Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Various Approaches towards Handwritten Digit Recognition

Pattern recognition plays a vital role due to demand in artificial intelligence in practical problem. One of the problem is, that the machine faced problem in handwritten digit recognition. To recognize the digits, different features are considered such as style, orientation, curve, size, edge, thickness of the digit. Based on these factors they classifies the digits. This paper describes the different approaches that where followed to recognize the Handwritten digits. And the discussion about the different algorithms used. There are two steps involved, one is feature extraction for that there are many feature extraction methods available like, Linear Binary Pattern, Histogram Oriented Graph, Convolutional Neural Network and many more algorithms. Another one is feature classification for that many machine learning methods available like Support Vector Machine, K Nearest Neighbor so on. The main objective of all these approaches is to improve the prediction accuracy. So our main intention is to find the most appropriate method which could give highest prediction rate. In order to obtain that we created a comparative table, which compares with respect to classification method, feature extraction method, accuracy, purpose, pros and cons. Also plotted graph to compare them.
Accumulation of manganese oxides in biological activated carbon filters: Implications for biodegradation studies

A comparison of granular and biological activated carbon (GAC and BAC) media used for drinking water treatment was made to assess differences in surface elemental composition. Fresh GAC, recently commissioned GAC and end‐of‐service life BAC from a water treatment plant in New Zealand were analyzed using scanning electron microscopy, energy‐dispersive spectroscopy, and inductively coupled plasma‐mass spectrometry (ICP‐MS). Imaging revealed dense microbial colonization of the BAC surface compared to GAC media, and a mineralized surface layer high in manganese and oxygen. ICP‐MS analysis also confirmed high levels of Mn in the BAC media relative to GAC media. As many bacterial species known to colonize BAC filters are also known as Mn oxidizers, this suggests a biogenic origin of the Mn‐oxide deposition on the BAC surface. Given the properties of Mn‐oxides, they may be implicated in the mechanism by which bacteria capture and metabolize substrates in BAC filters.
Performance of the 2017 European Alliance of Associations for Rheumatology/American College of Rheumatology Classification Criteria in Patients With Idiopathic Inflammatory Myopathy and Anti–Melanoma Differentiation–Associated Protein 5 Positivity

This study aimed to evaluate whether the 2017 European Alliance of Associations for Rheumatology (EULAR)/American College of Rheumatology (ACR) classification criteria for adult and juvenile idiopathic inflammatory myopathies (IIMs) could appropriately classify the diagnosis in adult patients with anti–melanoma differentiation–associated protein 5 (anti–MDA‐5)–positive IIM. In addition, this study sought to determine whether a status of anti–MDA‐5 positivity could be incorporated into the EULAR/ACR IIM classification criteria set and whether the recently modified criteria based on the presence of myositis‐specific autoantibodies (MSAs) could be used to appropriately classify the diagnosis in patients with anti–MDA‐5–positive IIM.
CasDinG is an ATP-dependent 5’-3’ DNA helicase with accessory domains essential for type IV CRISPR immunity

CRISPR-associated DinG protein (CasDinG) is essential to type IV-A CRISPR function. However, the enzymatic activities of CasDinG are unknown. Here we demonstrate that CasDinG from Pseudomonas aeruginosa strain 83 is an ATP- and metal-dependent 5’-3’ DNA helicase. The crystal structure of CasDinG reveals a helicase core of two RecA-like domains with three accessory domains (N-terminal, arch, and vestigial FeS). To examine the in vivo function of these CasDinG domains, we first identified the preferred PAM sequence (5’-GNAWN-3’ on the 5’-side of the target) with a plasmid library containing all combinations of the five nucleotides upstream of the target sequence. Plasmid clearance assays (using a 5’-GGAAA-3’ PAM) with CasDinG domain mutants demonstrated the vFeS and arch accessory domains are both essential for type IV immunity. These results provide a needed structural and biochemical framework for understanding the type IV-A CRISPR system.
The effect of selective logging on microclimates, arthropod abundance and the foraging behaviour of Eastern Himalayan birds

1. Selective logging—the practice of removing a subset of commercially important trees from a forest—is a globally pervasive form of forest degradation. Selective logging alters both the structure and function of forests and the composition of ecological communities. 2. Tropical insectivorous birds are highly vulnerable to microhabitat alterations in logged forest. Such altered microhabitats might affect the foraging of forest birds by altering (a) resource availability, and (b) foraging behaviour. 3. We investigated the effect of selective logging on microclimates, prey availability, foraging behaviour and the foraging success of eastern Himalayan birds in the breeding season. 4. Selective logging alters temperature-humidity microclimates and the composition of arthropod communities, both of which are likely to then collectively alter foraging behaviour by birds. We show that birds spent a lower proportion of their time foraging in primary compared with logged forest. Further, selective logging interacts with species traits such as body mass, preferred foraging stratum (understorey, midstorey or canopy) and foraging manoeuvre to influence foraging success. Gleaners generally foraged more successfully in primary forest and salliers in logged forest, although these patterns were modified by body mass and foraging stratum. 5. Synthesis and applications: Our study shows how altered microclimates in anthropogenically modified habitats can influence resource availability and have downstream impacts on the behaviour of species at higher trophic levels.
A Peronophythora litchii RXLR effector PlAvh202 enhances plant susceptibility by destabilizing host SAMS

Oomycete pathogens can secret hundreds of effectors into plant cells to interfere with plant immune system during infection. Here we identified a cytoplasmic RXLR effector from the most destructive pathogen of litchi, Peronophythora litchii, and named it as PlAvh202. PlAvh202 could suppress cell death triggered by INF1 and Avr3a/R3a in Nicotiana benthamiana, and was essential for P. litchii virulence. In addition, PlAvh202 also suppressed plant immune responses and promoted the susceptibility of N. benthamiana to Phytophthora capsici. Further research revealed that PlAvh202 could suppress ethylene (ET) production by targeting and destabilizing plant S-adenosyl-L-methionine synthetase (SAMS), a key enzyme in ET biosynthesis pathway, in a 26S proteasome-dependent manner. Transient expression of LcSAMS3 induced ET production and enhanced plant resistance, whereas inhibition of ET biosynthesis promoted P. litchii infection, supporting that LcSAMS and ET positively regulate litchi immunity towards P. litchii. Overall, these findings highlight that SAMS can be targeted by oomycete RXLR effector to manipulate ET-mediated plant immunity.
In Vitro Analysis of Bacterial Microcompartments and Shell Protein Superstructures by Confocal Microscopy

Microcompartments are large, organelle-like structures that help bacteria catabolize targeted metabolites while also protecting the cytosol against highly reactive metabolic intermediates. Their protein shell self-assembles into a polyhedral structure of approximately 100 to 200 nm in diameter. ABSTRACT The shell proteins that comprise bacterial microcompartments (BMCs) can self-assemble into an array of superstructures such as nanotubes, flat sheets, and icosahedra. The physical characterization of BMCs and these superstructures typically relies on electron microscopy, which decouples samples from their solution context. We hypothesize that an investigation of fluorescently tagged BMCs and shell protein superstructures in vitro using high-resolution confocal microscopy will lead to new insights into the solution behavior of these entities. We find that confocal imaging is able to capture nanotubes and sheets previously reported by transmission electron microscopy (TEM). Using a combination of fluorescent tags, we present qualitative evidence that these structures intermix with one another in a hetero- and homotypic fashion. Complete BMCs are also able to accomplish intermixing as evidenced by colocalization data. Finally, a simple colocalization experiment suggests that fluorescently modified encapsulation peptides (EPs) may prefer certain shell protein binding partners. Together, these data demonstrate that high-resolution confocal microscopy is a powerful tool for investigating microcompartment-related structures in vitro, particularly for colocalization analyses. These results also support the notion that BMCs may intermix protein components, presumably from the outer shell. IMPORTANCE Microcompartments are large, organelle-like structures that help bacteria catabolize targeted metabolites while also protecting the cytosol against highly reactive metabolic intermediates. Their protein shell self-assembles into a polyhedral structure of approximately 100 to 200 nm in diameter. Inside the shell are thousands of copies of cargo enzymes, which are responsible for a specific metabolic pathway. While different approaches have revealed high-resolution structures of individual microcompartment proteins, it is less clear how these factors self-assemble to form the full native structure. In this study, we show that laser scanning confocal microscopy can be used to study microcompartment proteins. We find that this approach allows researchers to investigate the interactions and potential exchange of shell protein subunits in solution. From this, we conclude that confocal microscopy offers advantages for studying the in vitro structures of other microcompartments as well as carboxysomes and other bacterial organelles.
Development of an adenosquamous carcinoma histopathology-selective lung cancer graft model

Preclinical tumor models with native tissue microenvironments provide essential tools to understand how heterogeneous tumor phenotypes relate to drug response. Here, we present syngeneic graft models of aggressive, metastasis-prone histopathology-specific NSCLC tumor types driven by KRAS mutation and loss of LKB1 (KL): adenosquamous carcinoma (ASC) and adenocarcinoma (AC). We show that subcutaneous injection of primary KL-ASC cells results in squamous cell carcinoma (SCC) tumors with high levels of stromal infiltrates, lacking the source heterogeneous histotype. Despite forming subcutaneous tumors, intravenously injected KL-AC cells were unable to form lung tumors. In contrast, intravenous injection of KL-ASC cells leads to their lung re-colonization and lesions recapitulating the mixed AC and SCC histopathology, tumor immune suppressive microenvironment and oncogenic signaling profile of source tumors, demonstrating histopathology-selective phenotypic dominance over genetic drivers. Pan-ERBB inhibition increased survival, while selective ERBB1/EGFR inhibition did not, suggesting a role of ERBB network crosstalk in resistance to ERBB1/EGFR. This immunocompetent NSCLC lung colonization model hence phenocopies key properties of the metastasis-prone ASC histopathology, and serves as a preclinical model to dissect therapy responses and metastasis-associated processes.
A survey of Lactobacilli isolated from traditional fermented Dahi at different altitudes in Nepal --Manuscript

: Dairy products are an important part of daily food in the Himalayan country of Nepal. A wide variety of traditional fermented milk products are obtained in relation to different geo-climatic conditions of the country and different ethnic groups. Locally called Dahi is the most popular product, but little data are available on the autochthonous lactic acid bacteria (LAB) characterizing this yoghurt-like product. Thirty-two replicate samples of indigenous Dahi were collected from four districts of Nepal, at different altitude. In total, 193 strains of LAB were isolated. The rod-shaped isolates, which represented the dominant LAB population (62%), were further identified at the species-level by using Internal Transcribed Spacers (ITS) amplification, 16S rRNA nucleotide sequence determination and species-specific PCR. A further characterization at the strain-level was carried out by combining analysis of repetitive elements and Randomly Amplified Polymorphic DNA (RAPD) typing. Based on these analyses, the 120 isolates were grouped in ten different species, among which L. delbrueckii subsp. bulgaricus, L. paracasei and L. rhamnosus represented the dominant species. A high degree of intra-species biodiversity and a partial correlation with the geographical Abstract Dairy products are an important part of daily food in the Himalayan country of Nepal. A wide 21 variety of traditional fermented milk products are obtained in relation to different geo-climatic conditions of 22 the country and different ethnic groups. Locally called Dahi is the most popular product, but little data are 23 available on the autochthonous lactic acid bacteria (LAB) characterizing this yoghurt-like product. Thirty- 24 two replicate samples of indigenous Dahi were collected from four districts of Nepal, at different altitude. In 25 total, 193 strains of LAB were isolated. The rod-shaped isolates, which represented the dominant LAB 26 population (62%), were further identified at the species-level by using Internal Transcribed Spacers (ITS) 27 amplification, 16S rRNA nucleotide sequence determination and species-specific PCR. A further 28 characterization at the strain-level was carried out by combining analysis of repetitive elements and 29 Randomly Amplified Polymorphic DNA (RAPD) typing. Based on these analyses, the 120 isolates were 30 grouped in ten different species, among which L. delbrueckii subsp . bulgaricus, L. paracasei and L. 31 rhamnosus represented the dominant species. A high degree of intra-species biodiversity and a partial 32 correlation with the geographical areas of sampling was also found. 33
Intrinsic neural diversity quenches the dynamic volatility of neural networks

Heterogeneity is the norm in biology. The brain is no different: neuronal cell-types are myriad, reflected through their cellular morphology, type, excitability, connectivity motifs and ion channel distributions. While this biophysical diversity enriches neural systems’ dynamical repertoire, it remains challenging to reconcile with the robustness and persistence of brain function over time. To better understand the relationship between heterogeneity and resilience, we analyzed both analytically and numerically a non-linear sparse neural network with balanced excitatory and inhibitory connections evolving over long time scales. We examined how neural diversity expressed as excitability heterogeneity in this network influences its dynamic volatility (i.e., its susceptibility to critical transitions). We exposed this network to slowly-varying modulatory fluctuations, continuously interrogating its stability and resilience. Our results show that excitability heterogeneity implements a homeostatic control mechanism tuning network stability in a context-dependent way. Such diversity was also found to enhance network resilience, quenching the volatility of its dynamics, effectively making the system independent of changes in many control parameters, such as population size, connection probability, strength and variability of synaptic weights as well as modulatory drive. Taken together, these results highlight the fundamental role played by cell-type heterogeneity in the robustness of brain function in the face of change. Significance Statement Contemporary research has identified widespread cell-to-cell intrinsic diversity in the brain, manifest through variations in biophysical features such as neuronal excitability. A natural question that arises from this phenomenon is what functional role, if any, this heterogeneity might serve. Combining computational and mathematical techniques, this interdisciplinary research shows that intrinsic cell-to-cell diversity, far from mere developmental noise, represents a homeostatic control mechanism, promoting the resilience of neuronal circuits. These results highlight the importance of diversity in the robustness and persistence of brain function over time and in the face of change.
Modulation of motor vigour by expectation of reward probability trial-by-trial is preserved in healthy ageing and Parkinson’s disease patients

Motor improvements, such as faster movement times or increased velocity, have been consistently associated with reward magnitude in deterministic contexts. Yet whether individual inferences on reward probability influence motor vigour dynamically remains undetermined. Here we investigated how dynamically inferring volatile action-reward contingencies modulated motor performance trial-by-trial in healthy younger (HYA, 37) and older adults (HOA, 37), and in medicated Parkinson’s Disease patients (PD, 20). We conducted an online study that coupled a standard one-armed bandit decision-making paradigm with a motor sequence task and used a validated hierarchical Bayesian model to fit trial-by-trial data. Our results showed that stronger predictions about the tendency of the action-reward contingency led to faster performance tempo on a trial-by-trial basis without modulating reaction times (RT). Using Bayesian linear mixed models, we demonstrated in HYA, HOA and PD a similar sensitivity (slope) of execution tempo to inferences about the reward probabilities, despite HOA and PD being generally slower than HYA (intercept). In a second experiment in HYA (39), we additionally showed that subjective inferences about credit assignment – whether lack of reward is associated with an incorrect decision or execution error – led to a similar modulation of motor vigour by reward expectation. Our study is the first to reveal that the dynamic updating of beliefs about volatile action-reward contingencies positively biases motor performance through faster execution tempo, without affecting RT. We also provide novel evidence for a preserved sensitivity of motor vigour to inferences about the action-reward mapping in ageing and medicated PD. SIGNIFICANCE STATEMENT Navigating a world rich in uncertainty relies on updating beliefs about the probability that our actions lead to reward. Here we investigated how inferring the action-reward contingencies in a volatile environment modulated motor vigour trial-by-trial in healthy younger and older adults, and in Parkinson’s Disease patients on medication. We found an association between trial- by-trial predictions about the tendency of the action-reward contingency and performance tempo, with stronger expectations speeding performance. We additionally provided evidence for a similar sensitivity of performance tempo to the strength of these predictions in all groups. Thus, dynamic beliefs about the changing relationship between actions and their outcome invigorated motor performance. This positive bias was not compromised by age or Parkinson’s disease.
MARVEL: an integrated alternative splicing analysis platform for single-cell RNA sequencing data

Alternative splicing is an important source of heterogeneity in gene expression between individual cells but remains an understudied area due to the paucity of computational tools to analyze splicing dynamics at single-cell resolution. Here, we present MARVEL, a comprehensive R package for single-cell splicing analysis applicable to RNA sequencing generated from the plate- and droplet-based methods. We performed extensive benchmarking of MARVEL against available tools and demonstrated its utility by analyzing iPSC differentiation into endoderm cells and cardiomyocytes. MARVEL enables systematic and integrated splicing and gene expression analysis of single cells to characterize the splicing landscape and reveal biological insights.
Using deep-learning predictions of inter-residue distances for model validation

Determination of protein structures typically entails building a model that satisfies the collected experimental observations and its deposition in the Protein Data Bank (PDB). Experimental limitations can lead to unavoidable uncertainties during the process of model building, which result in the introduction of errors into the deposited model. Many metrics are available for model validation, but most are limited to the consideration of the physico-chemical aspects of the model or its match to the map. The latest advances in the field of deep learning have enabled the increasingly accurate prediction of inter-residue distances, an advance which has played a pivotal role in the recent improvements observed in the field of protein ab initio modelling. Here we present new validation methods based on the use of these precise inter-residue distance predictions, which are compared with the distances observed in the protein model. Sequence register errors are particularly clearly detected, and the register shifts required for their correction can be reliably determined. The method is available in the package ConKit (www.conkit.org).
Analysis of a genetic region affecting mouse body weight

Genetic factors affect an individual’s risk of developing obesity, but in most cases each genetic variant has a small effect. Discovery of genes that regulate obesity may provide clues about its underlying biological processes and point to new ways the disease can be treated. Pre-clinical animal models facilitate genetic discovery in obesity because environmental factors can be better controlled compared to the human population. We studied inbred mouse strains to identify novel genes affecting obesity and glucose metabolism. BTBR T+ Itpr3tf/J (BTBR) mice are fatter and more glucose intolerant than C57BL/6J (B6) mice. Prior genetic studies of these strains identified an obesity locus on chromosome 2. Using congenic mice, we found that obesity was affected by a ~316 kb region, with only two known genes, pyruvate dehydrogenase kinase 1 (Pdk1) and integrin alpha 6 (Itga6). Both genes had mutations affecting their amino acid sequence and reducing mRNA levels. Both genes have known functions that could modulate obesity, lipid metabolism, insulin secretion and/or glucose homeostasis. We hypothesized that genetic variation in or near Pdk1 or Itga6 causing reduced Pdk1 and Itga6 expression would promote obesity and impaired glucose tolerance. We used knockout mice lacking Pdk1 or Itga6 fed an obesigenic diet to test this hypothesis. Under the conditions we studied, we were unable to detect an individual contribution of either Pdk1 or Itga6 to body weight. However, we identified a previously unknown role for Pdk1 in cardiac lipid metabolism providing the basis for future investigations in that area.