Miracle-dz/UniFAR-FTUs huggingface dataset:
Bacterial Load Comparison of the Three Main Lineages of Mycobacterium tuberculosis Complex in West Africa

Studies have shown an association between bacterial load and virulence; however, not much is known about the diversity in this phenotypic characteristic of Mycobacterium tuberculosis complex (MTBC). This study was therefore aimed to determine the differences in bacterial load of the three most prevalent MTBC genotypes (L4, L5, and L6) in West Africa at the time of diagnosis. A total of 170 paired fresh sputum samples were collected; one part in guanidinium thiocyanate (GTC) was used for RNA extraction and tuberculosis molecular bacterial load assay (TB-MBLA), and the other part without GTC was confirmed for TB positivity using GeneXpert MTB/RIF, smear microscopy grading, and culture on Löwenstein–Jensen media slants. The 170 sputum samples comprised 155 new cases, three follow-up cases, and 12 TB negative sputum samples. The time-to-culture positivity (TTP) and degree of culture positivity (DCP) were recorded. All 122 isolates obtained were spoligotyped for lineage (L) classification, but spoligotypes were obtained from 120 isolates. Of the typed isolates, 70.0, 10.8, 10.8, 4.2, 2.5, 0.8, and 0.8% were lineages 4, 5, 6, 2, 3, 1, and Mycobacterium bovis, respectively. Further analysis of the three most prevalent lineages showed significantly shorter TTP and higher DCP by L4 compared to L5 and L6, respectively: TTP 20.8, vs. 26.5, and 28.2 days; p-value = 0.005 and DCP 1.27, vs. 0.81 and 0.29, p < 0.001. The average TB-MBLA measured bacterial load of L4 was 3.82 Log10eCFU/ml which was not significantly different from 3.81 and 3.80 Log10eCFU/ml of L5 and L6, respectively, p = 0.84. Degrees of smear microscopy L4 = 1.20, L5 = 1.20, and L6 = 0.92 and GeneXpert Cq values L4 = 17.08, L5 = 18.37, and L6 = 17.59 showed no significant difference between the lineages, p = 0.72 and p = 0.48, respectively. Retrospective analysis of a larger sample confirmed the difference in TTP, p < 0.001. In conclusion, the observed shorter TTP and high DCP of L4 could signify high growth rate in culture that is independent of total bacterial load at diagnosis.
Preoperative Magnetic Resonance Imaging Radiomics for Predicting Early Recurrence of Glioblastoma

Purpose Early recurrence of glioblastoma after standard treatment makes patient care challenging. This study aimed to assess preoperative magnetic resonance imaging (MRI) radiomics for predicting early recurrence of glioblastoma. Patients and Methods A total of 122 patients (training cohort: n = 86; validation cohort: n = 36) with pathologically confirmed glioblastoma were included in this retrospective study. Preoperative brain MRI images were analyzed for both radiomics and the Visually Accessible Rembrandt Image (VASARI) features of glioblastoma. Models incorporating MRI radiomics, the VASARI parameters, and clinical variables were developed and presented in a nomogram. Performance was assessed based on calibration, discrimination, and clinical usefulness. Results The nomogram consisting of the radiomic signatures, the VASARI parameters, and blood urea nitrogen (BUN) values showed good discrimination between the patients with early recurrence and those with later recurrence, with an area under the curve of 0.85 (95% CI, 0.77-0.94) in the training cohort and 0.84 [95% CI, 0.71-0.97] in the validation cohort. Decision curve analysis demonstrated favorable clinical application of the nomogram. Conclusion This study showed the potential usefulness of preoperative brain MRI radiomics in predicting the early recurrence of glioblastoma, which should be helpful in personalized management of glioblastoma.
Contactless In-Home Monitoring of the Long-Term Respiratory and Behavioral Phenotypes in Older Adults With COVID-19: A Case Series

Currently, there is a limited understanding of long-term outcomes of COVID-19, and a need for in-home measurements of patients through the whole course of their disease. We study a novel approach for monitoring the long-term trajectories of respiratory and behavioral symptoms of COVID-19 patients at home. We use a sensor that analyzes the radio signals in the room to infer patients' respiration, sleep and activities in a passive and contactless manner. We report the results of continuous monitoring of three residents of an assisted living facility for 3 months, through the course of their disease and subsequent recovery. In total, we collected 4,358 measurements of gait speed, 294 nights of sleep, and 3,056 h of respiration. The data shows differences in the respiration signals between asymptomatic and symptomatic patients. Longitudinally, we note sleep and motor abnormalities that persisted for months after becoming COVID negative. Our study represents a novel phenotyping of the respiratory and behavioral trajectories of COVID recovery, and suggests that the two may be integral components of the COVID-19 syndrome. It further provides a proof-of-concept that contactless passive sensors may uniquely facilitate studying detailed longitudinal outcomes of COVID-19, particularly among older adults.
Quantitative Trait Locus Analysis and Identification of Candidate Genes for Micronaire in an Interspecific Backcross Inbred Line Population of Gossypium hirsutum × Gossypium barbadense

Cotton is the most important fiber crop and provides indispensable natural fibers for the textile industry. Micronaire (MIC) is determined by fiber fineness and maturity and is an important component of fiber quality. Gossypium barbadense L. possesses long, strong and fine fibers, while upland cotton (Gossypium hirsutum L.) is high yielding with high MIC and widely cultivated worldwide. To identify quantitative trait loci (QTLs) and candidate genes for MIC in G. barbadense, a population of 250 backcross inbred lines (BILs), developed from an interspecific cross of upland cotton CRI36 × Egyptian cotton (G. barbadense) Hai7124, was evaluated in 9 replicated field tests. Based on a high-density genetic map with 7709 genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers, 25 MIC QTLs were identified, including 12 previously described QTLs and 13 new QTLs. Importantly, two stable MIC QTLs (qMIC-D03-2 on D03 and qMIC-D08-1 on D08) were identified. Of a total of 338 genes identified within the two QTL regions, eight candidate genes with differential expression between TM-1 and Hai7124 were identified. Our research provides valuable information for improving MIC in cotton breeding.
Chromatin Network Analyses: Towards Structure-Function Relationships in Epigenomics

Recent technological advances have allowed us to map chromatin conformation and uncover the genome’s spatial organization of the genome inside the nucleus. These experiments have revealed the complexities of genome folding, characterized by the presence of loops and domains at different scales, which can change across development and in different cell types. There is strong evidence for a relationship between the topological properties of chromatin contacts and cellular phenotype. Chromatin can be represented as a network, in which genomic fragments are the nodes and connections represent experimentally observed spatial proximity of two genomically distant regions in a specific cell type or biological condition. With this approach we can consider a variety of chromatin features in association with the 3D structure, investigating how nuclear chromatin organization can be related to gene regulation, replication, malignancy, phenotypic variability and plasticity. We briefly review the results obtained on genome architecture through network theoretic approaches. As previously observed in protein-protein interaction networks and many types of non-biological networks, external conditions could shape network topology through a yet unidentified structure-function relationship. Similar to scientists studying the brain, we are confronted with a duality between a spatially embedded network of physical contacts, a related network of correlation in the dynamics of network nodes and, finally, an abstract definition of function of this network, related to phenotype. We summarise major developments in the study of networks in other fields, which we think can suggest a path towards better understanding how 3D genome configuration can impact biological function and adaptation to the environment.
Tumor Microenvironment–Responsive Polypeptide Nanogels for Controlled Antitumor Drug Delivery

Tumor microenvironment–responsive polypeptide nanogels belong to a biomaterial with excellent biocompatibility, easily adjustable performance, biodegradability, and non-toxic properties. They are developed for selective delivery of antitumor drugs into target organs to promote tumor cell uptake, which has become an effective measure of tumor treatment. Endogenous (such as reduction, reactive oxygen species, pH, and enzyme) and exogenous (such as light and temperature) responsive nanogels can release drugs in response to tumor tissues or cells to improve drug distribution and reduce drug side effects. This article systematically introduces the research progress in tumor microenvironment–responsive polypeptide nanogels to deliver antitumor drugs and provides a reference for the development of antitumor nanoformulations.
Validating the “Two Faces” of Envy: The Effect of Self-Control

Envy drives different behaviors, and while we often emphasize the negative effects of envy, there are also relatively positive aspects. This study explored the “two faces” of envy or behaviors that improve oneself or degrade others. In study 1 (N=466, 45.1% males and 54.9% females; Mage=18.53, SDage=2.05), we modeled the effects of envy and self-control on effort and aggression. In study 2 (N=102, 51% males and 49% females; Mage=20.56, SDage=1.88), we explored the influence of envy on striving behavior and aggressive behavior using an ego depletion paradigm. The different effects of envy on different levels were doubly verified. We established structural equation models of the interactions of benign envy, malicious envy, self-control, and associated behaviors, and we found that: (1) Individuals’ striving behavior was only affected by benign envy; (2) Individuals’ aggressive behavior was influenced by both malicious envy and self-control. Ego depletion moderated the effect of malicious envy on aggressive behavior.
Spatiotemporal Distribution of Herbivorous Insects Along Always-Green Mountaintop Forest Islands

Insects make up the bulk of terrestrial diversity and about half of insect species are herbivores that have direct relationships with their host plants and are the basis of the entire food chain, on which wildlife and humanity depend. Some herbivorous insect traits, such as their spatio-temporal distribution, are especially relevant in the current scenario of global changes, which are more pronounced in high elevation areas, helping to improve the effectiveness of conservation actions. Here we evaluated the influence that different spatiotemporal scales have on three free-feeding herbivorous insect guilds (fluid-feeding, leaf-chewing, and xylophagous insects) in montane forest islands immersed in a grassland-dominated matrix (campo rupestre). We assessed whether species turnover or nestedness was the main component determining both spatial and temporal species composition variation (β-diversity) of the herbivorous insect community. We also checked the temporal effect on herbivorous insect guilds composition between vertical strata. We sampled herbivorous insects during two summers and two winters in 14 forest islands of different sizes and shapes in a natural mountainous fragment located in southeastern Brazil. A total of 6597 herbivorous insects representing 557 morphospecies were sampled, 290 of which were fluid-feeding, 147 leaf-chewing and 120 xylophagous insects. We found a main contribution of time scale in the organization of the herbivorous insect composition sampled in this study, mainly by turnover, with small differences among guilds. Additionally, we could see that climate determined the local variation of species, corroborating that we have a highly variable always-green system over space and time where the understory community varies less in comparison to the canopy community. Our findings suggest that long-term ecological research on herbivorous community structure in relation to climatic variation is a key element for future investigations, which can be decisive for the conservation of herbivorous insect communities. We also suggest that the effects of anthropogenic pressures must be monitored in this system, since these forest islands may serve as warming refuges in a fragmented landscape holding an invaluable diversity of species that, without these old-growth forest reservoirs, would be doomed to disappear.
Persistent Effects of Historical Selective Logging on a Vascular Epiphyte Assemblage in the Forest Canopy of the Western Ghats, India

Forest canopies have been dubbed the last biological frontier and continue to remain underexplored. Vascular epiphytes form a rich assemblage of plants within the forest canopy and apart from sustaining diverse taxa, they also fulfill critical ecological functions. Vascular epiphytes are particularly sensitive to perturbations of microclimate and microhabitat within the canopy, especially from anthropogenic changes such as logging. The forests of the megadiverse Western Ghats in India harbor a rich assemblage of vascular epiphytes, but their ecology has not been examined systematically. We compared the diversity, abundance, and composition of a vascular epiphyte assemblage between an unlogged and a historically selectively logged forest in the southern Western Ghats, India, and identified factors affecting the epiphyte assemblage. Canopies of 100 trees each in selectively logged and unlogged forests were accessed using the single-rope technique. We found 20 species of vascular epiphytes with the assemblage dominated by members of Orchidaceae. The diversity and abundance of epiphytes were significantly greater in the selectively logged forest. One host tree, Cullenia exarillata, supported the greatest number of epiphytes in both forest stands. The niche widths of epiphyte species, computed with host tree species as a resource, were similar between the two stands but a greater number of species pairs overlapped in the selectively logged forest. Overall, epiphyte abundance was negatively associated with unlogged forests. Host tree species, tree height, and presence of moss on branches were positively associated with the abundance of epiphytes. Despite being ecologically important, no study has thus far examined the impact of selective logging on the epiphyte assemblage in the Western Ghats. Our findings contribute to the knowledge of vascular epiphytes from South and Southeast Asia and set the stage for future research and conservation.
A Review on the Application and Limitations of Administrative Health Care Data for the Study of Acute Kidney Injury Epidemiology and Outcomes in Children

Administrative health care databases contain valuable patient information generated by health care encounters. These “big data” repositories have been increasingly used in epidemiological health research internationally in recent years as they are easily accessible and cost-efficient and cover large populations for long periods. Despite these beneficial characteristics, it is also important to consider the limitations that administrative health research presents, such as issues related to data incompleteness and the limited sensitivity of the variables. These barriers potentially lead to unwanted biases and pose threats to the validity of the research being conducted. In this review, we discuss the effectiveness of health administrative data in understanding the epidemiology of and outcomes after acute kidney injury (AKI) among adults and children. In addition, we describe various validation studies of AKI diagnostic or procedural codes among adults and children. These studies reveal challenges of AKI research using administrative data and the lack of this type of research in children and other subpopulations. Additional pediatric-specific validation studies of administrative health data are needed to promote higher volume and increased validity of this type of research in pediatric AKI, to elucidate the large-scale epidemiology and patient and health systems impacts of AKI in children, and to devise and monitor programs to improve clinical outcomes and process of care.
Dietary Changes During COVID-19 Lockdown in Adults With Type 1 Diabetes on a Hybrid Artificial Pancreas

In this retrospective analysis, we examine the impact of the lockdown of the coronavirus pandemic (COVID-19) on eating habits in individuals with type 1 diabetes (T1D) on a hybrid artificial pancreas (HAP). Dietary composition before and during lockdown was assessed by 7-day food records of 12 participants with T1D on HAP (three men and nine women, ages 38 ± 13 years, HbA1c 6.8 ± 0.3%, M ± SD). Continuous glucose monitoring (CGM) metrics and lifestyle changes (online questionnaire) were also assessed. Compared to prelockdown, reported body weight tended to increase during lockdown with no changes in total energy intake. Participants significantly decreased animal protein intake (−2.1 ± 3.7% of total energy intake, p = 0.048), but tended to increase carbohydrate intake (+17 ± 28 g/day, p = 0.052). These changes were induced by modifications of eating habits at breakfast and lunch during weekdays. Patients consumed more cereals (+21 ± 33 g/day, p = 0.038), whole grain (+22 ± 32 g/day, p = 0.044), and sweets (+13 ± 17 g/day, p = 0.021), and less animal protein sources (−42 ± 67 g/day, p = 0.054). Participants showed a more regular meal timing and decreased physical activity. Blood glucose control remained optimal (time-in-range 76 ± 8 vs. 75 ± 7% before lockdown), and daily total insulin infusion increased (42 ± 10 vs. 39 ± 12 I.U., p = 0.045). During the lockdown, patients with T1D on HAP modified dietary habits by decreasing animal protein and increasing carbohydrate intake. This increase, mainly concerning whole grain and low-glycemic-index products, did not influence blood glucose control.
Green Leaf Volatile-Burst in Selaginella moellendorffii

Green leaf volatiles (GLVs) consist of six-carbon volatile aldehydes, alcohols, and their esters. They are formed from polyunsaturated fatty acids and are involved in the defense of plants against herbivores and pathogens. GLVs generally have low concentrations in intact healthy plant tissues, but the biosynthetic pathway to form GLVs is quickly activated by mechanical damage to tissues, an event called the GLV-burst. Most seed plants have the ability to implement GLV-burst; however, this potential in non-seed plants has not been extensively researched. In this study, we examined the GLV-burst capacity of monilophytes, lycophytes, and bryophytes, and confirmed that monilophytes and lycophytes showed substantial GLV-burst ability, while bryophytes did not, with a few exceptions. When the genome sequence of a model lycophyte, Selaginella moellendorffii was reviewed, 10 genes were found that showed high similarity with the non-canonical cytochrome P450 enzymes, CYP74s, specialized in oxylipin formation. Recombinant proteins expressed with Escherichia coli showed that one of them had the ability to encode allene oxide synthase, and another encoded hydroperoxide lyase (HPL), preferring linolenic acid 13-hydroperoxide, and it was inferred that this gene was responsible for GLV-burst in S. moellendorffii. Based on the phylogenetic tree constructed with CYP74s of non-seed and seed plants, we hypothesized that HPL was acquired independently in the lycophyte and seed plants through diversification of CYP74 genes.
Acute Exposure to Normobaric Hypoxia Impairs Balance Performance in Sub-elite but Not Elite Basketball Players

Although high and simulated altitude training has become an increasingly popular training method, no study has investigated the influence of acute hypoxic exposure on balance in team-sport athletes. Therefore, the purpose of this study was to investigate whether acute exposure to normobaric hypoxia is detrimental to balance performance in highly-trained basketball players. Nine elite and nine sub-elite male basketball players participated in a randomized, single-blinded, cross-over study. Subjects performed repeated trials of a single-leg balance test (SLBT) in an altitude chamber in normoxia (NOR; approximately sea level) with FiO2 20.9% and PiO2 ranging from 146.7 to 150.4 mmHg and in normobaric hypoxia (HYP; ~3,800 m above sea level) with FiO2 13.0% and PiO2 ranging from 90.9 to 94.6 mmHg. The SLBT was performed three times: 15 min after entering the environmental chamber in NOR or HYP, then two times more interspersed by 3-min rest. Peripheral oxygen saturation (SpO2) and heart rate (HR) were recorded at four time points: after the initial 15-min rest inside the chamber and immediately after each SLBT. Across the cohort, the balance performance was 7.1% better during NOR than HYP (P < 0.01, ηp2 = 0.58). However, the performance of the elite group was not impaired by HYP, whereas the sub-elite group performed worse in the HYP condition on both legs (DL: P = 0.02, d = 1.23; NDL: P = 0.01, d = 1.43). SpO2 was lower in HYP than NOR (P < 0.001, ηp2 = 0.99) with a significant decline over time during HYP. HR was higher in HYP than NOR (P = 0.04, ηp2 = 0.25) with a significant increase over time. Acute exposure to normobaric hypoxia detrimentally affected the balance performance in sub-elite but not elite basketball players.
Ranking Model Checking Backends for Automated Selection via Classification and Regression Learning

With classification and regression learning, we employ ranking approaches for the constraint solving backends of the ProB model checker to assess the most suited backend to use for a given constraint. In case the top ranked backend fails to solve the constraint, the predicted ranking yields a clear order of which backend to utilise in a second attempt. Our trained predictors achieve an overall runtime overhead of only 7 % while a static order of backends results in an overhead of 8.5 %. Thus, we are confident in our approach as it is more dynamic and offers
Towards Learning From Graph Representable Formal Models

We investigate different machine learning techniques to learn the semantics of graph representable formal models. Graph neural networks (GNN), which are able to learn any invariant function over graphs, became quite popular in recent years. We give empirical results on how well GNN perform in learning the semantics of nondeterministic finite automata (NFA). As our first results are positive, we discuss possible approaches to embed NFA in vector spaces such that their semantics are represented sufficiently and, thus, more classical ML techniques are applicable.