Miracle-dz/UniFAR-FTUs huggingface dataset:
A hierarchical Bayesian mixture model for inferring the expression state of genes in transcriptomes

Significance How do the cells of an organism—each with an identical genome—give rise to tissues of incredible phenotypic diversity? Key to answering this question is the transcriptome: the set of genes expressed in a given tissue. We would clearly benefit from the ability to identify qualitative differences in expression (whether a gene is active or inactive in a given tissue/species). Inferring the expression state of genes is surprisingly difficult, owing to the complex biological processes that give rise to transcriptomes and to the vagaries of techniques used to generate transcriptomic datasets. We develop a hierarchical Bayesian mixture model that—by describing those biological and technical processes—allows us to infer the expression state of genes from replicate transcriptomic datasets. Transcriptomes are key to understanding the relationship between genotype and phenotype. The ability to infer the expression state (active or inactive) of genes in the transcriptome offers unique benefits for addressing this issue. For example, qualitative changes in gene expression may underly the origin of novel phenotypes, and expression states are readily comparable between tissues and species. However, inferring the expression state of genes is a surprisingly difficult problem, owing to the complex biological and technical processes that give rise to observed transcriptomic datasets. Here, we develop a hierarchical Bayesian mixture model that describes this complex process and allows us to infer expression state of genes from replicate transcriptomic libraries. We explore the statistical behavior of this method with analyses of simulated datasets—where we demonstrate its ability to correctly infer true (known) expression states—and empirical-benchmark datasets, where we demonstrate that the expression states inferred from RNA-sequencing (RNA-seq) datasets using our method are consistent with those based on independent evidence. The power of our method to correctly infer expression states is generally high and remarkably, approaches the maximum possible power for this inference problem. We present an empirical analysis of primate-brain transcriptomes, which identifies genes that have a unique expression state in humans. Our method is implemented in the freely available R package zigzag.
Structural insights into filament recognition by cellular actin markers

Cellular studies of filamentous actin (F-actin) processes commonly utilize fluorescent versions of toxins, peptides and proteins that bind actin. While the choice of these markers has been largely based on availability and ease, there is a severe dearth of structural data for an informed judgment in employing suitable F-actin markers for a particular requirement. Here we describe the electron cryomicroscopy structures of phalloidin, lifeAct and utrophin bound to F-actin, providing the first high-resolution structures and comparison of widely used actin markers and their influence towards F-actin. Our results show that phalloidin binding does not induce conformations and lifeAct specifically recognizes ADP-actin state, which can be used as a sensor for distinguishing different nucleotide states of F-actin. The utrophin structural model aided designing minimal utrophin, which can be utilized as F-actin marker. Together, our study provides a structural perspective, where the binding sites of utrophin and lifeAct overlap with majority of actin binding proteins. Further offering an invaluable resource for researchers in choosing appropriate actin markers and generating new marker variants.
Effect of Collateral Puncture-bloodletting at JING Point on Expression of HSP70 Protein of Cerebral Cortex in Rats with Middle Cerebral Artery Occlusion

Objective To observe the brain-protective effects of collateral puncture-bloodletting at JING point on the expression of HSP protein of brain in rats with acute local cerebral ischemia. Methods The cerebral injury with acute local ischemia was induced by occlusion of the middle cerebral artery with blood concretion in rats. The expression of HSP protein in ischemic region of brain tissue was determined with immunohistochemistry and the intervention of bloodletting at JING point was observed. Result Acute cerebral ishemic injury resulted in the expression of HSP protein in the ischemic region of brain tissue and this effect increased gradually with time. Bloodletting at JING point can enhance the expression of HSP protein in initial stage of ischemia and increase the resistance of brain against the exacerbation of the ischemic injury. Conclusion Bloodletting at JING point may improve the anti-stress ability of brain tissue in ischemic field and the protective function of the brain effectively.
Neuro-computational account of arbitration between imitation and emulation during human observational learning

In observational learning (OL), organisms learn from observing the behavior of others. There are at least two distinct strategies for OL. Imitation involves learning to repeat the previous actions of other agents, while in emulation, learning proceeds from inferring the goals and intentions of others. While putative neural correlates for these forms of learning have been identified, a fundamental question remains unaddressed: how does the brain decides which strategy to use in a given situation? Here we developed a novel computational model in which arbitration between the strategies is determined by the predictive reliability, such that control over behavior is adaptively weighted toward the strategy with the most reliable prediction. To test the theory, we designed a novel behavioral task in which our experimental manipulations produced dissociable effects on the reliability of the two strategies. Participants performed this task while undergoing fMRI in two independent studies (the second a pre-registered replication of the first). Behavior manifested patterns consistent with both emulation and imitation and flexibly changed between the two strategies as expected from the theory. Computational modelling revealed that behavior was best described by an arbitration model, in which the reliability of the emulation strategy determined the relative weights allocated to behavior for each strategy. Emulation reliability - the model’s arbitration signal - was encoded in the ventrolateral prefrontal cortex, temporoparietal junction and rostral cingulate cortex. Being replicated across two fMRI studies, these findings suggest a neuro-computational mechanism for allocating control between emulation and imitation during observational learning.
Training deep neural density estimators to identify mechanistic models of neural dynamics

Mechanistic modeling in neuroscience aims to explain neural or behavioral phenomena in terms of underlying causes. A central challenge in building mechanistic models is to identify which models and parameters can achieve an agreement between the model and experimental data. The complexity of models and data characterizing neural systems makes it infeasible to solve model equations analytically or tune parameters manually. To overcome this limitation, we present a machine learning tool that uses density estimators based on deep neural networks— trained using model simulations—to infer data-compatible parameters for a wide range of mechanistic models. Our tool identifies all parameters consistent with data, is scalable both in the number of parameters and data features, and does not require writing new code when the underlying model is changed. It can be used to analyze new data rapidly after training, and can be applied to either raw data or selected data features. We demonstrate our approach for parameter inference on ion channels, receptive fields, and Hodgkin–Huxley models. Finally, we use it to explore the space of circuit configurations which give rise to rhythmic activity in a network model of the crustacean stomatogastric ganglion, and to provide hypotheses for compensation mechanisms. The approach presented here will help close the gap between data-driven and theory-driven models of neural dynamics.
Chapter 16. A Prototype Metabolic Cage for Rats and Mice for Biomedical Research in Nigeria

Animal experimentation is a regular feature of biomedical research and training. The common laboratory animals used include rats, mice, guinea pigs, rabbits, frogs, cats, dogs, monkeys, pigeons and hamsters (Badyal & Desai, 2014). These animals are typically used for research relating to drug discovery, the endocrine system, cosmetic testing (mutagenicity, phytotoxicity, genotoxicity, allergy, etc.) and toxicology. Ethics and animal use regulations require humane handling and reduction of pain of experimental animals (Flecknell, 2002).
Evaluation of Elite Sorghum [Sorghum bicolor (L.) Moench] Germplasm Lines for Morphological Traits

Sorghum [Sorghum bicolor (L.) Moench] also known as Jowar has originated in Africa about 5000 – 8000 years ago (De Candolle 1890). Sorghum is the fifth most important cereal crop providing food and fodder throughout the world (Doggett 1988). It is adapted to a wider range of stress conditions like salt and drought and known as a high-energy, drought tolerant crop because of its efficiency. It is planted in those areas which are considered to be hot and too dry for other cereals, because of its tolerance to heat and drought stress (Poehlman, 1987). Sorghum in general possesses a wide range of genetic variability. Adequate variability provides options from which selections are made for improvement and possible hybridization.
Preliminary cross-genera transferability of SSRs among threatened South American Cupressaceae

ABSTRACT Development of specific microsatellite primers is a relatively expensive and time-consuming process, so transferring already developed markers from one species to others is desirable, especially for non-model organisms with large genome structure such as conifers. In austral South America, the three Cupressaceae are monotypic genera of high conservation and evolutionary relevance. Although they had been the focus of numerous population genetic studies the lack of highly polymorphic markers as microsatellites for all species, has limited the possibility of evolutionary studies and the design of appropriate conservation plans. Thus the aim of this study is to transfer and test microsatellites primers early designed for Austrocedrus to Fitzroya and Pilgerodendron. Transferability of nine microsatellite primers and their utility were tested by comparing genetic parameters of 20 individuals of each species in six populations where the three species occur. Four markers were simultaneously transferred with success, representing the first study in conifers to achieve cross-genera transferability. This small set of primers yielded high levels of polymorphism for the three studied species and show unique alleles that separate pure taxa. These highly polymorphic markers provide relevant tools to study the evolutionary history of South American Cupressaceae and to generate information that could help to guide conservation efforts.
Biological features of the medicinal plant Plantago major L.

Paper provides an overview of the therapeutic, morphological, anatomical and phytochemical features of Plantago major L. For studies, plant samples were collected four times from April to September 2018 in the Almaty region, with freshly harvested plants used for morphological and anatomical studies, and specially dried leaves used for phytochemical studies. Anatomical sections were produced using the classic blade method. Chemical composition, including vitamins B1 (thiamine chloride), B2 (riboflavin), B3 (pantothenic acid), B6 (pyridoxine), C (ascorbic acid), E (tocopherol), tannins was studied at the research laboratory for assessing the quality and safety of food products of the Almaty Technological University. Vitamins were determined according to the State Standard 31483-2012, with the help of the device “Kapel105-M” by the method of capillary electrophoresis (M-04-41-2005). Tannins were estimated by titration of margon-acid potassium using the classical method according to the State Standard 24027.280. As a result of a phytochemical study, large amount of vitamin C (ascorbic acid) was determined among vitamins, on average of 0.432 mg/100g. This means that preparations obtained from Plantago major L. can be used in the treatment of bleeding gums, against viral and other diseases. However, vitamin E was not detected in the plant. Amount of tannins was around 77.94 mg/100g; which indicates its high antimicrobial, hemostatic properties and prevents the replenishment of the gastrointestinal tract. The results of this study can be used as an additional material in the educational process in such courses as “Botany”, “Medicinal plants”, “Anatomy and morphology of plants”.
Measurement and Management for Medical and Clinical Risks

Hosptial information system (HIS) collects all the data from all the branches of departments in a hospital, including laboratory tests, physiological tests, electronic patient records. Thus, HIS can be viewed as a large heterogenous database, which stores chronological changes in patients’ status. This paper overviews three applications of data mining and statistical methods to HIS. First, clustering of temporal sequences based on multiscale matching was applied for grouping chronic hepatitis. Second, decision tree method was used for detection of risk factors, which was successfully used to prevent nursing medication errors. Finally, several linear models were applied for hospital management data. These results show that data mining methods, including decision tree mining, temporal data mining, are useful for detection of risk factors from large distributed data such as HIS, whose process can be called risk mining.
IDphy: molecular and morphological identification of Phytophthora based on the types.

1. Transfer isolates into X-plate with agar (Z; such Z1, Z2, Z3, or Z4); grow for 3-7 days (18-24°C). 2. Transfer a few plugs from the border of the colony into the neighboring cells (Y). Add liquid (such as Y1, Y2.) only to the level of the plugs; do not overflow. Keep plates under continuous fluorescent light (24-48 hrs) for sporangia formation (oospores of homothallic species might be produced using this method). 3. After sporangia are produced, to induce zoospore release (1) incubate the plates at 5°C for 1020min, then bring back to room temperature; or (2) keep a bottle of DD H2O at 5°C, and place a couple drops of the cold water on the slides you use to observe sporangia. Asexual phase: sporangia, sporangiophores, hyphal swellings, and chlamydospores
Deficit Irrigation as a Sustainable Practice in Improving Irrigation Water Use Efficiency in Cauliflower under Mediterranean Conditions

Water shortage is one of the major constraints in vegetable production. Deficit irrigation is a sustainable technique that improves irrigation water use efficiency. Field studies were conducted during two growing seasons to evaluate the effects of deficit irrigation on plant growth, plant water status, productive response (curd yield and quality), irrigation water use efficiency (IWUE), and crop profitability of cauliflower. Nine irrigation treatments were used, applying 100%, 75% (moderate), or 50% (severe) of the irrigation water requirements (IWR) during the entire growing season (Continued Deficit Irrigation, CDI), or 75% and 50% of IWR during one of the following stages (Regulated Deficit Irrigation, RDI): Juvenility, curd induction, and curd growth. Severe deficit irrigation applied during juvenility and curd induction reduced the plant size, but it only led to a significant reduction of marketable yield (22%), and average curd size and weight if it was maintained throughout the crop cycle, supposing the highest IWUE (43.6 kg m−3). Moderate CDI or severe RDI during juvenility did not reduce significantly the curd yield compared to fully irrigated plants (4.4 kg m−2), thereby obtaining similar gross revenues (16,859 € ha−1) with important water savings (up to 24.3%), improving IWUE (up to 34.2 kg m−3).
MeSHHeading2vec: A new method for representing MeSH headings as feature vectors based on graph embedding algorithm

Motivation Effectively representing the MeSH headings (terms) such as disease and drug as discriminative vectors could greatly improve the performance of downstream computational prediction models. However, these terms are often abstract and difficult to quantify. Results In this paper, we converted the MeSH tree structure into a relationship network and applied several graph embedding algorithms on it to represent these terms. Specifically, the relationship network consisting of nodes (MeSH headings) and edges (relationships) which can be constructed by the rule of tree num. Then, five graph embedding algorithms including DeepWalk (DW), LINE, SDNE, LAP and HOPE were implemented on the relationship network to represent MeSH headings as vectors. In order to evaluate the performance of the proposed method, we carried out the node classification and relationship prediction tasks. The experimental results show that the MeSH headings characterized by graph embedding algorithms can not only be treated as an independent carrier for representation, but also can be utilized as additional information to enhance the distinguishable ability of vectors. Thus, it can act as input and continue to play a significant role in any disease-, drug-, microbe- and etc.-related computational models. Besides, our method holds great hope to inspire relevant researchers to study the representation of terms in this network perspective. Contact zhuhongyou@ms.xjb. ac.cn
Efecto de bacterias promotoras del crecimiento vegetal andinas sobre el crecimiento de plántulas de lechuga bajo condiciones industriales

Las bacterias promotoras del crecimiento vegetal (bpcv) pueden utilizarse para fortalecerel crecimiento sustentable de las plantas. En el presente trabajo se seleccionaron200 aislados obtenidos de pastos andinos de las zonas aridas de la cordillerade los Andes y de agroecosistemas del norte de Chile. Los aislados mostraron grancapacidad de solubilizar fosfatos, fijar nitrogeno, producir fitohormonas y sideroforos.Ademas, potenciaron significativamente el desarrollo de plantulas de lechugavariedad desert storm (escarola), respecto a su altura (45%), peso fresco (30%), longitudradicular (35%) y contenido de clorofila (lecturas de un 50% mas de od) a menoresdosis de fertilizacion (33%). Los resultados obtenidos sugieren que las bpcvidentificadas pueden emplearse para la produccion de plantulas de lechuga, bajocondiciones de invernadero, con fertirriego automatizado.
Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations

Eye movements are vital for human vision, and it is therefore important to understand how observers decide where to look. Meaning maps (MMs), a technique to capture the distribution of semantic importance across an image, have recently been proposed to support the hypothesis that meaning rather than image features guide human gaze. MMs have the potential to be an important tool far beyond eye-movements research. Here, we examine central assumptions underlying MMs. First, we compared the performance of MMs in predicting fixations to saliency models, showing that DeepGaze II – a deep neural network trained to predict fixations based on high-level features rather than meaning – outperforms MMs. Second, we show that whereas human observers respond to changes in meaning induced by manipulating object-context relationships, MMs and DeepGaze II do not. Together, these findings challenge central assumptions underlying the use of MMs to measure the distribution of meaning in images.
Persistent neural entrainment in the human cortex is frequency selective

Rhythmic stimulation, either sensory or electrical, aiming at entraining oscillatory activity to reveal or optimize brain functions, relies on a critically untested hypothesis: it should produce a persistent effect, outlasting the stimulus duration. We tested this assumption by studying cortical neural oscillations during and after presentation of rhythmic auditory stimuli. Using intracranial and surface recordings in humans, we reveal consistent neural response properties throughout the cortex, with persistent entrainment being selective to high-gamma oscillations. Critically, during passive perception, neural oscillations do not outlast low-frequency acoustic dynamics. We further show that our data are well-captured by a model of damped harmonic oscillator and can be classified into three classes of neural dynamics, with distinct damping properties and eigenfrequencies. This model thus provides a mechanistic and quantitative explanation of the frequency selectivity of persistent neural entrainment in the human cortex. Highlights - Neural oscillatory activity does not outlast low-frequency (2.5 Hz) acoustic dynamics during passive perception. - High-gamma activity is entrained by periodic auditory stimuli, with persistent activity up to 10 cycles after stimulus offset. - This frequency following response (FFR) is present throughout the cortex, up to inferior frontal and motor regions. - The frequency selective nature of neural entrainment is well-captured by a model of damped harmonic oscillator.
Pregnancy rates in hair sheep after Ovsynch synchronization and a combined intracervical fixed-time artificial insemination and 10-day mating period

Aim: This study aimed to evaluate the pregnancy rates in hair ewes using an Ovsynch synchronization protocol under a breeding system that combines fixed-time insemination plus a 10-day mating period as an alternative. Materials and Methods: Through an experimental study (n=27), ewes were randomly located into one of three treatments: (1) Pre-synch (n=9): Prostaglandin F2α (PGF2α)+Gonadotropin-releasing hormone (GnRH)+PGF2α+GnRH; (2) Ovsynch (n=9): GnRH+PGF2α+GnRH; and (3) control: Ewes bred by natural mating (NM) (n=9). Ewes were fixed-time inseminated (fixed-time artificial insemination [FTAI]) with fresh semen, collected just before the insemination time through vaginoscopy at 16 h after the second GnRH (gonadorelin) injection. Each experimental group was placed separately during 15 days and, after this time, fertile rams were allowed back with ewes for a 10-day mating period. Control group ewes remained with the rest of the herd suitable for breeding and were bred under NM. Pregnancy diagnosis was performed by ultrasound at 28-, 56-, and 84-day post-breeding to differentiate between FTAI and NM pregnancies. Total (FTAI±NM) pregnancy rates at 56-day post-breeding were used to compared Pre-synch, Ovsynch, and control. For this purpose, two-tailed proportions comparison z-test was used with a 95% confidence level, for testing as the null hypothesis whether two proportions were equal. Results: Pregnancy rates were higher in control ewes (66.4%) than FTAI (46.6%). When pregnancy rates after a 10-day mating period (40%) were added, the final rate (86.6%) was significantly (p<0.05) higher in Ovsynch-based protocols. The pregnancy rate was significantly lower in FTAI ewes compared to FTAI +10-day mating group (p<0.05). The overall pregnancy rate was 88.0, 85.7, and 67.0 (p>0.05) for Pre-synch, Ovsynch, and control ewes, respectively. Conclusion: These results provide evidence on the benefits of combined FTAI protocols for improving the reproductive efficiency of sheep.