Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Troodontid (Theropoda: Troodontidae) from the Lower Cretaceous Yixian Formation of Western Liaoning, China

Abstract A specimen collected from the Lower Cretaceous Yixian Formation of western Liaoning, China, represents a new genus and species of troodontid theropod. The new taxon is named and described on the basis of the holotype and the only known specimen, which comprises an articulated skeleton with the presacral vertebral, shoulder girdle and forelimbs missing as preserved. Diagnostic features of the new species include nasals that are sinusoid in lateral view, absence of a passage connecting the antorbital and maxillary fenestrae, relatively large teeth, plate‐like chevrons forming a band along most of the length of the tail, and a long neck between the femoral head and shaft. The temporal constraints of the three paravian groups (Troodontidae, Dromaeosauridae and Aves) combined with the character distributions among the earliest known troodontids indicate a rapid evolution at the base of the Troodontidae.
Achromatopsia—Visual Cortex Stability and Plasticity in the Absence of Functional Cones

Purpose Achromatopsia is a rare inherited disorder rendering retinal cone photoreceptors nonfunctional. As a consequence, the sizable foveal representation in the visual cortex is congenitally deprived of visual input, which prompts a fundamental question: is the cortical representation of the central visual field in patients with achromatopsia remapped to take up processing of paracentral inputs? Such remapping might interfere with gene therapeutic treatments aimed at restoring cone function. Methods We conducted a multicenter study to explore the nature and plasticity of vision in the absence of functional cones in a cohort of 17 individuals affected by autosomal recessive achromatopsia and confirmed biallelic disease-causing CNGA3 or CNGB3 mutations. Specifically, we tested the hypothesis of foveal remapping in human achromatopsia. For this purpose, we applied two independent functional magnetic resonance imaging (fMRI)–based mapping approaches, i.e. conventional phase-encoded eccentricity and population receptive field mapping, to separate data sets. Results Both fMRI approaches produced the same result in the group comparison of achromatopsia versus healthy controls: sizable remapping of the representation of the central visual field in the primary visual cortex was not apparent. Conclusions Remapping of the cortical representation of the central visual field is not a general feature in achromatopsia. It is concluded that plasticity of the human primary visual cortex is less pronounced than previously assumed. A pretherapeutic imaging workup is proposed to optimize interventions.
Caffeine, CYP1A2 Genotype, and Exercise Performance: A Systematic Review and Meta-analysis

ABSTRACT Purpose This study aimed to summarize and meta-analyze existing evidence regarding the influence of CYP1A2 genotypes on the acute effects of caffeine for exercise performance and to investigate the interaction between genotype, dosage, and timing of caffeine supplementation. Methods Six databases were searched for studies determining the effect of caffeine (except mouth rinsing) on exercise performance between CYP1A2 genotypes. Three-level meta-analyses were performed using standardized mean differences (SMD; Hedge’s g) to determine the effect of caffeine on exercise outcomes within and between CYP1A2 genotypes (AA, AC, and CC). Meta-regressions were performed for dose, timing, and presence of reported conflict of interests (RCOI). A meta-analysis was also performed with placebo values to assess for imbalances between genotypes. Results Thirteen studies, totaling 119 outcomes and 440 participants, were included (233 AA, 175 AC, ad 34 CC). Caffeine improved performance for AA (SMD = 0.30, 95% confidence interval [CI] = 0.21–0.39, P < 0.0001) and AC (SMD = 0.16, 95% CI = 0.06–0.25, P = 0.022) but worsened performance for CC (SMD = −0.22, 95% CI = −0.44 to −0.01, P < 0.0001). Dose affected only CC, with greater doses generating more positive SMD (CC–dose estimate: +0.19/1 mg·kg−1 body mass, 95% CI = 0.04–0.33, P = 0.01). Timing influenced only CC, with better performance with later onset of exercise after supplementation (CC–timing estimate: +0.01/min, 95% CI = 0.00–0.02, P = 0.02). RCOI only affected SMD of CC (CC–RCOI estimate: −0.57, 95% CI = −1.02 to −0.12, P = 0.01). After excluding studies with RCOI, no influence of genotype was seen (all P ≥ 0.19). Small, nonsignificant differences were seen in placebo between genotypes (SMD AA vs CC: −0.13; AA vs AC: −0.12; AC vs CC: −0.05; all P ≥ 0.26). Conclusions Caffeine improved performance for AA and AC but worsened performance for CC. Dose and timing moderated the efficacy of caffeine for CC only. Caution is advised because baseline differences and studies with RCOI could have influenced these results.
Surface textures of first cycle quartz sand grains

ABSTRACT Despite the publication of numerous papers on surface textures of quartz sand grains from different environments, only one paper has reported examining sand grains from a first cycle sand. Montara Beach, California is thought to contain first cycle sand grains derived from the adjacent granitic rocks of Montara Mountain. Sand grains were collected, prepared, and viewed with the Scanning Electron Microscope. Forty-five to 50 grains were examined and many photomicrographs taken of surface textures. These textures were compared to those reported as being diagnostic of high energy beach environments. Textures of grains from Montara Beach are indeed similar to those from other high energy beaches. This confirms that surface features described as Being diagnostic of beach environments are, n fact, produced on the beach.
Drug-Induced Hypoglycemia in Neonates Born to Nondiabetic Women Treated with Medications during the Pregnancy or the Labor: A Systematic Review of the Literature

Abstract The prompt identification of at-risk newborns for drug-induced hypoglycemia can minimize the risk for adverse side effects, inappropriate investigations, and considerable unnecessary costs. Existing literature discusses drug-induced hypoglycemia, but a systematic description of neonatal hypoglycemia induced or exacerbated by maternal medications is missing. We reviewed the association between neonatal hypoglycemia and maternal medications. We systematically searched the literature according to the PICOS model on drug-induced hypoglycemia in neonates born to nondiabetic women treated with medications during the pregnancy or the labor. The main outcomes of the review were: (1) prevalence of hypoglycemia, (2) risk factors and potential confounders, (3) time at onset and severity of hypoglycemia, (4) dose–response gradient, (5) metabolic features of hypoglycemia, (6) modalities to treat hypoglycemia, and (7) quality of the studies. We included 69 studies in this review and we identified 11 groups of maternal drugs related to neonatal hypoglycemia. Results were classified for each outcome. Our review aims at supporting clinicians in the identification of the newborn at risk for hypoglycemia and in the differential diagnosis of neonatal hypoglycemia. Further studies are necessary to assess the risk of neonatal hypoglycemia associated with common maternal medications. Key Points A systematic description of neonatal hypoglycemia induced or exacerbated by maternal medications is missing. In our review we identified 11 groups of maternal drugs related to neonatal hypoglycemia. Our review aims at supporting clinicians in the identification of the newborn at risk for hypoglycemia.
Forecasting regional-level COVID-19 hospitalisation in England as an ordinal variable using the machine learning method

Background COVID-19 causes substantial pressure on healthcare, with many healthcare systems now needing to prepare for and mitigate the consequences of surges in demand caused by multiple overlapping waves of infections. Therefore, public health agencies and health system managers also now benefit from short-term forecasts for respiratory infections that allow them to manage services better. However, the availability of easily implemented effective tools for generating precise forecasts at the individual regional level still needs to be improved. Methods We extended prior work on influenza to forecast regional COVID-19 hospitalisations in England for the period from 19th March 2020 to 31st December 2022, treating the number of hospital admissions in each region as an ordinal variable. We further developed the XGBoost model used previously to forecast influenza to enable it to exploit the ordering information in ordinal hospital admission levels. We incorporated different types of data as predictors: epidemiological data including weekly region COVID-19 cases and hospital admissions, weather conditions and mobility data for multiple categories of locations (e.g., parks, workplaces, etc). The impact of different discretisation methods and the number of ordinal levels was also considered. Results We find that the inclusion of weather data consistently increases the accuracy of our forecasts compared with models that rely only on the intrinsic epidemiological data, but only by a small amount. Mobility data brings about a more substantial increase in our forecasts. When both weather and mobility data are used in addition to the epidemiological data, the results are very similar to the model with only epidemiological data and mobility data. Conclusion Accurate ordinal forecasts of COVID-19 hospitalisations can be obtained using XGBoost and mobility data. While uniform ordinal levels show higher apparent accuracy, we recommend N-tile ordinal levels which contain far richer information.
Addressing Label Noise for Electronic Health Records: Insights from Computer Vision for Tabular Data

The analysis of extensive electronic health records (EHR) datasets often calls for automated solutions, with machine learning (ML) techniques, including deep learning (DL), taking a lead role. One common task involves categorizing EHR data into predefined groups. However, the vulnerability of EHRs to noise and errors stemming from data collection processes, as well as potential human labeling errors, poses a significant risk. This risk is particularly prominent during the training of DL models, where the possibility of overfitting to noisy labels can have serious repercussions in healthcare. Despite the well-documented existence of label noise in EHR data, few studies have tackled this challenge within the EHR domain. Our work addresses this gap by adapting computer vision (CV) algorithms to mitigate the impact of label noise in DL models trained on EHR data. Notably, it remains uncertain whether CV methods, when applied to the EHR domain, will prove effective, given the substantial divergence between the two domains. We present empirical evidence demonstrating that these methods, whether used individually or in combination, can substantially enhance model performance when applied to EHR data, especially in the presence of noisy/incorrect labels. We validate our methods and underscore their practical utility in real-world EHR data, specifically in the context of COVID-19 diagnosis. Our study highlights the effectiveness of CV methods in the EHR domain, making a valuable contribution to the advancement of healthcare analytics and research.
Multiple imputation assuming missing at random: auxiliary imputation variables that only predict missingness can increase bias due to data missing not at random

Epidemiological studies often have missing data, which are commonly handled by multiple imputation (MI). MI is valid (given correctly-specified models) if data are missing at random, conditional on the observed data, but not (unless additional information is available) if data are missing not at random (MNAR). In this paper we explore a previously-suggested strategy, namely, including an auxiliary variable predictive of missingness but not the missing data in the imputation model, when data are MNAR. We quantify, algebraically and by simulation, the magnitude of additional bias of the MI estimator, over and above any bias due to data MNAR, from including such an auxiliary variable. We demonstrate that where missingness is caused by the outcome, additional bias can be substantial when the outcome is partially observed. Furthermore, if missingness is caused by the outcome and the exposure, additional bias can be even larger, when either the outcome or exposure is partially observed. When using MI, it is important to identify, through a combination of data exploration and considering plausible casual diagrams and missingness mechanisms, the auxiliary variables most predictive of the missing data (in addition to all variables required for the analysis model and/or to minimise bias due to MNAR).
A Cross Sectional Survey of Community Awareness about Typhoid and its Major Vector Cockroach in Southern Punjab, Pakistan

Cockroaches live in close proximity to human beings. Due to filthy breeding sites i.e. sewer systems they carry up to 40 pathogenic bacteria. Typhoid is a notorious disease known to be transmitted by cockroaches worldwide. Human thought, perception and behavior vary according to the traditions, vicinity and knowledge. This study was carried out to understand the awareness of community about typhoid and its vector and the way they manage them. For this purpose a questionnaire was developed and data regarding typhoid and its vector were collected from 500 people belonging to 5 localities i.e. Multan, Shujabad, Muzaffargarh, KotAddu and Dera Ghazi Khan of southern Punjab. Results revealed that 44.6% of peoples were affected by typhoid at least once in their life. For season of prevalence, 57.0% of persons said that typhoid problem is more during summer season as compared to other seasons. In southern Punjab 92.2% interviewed persons said that cockroaches create more problem in houses and 84.2% of persons said that annoyance of cockroaches occur in night time but data regarding about insect vector or responsible insect of typhoid only 20.2% person have information that cockroaches spread the typhoid. Present survey in Southern Punjab showed that cockroaches create most problems in food commodities and person need to control it properly and very little person identify the insect vector of typhoid. This survey highlights the Southern Punjab people practices in control of cockroaches.
Application of RothC model to predict soil organic carbon stock on agricultural soils of Slovakia.

Soil organic matter (S om) takes part in many environmental functions and, depending on the conditions, it can be a source or a sink of the greenhouse gases. Presently, the changes in soil organic carbon (S oC) stock can arise because of the climatic changes or changes in the land use and land management. A promising method in the estimation of SoC changes is modelling, one of the most used models for the prediction of changes in soil organic carbon stock on agricultural land being the r othC model. Because of its simplicity and availability of the input data, r othC was used for testing the efficiency to predict the development of S oC stock during 35-year period on agri - cultural land of Slovakia. The received data show an increase of S oC stock during the first (20 years) phase and no significant changes in the course of the second part of modelling. The increase of S oC stock in the first phase can be explained by a high carbon input of plant residues and manure and a lower temperature in comparison with the second modelling part.
Racialised staff–patient relationships in inpatient mental health wards: a realist secondary qualitative analysis of patient experience data

Background The current study is a secondary analysis of qualitative data collected as part of EURIPIDES, a study which assessed how patient experience data were used to improve the quality of care in National Health Service (NHS) mental health services. Objective We undertook a detailed realist secondary qualitative analysis of 10 interviews in which expressions of racialisation were unexpectedly reported. This theme and these data did not form part of the primary realist evaluation. Methods Interviews were originally conducted with the patients (18–65 years: 40% female, 60% male) from four different geographically located NHS England mental health trusts between July and October 2017. Secondary qualitative data analysis was conducted in two phases: (1) reflexive thematic analysis and retroduction; (2) refinement of context–mechanism–outcome configurations to explore the generative mechanisms underpinning processes of racialisation and revision of the initial programme theory. Findings There were two main themes: (1) absence of safe spaces to discuss racialisation which silenced and isolated patients; (2) strained communication and power imbalances shaped a process of mutual racialisation by patients and staff. Non-reporting of racialisation and discrimination elicited emotions such as feeling othered, misunderstood, disempowered and fearful. Conclusions The culture of silence, non-reporting and power imbalances in inpatient wards perpetuated relational racialisation and prevented authentic feedback and staff–patient rapport. Clinical implications Racialisation in mental health trusts reflects lack of psychological safety which weakens staff–patient rapport and has implications for authentic patient engagement in feedback and quality improvement processes. Larger-scale studies are needed to investigate racialisation in the staff–patient relationships.
Efficacy of adhesive strapping on umbilical hernia in children: a systematic review and meta-analysis of cohort studies

Background Although adhesive strapping (AS) for pediatric umbilical hernia (UH), which was once obsolete, has been reconsidered as a common practice in Japan, its efficacy is still unclear. This study aimed to evaluate its efficacy by reviewing related articles. Methods A comprehensive literature search of PubMed, Cochrane, Google Scholar, and Igaku Chuo Zasshi via Ichushi-Web was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Cohort studies reporting on the UH closure rate after AS compared with observation-only management were included. Results A total of 10 cohort studies were included, and the overall UH closure rate was not statistically significant (p=0.31, risk ratio (RR)=0.76, 95% confidence interval (CI) 0.45 to 1.28). However, there were significant differences in the UH closure rate at the age of 6 months (p<0.01, RR=0.55, 95% CI 0.41 to 0.75) and the efficacy of preventing protruding umbilici with redundant skin (p=0.049, RR=0.16, 95% CI 0.03 to 0.99). Conclusions Although the efficacy of AS on UH compared with observation-only management did not differ in terms of the UH closure rate, the application of AS may be effective for faster UH closure and the prevention of protruding umbilici. However, due to the high heterogeneity of the study, further large-scale studies, particularly randomized controlled trials, are warranted to reach a conclusion. PROSPERO registration number CRD42022314417.
Placebo and nocebo effects and mechanisms associated with pharmacological interventions: an umbrella review

Objectives This review aimed to summarise the existing knowledge about placebo and nocebo effects associated with pharmacological interventions and their mechanisms. Design Umbrella review, adopting the Assessment of Multiple Systematic Reviews 2 tool for critical appraisal. Data sources MEDLINE/PubMed, Scopus, Web of Science, PsycINFO, Cochrane Central Register of Controlled Trial were searched in September 2022, without any time restriction, for systematic reviews, narrative reviews, original articles. Results were summarised through narrative synthesis, tables, 95% CI. Outcome measures Mechanisms underlying placebo/nocebo effects and/or their effect sizes. Results The databases search identified 372 studies, for a total of 158 312 participants, comprising 41 systematic reviews, 312 narrative reviews and 19 original articles. Seventy-three per cent of the examined systematic reviews were of high quality. Our findings revealed that mechanisms underlying placebo and/or nocebo effects have been characterised, at least in part, for: pain, non-noxious somatic sensation, Parkinson’s disease, migraine, sleep disorders, intellectual disability, depression, anxiety, dementia, addiction, gynaecological disorders, attention-deficit hyperactivity disorder, immune and endocrine systems, cardiovascular and respiratory systems, gastrointestinal disorders, skin diseases, influenza and related vaccines, oncology, obesity, physical and cognitive performance. Their magnitude ranged from 0.08 to 2.01 (95% CI 0.37 to 0.89) for placebo effects and from 0.32 to 0.90 (95% CI 0.24 to 1.00) for nocebo effects. Conclusions This study provides a valuable tool for clinicians and researchers, identifying both results ready for clinical practice and gaps to address in the near future. Funding Università Cattolica del Sacro Cuore, Milan, Italy with the ‘Finanziamento Ponte 2022’ grant. PROSPERO registration number CRD42023392281.
FFM Index, FM Index and PBF in Subjects with Normal, Overweight, and Obese BMI in Saudi Arabia Female Population

Aims: To assess Fat Free Mass Index, Fat Mass Index and Percent Body Fat in subjects with normal, overweight, and obese BMI and to examine if FFMI and FMI as compared to BMI have higher predictability in identification of high risk groups as defined by metabolic measurements among female college students and employees in Hail, Northern part of Saudi Arabia.Methods: Sample of 514 female college students and employees were enrolled and body composition was measured by using bioelectrical impendence technique. FFMI and FMI are calculated using the standard formula. Blood pressure (BP) and pulse were measured using automatic BP reader in a resting sitting position. Random blood glucose was tested using strip method (One touch, Simple). Results: Around 11 percent of study subjects were underweight while 25 percent were overweight and another 22 percent were obese. Only 42 percent of study population had normal weight. Except for height there were significant differences for weight, BMI, FM, FFM and %BF across age groups. Weight, FM, FFM shows a linear trend till the age 40 yrs after which an inverse trend begins. BMI continues to show linear trend across all ages. Mean FFMI was around 14 kg/m2 (range 5th – 95th percentile: 12.5 – 17.8 kg/m2) and was modestly but significantly higher (P < 0.001) in the higher age group. Similarly, Mean FMI was 8.4 kg/m2 (range 5th – 95th percentile: 3.8 – 18.3 kg/m2) and significantly higher (P < 0.001) in the higher age group. In Regression models for SBP, BMI and %BF explain 18.7 % of variance; while for DBP, WC and %BF explain 11.2 % of variance. For blood glucose, it is FFMI, FMI and Visceral fat which explain maximum variance.Conclusion: BMI alone cannot provide information about the respective contribution of FFM or fat mass to body weight. This study presents FFMI and BFMI values that correspond to low, normal, overweight, and obese BMIs. FFMI and BFMI provide information about body compartments, regardless of height.