Miracle-dz/UniFAR-FTUs huggingface dataset:
Feasibility of Self-Performed Lung Ultrasound with Remote Teleguidance for Monitoring at Home COVID-19 Patients

During the COVID-19 pandemic, use of telemedicine with the aim of reducing the rate of viral transmission increased. This proof-of-concept observational study was planned to test the feasibility of a home-based lung ultrasound (LUS) follow-up performed by patients with mild COVID-19 infection on themselves. We enrolled patients presenting to the emergency department with SARS-CoV-2 infection without signs of pneumonia and indication to discharge. Each patient received a brief training on how to perform LUS and a handheld ultrasound probe. Then, patients were contacted on a daily basis, and LUS images were acquired by the patients themselves under “teleguidance” by the investigator. Twenty-one patients were enrolled with a median age of 44 years. All evaluations were of sufficient quality for a follow up. Probability of a better LUS quality was related to higher degree (odds ratio, OR, 1.42, 95% CI 0.5–3.99) and a lower quality to evaluation time (from 0.71, 95% CI 0.55–0.92 for less than 7 min, to 0.52, 95% CI 0.38–0.7, between 7 and 10 min, and to 0.29, 95% CI 0.2–0.43, for evaluations longer than 10 min). No effect related to gender or age was detected. LUS performed by patients and remotely overseen by expert providers seems to be a feasible and reliable telemedicine tool.
Does the Better-Than-Average Eﬀect Show That People Are Overconﬁdent?: Two Experiments.

We conduct two experiements of the claim that people are overcon(cid:133)dent. We de-velop new tests of overplacement which are based on a formal Bayesian model. Our two experiments, on easy quizzes, (cid:133)nd overplacement. More precisely, we (cid:133)nd apparently overcon(cid:133)dent data that cannot be accounted for by a rational population of expected utility maximizers with a good understanding of the nature of the quizzes they took.
Effectiveness of a Group-Based Rehabilitation Program Combining Education with Multimodal Exercises in the Treatment of Patients with Nonspecific Chronic Low Back Pain: A Retrospective Uncontrolled Study

Simple Summary Low back pain is a major and worldwide cause of global disability. It is not rare that an acute episode of low back pain evolves towards a chronic status without any specific cause. While many clinicians focus their treatment on low-value -care interventions (e.g., massage or electrotherapy), best clinical practice guidelines now recommend a mixed approach combining exercises and education. Furthermore, owing to the potential advantages that confer patient interactions with others (support, motivation, and program compliance), we decided to launch such an intervention program in a group setting (MyBack program) and aimed to evaluate its effectiveness through this study. Following this 8-week intervention program, approximately three-quarters of the patients reported a relevant reduction in pain intensity (78%), catastrophic thinking (78%), functional disability (74%), and fear of movement and work-related activities (74%). Only a quarter of the patients (26%) reported a relevant improvement in quality of life, probably because this outcome was already high before treatment. The MyBack program combining education with multimodal group exercises led to satisfactory clinical, functional, and psychosocial outcomes. Abstract Currently, there is no consensus on the best rehabilitation program to perform for nonspecific chronic low back pain (NSCLBP). However, multimodal exercises, education, and group-based sessions seem to be beneficial. We, therefore, launched such a treatment program and aimed to evaluate its effectiveness in improving patient health status. We retrospectively analyzed the records of 23 NSCLB patients who followed the MyBack program at La Tour hospital from 2020 to 2022 (25 sessions, 8 weeks). Patients were evaluated before and after intervention using pain on a visual analog scale (pVAS), Roland–Morris Disability Questionnaire (RMDQ), Pain Catastrophizing Scale (PCS), Tampa Scale of Kinesiophobia (TSK), and the EuroQol-5D-3L (EQ-5D-3L). Responder rates were calculated using minimal clinically important differences. Patients reported a significant reduction (p < 0.05) in the pVAS (5.3 ± 1.2 vs. 3.1 ± 1.6), RMDQ (8.8 ± 3.3 vs. 4.0 ± 3.7), PCS (24.5 ± 9.4 vs. 11.7 ± 7.9) and TSK (41.5 ± 9.2 vs. 32.7 ± 7.0). The EQ-5D-3L also statistically improved (score: 0.59 ± 0.14 vs. 0.73 ± 0.07; and VAS: 54.8 ± 16.8 vs. 67.0 ± 15.2). The responder rates were 78% for the pVAS and PCS, 74% for the RMDQ and TSK, and only 26% for the EQ-5D-3L. The MyBack program combining education with multimodal group exercises led to satisfactory clinical, functional, and psychosocial outcomes.
Newcastle Disease Genotype VII Prevalence in Poultry and Wild Birds in Egypt

Newcastle Disease Virus (NDV) genotype VII is a highly pathogenic Orthoavulavirus that has caused multiple outbreaks among poultry in Egypt since 2011. This study aimed to observe the prevalence and genetic diversity of NDV prevailing in domestic and wild birds in Egyptian governorates. A total of 37 oropharyngeal swabs from wild birds and 101 swabs from domestic bird flocks including chickens, ducks, turkeys, and pelicans, were collected from different geographic regions within 13 governorates during 2019–2020. Virus isolation and propagation via embryonated eggs revealed 91 swab samples produced allantoic fluid containing haemagglutination activity, suggestive of virus presence. The use of RT-PCR targeted to the F gene successfully detected NDV in 85 samples. The geographical prevalence of NDV was isolated in 12 governorates in domestic birds, migratory, and non-migratory wild birds. Following whole genome sequencing, we assembled six NDV genome sequences (70–99% of genome coverage), including five full F gene sequences. All NDV strains carried high virulence, with phylogenetic analysis revealing that the strains belonged to class II within genotype VII.1. 1. The genetically similar yet geographically distinct virulent NDV isolates in poultry and a wild bird may allude to an external role contributing to the dissemination of NDV in poultry populations across Egypt. One such contribution may be the migratory behaviour of wild birds; however further investigation must be implemented to support the findings of this study. Additionally, continued genomic surveillance in both wild birds and poultry would be necessary for monitoring NDV dissemination and genetic diversification across Egypt, with the aim of controlling the disease and protecting poultry production.
Genotype Complements the Phenotype: Identification of the Pathogenicity of an LMNA Splice Variant by Nanopore Long-Read Sequencing in a Large DCM Family

Dilated cardiomyopathy (DCM) is a common cause of heart failure (HF) and is of familial origin in 20–40% of cases. Genetic testing by next-generation sequencing (NGS) has yielded a definite diagnosis in many cases; however, some remain elusive. In this study, we used a combination of NGS, human-induced pluripotent-stem-cell-derived cardiomyocytes (iPSC-CMs) and nanopore long-read sequencing to identify the causal variant in a multi-generational pedigree of DCM. A four-generation family with familial DCM was investigated. Next-generation sequencing (NGS) was performed on 22 family members. Skin biopsies from two affected family members were used to generate iPSCs, which were then differentiated into iPSC-CMs. Short-read RNA sequencing was used for the evaluation of the target gene expression, and long-read RNA nanopore sequencing was used to evaluate the relevance of the splice variants. The pedigree suggested a highly penetrant, autosomal dominant mode of inheritance. The phenotype of the family was suggestive of laminopathy, but previous genetic testing using both Sanger and panel sequencing only yielded conflicting evidence for LMNA p.R644C (rs142000963), which was not fully segregated. By re-sequencing four additional affected family members, further non-coding LMNA variants could be detected: rs149339264, rs199686967, rs201379016, and rs794728589. To explore the roles of these variants, iPSC-CMs were generated. RNA sequencing showed the LMNA expression levels to be significantly lower in the iPSC-CMs of the LMNA variant carriers. We demonstrated a dysregulated sarcomeric structure and altered calcium homeostasis in the iPSC-CMs of the LMNA variant carriers. Using targeted nanopore long-read sequencing, we revealed the biological significance of the variant c.356+1G>A, which generates a novel 5′ splice site in exon 1 of the cardiac isomer of LMNA, causing a nonsense mRNA product with almost complete RNA decay and haploinsufficiency. Using novel molecular analysis and nanopore technology, we demonstrated the pathogenesis of the rs794728589 (c.356+1G>A) splice variant in LMNA. This study highlights the importance of precise diagnostics in the clinical management and workup of cardiomyopathies.
A Two-Stage Structural Damage Detection Method Based on 1D-CNN and SVM

Deep learning has been applied to structural damage detection and achieved great success in recent years, such as the popular structural damage detection methods based on structural vibration response and convolutional neural networks (CNN). However, due to the limited number of vibration response samples that can be acquired in practice for damage detection, the CNN-based models may not be fully trained; thus, their performance for identifying different damage severity as well as the damage locations may be reduced. To solve this issue, in this paper, we follow the strategy of "divide-and-conquer" and propose a two-stage structural damage detection method. Specifically, in the first stage, a 1D-CNN model is constructed to extract the damage features automatically and identify the damage locations. In the second stage, a support vector machine (SVM) model and wavelet packet decomposition technique are combined to further quantify the damage. Experiments are conducted on an eight-level steel frame structure, and the accuracy of the experimental results is greater than 99%, which demonstrates the superiority of the proposed method compared to the state-of-the-art approaches.
Omics Data and Data Representations for Deep Learning-Based Predictive Modeling

Medical discoveries mainly depend on the capability to process and analyze biological datasets, which inundate the scientific community and are still expanding as the cost of next-generation sequencing technologies is decreasing. Deep learning (DL) is a viable method to exploit this massive data stream since it has advanced quickly with there being successive innovations. However, an obstacle to scientific progress emerges: the difficulty of applying DL to biology, and this because both fields are evolving at a breakneck pace, thus making it hard for an individual to occupy the front lines of both of them. This paper aims to bridge the gap and help computer scientists bring their valuable expertise into the life sciences. This work provides an overview of the most common types of biological data and data representations that are used to train DL models, with additional information on the models themselves and the various tasks that are being tackled. This is the essential information a DL expert with no background in biology needs in order to participate in DL-based research projects in biomedicine, biotechnology, and drug discovery. Alternatively, this study could be also useful to researchers in biology to understand and utilize the power of DL to gain better insights into and extract important information from the omics data.
Inﬂuence of Different Types of Retinal Cameras on the Performance of Deep Learning Algorithms in Diabetic Retinopathy Screening

: Background: The aim of this study was to assess the performance of regional graders and artiﬁcial intelligence algorithms across retinal cameras with different speciﬁcations in classifying an image as gradable and ungradable. Methods: Study subjects were included from a community-based nationwide diabetic retinopathy screening program in Thailand. Various non-mydriatic fundus cameras were used for image acquisition, including Kowa Nonmyd, Kowa Nonmyd α -DIII, Kowa Nonmyd 7, Kowa Nonmyd WX, Kowa VX 10 α , Kowa VX 20 and Nidek AFC 210. All retinal photographs were graded by deep learning algorithms and human graders and compared with a standard reference. Results: Images were divided into two categories as gradable and ungradable images. Four thousand eight hundred ﬁfty-two participants with 19,408 fundus images were included, of which 15,351 (79.09%) were gradable images and the remaining 4057 (20.90%) were ungradable images. Conclusions: The deep learning (DL) algorithm demonstrated better sensitivity, speciﬁcity and kappa than the human graders for all eight types of non-mydriatic fundus cameras. The deep learning system showed, more consistent diagnostic performance than the human graders across images of varying quality and camera types.
Could an Increased Percentage of Immature Granulocytes Accompanying Dyspepsia Predict COVID-19?

Background and Aim: Although vaccination practices continue at a fast pace around the world, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still threatens people’s lives. In this study, we aimed to determine the presence of SARS-CoV-2 in patients who do not have the typical symptoms of the novel coronavirus disease 2019 (COVID-19), but only present with dyspepsia, and to investigate the role of immature granulocytes in the early diagnosis of these patients. Material and Methods: Adult and pediatric patients suffering from dyspepsia were included in the study. The patients were divided into two groups, ‘‘positive’’ and ‘‘negative’’, based on their SARS-CoV-2 polymerase chain reaction test results. Immature granulocyte count (IG), immature granulocyte percentage (IG%), C-reactive protein (CRP), and neutrophil-to-lymphocyte ratio (NLR) values were recorded. Results: A total of 238 patients, including 25 (10.5%) pediatric and 213 (89.5%) adult patients, were included in the study. A total of 2 (8%) pediatric patients and 17 (7.9%) adult patients tested positive for SARS-CoV-2. The IG, IG%, and CRP parameters were significantly higher in the SARS-CoV-2-positive patients compared to the SARS-CoV-2-negative patients. The optimal cut-off value predictive of COVID-19 infection was determined to be ≥0.650 (sensitivity: 52.6% and specificity: 95.5%, p = 0.001) for IG%. Conclusions: It should be noted that dyspepsia may also be a COVID-19 symptom. IG% values, which can be determined with a hemogram test, a cheap and easily accessible test, may be a warning in the early detection of patients who do not have the typical symptoms of COVID-19.
Combination of Optical Biopsy with Patient Data for Improvement of Skin Tumor Identification

In this study, patient data were combined with Raman and autofluorescence spectral parameters for more accurate identification of skin tumors. The spectral and patient data of skin tumors were classified by projection on latent structures and discriminant analysis. The importance of patient risk factors was determined using statistical improvement of ROC AUCs when spectral parameters were combined with risk factors. Gender, age and tumor localization were found significant for classification of malignant versus benign neoplasms, resulting in improvement of ROC AUCs from 0.610 to 0.818 (p < 0.05). To distinguish melanoma versus pigmented skin tumors, the same factors significantly improved ROC AUCs from 0.709 to 0.810 (p < 0.05) when analyzed together according to the spectral data, but insignificantly (p > 0.05) when analyzed individually. For classification of melanoma versus seborrheic keratosis, no statistical improvement of ROC AUC was observed when the patient data were added to the spectral data. In all three classification models, additional risk factors such as occupational hazards, family history, sun exposure, size, and personal history did not statistically improve the ROC AUCs. In summary, combined analysis of spectral and patient data can be significant for certain diagnostic tasks: patient data demonstrated the distribution of skin tumor incidence in different demographic groups, whereas tumors within each group were distinguished using the spectral differences.
Low and Moderate Doses of Caffeinated Coffee Improve Repeated Sprint Performance in Female Team Sport Athletes

Simple Summary The bulk of research on caffeine as an ergogenic aid has been on endurance performance, however there is evidence that caffeine can enhance short-term high-intensity performance. Caffeine may have an ergogenic impact during anaerobic exercise by facilitating central effects by antagonizing adenosine receptors, hence decreasing the detrimental effects of adenosine on neurotransmission, arousal, and pain perception. Caffeine intake also activates the central nervous system, which promotes alertness and concentration. Additionally, athletes typically consume coffee containing caffeine. To date, the bulk of study has focused on the administration of 3–9 mg/kg of anhydrous caffeine, as opposed to the readily accessible source of caffeine, coffee, and has mostly been conducted on males. Consequently, there is a dearth of study evaluating the ergogenic impact of caffeine on females, particularly when consuming alternative caffeine delivery methods, such as coffee. The current study is the first to investigate the effects of low (3 mg/kg) and moderate (6 mg/kg) doses of caffeine from coffee on repeated sprint performance in females. Abstract The aim of this study was to determine the effect of low and moderate doses of caffeine ingestion via caffeinated coffee on repeated sprint test (RST) and plasma catecholamine concentration in trained female team-sport athletes. In a randomized, double-blind, crossover design, 13 female team-sport athletes (VO2max: 48.7 ± 4 mL·kg·min−1) completed three RST trials, separated by 4-day, 60 min post-ingestion of either 3 mg·kg−1 (LCOF) or 6 mg·kg−1 (MCOF) or placebo (PLA). The RST consisted of 12 × 4 s sprints on a cycle ergometer interspersed with 20 s of active recovery. Blood lactate (BLa) and glucose (GLU) and epinephrine and norepinephrine concentrations were collected before and 60 min after coffee ingestion, and after RST. Heart rate (HR) and ratings of perceived exertion (RPE) were measured at the beginning of RST, and after the 6th and 12th sprints. Average peak power score during RST was significantly improved after LCOF (p = 0.016) and MCOF (p = 0.041) compared to PLA, but peak and mean power output of the individual sprints, and fatigue index were not different between trials (all p > 0.05). Epinephrine and norepinephrine concentrations were significantly higher before and after RST in LCOF and MCOF compared to PLA (all p < 0.05). BLa was also higher after RST in both LCOF and MCOF compared to PLA (p = 0.005). HR, RPE, and GLU were not different between conditions (p > 0.05). In conclusion, low and moderate dose of caffeine ingestion can enhance the average peak power score during repeated sprints. These findings partly support low and moderate doses of caffeine supplementation via coffee as a nutritional ergogenic aid for trained female team-sport players during repeated sprint exercise.
Measuring Spatial Accessibility of Healthcare Facilities in Marinduque, Philippines

Sustainable development goal (SDG) 3 promotes well-being and healthy lives for people of all ages. However, based on the literature, one of the main challenges to achieving SDG 3 is inequality in access to health care. In order to support the efforts of the local government of the province to contribute to the achievement of SDG thru equitable access to health care, this study measured the spatial accessibility of healthcare facilities in Marinduque, Philippines. It used distance-based (i.e., travel-time) and area-based (i.e., enhanced two-step floating catchment analysis or E2SFCA) metrics. The distance from each healthcare facility to different villages in the province was established using QGIS and Google Maps. The distance traveled was measured using three (3) modes of transportation: tricycle, jeepney, and private vehicle. The E2SFCA scores were calculated for different population groups: the general population, women, children, and the elderly. Based on the results, island villages and those areas in the inner portion of the province lack physical access to healthcare facilities. Such a limitation was apparent in the distance- and area-based accessibility metrics. Among the population group considered in this study, the women population showed the lowest accessibility scores.
In Search of Effective Gen Z Engagement in the Hospitality Industry: Revisiting Issues of Servant and Authentic Leadership

The purpose of this study is to provide a theoretical framework that demonstrates how psychological capital (PsyCap) can simultaneously mediate the effects of servant leadership (ServL) and authentic leadership (AuthL) on employee engagement in the workplace. This study examines whether AuthL better explains PsyCap and workplace engagement from the perspective of Generation Z (Gen Z) than ServL, although recent research shows that ServL and AuthL correlate well with Generations X and Y, respectively. In addition, there is limited research on the above aspects in the hospitality industry. These studies either have a very limited sample, contradictory results in their own context, or contradictory results in the same industry regarding the above relationships. This study will attempt to shed light on these contradictory findings. The researchers surveyed 393 members of Gen Z working in the hospitality business in one of Russia’s most popular destinations, Krasnodar. Data were analyzed using structural equation modeling, bootstrap analysis and descriptive statistics. Although both leadership styles have a positive impact on PsyCap and work engagement (WorkE) of Gen Z employees, AuthL has a greater impact on PsyCap and work engagement than ServL, according to the results. PsyCap was found to mediate the relationship between the two leadership styles and frontline Gen Z employees, and the study also found that it influenced overall Gen Z performance. The influence of PsyCap on the job engagement of Gen Z employees in the Russian hospitality industry is examined.