Miracle-dz/UniFAR-FTUs huggingface dataset:
MiR-192 attenuates high glucose-induced pyroptosis in retinal pigment epithelial cells via inflammasome modulation

ABSTRACT Diabetic retinopathy is one of the most characteristic complications of diabetes mellitus, and pyroptosis plays acrucial role in the onset and development of diabetic retinopathy. Although microRNA-192 (miR-192) has been demonstrated to be involved in diabetic retinopathy progression, to the best of our knowledge, its potential and mechanism in cell pyroptosis in diabetic retinopathy have not been studied. The present study demonstrated that high glucose (HG) contributes to the pyroptosis of retinal pigment epithelial (RPE) cells in a dose-dependent manner. The results revealed that miR-192 was weakly expressed in HG-induced RPE cells. Furthermore, overexpression of miR-192 abrogated the role of HG in RPE cell pyroptosis. Based on the bioinformatics analysis, a dual-luciferase reporter assay, and an RNA pull-down assay, FTO α-ketoglutarate-dependent dioxygenase (FTO) was demonstrated to be a direct target of miR-192. Additionally, upregulation of FTO abolished the effects of miR-192 on RPE cells treated with HG. Nucleotide-binding domain leucine-rich repeat family protein 3 (NLRP3) inflammasome activation is vital for cell pyroptosis, and FTO functions as a pivotal modulator in the N6-methyladenosine modifications of various genes. Mechanistically, FTO enhanced NLRP3 expression by facilitating demethylation of NLRP3. In conclusion, the present results demonstrate that miR-192 represses RPE cell pyroptosis triggered by HG via regulation of the FTO/NLRP3 signaling pathway. GRAPHICAL ABSTRACT
Antiretroviral drug exposure in lymph nodes is heterogeneous and drug dependent

HIV reservoirs and infected cells may persist in tissues with low concentrations of antiretrovirals (ARVs). Traditional pharmacology methods cannot assess variability in ARV concentrations within morphologically complex tissues, such as lymph nodes (LNs). We evaluated the distribution of six ARVs into LNs and the proximity of these ARVs to CD4+ T cells and cell‐associated RT‐SHIV viral RNA.
Strategies to Increase Racial and Ethnic Diversity in the Surgical Workforce: A State of the Art Review

Objective To evaluate strategies to increase racial and ethnic diversity in the surgical workforce among trainees and faculty across surgical specialties. Data Sources Embase, OVID/Medline, and Web of Science Core Collection. Review Methods A review of US-based, peer-reviewed articles examining the effect of targeted strategies on racial and ethnic diversity in the surgical workforce was conducted from 2000 to 2020 with the PRISMA checklist and STROBE tool. Studies without an outlined strategy and associated outcomes were excluded. Eleven studies met inclusion criteria and were completed in general surgery, orthopaedic surgery, and otolaryngology–head and neck surgery. Conclusions Efforts to increase exposure to surgery through internship programs and required clerkships with efforts to improve mentorship were common (6 of 11 [54.5%] and 3 of 11 [27.3%] studies, respectively). Three (27.3%) studies aimed to diversify the recruitment and selection process for the residency match and faculty hiring, and 2 (18.2%) aimed to increase representation among trainees, faculty, and leadership through holistic review processes paired with departmental commitment. Outcome metrics included surgical residency applications for individuals underrepresented in medicine, interview and match rates, faculty hiring, measures of a successful academic surgical career, and leadership representation. All strategies were successful in increasing diversity in the surgical workforce. Implications for Practice A convincing yet limited body of literature exists to describe strategies and outcomes that address racial and ethnic diversity in the surgical workforce. While future inquiry is needed to move this field of interest forward, the evidence presented provides a framework for surgical residency programs/departments to develop approaches to increase racial and ethnic diversity.
MicroRNA-183-5p regulates MITF expression in vitiligo skin depigmentation

Abstract Microphthalmia-associated transcription factor (MITF) is a master regulatory factor for melanocytes. MITF regulates multiple pigmentary genes for maintaining cellular homeostasis. MicroRNAs (miRNAs) play crucial roles in numerous biological processes however their molecular/cellular mechanisms to regulate pigmentation have not been fully explored. This study was undertaken to investigate the role of miRNAs in skin depigmentation via regulation of MITF gene. Depigmentation in C57BL/6 black mice was induced by an autoimmune response against tyrosinase. Bioinformatics approach was used to detect miRNAs conserved in 3′untraslated region (3′UTR) of MITF mRNA. The iMC23 mouse melanocytes were used for transfection experiments. The data demonstrated that the MITF mRNA/protein was markedly low in lesional skin of depigmented mice (p < 0.05). Targetscan genomic database determined that 3′UTR of mouse MITF constitutes 4819 nucleotide bases and has 23 conserved sites for different miRNAs To validate the pairing of these predicted miRNAs with MITF mRNA, five miRNAs were deregulated in lesional skin (p < 0.05). Among them, mmu-miR-181a-5p and mmu-miR-183-5p were up-regulated, whereas mmu-miR-26a-5p, mmu-miR-26b-5p and mmu-miR-32-5p were down-regulated (p < 0.05). To verify these results, the iMC23 mouse melanocytes were used. Transfection of iMC23 cells with specific miRNAs mimics or inhibitors or with 3’UTR reporter clone of MITF, showed only mmu-miR-183-5p binds to 3’UTR of MITF mRNA and regulates its expression in iMC23 melanocytes. In conclusions, this is the first study shows that miR-183-5p is a direct regulator of MITF in iMC23 melanocytes. Thus, miR-183-5p is an important regulator of melanocytes homeostasis and may be a novel target for autoimmune depigmentation therapy.
Distinct Cognitive Function Profiles Are Associated With a Higher Presurgery Symptom Burden in Patients With Breast Cancer

Background Cancer-related cognitive impairment (CRCI) is a common symptom in patients with breast cancer. In our previous study of 397 women with breast cancer, we identified 3 groups of patients with distinct CRCI profiles (ie, high, moderate, and low-moderate attentional function). Compared with the other 2 classes, the low-moderate class was younger, had more comorbidities, and with lower functional status. Objectives In this study, we expand on this work and evaluate for differences among these latent classes in the severity of psychological (depression and anxiety) and physical (fatigue, decrements in energy, sleep disturbance, and pain) symptoms before surgery. Methods Cancer-related cognitive impairment was assessed using the Attentional Functional Index from before through 6 months after surgery. Lower Attentional Functional Index scores indicate higher levels of CRCI. Psychological and physical symptoms were assessed with valid instruments. Parametric and nonparametric tests were used to evaluate for differences in symptom severity scores among the latent classes. Results Approximately 60% of patients experienced CRCI (ie, moderate and low-moderate classes). Significant differences were found among the 3 classes in the severity of trait and state anxiety, depressive symptoms, fatigue, and sleep disturbance (ie, high < moderate < low-moderate). In addition, compared with the other 2 classes, the low-moderate class reported higher pain interference scores. Conclusions These findings suggest that women with clinically meaningful levels of persistent CRCI have a relatively high symptom burden before surgery. Implications for Practice Clinicians need to routinely perform preoperative assessments of CRCI and associated symptoms and initiate therapeutic interventions.
Comparative Genomics of Disease and Carriage Serotype 1 Pneumococci

Abstract The isolation of Streptococcus pneumoniae serotypes in systemic tissues of patients with invasive disease versus the nasopharynx of healthy individuals with asymptomatic carriage varies widely. Some serotypes are hyper-invasive, particularly serotype 1, but the underlying genetics remain poorly understood due to the rarity of carriage isolates, reducing the power of comparison with invasive isolates. Here, we use a well-controlled genome-wide association study to search for genetic variation associated with invasiveness of serotype 1 pneumococci from a serotype 1 endemic setting in Africa. We found no consensus evidence that certain genomic variation is overrepresented among isolates from patients with invasive disease than asymptomatic carriage. Overall, the genomic variation explained negligible phenotypic variability, suggesting a minimal effect on the disease status. Furthermore, changes in lineage distribution were seen with lineages replacing each other over time, highlighting the importance of continued pathogen surveillance. Our findings suggest that the hyper-invasiveness is an intrinsic property of the serotype 1 strains, not specific for a “disease-associated” subpopulation disproportionately harboring unique genomic variation.
Looking Beyond Single Images for Weakly Supervised Semantic Segmentation Learning

This article studies the problem of learning weakly supervised semantic segmentation (WSSS) from image-level supervision only. Current popular solutions leverage object localization maps from classifiers as supervision for semantic segmentation learning, and struggle to make the localization maps capture more complete object content. Rather than previous efforts that primarily focus on intra-image information, we address the value of cross-image semantic relations for comprehensive object pattern mining. To achieve this, two neural co-attentions are incorporated into the classifier to complementarily capture cross-image semantic similarities and differences. In particular, given a pair of training images, one co-attention enforces the classifier to recognize the common semantics from co-attentive objects, while the other one, called contrastive co-attention, drives the classifier to identify the unique semantics from the rest, unshared objects. This helps the classifier discover more object patterns and better ground semantics in image regions. In addition to boosting object pattern learning, the co-attention can leverage context from other related images to improve localization map inference, hence eventually benefiting semantic segmentation learning. More importantly, our algorithm provides a unified framework that handles well different WSSS settings, i.e., learning WSSS with 1) precise image-level supervision only, 2) extra simple single-label data, and 3) extra noisy web data. Without bells and whistles, it sets new state-of-the-arts on all these settings. Moreover, our approach ranked 1st place in the Weakly-Supervised Semantic Segmentation Track of CVPR2020 Learning from Imperfect Data Challenge. The extensive experimental results demonstrate well the efficacy and high utility of our method.
Deep Generative Learning Models for Cloud Intrusion Detection Systems

Intrusion detection (ID) on the cloud environment has received paramount interest over the last few years. Among the latest approaches, machine learning-based ID methods allow us to discover unknown attacks. However, due to the lack of malicious samples and the rapid evolution of diverse attacks, constructing a cloud ID system (IDS) that is robust to a wide range of unknown attacks remains challenging. In this article, we propose a novel solution to enable robust cloud IDSs using deep neural networks. Specifically, we develop two deep generative models to synthesize malicious samples on the cloud systems. The first model, conditional denoising adversarial autoencoder (CDAAE), is used to generate specific types of malicious samples. The second model (CDAEE-KNN) is a hybrid of CDAAE and the $K$ -nearest neighbor algorithm to generate malicious borderline samples that further improve the accuracy of a cloud IDS. The synthesized samples are merged with the original samples to form the augmented datasets. Three machine learning algorithms are trained on the augmented datasets and their effectiveness is analyzed. The experiments conducted on four popular IDS datasets show that our proposed techniques significantly improve the accuracy of the cloud IDSs compared with the baseline technique and the state-of-the-art approaches. Moreover, our models also enhance the accuracy of machine learning algorithms in detecting some currently challenging distributed denial of service (DDoS) attacks, including low-rate DDoS attacks and application layer DDoS attacks.
Influence of HIIRT With Fixed and Self-Selected Recovery Intervals on Physiological, Affective, and Enjoyment Responses

ABSTRACT Purpose: Recovery-interval strategies may influence physiological and psychological responses during highintensity interval resistance training (HIIRT). This study compared the intensity, performance, and psychological outcomes during all-out effort HIIRT performed with fixed (FRI) and self-selected (SSRI) recovery intervals. Methods: Sixteen trained males (27.2 ± 4.1 years; 84.5 ± 8.9 kg; 55.8 ± 7.1 mL.kg−1.min−1) performed HIIRT bouts interspersed with FRI (10 s) and SSRI (15.3 ± 7.9 s). Results: Relative heart rate (%HRmax) and oxygen uptake (%VO2Peak), number of repetitions, and psychological responses (affection: Feeling ScaleFS; Felt Arousal ScaleFAS; enjoyment: Physical Activity Enjoyment ScalePACES) were assessed. FRI and SSRI elicited similar relative average intensity (p > .05) (%HRmax: 88.1 ± 3.5% vs. 87.6 ± 3.0%; %VO2Peak: 55.3 ± 7.4% vs. 54.1 ± 8.1%, respectively). The number of repetitions similarly decreased in SSRI and FRI from rounds 1 to 4 (~15%; p < .006), with no difference of total volume across conditions (FRI: 358.6 ± 32 reps vs. SSRI:357.5 ± 28.2; p = .89). In each round, no difference between FRI and SSRI (p > .05) was found for FS (3- to 3.5 vs. 2- to 4, respectively) or FAS (2- to 4 vs. 2- to 4, respectively), while PACES was lower in FRI than SSRI (102.8 ± 15.8 vs. 109.2 ± 13.2; p = .04). Conclusion: In conclusion, relative intensity, total repetitions, and affective perception were not influenced by the strategy of recovery intervals. On the other hand, overall enjoyment was favored in SSRI vs. FRI.
Multi‐layer sequential network analysis improves protein 3D structural classification

Protein structural classification (PSC) is a supervised problem of assigning proteins into pre‐defined structural (e.g., CATH or SCOPe) classes based on the proteins' sequence or 3D structural features. We recently proposed PSC approaches that model protein 3D structures as protein structure networks (PSNs) and analyze PSN‐based protein features, which performed better than or comparable to state‐of‐the‐art sequence or other 3D structure‐based PSC approaches. However, existing PSN‐based PSC approaches model the whole 3D structure of a protein as a static (i.e., single‐layer) PSN. Because folding of a protein is a dynamic process, where some parts (i.e., sub‐structures) of a protein fold before others, modeling the 3D structure of a protein as a PSN that captures the sub‐structures might further help improve the existing PSC performance. Here, we propose to model 3D structures of proteins as multi‐layer sequential PSNs that approximate 3D sub‐structures of proteins, with the hypothesis that this will improve upon the current state‐of‐the‐art PSC approaches that are based on single‐layer PSNs (and thus upon the existing state‐of‐the‐art sequence and other 3D structural approaches). Indeed, we confirm this on 72 datasets spanning ~44 000 CATH and SCOPe protein domains.
Is carotid artery atherosclerosis associated with poor cognitive function assessed using the Mini-Mental State Examination? A systematic review and meta-analysis

Objectives To determine associations between carotid atherosclerosis assessed by ultrasound and the Mini-Mental State Examination (MMSE), a measure of global cognitive function. Design Systematic review and meta-analysis. Methods MEDLINE and EMBASE databases were searched up to 1 May 2020 to identify studies assessed the associations between asymptomatic carotid atherosclerosis and the MMSE. Studies reporting OR for associations between carotid plaque or intima-media thickness (cIMT) and dichotomised MMSE were meta-analysed. Publication bias of included studies was assessed. Results A total of 31 of 378 reviewed articles met the inclusion criteria; together they included 27 738 participants (age 35–95 years). Fifteen studies reported some evidence of a positive association between measures of atherosclerosis and poorer cognitive performance in either cross-sectional or longitudinal studies. The remaining 16 studies found no evidence of an association. Seven cross-sectional studies provided data suitable for meta-analysis. Meta-analysis of three studies that assessed carotid plaque (n=3549) showed an association between the presence of plaque and impaired MMSE with pooled estimate for the OR (95% CI) being 2.72 (0.85 to 4.59). An association between cIMT and impaired MMSE was reported in six studies (n=4443) with a pooled estimate for the OR (95% CI) being 1.13 (1.04 to 1.22). Heterogeneity across studies was moderate to small (carotid plaque with MMSE, I2=40.9%; cIMT with MMSE, I2=4.9%). There was evidence of publication bias for carotid plaque studies (p=0.02), but not cIMT studies (p=0.2). Conclusions There is some, limited cross-sectional evidence indicating an association between cIMT and poorer global cognitive function assessed with MMSE. Estimates of the association between plaques and poor cognition are too imprecise to draw firm conclusions and evidence from studies of longitudinal associations between carotid atherosclerosis and MMSE is limited. PROSPERO registration number CRD42021240077.
Supporting the involvement of older adults with complex needs in evaluation of outcomes in long‐term care at home programmes

It is important to involve older people in evaluating public programmes that affect their lives. This includes those with physical and cognitive impairments (such as dementia) who may need support to live at home. Many countries have implemented new approaches to support older people to live well at home for longer. However, it can be challenging to involve disabled people in service evaluation, so we are unclear whether services are meeting their needs.
Examining Patterns of Driving Avoidance Behaviors Among Older People Using Latent Class Analysis

Objectives: Some older drivers choose to avoid certain situations where they do not feel confident driving. Little is known about the process by which older drivers may use avoidance in transitioning to non-driving. Methods: We analyzed 2015 ConsumerStyles data for 1198 drivers aged 60+. Driving patterns were examined by sociodemographic and driving characteristics. Avoidance classes were characterized by latent class analysis. Results: Among drivers 60+, 79% reported driving 3+ days/week and 84% reported good to excellent health. We identified four driving avoidance classes (low, mild, moderate, and high). High- (versus low-) avoidance drivers were more likely female, 75+, not White/non-Hispanic, and to have income <$25,000/year. Discussion: Avoidance of selected driving behaviors may be one component of a multi-step process supporting the transition to non-driving. Drivers displaying avoidance behaviors may be receptive to resources to prepare for this transition and minimize negative health and quality of life outcomes that accompany driving cessation.
Modeling of the market-manufacturing system relationship aiming the product time and cost estimation

This paper presents a product time and cost estimation method taking account the market dynamics and manufacturing system competitiveness. The method is based on the behavioral modeling using on-line unsupervised learning. On one hand, it is modeled the interaction between task and manufacturing system, and on the other hand the interaction between task and market, finally resulting behavioral modeling of the market-manufacturing system relationship to substantiate the strategic component of the competitive management thus ensuring extension in time of the high performance.
Evidence of rotator cuff disease after breast cancer treatment: scapular kinematics of post-mastectomy and post-reconstruction breast cancer survivors

Abstract Background Breast cancer survivors may be at risk of experiencing rotator cuff disease after treatment. Biomechanical alterations following surgery potentially predispose survivors to develop this disorder. Objective To examine scapular kinematics in breast cancer survivors with and without impingement pain during an overhead reach task. Design A cross-sectional study. Methods Three surgery groups were included: non-cancer controls, mastectomy-only survivors and post-reconstruction survivors. Breast cancer survivor groups were also categorized by the presence of impingement pain. Scapular motion was tracked during an overhead reach task, performed separately by both arms. Maximum scapular internal rotation, upward rotation and tilt were calculated. Two-way analyses of variance with interactions (p < .05) were used to test the effects of group (control, mastectomy-only, reconstruction) and impingement pain (pain, no pain) on each variable within a (left/right) side. Results Scapular kinematics varied with the group by pain interaction. On the right side, the mastectomy-pain group had reduced upward rotation, while the reconstruction-pain group had higher upward rotation (mastectomy-only: 22.9° vs. reconstruction: 31.2°). On the left side, the mastectomy-pain group had higher internal rotation, while the reconstruction-pain group had reduced internal rotation (mastectomy-only: 45.1° vs. reconstruction: 39.3°). However, time since surgery was longer in the mastectomy-pain group than reconstruction-pain group, suggesting there may be a temporal component to kinematic compensations. Conclusions There are kinematic alterations in breast cancer survivors that may promote future development of rotator cuff disease. Compensations may begin as protective and progress to more harmful alterations with time. KEY MESSAGES Scapular kinematics varied with surgery and pain interaction: upward rotation was lower and internal rotation higher in mastectomy-pain group, while upward rotation was higher and internal rotation lower in reconstruction-pain group. Kinematics alterations may also be associated with time since surgery, as the mastectomy-pain group had longer time since surgery than the reconstruction-pain group. Kinematic alterations may transition from protective to harmful over time. In-depth analyses by reconstruction type are needed to determine surgery-specific effects on kinematics and their potential impact on the development of rotator cuff disease.