Effect of feeding Bengal gram residual forage-based pelleted total mixed ration on growth performance, nutrient availability, carcass traits and composition in finisher Barbari kids.

The study aimed to assess the impact of feeding Bengal gram residual forage-based pelleted Total Mixed Ration (TMR) with varying concentrate (C) to roughage (R) ratios on feed intake, nutrient utilization, growth, and carcass characteristics in Barbari kids. Sixteen weaned male Barbari kids (av. age, 233 ± 11 days; weight, 13.86 ± 0.76 kg) were divided into two groups (T1 and T2), each receiving different pelleted diets (TMR) with distinct concentrate to roughage ratios (T1 with 60:40; T2 with 40:60). The kids were fed for 133 days, and a digestion trial was conducted at the end of the study. After completion, all kids were slaughtered. Although, kids under T1 consumed higher (P < 0.001) amount of dry matter, and crude protein compared to T2, which was due to a higher concentrate to roughage ratio in T1. But, the average daily body weight gain (ADG) of finisher kids was 88.53, and 79.83 g/d/kid in T1 and T2, respectively; however, the difference was non-significant. Digestibility of organic matter, crude protein, and total carbohydrate was also greater in T1 compared to T2. Total digestible nutrients intake was higher (P < 0.001) in T1; similarly intake of digestible energy, and metabolizable energy were significantly increased (P < 0.01) in T1 compared to T2. Concentrations of volatile fatty acids and NH3-nitrogen were also enhanced (P < 0.05) in T1 compared to T2. We observed similar carcass weight, and dressing percentage in both groups, and carcass composition remained unaffected. The pelleted diet containing greater ratio of concentrate: roughage (60:40) had no additional benefits in terms of ADG, and carcass traits in finisher kids. Therefore, it may be concluded that the Bengal gram residual forage-based pelleted TMR diet containing C40: R60 (TDN 57.13%, DCP 7.64%, ME 9.11MJ/kg feed) is suitable for optimizing growth performance with desirable carcass traits, and meat composition in finisher Barbari kids reared under the intensive system.

Stray Dogs (Mongrels) Are Potent Reservoir of Drug-Resistant Pathogens: A Study in Peri-Urban Areas of Kolkata, India.

This study depicts the drug-resistance and phylogenomic characteristics of 365 Escherichia coli (EC) and 76 Klebsiella pneumoniae (KP) isolated from stray dogs (293) in and around Kolkata, India. Initial screening found 59 isolates, including 48 E. coli and 11 KP multidrug resistant, which included 33 extended-spectrum ß-lactamase, 41 AmpC ß-lactamase and 18 metallo-ß-lactamase producers carrying blaNDM-1 (11) and blaNDM-5 (7) genes. Majority of them had the resistant genes such as blaCTX-M (33), blaTEM (18), blaSHV (4), blaOXA (17), blaFOX (2), blaDHA (2), blaCITM (15), blaCMY-2 (13), blaGES (2) and blaVEB (2), qnrS (15), qnrB (3), aac-6'-Ib-cr (14), tetA (26), tetB (14), sul-1 (25), armA (2) and rmtB (6), in addition to adherence genes such as csgA (33), fimA (27), fliC (13), sdiA (33), rcsA (38), and rpoS (39). They also carried plasmid of diverse replicon types of which IncFIA and FIB were the most frequent. Phylogrouping categorized most of the MDR E. coli in phylogroup A (20), B1 (14), and B2 (6). Enterobacteriaceae repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR) showed genetic diversity of multidrug resistant isolates irrespective of their origin, resistance, and virulence types, differentiating the EC in five clades (A-E) and KP in four clades (A-D). As these stray dogs, which had no history or scope of previous antimicrobial therapy, were found to have contracted potential antimicrobial resistance pathogens, the role of environment in spread of such pathogens and further possibility of human infections cannot be ruled out.

Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References.

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

reguloGPT: Harnessing GPT for Knowledge Graph Construction of Molecular Regulatory Pathways.

Motivation: Molecular Regulatory Pathways (MRPs) are crucial for understanding biological functions. Knowledge Graphs (KGs) have become vital in organizing and analyzing MRPs, providing structured representations of complex biological interactions. Current tools for mining KGs from biomedical literature are inadequate in capturing complex, hierarchical relationships and contextual information about MRPs. Large Language Models (LLMs) like GPT-4 offer a promising solution, with advanced capabilities to decipher the intricate nuances of language. However, their potential for end-to-end KG construction, particularly for MRPs, remains largely unexplored. Results: We present reguloGPT, a novel GPT-4 based in-context learning prompt, designed for the end-to-end joint name entity recognition, N-ary relationship extraction, and context predictions from a sentence that describes regulatory interactions with MRPs. Our reguloGPT approach introduces a context-aware relational graph that effectively embodies the hierarchical structure of MRPs and resolves semantic inconsistencies by embedding context directly within relational edges. We created a benchmark dataset including 400 annotated PubMed titles on N6-methyladenosine (m6A) regulations. Rigorous evaluation of reguloGPT on the benchmark dataset demonstrated marked improvement over existing algorithms. We further developed a novel G-Eval scheme, leveraging GPT-4 for annotation-free performance evaluation and demonstrated its agreement with traditional annotation-based evaluations. Utilizing reguloGPT predictions on m6A-related titles, we constructed the m6A-KG and demonstrated its utility in elucidating m6A's regulatory mechanisms in cancer phenotypes across various cancers. These results underscore reguloGPT's transformative potential for extracting biological knowledge from the literature. Availability and implementation: The source code of reguloGPT, the m6A title and benchmark datasets, and m6A-KG are available at: https://github.com/Huang-AI4Medicine-Lab/reguloGPT.

Influence of Dietary Supplementation of Inorganic and Organic Chromium on Body Conformation, Carcass Traits, and Nutrient Composition in Muscle and Internal Organs of Black Bengal Goats.

The effect of dietary inorganic and organic chromium (Cr) on body morphometry, carcass traits, and nutrient composition, including different minerals and fatty acids in meat and internal organs of Black Bengal goats, was studied. Thirty weaned Black Bengal kids of 3-5 months (5.40 ± 0.34 kg body weight) were assigned randomly into five groups and fed additional Cr for 150 days. The experimental diets comprised a basal diet supplemented with Cr at the rate of 0 (control; without Cr supplementation), 1.0 and 1.5 mg/kg of inorganic Cr (Cr(III)-chloride), and 1.0 and 1.5 mg/kg of organic Cr (Cr-yeast). The body morphometry such as body length, heart girth, paunch girth, loin width, leg circumference, and the carcass traits, namely, slaughter body weight, dressing percentage, hind quarter and forequarter weight, and rib eye area of goats, were not significantly (P < 0.05) changed due to inorganic and organic Cr supplementation. However, organic Cr supplementation (1.0 and 1.5 mg/kg) resulted in a reduction of breast and back fat thickness (P < 0.05) compared with the control group. The weights of internal organs including liver, lungs, spleen, kidney, testes, and heart and their weights as a percentage of slaughter weight were similar (P > 0.05) among different experimental groups. Dry matter, ether extract, and total ash concentrations of muscle and internal organs of Cr-supplemented groups were not affected (P > 0.05) by Cr supplementation. However, crude protein contents in the liver, muscle, kidney, and lungs were greater (P < 0.05) in the organic Cr groups than in the control and inorganic Cr groups. In meat (longissimus dorsi muscle), total saturated fatty acid concentration was lower (P < 0.05; 59.4% versus 55.7%) and the unsaturated fatty acid concentration was greater (P < 0.05; 40.6% versus 44.3%) including palmitoleic acid, heptadecenoic acid, elaidic acid, and arachidonic acid in the organic or inorganic Cr-supplemented groups than in the basal diet group. In conclusion, dietary supplementation of organic Cr in Black Bengal goats has no influence on the carcass traits, but may improve the meat quality with greater protein content, lean, and healthier fatty acids for human consumption.

Molecular and immune signatures, and pathological trajectories of fatal COVID-19 lungs defined by in situ spatial single-cell transcriptome analysis.

Despite intensive studies during the last 3 years, the pathology and underlying molecular mechanism of coronavirus disease 2019 (COVID-19) remain poorly defined. In this study, we investigated the spatial single-cell molecular and cellular features of postmortem COVID-19 lung tissues using in situ sequencing (ISS). We detected 10 414 863 transcripts of 221 genes in whole-slide tissues and segmented them into 1 719 459 cells that were mapped to 18 major parenchymal and immune cell types, all of which were infected by SARS-CoV-2. Compared with the non-COVID-19 control, COVID-19 lungs exhibited reduced alveolar cells (ACs) and increased innate and adaptive immune cells. We also identified 19 differentially expressed genes in both infected and uninfected cells across the tissues, which reflected the altered cellular compositions. Spatial analysis of local infection rates revealed regions with high infection rates that were correlated with high cell densities (HIHD). The HIHD regions expressed high levels of SARS-CoV-2 entry-related factors including ACE2, FURIN, TMPRSS2 and NRP1, and co-localized with organizing pneumonia (OP) and lymphocytic and immune infiltration, which exhibited increased ACs and fibroblasts but decreased vascular endothelial cells and epithelial cells, mirroring the tissue damage and wound healing processes. Sparse nonnegative matrix factorization (SNMF) analysis of niche features identified seven signatures that captured structure and immune niches in COVID-19 tissues. Trajectory inference based on immune niche signatures defined two pathological routes. Trajectory A primarily progressed with increased NK cells and granulocytes, likely reflecting the complication of microbial infections. Trajectory B was marked by increased HIHD and OP, possibly accounting for the increased immune infiltration. The OP regions were marked by high numbers of fibroblasts expressing extremely high levels of COL1A1 and COL1A2. Examination of single-cell RNA-seq data (scRNA-seq) from COVID-19 lung tissues and idiopathic pulmonary fibrosis (IPF) identified similar cell populations consisting mainly of myofibroblasts. Immunofluorescence staining revealed the activation of IL6-STAT3 and TGF-ß-SMAD2/3 pathways in these cells, likely mediating the upregulation of COL1A1 and COL1A2 and excessive fibrosis in the lung tissues. Together, this study provides a spatial single-cell atlas of cellular and molecular signatures of fatal COVID-19 lungs, which reveals the complex spatial cellular heterogeneity, organization, and interactions that characterized the COVID-19 lung pathology.

Modeling driver behavior in critical traffic scenarios for the safety assessment of automated driving.

OBJECTIVE: Before market introduction, the safety of highly automated driving systems needs to be assessed prospectively. BMW has developed a holistic approach for the assessment of the traffic safety impact by these systems in which stochastic traffic simulations play a significant role. A driver behavior model which represents realistic driver behavior ranging from performance in non-critical everyday driving toward performance in critical situations is key for this approach. To ensure trustworthy results, validation of the driver model is needed. The paper aims at demonstrating that the presented driver model acts realistically in different critical real-world traffic scenarios. METHODS: BMW has been developing the Stochastic Cognitive Model (SCM) which models cognitive processes in traffic situations. These processes range from information acquisition by gaze behavior, mental representation of the environment, recognition of situations from the visual information and reaction to the situation. The driver model combines these cognitive processes with stochastic driver parameters to obtain a variation in driver behavior in simulations. Especially visual attention modeling is key to realistic traffic interactions in simulations as this is the input for the sequential cognitive processes, i.e., the recognition of situations and the reaction to the situation. Modeling of driver's gaze behavior with SCM is thus shown in this paper. RESULTS: SCM is applied in three critical real-world traffic scenarios in which gaze behavior, brake reaction times and time-to-collisions are evaluated and compared to the real-world data. Due to the stochastic approach not only a single SCM agent but a collective of virtual SCM test drivers is assessed. Results show that SCM is capable to simulate the influence of visual inattention on collision risk. CONCLUSION: Realistic driver behavior in simulations can be achieved by using SCM. Especially in the presented critical scenarios SCM is able to represent real-world driving behavior which is determined particularly by its gaze behavior and subsequent reaction. Driving performance varies over different SCM agents which mean that different driving behavior can be simulated with SCM as well. However, the investigation in this paper included only three real-world cases. Therefore, further critical, and additionally non-critical scenarios need to be investigated in the future.

The synergistic ramification of insoluble dietary fiber and associated non-extractable polyphenols on gut microbial population escorting alleviation of lifestyle diseases.

Most of the pertinent research which aims at exploring the therapeutic effects of polyphenols usually misapprehends a large fraction of non-extractable polyphenols due to their poor aqueous-organic solvent extractability. These polymeric polyphenols (i.e., proanthocyanins, hydrolysable tannins and phenolic acids) possess a unique property to adhere to the food matrix polysaccharides and protein sowing to their structural complexity with high glycosylation, degree of polymerization, and plenty of hydroxyl groups. Surprisingly resistance to intestinal absorption does not hinder its bioactivity but accelerates its functionality manifolds due to the colonic microbial catabolism in the gastrointestinal tract, thereby protecting the body from local and systemic inflammatory diseases. This review highlights not only the chemistry, digestion, colonic metabolism of non-extractable polyphenols (NEPP) but also summarises the synergistic effect of matrix-bound NEPP exerting local as well as systemic health benefits.

CBCT-guided adaptive radiotherapy using self-supervised sequential domain adaptation with uncertainty estimation.

Adaptive radiotherapy (ART) is an advanced technology in modern cancer treatment that incorporates progressive changes in patient anatomy into active plan/dose adaption during the fractionated treatment. However, the clinical application relies on the accurate segmentation of cancer tumors on low-quality on-board images, which has posed challenges for both manual delineation and deep learning-based models. In this paper, we propose a novel sequence transduction deep neural network with an attention mechanism to learn the shrinkage of the cancer tumor based on patients' weekly cone-beam computed tomography (CBCT). We design a self-supervised domain adaption (SDA) method to learn and adapt the rich textural and spatial features from pre-treatment high-quality computed tomography (CT) to CBCT modality in order to address the poor image quality and lack of labels. We also provide uncertainty estimation for sequential segmentation, which aids not only in the risk management of treatment planning but also in the calibration and reliability of the model. Our experimental results based on a clinical non-small cell lung cancer (NSCLC) dataset with sixteen patients and ninety-six longitudinal CBCTs show that our model correctly learns weekly deformation of the tumor over time with an average dice score of 0.92 on the immediate next step, and is able to predict multiple steps (up to 5 weeks) for future patient treatments with an average dice score reduction of 0.05. By incorporating the tumor shrinkage predictions into a weekly re-planning strategy, our proposed method demonstrates a significant decrease in the risk of radiation-induced pneumonitis up to 35% while maintaining the high tumor control probability.

Sophorolipids: A comprehensive review on properties and applications.

Sophorolipids are surface-active glycolipids produced by several non-pathogenic yeast species and are widely used as biosurfactants in several industrial applications. Sophorolipids provide a plethora of benefits over chemically synthesized surfactants for certain applications like bioremediation, oil recovery, and pharmaceuticals. They are, for instance less toxic, more benign and environment friendly in nature, biodegradable, freely adsorb to different surfaces, self-assembly in hydrated solutions, robustness for industrial applications etc. These miraculous properties result in valuable physicochemical attributes such as low critical micelle concentrations (CMCs), reduced interfacial surface tension, and capacity to dissolve non-polar components. Moreover, they exhibit a diverse range of physicochemical, functional, and biological attributes due to their unique molecular composition and structure. In this article, we highlight the physico-chemical properties of sophorolipids, how these properties are exploited by the human community for extensive benefits and the conditions which lead to their unique tailor-made structures and how they entail their interfacial behavior. Besides, we discuss the advantages and disadvantages associated with the use of these sophorolipids. We also review their physiological and functional attributes, along with their potential commercial applications, in real-world scenario. Biosurfactants are compared to their man-made equivalents to show the variations in structure-property correlations and possible benefits. Those attempting to manufacture purported natural or green surfactant with innovative and valuable qualities can benefit from an understanding of biosurfactant features structured along the same principles. The uniqueness of this review article is the detailed physico-chemical study of the sophorolipid biosurfactant and how these properties helps in their usage and detailed explicit study of their applications in the current scenario and also covering their pros and cons.

Can Hierarchical Transformers Learn Facial Geometry?

Human faces are a core part of our identity and expression, and thus, understanding facial geometry is key to capturing this information. Automated systems that seek to make use of this information must have a way of modeling facial features in a way that makes them accessible. Hierarchical, multi-level architectures have the capability of capturing the different resolutions of representation involved. In this work, we propose using a hierarchical transformer architecture as a means of capturing a robust representation of facial geometry. We further demonstrate the versatility of our approach by using this transformer as a backbone to support three facial representation problems: face anti-spoofing, facial expression representation, and deepfake detection. The combination of effective fine-grained details alongside global attention representations makes this architecture an excellent candidate for these facial representation problems. We conduct numerous experiments first showcasing the ability of our approach to address common issues in facial modeling (pose, occlusions, and background variation) and capture facial symmetry, then demonstrating its effectiveness on three supplemental tasks.

Effect of Bamboo Essential Oil on the Oxidative Stability, Microbial Attributes and Sensory Quality of Chicken Meatballs.

This study explores the efficacy of bamboo essential oil (BEO) incorporated at 15 ppm (T1, BEO-I) and 30 ppm (T2, BEO-II) on the overall physicochemical and oxidative stability, microbial deterioration, and sensory acceptability of meatballs stored for 20 days under refrigerated conditions. Analysis of various parameters, including physicochemical quality, color (CIE L*, CIE a* and CIE b*), generation of oxidative products (TBARS), microbial growth, and sensory acceptability of meatballs were evaluated at 5-day intervals. In addition, the total phenolics and flavonoid content of BEO were estimated, and fatty acids were determined by Gas chromatography (GC.) To gain insights into the biological activities of the BEO, antioxidant assays were determined in vitro using various methods. The antibacterial activity of BEO was also evaluated against Gram-positive (Staphylococcus aureus and Bacillus subtilis) and Gram-negative (Vibrio cholera, Salmonella Typhimurium, Shigella flexneri, Proteus vulgaris, Escherichia coli and Klebsiella pneumoniae) bacterial strains. The BEO contained a good quantity of total phenolics and flavonoids. In addition, the oil exhibited very potent antioxidant activity scavenging reactive oxygen and other such species, effectively showing IC50 at a very minimal concentration. Further, the BEO exhibited a strong antibacterial effect with MICs within 2 µL and MBCs from 5 to 7 µL for Gram-positive as well as Gram-negative bacteria, respectively. At both the concentrations used, BEO did not show any negative effect on the color of cooked meatballs but rather increased the microbiological and oxidative stability during the overall storage period. Meatballs treated with BEO had considerably reduced oxidative changes in terms of TBARS levels compared to the control. The total viable microbial count was lowest in BEO-treated meatballs and the highest in control. Both control and treated meatballs had a desirable flavor and good acceptability. The sensory attributes and aroma of treated meatballs were better and acceptable during the storage study, whereas the control samples were disliked by the panelists on 15th day. From this study, it can be concluded that bamboo essential oil could be used as a benign and non-toxic preservative to improve the quality and shelf life of cooked meatballs stored under refrigerated conditions.

Standardised Critical Care Strategies Improve Outcomes Following Cytoreductive Surgery with Hyperthermic Intraperitoneal Chemotherapy in an Indian Peritoneal Malignancy Centre.

Cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) is a major undertaking with profound peri-operative metabolic and haemodynamic alterations. It requires standardised protocols for immediate postoperative intensive care management to improve patient-related outcomes. A retrospective analysis of a prospectively maintained data-base of 244 patients who underwent CRS and HIPEC between June 2017 and July 2022 in our institute was done. Based on the audit, six strategies were implemented, namely, (1) dynamic multiparameter-based IVF therapy to aggressively correct the hyperlactatemia, (2) initiation of IV 20% human albumin infusion from POD-0, (3) correction of serum iCa2+ levels, (4) initiation of diuresis from POD-1, (5) prophylactic use of HFNO immediately post-extubation and (6) serum procalcitonin level-based empiric escalation of IV antibiotics. Patients were divided into two cohorts, pre-protocol group of 145 patients (from June 2017 to December 2020) and post-protocol group comprising of 99 patients (from January 2021 to July 2022), and were analysed for compliance and patient-related outcomes. Implementation of these strategies improved the patient-related outcomes among the two cohorts with significant reduction of Clavien-Dindo grade III/IV complications and improvement in failure to rescue (FTR) index (p < 0.05). There was highly significant reduction in median ICU and hospital stay among the two cohorts (p < 0.001). The formulated protocols of management strategies especially multiparameter-based dynamic fluid therapy, planned diuresis and prophylactic HFNO have improved the outcomes in our patients undergoing CRS and HIPEC.

Sketching and sampling approaches for fast and accurate long read classification.

BACKGROUND: In modern sequencing experiments, quickly and accurately identifying the sources of the reads is a crucial need. In metagenomics, where each read comes from one of potentially many members of a community, it can be important to identify the exact species the read is from. In other settings, it is important to distinguish which reads are from the targeted sample and which are from potential contaminants. In both cases, identification of the correct source of a read enables further investigation of relevant reads, while minimizing wasted work. This task is particularly challenging for long reads, which can have a substantial error rate that obscures the origins of each read. RESULTS: Existing tools for the read classification problem are often alignment or index-based, but such methods can have large time and/or space overheads. In this work, we investigate the effectiveness of several sampling and sketching-based approaches for read classification. In these approaches, a chosen sampling or sketching algorithm is used to generate a reduced representation (a "screen") of potential source genomes for a query readset before reads are streamed in and compared against this screen. Using a query read's similarity to the elements of the screen, the methods predict the source of the read. Such an approach requires limited pre-processing, stores and works with only a subset of the input data, and is able to perform classification with a high degree of accuracy. CONCLUSIONS: The sampling and sketching approaches investigated include uniform sampling, methods based on MinHash and its weighted and order variants, a minimizer-based technique, and a novel clustering-based sketching approach. We demonstrate the effectiveness of these techniques both in identifying the source microbial genomes for reads from a metagenomic long read sequencing experiment, and in distinguishing between long reads from organisms of interest and potential contaminant reads. We then compare these approaches to existing alignment, index and sketching-based tools for read classification, and demonstrate how such a method is a viable alternative for determining the source of query reads. Finally, we present a reference implementation of these approaches at https://github.com/arun96/sketching .

Lactic Acid Bacteria and Bacteriocins: Novel Biotechnological Approach for Biopreservation of Meat and Meat Products.

Meat and meat products are perishable in nature, and easily susceptible to microbial contamination and chemical deterioration. This not only results in an increased risk to health of consumers, but also causes economic loss to the meat industry. Some microorganisms of the lactic acid bacteria (LAB) group and their ribosomal-synthesized antimicrobial peptides-especially bacteriocins-can be used as a natural preservative, and an alternative to chemical preservatives in meat industry. Purified or partially purified bacteriocins can be used as a food additive or incorporated in active packaging, while bacteriocin-producing cells could be added as starter or protective cultures for fermented meats. Large-scale applications of bacteriocins are limited, however, mainly due to the narrow antimicrobial spectrum and varying stability in different food matrixes. To overcome these limitations, bioengineering and biotechnological techniques are being employed to combine two or more classes of bacteriocins and develop novel bacteriocins with high efficacy. These approaches, in combination with hurdle concepts (active packaging), provide adequate safety by reducing the pathogenicity of spoilage microorganisms, improving sensory characteristics (e.g., desirable flavor, texture, aroma) and enhancing the shelf life of meat-based products. In this review, the biosynthesis of different classes of LAB bacteriocins, their mechanism of action and their role in the preservation of meats and meat products are reviewed.

Antimicrobial Resistance Pattern, Clustering Mechanisms and Correlation Matrix of Drug-Resistant Escherichia coli in Black Bengal Goats in West Bengal, India.

A cross-sectional study covering four agro-climatic zones of West Bengal, India, was carried out to understand the risk-factors, antimicrobial resistance mechanism and clustering of the resistance characteristics of Escherichia coli isolated from healthy (170) and diarrhoeic (74) goats reared under intensive (52) and semi-intensive (192) farming practices. Of the 488 E. coli isolates, the majority, including the extended spectrum (n: 64, 13.11%) and AmpC ß-lactamase (ACBL) (n: 86, 17.62%) producers, were resistant to tetracycline (25.2%), followed by enrofloxacin (24.5%), cefotaxime (21.5%) and amikacin (20.5%). Statistical modelling revealed that the isolates from diarrhoeic animals (p < 0.001) are likely to be more ACBL-positive than those from the healthy counterparts. Similarly, cefotaxime (p < 0.05) and enrofloxacin-resistance (p < 0.01) were significantly higher in diarrhoeic goats and in goats reared intensively. The isolates (n = 35) resistant to multiple drugs revealed the presence of ß-lactamase [blaCTXM-1-(21), blaSHV-(7), blaTEM-(3), blaCMY-6-(1), blaCITM-(3)]; quinolone [qnrB-(10), qnrS-(7), aac(6')-Ib-cr-(3)]; tetracycline [tetA-(19), tetB-(4)] and sulphonamide resistance determinants [sul1-(4)]; multiple plasmids, especially those belonging to the IncF and IncI1 replicon types; and active acrAB efflux pumps. Further, two isolates harbored the carbapenem resistance (blaNDM-5) gene and eight were strong biofilm producers. This first ever study conducted to unravel the status of AMR in goat farming reveals that not only the intensive farming practices but also certain clinical ailments such as diarrhoea can increase the shedding of the drug-resistant isolate. The emergence of multi-drug resistant (MDR) E. coli in goats, particularly those that are carbapenem resistant, is a cause for concern that indicates the spread of such pathogens even in the livestock sub-sector generally considered as naive.

Multimodal explainable AI predicts upcoming speech behavior in adults who stutter.

A key goal of cognitive neuroscience is to better understand how dynamic brain activity relates to behavior. Such dynamics, in terms of spatial and temporal patterns of brain activity, are directly measured with neurophysiological methods such as EEG, but can also be indirectly expressed by the body. Autonomic nervous system activity is the best-known example, but, muscles in the eyes and face can also index brain activity. Mostly parallel lines of artificial intelligence research show that EEG and facial muscles both encode information about emotion, pain, attention, and social interactions, among other topics. In this study, we examined adults who stutter (AWS) to understand the relations between dynamic brain and facial muscle activity and predictions about future behavior (fluent or stuttered speech). AWS can provide insight into brain-behavior dynamics because they naturally fluctuate between episodes of fluent and stuttered speech behavior. We focused on the period when speech preparation occurs, and used EEG and facial muscle activity measured from video to predict whether the upcoming speech would be fluent or stuttered. An explainable self-supervised multimodal architecture learned the temporal dynamics of both EEG and facial muscle movements during speech preparation in AWS, and predicted fluent or stuttered speech at 80.8% accuracy (chance=50%). Specific EEG and facial muscle signals distinguished fluent and stuttered trials, and systematically varied from early to late speech preparation time periods. The self-supervised architecture successfully identified multimodal activity that predicted upcoming behavior on a trial-by-trial basis. This approach could be applied to understanding the neural mechanisms driving variable behavior and symptoms in a wide range of neurological and psychiatric disorders. The combination of direct measures of neural activity and simple video data may be applied to developing technologies that estimate brain state from subtle bodily signals.

Effect of supplementation of phytogenic feed additives on intake, in vitro fermentation, growth performance and carcass traits in weaned Barbari kids reared under intensive feeding.

Twenty-four weaned male Barbari kids (age 144.67 days; weight 11.99 ± 0.49 kg) were divided equally into three groups (T1, T2, and T3) in order to investigate the effect of supplementation of phytogenic feed additives (herbal mixture) in the complete pelleted feed on growth performance, in vitro rumen fermentation and carcass quality in kids reared under stall-fed condition. Treatment groups were as follows: T1, concentrate mixture (40%) plus arhar (Cajanus cajan) straw (60%) in total mixed ration (TMR) form fed ad libitum; T2, T1 diet in complete feed pellets form fed ad libitum; and T3, T1 diet in complete feed pellets form supplemented with herbal mixture (Tulsi/Haldi/Amla/Arni; ratio 1:1:1:1 on DM basis) at 0.5% in complete feed fed ad libitum. The experimental kids in each group were allowed for feeding for 8 months by following the respective feeding schedule. Rumen fermentation pattern under in vitro system was also studied using the same three diets as substrates. After 240 days of feeding, all goats were slaughtered following standard protocol. Total body weight gain (kg) and average daily gain (ADG, g/day/kid) were 18.57, 22.26, and 23.06 kg, and 79.91, 101.49, and 100.18 g in T1, T2, and T3 treatments, respectively. Pelleting of TMR (T2) and supplementation of herbal mixture in pelleted feed (T3) increased (P < 0.001) average daily weight gain in Barbari kids compared to T1 (TMR). Average dry matter intake (DMI, g/day/kid) during growth trial was greater (P < 0.05) in T3 (1079.17) than T1 (849.76) and T2 (968.76). Feed conversion efficiency was 8.92, 9.48, and 8.68% in T1, T2, and T3, respectively. The difference was statistically non-significant among the treatments. Supplementation of herbal mixture in the complete pelleted substrate had adjunct effect on improvement of TCA-precipitable-N and total VFAs in the incubation medium under in vitro system. Carcass weight (kg) tended to increase in finisher kids under T2 (16.58) and T3 (16.70) than T1 (14.61), but the variation was non-significant. The dressing percentage was similar among three treatments. Similarly, the muscle protein, fat, and cholesterol contents remained unaffected by different dietary treatments. Therefore, it may be concluded that densification of feeds in the form of complete pelleted feed and further supplementation with potential phytogenic feed additives increased total DMI and ADG and tended to enhance meat production potential in finisher Barbari kids without changing the meat chemical composition.

Photocatalytic performance and interaction mechanism of reverse micelle synthesized Cu-TiO2 nanomaterials towards levofloxacin under visible LED light.

The degradation performance of Cu-TiO2 nanomaterials towards levofloxacin (LFX) antibiotic was investigated under an environmentally benign visible LED light source. Cu-TiO2 nanomaterials were prepared using the reverse micelle sol-gel method with different copper content ranging from 0.25 to 1.0 wt% concerning titania. Characterization of Cu-TiO2 samples was performed by XRD, TEM, UV-Vis, BET, ICP-MS, FTIR and XPS techniques. 0.5 wt% Cu-TiO2 showed crystallite size below 6 nm, surface area (69.85 m2/g) and significant visible light absorption capacity. Both Cu1+ and Cu2+ are formed in lower Cu-doped TiO2 samples, whereas only Cu2+ is present in higher Cu-doped TiO2 samples as evident in XPS analysis. 0.5 wt% Cu-TiO2 has shown the optimum photocatalytic degradation of 75.5% under 6 h. of a visible light source. FTIR analysis of LFX adsorbed Cu-TiO2 materials indicated the pollutant-catalyst interaction, where the declining trend was observed in photocatalytic degradation efficiency for higher Cu-doped TiO2 samples due to copper-LFX complex formation. Copper-LFX complexes are formed due to the presence of Cu2+ in higher Cu-doped TiO2 nanomaterials, which might have hindered the photocatalytic activity under visible light. Effects of initial pollutant concentration, catalyst loading and visible light intensity on the degradation of LFX are studied. Photocatalytic degradation pathways of LFX using best performing Cu-TiO2 material were also proposed based on the LC-MS analysis.