Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-kingdom conservation of Arabidopsis RPS24 function in 18S rRNA maturation

All 81 ribosomal proteins (RPs) that form the Arabidopsis (Arabidopsis thaliana) 80S ribosome are encoded by several paralogous genes. For example, the nearly identical RPS24A and RPS24B proteins are encoded by RPS24A and RPS24B, respectively. Here we explored the functions of RPS24A and RPS24B in Arabidopsis. Their encoding genes exhibit combined haploinsufficiency, as at least two wild-type copies of either RPS24A or RPS24B are required for plant viability and at least three are required for normal plant development. Loss-of-function of either gene caused a pointed-leaf phenotype, a typical phenotype of null or hypomorphic recessive alleles of genes encoding ribosome biogenesis factors (RBFs) or RPs. We also found that RPS24A and RPS24B act as RBFs during early stages of 18S ribosomal RNA (rRNA) maturation, as loss of RPS24A or RPS24B function reduced the 18S/25S rRNA ratio. An RPS24B-GFP fusion protein predominantly localized to the nucleolus, as expected. The rps24b-2 mutation strengthened the phenotypes of the RBF mutants mRNA transporter4-2 and small organ4-3, which are defective in 5.8S rRNA maturation. This synergistic interaction might be an effect of increased 45S rDNA transcription, which we also observed in the rps24 mutants. Therefore, the Arabidopsis RPS24 proteins act as RBFs during 18S rRNA maturation, like their human and yeast putative orthologs. Only two plant RPs were previously shown to act not only as structural components of the ribosome but also as RBFs. We provide evidence that RPS24 proteins also regulate 45S rDNA transcription, which has not been described for their yeast or human orthologs.
Letter regarding “Evidence-based hyponatremia management in liver disease”

Copyright © 2023 by Korean Association for the Study of the Liver This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Corresponding author : Daphne J. Theodorou Department of Radiology, General Hospital of Ioannina, 13 Papadopoulos street, Ioannina, Greece Tel: +302651038003, Fax: +302651038003, E-mail: daphne_theodorou@hotmail.com https://orcid.org/0000-0002-2477-3871 pISSN 2287-2728 eISSN 2287-285X
Random paths through a convex region

The distribution of the length of random secants through a convex region is formulated in terms of the intersection volume of the convex region with its translated self. This method allows a more straightforward approach to calculating secant-length distributions for various measures of randomness. The results are applied to calculating the transit-time distribution of particles traversing a convex region. Several examples are given.
Infant Left Amygdala Volume Is Negatively Associated with Fecal Microbiota Diversity

Introduction Rodent studies have addressed the importance of early life gut microbiota in the development of emotional and social functioning. Studies in human infants are still scarce, but associations with cognition and temperament have been reported. Neuroimaging studies have linked the amygdala with fecal microbiota diversity in infants, but crucially these studies have not covered the neonatal period, and the current study addressed this gap. Methods The study population included 65 infants drawn from the ongoing, general population based FinnBrain Birth Cohort Study. Brain MRI was performed around the age of one month (mean age 25 days). Fecal microbiota profiles (mean 68 days) were assessed by 16s rRNA amplicon sequencing at the age of 2.5 months. Results We found a negative association between infant left amygdala volume and alpha diversity (n=52, beta =-0.0043, p=0.034, adjusted for infant sex, breastfeeding, delivery mode, age during fecal sampling, age from conception during scan, and intracranial volume, Fig.1). Amygdala volumes were not associated with beta diversity (p=0.21), nor with the abundances of individual genera when adjusted for the same covariates and multiple testing. Conclusion Our results provide first evidence for associations between the brain and fecal microbiota in human neonates. Although the reported data do not allow investigation of underlying mechanisms, i.e. about the directionality of the hypothesized gut-brain connection, the reported connection encourages for future investigations of manifestations of gut-brain axis in early life.
Phylogeny, morphology, virulence, ecology, and host range of Ordospora pajunii (Ordosporidae), a microsporidian symbiont of Daphnia spp

Impacts of microsporidia on host individuals are frequently subtle and can be context dependent. A key example of the latter comes from a recently discovered microsporidian symbiont of Daphnia, the net impact of which was found to shift from negative to positive based on environmental context. Given this, we hypothesized low baseline virulence of the microsporidian; here, we investigated the impact of infection on hosts in controlled conditions and the absence of other stressors. We also investigated its phylogenetic position, ecology and host range. The genetic data indicates that the symbiont is Ordospora pajunii, a newly described microsporidian parasite of Daphnia. We show that O. pajunii infection damages the gut, causing infected epithelial cells to lose microvilli and then rupture. The prevalence of this microsporidian could be high (up to 100% in the lab and 77% of adults in the field). Its overall virulence was low in most cases, but some genotypes suffered reduced survival and/or reproduction. Susceptibility and virulence were strongly host-genotype dependent. We found that North American O. pajunii were able to infect multiple Daphnia species, including the European species D. longispina, as well as Ceriodaphnia spp. Given the low, often undetectable virulence of this microsporidian, and potentially far reaching consequences of infections for the host when interacting with other pathogens or food, this Daphnia - O. pajunii symbiosis emerges as a valuable system for studying the mechanisms of context-dependent shifts between mutualism and parasitism, as well as for understanding how symbionts might alter host interactions with resources. Importance The net outcome of symbiosis depends on the costs and benefits to each partner. Those can be context dependent, driving the potential for an interaction to change between parasitism and mutualism. Understanding the baseline fitness impact in an interaction can help us understand those shifts; for an organism that is generally parasitic, it should be easier for it to become a mutualist if its baseline virulence is relatively low. Recently, a microsporidian was found to become beneficial to its Daphnia hosts in certain ecological contexts, but little was known about the symbiont (including its species identity). Here, we identify it as the microsporidium Ordospora pajunii. Despite the parasitic nature of microsporidia, we found O. pajunii to be, at most, mildly virulent; this helps explain why it can shift towards mutualism in certain ecological contexts and helps establish O. pajunii is a valuable model for investigating shifts along the mutualism-parasitism continuum.
Six-months clinical and intracoronary imaging follow-up after reverse T and protrusion or double-kissing and crush stenting for the treatment of complex left main bifurcation lesions

Background There is a debate regarding the best stent strategy for unprotected distal left main (LM) bifurcation disease. Among two-stent techniques, double-kissing and crush (DKC) is favored in current guidelines but is complex and requires expertise. Reverse T and Protrusion (rTAP) was shown to be a comparable strategy regarding short-term efficacy and safety, but with reduced procedural complexity. Aim To compare rTAP vs. DKC by optical coherence tomography (OCT) on the intermediate term. Methods 52 consecutive patients with complex unprotected LM stenoses (Medina 0,1,1 or 1,1,1) were randomized to either DKC or rTAP and followed-up for a median of 189[180–263] days for clinical and OCT outcomes. Results At follow-up OCT showed similar change in the side branch (SB) ostial area (primary endpoint). The confluence polygon showed a higher percentage of malapposed stent struts in the rTAP group that did not reach statistical significance (rTAP: 9.7[4.4–18.3] % vs. DKC: 3[0.07–10.9] %; p = 0.064). It also showed a trend towards larger neointimal area relative to the stent area (DKC: 8.8 [6.9 to 13.4] % vs. rTAP: 6.5 [3.9 to 8.9] %; p = 0.07), and smaller luminal area (DKC: 9.54[8.09–11.07] mm2 vs. rTAP: 11.21[9.53–12.42] mm²; p = 0.09) in the DKC group. The minimum luminal area in the parent vessel distal to the bifurcation was significantly smaller in the DKC group (DKC: 4.64 [3.64 to 5.34] mm² vs. rTAP: 6.76 [5.20 to 7.29] mm²; p = 0.03). This segment also showed a trend for smaller stent areas (p = 0.05 to 0.09), and a bigger neointimal area relative to the stent area (DKC: 8.94 [5.43 to 10.5]% vs. rTAP: 4.75 [0.08 to 8.5]%; p = 0.06) in the DKC patients. The incidence of clinical events was comparably low in both groups. Conclusion At 6-months, OCT showed a similar change in the SB ostial area (primary endpoint) in rTAP compared to DKC. There was also a trend for smaller luminal areas in the confluence polygon and the distal parent vessel, and a larger neointimal area relative to the stent area, in DKC, along with a tendency for more malapposed stent struts in rTAP. Clinical Trial Registration https://clinicaltrials.gov/ct2/show/NCT03714750, identifier: NCT03714750.
Norms and T-scores for screeners of alcohol use, depression and anxiety in the population of Suriname

Background There is a considerable gap between care provision and the demand for care for common mental disorders in low-and-middle-income countries. Screening for these disorders, e.g., in primary care, will help to close this gap. However, appropriate norms and threshold values for screeners of common mental disorders are lacking. Methods In a survey study, we gathered data on frequently used screeners for alcohol use disorders, (AUDIT), depression, (CES-D), and anxiety disorders (GAD-7, ACQ, and BSQ) in a representative sample from Suriname, a non-Latin American Caribbean country. A stratified sampling method was used by random selection of 2,863 respondents from 5 rural and 12 urban resorts. We established descriptive statistics of all scale scores and investigated unidimensionality. Furthermore, we compared scores by gender, age-group, and education level with t-test and Mann–Whitney U tests, using a significance level of p < 0.05. Results Norms and crosswalk tables were established for the conversion of raw scores into a common metric: T-scores. Furthermore, recommended cut-off values on the T-score metric for severity levels were compared with international cut-off values for raw scores on these screeners. Discussion The appropriateness of these cut-offs and the value of converting raw scores into T-scores are discussed. Cut-off values help with screening and early detection of those who are likely to have a common mental health disorder and may require treatment. Conversion of raw scores to a common metric in this study facilitates the interpretation of questionnaire results for clinicians and can improve health care provision through measurement-based care.
Dung beetles (Coleoptera: Scarabaeidae) in grazing lands of the Neotropics: A review of patterns and research trends of taxonomic and functional diversity, and functions

Dung beetles are one of the most representative groups of insects associated with livestock, as they take advantage of the manure of livestock for food and reproduction. They have been widely used as a bio-indicator group to evaluate their responses to land-use change and other environmental disturbances by analyzing species diversity at different spatial and temporal scales. However, the impacts of livestock management practices, forms, and history on dung beetle diversity are still poorly understood. This paper is an exhaustive and systematic review of the existing peer-reviewed and indexed literature on the taxonomic diversity (species richness and composition), functional diversity, and ecological functions of dung beetles from different provinces and biogeographic domains in tropical grazing lands of the Neotropics. We analyzed the timeline of the studies conducted so far, and we detected increasing literature produced mainly in South America. We included the most frequent objectives, tendencies, software, and statistical analyses. Given the significant heterogeneity of livestock landscapes in the Neotropics, the reviewed studies have conceptualized broadly what a pasture is, and the authors have used different descriptions of other grazing lands. Additionally, management data and livestock practices vary widely among studies, and management history is poorly described. In future research, it is relevant to include as much information as possible and the consequences of different livestock management practices on additional ecological attributes of dung beetle assemblages at different landscape scales (spatial and temporal) to predict how ecological processes change in Neotropical landscapes. Considering the importance of the data to be included in future work, we propose a collection format to unify the information collected in the field when conducting ecological studies in grazing lands. Moreover, we define a classification system to homogenize the features that distinguish the multiple tropical grazing lands reported in the literature. Preserving dung beetle diversity and associated ecological functions is urgent for maintaining ecosystem services in grazing lands. The challenge for research institutions is to continue filling gaps in knowledge to help those who work in transferring knowledge, to help ranchers exercise better options for more sustainable livestock farming, and to publish results for conservation decision-making.
Perception of disease, dyadic coping, and the quality of life of oncology patients in the active treatment phase and their life partners: an approach based on the actor-partner interdependence model

Objective The aim of this study based on the Systemic Transactional Model was to examine the relationship between dyadic coping and (1) disease perception and (2) quality of life of a sample of cancer patients and their life partners. Method This cross-sectional study included 138 oncological dyads. The following questionnaires were used: Stress Appraisal Measure, Dyadic Coping Inventory, and European Organisation for Research and Treatment of Cancer QLQ-C30. Data collected was analysed by applying the actor-partner interdependence model. Results The perception of the disease as a threat as well as its centrality significantly negatively influences the positive forms of dyadic coping whilst the perception of the disease as a challenge has a significant positive influence on them. Dyadic coping does not influence symptoms but has significant influences on global health/quality of life. Conclusion This study has highlighted new information regarding how couples cope with cancer. The results encourage the inclusion of the perception of the disease and dyadic coping in interventions that aim to improve the quality of life of cancer patients and their life partners.
Machine learning for the prediction of cognitive impairment in older adults

Objective The purpose of this study was to develop and validate a predictive model of cognitive impairment in older adults based on a novel machine learning (ML) algorithm. Methods The complete data of 2,226 participants aged 60–80 years were extracted from the 2011–2014 National Health and Nutrition Examination Survey database. Cognitive abilities were assessed using a composite cognitive functioning score (Z-score) calculated using a correlation test among the Consortium to Establish a Registry for Alzheimer's Disease Word Learning and Delayed Recall tests, Animal Fluency Test, and the Digit Symbol Substitution Test. Thirteen demographic characteristics and risk factors associated with cognitive impairment were considered: age, sex, race, body mass index (BMI), drink, smoke, direct HDL-cholesterol level, stroke history, dietary inflammatory index (DII), glycated hemoglobin (HbA1c), Patient Health Questionnaire-9 (PHQ-9) score, sleep duration, and albumin level. Feature selection is performed using the Boruta algorithm. Model building is performed using ten-fold cross-validation, machine learning (ML) algorithms such as generalized linear model (GLM), random forest (RF), support vector machine (SVM), artificial neural network (ANN), and stochastic gradient boosting (SGB). The performance of these models was evaluated in terms of discriminatory power and clinical application. Results The study ultimately included 2,226 older adults for analysis, of whom 384 (17.25%) had cognitive impairment. After random assignment, 1,559 and 667 older adults were included in the training and test sets, respectively. A total of 10 variables such as age, race, BMI, direct HDL-cholesterol level, stroke history, DII, HbA1c, PHQ-9 score, sleep duration, and albumin level were selected to construct the model. GLM, RF, SVM, ANN, and SGB were established to obtain the area under the working characteristic curve of the test set subjects 0.779, 0.754, 0.726, 0.776, and 0.754. Among all models, the GLM model had the best predictive performance in terms of discriminatory power and clinical application. Conclusions ML models can be a reliable tool to predict the occurrence of cognitive impairment in older adults. This study used machine learning methods to develop and validate a well performing risk prediction model for the development of cognitive impairment in the elderly.
The relationship between use of complementary and alternative medicine and health literacy in chronically ill outpatient cases: a cross-sectional study in southeastern Iran

Background Chronically ill outpatient cases use a variety of complementary and alternative medicines due to their diseases and therapeutic complications. Chronic condition, quality of life, and health literacy all affect the use of complementary medicine among chronically ill outpatient cases. Health literacy helps patients make fully informed decisions about the use of complementary and alternative medicine. This study aimed to investigate the relationship between complementary and alternative medicine and health literacy in chronically ill outpatient cases. Method This cross-sectional analytical-descriptive study was conducted on 400 chronically ill outpatient cases referred to medical centers affiliated to Kerman University of Medical Sciences. Convenience sampling was used. Research tools included the complementary and alternative medicine questionnaire and the health literacy questionnaire. SPSS25 was used to analyze data. Results The mean use of complementary and alternative medicine in a recent year was 16.75 ± 7.89, which was lower than the mid-point of the questionnaire (84). Prayer, medicinal plants, vitamin supplements, music therapy, and art therapy were the mostly used complementary and alternative medicine methods. The most common reasons for using complementary medicine were to reduce physical complications and improve anxiety and stress. The mean satisfaction with the use of complementary and alternative medicine was 34.96 ± 6.69. The mean health literacy score was 67.13 ± 19.90. Decision-making and the use of health information had the highest mean score among the dimensions of health literacy, whereas reading skills received the lowest mean score. We found a significant and direct relationship between the use of complementary and alternative medicine, health literacy, and all its dimensions. Conclusion The study results showed that health literacy predicted the use of complementary and alternative medicine. Health education and promotion programs may be useful for improvement of health literacy in the community.
The electrophysiological characteristics of social exclusion: the perspective of close and distant relationships

The sources of social exclusion are very wide, ranging from the closest people to strangers. However, current studies mainly reveal the electrophysiological characteristics of social exclusion by means of binary comparison between social exclusion and social inclusion, and lack of in-depth analysis of the differences caused by different sources of exclusion. In this study, a static passing ball paradigm system including close and distant relationship identity information was used to reveal the electrophysiological characteristics of individuals when they were excluded by people with different close and distant relationships. The results showed that there was a degree effect of P2, P3a, and LPC components when individuals were excluded by people with different close and distant relationships. Specifically, the amplitude of P2, P3a, and LPC components was larger when individuals were excluded by more distant people. The results indicated that individuals would become more alert and perceive stronger exclusion experience when they were excluded by more distant people, which provided more diversified evidence for the conclusion that electrophysiological components were larger under the condition of exclusion, and revealed the electrophysiological basis behind the multiple motivation models. The results also helped to explain the physiological reasons behind individuals’ different coping behaviors toward excluder with different importance of relationship.
Barcode demultiplexing of nanopore sequencing raw signals by unsupervised machine learning

Introduction: Oxford Nanopore Technologies (ONT) is a third generation sequencing approach that allows the analysis of individual, full-length nucleic acids. ONT records the alterations of an ionic current flowing across a nano-scaled pore while a DNA or RNA strand is threading through the pore. Basecalling methods are then leveraged to translate the recorded signal back to the nucleic acid sequence. However, basecall generally introduces errors that hinder the process of barcode demultiplexing, a pivotal task in single-cell RNA sequencing that allows for separating the sequenced transcripts on the basis of their cell of origin. Methods: To solve this issue, we present a novel framework, called UNPLEX, designed to tackle the barcode demultiplexing problem by operating directly on the recorded signals. UNPLEX combines two unsupervised machine learning methods: autoencoders and self-organizing maps (SOM). The autoencoders extract compact, latent representations of the recorded signals that are then clustered by the SOM. Results and Discussion: Our results, obtained on two datasets composed of in silico generated ONT-like signals, show that UNPLEX represents a promising starting point for the development of effective tools to cluster the signals corresponding to the same cell.