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Background Patients with chronic-obstructive-pulmonary-disease (COPD) undergo bronchoscopy for various reasons, and are at relatively higher risk of complications. This study evaluated the efficacy of non-invasive ventilation (NIV) and high-flow-oxygen-therapy (HFOT) compared with conventional-oxygen-therapy (COT) in patients with COPD undergoing bronchoscopy, to prevent hypoxia.Methods It was a triple-arm, open-label, randomised controlled trial. Ninety patients with COPD were randomly assigned into three intervention arms in 1:1:1 ratio. The incidence of hypoxia, lowest recorded oxygen saturation measured by plethysmography (SpO2), ECG, patient vitals and comfort levels were assessed.Results Mean age of the study population was 61.71±7.5 years. Out of 90 cases enrolled, 51, 34 and 5 were moderate, severe and very-severe COPD, respectively, as per GOLD (Global Initiative for Chronic Obstructive Lung Disease) classification. Rest of the baseline characteristics were similar. SpO2 during flexible bronchoscopy (FB) was lowest in COT group (COT: 87.03±5.7% vs HFOT: 95.57±5.0% vs NIV: 97.40±1.6%, p

The MATRIX protocol presents a novel miniaturized 24-well plate approach for microbial cultivation profiling, enabling the efficient and parallel assessment of microbial metabolite production. This method integrates a media MATRIX within a microbioreactor to facilitate the creation of diverse growth conditions for microbial cultivation. The 24-well format supports the simultaneous study of multiple microbial strains and conditions, allowing the discovery of novel bioactive compounds. By employing a variety of media compositions and cultivations, MATRIX enhances the understanding of microbial metabolic pathways and interactions. This protocol provides a robust platform for natural product discovery, microbial ecology studies, and drug development, showcasing its potential to uncover new natural products and other valuable bioactives. The MATRIX approach offers a resource-efficient platform for microbial biodiscovery, contributing significantly to natural product research and drug development. [ABSTRACT FROM AUTHOR]

Aluminum metal matrix composites (AMMCs) are currently widely engaged in industrial sectors. No other monolithic material can match the characteristics of AMMCs. AMMCs are stronger than traditional materials and have a wide range of industrial uses. This research work aims to study the tribological properties of AA8079/Zirconium boride (ZrB2) composite manufactured via the stir casting (SC) process. The different combinations of composites are AA8079/0wt.% ZrB2, AA8079/5wt.% ZrB2, AA8079/10wt.% ZrB2, and AA8079/15wt.% ZrB2. The parameters are reinforcement wt.% [A], load [B], sliding velocity [C], and sliding distance [D]. When designing experiments using the Taguchi method, an L16 orthogonal array was used. In order to determine which process parameter had the biggest influence on the output variables, wear rate (WR), coefficient of friction (COF), and analysis of variance (ANOVA) were applied. Successful fabrication of different weight fractions of ZrB2 was synthesized with AA8079 matrix through the SC process. The microstructural investigations revealed the dispersion of ZrB2 particles over the surface of the base AA8079. The response table clearly depicts that the combinations of A and C are the more dominant factor for WR, while the combinations of B and C are the more interacting parameters for COF. From the ANOVA results, it is clear that A with a 55.26% contribution, is the most predominant parameter in attaining the least WR, and for COF, B with a 31.39% contribution, is the major influencing parameter. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) serves a vital role in sustaining environmental quality and supporting agroecosystems. The study evaluated the effects of long-term manuring and fertilization on SOC pools in rice-rice cropping system in the lateritic soils of Central Plain, Kerala, India. Soil samples from the long term fertilizer plots were used to determine the SOC pools. Treatments were: 50% recommended dose of nitrogen (N), phosphorus (P), potassium (K) (50% NPK), 100% NPK, 150% NPK, 100% NPK + lime, 100% NP, 100% N, 100% NPK + farm yard manure (FYM) (100% NPK + FYM), 50% NPK + FYM, 100% NPK + Sesbania aculeata (SA), 50% NPK + SA and no fertilizers or manures (control). Integrated nutrient management (INM) treatments improved the Walkley and Black carbon (WBC) content. Water-soluble carbon (WSC) ranged from 0.009 to 0.012%, with the highest value found in INM. KMnO4-oxidizable carbon ranged from 0.092 to 0.158%. The management practices were found to greatly influence microbial biomass carbon (MBC) in the soil with values 195.55 to 298.19 µg g−1 soils. The treatments had a significant effect on fractions of SOC that are strongly connected to aggregate stability namely, total polysaccharides, and glomalin. Application of NPK from 50% to 150% improved WBC, WSC and MBC by 7.69%, 22.22% and 27.90%, respectively. The INM practices also improved the SOC stocks. The carbon management index (CMI) found to be superior in one receiving INM practices than one receiving prescribed levels of nutrition using only mineral fertilizers. [ABSTRACT FROM AUTHOR]

Comprehensive sexuality education (CSE) provides coherent information to promote the well-being of individuals irrespective of age, gender, and qualification. It provides complete knowledge to understand the reproductive system, sexuality, gender, different life skills, sexually transmitted diseases, and contraceptives. This study aims to understand the different modes of delivery, study design, essential topics covered, and implications of different studies in the CSE intervention. The PRISMA 2020 guidelines were used for a systematic literature review. Studies between 2008 and 2023, indexed and cited in Scopus, Web of Science, PubMed, Sage Journal, and Google Scholar were incorporated. It is inferred that the studies in the literature promote age-appropriate CSE intervention to implement in different populations. This systematic literature review on CSE intervention provides a strong foundation for understanding the different implications of sexuality education, the different modes, topics, theoretical framework, and study designs. However, the modules proposed earlier in the literature have not focused on the aforementioned components in CSE. Finally, this review suggests to researchers the necessity and development of an appropriate module to deliver and spread more awareness among the study population in society. LAY SUMMARY: The current review is beneficial in understanding the different topics and methodologies under CSE used in the literature to provide innovative intervention plans for the betterment of society which have not been explored. [ABSTRACT FROM AUTHOR]

Automated analysis of the scientific literature using natural language processing (NLP) can accelerate the identification of potentially unexplored formulations that enable innovations in materials engineering with fewer experimentation and testing cycles. This strategy has been successful for specific classes of inorganic materials, but their general application in broader material domains such as bioplastics remains challenging. To begin addressing this gap, we explore correlations between the ingredients and physicochemical properties of seaweed-based biofilms from a corpus of 2000 article abstracts from the scientific literature since 1958, using a supervised word co-occurrence analysis and an unsupervised approach based on the language model MatBERT without fine-tuning. Using known relations between ingredients and properties for test scenarios, we discuss the potential and limitations of these NLP approaches for identifying novel combinations of polysaccharides, plasticizers, and additives that are related to the functionality of seaweed biofilms. The model demonstrates a valuable predictive ability to identify ingredients associated with increased water vapor permeability, suggesting its potential utility in optimizing formulations for future research. Using the model further revealed alternative combinations that are underrepresented in the literature. This automated method facilitates the mapping of relationships between ingredients and properties, guiding the development of seaweed bioplastic formulations. The unstructured and heterogeneous nature of the literature on bioplastics represents a particular challenge that demands ad hoc fine-tuning strategies for state-of-the-art language models for advancing the field of seaweed bioplastics. [ABSTRACT FROM AUTHOR]

Thyroid dysfunction, comprising conditions such as hyperthyroidism and hypothyroidism, represents a substantial global health challenge, necessitating timely and precise diagnosis for effective therapeutic intervention and patient welfare. Conventional diagnostic modalities often involve invasive procedures, that could cause discomfort and inconvenience for individuals. The non-invasive techniques like diffuse reflectance spectroscopy (DRS) can offer a promising alternative. This study underscores the critical role of preprocessing methods in enhancing the accuracy of thyroid hormone functionality through a non-invasive approach. In the proposed study the spectral data acquired from the DRS setup are subjected to different preprocessing techniques to improve the efficacy of the prediction model. Thirty individuals with thyroid dysfunction were included in the study, and preprocessing methods such as baseline correction, multiplicative scatter correction (MSC), and standard normal variate (SNV), were systematically evaluated. The study highlights that SNV preprocessing outperformed other methods with a root mean square error (RMSE) of 0.005 and an R² of 0.99. In contrast, MSC resulted in an RMSE of 0.87 and an R² of 0.86, while baseline correction showed a RMSE of 0.84 and an unusual R² of 1.09, indicating potential issues. SNV proved to be the most effective technique. [ABSTRACT FROM AUTHOR]

Introduction: Morphology is routinely used for detecting malignant cells in body fluids, but it has limitations. Recently, flow cytometry (FCM) is used as an effective tool for studying non‐haematological malignancies. The main objective of this study is to standardize a simple and rapid FCM test for the detection of malignant epithelial cells in body fluids. Materials and Methods: Body fluids that had been processed for cytology/cytology and FCM were enrolled in this prospective study. We developed a fluorescent‐labelled, monoclonal antibody panel composed of cell surface markers for this FCM assay. We compared the results of cytology/cell block and FCM. Results: A total of 121 fluid samples were studied. Comparing the diagnostic performance of cytology/cell block and FCM, 52 (43%) cases were positive and 60 (49.5%) cases were negative for carcinoma cells by both techniques. Nine cases showed discordant results between the two techniques. Six cases were cytology+ but FCM‐ and three cases were FCM+ cytology‐. Clustered Epithelial Cell Adhesion Molecule (EpCAM)‐positive events with high scatter properties were definitive for positive diagnosis by FCM. We studied PD‐L1 expression in 13 cases by FCM. Six cases were reported as false negative by this FCM assay due to hypocellularity and lack of EpCAM expression in malignant cells. Conclusions: This FCM assay is simple, easier and cost‐effective yielding sensitive results with no inter‐observer variability. FCM would become a valuable tool to complement routine diagnostic cytology and reduces misdiagnosis. [ABSTRACT FROM AUTHOR]

The Australian roadside soil-derived fungus Penicillium shearii CMB-STF067 was prioritized for chemical investigation based on an SDA cultivation extract exhibiting both antibacterial properties and natural products with unprecedented molecular formulae (GNPS). Subsequent miniaturized 24-well plate cultivation profiling (MATRIX) identified red rice as optimal for the production of the target chemistry, with scaled-up cultivation, extraction and fractionation yielding four new xanthone–anthraquinone heterodimers, jugiones A–D (1–4), whose structures were assigned by detailed spectroscopic analysis and biosynthetic considerations. Of note, where 1–2 and 4 were active against the Gram-positive bacteria vancomycin-resistant Enterococcus faecalis (IC50 2.6–3.9 μM) and multiple-drug-resistant clinical isolates of Staphylococcus aureus (IC50 1.8–6.4 μM), and inactive against the Gram-negative bacteria Escherichia coli (IC50 > 30 μM), the closely related analog 3 exhibited no antibacterial properties (IC50 > 30 μM). Furthermore, where 1 was cytotoxic to human carcinoma (IC50 9.0–9.8 μM) and fungal (IC50 4.1 μM) cells, 2 and 4 displayed no such cytotoxicity (IC50 > 30 μM), revealing an informative structure activity relationship (SAR). We also extended the SAR study to other known compounds of this heterodimer class, which showed that the modification of ring G can reduce or eliminate the cytotoxicity while retaining the antibacterial activity.

Heart strokes are a significant global health concern, profoundly affecting the wellbeing of the population. Many research endeavors have focused on developing predictive models for heart strokes using ML and DL techniques. Nevertheless, prior studies have often failed to bridge the gap between complex ML models and their interpretability in clinical contexts, leaving healthcare professionals hesitant to embrace them for critical decision-making. This research introduces a meticulously designed, effective, and easily interpretable approach for heart stroke prediction, empowered by explainable AI techniques. Our contributions include a meticulously designed model, incorporating pivotal techniques such as resampling, data leakage prevention, feature selection, and emphasizing the model’s comprehensibility for healthcare practitioners. This multifaceted approach holds the potential to significantly impact the field of healthcare by offering a reliable and understandable tool for heart stroke prediction. In our research, we harnessed the potential of the Stroke Prediction Dataset, a valuable resource containing 11 distinct attributes. Applying these techniques, including model interpretability measures such as permutation importance and explainability methods like LIME, has achieved impressive results. While permutation importance provides insights into feature importance globally, LIME complements this by offering local and instance-specific explanations. Together, they contribute to a comprehensive understanding of the Artificial Neural Network (ANN) model. The combination of these techniques not only aids in understanding the features that drive overall model performance but also helps in interpreting and validating individual predictions. The ANN model has achieved an outstanding accuracy rate of 95%.

The electrical energy is very necessary to address all household needs and commercial needs. This energy is used all over the world for almost all purposes. It is diminished day by day as fossil fuels are used for energy production. As natural resources are limited and getting exhausted, there is every need to conserve energy. It even involves in rising up pollution and increasing the global temperature by emitting greenhouse gases. It shows severe impact of climate. This paper explains the term energy conservation, methods to conserve energy, use of energy efficient devices and also how energy efficient devices are chosen for various purposes. This paper even focuses on net zero energy buildings and explains a methodology for arranging lights and blind control for windows in net zero buildings to conserve energy.

PurposeTo report our experience with 2 cases of Capnocytophaga keratitis.MethodsThis is a retrospective study of case reports. We present the clinical presentation, diagnosis, and treatment strategies of 2 patients who presented with Capnocytophaga keratitis.ResultsBoth patients had risk factors including systemic immune compromise and ocular trauma. Both patients had robust inflammatory keratitis with necrosis. Case 1 demonstrates identification of Capnocytophaga with traditional microbiologic techniques. Case 2 demonstrates the use of unbiased metagenomic deep sequencing for identification of this unusual corneal pathogen.ConclusionsCapnocytophaga is a rare and aggressive infection. Even when traditional culture identifies the pathogen rapidly, keratitis can progress to perforation. In cases of severe keratitis in which traditional culture methods are unrevealing, metagenomic deep sequencing has potential to provide actionable diagnoses.

PurposeTo report our experience with 2 cases of Capnocytophaga keratitis.MethodsThis is a retrospective study of case reports. We present the clinical presentation, diagnosis, and treatment strategies of 2 patients who presented with Capnocytophaga keratitis.ResultsBoth patients had risk factors including systemic immune compromise and ocular trauma. Both patients had robust inflammatory keratitis with necrosis. Case 1 demonstrates identification of Capnocytophaga with traditional microbiologic techniques. Case 2 demonstrates the use of unbiased metagenomic deep sequencing for identification of this unusual corneal pathogen.ConclusionsCapnocytophaga is a rare and aggressive infection. Even when traditional culture identifies the pathogen rapidly, keratitis can progress to perforation. In cases of severe keratitis in which traditional culture methods are unrevealing, metagenomic deep sequencing has potential to provide actionable diagnoses.

[This corrects the article DOI: 10.1038/s41522-017-0040-3.].

Cassava is one of the most important food and industrial crops in Asia, Africa, and South America. Cassava mosaic disease (CMD), caused by cassava mosaic geminivirus, is one of the major constraints to cassava cultivation. In Asia, the disease is caused by the Indian cassava mosaic virus and Sri Lankan cassava mosaic virus. Phytosanitation, vector control, breeding, and genetic engineering strategies have been widely adopted to manage the disease. This study provides a comprehensive review of the disease spread, the development of diagnostic methods, and various approaches employed for the management of CMD in South and Southeast Asia.

In the past decades, more than fifty different yoga styles have been implemented in the therapeutic context to manage various diseases. Yet, not all of these yoga styles have been validated or standardized as a program. The aim of this article is to review the different methodologies used for yoga module development and to assess their quality. Three databases (PubMed, Web of Science, and Scopus) were searched using the following keywords and Boolean operators: (validation OR development OR design) AND (yoga OR mind-body) AND (module OR protocol OR program). Three thousand six hundred and seventy-one articles were enlisted, and based on the inclusion and exclusion criteria, 37 articles were narrowed down for review. Since no checklist exists to assess the quality of yoga modules, the authors designed a 23-item checklist to categorize each having low, medium, or high quality. As per the yoga module quality checklist, only 21.6% of the studies had high quality, while 75.3% of the articles had medium quality and 8.11% had low quality. A commonly used development method was literature review, while for validation, experts' scoring of the Likert scale was the preferred means. The feasibility of the module was carried out only by half of the studies. Few diseases such as cardiovascular disease, diabetes mellitus, obesity, Parkinson's disease, and obesity had more than one yoga module developed. The findings of this systematic review have shed some light on the growing need for standardized methods of yoga module development. The 23-item checklist can guide researchers in the homogeneous development strategies when designing yoga interventions in the future.

IntroductionThe incidence of Lyme disease (LD) in Canada and the United States has risen over the last decade, nearing 480,000 cases each year. Borrelia burgdorferi sensu lato, the causative agent of LD, is transmitted to humans through the bite of an infected tick, resulting in flu-like symptoms and often a characteristic bull’s-eye rash. In more severe cases, disseminated bacterial infection can cause arthritis, carditis and neurological impairments. Currently, no vaccine is available for the prevention of LD in humans.MethodsIn this study, we developed a lipid nanoparticle (LNP)-encapsulated DNA vaccine encoding outer surface protein C type A (OspC-type A) of B. burgdorferi.ResultsVaccination of C3H/HeN mice with two doses of the candidate vaccine induced significant OspC-type A-specific antibody titres and borreliacidal activity. Analysis of the bacterial burden following needle challenge with B. burgdorferi (OspC-type A) revealed that the candidate vaccine afforded effective protection against homologous infection across a range of susceptible tissues. Notably, vaccinated mice were protected against carditis and lymphadenopathy associated with Lyme borreliosis.DiscussionOverall, the results of this study provide support for the use of a DNA-LNP platform for the development of LD vaccines.

Multiphoton microscopy (MPM) has emerged as a vital tool in neuroscience, enabling deeper imaging with a broader field of view, as well as faster and sub-cellular resolution. Recent innovations in ultrafast fiber laser technology have revolutionized MPM applications in living brains, offering advantages like cost-effectiveness and user-friendliness. In this review, we explore the progress in ultrafast fiber laser technology, focusing on its integration into MPM for neuroscience research. We also examine the utility of femtosecond fiber lasers in fluorescence and label-free two- and three-photon microscopy applications within the field. Furthermore, we delve into future possibilities, including next-generation fiber laser designs, novel laser characteristics, and their potential for achieving high spatial and temporal resolution imaging. We also discuss the integration of fiber lasers with implanted microscopes, opening doors for clinical and fundamental neuroscience investigations.

In recent years, lipid nanoparticles (LNPs) have emerged as a revolutionary technology for vaccine delivery. LNPs serve as an integral component of mRNA vaccines by protecting and transporting the mRNA payload into host cells. Despite their prominence in mRNA vaccines, there remains a notable gap in our understanding of the potential application of LNPs for the delivery of DNA vaccines. In this study, we sought to investigate the suitability of leading LNP formulations for the delivery of plasmid DNA (pDNA). In addition, we aimed to explore key differences in the properties of popular LNP formulations when delivering either mRNA or DNA. To address these questions, we compared three leading LNP formulations encapsulating mRNA- or pDNA-encoding firefly luciferase based on potency, expression kinetics, biodistribution, and immunogenicity. Following intramuscular injection in mice, we determined that RNA-LNPs formulated with either SM-102 or ALC-0315 lipids were the most potent (all p-values < 0.01) and immunogenic (all p-values < 0.05), while DNA-LNPs formulated with SM-102 or ALC-0315 demonstrated the longest duration of signal. Additionally, all LNP formulations were found to induce expression in the liver that was proportional to the signal at the injection site (SM102: r = 0.8787, p < 0.0001; ALC0315: r = 0.9012, p < 0.0001; KC2: r = 0.9343, p < 0.0001). Overall, this study provides important insights into the differences between leading LNP formulations and their applicability to DNA- and RNA-based vaccinations.