Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Circles Measurement and the ABC Classification of Acromioclavicular Joint Injuries

Background: Acromioclavicular joint (ACJ) injuries are common. Despite this, it remains unclear how best to assess, classify, and manage these cases. A simple, reliable, valid, and accurate radiographic parameter to measure ACJ displacement would allow improved consistency of diagnosis and subsequent treatment pathways. Purpose: To evaluate “the circles measurement” and associated “ABC classification” as a tool for assessing ACJ displacement and injury classification. Study Design: Descriptive laboratory study. Methods: The circles measurement is taken from a lateral Alexander radiograph of the shoulder. The measurement is the center-to-center distance between 2 circles drawn to define the lateral extent of the clavicle and the anteromedial extent of the acromion; it is independent of the displacement plane, judging total ACJ displacement in any direction rather than trying to quantify vertical and/or horizontal displacement. When utilized clinically, the circles measurement is a single measurement calculated as the difference between values recorded for the injured and uninjured sides. Validation of the circles measurement was performed using lateral Alexander radiographs (including ±20° projection error in all planes) and computed tomography of standardized ACJ injury simulations. We assessed inter- and intrarater reliability, convergent validity, and discriminant validity of the circles measurement and subsequently generated a classification of ACJ injury based on displacement. Results: Reliability and validity of the circles measurement was excellent throughout. Interrater reliability (ICC [intraclass correlation coefficient] [2,1], 95% CI; n = 78; 4 observers) was 0.976 (0.964-0.985). Intrarater reliability (ICC [2,1]; 95% CI; n = 78; 2 measures) was 0.998 (0.996-0.998). Convergent validity (Pearson correlation coefficient, r) was 0.970 for ideal radiographs and 0.889 with ±20° projection error in all planes. Discriminant validity, with 1-way analysis of variance, showed a P value of <. 0001 and effect size (η2) of 0.960, with the ability to distinguish between the previously defined stable (Rockwood IIIA) and unstable (Rockwood IIIB) injuries. The results permitted objective, statistically sound parameters for the proposed ABC classification system. Conclusion: The circles measurement is a simple, reliable, valid, accurate, and resilient parameter for assessing ACJ displacement and can be used in conjunction with the proposed ABC classification to define ACJ injuries more accurately and objectively than previously described. Clinical Relevance: This novel parameter has the potential to standardize the initial assessment and possibly the subsequent clinical management of ACJ injuries, in addition to providing a standardized measure for future research.
The impact of COVID-19 on gambling and gambling disorder: emerging data

Purpose of review The lockdown response to the COVID-19 pandemic has significantly impacted commercial gambling in many jurisdictions around the world. The goal of this review is to systematically identify and describe the survey data and findings to date examining the effect on individual gambling and gambling disorder. Recent findings Of the 17 publications meeting inclusion criteria, the majority reported cross-sectional assessments (n = 11, 65%) and remainder were longitudinal in that they had earlier gambling data for participants (n = 6, 35%). Not surprisingly given the closure of land-based gambling, an overall reduction in gambling frequency and expenditure was reported in all studies. The estimate of the proportion of participants in both the general population and the population that gambles who increased overall gambling or online gambling was variable. The most consistent correlates of increased gambling during the lockdown were increased problem gambling severity, younger age groups, and being male. Summary These results suggest that the impacts of the COVID-19 pandemic on gambling and problematic gambling are diverse – possibly causing a reduction in current or future problems in some, but also promoting increased problematic gambling in others. The longer-term implications of both the reduction in overall gambling, and the increase in some vulnerable groups are unclear, and requires assessment in subsequent follow-up studies. However, in the short term, individuals with existing gambling problems should be recognized as a vulnerable group.
Materials for Improving Immune Cell Transfection

Chimeric antigen receptor T cell (CAR‐T) therapy holds great promise for preventing and treating deadly diseases such as cancer. However, it remains challenging to transfect and engineer primary immune cells for clinical cell manufacturing. Conventional tools using viral vectors and bulk electroporation suffer from low efficiency while posing risks like viral transgene integration and excessive biological perturbations. Emerging techniques using microfluidics, nanoparticles, and high‐aspect‐ratio nanostructures can overcome these challenges, and on top of that, provide universal and high‐throughput cargo delivery. Herein, the strengths and limitations of traditional and emerging materials for immune cell transfection, and commercial development of these tools, are discussed. To enhance the characterization of transfection techniques and uptake by the clinical community, a list of in vitro and in vivo assays to perform, along with relevant protocols, is recommended. The overall aim, herein, is to motivate the development of novel materials to meet rising demand in transfection for clinical CAR‐T cell manufacturing.
Amyotrophic lateral sclerosis caregiver burden and patients’ quality of life during COVID-19 pandemic

Abstract Objective: To assess patients Quality of life (QoL) and the burden of their caregivers during Covid-19 pandemic and specifically the impact of two-month lockdown period. Methods: In April 2020, a total of 60 patients and 59 caregivers were administered by phone scales assessing patients’ QoL (McGill QoL Questionnaire), general health status (EQ-5D-5L), and caregiver burden (Zarit Burden Interview). The administration was repeated one month after the end of lockdown measures, with the addition of a qualitative questionnaire (COVID-QoL Questionnaire) exploring family reorganization and personal perception of lock down. Results: QoL and perceived health status did not worsen during lockdown, while caregiver burden increased (p = 0.01). Patient’s QoL and caregiver burden were inversely correlated at T1 (ZBI total score mildly correlated with Mc Gill existential subscore, p = 0.02, rho = 0.30 and with Mc Gill total score, p = 0.05, rho = 0.265). No significant correlations were found at T2. According to the COVID-QoL questionnaire, caregivers perceived lower family help compared to patients (p < 0.001). Conclusions: Restricted measures of lockdown period during COVID-19 pandemic did not result in a significant reduction of QoL in our cohort of ALS patients, while caregiver burden significantly increased. ALS motor impairment may have played a role in the unchanged life conditions of patients. Instead, the restriction of family help for primary caregivers could be responsible of their increased burden, reflecting the importance of a wide social support in the management of this clinical condition.
NET WATER TRANSPORT VIA RAT COLON EPITELIUM UNDER THE EXPERIMENTAL DYSBIOSIS

: The aim of the present study was to investigate the effect of cephalosporin antibiotic ceftriaxone (50 mg/kg, i/m) and mac- rolide antibiotic azithromycin (15 mg/kg, per.os.) on net water transport across rat colonic epithelium. Study was done on male Wistar rats (180-250 g). Azithromycin or ceftriaxone was injected daily for 5 days. Net water transport was evaluated on the 6th day by isolated colonic loop perfusion technique in vivo on anaesthetized rats. Treatment with azithromycin increased 2,4-fold the absorption of water, while ceftriaxone caused decrease 1,9-fold water absorption. The antibiotics treatment within five days didn't change the composition of the fecal and colonic parietal microbiota. Azithromycin-induced increase in water absorption was associated with upregulation of AQP 8 water channel expression (P < 0.05) in colonic mucosa. Ceftriaxone treatment didn't change protein level of AQP8 but induced pro-inflammatory changes in colonic mucosa structure and mast cells degranulation. We showed for the first time the opposite effects ofmacrolide and cephalosporin antibiotics on net water transport across rat colonic epithelium.
Test-retest Reliability for HAQ-DI and SF-36 PF for the Measurement of Physical Function in Psoriatic Arthritis

Objective. Due to no existing data, we aimed to derive evidence to support test-retest reliability for the Health Assessment Questionnaire–Disability Index (HAQ-DI) and 36-item Short Form Health Survey physical functioning domain (SF-36 PF) in psoriatic arthritis (PsA). Methods. We identified datasets that collected relevant data for test-retest reliability for HAQ-DI and SF-36 PF, and evaluated them using Outcome Measures in Rheumatology (OMERACT) Filter 2.1 methodology. We calculated intraclass correlation coefficients (ICC) as a measure of test-retest reliability. We then conducted a quality assessment and evaluated the adequacy of test-retest reliability performance. Results. Two datasets were identified for HAQ-DI and 1 for SF-36 PF in PsA. The quality of the datasets was good. The ICCs for HAQ-DI were good and excellent in study 1 (0.90, 95% CI 0.79–0.95) and study 2 (0.94, 95% CI 0.89–0.97). The ICC for SF-36 PF was excellent (0.96, 95% CI 0.92–0.98). The performance of test-retest reliability for both instruments was judged to be adequate. Conclusion. The new data derived support good and reasonable test-retest reliability for HAQ-DI and SF-36 PF in PsA.
PEI-modified diatomite/chitosan composites as bone tissue engineering scaffold for sustained release of BMP-2

Abstract The bone healing defects resulting from bone disease remain a significant clinical challenge. The bone tissue engineering scaffolds combined with osteoinductive compounds represent an effective approach to overcome this challenge. In this study, a novel chitosan-based scaffold was prepared by incorporating modified natural diatomite (DE) as filler and adsorption element. Specifically, modified-diatomite (MDE) was synthesized by grafting polyethyleneimine (PEI) on the surface of diatomite via hydroxyl groups. The physicochemical characteristics of MDE, including chemical composition, zeta potential, and adsorption behavior, were investigated successively. Further, the mechanical strength, drug release, cytotoxicity and osteogenic activity analyses were carried out for the scaffold material. The FTIR and zeta potential analyses exhibited that the amino groups (–NH2) were grafted on MDE, and the surface potential of diatomite altered from −24 mV to 55 mV. Subsequently, the protein adsorption capacity and cytocompatibility of MDE were observed to be improved as compared to DE. The compressive strength was observed to be enhanced due to the addition of MDE. Besides, the composite scaffold loaded with rhBMP-2 demonstrated a more positive impact on proliferation and osteogenic differentiation of the bone mesenchymal stem cells, thus, indicating an optimal bone regeneration capacity. The findings obtained in this study reveal that the MDE-rhBMP-2/CS composite scaffold can be potentially used to promote the bone tissue regeneration.
SRSF1 serves as a critical posttranscriptional regulator at the late stage of thymocyte development

RNA binding protein SRSF1 controls the development of late thymocytes via posttranscriptional regulation. The underlying mechanisms of thymocyte maturation remain largely unknown. Here, we report that serine/arginine-rich splicing factor 1 (SRSF1) intrinsically regulates the late stage of thymocyte development. Conditional deletion of SRSF1 resulted in severe defects in maintenance of late thymocyte survival and a blockade of the transition of TCRβhiCD24+CD69+ immature to TCRβhiCD24−CD69− mature thymocytes, corresponding to a notable reduction of recent thymic emigrants and diminished periphery T cell pool. Mechanistically, SRSF1 regulates the gene networks involved in thymocyte differentiation, proliferation, apoptosis, and type I interferon signaling pathway to safeguard T cell intrathymic maturation. In particular, SRSF1 directly binds and regulates Irf7 and Il27ra expression via alternative splicing in response to type I interferon signaling. Moreover, forced expression of interferon regulatory factor 7 rectifies the defects in SRSF1-deficient thymocyte maturation via restoring expression of type I interferon–related genes. Thus, our work provides new insight on SRSF1-mediated posttranscriptional regulatory mechanism of thymocyte development.
M-Payments, Financial Inclusion, and Full Market Coverage

Mobile payments (m-payments) increase the accessibility of large segments of society to financial services while before the traditional banking system excluded these for lack of proof of identity and because of unsafe environments. This constitutes a key driver of new growth strategies of the developing world. Smartphones are essential to perform m-payments. In that regard, recent criticism from different sides has expressed the view that manufacturers’ strategies generate partial market coverage whereby the purchase of a phone and financial inclusion also remain out of reach for the group of poor consumers. Our aim in this paper is to examine the theoretical premises of this conjecture in a small open economy and uncover the conditions under which full market coverage is efficient and desirable. We analyze subgame perfect equilibria of a vertical duopoly model characterized by consumers’ taste for quality. The government uses taxes and/or subsidies to modify the market equilibrium. Given this, the following issues are considered: (a) What is the impact of different standards of payment security on the equilibrium number of low-and high-quality users? (b) What are the aggregate welfare gains of complete financial inclusion? (c) What happens if phone makers are foreign?
Making Diabetes Care Fit—Are We Making Progress?

The care of patients with diabetes requires plans of care that make intellectual, practical, and emotional sense to patients. For these plans to fit well, patients and clinicians must work together to develop a common understanding of the patient’s problematic human situation and co-create a plan of care that responds well to it. This process, which starts at the point of care, needs to continue at the point of life. There, patients work to fit the demands of their care plan along with the demands placed by their lives and loves. Thought in this way, diabetes care goes beyond the control of metabolic parameters and the achievement of glycemic control targets. Instead, it is a highly individualized endeavor that must arrive at a care plan that reflects the biology and biography of the patient, the best available research evidence, and the priorities and values of the patient and her community. It must also be feasible within the life of the patient, minimally disrupting those aspects of the patient life that are treasured and justify the pursuit of care in the first place. Patient-centered methods such as shared decision making and minimally disruptive medicine have joined technological advances, patient empowerment, self-management support, and expert patient communities to advance the fit of diabetes care both at the point of care and at the point of life.
Artificial Intelligence for Prognostic Scores in Oncology: a Benchmarking Study

Introduction: Prognostic scores are important tools in oncology to facilitate clinical decision-making based on patient characteristics. To date, classic survival analysis using Cox proportional hazards regression has been employed in the development of these prognostic scores. With the advance of analytical models, this study aimed to determine if more complex machine-learning algorithms could outperform classical survival analysis methods. Methods: In this benchmarking study, two datasets were used to develop and compare different prognostic models for overall survival in pan-cancer populations: a nationwide EHR-derived de-identified database for training and in-sample testing and the OAK (phase III clinical trial) dataset for out-of-sample testing. A real-world database comprised 136K first-line treated cancer patients across multiple cancer types and was split into a 90% training and 10% testing dataset, respectively. The OAK dataset comprised 1,187 patients diagnosed with non-small cell lung cancer. To assess the effect of the covariate number on prognostic performance, we formed three feature sets with 27, 44 and 88 covariates. In terms of methods, we benchmarked ROPRO, a prognostic score based on the Cox model, against eight complex machine-learning models: regularized Cox, Random Survival Forests (RSF), Gradient Boosting (GB), DeepSurv (DS), Autoencoder (AE) and Super Learner (SL). The C-index was used as the performance metric to compare different models. Results: For in-sample testing on the real-world database the resulting C-index [95% CI] values for RSF 0.720 [0.716, 0.725], GB 0.722 [0.718, 0.727], DS 0.721 [0.717, 0.726] and lastly, SL 0.723 [0.718, 0.728] showed significantly better performance as compared to ROPRO 0.701 [0.696, 0.706]. Similar results were derived across all feature sets. However, for the out-of-sample validation on OAK, the stronger performance of the more complex models was not apparent anymore. Consistently, the increase in the number of prognostic covariates did not lead to an increase in model performance. Discussion: The stronger performance of the more complex models did not generalize when applied to an out-of-sample dataset. We hypothesize that future research may benefit by adding multimodal data to exploit advantages of more complex models.
Incidence and Costs of Personal and Property Crimes in the USA, 2017

Abstract Total cost estimates for crime in the USA are both out-of-date and incomplete. We estimated incidence and costs of personal crimes (both violent and non-violent) and property crimes in 2017. Incidence came from national arrest data, multi-state estimates of police-reported crimes per arrest, national victimization and road crash surveys, and police underreporting studies. We updated and expanded upon published unit costs. Estimated crime costs totaled $2.6 trillion ($620 billion in monetary costs plus quality of life losses valued at $1.95 trillion; 95 % uncertainty interval $2.2–$3.0 trillion). Violent crime accounted for 85 % of costs. Principal contributors to the 10.9 million quality-adjusted life years lost were sexual violence, physical assault/robbery, and child maltreatment. Monetary expenditures caused by criminal victimization represent 3 % of Gross Domestic Product – equivalent to the amount spent on national defense. These estimates exclude the additional costs of preventing and avoiding crime such as enhanced lighting and burglar alarms. They also exclude crimes against businesses and most white-collar and corporate offenses.
European and International Perspectives on Benefit-Cost Analysis: Symposium Introduction

Abstract The idea of assessing the costs and benefits of public and private projects is not new to Europe, dating back to studies at the Ecole des Ponts et Chaussees (Paris) in the XIX century. Later on, in the last century, Benefit-Cost Analysis (BCA) in its current form has been more extensively used in the United States than in Europe. In the last two decades, however, there has been a rapid increase in its use in a number of European countries and at the European Union (EU) level. European governments often undertake tasks that would be done by private companies in the United States, such as the provision of transport, energy, water and waste management, health services, etc. In the United States the focus of BCA has often been regulatory impact analysis, rather than public project evaluation. One might, therefore, expect that Europeans might approach some things differently from their American counterparts and that new insights might result from these efforts. The articles in this symposium, taken from the recent European Society for Benefit-Cost Analysis (SBCA) conference in Toulouse, illustrate some of these differences and some converging themes.
Multiple aspect trajectories: a case study on fishing vessels in the Northern Adriatic sea

In this paper we build, implement and analyze a spatio-temporal database describing the fishing activities in the Northern Adriatic Sea over four years. The database results from the fusion of two complementary data sources: trajectories from fishing vessels (obtained from terrestrial Automatic Identification System, or AIS, data feed) and the corresponding fish catch reports (i.e., the quantity and type of fish caught). We present all the phases of the dataset creation, starting from the raw data and proceeding through data exploration, data cleaning, trajectory reconstruction and semantic enrichment. Moreover, we formalise and compare different techniques to distribute the fish caught by the fishing vessels along their trajectories. We implement the database with MobilityDB, an open source geospatial trajectory data management and analysis platform. Subsequently, guided by our ecological experts, we perform some analyses on the resulting spatio-temporal database, with the goal of mapping the fishing activities on some key species, highlighting all the interesting information and inferring new knowledge that will be useful for fishery management.
An Automatic Participant Detection Framework for Event Tracking on Twitter

Topic Detection and Tracking (TDT) on Twitter emulates human identifying developments in events from a stream of tweets, but while event participants are important for humans to understand what happens during events, machines have no knowledge of them. Our evaluation on football matches and basketball games shows that identifying event participants from tweets is a difficult problem exacerbated by Twitter’s noise and bias. As a result, traditional Named Entity Recognition (NER) approaches struggle to identify participants from the pre-event Twitter stream. To overcome these challenges, we describe Automatic Participant Detection (APD) to detect an event’s participants before the event starts and improve the machine understanding of events. We propose a six-step framework to identify participants and present our implementation, which combines information from Twitter’s pre-event stream and Wikipedia. In spite of the difficulties associated with Twitter and NER in the challenging context of events, our approach manages to restrict noise and consistently detects the majority of the participants. By empowering machines with some of the knowledge that humans have about events, APD lays the foundation not just for improved TDT systems, but also for a future where machines can model and mine events for themselves.