77 research outputs found

    рдЬрдирдЬрд╛рддрд┐рдпреЛрдВ рдХреА рдЖрд░реНрдерд┐рдХ рд╕рдорд╕реНрдпрд╛рдВрдР рдФрд░ рд╕рдордХрд╛рд▓реАрди рдЪреБрдиреМрддрд┐рдпрд╛рдВ

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    рднрд╛рд░рдд рджреЗрд╢ рдореЗрдВ рдЧреЛрдВрдб рдФрд░ рдЖрджрд┐рд╡рд╛рд╕реА рд╕рдорд╛рдЬ рдЬрдВрдЧрд▓реЛрдВ рдореЗрдВ рд░рд╣рдХрд░ рдЕрдкрдирд╛ рдЬреАрд╡рди рдпрд╛рдкрди рдХрд░рддреЗ рд╣реИрдВ рдЬрд┐рдирдХреА рдХрдо рд╕реЗ рдХрдо рдЖрдмрд╛рджреА рей рдХрд░реЛрдб рдХреЗ рдКрдкрд░ рд╣реИ | 2006 рдореИрдВ рдЖрджрд┐рд╡рд╛рд╕рд┐рдпреЛрдВ рдХреЛ рдЖрдЬ рдХреЗ рд╣рдХ рджрд┐рд▓рд╛рдиреЗ рдХреЗ рд▓рд┐рдП рдлреЙрд░реЗрд╕реНрдЯ рд▓реЙ рдкрд╛рд╕ рдХрд┐рдпрд╛ рдЧрдпрд╛ | рдЖрдВрдзреНрд░ рдкреНрд░рджреЗрд╢ рдХреА рд░рд╛рдЬрдзрд╛рдиреА рд╣реИрджрд░рд╛рдмрд╛рдж рдореЗрдВ рдЗрд╕рдХреА рд╕рдореАрдХреНрд╖рд╛ рд╣реБрдИ рдереА | рдПрди рдЖрдИ рдЖрд░ рдбреА (NIRD) рдХреИрдВрдкрд╕ рдореЗрдВ рджреЛ рджрд┐рд╡рд╕реАрдп рдЗрд╕ рд╕рд░рдХрд╛рд░реА рд╕рдореАрдХреНрд╖рд╛ рд╕рднрд╛ рдореЗрдВ рдЖрдВрдзреНрд░ рдкреНрд░рджреЗрд╢, рдХрд░реНрдирд╛рдЯрдХ, рддрдорд┐рд▓рдирд╛рдбреБ, рдХреЗрд░рд▓, рдЫрддреНрддреАрд╕рдЧрдврд╝, рджрд┐рд▓реНрд▓реА, рдЙрдбрд╝реАрд╕рд╛ рддрдерд╛ рдорд╣рд╛рд░рд╛рд╖реНрдЯреНрд░ рдХреЗ рдкреНрд░рддрд┐рдирд┐рдзрд┐ рдЙрдкрд╕реНрдерд┐рдд рдереЗ | рдорд╣рд╛рд░рд╛рд╖реНрдЯреНрд░ рд░рд╛рдЬреНрдп рд╕реЗ рдЪрд╛рдВрджрд╛рдЧрдврд╝ (рдЪрдВрджреНрд░рдкреБрд░) рдХреЗ рдЧреЛрдВрдбрд░рд╛рдЬрд╛ рдбреЙ. рдмрд┐рд░рд╢рд╛рд╣рд╛ рдЖрддреНрд░рд╛рдо рдФрд░ рд░рд╛рдЬрдХреБрд╡рд░ рд╡рд┐рдХреНрд░рд╛рдВрддрд╢рд╛рд╣ рдЖрддреНрд░рд╛рдо рдЙрдкрд╕реНрдерд┐рдд рдереЗ| рдЖрджрд┐рд╡рд╛рд╕реА рдЬрдВрдЧрд▓реЛрдВ рдореЗрдВ рд░рд╣рдХрд░ рдЕрдкрдирд╛ рдЧреБрдЬрд░-рдмрд╕рд░ рдХрд░рддреЗ рд╣реИрдВ рдЦреЗрдд рдЦрд▓рд┐рдпрд╛рди рдХрд░рддреЗ рд╣реИрдВ рдЙрдиреНрд╣реЗрдВ рдЙрдирдХреА рдЬрдореАрди рдХреЗ рдкрдЯреНрдЯреЗ рднрд╛рд░рдд рд╕рд░рдХрд╛рд░ рджреНрд╡рд╛рд░рд╛ рджреЗрдиреЗ рдХреЗ рд▓рд┐рдП рдФрд░ рдЙрдирдХрд╛ рдЬрдВрдЧрд▓реЛрдВ рдкрд░ рд╣рдХ рдорд╛рдиреНрдп рдХрд░рдиреЗ рдХреЗ рд▓рд┐рдП 2006 рдХрд╛ рдлреЙрд░реЗрд╕реНрдЯ рд▓реЙ рдкрд░ рдмреИрдардХ рдЪрд▓ рд░рд╣реА рдереА рдФрд░ рдЙрд╕рдореЗрдВ рд╕рдВрд╢реЛрдзрди рдХрд░ рдЖрджрд┐рд╡рд╛рд╕реА рдЧреЛрдВрдб рдХреЗ рдКрдкрд░ рд╣реЛрдиреЗ рд╡рд╛рд▓реЗ рдЕрддреНрдпрд╛рдЪрд╛рд░ рдХреЛ рдЦрддреНрдо рдХрд░рдиреЗ рдХреЗ рд▓рд┐рдП рд╡реНрдпрд╡рд╕реНрдерд╛ рдореЗрдВ рдкрд░рд┐рд╡рд░реНрддрди рд╣реЛ рд░рд╣рд╛ рдерд╛| рдЗрд╕ рдкрд░ рдЕрдиреНрдп рдкреНрд░рд╛рдВрддреЛрдВ рдХреЗ рдЖрджрд┐рд╡рд╛рд╕реА (рд╡рд┐рднрд┐рдиреНрди) рдЖрджрд┐рд╡рд╛рд╕рд┐рдпреЛрдВ рдХреЗ рдореБрдЦрд┐рдпрд╛ рдЙрдкрд╕реНрдерд┐рдд рд░рд╣рдХрд░ рд╕реБрдЭрд╛рд╡ рджреЗ рд░рд╣реЗ рдереЗ рдЖрджрд┐рд╡рд╛рд╕реА рдШрдмрд░рд╛ рдЧрдпреЗ| рдЬреЛ рдЕрдзрд┐рдХрд╛рд░ рдЖрджрд┐рд╡рд╛рд╕реА рдЕрдиреНрдп рдЬрдирдЬрд╛рддрд┐рдпреЛрдВ рдХреЗ рд╕рд╛рде рдЧреЛрдВрдб рд╕рдореБрджрд╛рдп рдХреЛ рдорд┐рд▓рд╛ рдерд╛ рд╡рд╣ рд╕рд░рдХрд╛рд░ рд╕реЗ рдЦрддрд░реЗ рдореЗрдВ рдкрдбрд╝ рдЧрдпрд╛

    Review of Mooshika Visha (Rat Poison) : Ayurvedic Concept

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    Ayurveda is an ancient Indian system of medicine having eight important branches. Agada Tantra is one of them which deals with Visha (poison) its manifestation and its treatment. In Ayurvedic texts Mooshika Visha is described well. There are eighteen types of Mooshika, signs and symptoms of their bite and its treatment is described by Sushrutaacharya and Vaagbhataacharya. There are five modes of spread of Mooshika (rat) poison. Semen, faeces, urine, scratches by nails and bites with teeth of Mooshika are poisonous. In case of Mooshika bite, bite site should be cauterized and blood letting should be done. After this various drugs paste should be applied on bite site. Various putrifictory therapies should be given e.g. Vamana (Vomiting), Virechana (Purgation), Nasya (Nasal medication), anjana (Collyrium) etc. Various drug preparations like medicated ghee, decoctions, paste of drugs, juice of drugs are described. Ayurvedic treatment of Mooshika poisoning can be given in all diseases where source of infection is rat

    Impact of modular mitochondrial epistatic interactions on the evolution of human subpopulations

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    Investigation of human mitochondrial (mt) genome variation has been shown to provide insights to the human history and natural selection. By analyzing 24,167 human mt-genome samples, collected for five continents, we have developed a co-mutation network model to investigate characteristic human evolutionary patterns. The analysis highlighted richer co-mutating regions of the mt-genome, suggesting the presence of epistasis. Specifically, a large portion of COX genes was found to co-mutate in Asian and American populations, whereas, in African, European, and Oceanic populations, there was greater co-mutation bias in hypervariable regions. Interestingly, this study demonstrated hierarchical modularity as a crucial agent for these co-mutation networks. More profoundly, our ancestry-based co-mutation module analyses showed that mutations cluster preferentially in known mitochondrial haplogroups. Contemporary human mt-genome nucleotides most closely resembled the ancestral state, and very few of them were found to be ancestral-variants. Overall, these results demonstrated that subpopulation-based biases may favor mitochondrial gene specific epistasis

    Targeted isolation of antibiofilm compounds from halophytic endophyte Bacillus velezensis 7NPB-3B using LC-HR-MS-based metabolomics

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    The discovery of new natural products has become more challenging because of the re-isolation of compounds and the lack of new sources. Microbes dwelling in extreme conditions of high salinity and temperature are huge prospects for interesting natural metabolites. In this study, the endophytic bacteria Bacillus velezensis 7NPB-3B isolated from the halophyte Salicornia brachiata was screened for its biofilm inhibition against methicillin-resistant Staphylococcus aureus (MRSA). The fractionation of the crude extract was guided by bioassay and LC-HRMS-based metabolomics using multivariate analysis. The 37 fractions obtained by high-throughput chromatography were dereplicated using an in-house MS-Excel macro coupled with the Dictionary of Natural Products database. Successive bioactivity-guided separation yielded one novel compound (1), a diketopiperazine (m/z 469.258 [M тИТ H]тИТ) with an attached saturated decanoic acid chain, and four known compounds (2тАУ5). The compounds were identified based on 1D- and 2D-NMR and mass spectrometry. Compounds 1 and 5 exhibited excellent biofilm inhibition properties of >90% against the MRSA pathogen at minimum inhibition concentrations of 25 and 35 ┬╡g/mL, respectively. The investigation resulted in the isolation of a novel diketopiperazine from a bacterial endophyte of an untapped plant using an omics approach

    Relation of COVID-19 with acute ischemic bowel disease: A retrospective observational study

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    Introduction: COVID-19 is a serious respiratory disease caused by SARS-CoV-2, aside from the respiratory system, the gastrointestinal system is the most common site of SARS-COV-2 infection. The study aimed to assess relation between COVID and ischemic bowel disease by analysing length of hospital stay and mortality rates between COVID and non-COVID groups. Methods: The study was conducted from June 2020 to November 2021 in the surgical wards of Seth GS Medical College and KEM Hospital, Mumbai. Included patients presented to emergency room with acute abdomen which diagnosed as acute ischemic bowel disease during the period of study and then compared the outcomes between COVID and non-COVID groups. Results: Out of 40 patients, 16 had no history of COVID and remaining 24 had either previous history of COVID or diagnosed presently with COVID. In both COVID and non-COVID population, distribution of comorbidities were almost equal exception being stroke, where both the cases had previous history of COVID, diabetes was the most common comorbidity in both the groups followed by hypertension. Patients with active COVID infection had higher mortality of 75% (3 out of 4) followed by patients with past history of infection with mortality rate of 65% (13 out of 20) whereas the mortality rate in non-COVID patients were 37.5% (6 out of 16). Conclusion: Ischemic bowel disease among COVID-19 patients is rare, but its association with high mortality rates and prolonged length of stay necessitates clinical suspicion and prompt intervention

    Chemoenzymatic Synthesis of Glycosylated Macrolactam Analogues of the Macrolide Antibiotic YCтАР17

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    YCтАР17 is a 12тАРmembered ring macrolide antibiotic produced from Streptomyces venezuelae ATCC 15439 and is composed of the polyketide macrolactone 10тАРdeoxymethynolide appended with DтАРdesosamine. In order to develop structurally diverse macrolactam analogues of YCтАР17 with improved therapeutic potential, a combined approach involving chemical synthesis and engineered cellтАРbased biotransformation was employed. Eight new antibacterial macrolactam analogues of YCтАР17 were generated by supplying a novel chemically synthesized macrolactam aglycone to S. venezuelae mutants harboring plasmids capable of synthesizing several unnatural sugars for subsequent glycosylation. Some YCтАР17 macrolactam analogues were active against erythromycinтАРresistant bacterial pathogens and displayed improved metabolic stability in vitro. The enhanced therapeutic potential demonstrated by these glycosylated macrolactam analogues reveals the unique potential of chemoenzymatic synthesis in antibiotic drug discovery and development.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113147/1/adsc_201500250_sm_miscellaneous_information.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/113147/2/2697_ftp.pd

    Utilization of decorticated cottonseed meal with or without protease in diets of broiler chicken

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    The present study was conducted to evaluate the feeding value of decorticated cottonseed meal (DCSM, non- detectable free-gossypol) with or without supplemental protease on the basis of growth performance, nutrient utilization and feed-cost of production in broiler chicken. Accordingly, a six weeks (0 to 6 weeks of age of broiler chickens) feeding trial was conducted following 5 ├Ч 2 factorial design involving five dietary levels (0, 5, 10, 15 and 20%) of DCSM, with (0.035%) or without protease in a standard broiler chicken diet. Day-old chicks (320) were divided into 40 groups of eight birds each (replicate) and each dietary treatment was offered to four replicated groups. There was no significant difference in body weight gain, feed intake and feed conversion ratio, protein and energy utilization efficiency due to levels of decorticated cottonseed meals in diets replacing soybean meal of control diet and protease supplementation. Nitrogen retention was not influenced either by cottonseed meal or by protease in diet. There was no adverse effect on cellular as well as humoral immunity on addition of cottonseed meal in diet. Addition of protease in diet did not improve the above mentioned performance parameters. Feed-cost of production decreased significantly and linearly on addition of cottonseed meal at graded levels. The present study revealed that incorporation of DCSM up to 20% level in diet, either with or without enzyme supplementation, did not affect growth performance of broiler chicken during 0тАУ6 weeks of age. Therefore, decorticated cottonseed meal can safely and effectively be included up to 20% level without enzyme supplementation in maize-soybean based diets of broiler chickens replacing soybean meal for profitable broiler production

    Multiclass classification of Covid-19, Tb, Pneumonia, and health cases using Deep Learning

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    In recent times we have been made aware of the high infection rate and lethality that can be caused by the outbreak of pulmonary diseases like Covid-19. The need for an economical and quick diagnosis of such a disease is also increasing. It is important to consider that a disease like covid has a resemblance to some of the other pulmonary diseases like pneumonia and tuberculosis and has overlapping symptoms and characteristics with them. There have been many previous types of research that have used chest x-rays for the classification of covid and healthy cases or covid and pneumonia or covid and TB using binary classification. This research proposes a deep learning framework for multiclass classification of Covid-19, pneumonia, Tuberculosis, and normal cases with the use of chest X-rays. In this research, I have used a combination of three open datasets available on Kaggle to create my dataset for research which has a total of 4136 images. I have used image data augmentation and applied pre-trained models like VGG16 and DenseNet121. I have also created a CNN from scratch which can perform classification with 91 per cent overall accuracy and high precision and an F1 score which I have discussed further in the report. This investigation can help physicians and patients in early diagnosis and can act as a pre-diagnosis method to start early treatment or isolation of the patient. It can also act as a patient prioritization tool to help physicians focus on people that have a high probability to be infected in case of a high number of patients due to a sudden outbreak
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