Miracle-dz/UniFAR-FTUs huggingface dataset:
Whole-Exome Sequencing of Radiation-Induced Thymic Lymphoma in Mouse Models Identifies Notch1 Activation as a Driver of p53 Wild-Type Lymphoma

These findings reveal the mutational landscape and key drivers in murine radiation-induced thymic lymphoma, a classic animal model that has been used to study radiation carcinogenesis for over 70 years. Mouse models of radiation-induced thymic lymphoma are widely used to study the development of radiation-induced blood cancers and to gain insights into the biology of human T-cell lymphoblastic leukemia/lymphoma. Here we aimed to identify key oncogenic drivers for the development of radiation-induced thymic lymphoma by performing whole-exome sequencing using tumors and paired normal tissues from mice with and without irradiation. Thymic lymphomas from irradiated wild-type (WT), p53+/−, and KrasLA1 mice were not observed to harbor significantly higher numbers of nonsynonymous somatic mutations compared with thymic lymphomas from unirradiated p53−/− mice. However, distinct patterns of recurrent mutations arose in genes that control the Notch1 signaling pathway based on the mutational status of p53. Preferential activation of Notch1 signaling in p53 WT lymphomas was also observed at the RNA and protein level. Reporter mice for activation of Notch1 signaling revealed that total-body irradiation (TBI) enriched Notch1hi CD44+ thymocytes that could propagate in vivo after thymocyte transplantation. Mechanistically, genetic inhibition of Notch1 signaling in immature thymocytes prevented formation of radiation-induced thymic lymphoma in p53 WT mice. Taken together, these results demonstrate a critical role of activated Notch1 signaling in driving multistep carcinogenesis of thymic lymphoma following TBI in p53 WT mice. Significance: These findings reveal the mutational landscape and key drivers in murine radiation-induced thymic lymphoma, a classic animal model that has been used to study radiation carcinogenesis for over 70 years.
Feedforward modulation of gamma motor neuron activity can improve motor command accuracy

Objective. Coactivation of gamma and alpha motor neuron activity ensures that muscle spindle responsiveness is maintained during muscle contractions. However, some evidence suggests that the activity of gamma motor neurons is phase-advanced with respect to that of alpha motor neurons during manual control tasks. We hypothesized that this might be a deliberate control strategy to maximize movement accuracy. Approach. Using a computational model of the neural activation of a muscle and its type Ia sensory feedback to the motor neurons, we systematically investigated the impact of the phase difference between oscillatory descending input to alpha and dynamic gamma motor neurons. Specifically, the amplification of the alpha motor neuron drive to the muscle was investigated as a function of the frequency of the synaptic input (1–9 Hz individually or superimposed) and the alpha–gamma phase difference (0–2π). Main results. Simulation results showed that when the phase advance of the dynamic gamma drive resulted in delays between muscle velocity and type Ia afferent feedback similar to those previously observed experimentally, low-frequency components (1 and 2 Hz) of the motor neuron synaptic input were amplified (gain up to 1.7). On the other hand, synaptic input at higher frequencies was unaffected. Significance. This finding suggests that by imposing a phase advance of the input to dynamic gamma motor neurons, components of the neural drive usually associated with voluntary control are amplified. In this way, our study suggests that this neural strategy increases the control-to-neural-noise ratio of the motor output during movement.
Perinatal development of innate immune topology

At the transition from intrauterine to postnatal life, drastic alterations are mirrored by changes in cellular immunity. These changes are in part immune cell intrinsic, originate in the replacement of fetal cells, or result from global regulatory mechanisms and adaptation to changes in the tissue microenvironment. Overall, longer developmental trajectories are intersected by events related to mother-infant separation, birth cues, acquisition of microbiota and metabolic factors. Perinatal alterations particularly affect immune niches, where structures with discrete functions meet, the intestinal mucosa, epidermis and lung. Accordingly, the following questions will be addressed in this review: How does the preprogrammed development supported by endogenous cues, steer innate immune cell differentiation, adaptation to tissue structures, and immunity to infection? How does the transition at birth impact on tissue immune make-up including its topology? How do postnatal cues guide innate immune cell differentiation and function at immunological niches?
Tick salivary gland extract induces alpha‐gal syndrome in alpha‐gal deficient mice

Alpha‐gal syndrome (AGS) is characterized by delayed hypersensitivity to non‐primate mammalian meat in people having specific immunoglobulin E (sIgE) to the oligosaccharide galactose‐alpha‐1,3‐galactose. AGS has been linked to tick bites from Amblyomma americanum (Aa) in the U.S. A small animal model of meat allergy is needed to study the mechanism of alpha‐gal sensitization, the effector phase leading to delayed allergic responses and potential therapeutics to treat AGS.
Fragility-Confinement Effects: Apparent Universality as a Function of Scaled Thickness in Films of Freely Deposited, Linear Polymer and Its Absence in Densely Grafted Brushes

Ellipsometry measurements as a function of cooling rate are used to study nanoscale confinement effects on dynamic fragility (kinetic fragility), m, in supported films of freely deposited, linear polymer. Polymers include neat polystyrene (PS), neat polycarbonate (PC), and PS + 2 wt % 1,10-bis(1-pyrene)decane (BPD) as small-molecule diluent; in each case, the substrate/polymer interface lacks significant attractive interactions. In terms of both the length scale at which confinement effects become evident and the percentage reduction in m from its bulk value, the magnitude of the m-confinement effect increases with increasing bulk polymer system m. Additionally, for films of linear polymer lacking significant attractive interactions with the substrate surface, m-confinement effects are evident at larger onset thicknesses than those commonly reported in the literature for the glass transition temperature (Tg)-confinement effect. Evans et al. [Macromolecules 2013, 46, 6091] found that the Tg-confinement eff.
Too much death can kill you: inhibiting intrinsic apoptosis to treat disease

Apoptotic cell death is implicated in both physiological and pathological processes. Since many types of cancerous cells intrinsically evade apoptotic elimination, induction of apoptosis has become an attractive and often necessary cancer therapeutic approach. Conversely, some cells are extremely sensitive to apoptotic stimuli leading to neurodegenerative disease and immune pathologies. However, due to several challenges, pharmacological inhibition of apoptosis is still only a recently emerging strategy to combat pathological cell loss. Here, we describe several key steps in the intrinsic (mitochondrial) apoptosis pathway that represent potential targets for inhibitors in disease contexts. We also discuss the mechanisms of action, advantages and limitations of small‐molecule and peptide‐based inhibitors that have been developed to date. These inhibitors serve as important research tools to dissect apoptotic signalling and may foster new treatments to reduce unwanted cell loss.
Learning Semantic Segmentation of Large-Scale Point Clouds With Random Sampling

We study the problem of efficient semantic segmentation of large-scale 3D point clouds. By relying on expensive sampling techniques or computationally heavy pre/post-processing steps, most existing approaches are only able to be trained and operate over small-scale point clouds. In this paper, we introduce RandLA-Net, an efficient and lightweight neural architecture to directly infer per-point semantics for large-scale point clouds. The key to our approach is to use random point sampling instead of more complex point selection approaches. Although remarkably computation and memory efficient, random sampling can discard key features by chance. To overcome this, we introduce a novel local feature aggregation module to progressively increase the receptive field for each 3D point, thereby effectively preserving geometric details. Comparative experiments show that our RandLA-Net can process 1 million points in a single pass up to 200× faster than existing approaches. Moreover, extensive experiments on five large-scale point cloud datasets, including Semantic3D, SemanticKITTI, Toronto3D, NPM3D and S3DIS, demonstrate the state-of-the-art semantic segmentation performance of our RandLA-Net.
Searching for a dynamic equilibrium in decision making: the voices of adults with mild intellectual disability and their significant others in Hong Kong

Abstract Purpose The self-determination of people with intellectual disability (ID) is influenced by their interpersonal environment. This study set out to understand better the experience of Hong Kong adults with mild ID in exercising self-determination and to explore the relational and contextual dynamics of how they make decisions in conjunction with parents and paid carers. Method A qualitative study was conducted using focus groups for data collection. In total, 32 participants including people with mild ID, parents and rehabilitation personnel were recruited using purposive sampling. Five focus group discussions took place and the data were analysed using a thematic approach. Results Our findings highlight a continuum of autonomy in decision making in which participants with mild ID exercise different levels of autonomy in different contexts. In the triangular relationship with parents and rehabilitation personnel, all three parties are simultaneously looking to establish a dynamic equilibrium in decision making. Conclusions The study enriches our understanding of the relational and contextual considerations for people with ID in decision making. They may have their own priorities for all the decisions they make, but these involve a dynamic interaction between all three parties. Implications for Rehabilitation The search for dynamic equilibrium in decision-making is a new finding in studies of the self-determination of people with intellectual disability (ID). The findings embed the considerations of the roles of autonomy and relatedness in the self-determination of people with ID at the intrapersonal level. The findings highlight the importance of understanding the relational concerns people with ID have about those they respect while fostering their self-determination. It is also important to address the dynamic interactions among adults with ID, parents and rehabilitation personnel, and the efforts others make in facilitating the self-determination of people with ID.
The CYP19A1 (TTTA)n Repeat Polymorphism May Affect the Prostate Cancer Risk: Evidence from a Meta-Analysis

Abnormal aromatase (CYP19A1) expression may participate in prostate cancer (PCa) carcinogenesis. However, the results of studies on the CYP19A1 gene polymorphisms and PCa are conflicting. This meta-analysis aimed to systematically evaluate the associations between the CYP19A1 Arg264Cys polymorphism and the (TTTA)n repeat polymorphism and PCa. Electronic databases (PubMed, EmBase, ScienceDirect, and Cochrane Library) were comprehensively searched to identify eligible studies. The strength of the association between the Arg264Cys polymorphism and PCa was assessed by pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) in allelic, dominant, recessive, homozygous, and heterozygous genetic models. To analyze the impact of the (TTTA)n repeat polymorphism, we sequentially took the N-repeat allele (where N equals 7,8,10,11,12, and 13) as the minor allele and the sum of all the other alleles as the major allele. The ORs and 95% CIs were calculated in the allelic model; this analysis was performed individually for each repeat number. Pooled estimates of nine studies addressing the Arg264Cys polymorphism indicated that this polymorphism was not associated with PCa risk in the overall population or in the Caucasian or Asian subgroups. The 8-repeat allele in the (TTTA)n repeat polymorphism increased PCa risk in the overall population (OR = 1.34, 95% CI = 1.14–1.58, p = .001) and in the subgroup with population-based (PB) controls (OR = 1.41, 95% CI = 1.13–1.74, p = .002) as well as in the subgroup using capillary electrophoresis to identify this polymorphism (OR = 1.34, 95% CI = 1.09–1.65, p = .006). The meta-analysis indicated that the CYP19A1 (TTTA)n repeat polymorphism, but not the Arg264Cys polymorphism, may affect PCa risk.
3DCANN: A Spatio-Temporal Convolution Attention Neural Network for EEG Emotion Recognition

Since electroencephalogram (EEG) signals can truly reflect human emotional state, emotion recognition based on EEG has turned into a critical branch in the field of artificial intelligence. Aiming at the disparity of EEG signals in various emotional states, we propose a new deep learning model named three-dimension convolution attention neural network (3DCANN) for EEG emotion recognition in this paper. The 3DCANN model is composed of spatio-temporal feature extraction module and EEG channel attention weight learning module, which can extract the dynamic relation well among multi-channel EEG signals and the internal spatial relation of multi-channel EEG signals during continuous period time. In this model, the spatio-temporal features are fused with the weights of dual attention learning, and the fused features are input into the softmax classifier for emotion classification. In addition, we utilize SJTU Emotion EEG Dataset (SEED) to appraise the feasibility and effectiveness of the proposed algorithm. Finally, experimental results display that the 3DCANN method has superior performance over the state-of-the-art models in EEG emotion recognition.
Acute kidney injury: Incidence, risk factors, and outcomes in severe COVID-19 patients

Background COVID-19 is a multisystemic disorder that frequently causes acute kidney injury (AKI). However, the precise clinical and biochemical variables associated with AKI progression in patients with severe COVID-19 remain unclear. Methods We performed a retrospective study on 278 hospitalized patients who were admitted to the ward and intensive care unit (ICU) with COVID-19 between March 2020 and June 2020, at the University Hospital, São Paulo, Brazil. Patients aged ≥ 18 years with COVID-19 confirmed on RT-PCR were included. AKI was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) criteria. We evaluated the incidence of AKI, several clinical variables, medicines used, and outcomes in two sub-groups: COVID-19 patients with AKI (Cov-AKI), and COVID-19 patients without AKI (non-AKI). Univariate and multivariate analyses were performed. Results First, an elevated incidence of AKI (71.2%) was identified, distributed across different stages of the KDIGO criteria. We further observed higher levels of creatinine, C-reactive protein (CRP), leukocytes, neutrophils, monocytes, and neutrophil-to-lymphocyte ratio (NLR) in the Cov-AKI group than in the non-AKI group, at hospital admission. On univariate analysis, Cov-AKI was associated with older age (>62 years), hypertension, CRP, MCV, leucocytes, neutrophils, NLR, combined hydroxychloroquine and azithromycin treatment, use of mechanical ventilation, and vasoactive drugs. Multivariate analysis showed that hypertension and the use of vasoactive drugs were independently associated with a risk of higher AKI in COVID-19 patients. Finally, we preferentially found an altered erythrocyte and leukocyte cellular profile in the Cov-AKI group compared to the non-AKI group, at hospital discharge. Conclusions In our study, the development of AKI in patients with severe COVID-19 was related to inflammatory blood markers and therapy with hydroxychloroquine/azithromycin, with vasopressor requirement and hypertension considered potential risk factors. Thus, attention to the protocol, hypertension, and some blood markers may help assist doctors with decision-making for the management of COVID-19 patients with AKI.
Analysis of the coverage of inactivated enterovirus 71 (EV71) vaccine and adverse events following immunization with the EV71 vaccine among children from 2016 to 2019 in Guangzhou

ABSTRACT Background: Since 2016, China has approved the use of inactivated enterovirus 71 (EV71) vaccines produced by three manufacturers. The coverage and safety of different EV71 vaccines need to be evaluated. Research design and methods: The EV71 vaccination and AEFI data were collected from the Guangzhou Children’s Vaccination Information Report Management System and the China AEFI Monitoring Information Management System, and the EV71 vaccine coverage rate and the AEFI incidence rate were analyzed. Results: From 2016 to 2019, the number of people who should have been vaccinated in Guangzhou was 2,781,618, and the coverage rates for doses 1 and 2 were 24.71% and 19.44%, respectively. The inoculation rates of vaccines from manufacturers A and B were between 3.03 and 10.46%. The reported incidence of AEFIs was 11.97 per 100,000 (147 cases), with fever (106 cases, 8.63 per 100,000) and allergic rash (59 cases, 4.80 per 100,000) being the most common reactions. There were no differences in the AEFI responses to the EV71 vaccines from the three manufacturers. Conclusion: The EV71 vaccines from the three manufacturers have good safety, but the EV71 vaccine coverage rate is low. It is recommended that vaccine publicity be strengthened and that the vaccine coverage rate in children be increased.
Assessing the Feasibility of an Open-Source Virtual Reality Mirror Visual Feedback Module for Complex Regional Pain Syndrome: Pilot Usability Study

Background Complex regional pain syndrome (CRPS) is a rare and severe chronic pain condition, with effective treatment options not established for many patients. The underlying pathophysiology remains unclear, but there is a growing appreciation for the role of central mechanisms which have formed the basis for brain-based therapies such as transcranial magnetic stimulation and mirror visual feedback (MVF). MVF has been deployed in the treatment of CRPS using both conventional mirrors and virtual reality (VR). Objective The aim of this study was to further investigate the use of VR in the treatment of patients with unilateral upper limb CRPS. VR has the potential advantage of more flexible and more motivating tasks, as well as the option of tracking patient improvement through the use of movement data. Methods We describe the development, acceptability, feasibility, and usability of an open-source VR program MVF module designed to be used with consumer VR systems for the treatment of CRPS. The development team was an interdisciplinary group of physical therapists, pain researchers, and VR researchers. Patients recruited from a pain clinic completed 3-5 visits each to trial the system and assessed their experiences in pre- and post-treatment questionnaires. Results All 9 (100%) participants were able to use the system for 3, 4, or 5 trials each. None of the participants quit any trial due to cybersickness. All 9 (100%) participants reported interest in using the module in the future. Participants’ reported average pain scores in the affected limb were not significantly different from baseline during treatment or after treatment (P=.16). We did not find a statistically significant effect on participants’ self-reported average pain scores. Conclusions We propose that this module could be a useful starting point for modification and testing for other researchers. We share modifications to make this module usable with standalone headsets and finger tracking. Next steps include adapting this module for at-home use, or for use with participants with lower limb pain.
Changes in measures of cognitive function in patients with end-stage kidney disease on dialysis and the effect of dialysis vintage: A longitudinal cohort study

Introduction Prevalence of cognitive impairment increases with worsening severity of chronic kidney disease (CKD) and majority of end-stage kidney disease (ESKD) patients on dialysis have cognitive impairment. Trends of cognitive function (CF) in this population are less well known with published studies reporting conflicting results. Methods We assessed CF in a cohort of non-dialysis CKD and ESKD patients undergoing dialysis using modified mini-mental state examination (3MS), trail-making test (TMT-A & B) scores and Stroop task, and evaluated demographics, comorbidities and depression using Beck depression inventory at baseline. We repeated tests of CF and depression ≥ 1-year after baseline in both groups and compared change scores in CF and depression between ESKD/ CKD sub-groups. Among ESKD patients we compared change scores between patients with dialysis vintage of <1-year and >1-year. Analysis of covariance was used to adjust for the effect of age on these change scores. Results At baseline (N = 211), compared to CKD (N = 108), ESKD (N = 103) patients had significantly worse CF based on 3MS and TMT-A & B scores, and depression scores. On follow-up (N = 160) 3MS scores, especially the memory subscale significantly improved in ESKD, but worsened in CKD, with no significant changes in TMT A /TMT-B, or depression scores after adjusting for age. Among ESKD patients, 3MS, especially memory subscale improved in patients with dialysis vintage <1-year compared to >1-year. The 51 patients who discontinued after baseline assessment had worse baseline CF scores suggesting differential attrition. Conclusion Though baseline cognitive scores were worse in ESKD patients on dialysis, compared to CKD, their 3MS, especially memory subscale improved on follow-up. Among ESKD patients, the improvement was significant only in patients who have been on dialysis for less than one-year which may indicate a beneficial effect of clearance of uraemic toxins. Differential attrition of study subjects may have impacted the observed results.
Classification of Alzheimer’s Disease Using Ensemble of Deep Neural Networks Trained Through Transfer Learning

Alzheimer’s disease (AD) is one of the deadliest neurodegenerative diseases ailing the elderly population all over the world. An ensemble of Deep learning (DL) models can learn highly complicated patterns from MRI scans for the detection of AD by utilizing diverse solutions. In this work, we propose a computationally efficient, DL-architecture agnostic, ensemble of deep neural networks, named ‘Deep Transfer Ensemble (DTE)’ trained using transfer learning for the classification of AD. DTE leverages the complementary feature views and diversity introduced by many different locally optimum solutions reached by individual networks through the randomization of hyper-parameters. DTE achieves an accuracy of 99.05% and 85.27% on two independent splits of the large dataset for cognitively normal (NC) vs AD classification task. For the task of mild cognitive impairment (MCI) vs AD classification, DTE achieves 98.71% and 83.11% respectively on the two independent splits. It also performs reasonable on a small dataset consisting of only 50 samples per class. It achieved a maximum accuracy of 85% for NC vs AD on the small dataset. It also outperformed snapshot ensembles along with several other existing deep models from similar kind of previous works by other researchers.