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In this research paper we are reporting how experiments on Rectifier are performed using the concept of virtual Intelligent SoftLab (VIS). Rectification is the conversion of alternating current (AC) to direct current (DC). This model explains you with the fundamentals of AC (alternating current) and DC (direct current) voltages using VIS model. The process of converting bi-directional AC Voltage into unidirectional DC is show graphically. Software for conducting the experimentations in Rectifier has been developed which helps students to perform and practice the experiments. A Rectifier experiments provides a pictorial method of design and evaluating experiments. A Rectifier constructed using the Virtual SoftLab and observed actual outputs. This will help students in understanding working of rectifiers. This model performs half wave and full wave rectification successfully. [ABSTRACT FROM AUTHOR]

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Abstract: Influence of fermentation pH and substrate composition (composite chemical wastewater as primary carbon source) on molecular production was studied in batch experiments using sequentially pretreated [heat-shock (; 2h) and acid (pH 3; 24h)] anaerobic mixed consortia as inoculum. Sequentially coupled repeated pretreatments showed positive influence on the overall generation. Effective production was evidenced at fermentation pH 6 ) compared to 5 () and 7 (). Fermentation pH of 6.0 was found to be optimum for effective generation with the pretreated inoculum. The feed consisting of only glucose as primary substrate showed low yield, while feed with chemical wastewater admixed either with glucose or sewage wastewater as co-substrates demonstrated high yield. Addition of co-substrate (glucose or sewage wastewater) along with chemical wastewater showed enhanced yield. Glucose concentration exceeding 2g/l resulted in reduced yield. Higher VFA concentrations were recorded in experiments carried out at fermentation pH 5 than 7. At fermentation pH 6 VFA composition showed the presence of acetate, butyrate, and propionate with relatively lower concentration of ethanol. Acid-forming pathway with acetic acid as a major metabolite dominated the metabolic flow during the production. [Copyright &y& Elsevier]

Biological decolourisation of two azo dye effluents (direct and reactive dye) were investigated using a commonly available green algae Spirogyra sp. in viable form. Batch studies revealed the potential of algal species in removing the dye colour and dye removal was dependant on initial algal inoculum, concentration and application class of the dye. Maximum dye uptake was noticed on the third day for both the dyes. Higher dye uptake was observed in the case of direct red 28 compared to reactive red 2. Dye colour removal by the algal species may be attributed to biosorption of the dye molecules onto the surface of algal cell and subsequent diffusion and participation in metabolism (bioconversion). The remaining dye molecules could be further removed from the aqueous phase by adsorption and/or chelation reaction of the exopolymers released by the algae (biocoagulation). The results of the present study reveal the potential nature of algae in treating azo dyes which in turn can be extended to oxidation pond system of wastewater treatment. [ABSTRACT FROM AUTHOR]

Background/aim: Helicobacter pylori (H. pylori) colonization affects the gastric microbiome, causing gastrointestinal (GI) diseases. Modern sequencing technology provides insights into GI microbe interaction with H. pylori and their metabolic pathways in causing GI diseases. We aim to compare the gastric microbiota alteration due to H. pylori infection in patients suffering from GI diseases., Materials and Methods: Genomic DNA were isolated from gastric antrum tissue from 37 H.pylori-infected patients diagnosed with GERD, duodenal ulcers, and gastritis. We conducted the genomic library preparation and sequencing of the amplified product using 16S rRNA NGS analysis. Using microbiome analyst tool diversity analysis, random forest analysis and ANOVA were conducted to find out the comparison of microbial abundance. We have also conducted functional pathway prediction analysis using PICRUSt., Results: Metagenomic analysis shows high bacterial diversity in H. pylori-positive gastritis patients. Streptococcus infantis and Neisseria subflava were significantly higher in duodenal ulcer (DU) and gastritis groups. Acinetobacter lwoffii and Helicobacter pullorum were significantly high in the gastritis group only. The functional metabolic pathway analyses revealed that gastroesophageal reflux disease (GERD) samples were significantly enriched with the energy metabolism and xenobiotic biodegradation and metabolism pathways, whereas fructose-1,6-bisphosphatase III was found less in gastritis and DU groups., Conclusion: There is a difference in microbiota composition in different disease outcomes. We found positive association between microbial diversity and H. pylori in gastritis group only, whereas negative association was found in DU and GERD groups. The functional metabolic pathway analysis revealed significant differences in various disease outcomes., (Copyright © 2024 Copyright: © 2024 Indian Journal of Pathology and Microbiology.)

Background: The emergence of coronavirus disease (COVID-19) as a global pandemic has resulted in the loss of many lives and a significant decline in global economic losses. Thus, for a large country like India, there is a need to comprehend the dynamics of COVID-19 in a clustered way., Objective: To evaluate the clinical characteristics of patients with COVID-19 according to age, gender, and preexisting comorbidity. Patients with COVID-19 were categorized according to comorbidity, and the data over a 2-year period (1 January 2020 to 31 January 2022) were considered to analyze the impact of comorbidity on severe COVID-19 outcomes., Methods: For different age/gender groups, the distribution of COVID-19 positive, hospitalized, and mortality cases was estimated. The impact of comorbidity was assessed by computing incidence rate (IR), odds ratio (OR), and proportion analysis., Results: The results indicated that COVID-19 caused an exponential growth in mortality. In patients over the age of 50, the mortality rate was found to be very high, ~80%. Moreover, based on the estimation of OR, it can be inferred that age and various preexisting comorbidities were found to be predictors of severe COVID-19 outcomes. The strongest risk factors for COVID-19 mortality were preexisting comorbidities like diabetes (OR: 2.39; 95% confidence interval (CI): 2.31-2.47; p < 0.0001), hypertension (OR: 2.31; 95% CI: 2.23-2.39; p < 0.0001), and heart disease (OR: 2.19; 95% CI: 2.08-2.30; p < 0.0001). The proportion of fatal cases among patients positive for COVID-19 increased with the number of comorbidities., Conclusion: This study concluded that elderly patients with preexisting comorbidities were at an increased risk of COVID-19 mortality. Patients in the elderly age group with underlying medical conditions are recommended for preventive medical care or medical resources and vaccination against COVID-19., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Singh, Bhaskar, Verma, Rana, Goel, Kumar, Gouda and Singh.)

During long ocean voyages, crew members are subject to complex pressures from their living and working environment, which lead to chronic diseases-like sub-optimal health status. Although the association between dysbiotic gut microbiome and chronic diseases has been broadly reported, the correlation between the sub-optimal health status and gut microbiome remains elusive. Here, the health status of 77 crew members (20-35 years old Chinese, male) during a 135-day sea expedition was evaluated using the shotgun metagenomics of stool samples and health questionnaires taken before and after the voyage. We found five core symptoms (e.g., abnormal defecation frequency, insomnia, poor sleep quality, nausea, and overeating) in 55 out of 77 crew members suffering from sub-optimal health status, and this was termed "seafaring syndrome" (SS) in this study. Significant correlation was found between the gut microbiome and SS rather than any single symptom. For example, SS was proven to be associated with individual perturbation in the gut microbiome, and the microbial dynamics between SS and non-SS samples were different during the voyage. Moreover, the microbial signature for SS was identified using the variation of 19 bacterial species and 26 gene families. Furthermore, using a Random Forest model, SS was predicted with high accuracy (84.4%, area under the concentration-time curve = 0.91) based on 28 biomarkers from pre-voyage samples, and the prediction model was further validated by another 30-day voyage cohort (accuracy = 83.3%). The findings in this study provide insights to help us discover potential predictors or even therapeutic targets for dysbiosis-related diseases. IMPORTANCE Systemic and chronic diseases are important health problems today and have been proven to be strongly associated with dysbiotic gut microbiome. Studying the association between the gut microbiome and sub-optimal health status of humans in extreme environments (such as ocean voyages) will give us a better understanding of the interactions between observable health signs and a stable versus dysbiotic gut microbiome states. In this paper, we illustrated that ocean voyages could trigger different symptoms for different crew member cohorts due to individual differences; however, the co-occurrence of high prevalence symptoms indicated widespread perturbation of the gut microbiome. By investigating the microbial signature and gut microbiome dynamics, we demonstrated that such sub-optimal health status can be predicted even before the voyage. We termed this phenomenon as "seafaring syndrome." This study not only provides the potential strategy for health management in extreme environments but also can assist the prediction of other dysbiosis-related diseases.

Microalgae are among the most genetically and metabolically diverse organisms on earth, yet their identification and metabolic profiling have generally been slow and tedious. Here, we established a reference ramanome database consisting of single-cell Raman spectra (SCRS) from >9000 cells of 27 phylogenetically diverse microalgal species, each under stationary and exponential states. When combined, prequenching ("pigment spectrum" (PS)) and postquenching ("whole spectrum" (WS)) signals can classify species and states with 97% accuracy via ensemble machine learning. Moreover, the biosynthetic profile of Raman-sensitive metabolites was unveiled at single cells, and their interconversion was detected via intra-ramanome correlation analysis. Furthermore, not-yet-cultured cells from the environment were functionally characterized via PS and WS and then phylogenetically identified by Raman-activated sorting and sequencing. This PS-WS combined approach for rapidly identifying and metabolically profiling single cells, either cultured or uncultured, greatly accelerates the mining of microalgae and their products.

In selective RNA processing and stabilization (SRPS) operons, stem-loops (SLs) located at the 3'-UTR region of selected genes can control the stability of the corresponding transcripts and determine the stoichiometry of the operon. Here, for such operons, we developed a computational approach named SLOFE (stem-loop free energy) that identifies the SRPS operons and predicts their transcript- and protein-level stoichiometry at the whole-genome scale using only the genome sequence via the minimum free energy (Δ G ) of specific SLs in the intergenic regions within operons. As validated by the experimental approach of differential RNA-Seq, SLOFE identifies genome-wide SRPS operons in Clostridium cellulolyticum with 80% accuracy and reveals that the SRPS mechanism contributes to diverse cellular activities. Moreover, in the identified SRPS operons, SLOFE predicts the transcript- and protein-level stoichiometry, including those encoding cellulosome complexes, ATP synthases, ABC transporter family proteins, and ribosomal proteins. Its accuracy exceeds those of existing in silico approaches in C. cellulolyticum , Clostridium acetobutylicum , Clostridium thermocellum , and Bacillus subtilis . The ability to identify genome-wide SRPS operons and predict their stoichiometry via DNA sequence in silico should facilitate studying the function and evolution of SRPS operons in bacteria., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Bhaskar, Su, Xu and Xu.)

Deep brain stimulation (DBS) is a widely used treatment for neurodegenerative disorders like Parkinson's disease. Recently, several studies have used preclinical animal models to suggest that DBS has a potential to improve emotional symptoms in mental disorders such as treatment-resistant depression and post-traumatic stress disorder. An important difference between neurodegenerative and emotional disorders is the crucial role of environment in the ontogeny of the latter. Thus, it is important to understand the effects of DBS in the context of environmental variation. In this study, we show that DBS of ventromedial prefrontal cortex reduces anxiety in rats when it is coupled with simultaneous exposure to an enriched environment (EE). In contrast, effects of DBS on anxiety-like behaviors remained equivocal when animals were housed in standard laboratory conditions. These results suggest that the ability of DBS to treat anxiety and related phenotypes can be significantly enhanced by EE opportunities.

Cardiovascular disease is emerging as the leading cause of death in the Caribbean region with hypertension along with diabetes mellitus representing the major causes. Left ventricular hypertrophy associated with hypertension results in a two to fourfold increase in cardiac morbidity and mortality. One hundred and eleven patients, 67% female, mean age 46 years with a mean of seven years since diagnosis, had resting blood pressure, electrocardiogram and sector-focused M-mode echocardiogram performed The electrocardiograms were analyzed for left ventricular hypertrophy using Sokolow-Lyon, Cornell, Romhilts-Estes, 12 lead sum, QRS duration, 12 lead-QRS product and left ventricular strain pattern. The echocardiograms were analyzed for increased left ventricular mass using the formula of Devereux and Reichek indexed to height. The mean systolic blood pressure was 156 mmHg, mean diastolic blood pressure was 97 mmHg on treatment. At least one electrocardiographic criterion for left ventricular hypertrophy was seen in 47/111 (42%) patients and increased left ventricular mass index was seen in 55/111 (50%) patients. Sensitivity, specificity and positive predictive value of the electrocardiogram in predicting increased left ventricular mass index was best for Sokolow-Lyon (31%, 86%, 76%), Cornell (23%, 96%, 88%) and 12 lead-QRS product (30%, 86%, 72%). Sensitivity ranged from 3 to 31%, specificity from 80 to 96% and positive predictive value from 40 to 88%. The electrocardiogram is insensitive in detecting increased echocardiographic left ventricular mass index, as in patients from developed countries, and is less specific for the finding as in African Americans.

The feasibility of laccase production by immobilization of Pleurotus ostreatus 1804 on polyurethane foam (PUF) cubes with respect to media composition was studied in both batch and reactor systems. Enhanced laccase yield was evidenced due to immobilization. A relatively high maximum laccase activity of 312.6 U was observed with immobilized mycelia in shake flasks compared to the maximum laccase activity of free mycelia (272.2 U). It is evident from this study that the culture conditions studied, i.e. biomass level, pH, substrate concentration, yeast extract concentration, Cu2+ concentration, and alcohol nature, showed significant influence on the laccase yield. Gel electrophoretic analysis showed the molecular weight of the laccase produced by immobilized P. ostreatus to be 66 kDa. The laccase yield was significantly higher and more rapid in the packed bed reactor than in the shake flask experiments. A maximum laccase yield of 392.9 U was observed within 144 h of the fermentation period with complete glucose depletion.