trained community assistants, who provided multilingual translation of study materials as needed. The study (i) describes the surgical burden of disease and outcomes; (ii) assesses health-seeking behaviour and barriers to care using the Three Delays framework; and (iii) uses descriptive statistics to characterise respondent demographics and surgical experiences and χ2 tests to compare awareness, attitudes and acceptability across genders and locations. Data from 432 valid responses of 450 surveys conducted showed that chronic diseases were common, affecting 240/431 (56%), with a higher prevalence in females than in males (171/285 (60%) v. 63/133 (47%), p<0.05). Most participants (208/432, 44%) lived within 10 km of their nearest healthcare facility, predominantly public facilities (417/432, 97%). The Three Delays framework showed that 87/432 (20%) delayed seeking surgical care, 114/432 (26%) experienced delays reaching facilities and 95/432 (32%) faced delays in receiving appropriate care, while 95/432 (22%) reported no delays. The surgical burden was substantial, with 260/428 (60%) having undergone surgery in their lifetime and 195 surgical procedures performed in the last 5 years. Postoperative disability affected 43/432 (10%) of participants, primarily manifesting as body function impairments (22/43, 51.2%) and activity limitations (7/43, 16.3%). Only 67% understood post-surgical treatment protocols. This study reveals significant challenges in surgical care delivery in this peri-urban community. Key findings include a high chronic disease burden, substantial delays in accessing surgical care and significant postoperative disability rates. These results provide the first comprehensive assessment of surgical experiences in peri-urban Cape Town, highlighting the need for comprehensive interventions targeting chronic disease and surgical care, even in peri-urban areas close to public health facilities.