Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning Approach for Imputation of Missing Values in Actigraphy Data: Algorithm Development Study

Background Data collected by an actigraphy device worn on the wrist or waist can provide objective measurements for studies related to physical activity; however, some data may contain intervals where values are missing. In previous studies, statistical methods have been applied to impute missing values on the basis of statistical assumptions. Deep learning algorithms, however, can learn features from the data without any such assumptions and may outperform previous approaches in imputation tasks. Objective The aim of this study was to impute missing values in data using a deep learning approach. Methods To develop an imputation model for missing values in accelerometer-based actigraphy data, a denoising convolutional autoencoder was adopted. We trained and tested our deep learning–based imputation model with the National Health and Nutrition Examination Survey data set and validated it with the external Korea National Health and Nutrition Examination Survey and the Korean Chronic Cerebrovascular Disease Oriented Biobank data sets which consist of daily records measuring activity counts. The partial root mean square error and partial mean absolute error of the imputed intervals (partial RMSE and partial MAE, respectively) were calculated using our deep learning–based imputation model (zero-inflated denoising convolutional autoencoder) as well as using other approaches (mean imputation, zero-inflated Poisson regression, and Bayesian regression). Results The zero-inflated denoising convolutional autoencoder exhibited a partial RMSE of 839.3 counts and partial MAE of 431.1 counts, whereas mean imputation achieved a partial RMSE of 1053.2 counts and partial MAE of 545.4 counts, the zero-inflated Poisson regression model achieved a partial RMSE of 1255.6 counts and partial MAE of 508.6 counts, and Bayesian regression achieved a partial RMSE of 924.5 counts and partial MAE of 605.8 counts. Conclusions Our deep learning–based imputation model performed better than the other methods when imputing missing values in actigraphy data.
A Real‐World Evidence Framework for Optimizing Dosing in All Patients With COVID‐19

Potential treatments for coronavirus disease 2019 (COVID‐19) are being investigated at unprecedented speed, and successful treatments will rapidly be used in tens or hundreds of thousands of patients. To ensure safe and effective use in all those patents it is essential also to develop, at unprecedented speed, a means to provide frequently updated, optimal dosing information for all patient subgroups. Success will require immediate collaboration between drug developers, academics, and regulators.
Location First: Targeting Acute Myeloid Leukemia Within Its Niche

Despite extensive research and development of new treatments, acute myeloid leukemia (AML)-backbone therapy has remained essentially unchanged over the last decades and is frequently associated with poor outcomes. Eradicating the leukemic stem cells (LSCs) is the ultimate challenge in the treatment of AML. Emerging evidence suggests that AML remodels the bone marrow (BM) niche into a leukemia-permissive microenvironment while suppressing normal hematopoiesis. The mechanism of stromal-mediated protection of leukemic cells in the BM is complex and involves many adhesion molecules, chemokines, and cytokines. Targeting these factors may represent a valuable approach to complement existing therapies and overcome microenvironment-mediated drug resistance. Some strategies for dislodging LSCs and leukemic blasts from their protective niche have already been tested in patients and are in different phases of the process of clinical development. Other strategies, such as targeting the stromal cells remodeling processes, remain at pre-clinical stages. Development of humanized xenograft mouse models, which overcome the mismatch between human leukemia cells and the mouse BM niche, is required to generate physiologically relevant, patient-specific human niches in mice that can be used to unravel the role of human AML microenvironment and to carry out preclinical studies for the development of new targeted therapies.
Mechanisms of Hamstring Strain Injury: Interactions between Fatigue, Muscle Activation and Function

Isolated injury to the long head of biceps femoris is the most common type of acute hamstring strain injury (HSI). However, the precise hamstring injury mechanism (i.e., sprint-type) is still not well understood, and research is inconclusive as to which phase in the running cycle HSI risk is the greatest. Since detailed information relating to hamstring muscle function during sprint running cannot be obtained in vivo in humans, the findings of studies investigating HSI mechanisms are based on modeling that requires assumptions to be made based on extrapolations from anatomical and biomechanical investigations. As it is extremely difficult to account for all aspects of muscle-tendon tissues that influence function during high-intensity running actions, much of this complexity is not included in these models. Furthermore, the majority of analyses do not consider the influence of prior activity or muscular fatigue on kinematics, kinetics and muscle activation during sprinting. Yet, it has been shown that fatigue can lead to alterations in neuromuscular coordination patterns that could potentially increase injury risk. The present critical review will evaluate the current evidence on hamstring injury mechanism(s) during high-intensity running and discuss the interactions between fatigue and hamstring muscle activation and function.
HEMOGLOBIN POTENTIATES THE PRODUCTION OF REACTIVE OXYGEN SPECIES BY ALVEOLAR MACROPHAGES

The objectives of this investigation were (1) to determine the effects of hemoglobin on the production of reactive oxygen species by activated rat alveolar macrophages, (2) to determine a possible mechanism for these effects, and (3) to determine which part of the hemoglobin molecule is responsible for these effects. Production of reactive oxygen species by phorbol myristate acetate (PMA)-stimulated cells was assessed by measuring luminol-enhanced chemiluminescence (CL). Hemoglobin enhances PMA-stimulated CL in a dose-dependent manner. The effect is maximal at 0.5 1.0mu M hemoglobin where PMA-induced CL is increased by approximately 20-fold. Superoxide anion release from PMA stimulated cells is not affected by hemoglobin. However, the hemoglobin-induced enhancement of PMA stimulated CL is inhibited by superoxide dismutase, catalase, dimethylthiourea, or deferoxamine. These results suggest that hydroxyl radical may be formed from hydrogen peroxide which is derived from superoxide anion. Measurements of electron spin resonance spectra following spin trapping of radicals verify that hydroxyl radicals are produced by the cells in the presence of PMA and hemoglobin. The hemoglobin effects appear to require iron in a protoporphyrin complex, because hemin stimulates PMA induced CL, whereas neither ferrous nor ferric iron has any effect. These findings taken together suggest that hemoglobin can act as a biological Fenton reagent to enhance the production of reactive oxygen species from alveolar macrophages and potentially contribute to lung damage during leakage of blood into the alveolar spaces.
Metagenomic profiling of ammonia- and methane-oxidizing microorganisms in a Dutch drinking water treatment plant

Elevated concentrations of ammonium and methane in groundwater can cause severe problems during drinking water production. To avoid their accumulation, raw water in the Netherlands, and many other countries, is purified by sand filtration. These drinking water filtration systems select for microbial communities that mediate the biodegradation of organic and inorganic compounds. In this study, the active layers and wall biofilm of a Dutch drinking water treatment plant (DWTP) were sampled at different locations along the filtration units of the plant over three years. We used high-throughput sequencing in combination with differential coverage and sequence composition-based binning to recover 56 near-complete metagenome-assembled genomes (MAGs) with an estimated completion of ≥70% and with ≤10% redundancy. These MAGs were used to characterize the microbial communities involved in the conversion of ammonia and methane. The methanotrophic microbial communities colonizing the wall biofilm (WB) and the granular material of the primary rapid sand filter (P-RSF) were dominated by members of the Methylococcaceae and Methylophilaceae. The abundance of these bacteria drastically decreased in the secondary rapid sand filter (S-RSF) samples. In all samples, complete ammonia-oxidizing (comammox) Nitrospira were the most abundant nitrifying guild. Clade A comammox Nitrospira dominated the P-RSF, while clade B was most abundant in WB and S-RSF, where ammonium concentrations were much lower. In conclusion, the knowledge obtained in this study contributes to understanding the role of microorganisms in the removal of carbon and nitrogen compounds during drinking water production. We furthermore found that drinking water treatment plants represent valuable model systems to study microbial community function and interaction. Highlights Microbial distribution was mainly influenced by sampling location within the DWTP Clade A comammox Nitrospira were the dominant nitrifiers in the primary sand filter Clade B was most abundant in samples from wall biofilm and the secondary filter A novel Methylophilaceae-affiliated methanotroph dominated the primary sand filter
Habitat use and diet in sympatric species of rodents of the low Paraná delta, Argentina

La disponibilite de la couverture vegetale a ete consideree comme l'une des ressources les plus importantes qui determinent l'utilisation de l'habitat par les Cricetines. Nous decrivons dans ce travail l'effet des variations des principaux items alimentaires (identifies sur place) sur l'utilisation des habitats par Oxymycterus rutilans, Akodon azarae, Scapteromys tumidus et Oligoryzomys delticola dans le delta de Buenos Aires. Nos resultats montrent que A. azarae se nourrit surtout d'invertebres, et a un degre moindre de vegetaux. Les invertebres sont aussi l'item principal du regime de S. tumidus et O. rutilans, alors que O. delticola prefere la vegetation verte. S. tumidus et O. delticola utilisent toute l'annee des habitats bas tandis que A. azarae et O. rutilans montrent des variations saisonnieres dans leurs preferences d'habitat; mais ces variations n'etaient pas associes a la disponibilite de la nourriture. Nous suggerons que les adaptations morphologiques a la vie amphibie de S. tumidus et les aptitudes au grimper de O. delticola rendent ces especes plus efficaces dans les habitats bas (c'est-a-dire inondables, avec une strate de buissons) que A. azarae et O. rutilans. Chez cette derniere espece les variations saisonnieres de l'utilisation de l'habitat paraissent etre une strategie utilisee par les populations pour eviter les effets negatifs des temperatures extremes.
Fabrication of Transgelosomes for Enhancing the Ocular Delivery of Acetazolamide: Statistical Optimization, In Vitro Characterization, and In Vivo Study

Acetazolamide (ACZ) is a potent carbonic anhydrase inhibitor that is used for the treatment of glaucoma. Its oral administration causes various undesirable side effects. This study aimed to formulate transgelosomes (TGS) for enhancing the ocular delivery of ACZ. ACZ-loaded transfersomes were formulated by the ethanol injection method, using phosphatidylcholine (PC) and different edge activators, including Tween 80, Span 60, and Cremophor RH 40. The effects of the ratio of lipid to surfactant and type of surfactant on % drug released after 8 h (Q8h) and entrapment efficiency (EE%) were investigated by using Design-Expert software. The optimized formula was formulated as TGS, using poloxamers as gelling agents. In vitro and in vivo characterization of ACZ-loaded TGS was performed. According to optimization study, F8 had the highest desirability value and was chosen as the optimized formula for preparing TGS. F8 appeared as spherical elastic nanovesicles with Q8h of 93.01 ± 3.76% and EE% of 84.44 ± 2.82. Compared to a free drug, TGS exhibited more prolonged drug release of 71.28 ± 0.46% after 8 h, higher ex vivo permeation of 66.82 ± 1.11% after 8 h and a significant lowering of intraocular pressure (IOP) for 24 h. Therefore, TGS provided a promising technique for improving the corneal delivery of ACZ.
Simple Rules for Interspecific Dominance in Systems with Exploitative and Apparent Competition

Because mechanistic models of interspecific interactions are often complex, one should deliberately seek simple unifying principles that transcend system-specific details. Earlier work on resource competition has led to the "R* rule," which states that a dominant competitor suppresses resources to a lower level than any other competing species. This rule describes the outcome of even ornate models of competition. Here we show that analogous simple rules can characterize systems with predation. We first demonstrate, for a simple two-prey, one-predator model without resource competition but with a predator numerical response leading to apparent competition, that the winning prey supports (and withstands) the higher predator density; that is, the outcome is described by a "P* rule. " We then develop a general model in which predation is inflicted evenhandedly on two prey species competing for a single resource and show that the R* and P* rules hold: the winning prey both depresses resources to the lowest level and sustains the higher predator density. We next examine a more complex model with differential predation. Assuming a closed system (i.e., a fixed nutrient pool), we portray the four-dimensional system dynamics in a two-dimensional graphical model, and we assess the domain of applicability of simple dominance rules in more complex systems. We address the generality of our conclusions and end by examining the implications of different, reasonable biological constraints for community structure.
Ultra-high resolution fMRI reveals origins of feedforward and feedback activity within laminae of human ocular dominance columns

Ultra-high field MRI can functionally image the cerebral cortex of human subjects at the submillimeter scale of cortical columns and laminae. Here, we investigate both in concert, by, for the first time, imaging ocular dominance columns (ODCs) in primary visual cortex (V1) across different cortical depths. We ensured that putative ODC patterns in V1 (a) are stable across runs, sessions, and scanners located in different continents (b) have a width (∼1.3 mm) expected from post-mortem and animal work and (c) are absent at the retinotopic location of the blind spot. We then dissociated the effects of bottom-up thalamo-cortical input and attentional feedback processes on activity in V1 across cortical depth. Importantly, the separation of bottom-up information flows into ODCs allowed us to validly compare attentional conditions while keeping the stimulus identical throughout the experiment. We find that, when correcting for draining vein effects and using both model-based and model-free approaches, the effect of monocular stimulation is largest at deep and middle cortical depths. Conversely, spatial attention influences BOLD activity exclusively near the pial surface. Our findings show that simultaneous interrogation of columnar and laminar dimensions of the cortical fold can dissociate thalamocortical inputs from top-down processing, and allow the investigation of their interactions without any stimulus manipulation. Significance Statement The advent of ultra-high field fMRI allows for the study of the human brain non-invasively at submillimeter resolution, bringing the scale of cortical columns and laminae into focus. De Hollander et al imaged the ocular dominance columns and laminae of V1 in concert, while manipulating top-down attention. This allowed them to separate feedforward from feedback processes in the brain itself, without resorting to the manipulation of incoming information. Their results show how feedforward and feedback processes interact in the primary visual cortex, highlighting the different computational roles separate laminae play.
Agro-morphological and phenotypic variability of sweet basil (Ocimum basilicum L.) genotypes for breeding purposes

The genus Ocimum is very complicated due to the presence of huge morphological variability along with genetic diversity. Basil (Ocimum basilicum L.) has pharmacological properties like headaches, coughs, diarrhea, constipation, warts, worms, kidney malfunction, and its potential as a therapeutic agent in treating various age-related diseases. The present investigation comprised of sixty-one genotypes of basil was undertaken to characterize the genotypes based on morphological and phenological features, herbs and essential oil yield of genotypes. A wide range of variations for traits like days to first cutting (56.92-101.6), plant height (13.67-71.90 cm), branch number (3.28-19.43 number/plant), fresh herb yields (12.94-274.11 g/plant), and essential oil yield (0.04-1.71%) were observed and can be useful for breeding purposes. PI 652070 and PI 296391 genotypes were found superior in case of the highest herbs yield as compared with other genotypes. Overall, in PI 358469 and Ames 32309 genotypes exhibited the highest essential oil content. The constellation analysis was conducted to investigate the genetic diversity of basil genotypes. According to the constellation plot analysis, leaf shape and color were evaluated in 2017 and most of the basil genotypes located in the same main group. In 2018, moonlight and dino cultivars located in the same cluster 1 (C1) with PI 141198 (US/Maryland) genotype and Georgia genotypes located in the same main group and they also took place in the sub-main group except Ames 32314 genotype depending on UPOV criteria. Each two years, Bolu genotype and midnight were found in the same main group.
The Nervous System Cytoskeleton under Oxidative Stress

Oxidative stress is a key mechanism causing protein aggregation, cell death and neurodegeneration in the nervous system. The neuronal cytoskeleton, that is, microtubules, actin filaments and neurofilaments, plays a key role in defending the nervous system against oxidative stress-induced damage and is also a target for this damage itself. Microtubules appear particularly susceptible to damage, with oxidative stress downregulating key microtubule-associated proteins [MAPs] and affecting tubulin through aberrant post-translational modifications. Actin filaments utilise oxidative stress for their reorganisation and thus may be less susceptible to deleterious effects. However, because cytoskeletal components are interconnected through crosslinking proteins, damage to one component affects the entire cytoskeletal network. Neurofilaments are phosphorylated under oxidative stress, leading to the formation of protein aggregates reminiscent of those seen in neurodegenerative diseases. Drugs that target the cytoskeleton may thus be of great use in treating various neurodegenerative diseases caused by oxidative stress.
DDRP: Real-time phenology and climatic suitability modeling of invasive insects

Rapidly detecting and responding to new invasive species and the spread of those that are already established is essential for reducing their potential threat to food production, the economy, and the environment. We describe a new multi-species spatial modeling platform that integrates mapping of phenology and climatic suitability in real-time to provide timely and comprehensive guidance for stakeholders needing to know both where and when invasive insect species could potentially invade the conterminous United States. The Degree-Days, Risk, and Phenological event mapping (DDRP) platform serves as an open-source and relatively easy-to-parameterize decision support tool to help detect new invasive threats, schedule monitoring and management actions, optimize biological control, and predict potential impacts on agricultural production. DDRP uses a process-based modeling approach in which degree-days and temperature stress are calculated daily and accumulate over time to model phenology and climatic suitability, respectively. Products include predictions of the number of completed generations, life stages present, dates of phenological events, and climatically suitable areas based on two levels of climate stress. Species parameter values can be derived from laboratory and field studies, and from published and newly fitted CLIMEX models. DDRP is written entirely in R, making it flexible and extensible, and capitalizes on multiple R packages to generate gridded and graphical outputs. We illustrate the DDRP modeling platform and the process of model parameterization using two invasive insect species as example threats to United States agriculture: the light brown apple moth, Epiphyas postvittana, and the small tomato borer, Neoleucinodes elegantalis. We then discuss example applications of DDRP as a decision support tool, review its potential limitations and sources of model error, and outline some ideas for future improvements to the platform.
EFFECTS OF SESAME LIGNAN EXTRACT ON LINOLEIC ACID, LIPID OXIDATION, COLOR AND TEXTURAL PROPERTIES OF GROUND PORK, AND SAUSAGE PRODUCTS

Sesame lignan extract was prepared from roasted sesame oil and added at 0.02, 0.05, 0.10 and 0.20% (w/w) to linoleic acid and ground pork products. Cooked ground pork containing more than 0.02% of lignan extract showed TBA values lower than those containing butylated hydroxyanisole (BHA) during storage. Sausages containing 0.05% of lignan extract had lower thiobarbituric acid (TBA) values when stored at 4C for 14 days; they also showed higher CIE color values than the control meat sample (P 0.02% or in sausages at > 0.05%.
Single molecule structure sequencing reveals RNA structural dependencies, breathing and ensembles

RNA molecules can form secondary and tertiary structures that can regulate their localization and function. Using enzymatic or chemical probing together with high-throughput sequencing, secondary structure can be mapped across the entire transcriptome. However, a limiting factor is that only population averages can be obtained since each read is an independent measurement. Although long-read sequencing has recently been used to determine RNA structure, these methods still used aggregate signals across the strands to detect structure. Averaging across the population also means that only limited information about structural heterogeneity across molecules or dependencies within each molecule can be obtained. Here, we present Single-Molecule Structure sequencing (SMS-seq) that combines structural probing with native RNA sequencing to provide non-amplified, structural profiles of individual molecules with novel analysis methods. Our new approach using mutual information enabled single molecule structural interrogation. Each RNA is probed at numerous bases enabling the discovery of dependencies and heterogeneity of structural features. We also show that SMS-seq can capture tertiary interactions, dynamics of riboswitch ligand binding, and mRNA structural features.