Miracle-dz/UniFAR-FTUs huggingface dataset:
T cells are present in non-diabetic islets and accumulate during aging

Background The resident immune population of pancreatic islets has roles in islet development, beta cell physiology, and the pathology of diabetes. These roles have largely been attributed to islet macrophages, comprising 90% of islet immune cells (in the absence of islet autoimmunity), and, in the case of type 1 diabetes, to infiltrating autoreactive T cells. In adipose, tissue-resident and recruited T and B cells have been implicated in the development of insulin resistance during diet-induced obesity and aging, but whether this is paralleled in the pancreatic islets is not known. Here, we investigated the non-macrophage component of resident islet immune cells in islets isolated from C57BL/6J male mice during aging (3 to 24 months of age) and following diet-induced obesity (12 weeks 60% high fat diet). Immune cells were also examined by flow cytometry in cadaveric non-diabetic human islets. Results Immune cells comprised 2.7 ± 1.3% of total islet cells in non-diabetic mouse islets, and 2.3 ± 1.7% of total islet cells in non-diabetic human islets. In 3-month old mice on standard diet, B and T cells each comprised approximately 2-4% of the total islet immune cell compartment, and approximately 0.1% of total islet cells. A similar amount of T cells were present in non-diabetic human islets. Islet T cells were comprised of CD8-positive, CD4-positive, and regulatory T cells. Interestingly, while islet B cells and macrophage numbers were unaltered by age, the number of islet T cells increased linearly (R2=0.9902) with age from 0.10 ± 0.05% (3 months) to 0.38 ±0.11% (24 months) of islet cells. This increase was uncoupled from body weight, and was not phenocopied by a degree similar weight gain induced by high fat diet in mice. Conclusions This study reveals that T cells are a part of the normal islet immune population in mouse and human islets, and that they accumulate in islets during aging in a body weight-independent manner. Though comprising only a small subset of the immune cells within islets, islet T cells may play a role in the physiology of islet aging.
Identifying transcription patterns of histology and radiomics features in NSCLC with neural networks

Purpose To investigate the use of deep neural networks to learn associations between gene expression and radiomics or histology in non-small cell lung cancer (NSCLC). Materials and Methods Deep feedforward neural networks were used for radio-genomic mapping, where 21,766 gene expressions were inputs to individually predict histology and 101 CT radiomic features. Models were compared against logistic regression, support vector machines, random forests, and gradient boosted trees on 262 training and 89 testing patients. Neural networks were interpreted using gene masking to derive the learned associations between subsets of gene expressions to a radiomic feature or histology type. Results Neural networks outperformed other classifiers except in five radiomic features, where training differences were <0.026 AUC. In testing, neural networks classified histology with AUCs of 0.86 (adenocarcinoma), 0.91 (squamous), and 0.71 (other); and 14 radiomics features with >= 0.70 AUC. Gene masking of the models showed new and previously reported histology-gene or radiogenomic associations. For example, hypoxia genes could predict histology with >0.90 test AUC and published gene signatures for histology prediction were also predictive in our models (>0.80 test AUC). Gene sets related to the immune or cardiac systems and cell development processes were predictive (>0.70 test AUC) of several different radiomic features while AKT signaling, TNF, and Rho gene sets were each predictive of tumor textures. Conclusion We demonstrate the ability of neural networks to map gene expressions to radiomic features and histology in NSCLC and interpret the models to identify predictive genes associated with each feature or type. Author Summary Non-small-cell lung cancer (NSCLC) patients can have different presentations as seen in the CT scans, tumor gene expressions, or histology types. To improve the understanding of these complementary data types, this study attempts to map tumor gene expressions associated with a patient’s CT radiomic features or a histology type. We explore a deep neural network approach to learn gene-radiomic associations (i.e., the subsets of co-expressed genes that are predictive of a value of an individual radiomic feature) and gene-histology associations in two separate public cohorts. Our modeling approach is capable of learning relevant information by showing the model can predict histology and that the learned relationships are consistent with prior works. The study provides evidence for coherent patterns between gene expressions and radiomic features and suggests such integrated associations could improve patient stratification.
Two-dimensional video-based analysis of human gait using pose estimation

Walking is the primary mode of human locomotion. Accordingly, people have been interested in studying human gait since at least the fourth century BC. Human gait analysis is now common in many fields of clinical and basic research, but gold standard approaches – e.g., three-dimensional motion capture, instrumented mats or footwear, and wearables – are often expensive, immobile, data-limited, and/or require specialized equipment or expertise for operation. Recent advances in video-based pose estimation have suggested exciting potential for analyzing human gait using only two-dimensional video inputs collected from readily accessible devices (e.g., smartphones, tablets). However, we currently lack: 1) data about the accuracy of video-based pose estimation approaches for human gait analysis relative to gold standard measurement techniques and 2) an available workflow for performing human gait analysis via video-based pose estimation. In this study, we compared a large set of spatiotemporal and sagittal kinematic gait parameters as measured by OpenPose (a freely available algorithm for video-based human pose estimation) and three-dimensional motion capture from trials where healthy adults walked overground. We found that OpenPose performed well in estimating many gait parameters (e.g., step time, step length, sagittal hip and knee angles) while some (e.g., double support time, sagittal ankle angles) were less accurate. We observed that mean values for individual participants – as are often of primary interest in clinical settings – were more accurate than individual step-by-step measurements. We also provide a workflow for users to perform their own gait analyses and offer suggestions and considerations for future approaches.
Fusion of Hyperspectral CASI and Airborne LiDAR Data for Ground Object Classification through Residual Network

Modern satellite and aerial imagery outcomes exhibit increasingly complex types of ground objects with continuous developments and changes in land resources. Single remote-sensing modality is not sufficient for the accurate and satisfactory extraction and classification of ground objects. Hyperspectral imaging has been widely used in the classification of ground objects because of its high resolution, multiple bands, and abundant spatial and spectral information. Moreover, the airborne light detection and ranging (LiDAR) point-cloud data contains unique high-precision three-dimensional (3D) spatial information, which can enrich ground object classifiers with height features that hyperspectral images do not have. Therefore, the fusion of hyperspectral image data with airborne LiDAR point-cloud data is an effective approach for ground object classification. In this paper, the effectiveness of such a fusion scheme is investigated and confirmed on an observation area in the middle parts of the Heihe River in China. By combining the characteristics of hyperspectral compact airborne spectrographic imager (CASI) data and airborne LiDAR data, we extracted a variety of features for data fusion and ground object classification. Firstly, we used the minimum noise fraction transform to reduce the dimensionality of hyperspectral CASI images. Then, spatio-spectral and textural features of these images were extracted based on the normalized vegetation index and the gray-level co-occurrence matrices. Further, canopy height features were extracted from airborne LiDAR data. Finally, a hierarchical fusion scheme was applied to the hyperspectral CASI and airborne LiDAR features, and the fused features were used to train a residual network for high-accuracy ground object classification. The experimental results showed that the overall classification accuracy was based on the proposed hierarchical-fusion multiscale dilated residual network (M-DRN), which reached an accuracy of 97.89%. This result was found to be 10.13% and 5.68% higher than those of the convolutional neural network (CNN) and the dilated residual network (DRN), respectively. Spatio-spectral and textural features of hyperspectral CASI images can complement the canopy height features of airborne LiDAR data. These complementary features can provide richer and more accurate information than individual features for ground object classification and can thus outperform features based on a single remote-sensing modality.
Development of predictive QSAR models on the phosphopeptide binding affinity against 14-3-3 isoforms

14-3-3s present in multiple isoforms in human cells and mediate signal transduction by binding to phosphoserine-containing proteins. Recent findings have demonstrated that 14-3-3s act as a key factor in promoting chemoresistance of cancer. Here, we aimed to develop the predictive models that can determine the binding affinity of phosphopeptide fragments against 14-3-3s. It is found that the hydrophobic property of residues in phosphopeptides has a significant contribution to the binding affinity for most of 14-3-3 isoforms. The conserved patterns of 14-3-3 biding motifs were verified by our predictions. A group of peptide sequences were predicted with high binding affinity and high sequence conservation, which had agreement with 14-3-3s ligands. Overall, our results demonstrate that how the residues are likely to function in 14-3-3s interaction and the computational methods we introduced may contribute to the further research.
Epstein-Barr Virus Promotes Human Monocyte Survival and Maturation through a Paracrine Induction of IFN-α

The role of monocytes and macrophages during EBV infection is not clear. The interaction of EBV with human monocytes was investigated in terms of cell survival and morphological and phenotypic changes to gain a better understanding of the role of these cells during EBV infection. We show that EBV infection of PBMCs rescues monocytes from undergoing spontaneous apoptosis and dramatically enhances their survival. Results obtained with heat-inactivated virus, neutralizing anti-EBV mAb 72A1 and recombinant gp350, suggest that enhancement of viability by EBV requires both infectious virus and interaction between gp350 and its receptor. IFN-α either secreted within 24 h from PBMCs upon infection with EBV or exogenously added to unstimulated monocytes inhibited spontaneous apoptosis, indicating that induction of IFN-α is an early important survival signal responsible for the delay in the apoptosis of monocytes. EBV infection also induced acute maturation of monocytes to macrophages with morphological and phenotypic characteristics of potent APCs. Monocytes exposed to EBV became larger in size with increased granularity and expressed considerably higher levels of membrane HLA classes I and II, ICAM-1, CD80, CD86, and CD40 compared with uninfected cultures. These observations provide the first immunoregulatory links among EBV, IFN-α, and monocyte survival and maturation and importantly raise the possibility that these cells may serve as a vehicle for the dissemination of the virus as well as being active participants in eliciting anti-EBV T cell responses during acute infection.
The biphasic and age-dependent impact of klotho on hallmarks of aging and skeletal muscle function

Aging is accompanied by a disrupted information flow, which results from accumulation of molecular mistakes. These mistakes ultimately give rise to debilitating disorders such as skeletal muscle wasting, or sarcopenia. To estimate the growing “disorderliness” of the aging muscle system, we employed a statistical physics approach to estimate the state parameter, entropy, as a function of genes associated with hallmarks of aging. Although the most prominent structural and functional alterations were observed in the oldest old mice (27-29 months), we found that the escalating network entropy reached an inflection point at old age (22-24 months). To probe the potential for restoration of molecular “order” and reversal of the sarcopenic phenotype, we overexpressed the longevity protein, α-Klotho. Klotho overexpression modulated genes representing all hallmarks of aging in both old and oldest-old mice. However, whereas Klotho improved strength in old mice, intervention failed to induce a benefit beyond the entropic tipping point.
Ferocactus (Cactaceae) epidermis: its systematic value1

Abstract The stem epidermis of 23 species and three subspecies of Ferocactus Britton & Rose from the tribe Cacteae-Cactaceae are described and compared using scanning electron and light microscopy. Epidermal-hypodermal samples were removed, prepared for observation, and analyzed using a similarity method. Our observations showed that most epidermal cells had an elongate-tetragonal outline with straight anticlinal walls. However, S and U-undulated anticlinal walls occurred in F. glaucescens (DC.) Britton & Rose and F. peninsulae (Engelm. ex F.A.C. Weber) Britton & Rose (Cactaceae). The microrelief of the anticlines was flat and inconspicuous or striate. The periclinal wall relief varied from none to rugose or verrucose among species; 89% of the studied species had slightly sunken or sunken parallelocytic stomata with 2 or 3 pairs of subsidiary cells. Cuticle thickness varied from 2.54 µm in F. histrix (DC.) G.E. Linds to 39.74 µm in F. flavovirens (Scheidw.) Britton & Rose and their thickness is not related to environment. Silica bodies in the hypodermis cell lumina are present in 90% of the species studied. The epidermal characters of the Ferocactus species have been described in other members of Cactoideae, none of them can be postulated as possible synapomorphies to the genus level. Pustules, which are a cutin accumulations on the outer epidermal walls are distinctive feature of F. emoryi (Engelm.) Orcutt, and here are described for the first time for the Cactaceae. The phenogram revealed three groups, and F. haematacanthus (Salm-Dyck) Bravo was revealed as the most distinct species within the genus as well as F. histrix. Both were the early derived species in the most recent phylogeny. A combination of epidermal characters can help to distinguish some Ferocactus species, but failed to support the infrageneric classifications. However, some groups of species based on their epidermal similarities agree with some clades in the most recent phylogeny.
Prognostic Value of the Platelet-to-Lymphocyte Ratio in Patients With Melanoma: A Meta-Analysis

Background: The prognostic role of the platelet-to-lymphocyte ratio (PLR) is controversial in patients with melanoma. Therefore, we performed a meta-analysis to assess the prognostic value of the PLR in patients with melanoma. Methods: PubMed, Web of Science, Embase, Cochrane library, WanFang, and China National Knowledge Infrastructure were searched for eligible studies. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to evaluate the association between the PLR and overall survival (OS) and progression-free survival (PFS). Results: Nine studies with 2,396 patients were included in this meta-analysis. A high PLR was a predictor of shorter OS (HR = 1.67, 95% CI = 1.18–2.38, p = 0.004), but not PFS (HR = 1.53, 95% CI = 0.96–2.44, p = 0.075) in patients with melanoma. Subgroup analysis revealed that the PLR remained a significant prognostic indicator of both OS and PFS in patients with non-metastatic disease; the PLR cutoff value of <120 had a consistent prognostic value. Conclusions: An increased PLR was associated with poor OS of patients with melanoma. Hence, we suggest that the preoperative PLR could be used to identify high-risk patients and provide information regarding the prognosis of patients with melanoma.
LASDU: A Large-Scale Aerial LiDAR Dataset for Semantic Labeling in Dense Urban Areas

The semantic labeling of the urban area is an essential but challenging task for a wide variety of applications such as mapping, navigation, and monitoring. The rapid advance in Light Detection and Ranging (LiDAR) systems provides this task with a possible solution using 3D point clouds, which are accessible, affordable, accurate, and applicable. Among all types of platforms, the airborne platform with LiDAR can serve as an efficient and effective tool for large-scale 3D mapping in the urban area. Against this background, a large number of algorithms and methods have been developed to fully explore the potential of 3D point clouds. However, the creation of publicly accessible large-scale annotated datasets, which are critical for assessing the performance of the developed algorithms and methods, is still at an early age. In this work, we present a large-scale aerial LiDAR point cloud dataset acquired in a highly-dense and complex urban area for the evaluation of semantic labeling methods. This dataset covers an urban area with highly-dense buildings of approximately 1 km2 and includes more than three million points with five classes of objects labeled. Moreover, experiments are carried out with the results from several baseline methods, demonstrating the feasibility and capability of the dataset serving as a benchmark for assessing semantic labeling methods.
Postural Stability and Cognitive Performance of Subjects With Parkinson’s Disease During a Dual-Task in an Upright Stance

Background The reviewed studies on center of pressure (COP) displacement in Parkinson’s disease (PD) subjects show important methodological differences and contradictory results with regard to healthy subjects. The dual-task paradigm method has been used to examine cognitive prioritization strategies to control concurrent postural and cognitive tasks. The motor requirements, such as pronouncing words, involved in the cognitive tasks used in double-task conditions could be related to the heterogeneity of the results. Research Objective To compare postural sway and cognitive performance in subjects with PD and controls using a dual-task paradigm with a cognitive task free of motor demands. We tried to examine the prioritization strategy of PD patients regarding healthy adults to control for concurrent postural and cognitive tasks. Materials and Methods 25 subjects with PD and 20 healthy controls carried out a postural task under both single-task and dual-task conditions. The postural task was to stand as still as possible, with eyes first open and then closed. The dual-task condition added a concurrent cognitive task based on phoneme monitoring. COP displacement variables and cognitive performance were compared between the groups and within-subject factors were also examined. Results PD participants showed higher COP displacement results than the controls. All participants shortened the mean sway radius in dual-task conditions compared with single-task conditions; only healthy subjects presented less transversal COP sway in dual-task conditions than in single-task conditions. The cognitive performance of PD patients on a phoneme monitoring task worsened when they carried it out while maintaining balance in a standing position compared to sitting. The opposite effect occurred in control subjects. Conclusion This study confirms the negative influence of Parkinson’s disease on the control of standing stability, increasing the COP sway amplitude. The attentional demands of a postural task, such as standing balance, may be greater in PD patients than in healthy subjects. This would affect the performance of patients during dual-task conditions to be able to control a postural task while performing other cognitive tasks. In these conditions, cognitive performance would be negatively affected. These results suggest that subjects with PD, at least during initial disease stages, prioritize postural control over other concurrent tasks, as is also seen in healthy subjects.
Stress modulates the enzymatic inducibility by benzo[α]pyrene in the rat liver

The role of stress on the inducibility by benzo[ α ]pyrene (B[ α ]P), a representative polycyclic aromatic hydrocarbon, of several drug-metabolizing enzymes was investigated in rats, using restraint stress and mild unpredictable stress as models of psychological stress. Restraint stress was found to significantly suppress basal ethoxyresorufin 7-dealkylase (EROD) and pentoxyresorufin 7-dealkylase (PROD) activities (two-fold). In contrast, mild unpredictable stress markedly increased basal EROD activity, while PROD activity was not affected. In addition, both types of stress resulted in a significant reduction of basal p -nitrophenol hydroxylation (PNP). It is worth noting that restraint stress greatly enhanced the inducibility of EROD, methoxyresorufin 7-dealkylase (MROD) and to a lesser extent PROD activities by B[ α ]P, while mild unpredictable stress had no, or only a mild effect on the inducibility of cytochrome P450s (CYPs) by B[ α ]P. In conclusion, psychological stress may modulate different enzymatic systems which are vital elements of the detoxification mechanisms of the body. The two distinct types of psychological stress used in this study appear to affect the enzymatic systems under investigation in a stress-specific manner at the basal level and at the induced state by B[ α ]P.
Cigarette smoking and risk of intracranial aneurysms in middle-aged women

Background and purpose We previously reported a single-centre study demonstrating that smoking confers a six-fold increased risk for having an unruptured intracranial aneurysm (UIA) in women aged between 30 and 60 years and this risk was higher if the patient had chronic hypertension. There are no data with greater generalisability evaluating this association. We aimed to validate our previous findings in women from a multicentre study. Methods A multicentre case-control study on women aged between 30 and 60 years, that had magnetic resonance angiography (MRA) during the period 2016–2018. Cases were those with an incidental UIA, and these were matched to controls based on age and ethnicity. A multivariable conditional logistic regression was conducted to evaluate smoking status and hypertension differences between cases and controls. Results From 545 eligible patients, 113 aneurysm patients were matched to 113 controls. The most common reason for imaging was due to chronic headaches in 62.5% of cases and 44.3% of controls. A positive smoking history was encountered in 57.5% of cases and in 37.2% of controls. A multivariable analysis demonstrated a significant association between positive smoking history (OR 3.7, 95%CI 1.61 to 8.50), hypertension (OR 3.16, 95% CI 1.17 to 8.52) and both factors combined with a diagnosis of an incidental UIA (OR 6.9, 95% CI 2.49 to 19.24). Conclusions Women aged between 30 and 60 years with a positive smoking history have a four-fold increased risk for having an UIA, and a seven-fold increased risk if they have underlying chronic hypertension. These findings indicate that women aged between 30 and 60 years with a positive smoking history might benefit from a screening recommendation.