Miracle-dz/UniFAR-FTUs huggingface dataset:
Vitamin D Receptor Gene Polymorphisms and Cigarette Smoking Impact on Oral Health: A Case-Control Study

Periodontal diseases are multiperspective problems resulting from numerous and diverse exposures that influence the process of initiation or progression of disease. The negative influence of tobacco smoking on oral health is well documented. The aim of the study was to analyze three SNPs in vitamin D receptor gene—rs7975232 (ApaI), rs2228570 (FokI) and rs1544410 (BsmI)—combined with oral health assessment—pH, gingival index, dry mouth, periodontitis, dry socket, redness of oral cavity mucosa, leukoplakia—in a group of cigarette smokers and in non-smokers. Moreover, the possibility of interactions between these polymorphisms and smoking was examined. When comparing the smokers and non-smokers groups, we noticed that rs1544410 heterozygotes were significantly more frequent in the first group, and for the second, both homozygotes were more frequent. Additionally, we observed the impact of interaction between the rs7975232 genotype and smoking status on gingival index. Current smoking was also associated with all analyzed oral health measures except for leucoplakia. Correlation between pH and age in both smokers and non-smokers was also present. Results of our analysis indicate that in our study group lifestyle and aging were leading factors associated with worse oral health status. However, the impact of genetic variants, and also the impact of their interaction with smoking on analyzed parameters was also visible. These results show great possibilities for all levels of prevention of oral diseases by means of education based on evidence-based medicine, but also for incorporating genetic testing and early interventions into this process for predisposed individuals.
Patterns of plant species distribution in the Trans-Himalayan region of Ladakh, India

Abstract We studied the vegetation distribution in eight landscape types distinguished along an altitudinal gradient in the Trans-Himalayan region of Ladakh, India. The point-intercept method was used for vegetation sampling. Six plant communities were distinguished by cluster analysis. Of these 6 communities, three communities were dominated by shrub species. Table lands are the landscape type with the highest species diversity followed by undulating areas and river beds. Most plant species were restricted to one landscape type. Nomenclature: Kachroo et al. (1977); Polunin & Stainton (1984).
Efficacy of Interventions Based on Applied Behavior Analysis for Autism Spectrum Disorder: A Meta-Analysis

Objective To systematically evaluate evidence for the use of interventions based on appied behavior analysis (ABA) to manage various symptoms of children with autism spectrum disorder (ASD). Methods Sensitivity analyses were conducted by removing any outlying studies and subgroup analyses were performed to compare the effectiveness of ABA and early start denver model (ESDM), picture exchange communication systems (PECS) and discrete trial training (DTT). Results 14 randomized control trials of 555 participants were included in this meta-analysis. The overall standardized mean difference was d=-0.36 (95% CI -1.31, 0.58; Z=0.75, p=0.45) for autism general symptoms, d=0.11 (95% CI -0.31, 0.54; Z=0.52, p=0.60) for socialization, d=0.30 (95% CI -0.02, 0.61; Z=1.84, p=0.07) for communication and d=-3.52 (95% CI -6.31, -0.72; Z=2.47, p=0.01) for expressive language, d=-0.04 (95% CI -0.44, 0.36; Z=0.20, p=0.84) for receptive language. Those results suggested outcomes of socialization, communication and expressive language may be promising targets for ABA-based interventions involving children with ASD. However, significant effects for the outcomes of autism general symptoms, receptive language, adaptive behavior, daily living skills, IQ, verbal IQ, nenverbal IQ, restricted and repetitive behavior, motor and cognition were not observed. Conclusion The small number of studies included in the present study limited the ability to make inferences when comparing ABA, ESDM, PECS and DTT interventions for children with ASD.
Fine chromatin-driven mechanism of transcription interference by antisense noncoding transcription

Eukaryotic genomes are almost entirely transcribed by RNA polymerase II (RNAPII). Consequently, the transcription of long noncoding RNAs (lncRNAs) often overlaps with coding gene promoters triggering potential gene repression through a poorly characterized mechanism of transcription interference. In this study, we propose a global model of chromatin-based transcription interference in Saccharomyces cerevisiae (S. cerevisiae). By using a noncoding transcription inducible strain, we analyzed the relationship between antisense elongation and coding sense repression, nucleosome occupancy and transcription-associated histone modifications using near-base pair resolution techniques. We show that antisense noncoding transcription leads to the deaceylation of a subpopulation of −1/+1 nucleosomes associated with increased H3K36 trimethylation (H3K36me3). Reduced acetylation results in decreased binding of the RSC chromatin remodeler at −1/+1 nucleosomes and subsequent sliding into the Nucleosome-Depleted Region (NDR) hindering Pre-Initiation Complex (PIC) association. Finally, we extend our model by showing that natural antisense noncoding transcription significantly represses around 20% of S. cerevisiae genes through this chromatin-based transcription interference mechanism. Highlights Induction of antisense noncoding transcription leads to −1/+1 nucleosome sliding that competes with sense transcription PIC deposition. Antisense induction leads to a subpopulation of H3K36me3 nucleosomes differently positioned compared to H3K18ac nucleosomes. RSC chromatin remodeler recruitment to −1/+1 nucleosomes is modulated by histone acetylation levels. 20% of S. cerevisiae genes are significantly repressed by this antisense-dependent chromatin-based transcription interference mechanism.
Prevention and management of adverse effects of disease modifying treatments in multiple sclerosis.

PURPOSE OF REVIEW To summarize the currently known side effects of the approved therapies of multiple sclerosis and to suggest monitoring procedures. RECENT FINDINGS The progress in the treatment of multiple sclerosis with new very effective therapies is accompanied by a number of side effects. Some of these have already been described in the approval studies, but some only after approval in a real world situation. The reason for this is the short duration of the clinical studies, the very heterogeneous patient profile in the real world setting with a number of comorbidities, pretherapies, and wider age range. The side effects may occur during application of therapies or afterwards during the course of the treatment. The side effects may range from mild infections, mild laboratory abnormalities, secondary autoimmune diseases to life-threatening side effects such as progressive multifocal leukoencephalopathy. SUMMARY It has to be pointed out that these side effects are not to be considered as final and neurologists should be vigilant against new unknown side effects. The doctor should be aware of these undesirable effects, should weigh the benefits of the therapies against the risks, but at the same time she/he should keep in mind that multiple sclerosis can be a very disabling disease if not treated properly.
Cytological Study in the Genus Silene (sec. Sclerocalycinae)

Karyotype study was performed in 23 populations of nine Silene species belonging to the section Sclerocalycinae growing in Iran. The species studied were diploid (2n=2x=24) and tetraploid (2n=4x=48). The highest value of total and mean haploid chromosome length occurred in the Kerman 2 population of S. stapfii, while the lowest value of the same parameters occurred in the Kerman population of S. shahrudensis. ANOVA and LSD tests showed a significant difference for total size of the chromosomes and size of the short and long arms among the species studied, indicating the role of quantitative genomic changes in the Silene species diversification. A positive significant correlation was observed between total chromosome length, mean chromosome length, size of the longest chromosome, size of the shortest chromosome and A1 index of Romero-Zarco, while total chromosome length showed negative significant correlation with TF%, indicating that lower values of total chromosome length occur in the species having more symmetrical karyotypes (higher TF%), while higher values occur in asymmetric karyotypes (higher A1 values). The species studied differed in their karyotype formulae, indicating the occurrence of structural changes in their chromosomes
Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning

Objectives To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. Background Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. Methods Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. Results The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs. , and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. Conclusions An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level.
Editorial: Immune mechanisms and brain dysfunction.

DOI:10.1097/WCO.0000000000000819 The essays in this section describe the interaction of the stimulated immune system and the pathological processes that result in the central nervous system (CNS). It is well known that B and T cells through antibody and cytokine production, can cause acute neuronal damage when they have direct access to the CNS through mechanisms initiated by crossreactivity and inflammatory inducing proteins. Less well known, but increasingly more often appearing in clinical outcome studies, are the issues of impaired cognition in patients who survive the acute attack from virus, or the repeated flares of autoimmune disease activity. Persistent immune activation, whether initiated to fend off viruses, or part of waxing/waning autoimmune disease, or, as Sankowsky (pp. 341–346) reminds us, for those who survive overwhelming sepsis, may not only be a driver of continued disease [1], but also cause CNS damage [2]. The issues of molecules large and small crossing the blood–brain barrier (BBB) has afforded the brain some measure of protection from the immune system agents [3]. But the contingency of ‘. when they have access. ’ may under certain circumstances have become moot, as Arinuma (pp. 347–352) recounts the discovery of an antibody to an abundant molecule, glucose-regulated protein 78 (GRP78). GRP78 is a stress protein in the heat shock protein 70 family that acts as an endoplasmic reticulum chaperone on all cells in the CNS. To date it plays a role in downstream signaling in cancer cells, but, for the purpose of this review, Shimizu et al. [4], demonstrated a role for GRP78 on brain microvascular endothelial cells such that exposure to GRP78specific antibody led to BBB breach and leakage of vascular proteins into the extracellular brain parenchymal space. Arinuma reported his group’s finding of anti-GRP78 antibodies in patients with systemic lupus erythematosus (SLE) [5]; thus, the added potential for toxic autoantibodies to cross BBB, and a more flexible initial stage of toxic antibody access to the CNS parenchyma. He continues to report the progress of anti-DNA, anti-N-methyl-Daspartate (NMDA) receptor antibody found in SLE patients with a range of brain impairments from cognitive impairment to encephalopathy that is called diffuse neuropsychiatric SLE (NPSLE) [6]. He
Serum albumin, cardiometabolic and other adverse outcomes: systematic review and meta-analyses of 48 published observational cohort studies involving 1,492,237 participants

Abstract Objectives. A general body of evidence suggests that low serum albumin might be associated with increased risk of adverse cardiometabolic outcomes, but findings are divergent. We aimed to quantify associations of serum albumin with the risk of type 2 diabetes (T2D), cardiovascular disease (CVD), all-cause mortality, and other adverse outcomes using a systematic review and meta-analyses of published observational cohort studies. Design. MEDLINE, Embase, Web of Science, and manual search of relevant bibliographies were systematically searched to January 2020. Relative risks (RRs) with 95% confidence intervals (CIs) comparing top versus bottom thirds of serum albumin levels were pooled. Results. Fifty-four articles based on 48 unique observational cohort studies comprising of 1,492,237 participants were eligible. Multivariable adjusted RRs (95% CIs) comparing the top vs bottom third of serum albumin levels were: 1.03 (0.86–1.22) for T2D; 0.60 (0.53–0.67) for CVD; 0.74 (0.66–0.84) for coronary heart disease (CHD); 0.57 (0.36–0.91) for CHD death; 0.76 (0.65–0.87) for myocardial infarction; 0.66 (0.55–0.77) for all-cause mortality; 0.71 (0.61–0.83) for venous thromboembolism; 0.65 (0.48–0.88) for cancer mortality; and 0.62 (0.46–0.84) for fracture. Heterogeneity between contributing studies of T2D was partly explained by sample sizes of studies (p for meta-regression = .035). Conclusions. Elevated levels of serum albumin are associated with reduced risk of vascular outcomes, all-cause mortality, certain cancers, and fracture. Inconsistent findings for T2D may be attributed to selective reporting by studies. Further research is needed to assess any potential causal relevance to these findings and the role of serum albumin concentrations in disease prevention. Systematic review registration: PROSPERO 2019: CRD42019125869
Addition of structural complexity – contrasting effect on juvenile brown trout in a natural stream

In a field experiment, we examined the effects of structural complexity in the form of added artificial plastic plants and shredded plastic bags on growth and abundance of juvenile brown trout (Salmo trutta). Just after emergence, the added complexity had a positive effect on the density, biomass and condition factor of young-of-the-year (0+) brown trout. This difference in density was not present six weeks later. In contrast, both young-of-the-year and older brown trout generally tended to be larger in the simple habitat. Hence, our data suggest that increased complexity initially is beneficial for young-of-the-year individuals probably due to lower risk of predation and increased densities of prey. However, as density increases in the complex environment, it may induce negative density-dependent effects, here reflected in smaller sized fish in the complex environment. This might force fish to redistribute to habitats with lower densities of conspecifics as they grow larger. We propose that habitat complexity can increase survival of yearlings in early phases and thereby also affect the overall population structure of brown trout in natural streams.
People experiencing homelessness urgently need to be recognised as a high risk group for COVID-19.

History shows that pandemics rarely impact on the population equally - the 14th century Black Death plague reduced the global population by a third, with the greatest number of deaths occurring among the poor.1 Fast forward six centuries, and the same pandemic inequities are prevailing due to COVID-19; with Smith and Judd articulating that "while COVID-19 has the potential to impact everyone in society, these impacts will be felt differentially… the most vulnerable will be hardest hit"2 in their recent Health Promotion Journal of Australia editorial.
Single-Cell RNA Sequencing and Its Combination with Protein and DNA Analyses

Heterogeneity in cell populations poses a significant challenge for understanding complex cell biological processes. The analysis of cells at the single-cell level, especially single-cell RNA sequencing (scRNA-seq), has made it possible to comprehensively dissect cellular heterogeneity and access unobtainable biological information from bulk analysis. Recent efforts have combined scRNA-seq profiles with genomic or proteomic data, and show added value in describing complex cellular heterogeneity than transcriptome measurements alone. With the rising demand for scRNA-seq for biomedical and clinical applications, there is a strong need for a timely and comprehensive review on the scRNA-seq technologies and their potential biomedical applications. In this review, we first discuss the latest state of development by detailing each scRNA-seq technology, including both conventional and microfluidic technologies. We then summarize their advantages and limitations along with their biomedical applications. The efforts of integrating the transcriptome profile with highly multiplexed proteomic and genomic data are thoroughly reviewed with results showing the integrated data being more informative than transcriptome data alone. Lastly, the latest progress toward commercialization, the remaining challenges, and future perspectives on the development of scRNA-seq technologies are briefly discussed.
Curved Versus Flat Monitors: Interactive Effects of Display Curvature Radius and Display Size on Visual Search Performance and Visual Fatigue

Objective The aim of this study is to examine the interactive effects of display curvature radius and display size on visual search accuracy, visual search speed, and visual fatigue. Background Although the advantages of curved displays have been reported, little is known about the interactive effects of display curvature radius and size. Method Twenty-seven individuals performed visual search tasks at a viewing distance of 50 cm using eight configurations involving four display curvature radii (400R, 600R, 1200R, and flat) and two display sizes (33″ and 50″). To simulate curved screens, five flat display panels were horizontally arranged with their centers concentrically repositioned following each display curvature radius. Results For accuracy, speed, and fatigue, 33″–600R and 50″–600R provided the best or comparable-to-best results, whereas 50″–flat provided the worst results. For accuracy and fatigue, 33″–flat was the second worst. The changes in the horizontal field of view and viewing angle due to display curvature as well as the association between effective display curvature radii and empirical horopter (loci of perceived equidistance) can explain these results. Conclusion The interactive effects of display curvature radius and size were evident for visual search performance and fatigue. Beneficial effects of curved displays were maintained across 33″ and 50″, whereas increasing flat display size from 33″ to 50″ was detrimental. Application For visual search tasks at a viewing distance of 50 cm, 33″–600R and 50″ 600R displays are recommended, as opposed to 33″ and 50″ flat displays. Wide flat displays must be carefully considered for visual display terminal tasks.
Social change and birth cohort decrease in social support for older adults in China: A cross-temporal meta-analysis, 1994-2018.

Social support not only plays an important role in the physical and mental health of the elderly people but also constitutes an essential resource for healthy ageing. With the rapid economic and social development during the last 40 years in China, the acceleration of urbanisation, and the disintegration of traditional extended families, the social support that Chinese older adults receive may be declining, leading to deterioration in quality of life for the rapidly ageing population. Cross-temporal meta-analysis was employed to investigate changes in older Chinese adults' social support from 1994 to 2018. One hundred and thirty-six studies (N = 82,722; age ≥ 60) that used the social support rating scale (SSRS) were analysed. Additionally, social support scores were correlated with social indicators to explore the relationship between social support and the environment of social development. Results show that social support scores decreased by 5.09 and 0.73 standard deviations over the past 24 years. Correlation with social indicators suggests that a decrease in social connectedness and an increase in economic imbalance may be responsible for the reduction in social support.
PPAR Beta/Delta and the Hallmarks of Cancer

Peroxisome proliferator-activated receptors (PPARs) belong to the nuclear hormone receptor family. Three different isoforms, PPAR alpha, PPAR beta/delta and PPAR gamma have been identified. They all form heterodimers with retinoic X receptors to activate or repress downstream target genes dependent on the presence/absence of ligands and coactivators or corepressors. PPARs differ in their tissue expression profile, ligands and specific agonists and antagonists. PPARs attract attention as potential therapeutic targets for a variety of diseases. PPAR alpha and gamma agonists are in clinical use for the treatment of dyslipidemias and diabetes. For both receptors, several clinical trials as potential therapeutic targets for cancer are ongoing. In contrast, PPAR beta/delta has been suggested as a therapeutic target for metabolic syndrome. However, potential risks in the settings of cancer are less clear. A variety of studies have investigated PPAR beta/delta expression or activation/inhibition in different cancer cell models in vitro, but the relevance for cancer growth in vivo is less well documented and controversial. In this review, we summarize critically the knowledge of PPAR beta/delta functions for the different hallmarks of cancer biological capabilities, which interplay to determine cancer growth.
PGC‐1α‐Induced Mitochondrial Alterations in 3T3 Fibroblast Cells

Abstract: Peroxisome proliferation activator receptor (PPAR) γ‐coactivator 1α (PGC‐1α), a transcription coactivator, functions as a master regulator of a wide array of metabolic and physiological processes and is an essential factor in the process of mitochondrial biogenesis. Transfection of NIH 3T3 fibroblasts with a mouse cDNA for PGC‐1α led to the induction of markers of mitochondrial biogenesis, that is, mitochondrial transcription factor A (mtTFA), cytochrome c, and mitochondrial DNA (mtDNA). Mitochondrial biogenesis‐associated net protein synthesis appears to be accomplished by a reduction in the rate of mitochondrial protein degradation with little or no change in the rate of protein synthesis. Overexpression of PGC‐1α did not adversely affect cellular proliferation. Cellular ATP levels were increased in the transfected cells and they were more resistant to oxidative stress than the control nontransfected 3T3 cells. This resistance to oxidative stress was manifested by both an improved viability and the maintenance of mitochondrial membrane potential in the transfected cells when exposed to t‐butyl hydroperoxide (t‐BOOH). It therefore appears that PGC‐1α overexpression stimulates mitochondrial biogenesis in 3T3 cells making them more resistant to oxidative stressors.