Miracle-dz/UniFAR-FTUs huggingface dataset:
Personality of patients with central serous chorioretinopathy

Introduction: Central serous chorioretinopathy (CSC) is a disease of the retina that is a frequent cause of mild to moderate visual impairment. The disease can be precipitated by psychosocial stress and hypercortisolism while full remission will often be spontaneous within a few months. Risk factors have included male gender, increased plasma cortisol due to other conditions or steroid use and Type A behavior. Methods: This is a cross-sectional study comparing three research groups that included 100 CSC patients, 200 healthy volunteers, and 200 patients with other ophthalmic disease on their results in the Zuckerman–Kuhlman Personality Questionnaire (ZKPQ). Results: CSC patients differed from the other subjects on increased high Neuroticism-Anxiety, low Sociability, and high Aggression-Hostility. Conclusions: Since high Neuroticism is related to increased cortisol levels only in males, and high Aggression-Hostility is related to increased cortisol response, these findings point to the possibility of a robust neurobiological background to the etiopathogenesis of CSC that merits further research. The association of Type A behavior with CSC may be a spurious one and its widespread reference in ophthalmology texts should be re-examined.
Testing the stability of theory of mind: A longitudinal approach

An explicit understanding of false belief develops around the age of four years. However, tasks based on spontaneous responses have revealed an implicit understanding of belief and other theory of mind constructs in infants in their second year of life. The few longitudinal studies that have examined conceptual continuity of theory of mind from infancy to early childhood have reported mixed findings. Here we report two longitudinal experiments to investigate the developmental relation between implicit and explicit theory of mind. No link was observed in the first experiment between false belief and intention understanding measured at 14 and 18 months with the violation of expectation paradigm and tasks measuring explicit and implicit false belief at four or five years of age. In the second experiment, infants aged 18 months were tested with a battery of tasks that measured knowledge inference and false belief. They were then tested with the theory of mind scale at five years of age. The parents completed the Children’s Social Understanding Scale (CSUS) and the Social Communication Questionnaire (SCQ). As in the first experiment, there were no associations between early and later forms of theory of mind. We suggest that these findings do not support the view that there is conceptual continuity in theory of mind development.
Risk Factors for Poor Outcome of Cervical Laminoplasty: Multivariate Analysis in 505 Patients with Cervical Spondylotic Myelopathy.

STUDY DESIGN A prospective study OBJECTIVE. : To characterize the risk factors for poor outcome following cervical laminoplasty in patients with cervical spondylotic myelopathy (CSM). SUMMARY OF BACKGROUND DATA Prior research has identified a variety of potential predictive factors that might affect outcomes after cervical laminoplasty. However, no study till date has assessed the effects of such risk factors, including internal medicine comorbidity and quantitative performance tests, on the outcome of laminoplasty in a large series of patients with CSM. METHODS A total of 505 consecutive patients with CSM (311 males; 194 females; mean age, 66.6 years; age range, 41-91 years) who underwent double-door laminoplasty were prospectively included. The average postoperative follow-up period was 26.5 months (range, 12-66 months). We evaluated the recovery rate (RR) on the basis of the Japanese Orthopaedic Association score. Logistic regression analysis was performed to identify the risk factors for poor outcome, which was defined as a postoperative RR of < 50%. Relationship between outcome and various clinical and imaging predictors was examined. RESULTS Two hundred ninety-five patients had good outcomes with RR > 50%, whereas 210 patients had poor outcomes with RR < 50%. Compared with the good-outcome group, the poor-outcome group had a significantly higher prevalence of diabetes and hypertension and use of anticoagulant / antiplatelet agent and smoking history (P < 0.05). Multivariate logistic regression analysis showed independent risks associated with increased age (odds ratio (ORs)=1.029, 95% confidence interval (CI)=1.004-1054, P = 0.023). Logistic regression analysis determined that symptom duration of CSM (OR = 1.017, 95% CI = 1.008-1.026, P < 0.001) and preoperative 10-s step test (OR = 0.922, 95% CI = 0.865-0.983, P = 0.013) were significant risk factors for poor outcome. CONCLUSIONS These findings suggest that advanced age, long-term CSM symptoms and lower score of preoperative 10-s step test are risk factors for poor outcome in patients with CSM. LEVEL OF EVIDENCE 2.
Birth and Infant Outcomes Following Laboratory-Confirmed SARS-CoV-2 Infection in Pregnancy — SET-NET, 16 Jurisdictions, March 29–October 14, 2020

Pregnant women with coronavirus disease 2019 (COVID-19) are at increased risk for severe illness and might be at risk for preterm birth (1-3). The full impact of infection with SARS-CoV-2, the virus that causes COVID-19, in pregnancy is unknown. Public health jurisdictions report information, including pregnancy status, on confirmed and probable COVID-19 cases to CDC through the National Notifiable Diseases Surveillance System. * Through the Surveillance for Emerging Threats to Mothers and Babies Network (SET-NET), 16 jurisdictions collected supplementary information on pregnancy and infant outcomes among 5,252 women with laboratory-confirmed SARS-CoV-2 infection reported during March 29-October 14, 2020. Among 3,912 live births with known gestational age, 12.9% were preterm (<37 weeks), higher than the reported 10.2% among the general U.S. population in 2019 (4). Among 610 infants (21.3%) with reported SARS-CoV-2 test results, perinatal infection was infrequent (2.6%) and occurred primarily among infants whose mother had SARS-CoV-2 infection identified within 1 week of delivery. Because the majority of pregnant women with COVID-19 reported thus far experienced infection in the third trimester, ongoing surveillance is needed to assess effects of infections in early pregnancy, as well the longer-term outcomes of exposed infants. These findings can inform neonatal testing recommendations, clinical practice, and public health action and can be used by health care providers to counsel pregnant women on the risks of SARS-CoV-2 infection, including preterm births. Pregnant women and their household members should follow recommended infection prevention measures, including wearing a mask, social distancing, and frequent handwashing when going out or interacting with others or if there is a person within the household who has had exposure to COVID-19. †.
Implications of Tumor Characteristics and Treatment Modality on Local Recurrence and Functional Outcomes in Children With Chest Wall Sarcoma

Objective: To determine the impact of tumor characteristics and treatment approach on (1) local recurrence, (2) scoliosis development, and (3) patient-reported quality of life in children with sarcoma of the chest wall. Summary of Background Data: Children with chest wall sarcoma require multimodal therapy including chemotherapy, surgery, and/or radiation. Despite aggressive therapy which places them at risk for functional impairment and scoliosis, these patients are also at significant risk for local recurrence. Methods: A multi-institutional review of 175 children (median age 13 years) with chest wall sarcoma treated at seventeen Pediatric Surgical Oncology Research Collaborative institutions between 2008 and 2017 was performed. Patient-reported quality of life was assessed prospectively using PROMIS surveys. Results: The most common diagnoses were Ewing sarcoma (67%) and osteosarcoma (9%). Surgical resection was performed in 85% and radiation in 55%. A median of 2 ribs were resected (interquartile range = 1–3), and number of ribs resected did not correlate with margin status (P = 0.36). Local recurrence occurred in 23% and margin status was the only predictive factor (HR 2.24, P = 0.039). With a median follow-up of 5 years, 13% developed scoliosis (median Cobb angle 26) and 5% required corrective spine surgery. Scoliosis was associated with posteriorrib resection (HR 8.43; P= 0.003) and increased number of ribs resected (HR 1.78; P = 0.02). Overall, patient-reported quality of life is not impaired after chest wall tumor resection. Conclusions: Local recurrence occurs in one-quarter of children with chest wall sarcoma and is independent of tumor type. Scoliosis occurs in 13% of patients, but patient-reported quality of life is excellent.
On the robustness of deep learning-based lung-nodule classification for CT images with respect to image noise

Robustness is an important aspect when evaluating a method of medical image analysis. In this study, we investigated the robustness of a deep learning (DL)-based lung-nodule classification model for CT images with respect to noise perturbations. A deep neural network (DNN) was established to classify 3D CT images of lung nodules into malignant or benign groups. The established DNN was able to predict malignancy rate of lung nodules based on CT images, achieving the area under the curve of 0.91 for the testing dataset in a tenfold cross validation as compared to radiologists’ prediction. We then evaluated its robustness against noise perturbations. We added to the input CT images noise signals generated randomly or via an optimization scheme using a realistic noise model based on a noise power spectrum for a given mAs level, and monitored the DNN’s output. The results showed that the CT noise was able to affect the prediction results of the established DNN model. With random noise perturbations at 100 mAs, DNN’s predictions for 11.2% of training data and 17.4% of testing data were successfully altered by at least once. The percentage increased to 23.4% and 34.3%, respectively, for optimization-based perturbations. We further evaluated robustness of models with different architectures, parameters, number of output labels, etc, and robustness concern was found in these models to different degrees. To improve model robustness, we empirically proposed an adaptive training scheme. It fine-tuned the DNN model by including perturbations in the training dataset that successfully altered the DNN’s perturbations. The adaptive scheme was repeatedly performed to gradually improve DNN’s robustness. The numbers of perturbations at 100 mAs affecting DNN’s predictions were reduced to 10.8% for training and 21.1% for testing by the adaptive training scheme after two iterations. Our study illustrated that robustness may potentially be a concern for an exemplary DL-based lung-nodule classification model for CT images, indicating the needs for evaluating and ensuring model robustness when developing similar models. The proposed adaptive training scheme may be able to improve model robustness.
Effect of COVID-19 on delivery plans and postnatal depression scores of pregnant women.

INTRODUCTION Owing to the coronavirus disease 2019 outbreak Hong Kong hospitals have suspended visiting periods and made mask wearing mandatory. In obstetrics, companionship during childbirth has been suspended and prenatal exercises, antenatal talks, hospital tours, and postnatal classes have been cancelled. The aim of the present study was to investigate the effects of these restrictive measures on delivery plans and risks of postpartum depression. METHODS We compared pregnancy data and the Edinburgh Postpartum Depression Scale (EPDS) scores of women who delivered between the pre-alert period (1 Jan 2019 to 4 Jan 2020) and post-alert period (5 Jan 2020 to 30 Apr 2020) in a tertiary university public hospital in Hong Kong. Screening for postpartum depression was performed routinely using the EPDS questionnaire 1 day and within 1 week after delivery. RESULTS There was a 13.1% reduction in the number of deliveries between 1 January and 30 April from 1144 in 2019 to 994 in 2020. The EPDS scores were available for 4357 out of 4531 deliveries (96.2%). A significantly higher proportion of women had EPDS scores of ≥10 1 day after delivery in the post-alert group than the pre-alert group (14.4% vs 11.9%; P<0.05). More women used pethidine (6.2% vs 4.6%) and fewer used a birthing ball (8.5% vs 12.4%) for pain relief during labour in the post-alert group. CONCLUSIONS Pregnant women reported more depressive symptoms in the postpartum period following the alert announcement regarding coronavirus infection in Hong Kong. This was coupled with a drop in the delivery rate at our public hospital. Suspension of childbirth companionship might have altered the methods of intrapartum pain relief and the overall pregnancy experience.
HIV- 1 RNA dimerization at the single-molecule level

HIV-1 RNA DIMERIZATION AT THE SINGLE-MOLECUEL LEVEL by HANSINI RASANGA MUNDIGALA May 2014 Advisors: Dr. David Rueda & Dr. Andrew Feig Major: Chemistry (Analytical) Degree: Doctor of Philosophy The HIV-1 dimerization initiation sequence (DIS) is a conserved palindrome in the apical loop of a conserved hairpin motif in the 5’-UTR of its RNA genome. The DIS hairpin plays an important role in genome dimerization by forming a “kissing complex” (KC) between two complementary hairpins. Understanding the kinetics of this interaction is key to exploiting DIS as a possible HIV drug target. Here, we present a single-molecule Förster resonance energy transfer (smFRET) study of the dimerization reaction kinetics. Our data show the real-time formation and dissociation dynamics of individual kissing complexes, as well as, the formation of the mature extended duplex complex that is ultimately required for virion packaging. Interestingly, the singlemolecule trajectories reveal the presence of a previously unobserved bent intermediate required for extended duplex formation. The universally conserved A272 is essential for the formation of this intermediate, which is stabilized by Mg, but not by K, cations. We propose a 3D model of a possible bent intermediate and a minimal dimerization pathway consisting of three steps with two obligatory intermediates (kissing complex and bent intermediate) and driven by Mg ions. Additionally, it was confirmed that in the
The difference between trait disinhibition and impulsivity-and why it matters for clinical psychological science.

In the psychological science field, there is substantial interest in quantifying individual differences in self-regulatory capacity because of its transdiagnostic relevance to various forms of psychopathology. Trait disinhibition and impulsiveness are popular conceptualizations of dispositions reflecting self-regulation of behavioral and emotional responding. In the literature, these constructs are often treated interchangeably because of their shared focus on general disconstraint and a lack of direct comparisons between measures of each. The current work used structural modeling to examine conceptual and empirical differences between 2 popular operationalizations of these traits in 2 samples (Ns = 400, 308), and employed regression and dominance analyses to compare their predictive relations with criterion measures of externalizing problems and negative affectivity (NA). Impulsigenic traits were related both to externalizing problems and NA, whereas trait disinhibition was selectively associated with externalizing. In a dominance analysis, trait disinhibition exhibited complete dominance over all impulsigenic traits in predicting externalizing problems. Conversely, multiple impulsigenic traits evidenced complete dominance over trait disinhibition in prediction of NA. The current work provides evidence that (a) disinhibition and impulsigenic traits are not interchangeable, (b) disinhibition specifically indexes propensity for externalizing problems, and (c) impulsigenic traits reflect a blend of externalizing and NA that appears relevant to diverse forms of psychopathology. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Decoding the Genomic Variability among Members of the Bifidobacterium dentium Species

Members of the Bifidobacterium dentium species are usually identified in the oral cavity of humans and associated with the development of plaque and dental caries. Nevertheless, they have also been detected from fecal samples, highlighting a widespread distribution among mammals. To explore the genetic variability of this species, we isolated and sequenced the genomes of 18 different B. dentium strains collected from fecal samples of several primate species and an Ursus arctos. Thus, we investigated the genomic variability and metabolic abilities of the new B. dentium isolates together with 20 public genome sequences. Comparative genomic analyses provided insights into the vast metabolic repertoire of the species, highlighting 19 glycosyl hydrolases families shared between each analyzed strain. Phylogenetic analysis of the B. dentium taxon, involving 1140 conserved genes, revealed a very close phylogenetic relatedness among members of this species. Furthermore, low genomic variability between strains was also confirmed by an average nucleotide identity analysis showing values higher than 98.2%. Investigating the genetic features of each strain, few putative functional mobile elements were identified. Besides, a consistent occurrence of defense mechanisms such as CRISPR–Cas and restriction–modification systems may be responsible for the high genome synteny identified among members of this taxon.
Soiling of Pig Pens: A Review of Eliminative Behaviour

Simple Summary The soiling of pig pens has important negative consequences in terms of animal welfare, health, workload, and environmental emissions of pig farming. The aim of this review is to present the state-of-the-art regarding pigs’ normal eliminatory behaviour (i.e., defaecation and urination) and pen soiling, aimed here at solving pen-soiling problems in existing systems, and in a following publication aimed at the design of a more sustainable pig-farming system. To this end, we summarize a large body of literature on pen soiling and pigs’ eliminative behaviour in different farming systems. We propose a “disease framework” interpretation of pen soiling, to help identify its causes, underlying mechanisms, and solutions. Abstract This is a comprehensive review on the pigs’ normal eliminatory behaviour (i.e., defaecation and urination) and pen soiling. This review is aimed primarily at solving issues with pen soiling in current systems, and ultimately at the future design of a well-functioning pig toilet, which we intend to elaborate on in a subsequent publication. In this paper, first, normal elimination is described in relation to what is known about its phylogeny, ontogeny, causation, and function, i.e., according to Tinbergen’s four why questions concerning animal behaviour. Then, pen soiling is described as if it were a medical disorder, highlighting its importance, aetiology, symptoms, diagnosis, pathogenesis, treatment, and prevention. Due to its negative consequences in terms of animal welfare, health, workload, and environmental emissions, possible methods to address pen soiling in current systems are described. Probably, pigs do not choose a specific place to eliminate but rather choose the most comfortable place for resting, and avoid eliminating there. We identified four main strategies to reduce pen soiling: (1) reducing the suitability of the designated elimination area to be used for other functions, especially resting or thermoregulation; (2) improving the suitability of other functional areas in the pen to be used for their specific function, such as resting and activity; (3) reducing the suitability of other functional areas to be used for elimination; and (4) improving the suitability of the elimination area for elimination. These prevention strategies and the encompassing disease framework provide a structured approach to deal with pen soiling in existing systems and to support the future design, development, and implementation of a well-functioning pig toilet that can help to achieve some of the main goals of modern pig production, namely reducing environmental emissions as well as substantially improving pig welfare.
A New Lung Ultrasound Protocol Able to Predict Worsening in Patients Affected by Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection can generate severe pneumonia associated with high mortality. A bedside lung ultrasound (LUS) examination has been shown to have a potential role in this setting. The purpose of this study was to evaluate the potential prognostic value of a new LUS protocol (evaluation of 14 anatomic landmarks, with graded scores of 0–3) in patients with SARS‐CoV‐2 pneumonia and the association of LUS patterns with clinical or laboratory findings.
Development and Validation of a Deep Learning–Based Automatic Brain Segmentation and Classification Algorithm for Alzheimer Disease Using 3D T1-Weighted Volumetric Images

BACKGROUND AND PURPOSE: Limited evidence has suggested that a deep learning automatic brain segmentation and classification method, based on T1-weighted brain MR images, can predict Alzheimer disease. Our aim was to develop and validate a deep learning–based automatic brain segmentation and classification algorithm for the diagnosis of Alzheimer disease using 3D T1-weighted brain MR images. MATERIALS AND METHODS: A deep learning–based algorithm was developed using a dataset of T1-weighted brain MR images in consecutive patients with Alzheimer disease and mild cognitive impairment. We developed a 2-step algorithm using a convolutional neural network to perform brain parcellation followed by 3 classifier techniques including XGBoost for disease prediction. All classification experiments were performed using 5-fold cross-validation. The diagnostic performance of the XGBoost method was compared with logistic regression and a linear Support Vector Machine by calculating their areas under the curve for differentiating Alzheimer disease from mild cognitive impairment and mild cognitive impairment from healthy controls. RESULTS: In a total of 4 datasets, 1099, 212, 711, and 705 eligible patients were included. Compared with the linear Support Vector Machine and logistic regression, XGBoost significantly improved the prediction of Alzheimer disease (P < .001). In terms of differentiating Alzheimer disease from mild cognitive impairment, the 3 algorithms resulted in areas under the curve of 0.758–0.825. XGBoost had a sensitivity of 68% and a specificity of 70%. In terms of differentiating mild cognitive impairment from the healthy control group, the 3 algorithms resulted in areas under the curve of 0.668–0.870. XGBoost had a sensitivity of 79% and a specificity of 80%. CONCLUSIONS: The deep learning–based automatic brain segmentation and classification algorithm allowed an accurate diagnosis of Alzheimer disease using T1-weighted brain MR images. The widespread availability of T1-weighted brain MR imaging suggests that this algorithm is a promising and widely applicable method for predicting Alzheimer disease.