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This article presents Ansys simulations and experimental testing to determine how TBC affects engine performance and emissions. In this work, two distinct thermal barrier coatings have been identified, and the same coating materials were subsequently sprayed onto the pistons of an internal combustion engine. Transient thermal analysis reveals that TBC-1 and TBC-2 coatings reduce surface temperature distributions by 35% and 18%, respectively, and that these engines improve Brake Thermal Efficiency (BTE) by 8.71% and 7.62%, respectively, compared to non-coated engines operating under full load. TBC-1 and TBC-2 coated engines are found to have Brake-Specific Fuel Consumption (BSFC) reductions of 27.13% and 18.81%, respectively. Complete combustion reduces emissions of CO and HC, as the heat balance sheet indicates because the conversion of energy and mechanical work are enhanced by 3.56 percentage points and 2.0 percentage points, respectively.

Microbiomes in soil ecosystems play a significant role in solubilizing insoluble inorganic and organic phosphate sources with low availability and mobility in the soil. They transfer the phosphate ion to plants, thereby promoting plant growth. In this study, we isolated an unidentified fungal strain, POT1 (Penicillium olsonii TLL1) from indoor dust samples, and confirmed its ability to promote root growth, especially under phosphate deficiency, as well as solubilizing activity for insoluble phosphates such as AlPO4, FePO4·4H2O, Ca3(PO4)2, and hydroxyapatite. Indeed, in vermiculite containing low and insoluble phosphate, the shoot fresh weight of Arabidopsis and leafy vegetables increased by 2-fold and 3-fold, respectively, with POT1 inoculation. We also conducted tests on crops in Singapore’s local soil, which contains highly insoluble phosphate. We confirmed that with POT1, Bok Choy showed a 2-fold increase in shoot fresh weight, and Rice displayed a 2-fold increase in grain yield. Furthermore, we demonstrated that plant growth promotion and phosphate solubilizing activity of POT1 were more effective than those of four different Penicillium strains such as Penicillium bilaiae, Penicillium chrysogenum, Penicillium janthinellum, and Penicillium simplicissimum under phosphate-limiting conditions. Our findings uncover a new fungal strain, provide a better understanding of symbiotic plant-fungal interactions, and suggest the potential use of POT1 as a biofertilizer to improve phosphate uptake and use efficiency in phosphate-limiting conditions.

The skin plays a crucial role in maintaining hydration, preventing dehydration, and protecting against harmful microorganisms. Skin injury can lead to inflammation and fluid loss, which are detrimental to human health. Nanotechnology has been proposed as a potential solution to prevent skin damage because it can more effectively penetrate the skin barrier and deliver targeted treatments directly to the cells that require them. In this study, we biosynthesized gold nanoparticles (AuNPs) using Isodon excisus (Maxim.) Kudo (IE) leaf tissue. The formation of IE gold nanoparticles (IE-AuNPs) was confirmed using various techniques. Furthermore, the cytotoxicity of IE-AuNPs on human keratinocytes (HaCaT cells) was evaluated, and it was found that the IE-AuNPs had no cytotoxic effect on HaCaT cells (50 µg/mL). The ability of IE-AuNPs to penetrate HaCaT cells and reduce skin inflammation was investigated using dark-field microscopy (DFM) and enzyme-linked immunosorbent assay (ELISA). Real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to assess inflammatory biomarkers such as IL-6, IL-8, CCL17/TARC, CCL27/CTACK, and CCL5/RANTES. Additionally, western blotting demonstrated that IE-AuNPs exhibited anti-inflammatory effects on the skin by activating autophagy biomarkers and inhibiting the PI3K/AKT signaling pathway at the upstream level. Overall, our findings suggest that IE-AuNPs enhance the anti-inflammatory effect on skin cells and can be used in the development of nano-based treatments for skin-related diseases.

BackgroundResearch around the weedkiller Roundup is among the most contentious of the twenty-first century. Scientists have provided inconclusive evidence that the weedkiller causes cancer and other life-threatening diseases, while industry-paid research reports that the weedkiller has no adverse effect on humans or animals. Much of the controversial evidence on Roundup is rooted in the approach used to determine safe use of chemicals, defined by outdated toxicity tests. We apply a system biology approach to the biomedical and ecological model species Daphnia to quantify the impact of glyphosate and of its commercial formula, Roundup, on fitness, genome-wide transcription and gut microbiota, taking full advantage of clonal reproduction in Daphnia. We then apply machine learning-based statistical analysis to identify and prioritize correlations between genome-wide transcriptional and microbiota changes.ResultsWe demonstrate that chronic exposure to ecologically relevant concentrations of glyphosate and Roundup at the approved regulatory threshold for drinking water in the US induce embryonic developmental failure, induce significant DNA damage (genotoxicity), and interfere with signaling. Furthermore, chronic exposure to the weedkiller alters the gut microbiota functionality and composition interfering with carbon and fat metabolism, as well as homeostasis. Using the "Reactome," we identify conserved pathways across the Tree of Life, which are potential targets for Roundup in other species, including liver metabolism, inflammation pathways, and collagen degradation, responsible for the repair of wounds and tissue remodeling.ConclusionsOur results show that chronic exposure to concentrations of Roundup and glyphosate at the approved regulatory threshold for drinking water causes embryonic development failure and alteration of key metabolic functions via direct effect on the host molecular processes and indirect effect on the gut microbiota. The ecological model species Daphnia occupies a central position in the food web of aquatic ecosystems, being the preferred food of small vertebrates and invertebrates as well as a grazer of algae and bacteria. The impact of the weedkiller on this keystone species has cascading effects on aquatic food webs, affecting their ability to deliver critical ecosystem services. Video Abstract.

Mycoplasma pneumoniae is recognized as the leading cause of community-acquired lower respiratory tract infection in children, accounting for a significant proportion of pediatric mortality. Macrolides are the first-line treatment for M. pneumoniae infections. However, the extensive use of macrolides in clinical practice resulted in the emergence of macrolide-resistant M. pneumoniae (MRMP), which has a negative impact on treatment outcomes. Hence, in the present study, MRMP was determined in hospitalized children with community-acquired pneumonia (CAP). Real-time PCR detected M. pneumoniae in 41 of 348 clinical samples. Sanger sequencing revealed that none of the isolates were associated with the A2063G or A2064G base mutation, which confers macrolide resistance, in domain V of the 23S rRNA gene. Although MRMP was not observed in children with CAP in our study, healthcare practitioners should be vigilant about the potential risk of MRMP infections.

Abstract Cotton is a natural fiber containing more than 95% of cellulose. With worldwide cotton consumption continuously increasing, the amount of cotton waste generated is enormous. Most of the cotton waste ends up in landfill or incinerators, resulting in a huge waste of this excellent natural resource. In this project, cotton waste was recycled to produce polypropylene nanocomposites. Instead of using the traditional two-step nanofiber extraction and compounding technique, an integrated process was adopted to combine nanofibrillation and compounding into one step. Results showed that cotton fibers with a slight prefibrillation and hydrophobic surface modification were successfully fibrillated into tens to hundreds of nanometers in width during compounding. The nanofibers reinforced polypropylene composites exhibited significantly enhanced tensile and flexural strength and moduli. For instance, when 30% fibers from bleached white and indigo-dyed denim fabrics were introduced, the tensile moduli of the resultant composites reached 4.57 and 4.59 GPa, respectively, compared to 1.60 GPa, the modulus of neat PP. Meanwhile, denim fabrics had a remarkable reinforcing effect on the composites’ impact strength attributing to the hydrophobic indigo dyes that improved the interfacial bonding between cotton fibers and the matrix. The highest impact strength of denim reinforced composites was 4.96 kJ/m2 with 20% fiber loading; while the impact strength of neat polypropylene was 2.46 kJ/m2. The low water uptake of the composites further indicated the excellent adhesion at the filler/matrix interface. In general, a very promising processing technique to recycle cotton waste for high-value products was demonstrated.

The high-speed development of wireless communication technology has emerged in the surging insistence on optimal spectrum resources. Nevertheless, in consonance to a contemporary study, most of the assigned frequency encounters notable underutilization as far as Cognitive Radio Network (CRN) is concerned. One important issue correlated with spectrum management is how to properly estimate and allocate the spectrum to a Secondary User (SU) for a highly dynamic environment in an optimal manner with minimum sensing delay. In this paper, a Chebyshev Vector Dynamic Spectrum and Kolmogorov-Smirnov Convolutional Network (CVDS-KSCN) method for dynamic spectrum estimation and optimal secondary user selection in CRN is developed. First, it is proposed to tackle the dynamic spectrum access issue with minimum sensing delay in CRN attaining robust spectrum channel throughput with minimum sensing delay. The spectrum estimation is modeled using the Chebyshev distance-based Harmonious Vector Spectrum Estimation model in a dynamic manner. With the dynamic spectrum estimated results, a Kolmogorov-Smirnov Convolutional Neural Network-based Secondary User Selection model is applied to retrieve optimal secondary users in CRN. The performance of CVDS-KSCN is assessed over numerous key aspects, where simulation results confirm the efficiency of the proposed method in achieving high reliable spectrum estimation and Secondary User selection. It is expressive in the simulation results that the proposed CVDS-KSCN method can achieve a good probability of throughput and reduction in sensing delay during Secondary User Selection with low probability of false alarm. The results show that the proposed method outperfroms the DRS and EFAHP algorithms quantitatively in terms of four parameters, namely throughput, sensing delay, false alarm percentage and Secondary User Selection Time.

Objective: To derive a clinical score from parameters that favor remission of Cushing's disease (CD) after pituitary surgery. Methods: This is an analysis of 11 clinical, hormonal, and post-operative parameters that each favored remission in a cohort of 145 patients with CD treated by trans-sphenoidal surgery (TSS). Each parameter was designated as a categorical variable (presence/absence), and several favorable parameters present for each patient were calculated. From this, a median parameter score (clinical score) of the entire cohort was derived, which was then compared to the event of remission/persistence of CD. Results: The median number of favorable parameters present in the entire cohort was 3 (0–7). The significant count of patients in remission increased with the increasing number of parameters. The receiver-operator characteristic curve showed that the presence of ≥3 parameters was associated with remission in CD with a sensitivity of 84.2% and a specificity of 80%. Patients with a clinical score ≥3 had significantly higher remission rates (88.9%) than those who had persistent disease (27.3%; P = 0.001).Conclusion: A clinical score of ≥3 predicts remission in CD treated by TSS; however, it requires validation in other large cohorts. Rather than assessing individual parameters to predict remission in CD, an integrated clinical score is a better tool for follow-up and patient counseling.

Introduction: Prolonged COVID-19 pandemic accelerates the emergence and transmissibility of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants through the accumulation of adaptive mutations. Particularly, adaptive mutations in spike (S) protein of SARS-CoV-2 leads to increased viral infectivity, severe morbidity and mortality, and immune evasion. This study focuses on the phylodynamic distribution of SARS-CoV-2 variants during the year 2021 in India besides analyzing the functional significance of mutations in S-protein of SARS-CoV-2 variants. Methods: Whole genome of SARS-CoV-2 sequences (n = 87957) from the various parts of India over the period of January to December 2021 was retrieved from Global Initiative on Sharing All Influenza Data. All the S-protein sequences were subjected to clade analysis, variant calling, protein stability, immune escape potential, structural divergence, Furin cleavage efficiency, and phylogenetic analysis using various in silico tools. Results: Delta variant belonging to 21A, 21I, and 21J clades was found to be predominant throughout the year 2021 though many variants were also present. A total of 4639 amino acid mutations were found in S-protein. D614G was the most predominant mutation in the S-protein followed by P681R, L452R, T19R, T478K, and D950N. The highest number of mutations was found in the N-terminal domain of S-protein. Mutations in the crucial sites of S-protein impacting pathogenicity, immunogenicity, and fusogenicity were identified. Intralineage diversity analysis showed that certain variants of SARS-CoV-2 possess high diversification. Conclusions: The study has disclosed the distribution of various variants including the Delta, the predominant variant, in India throughout the year 2021. The study has identified mutations in S-protein of each SARS-CoV-2 variant that can significantly impact the virulence, immune evasion, increased transmissibility, high morbidity, and mortality. In addition, it is found that mutations acquired during each viral replication cycle introduce new sub-lineages as studied by intralineage diversity analysis.

Background: Indiscriminate use and disposal of plastic products has deleterious effects on ecosystem. Studies suggest discarded plastic waste as potential breeding source for Aedes mosquitoes. Aim and Objectives: To compare plastic waste disposal practices in low and high dengue incidence areas and identify possible association between plastic waste disposal practices and dengue outbreaks. Material and Methods: This was a descriptive, cross-sectional, comparative study conducted between January and February 2021 in Chengalpattu district, Tamil Nadu, among 100 households each selected from low and high dengue incidence areas, categorized based on previous year statistics. A pre-tested, semi-structured questionnaire and an observational checklist were used to assess household plastic use and waste disposal practices. Value of p ≤0.05 was considered statistically significant. Results: Low-incidence areas were characterized by higher proportion of respondents with diploma/degree (61.5%), pucca houses (54.5%) and apartments (88.9%). Majority (98%) were aware about law prohibiting single-use plastic. Types of plastic products used and reused were similar among both areas, except, plastic covers, barrels and medicine bottles (p ≤0.05). Plastic waste segregation (45%) and safe (64.5%) or moderately safe (54.5%) disposal methods was higher in low-incidence areas. A greater proportion of study units in high-incidence areas had signs of burning waste, open disposal, contamination of water bodies, clogging of drains with plastic waste, used and unused plastic containers within and outside premises, plastic waste with water collections and larval breeding compared to low incidence areas (p ≤ 0.05). Conclusion: Our research reveals high plastic products usage and inadequate waste management practices. Despite similar pattern of use, low- and high- dengue incidence areas, showed marked difference in plastic waste disposal practices, pointing to potential relationship between poor plastic waste management and occurrence of dengue.

Across India, there have been multiple studies conducted to address the issues of the mental health of healthcare workers during the COVID-19 pandemic. The present study estimated the pooled prevalence of psychological morbidity among healthcare workers during the early phase of the COVID 19 pandemic in India. We searched the following electronic bibliographic databases: PubMed, ScienceDirect, Wiley online library, and Google scholar for studies conducted from the onset of the COVID 19 pandemic until 25 September 2021. The methodological quality of each study was scored and outcome measures with uniform cut off scores as per various screening measurements were evaluated. According to the current meta analysis, the pooled estimates of depression, anxiety, stress, and insomnia among Indian healthcare workers during the COVID 19 pandemic are 20.1% (95% CI: 15.6 to 24.6%; n = 21 studies), 25.0% (95% CI: 18.4 to 31.6%; n = 20 studies), 36% (95% CI: 23.7 to 48.2%; n = 22 studies) and 18.9% (95% CI: 9.9 to 28.0%; n = 6 studies) respectively. In subgroup analyses, low quality studies based on the JBI checklist (Score < 3/9) and studies using DASS 21 showed a higher pooled prevalence of depression and anxiety. About 20–36% of the healthcare workers in India reported having depression, anxiety, and stress during the early phase of the COVID 19 pandemic. The present study provides a comprehensive review of the overall burden of mental health problems among healthcare workers during the COVID 19 pandemic in India necessitating appropriate intervention strategies to protect these frontline groups before the memory of the pandemic crisis starts to fade.

In this manuscript, we are proposing a new kind of modified Susceptible Exposed Infected Quarantined Recovered model (SEIQR) with some assumed data. The novelty imposed here in the study is that we are studying simultaneously SIR, SEIR, SIQR, and SEQR pandemic models with the same data unchanged as the SEIQR model. We are taking this model a step ahead by using a non-helpful transition because it was mostly skipped in the literature. All sorts of features that are essential to study the models, such as basic reproduction number, stability analysis, and numerical simulations have been examined for this modified SEIQR model with decomposed other epidemic models.

Ragul Paramasivam,1 Dhinakar Raj Gopal,2 Ranjithkumar Dhandapani,1 Ramalakshmi Subbarayalu,1 Mahesh Prabu Elangovan,1 Bhavadharani Prabhu,1 Veeramani Veerappan,1 Arunkumar Nandheeswaran,1 Siddarth Paramasivam,1 Saravanan Muthupandian3,4 1Research and Development Division, Chimertech Private Limited, Chennai, India; 2Department of Animal Biotechnology, Madras Veterinary College, Tamilnadu Veterinary and Animal Science University (TANUVAS), Chennai, 600007, India; 3AMR and Nanotherapeutics Lab, Centre for Transdisciplinary Research (CFTR), Department of Pharmacology, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, India; 4Division of Biomedical Science, College of Health Sciences, School of Medicine, Mekelle University, Mekelle, EthiopiaCorrespondence: Saravanan Muthupandian, Email bioinfosaran@gmail.comBackground: Bovine mastitis is the most frequent and costly illness impacting dairy herds worldwide. The presence of subclinical mastitis in dairy cows has an impact on the decreased output of milk and milk quality, culling of affected cows, mortality rate, as well as mastitis-related treatment expenses, generating significant financial loss to the dairy industry. The pathogenic bacteria invade through the mammary gland, which then multiply in the milk-producing tissues causing infection, and the presence of pathogenic bacteria in milk is concerning, jeopardizes human health, and also has public health consequences. Intervention to promote herd health is essential to protect public health and the economy.Results: This review attempts to provide an overview of subclinical mastitis, including mastitis in different species, the effect of mastitis on human health and its pathogenic mechanism, the prevalence and incidence of subclinical mastitis, and current preventive, diagnostic, and treatment methods for subclinical mastitis. It also elaborates on the management practices that should be followed by the farms to improve herd immunity and health.Conclusion: This review brings the importance of the threat of antimicrobial resistance organisms to the dairy industry. Furthermore, this review gives a glimpse of the economic consequences faced by the farmers and a futuristic mastitis market analysis in the dairy industry.Keywords: subclinical mastitis, human health, economy, pathogenic mechanism, management

Byline: Manju. Dhandapani, Jaison. Joseph, Suresh. Sharma, Surekha. Dabla, Biji. Varkey, Venkata. Narasimha, Abin. Varghese, Sivashanmugam. Dhandapani Background: The significant burden of stroke on the mortality rates of developing countries, [...]