Bilateral hip septic arthritis caused by nontyphoidal Salmonella group D in a 16-year-old girl with COVID-19 : a case report

Introduction and importance Nontyphoidal Salmonella infection can lead to gastroenteritis, enteric fever, and bacteremia. However, joint infections due to this bacterium are rare, and usually associated with immunosuppressive disorders. Case presentation A 16-year-old girl, with a recent history of acute lymphocytic leukemia (ALL) presented with bacteremia, and bilateral hip pain after COVID-19 symptoms. Clinical presentation, laboratory features and imaging showed bilateral nontyphoidal Salmonella septic arthritis. We administered antibiotics, based on antibiotics susceptibility pattern of the isolated Salmonella. Clinical discussion The case is presented because reports of bilateral hip joint infection due to nontyphoidal Salmonella are rare especially after COVID-19. When the patient presents with joint discomfort, the clinician should think infection especially in immunocompromised hosts. Conclusion It illustrates successful management of septic arthritis requires prompt clinical diagnosis, microorganism identification, administration of appropriate systemic antibiotics and hip joint surgery

Preparation and evaluation of a thermosensitive liposomal hydrogel for sustained delivery of danofloxacin using mesoporous silica nanoparticles

BACKGROUND: Sustained release delivery system can reduce the dosage frequency and maintain the therapeutic level of drugs for a longer time. Biodegradable, biocompatible and thermosensitive chitosan-beta-glycerophosphate (C-GP) solutions can solidify at body temperature and maintain their physical integrity for a longer duration. OBJECTIVES: To develop a novel delivery system based on the integration of liposomes in hydrogel using mesoporous silica nanoparticles (MSNs) for sustained release of danofloxacin in farm animals. METHODS: The MSNs were prepared using N-cetyltrimethylammonium bromide and tetraethylortho silica. The liposomes were prepared by thin film hydration method. C-GP solution containing danofloxacin-loaded MSN liposomes underwent different in-vitro tests, including evaluation of the entrapment efficiency, gelation time, morphology, drug release pattern as well as antimicrobial activities against S. aureus and E. coli. RESULTS: The mean pore size of MSNs was 2.8 nm and the mean MSN entrapment efficiency was 45%. Kinetics of danofloxacin release from liposomal hydrogel followed the Higuchi’s model. This formulation was capable of sustaining the danofloxacin release for more than 96 h. The FTIR studies showed that there were no interactions between danofloxacin and hydrogel excipients. Scanning electron microscopy (SEM) showed that the formed gel had a continuous texture, while the swelled gel in the phosphate buffer had a porous structure. Microbiological tests revealed a high antibacterial activity for lipomosal hydrogel of danofloxacin-loaded MSN comparable with danofloxacin solution. CONCLUSIONS: The liposomal hydrogel solidified at body temperature, effectively sustained the release of danofloxacin and showed in vitro antibacterial effects

SinGAN-Seg: Synthetic Training Data Generation for Medical Image Segmentation

Processing medical data to find abnormalities is a time-consuming and costly task, requiring tremendous efforts from medical experts. Therefore, Ai has become a popular tool for the automatic processing of medical data, acting as a supportive tool for doctors. AI tools highly depend on data for training the models. However, there are several constraints to access to large amounts of medical data to train machine learning algorithms in the medical domain, e.g., due to privacy concerns and the costly, time-consuming medical data annotation process. To address this, in this paper we present a novel synthetic data generation pipeline called SinGAN-Seg to produce synthetic medical data with the corresponding annotated ground truth masks. We show that these synthetic data generation pipelines can be used as an alternative to bypass privacy concerns and as an alternative way to produce artificial segmentation datasets with corresponding ground truth masks to avoid the tedious medical data annotation process. As a proof of concept, we used an open polyp segmentation dataset. By training UNet++ using both the real polyp segmentation dataset and the corresponding synthetic dataset generated from the SinGAN-Seg pipeline, we show that the synthetic data can achieve a very close performance to the real data when the real segmentation datasets are large enough. In addition, we show that synthetic data generated from the SinGAN-Seg pipeline improving the performance of segmentation algorithms when the training dataset is very small. Since our SinGAN-Seg pipeline is applicable for any medical dataset, this pipeline can be used with any other segmentation datasets

Enhancing questioning skills through child avatar chatbot training with feedback

Training child investigative interviewing skills is a specialized task. Those being trained need opportunities to practice their skills in realistic settings and receive immediate feedback. A key step in ensuring the availability of such opportunities is to develop a dynamic, conversational avatar, using artificial intelligence (AI) technology that can provide implicit and explicit feedback to trainees. In the iterative process, use of a chatbot avatar to test the language and conversation model is crucial. The model is fine-tuned with interview data and realistic scenarios. This study used a pre-post training design to assess the learning effects on questioning skills across four child interview sessions that involved training with a child avatar chatbot fine-tuned with interview data and realistic scenarios. Thirty university students from the areas of child welfare, social work, and psychology were divided into two groups; one group received direct feedback (n = 12), whereas the other received no feedback (n = 18). An automatic coding function in the language model identified the question types. Information on question types was provided as feedback in the direct feedback group only. The scenario included a 6-year-old girl being interviewed about alleged physical abuse. After the first interview session (baseline), all participants watched a video lecture on memory, witness psychology, and questioning before they conducted two additional interview sessions and completed a post-experience survey. One week later, they conducted a fourth interview and completed another postexperience survey. All chatbot transcripts were coded for interview quality. The language model’s automatic feedback function was found to be highly reliable in classifying question types, reflecting the substantial agreement among the raters [Cohen’s kappa (κ) = 0.80] in coding open-ended, cued recall, and closed questions. Participants who received direct feedback showed a significantly higher improvement in open-ended questioning than those in the non-feedback group, with a significant increase in the number of open-ended questions used between the baseline and each of the other three chat sessions. This study demonstrates that child avatar chatbot training improves interview quality with regard to recommended questioning, especially when combined with direct feedback on questioning

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Adherence to Iron- Folic- Acid Supplementation and its Related Factors among Pregnant Women in Mazandaraz, Iran in 2022

Introduction: Adhering to the daily intake of folic acid-iron during pregnancy reduces maternal complications such as premature birth, low birth weight and fetal defects. It seems necessary to identify factors related to iron/ folic acid adherence. This study was conducted with aim to determine the adherence to iron- folic acid supplementation and its related factors among pregnant women.Methods: This descriptive-analytical study was conducted in 2022 on 178 pregnant women in Mazandaran province/ Iran. Data were collected via questionnaires (Demographic, self-report adherence, Morisky questionnaire and Iron/ folic acid knowledge). Analysis was done using SPSS software (version 21) and chi-square test and logistic regression analysis. P<0.05 was considered statistically significant.Results: Nearly 70% of pregnant women adhered to iron-folic acid intake. The most observed side effects were gastrointestinal complications, and the most common reason for non-adherence to use was forgetfulness. Age over 30 years old (OR=2.49; p=0.027), prenatal care more than 4 times (OR=2.33; p=0.042), and the absence of drug side effects (OR=2.42; p=0.033) increased the chances of adhering to iron-folic acid. The chance of adhering decreased in working mothers (OR=0.33; p=0.025).Conclusion: In this study, adherence to iron and folic acid intake in pregnant women was high. Regular prenatal care and appropriate consultation will improve adherence to iron/folic acid intake in pregnant women