Respiratory diseases represent a significant economic and health burden worldwide, affecting millions of individuals each year in both human and animal populations. MicroRNAs (miRNAs) play crucial roles in gene expression regulation and are involved in various physiological and pathological processes. Exosomal miRNAs and cellular miRNAs have been identified as key regulators of several immune respiratory diseases, such as chronic respiratory diseases (CRD) caused by Mycoplasma gallisepticum (MG), Mycoplasma pneumoniae pneumonia (MMP) caused by the bacterium Mycoplasma pneumoniae, coronavirus disease 2019 (COVID-19), chronic obstructive pulmonary disease (COPD), asthma, and acute lung injury/acute respiratory distress syndrome (ALI/ARDS). Consequently, miRNAs seem to have the potential to serve as diagnostic biomarkers and therapeutic targets in respiratory diseases. In this review, we summarize the current understanding of the functional roles of miRNAs in the above several respiratory diseases and discuss the potential use of miRNAs as stable diagnostic biomarkers and therapeutic targets for several immune respiratory diseases, focusing on the identification of differentially expressed miRNAs and their targeting of various signaling pathways implicated in disease pathogenesis. Despite the progress made, unanswered questions and future research directions are discussed to facilitate personalized and targeted therapies for patients with these debilitating conditions.

Ionizing radiation gives tremendous benefit to mankind in the hospital through diagnosis and treatment to patients but unnecessary radiation may cause harm to healthcare workers & the public. The purpose of the study is to continuous radiation monitoring in & around the three largest radiological facilities of Bangladesh such as Atomic Energy Centre Dhaka (AECD), Dhaka Medical College Hospital (DMCH) & Bangabandhu Sheikh Mujib Medical University (BSMMU) campuses, and estimation of radiation risk on healthcare workers & public health. Continuous radiation monitoring was performed in & around the AECD, DMCH, BSMMU campuses from August-October 2020 using the Chemiluminescent Dosimeters. The yearly effective doses to healthcare workers and the public due to radiation released from the facilities were ranged from 0.606 ± 0.031 mSv to 0.801 ± 0.0.042 mSv with a mean of 0.707 ± 0.053 mSv. The excess lifetime cancer risk (ELCR) on healthcare workers & public health were evaluated based on the yearly effective dose and ranged from 2.486 Χ 10-3 to 3.287 Χ 10-3 with a mean of 2.900 Χ 10-3. The average yearly effective dose and ELCR on healthcare workers & public health were lower than those of the worldwide permissible values. Continuous radiation monitoring in & around the largest radiological facilities is required for detection of the radiation generating equipment’s malfunctions and improper handling of the radioactive materials. The study would help for minimization of radiation risk on healthcare workers & the public and this keeps the hospital’s environment free from radiation hazard.

1. This study determined the effective indicators and proteins involved in long-duration fertility (DF) in chickens.2. Three lines of Chinese Xinhua chickens (900) were compared using seven phenotypic trait indicators, and the best was determined based on repeatability value. Subsequently, differential expression analysis, functional annotation and protein-protein interaction (PPI) network analyses were performed to investigate the pathways and hub proteins. Finally, qPCR analysis was conducted to validate the expression of identified hub proteins, and functional annotation with previously published genes was performed to explain how hub proteins work to maintain the trait.3. The study found that the number of fertilised eggs (FN) and maximum fertilised eggs (MCF) were the most repeatable among the seven indicators. It identified 231 differentially expressed proteins, with 144 being down-regulated and 87 being up-regulated. The differentially expressed proteins exhibited high clustering within various cellular compartments, including the cytosol and cytoplasm and GTP binding. Multiple pathways were identified, including tight and adherens junctions, TGF-beta signalling, autophagy-animal, regulation of actin cytoskeleton and the ribosome that may regulate the trait. Three hub proteins, KRAS, RPL5 (p < 0.001), and HSPA4 (p < 0.01), were significantly differentially expressed between high and low DF groups.4. This study identified FN and MCF as effective indicators for addressing DF. As it is a quantitative trait, KRAS, HSPA4, and RPL5 are potential hub proteins that work with other genes to maintain the trait.

Query similarity prediction task is generally solved by regression based models with square loss. Such a model is agnostic of absolute similarity values and it penalizes the regression error at all ranges of similarity values at the same scale. However, to boost e-commerce platform's monetization, it is important to predict high-level similarity more accurately than low-level similarity, as highly similar queries retrieves items according to user-intents, whereas moderately similar item retrieves related items, which may not lead to a purchase. Regression models fail to customize its loss function to concentrate around the high-similarity band, resulting poor performance in query similarity prediction task. We address the above challenge by considering the query prediction as an ordinal regression problem, and thereby propose a model, ORDSIM (ORDinal Regression for SIMilarity Prediction). ORDSIM exploits variable-width buckets to model ordinal loss, which penalizes errors in high-level similarity harshly, and thus enable the regression model to obtain better prediction results for high similarity values. We evaluate ORDSIM on a dataset of over 10 millions e-commerce queries from eBay platform and show that ORDSIM achieves substantially smaller prediction error compared to the competing regression methods on this dataset.

This study integrated phenotypic and molecular characterisation of LAB isolated from whole‐crop maize and Napier fodder and silage with laboratory‐scale ensiling to evaluate their fermentation efficacy in maize silage. Twenty‐one LAB isolates were screened, of which seven were confirmed by 16 s rRNA gene sequenced as Limosilactobacillus fermentum and Bacillus subtilis . The isolates exhibited broad physiological tolerance, growth at 15°C–43°C, pH 4.0–9.5, 7% NaCl, and the ability to ferment multiple carbohydrates. Selected strains ( L. fermentum PQ482012 and B. subtilis PQ482016) were evaluated as silage inoculants in maize fodder over 45 days under controlled conditions. Inoculated silages exhibited significantly improved fermentation, with reduced pH (4.04–4.09; p = 0.004) and lower ammonia‐nitrogen (4.20–6.10 mg/100 mL; p = 0.001) compared to uninoculated control (pH, 4.19; 7.25 mg/100 mL). L. fermentum inoculation resulted in higher crude protein retention (92.20 g/kg of dry matter; p = 0.001), whilst combined inoculation enhanced acidification but caused greater DM loss (48.65 g/kg; p = 0.001). Inoculated silage also exhibited higher LAB counts, suppression of yeast, and absence of moulds. Overall, the native L. fermentum and B. subtilis strains exhibit strong strain‐specific fermentation traits, showing promise as bio‐inoculants for enhancing maize silage quality.

1. This study identified the most effective indicator for assessing the duration of fertility (DF) in chickens by comparing six potential indicators; number of fertilised eggs (NFE), maximum number of fertilised eggs continuously produced (MNFE), effective duration of fertility (EDF), fertility duration day (FDD), maximum duration of fertility conditional (MDFC) and maximum duration of fertility (MDF).2. This study used 1162 Xinhua chickens in two groups: 764 parental (unselected) and 398 selected (first-generation obtained from the parent MNFE > 6) groups, with three lines (B, C and D) in each group. Data from two artificial insemination cycles (17 d) in 60-week-old birds were used to calculate the indicator value. Subsequently, a comparative analysis of the indicators, heritability, selection response and repeatability was conducted within and between groups to assess genetic and environmental influences. Correlation analysis was performed to evaluate the relationship between the indicators and egg production status (unfertilised egg production (UEP), total egg production number (TEP) and individual fertility rate (IFR)).3. Comparing the two groups, there were significant (p < 0.001) differences in all indicators except MDFC and MDF. Among the indicators, NFE exhibited the highest heritability (h² = 0.23), the strongest selection response (R = 0.80) and the highest repeatability in both groups. Analysis showed that NFE was significantly (p < 0.001) correlated with all indicators and highly correlated with TEP(r = 0.73), IFR (r = 0.74) and negatively moderately correlated with UEP (r = -0.49).4. The data suggested that NFE was the most reliable DF indicator, offering consistency and comparatively higher genetic influence.