Miracle-dz/UniFAR-FTUs huggingface dataset:
Shoulder Rehabilitation Exercises With Kinematic Biofeedback After Arthroscopic Rotator Cuff Repair: Protocol for a New Integrated Rehabilitation Program

Background The recovery of scapular and humeral physiological kinematic parameters, as well as the sensorimotor control of movement, plays a primary role in the rehabilitation process after arthroscopic rotator cuff repair. A highly customized rehabilitation approach is required to achieve this aim. Biofeedback can be a useful tool, but there is poor evidence of its application in the rehabilitation after arthroscopic rotator cuff tear repair. Objective The aim of this paper is to outline an innovative exercise-based rehabilitation program exploiting visual biofeedback for the recovery of patients arthroscopically treated for rotator cuff repair. Methods For establishment of the innovative program, a multidisciplinary team involving experts in shoulder surgery, rehabilitation medicine, physical therapy, and biomedical and clinical engineering was formed. Starting from a conventional rehabilitation program, the team selected a set of exercises to be integrated with a biofeedback tool, named the INAIL (National Institute for Insurance against Accidents at Work) Shoulder and Elbow Outpatient program (ISEO program). ISEO is a motion analysis system based on inertial wearable sensors positioned over the thorax, scapula, humerus, and forearm. ISEO can return a visual biofeedback of humerus and scapula angles over time or of the scapula-humeral coordination, with possible overlap of patient-specific or asymptomatic reference values. A set of 12 progressive exercises was defined, divided into four groups based on humerus and scapula movements. Each group comprises 2-4 of the 12 exercises with an increasing level of complexity. Exercises can require the use of a ball, stick, rubber band, and/or towel. For each exercise, we present the starting position of the patient, the modality of execution, and the target position, together with notes about the critical factors to observe. The type of visual biofeedback to adopt is specified, such as the coordination between angles or the variation of a single angle over time. To guide the therapist in customizing the patient’s rehabilitation program, a list of operative guidelines is provided. Results We describe various applications of the ISEO exercise program in terms of frequency and intensity. Conclusions An innovative rehabilitation program to restore scapular and humeral kinematics after rotator cuff repair based on kinematic biofeedback is presented. Biofeedback is expected to increase patient awareness and self-correction under therapist supervision. Randomized controlled trials are needed to investigate the potential effect of the exercise-based biofeedback in comparison with conventional rehabilitation programs. International Registered Report Identifier (IRRID) DERR1-10.2196/35757
Discrimination of Liver Metastases of Digestive System Neuroendocrine Tumors From Neuroendocrine Carcinoma by Computed Tomography–Based Radiomics Analysis

Objective The aim of the study is to investigate the value of computed tomography (CT) radiomics features to discriminate the liver metastases (LMs) of digestive system neuroendocrine tumors (NETs) from neuroendocrine carcinoma (NECs). Methods Ninety-nine patients with LMs of digestive system neuroendocrine neoplasms from 2 institutions were included. Radiomics features were extracted from the portal venous phase CT images by the Pyradiomics and then selected by using the t test, Pearson correlation analysis, and least absolute shrinkage and selection operator method. The radiomics score (Rad score) for each patient was constructed by linear combination of the selected radiomics features. The radiological model was constructed by radiological features using the multivariable logistic regression. Then, the combined model was constructed by combining Rad score and the radiological model into logistic regression. The performance of all models was evaluated by the receiver operating characteristic curves with the area under curve (AUC). Results In the radiological model, only the enhancement degree (odds ratio, 8.299; 95% confidence interval, 2.070–32.703; P = 0.003) was an independent predictor for discriminating the LMs of digestive system NETs from those of NECs. The combined model constructed by the Rad score in combination with the enhancement degree showed good discrimination performance, with AUCs of 0.893, 0.841, and 0.740 in the training, testing, and external validation groups, respectively. In addition, it performed better than radiological model in the training and testing groups (AUC, 0.893 vs 0.726; AUC, 0.841 vs 0.621). Conclusions The CT radiomics might be useful for discrimination LMs of digestive system NECs from NETs.
Staphylococcus aureus FadB is a dehydrogenase that mediates cholate resistance and survival under human colonic conditions

Staphylococcus aureus is a common colonizer of the human gut and in doing so it must be able to resist the actions of the host’s innate defences. Bile salts are a class of molecules that possess potent antibacterial activity that control growth. Bacteria that colonize and survive in that niche must be able to resist the action of bile salts, but the mechanisms by which S. aureus does so are poorly understood. Here we show that FadB is a bile-induced oxidoreductase which mediates bile salt resistance and when heterologously expressed in Escherichia coli renders them resistant. Deletion of fadB attenuated survival of S. aureus in a model of the human distal colon.
Decoding firings of a large population of human motor units from high‐density surface electromyogram in response to transcranial magnetic stimulation

We describe a novel application of methodology for high‐density surface electromyography (HDsEMG) decomposition to identify motor unit (MU) firings in response to transcranial magnetic stimulation (TMS). The method is based on the MU filter estimation from HDsEMG decomposition with convolution kernel compensation during voluntary isometric contractions and its application to contractions elicited by TMS. First, we simulated synthetic HDsEMG signals during voluntary contractions followed by simulated motor evoked potentials (MEPs) recruiting an increasing proportion of the motor pool. The estimation of MU filters from voluntary contractions and their application to elicited contractions resulted in high (>90%) precision and sensitivity of MU firings during MEPs. Subsequently, we conducted three experiments in humans. From HDsEMG recordings in first dorsal interosseous and tibialis anterior muscles, we demonstrated an increase in the number of identified MUs during MEPs evoked with increasing stimulation intensity, low variability in the MU firing latency and a proportion of MEP energy accounted for by decomposition similar to voluntary contractions. A negative relationship between the MU recruitment threshold and the number of identified MU firings was exhibited during the MEP recruitment curve, suggesting orderly MU recruitment. During isometric dorsiflexion we also showed a negative association between voluntary MU firing rate and the number of firings of the identified MUs during MEPs, suggesting a decrease in the probability of MU firing during MEPs with increased background MU firing rate. We demonstrate accurate identification of a large population of MU firings in a broad recruitment range in response to TMS via non‐invasive HDsEMG recordings.
Efficient non-viral delivery of macromolecules in human primary hematopoietic stem cells and lymphocytes

1 State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming 650091, China 2 Department of Rheumatology and Immunology, Medical Research Institute, Frontier Science Center for Immunology and Metabolism, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan 430071, China 3 State Key Laboratory of Virology, Wuhan University, Wuhan 430071, China * Correspondence to: Ying Zhang, E-mail: ying.zhang84@whu.edu. cn; Ke-Qin Zhang, E-mail: kqzhang1@ynu.edu. cn
Haemophilia item bank based on International Classification of Functioning, Disability and Health: a systematic review

ABSTRACT Background and Objectives Haemophilia comprises a continuum of blood disorders that often include joint and muscular dysfunction, which may lead to a constellation of activity limitations and participation restrictions. However, there is scant research incorporating functional assessment scales into the common language provided by the International Classification of Functioning, Disability and Health (ICF). This study aims to identify the ICF categories to include in an item bank of functioning aspects relevant for haemophilia. Design and Methods A systematic search was carried out in July 2021 based on the PubMed MEDLINE, CLINICAL, and Cochrane databases for qualified articles, investigating haemophilia-specific scales and the scales recommended by the World Federation of Haemophilia (WFH) linked to ICF categories between 2001 and 2021. Well-trained healthcare professionals in the haemophilia field and ICF evaluation conducted group discussions to determine the ICF items for haemophilia. Results A total of 112 out of 176 items measuring function were collected for the haemophilia ICF item bank, including 32 items for body function (b), 45 items for activity and participation (d), 27 items for environmental factors (e), and 8 items for body structure(s). Interpretation and Conclusions We recommend that future haemophilia research use the haemophilia-specific ICF item bank, which could capture a whole spectrum of functional measurements and facilitate multidisciplinary and worldwide communication. This study also indicates that further development and analysis of the psychometric properties of the 112 haemophilia-related ICF items is warranted.
Degradation of Ubiquitin-Editing Enzyme A20 following Autophagy Activation Promotes RNF168 Nuclear Translocation and NF-κB Activation in Lupus Nephritis

The correlation between ubiquitin-editing enzyme A20 and E3 ubiquitin ligase ring finger protein (RNF) 168 has been reported to be critical for repair of DNA damage. This study aimed to evaluate the potential role of this regulatory interaction in the pathogenesis of lupus nephritis (LN). The expression of RNF168 and A20 was measured in the podocytes derived from MRL/lpr murine lupus as well as patients with LN. Cell-based studies using renal podocytes bearing silenced RNF168, over-expressed A20, autophagy-related gene (Atg) 5 (a ubiquitin-like modifier), or silenced Atg5 were used to assess the effect of RNF168, A20, and Atg5 on DNA damage repair and nuclear factor kappa-B (NF-κB) activation in LN. It was found that podocyte autophagy was over-activated in LN and the abnormal podocyte autophagy led to down-regulation of A20, up-regulation of RNF168, and activation of the NF-κB. RNF168 silencing or A20 restoration inhibited activation of NF-κB pathway and promoted repair of DNA damage, where the level of autophagy was not changed. Activated A20 in podocytes weakened the promoting action of cell autophagy on RNF168. The current results suggest that RNF168 dysfunction may be involved in the pathogenesis of LN via down-regulation of A20 expression. Autophagy and RNF168 may be therapeutic targets for the prevention and treatment of LN.
Review of economic modeling evidence from NICE appraisals of rare disease treatments for spinal muscular atrophy

ABSTRACT Introduction The National Institute for Health and Care Excellence (NICE) in England has appraised three treatments for spinal muscular atrophy (SMA), namely, nusinersen, onasemnogene abeparvovec, and risdiplam. As rare disease treatments (RDTs) commonly face challenges in health technology assessment (HTA) processes due to their clinical and economic uncertainties, an in-depth review of these appraisals is useful to enable a deeper understanding of economic modeling considerations for SMA. Areas covered This review is a detailed analysis of NICE appraisals for SMA and aims to compare the economic modeling evidence from the three RDTs. This is done by examining differences and similarities and by discussing critical outstanding issues across the economic evaluations of the appraisals. Expert opinion This article aims to contribute to the development of evidence that can be used as guidance to inform resource allocation decisions for RDTs for SMA, but also to be a resource about approaches for the generation, analysis and interpretation of economic modeling evidence for RDTs more broadly.
The Perceptual Science of Augmented Reality.

Augmented reality (AR) systems aim to alter our view of the world and enable us to see things that are not actually there. The resulting discrepancy between perception and reality can create compelling entertainment and can support innovative approaches to education, guidance, and assistive tools. However, building an AR system that effectively integrates with our natural visual experience is hard. AR systems often suffer from visual limitations and artifacts, and addressing these flaws requires basic knowledge of perception. At the same time, AR system development can serve as a catalyst that drives innovative new research in perceptual science. This review describes recent perceptual research pertinent to and driven by modern AR systems, with the goal of highlighting thought-provoking areas of inquiry and open questions. Expected final online publication date for the Annual Review of Vision Science, Volume 9 is September 2023. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
The role of executive function deficits, delay aversion and emotion dysregulation in internet gaming disorder and social media disorder: Links to psychosocial outcomes

Abstract Background and aims It has been argued that it is important to consider underlying mechanisms of mental health problems. Previous studies have shown that executive deficits, delay aversion, and emotion dysregulation are related to Internet Gaming Disorder (IGD) and Social Media Disorder (SMD). However, the present study is the first to investigate whether these neuropsychological deficits show additive effects or if they interact. The present study also investigated whether these deficits mediate the association between IGD/SMD and psychosocial outcomes. Methods The study involved 995 university students who completed a survey measuring IGD/SMD symptom severity, neuropsychological functions, and psychosocial outcomes. Both dimensional and categorical analyses were used to assess the associations between neuropsychological functions and IGD/SMD. Simple and multiple mediation analyses were conducted to examine if neuropsychological functioning mediates the association between IGD/SMD and psychosocial outcomes. Results All neuropsychological functions were significantly associated with both IGD and SMD symptom severity. However, only inhibition and emotion regulation, as well as delay aversion for SMD, remained significant when controlling for the overlap between different functions. Associations were significantly stronger for men compared to women for IGD. In the categorical analyses, individuals with IGD/SMD were more likely to have neuropsychological deficits (odds ratios between 3.33 and 8.81). Finally, all neuropsychological functions, except inhibition, were significant mediators in the link between IGD/SMD and psychosocial outcomes. Discussion and conclusions These results shed light on the neuropsychological underpinnings of IGD/SMD, which can be used to identify more homogenous subgroups and provide more individualized treatment options.
Empirical Likelihood Local Polynomial Regression Analysis of Clustered Data

Abstract. In this article, a naive empirical likelihood ratio is constructed for a non‐parametric regression model with clustered data, by combining the empirical likelihood method and local polynomial fitting. The maximum empirical likelihood estimates for the regression functions and their derivatives are obtained. The asymptotic distributions for the proposed ratio and estimators are established. A bias‐corrected empirical likelihood approach to inference for the parameters of interest is developed, and the residual‐adjusted empirical log‐likelihood ratio is shown to be asymptotically chi‐squared. These results can be used to construct a class of approximate pointwise confidence intervals and simultaneous bands for the regression functions and their derivatives. Owing to our bias correction for the empirical likelihood ratio, the accuracy of the obtained confidence region is not only improved, but also a data‐driven algorithm can be used for selecting an optimal bandwidth to estimate the regression functions and their derivatives. A simulation study is conducted to compare the empirical likelihood method with the normal approximation‐based method in terms of coverage accuracies and average widths of the confidence intervals/bands. An application of this method is illustrated using a real data set.
Asymptotic analysis of a state-dependent M / G /1 queueing system

We present new asymptotic methods for the analysis of queueing systems. These methods are applied to a state-dependent $M/G/1$ queue. We formulate problems for and compute approximations to (i) the stationary density of the unfinished work; (ii) the mean length of time until the end of a busy period; (iii) the mean length of a busy period; and (iv) the mean time until the unfinished work reaches or exceeds a specified capacity. The methods are applied to the full Kolmogorov equations, scaled so that the arrival rate is rapid and the mean service is small. Thus, we do not truncate equations as in diffusion approximations. For state-independent $M/G/1$ queues, our results are shown to agree with the known exact solutions. We include comparisons, both analytic and numerical, between our results and those obtained from diffusion approximations.
Kinetics of Arf1 inactivation regulates Golgi organisation and function in non-adherent fibroblasts

ABSTRACT Arf1 belongs to the Arf family of small GTPases that localise at the Golgi and plasma membrane. Active Arf1 plays a crucial role in regulating Golgi organisation and function. In mouse fibroblasts, loss of adhesion triggers a consistent drop (∼50%) in Arf1 activation that causes the Golgi to disorganise but not fragment. In suspended cells, the trans-Golgi (GalTase) disperses more prominently than cis-Golgi (Man II), accompanied by increased active Arf1 (detected using GFP-ABD: ARHGAP10 Arf1 binding domain) associated with the cis-Golgi compartment. Re-adhesion restores Arf1 activation at the trans-Golgi as it reorganises. Arf1 activation at the Golgi is regulated by Arf1 Guanine nucleotide exchange factors (GEFs), GBF1, and BIG1/2. In non-adherent fibroblasts, the cis-medial Golgi provides a unique setting to test and understand the role GEF-mediated Arf1 activation has in regulating Golgi organisation. Labelled with Man II-GFP, non-adherent fibroblasts treated with increasing concentrations of Brefeldin-A (BFA) (which inhibits BIG1/2 and GBF1) or Golgicide A (GCA) (which inhibits GBF1 only) comparably decrease active Arf1 levels. They, however, cause a concentration-dependent increase in cis-medial Golgi fragmentation and fusion with the endoplasmic reticulum (ER). Using selected BFA and GCA concentrations, we find a change in the kinetics of Arf1 inactivation could mediate this by regulating cis-medial Golgi localisation of GBF1. On loss of adhesion, a ∼50% drop in Arf1 activation over 120 min causes the Golgi to disorganise. The kinetics of this drop, when altered by BFA or GCA treatment causes a similar decline in Arf1 activation but over 10 min. This causes the Golgi to now fragment which affects cell surface glycosylation and re-adherent cell spreading. Using non-adherent fibroblasts this study reveals the kinetics of Arf1 inactivation, with active Arf1 levels, to be vital for Golgi organisation and function.
Using a New Deep Learning Method for 3D Cephalometry in Patients With Cleft Lip and Palate

Deep learning algorithms based on automatic 3-dimensional (D) cephalometric marking points about people without craniomaxillofacial deformities has achieved good results. However, there has been no previous report about cleft lip and palate. The purpose of this study is to apply a new deep learning method based on a 3D point cloud graph convolutional neural network to predict and locate landmarks in patients with cleft lip and palate based on the relationships between points. The authors used the PointNet++ model to investigate the automatic 3D cephalometric marking points. And the mean distance error of the center coordinate position and the success detection rate (SDR) were used to evaluate the accuracy of systematic labeling. A total of 150 patients were enrolled. The mean distance error for all 27 landmarks was 1.33 mm, and 9 landmarks (30%) showed SDRs at 2 mm over 90%, and 3 landmarks (35%) showed SDRs at 2 mm under 70%. The automatic 3D cephalometric marking points take 16 seconds per dataset. In summary, our training sets were derived from the cleft lip with/without palate computed tomography to achieve accurate results. The 3D cephalometry system based on the graph convolutional neural network algorithm may be suitable for 3D cephalometry system in cleft lip and palate cases. More accurate results may be obtained if the cleft lip and palate training set is expanded in the future.
Geometric error correction of convergent multi-view images

A geometric error correction of convergent multi-view images is proposed. Shape factors and camera parameters of the captured multi-view image are used to estimate an ideal multi-camera arrangement and its camera parameters. A correction transform of each viewpoint to reduce the geometric error is calculated based on the original and estimated camera parameters. The error-corrected multi-view image is obtained by applying the transform to the captured images. The experimental results show that the proposed method efficiently reduces the geometric error of the convergent multi-view images.
Resistance Training Improves Hypertrophic and Mitochondrial Adaptation in Skeletal Muscle

Abstract Resistance training is employed for pursuing muscle strength characterized by activation of mammalian target of rapamycin (mTOR)-mediated hypertrophic signaling for protein production. Endurance training elevates peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α) signaling of mitochondrial adaptations for oxidative phosphorylation. Now, emerging evidence suggests that, like endurance training, resistance training also elicits profound effects on mitochondrial adaptations in skeletal muscle, which means that resistance training yields both strength and endurance phenotypes in myofibers, which has treatment value for the muscle loss and poor aerobic capacity in humans. Our review outlines a brief overview of muscle hypertrophic signals with resistance training, and focuses on the effects of resistance training on mitochondrial biogenesis and respiration in skeletal muscle. This study provides novel insights into the therapeutic strategy of resistance training for the metabolically dysfunctional individuals with declined mitochondrial function.
A c-di-GMP binding effector controls cell size in a cyanobacterium

Significance Cell size homeostasis is an essential physical trait of bacteria, and how the cell size is maintained and regulated remains an important question in microbiology. We recently found that the second messenger c-di-GMP may be an intracellular proxy for cell size control in Anabaena. In this study, we identified and characterized a highly conserved c-di-GMP receptor in cyanobacteria and demonstrated that it regulates cell size via interaction with the transcription factor DevH in Anabaena. These findings not only provide a mechanism of cell size regulation but also extend the role of c-di-GMP receptors in bacteria. Since c-di-GMP plays broad functions in cyanobacteria, our pioneering study constitutes a basis for studies on c-di-GMP signaling in these organisms.