Wild Fodder Yielding Plants in the Protected Areas of Bangladesh

Wildlife habitat is degrading worldwide due to myriads of biotic and abiotic reasons. The governments across the world countries are trying to halt the degradation through declaring protected areas (PAs) with potential wildlife habitats and strengthening conservation initiatives. These measures are expected to uphold the richness and diversity of the fodder yielding plants. But there is a dire necessity of information on composition and overall status of the fodder yielding plants for continuous monitoring of these habitats. Moreover, the potentiality of the protected areas can also be judged based on the composition and richness of fodder yielding plants. Having all these in mind, we assessed the composition and conservation status of the fodder yielding plants of all habit forms from three recognized protected areas named Chunati Wildlife Sanctuary, Dudhpukuria-Dhopachari Wildlife Sanctuary, and Madhupur National Park. The study indicated the presence of 306 fodder yielding plant species of all habit forms in the three studied protected areas. This chapter describes the composition, status, habit forms, and nature of occurrences of the wild fodder yielding plants which is expected to be highly helpful in wildlife habitat monitoring and undertaking specific measures for multiplication and conservation of fodder yielding plants

ANTIBIOTIC RESISTANCE AND CHROMIUM REDUCTION PATTERN AMONG ACTINOMYCETES

ABSTRACT Actinomycetes, one of the most important groups of microbes, exhibit many interesting activities such as degradation and transformation of organic and metal substrates together with production of antibiotics. With these bioactivities, actinomycetes would play an important role in the webs of the marine environment. The present study was designed to evaluate the antibiotic resistance pattern, antibiotic producing potential and chromium resistance as well as chromium reduction potential of a range of actinomycetes isolated from marine environments. Actinomycetes were isolated from marine sediment samples obtained from St. Martin's Island in Bangladesh. Antibiotic resistance among the selected isolates was studied against 10 different antibiotics by disc diffusion method and antibiotic producing potential was assessed by the perpendicular streak method. The isolates were screened for resistance towards heavy metal Cr(VI) on culture plates supplemented with Cr(VI) at concentrations ranging from 1-5 mM of Cr(VI). Highly resistant isolates were subjected to screening for Cr(VI) reduction activity, which was estimated using the Cr(VI) specific colorimetric reagent 1, 5-diphenylcarbazide. Out of the total 30 different selected isolates, 25 (83.33%) showed resistance against more than three antibiotics and 6 (20%) showed resistance to more than six antibiotics. Ninety three percent of the isolates showed MAR index greater than 0.2 and tolerance to Cr(VI) at 1mM of initial Cr(VI). None of the isolates displayed antimicrobial activity against the organisms tested. Among the isolates tested for chromate reduction, two were most efficient showing complete reduction of 1mM Cr(VI) within 24 h. These two isolates were capable of reducing chromate even at high initial Cr(VI) concentrations. Remarkably, the isolate SM-11 was found to reduce 82.67%, 44.34% of Cr(VI) at 2.5mM, 5mM of initial Cr(VI) concentrations respectively, within 72h of incubation. The majority of the actinomycetes isolates displayed resistance to both antibiotics and heavy metal chromium which indicates the possible acquisition of resistance factors due to environmental or human activities. The study also demonstrates possible correlation between antibiotic resistance and metal tolerance. Two of the isolates which showed considerable chromium reduction activity even at high chromium concentrations, may find potential application in bioremediation approaches

MRIAD: A Pre-clinical Prevalence Study on Alzheimer's Disease Prediction Through Machine Learning Classifiers

Alzheimer’s disease (AD) is a neurological illness that worsens with time. The aged population has expanded in recent years, as has the prevalence of geriatric illnesses. There is no cure, but early detection and proper treatment allow sufferers to live normal lives. Furthermore, people with this disease’s immune systems steadily degenerate, resulting in a wide range of severe disorders. Neuroimaging Data from magnetic resonance imaging (MRI) is utilized to identify and detect the disease as early as possible. The data is derived from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) collection of 266 people with 177 structural brain MRI imaging, DTI, and PET data for intermediate disease diagnosis. When neuropsychological and cognitive data are integrated, the study found that ML can aid in the identification of preclinical Alzheimer’s disease. Our primary objective is to develop a model that is reliable, simple, and rapid for diagnosing preclinical Alzheimer’s disease. According to our findings (MRIAD), the Logistic Regression (LR) model has the best accuracy and classification prediction of about 98%. The ML model is also developed in the paper. This article profoundly, describes the possibility to getting into Alzheimer’s disease (AD) information from the pre-clinical or non-preclinical trial datasets using Machine Learning Classifier (ML) approaches.</p

Epidemiology and outcomes of hospital-acquired bloodstream infections in intensive care unit patients: the EUROBACT-2 international cohort study

Purpose In the critically ill, hospital-acquired bloodstream infections (HA-BSI) are associated with significant mortality. Granular data are required for optimizing management, and developing guidelines and clinical trials. Methods We carried out a prospective international cohort study of adult patients (≥ 18 years of age) with HA-BSI treated in intensive care units (ICUs) between June 2019 and February 2021. Results 2600 patients from 333 ICUs in 52 countries were included. 78% HA-BSI were ICU-acquired. Median Sequential Organ Failure Assessment (SOFA) score was 8 [IQR 5; 11] at HA-BSI diagnosis. Most frequent sources of infection included pneumonia (26.7%) and intravascular catheters (26.4%). Most frequent pathogens were Gram-negative bacteria (59.0%), predominantly Klebsiella spp. (27.9%), Acinetobacter spp. (20.3%), Escherichia coli (15.8%), and Pseudomonas spp. (14.3%). Carbapenem resistance was present in 37.8%, 84.6%, 7.4%, and 33.2%, respectively. Difficult-to-treat resistance (DTR) was present in 23.5% and pan-drug resistance in 1.5%. Antimicrobial therapy was deemed adequate within 24 h for 51.5%. Antimicrobial resistance was associated with longer delays to adequate antimicrobial therapy. Source control was needed in 52.5% but not achieved in 18.2%. Mortality was 37.1%, and only 16.1% had been discharged alive from hospital by day-28. Conclusions HA-BSI was frequently caused by Gram-negative, carbapenem-resistant and DTR pathogens. Antimicrobial resistance led to delays in adequate antimicrobial therapy. Mortality was high, and at day-28 only a minority of the patients were discharged alive from the hospital. Prevention of antimicrobial resistance and focusing on adequate antimicrobial therapy and source control are important to optimize patient management and outcomes