Miracle-dz/UniFAR-FTUs huggingface dataset:
A game theory model for gut bacterial nutrient utilization strategies during human infancy

Despite the fact that infant gut colonization patterns have been extensively studied, we have limited knowledge about the underlying ecological processes. This particularly relates to the ecological choice of nutrient utilization strategies. The aim of the current study was therefore to compare empirically determined nutrient utilization strategies with that expected from a combinatorial game theory model. Observational analyses for 100 mother–child pairs suggested mother–child transmission of specialists with the potential to use few nutrients. Generalists, on the other hand, with the potential to use many nutrients, peaked at three months of age for the children. The level of generalists was gradually replaced with specialists up to 12 months of age. Game theory simulation revealed a competitive advantage of generalists in an expanding population, while more specialized bacteria were favoured with the maturation of the population. This suggests that the observed increase in generalists in the three-month-old children could be due to an immature, expanding gut microbiota population while the increase of specialists at 12 months could be due to population maturation. The simulated and empirical data also correspond with respect to an increased α diversity and a decreased β diversity with the number of simulations and age, respectively. Taken together, game theory simulation of nutrient utilization strategies can therefore provide novel insight into the maturation of the human gut microbiota during infancy.
LosPem

New and emerging types of Persistent Memory (PM) technologies boost the opportunity to improve the performance of storage systems. PM can unify the main memory and secondary storage by incorporating it into legacy computer systems through the memory bus. In recent years, innovative results have been presented that exploit the byte-addressability, low latency, and non-volatility of PM; these have included local PM file systems and PM systems. However, the high overhead of ensuring data consistency has limited the performance of these systems. In this article, we propose LosPem, a novel log-structured framework for persistent memory to address the performance challenge. LosPem utilizes two techniques to accomplish this. Firstly, LosPem deploys efficient hash-indexed linked lists to maintain the log contents to reduce the significant overhead of log content retrieval. Secondly, LosPem improves the transaction throughput by decoupling a transaction into two asynchronous steps and creating a write buffer on Dynamic Random Access Memory (DRAM) write buffer for processing the frequent data writes. The experimental results show that LosPem outperforms Non-volatile Memory Library (NVML), Mnemosyne and Log-structured Non-volatile Main Memory (LSNVMM) by 27%, 1.2x, and 1.0x on a read-intensive workload. On a write-intensive workload, LosPem outperforms NVML, Mnemosyne, and LSNVMM by 1.8x, 1.2x, and 34%, respectively.
Author response: Low-density lipoprotein cholesterol and risk of intracerebral hemorrhage: A prospective study

We appreciate the comment by Sampietro et al. on our article.1 We did not collect specific information on statin use in the current study. We, thus, cannot examine whether statin use was associated with altered risk of intracerebral hemorrhage (ICH). Further studies are warranted to understand a relationship between lipid-lowering medication use and risk of ICH. We agree with you that it is important to “obtain an optimal balance between cardiovascular risk reduction, hemorrhagic risk avoidance, and mitigation of side effects related to lipid-lowering therapy. ”
Fibroblast growth factor 10 is a negative regulator of postnatal neurogenesis in the mouse hypothalamus

ABSTRACT New neurons are generated in the postnatal rodent hypothalamus, with a subset of tanycytes in the third ventricular (3V) wall serving as neural stem/progenitor cells. However, the precise stem cell niche organization, the intermediate steps and the endogenous regulators of postnatal hypothalamic neurogenesis remain elusive. Quantitative lineage-tracing in vivo revealed that conditional deletion of fibroblast growth factor 10 (Fgf10) from Fgf10-expressing β-tanycytes at postnatal days (P)4-5 results in the generation of significantly more parenchymal cells by P28, composed mostly of ventromedial and dorsomedial neurons and some glial cells, which persist into adulthood. A closer scrutiny in vivo and ex vivo revealed that the 3V wall is not static and is amenable to cell movements. Furthermore, normally β-tanycytes give rise to parenchymal cells via an intermediate population of α-tanycytes with transient amplifying cell characteristics. Loss of Fgf10 temporarily attenuates the amplification of β-tanycytes but also appears to delay the exit of their α-tanycyte descendants from the germinal 3V wall. Our findings suggest that transience of cells through the α-tanycyte domain is a key feature, and Fgf10 is a negative regulator of postnatal hypothalamic neurogenesis. Summary: Generation of new hypothalamic neurons after birth is a multistep process involving cell division and cell movements that are controlled by Fgf10.
Carbapenemase-Producing Klebsiella pneumoniae From Transplanted Patients in Brazil: Phylogeny, Resistome, Virulome and Mobile Genetic Elements Harboring blaKPC–2 or blaNDM–1

Objectives Carbapenemase-producing Klebsiella pneumoniae (CP-Kp) is a major cause of infections in transplanted patients and has been associated with high mortality rates in this group. There is a lack of information about the Brazilian structure population of CP-Kp isolated from transplanted patients. By whole-genome sequencing (WGS), we analyzed phylogeny, resistome, virulome of CP-Kp isolates, and the structure of plasmids encoding blaKPC–2 and blaNDM–1 genes. Methods One K. pneumoniae isolated from each selected transplanted patient colonized or infected by CP-Kp over a 16-month period in a hospital complex in Porto Alegre (Brazil) was submitted for WGS. The total number of strains sequenced was 80. The hospital complex in Porto Alegre comprised seven different hospitals. High-resolution SNP typing, core genome multilocus sequence typing (cgMLST), resistance and virulence genes inference, and plasmid reconstruction were performed in 80 CP-Kp. Results The mortality rate of CP-Kp colonized or infected transplanted inpatients was 21.3% (17/80). Four CP-Kp epidemic clones were described: ST11/KPC-2, ST16/KPC-2, and ST15/NDM-1, all responsible for interhospital outbreaks; and ST437/KPC-2 affecting a single hospital. The average number of acquired resistance and virulence genes was 9 (range = 2–14) and 27 (range = 6–36), respectively. Two plasmids carrying the blaKPC–2 were constructed and belonged to IncN and IncM types. Additionally, an IncFIB plasmid carrying the blaNDM–1 was described. Conclusion We detected intrahospital and interhospital spread of mobile structures and international K. pneumoniae clones as ST11, ST16, and ST15 among transplanted patients, which carry a significant range of acquired resistance and virulence genes and keep spreading across the world.
Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults

Background: Home monitoring sensor systems are increasingly used to monitor seniors in their apartments for detection of emergency situations. The aim of this study was to deliver a proof-of-concept for the use of multimodal sensor systems with pervasive computing technology for the detection of clinically relevant health problems over longer time periods. Methods: Data were collected with a longitudinal home monitoring study in Switzerland (StrongAge Cohort Study) in a cohort of 24 old and oldest-old, community-dwelling adults over a period of 1 to 2 years. Physical activity in the apartment, toilet visits, refrigerator use, and entrance door openings were quantified using a commercially available passive infrared motion sensing system (Domosafety S.A., Switzerland). Heart rate, respiration rate, and sleep quality were recorded with the commercially available EMFIT QS bed sensor device (Emfit Ltd., Finland). Vital signs and contextual data were collected using a wearable sensor on the upper arm (Everion, Biovotion, Switzerland). Sensor data were correlated with health-related data collected from the weekly visits of the seniors by health professionals, including information about physical, psychological, cognitive, and behavior status, health problems, diseases, medication, and medical diagnoses. Results: Twenty of the 24 recruited participants (age 88.9 ± 7.5 years, 79% females) completed the study; two participants had to stop their study participation because of severe health deterioration, whereas two participants died during the course of the study. A history of chronic disease was present in 12/24 seniors, including heart failure, heart rhythm disturbances, pulmonary embolism, severe insulin-dependent diabetes, and Parkinson's disease. In total, 242,232 person-hours were recorded. During the monitoring period, 963 health status records were reported and repeated clinical assessments of aging-relevant indicators and outcomes were performed. Several episodes of health deterioration, including heart failure worsening and heart rhythm disturbances, could be captured by sensor signals from different sources. Conclusions: Our results indicate that monitoring of seniors with a multimodal sensor and pervasive computing system over longer time periods is feasible and well-accepted, with a great potential for detection of health deterioration. Further studies are necessary to evaluate the full range of the clinical potential of these findings.
Analysis of Malassezia Lipidome Disclosed Differences Among the Species and Reveals Presence of Unusual Yeast Lipids

Malassezia yeasts are lipid dependent and part of the human and animal skin microbiome. However, they are also associated with a variety of dermatological conditions and even cause systemic infections. How these yeasts can live as commensals on the skin and switch to a pathogenic stage has long been a matter of debate. Lipids are important cellular molecules, and understanding the lipid metabolism and composition of Malassezia species is crucial to comprehending their biology and host–microbe interaction. Here, we investigated the lipid composition of Malassezia strains grown to the stationary phase in a complex Dixon medium broth. In this study, we perform a lipidomic analysis of a subset of species; in addition, we conducted a gene prediction analysis for the detection of lipid metabolic proteins. We identified 18 lipid classes and 428 lipidic compounds. The most commonly found lipids were triglycerides (TAG), sterol (CH), diglycerides (DG), fatty acids (FAs), phosphatidylcholine (PC), phosphatidylethanolamine (PE), ceramides, cholesteryl ester (CE), sphingomyelin (SM), acylcarnitine, and lysophospholipids. Particularly, we found a low content of CEs in Malassezia furfur, atypical M. furfur, and Malassezia pachydermatis and undetectable traces of these components in Malassezia globosa, Malassezia restricta, and Malassezia sympodialis. Remarkably, uncommon lipids in yeast, like diacylglyceryltrimethylhomoserine and FA esters of hydroxyl FAs, were found in a variable concentration in these Malassezia species. The latter are bioactive lipids recently reported to have antidiabetic and anti-inflammatory properties. The results obtained can be used to discriminate different Malassezia species and offer a new overview of the lipid composition of these yeasts. We could confirm the presence and the absence of certain lipid-biosynthesis genes in specific species. Further analyses are necessary to continue disclosing the complex lipidome of Malassezia species and the impact of the lipid metabolism in connection with the host interaction.
Grape Leaf Disease Identification Using Improved Deep Convolutional Neural Networks

Anthracnose, brown spot, mites, black rot, downy mildew, and leaf blight are six common grape leaf pests and diseases, which cause severe economic losses to the grape industry. Timely diagnosis and accurate identification of grape leaf diseases are decisive for controlling the spread of disease and ensuring the healthy development of the grape industry. This paper proposes a novel recognition approach that is based on improved convolutional neural networks for the diagnoses of grape leaf diseases. First, based on 4,023 images collected in the field and 3,646 images collected from public data sets, a data set of 107,366 grape leaf images is generated via image enhancement techniques. Afterward, Inception structure is applied for strengthening the performance of multi-dimensional feature extraction. In addition, a dense connectivity strategy is introduced to encourage feature reuse and strengthen feature propagation. Ultimately, a novel CNN-based model, namely, DICNN, is built and trained from scratch. It realizes an overall accuracy of 97.22% under the hold-out test set. Compared to GoogLeNet and ResNet-34, the recognition accuracy increases by 2.97% and 2.55%, respectively. The experimental results demonstrate that the proposed model can efficiently recognize grape leaf diseases. Meanwhile, this study explores a new approach for the rapid and accurate diagnosis of plant diseases that establishes a theoretical foundation for the application of deep learning in the field of agricultural information.
Murine Models for the Study of Fetal Alcohol Spectrum Disorders: An Overview

Prenatal alcohol exposure is associated to different physical, behavioral, cognitive, and neurological impairments collectively known as fetal alcohol spectrum disorder. The underlying mechanisms of ethanol toxicity are not completely understood. Experimental studies during human pregnancy to identify new diagnostic biomarkers are difficult to carry out beyond genetic or epigenetic analyses in biological matrices. Therefore, animal models are a useful tool to study the teratogenic effects of alcohol on the central nervous system and analyze the benefits of promising therapies. Animal models of alcohol spectrum disorder allow the analysis of key variables such as amount, timing and frequency of ethanol consumption to describe the harmful effects of prenatal alcohol exposure. In this review, we aim to synthetize neurodevelopmental disabilities in rodent fetal alcohol spectrum disorder phenotypes, considering facial dysmorphology and fetal growth restriction. We examine the different neurodevelopmental stages based on the most consistently implicated epigenetic mechanisms, cell types and molecular pathways, and assess the advantages and disadvantages of murine models in the study of fetal alcohol spectrum disorder, the different routes of alcohol administration, and alcohol consumption patterns applied to rodents. Finally, we analyze a wide range of phenotypic features to identify fetal alcohol spectrum disorder phenotypes in murine models, exploring facial dysmorphology, neurodevelopmental deficits, and growth restriction, as well as the methodologies used to evaluate behavioral and anatomical alterations produced by prenatal alcohol exposure in rodents.
Kinetics of Phenol Biodegradation by Heavy Metal Tolerant Rhizobacteria Glutamicibacter nicotianae MSSRFPD35 From Distillery Effluent Contaminated Soils

Biodegradation of phenol using bacteria is recognized as an efficient, environmentally friendly and cost-effective approach for reducing phenol pollutants compared to the current conventional physicochemical processes adopted. A potential phenol degrading bacterial strain Glutamicibacter nicotianae MSSRFPD35 was isolated and identified from Canna indica rhizosphere grown in distillery effluent contaminated sites. It showed high phenol degrading efficiency up to 1117 mg L–1 within 60 h by the secretion of catechol 1,2-dioxygenase via ortho intradial pathway. The strain MSSRFPD35 possess both the catechol 1,2 dioxygenase and catechol 2,3 dioxygenase coding genes that drive the ortho and meta pathways, but the enzymatic assay revealed that the strain cleaves catechol via ortho pathway. Haldane’s kinetic method was well fit to exponential growth data and the following kinetic parameter was obtained: μ∗ = 0.574 h–1, Ki = 268.1, Ks = 20.29 mg L–1. The true μmax and Sm were calculated as 0.37 h–1 and 73.76 mg L–1, respectively. The Haldane’s constant values were similar to earlier studies and healthy fitness depicted in correlation coefficient value R2 of 0.98. Phenol degrading kinetic’s was predicted using Haldane’s model as qmax 0.983, Ki′ 517.5 and Ks′ 9.152. Further, MSSRFPD35 was capable of utilizing different monocyclic and polycyclic aromatic hydrocarbons and to degrade phenol in the presence of different heavy metals. This study for the first time reports high phenol degrading efficiency of G. nicotianae MSSRFPD35 in the presence of toxic heavy metals. Thus, the strain G. nicotianae MSSRFPD35 can be exploited for the bioremediation of phenol and its derivatives polluted environments, co-contaminated with heavy metals.
Época de colheita e capacidade germinativa de sementes de Tibouchina mutabilis (Vell.) Cogn. (Melastomataceae)

Simao, E. , Nakamura, A.T. & Takaki, M. Harvest period and germination capacity of Tibouchina mutabilis (Vell.) Cogn. (Melastomataceae) seeds. Biota Neotrop. Jan/Apr 2007 vol. 7, no. 1 http://www.biotaneotropica. org.br/v7n1/pt/abstract? article+bn01507012007 ISSN 1676-0603. An important step for understanding the dynamic of plant species in their environment is the study of their reproductive feature. Tibouchina mutabilis (Vell.) Cogn. (Melastomataceae) is a characteristic species of Serra do Mar, with potential for recovery of degraded areas and with landscaping purpose. The aim of this study was to investigate the acquisition of germination capacity of seeds and establishment of the best period for fruit harvest by weekly harvests, when morphological and germination capacity features were observed in four stages of development. The T. mutabilis seeds germinated only under white light. Besides the necessity of light for germination, seeds of T. mutabilis did not show another type of dormancy at the end of the ripening, with high germination percentage. The germination rate increases progressively in the function of lose of moisture in the subsequent stages of development, suggesting that the high moisture was the factor that restricted the germination. The best indicator of physiological maturation of seeds is the natural opening of the capsule. The advantage of this parameter is that it can be widely utilized and it is easy to recognize it. Due to the anemochoric dispersion of seeds, we propose that the harvest must be done, with good results, of fruit with 21 days after anthesis, and drying the fruit for capsule opening for seed extraction.
Speciation and the developmental alarm clock

New species arise as the genomes of populations diverge. The developmental ‘alarm clock’ of speciation sounds off when sufficient divergence in genetic control of development leads hybrid individuals to infertility or inviability, the world awoken to the dawn of new species with intrinsic post-zygotic reproductive isolation. Some developmental stages will be more prone to hybrid dysfunction due to how molecular evolution interacts with the ontogenetic timing of gene expression. Considering the ontogeny of hybrid incompatibilities provides a profitable connection between ‘evo-devo’ and speciation genetics to better link macroevolutionary pattern, microevolutionary process, and molecular mechanisms. Here we explore speciation alongside development, emphasizing their mutual dependence on genetic network features, fitness landscapes, and developmental system drift. We assess models for how ontogenetic timing of reproductive isolation can be predictable. Experiments and theory within this synthetic perspective can help identify new rules of speciation as well as rules in the molecular evolution of development. Impact Statement Integrating speciation genetics with ontogeny can identify predictable rules in the molecular evolution of developmental pathways and in the accumulation of reproductive isolation as genomes diverge.
Switch-like control of helicase processivity by single-stranded DNA binding protein

Helicases utilize the energy of NTP hydrolysis to translocate along single-stranded nucleic acids (NA) and unwind the duplex. In the cell, helicases function in the context of other NA-associated proteins which regulate helicase function. For example, single-stranded DNA binding proteins are known to enhance helicase activity, although the underlying mechanisms remain largely unknown. F. acidarmanus XPD helicase serves as a model for understanding the molecular mechanisms of Superfamily 2B helicases, and previous work has shown that its activity is enhanced by the cognate single-stranded DNA binding protein RPA2. Here, single-molecule optical trap measurements of the unwinding activity of a single XPD helicase in the presence of RPA2 reveal a mechanism in which XPD interconverts between two states with different processivities and transient RPA2 interactions stabilize the more processive state, activating a latent “processivity switch” in XPD. These findings provide new insights on mechanisms of helicase regulation by accessory proteins.
Achieving functional neuronal dendrite structure through sequential stochastic growth and retraction

Class I ventral posterior dendritic arborisation (c1vpda) proprioceptive sensory neurons respond to contractions in the Drosophila larval body wall during crawling. Their dendritic branches run along the direction of contraction, possibly a functional requirement to maximise membrane curvature during crawling contractions. Although the molecular machinery of dendritic patterning in c1vpda has been extensively studied, the process leading to the precise elaboration of their comb-like shapes remains elusive. Here, to link dendrite shape with its proprioceptive role, we performed long-term, non-invasive, in vivo time-lapse imaging of c1vpda embryonic and larval morphogenesis to reveal a sequence of differentiation stages. We combined computer models and dendritic branch dynamics tracking to propose that distinct sequential phases of targeted growth and stochastic retraction achieve efficient dendritic trees both in terms of wire and function. Our study shows how dendrite growth balances structure–function requirements, shedding new light on general principles of self-organisation in functionally specialised dendrites. In brief An optimal wire and function trade-off emerges from noisy growth and stochastic retraction during Drosophila class I ventral posterior dendritic arborisation (c1vpda) dendrite development. Highlights C1vpda dendrite outgrowth follows wire constraints. Stochastic retraction of functionally suboptimal branches in a subsequent growth phase. C1vpda growth rules favour branches running parallel to larval body wall contraction. Comprehensive growth model reproduces c1vpda development in silico.