Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of postpartum pelvic floor dysfunction with a nomogram model based on big data collected during pregnancy.

BACKGROUND Pregnancy and childbirth are the main causes of pelvic floor dysfunction (PFD). Although pelvic floor muscle tension is typically measured at 42 days postpartum to assess the severity of PFD and provide timely rehabilitation, it is still impossible to predict PFD and take targeted preventive measures in clinical practice. A PFD prediction model based on big data obtained in prenatal check-ups was established in this study to allow the formulation of personalized preventive strategies to reduce the incidence of PFD. METHODS A total of 1,500 women who underwent regular prenatal checkups and examinations for PFD at 42 days postpartum at the Zhuji Maternal and Child Health Hospital between May 2015 and May 2020 were selected. The data from 1,000 of them were selected as the training cohort, and the data from 500 of them were used as the validation cohort. The women were divided into a PFD group and a non-PFD group according to whether PFD was diagnosed at 42 days postpartum. A nomogram prediction model was created using the influencing factors that lead to PFD, and the discrimination and calibration of the nomogram were evaluated through internal and external validation. RESULTS A total of 389 cases (38.9%) of PFD were included in the training cohort. Multivariate analysis showed that age (odds ratio (OR) =1.896, P<0.001), history of childbirth (OR =4.531, P<0.001), history of constipation (OR =2.475, P<0.001), urinary incontinence during pregnancy (OR =4.416, P<0.001), and biparietal diameter at 32 weeks of gestation (OR =51.672, P=0.012) were independent influencing factors of PFD at 42 days postpartum. These factors were used to establish a nomogram prediction model. This prediction model maintained good discrimination between the training cohort and the external validation cohort (the area under the curve was 0.893 and 0.842 for the training and validation cohorts, respectively). CONCLUSIONS The study validated that the nomogram prediction model based on the factors influencing PFD can be used to predict PFD at 32 weeks of gestation for timely intervention and prevention of PFD.
The Experiences of Counsellors Offering Problem-Solving Therapy for Common Mental Health Issues at the Youth Friendship Bench in Zimbabwe

Abstract There is growing evidence that lay health workers providing counselling is a feasible approach of addressing the universally large treatment gap for mental disorders. This study illuminates the experiences of the counsellors in the Youth Friendship Bench in Zimbabwe, a pilot project where students provide problem-solving therapy to adolescents with common mental disorders. Twelve interviews were analysed using content analysis. The first theme “Working in a meaningful project” describes how the counsellors managed to create an alliance with the clients. The project was perceived as helpful, meaningful and urgent, and the counsellors’ experienced a professional and individual development through the support of the Friendship Bench organization. The second theme “Encountering obstacles” illuminates how counsellors experienced situations where they failed to reach out to clients, felt unprepared and inadequate, and how they combated preconceptions and taboos. In the third theme, “Carrying an emotional burden,” the counsellors described experiences of recognising own problems and empathising with the client.
Leukocyte Telomere Length Is Not Reduced in Children and Adults with Cystic Fibrosis but Associates with Clinical Characteristics—A Cross-Sectional Study

We hypothezied that telomere length is considerably altered in cystic fibrosis (CF) patients compared to healthy subjects (HS), and that leukocyte telomere length variation reflects the severity of CF. Relative telomere length (RTL) was assessed by qPCR in 70 children aged 5–10 (34 CF; 36 HS) and 114 adults aged 18–45 (53 CF; 61 HS). Telomere length was similar in CF and HS (median (interquartile range): 0.799 (0.686–0.950) vs. 0.831 (0.707–0.986); p = 0.5283) both in children and adults. In adults, women had longer telomeres than men (0.805 (0.715–0.931) vs. 0.703 (0.574–0.790); p = 0.0002). Patients treated with inhaled corticosteroids had a shorter RTL compared to those without steroid therapy (0.765 (0.664–0.910) vs. 0.943 (0.813–1.191); p = 0.0007) and this finding remained significant after adjusting for gender, age, BMI, and child/adult status (p = 0.0003). Shorter telomeres were independently associated with the presence of comorbidities (0.763 (0.643–0.905) vs. 0.950 (0.783–1.130); p = 0.0006) and antibiotic treatment at the moment of blood sampling (0.762 (0.648–0.908) vs. 0.832 (0.748–1.129); p = 0.0172). RTL correlated with number of multiple-day hospitalizations (rho = −0.251; p = 0.0239), as well as number of hospitalization days (rho = −0.279; p = 0.0113). Leukocyte RTL in children and adults with CF was not shorter than in healthy controls, and did not seem to have any potential as a predictor of CF survival. However, it inversely associated with the investigated clinical characteristics.
Loss of Smell and Taste Can Accurately Predict COVID-19 Infection: A Machine-Learning Approach

The COVID-19 outbreak has spread extensively around the world. Loss of smell and taste have emerged as main predictors for COVID-19. The objective of our study is to develop a comprehensive machine learning (ML) modelling framework to assess the predictive value of smell and taste disorders, along with other symptoms, in COVID-19 infection. A multicenter case-control study was performed, in which suspected cases for COVID-19, who were tested by real-time reverse-transcription polymerase chain reaction (RT-PCR), informed about the presence and severity of their symptoms using visual analog scales (VAS). ML algorithms were applied to the collected data to predict a COVID-19 diagnosis using a 50-fold cross-validation scheme by randomly splitting the patients in training (75%) and testing datasets (25%). A total of 777 patients were included. Loss of smell and taste were found to be the symptoms with higher odds ratios of 6.21 and 2.42 for COVID-19 positivity. The ML algorithms applied reached an average accuracy of 80%, a sensitivity of 82%, and a specificity of 78% when using VAS to predict a COVID-19 diagnosis. This study concludes that smell and taste disorders are accurate predictors, with ML algorithms constituting helpful tools for COVID-19 diagnostic prediction.
Development of a Submillimetric GNSS-Based Distance Meter for Length Metrology †

Absolute distance determination in the open air with an uncertainty of a few tenths of a millimetre is increasingly required in many applications that involve high precision geodetic metrology. No matter the technique used to measure, the resulting distances must be proven consistent with the unit of length (SI-metre) as realized in the outdoor facilities traditionally used in length metrology, which are also known as calibration baselines of reference. The current calibration baselines of reference have distances in the range of 10 to 1000 m, but at present there is no solution on the market to provide distances with submillimetric precision in that range. Consequently, new techniques such as multi-wave interferometry, two-wave laser telemeters or laser trackers are being developed. A possible alternative to those sophisticated and expensive techniques is the use of widely used Global Navigation Satellite Systems (GNSS) in order to provide a GNSS-Based Distance Meter (GBDM). The use of a GBDM as a potential technique for length metrology has been thoroughly analysed in several European research projects by using the state-of-the-art geodetic software, such as Bernese 5.2, but no definite conclusions have been drawn and some metrological questions are considered still open. In this paper, we describe a dedicated approach to build up a submillimetric GBDM able to be applied in the current calibration baselines of reference, as well as possible methods to cope with the multipath error of the GNSS signals which is the major limitation for the practical uptaking of the technique in metrology. The accuracy of the proposed approach has been tested following the length metrology standards in four experiments carried out in the Universitat Politècnica de València (UPV). The results demonstrate that the proposed GBDM can provide an accuracy of a few tenths of a millimetre in the current calibration baselines of reference.
Modelling the Economic Impact of Reducing Loneliness in Community Dwelling Older People in England

Loneliness has been associated with poor mental health and wellbeing. In England, a 2018 national strategy on loneliness was published, and public health guidelines recommend participation in social activities. In the absence of existing economic evidence, we modelled the potential cost effectiveness of a service that connects lonely older people to social activities against no-intervention. A 5-year Markov model was constructed from a health and social care perspective. Parameters were drawn from the literature, with the intervention structure based on an existing loneliness alleviation programme implemented in several settings across England. Univariate and probabilistic sensitivity analyses were undertaken. The total expected cost per participant in the intervention group is £7131 compared to £6783 in the usual care group with 0.45 loneliness free years (LFY) gained. The incremental cost per LFY gained is £768; in the probabilistic sensitivity analysis the intervention is cost saving in 3.5% of iterations. Potentially such interventions may be cost-effective but are unlikely to be cost-saving even allowing for sustained effects and cumulative adverse health and social care events averted. Empirical studies are needed to determine the cost-effectiveness of these interventions, ideally mapping changes in loneliness to the quality of life, in order to allow the key metric in health economic studies, cost per quality adjusted life year to be estimated.
Diagnostic and Pharmacological Potency of Creatine in Post-Viral Fatigue Syndrome

Post-viral fatigue syndrome (PVFS) is a widespread chronic neurological disease with no definite etiological factor(s), no actual diagnostic test, and no approved pharmacological treatment, therapy, or cure. Among other features, PVFS could be accompanied by various irregularities in creatine metabolism, perturbing either tissue levels of creatine in the brain, the rates of phosphocreatine resynthesis in the skeletal muscle, or the concentrations of the enzyme creatine kinase in the blood. Furthermore, supplemental creatine and related guanidino compounds appear to impact both patient- and clinician-reported outcomes in syndromes and maladies with chronic fatigue. This paper critically overviews the most common disturbances in creatine metabolism in various PVFS populations, summarizes human trials on dietary creatine and creatine analogs in the syndrome, and discusses new frontiers and open questions for using creatine in a post-COVID-19 world.
Virulence Factors in Coagulase-Negative Staphylococci

Coagulase-negative staphylococci (CoNS) have emerged as major pathogens in healthcare-associated facilities, being S. epidermidis, S. haemolyticus and, more recently, S. lugdunensis, the most clinically relevant species. Despite being less virulent than the well-studied pathogen S. aureus, the number of CoNS strains sequenced is constantly increasing and, with that, the number of virulence factors identified in those strains. In this regard, biofilm formation is considered the most important. Besides virulence factors, the presence of several antibiotic-resistance genes identified in CoNS is worrisome and makes treatment very challenging. In this review, we analyzed the different aspects involved in CoNS virulence and their impact on health and food.
Plumbagin, a Potent Naphthoquinone from Nepenthes Plants with Growth Inhibiting and Larvicidal Activities

Some plant species are less susceptible to herbivore infestation than others. The reason for this is often unknown in detail but is very likely due to an efficient composition of secondary plant metabolites. Strikingly, carnivorous plants of the genus Nepenthes show extremely less herbivory both in the field and in green house. In order to identify the basis for the efficient defense against herbivorous insects in Nepenthes, we performed bioassays using larvae of the generalist lepidopteran herbivore, Spodoptera littoralis. Larvae fed with different tissues from Nepenthes x ventrata grew significantly less when feeding on a diet containing leaf tissue compared with pitcher-trap tissue. As dominating metabolite in Nepenthes tissues, we identified a naphthoquinone, plumbagin (5-hydroxy-2-methyl-1,4-naphthoquinone). When plumbagin was added at different concentrations to the diet of S. littoralis larvae, an EC50 value for larval growth inhibition was determined with 226.5 µg g−1 diet. To further determine the concentration causing higher larval mortality, sweet potato leaf discs were covered with increasing plumbagin concentrations in no-choice-assays; a higher mortality of the larvae was found beyond 60 µg plumbagin per leaf, corresponding to 750 µg g−1. Plant-derived insecticides have long been proposed as alternatives for pest management; plumbagin and derivatives might be such promising environmentally friendly candidates.
Validation and Screening Capacity of the European Portuguese Version of the SUNFRAIL Tool for Community-Dwelling Older Adults

Early detection of frailty may prevent or delay adverse health outcomes in community-dwelling older adults. In Portugal, there are currently no valid multidimensional frailty screening tools. SUNFRAIL is a user-friendly multidimensional tool for frailty screening that can be used in primary care. Aims: (i) to determine the validity and reliability of the European Portuguese version of the SUNFRAIL tool for use in community-dwelling older adults; (ii) to assess the screening capacity of this version of SUNFRAIL using Fried’s phenotypic model criteria for frailty as a reference test. Methods: Cross-sectional pilot study in a convenience sample of 128 community-dwelling older adults. Objective and subjective data were collected. Internal consistency, concurrent validity, sensitivity, and specificity (ROC curve analysis) were examined. Results: Internal consistency was low. Significant moderate to strong correlations were found between different domains and the total score. The differences between robust, pre-frail, and frail older adults were significant. SUNFRAIL was also correlated with multimorbidity. Sensitivity and specificity were satisfactory. Conclusions: The European Portuguese version of the SUNFRAIL tool is a promising frailty screening tool for community-dwelling older adults to be routinely used in clinical practice. However, more consistent results on its validity and reliability are needed to be used nationwide.
The impact of time spent on the electronic health record after work and of clerical work on burnout among clinical faculty

OBJECTIVE To identify specific thresholds of daily electronic health record (EHR) time after work and daily clerical time burden associated with burnout in clinical faculty. MATERIALS AND METHODS We administered an institution-wide survey to faculty in all departments at Mount Sinai Health System from November 2018 to February 2019. The Maslach Burnout Inventory and Mayo Well-Being Index assessed burnout. Demographics, possible confounding variables, and time spent on EHR work/clerical burden were assessed. RESULTS Of 4156 eligible faculty members, 1781(42.9%) participated in the survey. After adjustment for background factors, EHR frustration (odds ratio [OR]=1.64-1.66), spending >90 minutes on EHR-outside the workday by self-report (OR = 1.41-1.90) and >1 hour of self-reported clerical work/day (OR = 1.39) were associated with burnout. Reporting that one's practice unloads clerical burden (OR = 0.50-0.66) and higher resilience scores (OR = 0.77-0.84) were negatively associated with burnout.Spending >90 minutes/day on EHR-outside work (OR = 0.66-0.67) and >60 minutes/day on clerical work (OR = 0.54-0.58) was associated with decreased likelihood of satisfactory work-life integration (WLI) and professional satisfaction (PS). Greater meaning in work was associated with an increased. LIKELIHOOD of achieving WLI (OR = 2.51) and PS (OR = 21.67). CONCLUSION Results suggest there are thresholds of excessive time on the EHR-outside the workday (>90 minutes) and overall clerical tasks (>60 minutes), above which clinical faculty may be at increased risk for burnout, as well as reduced WLI and PS, independent of demographic characteristics and clinical work hours. These thresholds of EHR and clerical burden may inform interventions aimed at mitigating this burden to reduce physician burnout.
Positive Effect of Cannabis sativa L. Herb Extracts on Skin Cells and Assessment of Cannabinoid-Based Hydrogels Properties

The skin is an organ that is constantly exposed to many external factors that can affect its structure and function. Due to the presence of different cannabinoid receptors on many types of skin cells, cannabinoids can interact directly with them. Therefore, as part of this work, the impact of two types of Cannabis sativa L. herb extracts on keratinocytes and fibroblasts was assessed. The content of biologically active compounds such as phenols, flavonoids, chlorophylls and cannabinoids was evaluated. The antioxidant capacity of prepared extracts using the DPPH radical, H2DCFDA probe and measurement of superoxide dismutase activity was also assessed. The cytotoxicity of hemp extracts was determined using the Alamar Blue, Neutral Red and LDH assays. The ability of the extracts to inhibit the activity of matrix metalloproteinases, collagenase and elastase, was assessed. Preparations of model hydrogels were also prepared and their effect on transepidermal water loss and skin hydration was measured. The obtained results indicate that hemp extracts can be a valuable source of biologically active substances that reduce oxidative stress, inhibit skin aging processes and positively affect the viability of skin cells. The analysis also showed that hydrogels based on cannabis extracts have a positive effect on skin hydration.
Anthropogenic climate change is worsening North American pollen seasons

Significance Human-caused climate change could impact respiratory health, including asthma and allergies, through temperature-driven increases in airborne pollen, but the long-term continental pollen trends and role of climate change in pollen patterns are not well-understood. We measure pollen trends across North America from 1990 to 2018 and find increases in pollen concentrations and longer pollen seasons. We use an ensemble of climate models to test the role of climate change and find that it is the dominant driver of changes in pollen season length and a significant contributor to increasing pollen concentrations. Our results indicate that human-caused climate change has already worsened North American pollen seasons, and climate-driven pollen trends are likely to further exacerbate respiratory health impacts in coming decades. Airborne pollen has major respiratory health impacts and anthropogenic climate change may increase pollen concentrations and extend pollen seasons. While greenhouse and field studies indicate that pollen concentrations are correlated with temperature, a formal detection and attribution of the role of anthropogenic climate change in continental pollen seasons is urgently needed. Here, we use long-term pollen data from 60 North American stations from 1990 to 2018, spanning 821 site-years of data, and Earth system model simulations to quantify the role of human-caused climate change in continental patterns in pollen concentrations. We find widespread advances and lengthening of pollen seasons (+20 d) and increases in pollen concentrations (+21%) across North America, which are strongly coupled to observed warming. Human forcing of the climate system contributed ∼50% (interquartile range: 19–84%) of the trend in pollen seasons and ∼8% (4–14%) of the trend in pollen concentrations. Our results reveal that anthropogenic climate change has already exacerbated pollen seasons in the past three decades with attendant deleterious effects on respiratory health.
Hyperlactataemia as a predictor of adverse outcomes post-cardiac surgery in neonates with congenital heart disease

Abstract Objective: To evaluate the discriminative ability of hyperlactataemia for early morbidity and mortality in neonates with CHD following cardiac surgery. Methods: Retrospective, observational study of neonates who underwent cardiac surgery on cardiopulmonary bypass at a tertiary care children’s hospital from June 2015 to June 2019. The primary predictor was lactate. The primary composite outcome was defined as ≥1 of the following: cardiac arrest or extracorporeal membrane oxygenation within 72 hours or 30-day mortality post-operatively. The secondary outcome was the presence of major residual lesions, according to the Technical Performance Score. Results: Of 432 neonates, 28 (6.5%) sustained the composite outcome. On univariate analysis, peak lactate within 48 hours, increase in lactate from ICU admission through 12 hours, and single ventricle physiology were significantly associated with the composite outcome. The peak lactate occurred at a median of 2.9 hours (interquartile range: 1, 35) before the event. Through multi-variable analysis, a multi-variable risk algorithm was created. Predicted probabilities demonstrated an increasing risk based on single ventricle status and delta lactate, ranging from 1.8% (95% CI: 0.9, 3.9) to 52.4% (95% CI: 32.4, 71.7). The model had good discriminative ability for the composite outcome on receiver operating characteristic analysis (area under the curve = 0.79; 95% CI: 0.75, 0.89). Moreover, a peak lactate of 7.3 mmol/l or greater was significantly associated with the presence of a major residual lesion (odds ratios: 5.16, 95% CI: 3.01, 8.87). Conclusions: We present a simple, two-variable model, including delta lactate in the immediate post-operative period and single ventricle status, to prognosticate the risk of early morbidity and mortality in neonates undergoing cardiac surgery for potential intervention.
Experimental Comparison between Event and Global Shutter Cameras

We compare event-cameras with fast (global shutter) frame-cameras experimentally, asking: “What is the application domain, in which an event-camera surpasses a fast frame-camera? ” Surprisingly, finding the answer has been difficult. Our methodology was to test event- and frame-cameras on generic computer vision tasks where event-camera advantages should manifest. We used two methods: (1) a controlled, cheap, and easily reproducible experiment (observing a marker on a rotating disk at varying speeds); (2) selecting one challenging practical ballistic experiment (observing a flying bullet having a ground truth provided by an ultra-high-speed expensive frame-camera). The experimental results include sampling/detection rates and position estimation errors as functions of illuminance and motion speed; and the minimum pixel latency of two commercial state-of-the-art event-cameras (ATIS, DVS240). Event-cameras respond more slowly to positive than to negative large and sudden contrast changes. They outperformed a frame-camera in bandwidth efficiency in all our experiments. Both camera types provide comparable position estimation accuracy. The better event-camera was limited by pixel latency when tracking small objects, resulting in motion blur effects. Sensor bandwidth limited the event-camera in object recognition. However, future generations of event-cameras might alleviate bandwidth limitations.