Emergence, ecology and dispersal of the pandemic generating Vibrio cholerae lineage

Although cholera is an ancient disease that first arose at least half a millennium ago, it remains a major health threatglobally. Its pandemic form is caused by strains from a single lineage of the bacterium Vibrio cholerae. The ancestor of this lineageharbored several distinctive characteristics, the most notable being the O1 antigen polysaccharide. This lineage generatedtwo biotypes, first Classical, responsible for six pandemics, and later El Tor, responsible for the seventh and ongoing pandemic.Just as El Tor replaced Classical as the main cause of outbreaks in the last fifty years, several variants of El Tor have evolved anddisplaced their predecessors worldwide. Understanding the ecology, evolution and dispersal of pandemic V. cholerae is centralto studying this complex disease with environmental reservoirs. Here, we present recent advancements of our knowledge on theemergence and spread of the pandemic generating lineage of V. cholerae in the light of established eco-evolutionary observations.Specific ecological interactions shape seasonal cholera, playing a role in the abundance and distribution of its causative agent.Both species-specific and lineage-specific genetic determinants play a role in the ability of V. cholerae strains to cause pandemicswith seasonal outbreaks, having evolved gradually over centuries. On the basis of the current understanding, we outline futurethreats and changes in biogeographical and genomic-based investigation strategies to combat this global problem

Improved Solar Photovoltaic Array Model with FLC Based Maximum Power Point Tracking

This paper presents an improved model of solar photovoltaic (PV) array along with the implementation of fuzzy logic as maximum power point tracking (MPPT). The proposed PV array behavioral model is more accurate and with reduced complexity though considered discrete components. The PV array model was well verified by considering the effect of change of environmental conditions, mainly intensity of solar irradiation (insolation) and temperature. The model was tested by feed a single phase inverter. MPPT control the operating voltage of  PV arrays in order to maximize their power output as a result maximize the array efficiency and minimize  the overall system cost. Using a Fuzzy logic based algorithm, the duty cycle of the converter inserted between source and load is adjusted continuously to track the MPP and compared with the conventional perturb and observed (P&O) method for changing environmental conditions. It was found that the Fuzzy logic based method can track the MPP more precisely and rapidly than the conventional one. In P&O method, if step size of input variable is very small, the accuracy in tracking MPP is sufficient but tracking speed becomes too slow. On the other hand if the step size is increased to imitate the rapidly changing weather conditions, accuracy deteriorates and unexpected results occur due to oscillation around a mean point although tracking speed increased. But in the case of proposed FLC whatever the step size of input variable it best suited to track MPP continuously and accurately. The obtained simulation results validate the competent of the solar PV array model as well as the fuzzy controller.DOI:http://dx.doi.org/10.11591/ijece.v2i6.132

Feature selection and prediction of heart disease using machine learning approaches

Heart Disease (HD) is the world's most serious illness that seriously impacts human life. The heart does not push blood to other areas of the body in cardiac disease. For the prevention and treatment of cardiac failure, accurate and timely diagnosis of heart disease is critical. The diagnosis of cardiac disease has been considered via conventional medical history. Non-invasive approaches like machine learning are effective and powerful to categorize healthy people and people with heart disease. In the proposed research, by using the cardiovascular disease dataset, we created a machine-learning model to predict cardiac disease. In this paper, it is capable of recognizing and classifying the heart disease patient from healthy people by using three standard machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). In addition, the Area Under Curve (AUC) value is calculated for each classification algorithms. In the proposed scheme, we also used the feature selection algorithm to reduce dimensions over a qualified heart disease dataset. After that, the whole structure for the classification of heart disease has been created. On complete features and reduced features, the performance of the proposed approach has been verified. The decrease in features affects the accuracy and time of execution of the classifiers. With the selected features, the highest classification accuracy is obtained for the KNN algorithm is about 93%, with a sensitivity is 0.9750 and specificity is 0.8529. Therefore, with the complete features, the classification accuracy is about 91%

Comparison Between Reduced Susceptibility to Disinfectants and Multidrug Resistance Among Hospital Isolates of Pseudomonas aeruginosa and Staphylococcus aureus in Bangladesh

Disinfectants have been used largely in hospitals, health care centers and different pharmaceuticals for the removal of microorganisms. It is evident that microorganisms are showing reduced sensitivity against many disinfectants or their minimum inhibitory concentration (MIC) is increasing day by day due to improper use. The aim of this study was to compare the reduced susceptibility to disinfectants and antibiotics of 25 hospital isolates of Pseudomonas aeruginosa and 40 hospital isolates of Staphylococcus aureus isolated from 5 different hospitals at Noakhali region of Bangladesh. Susceptibility of the selected isolates to two disinfectants (savlon and herpic) and ten separate antimicrobial agents for both P. aeruginosa and S. aureus were investigated and compared. Multidrug resistant pattern of all the hospital isolates were determined by agar diffusion method and MIC of the disinfectants were determined by the serial dilution method. All the hospital isolates of P. aeruginosa and S. aureus were multidrug resistant. No severe evident resistance to disinfectants was seen among the 25 isolates of P. aeruginosa and 40 isolates of S. aureus. Interestingly, satisfactory MIC of savlon for 25 isolates of P. aeruginosa and 40 isolates of S. aureus reached at 0.5% to 0.7% (v/v) solution whereas satisfactory MIC of herpic reached at 2% to 2.5% (v/v) solution for all hospital isolates but four isolates of S. aureus showed MIC against herpic at 1.75% (v/v) solution. No sign of co-resistant of disinfectant and antibiotics were found. So, it can be concluded that disinfectants (savlon and herpic) can’t be responsible for P. aeruginosa and S. aureus to become multidrug resistant, when the semi inhibitory dilution of these disinfectants are used

Evaluation of psychopharmacological and neurosafety profile of Swas Kas Chintamani Ras (SKC) in Swiss-Webster mice

Objectives: Swas Kas Chintamani Ras (SKC) is an ayurvedic preparation indicated for respiratory diseases. Our study was aimed to determine the psychopharmacological and neurosafety profile of SKC. Materials and Methods: Psychopharmacological effects and neurosafety profile of this drug were determined by nine complementary test methods namely, open field, locomotor activity, hole cross, hole board test, elevated plus maze, staircase, forced swimming test, and rotarod test. Male mice (Swiss-Webster strain, 20-40 g body weight) bred in the Animal House of the Department of Pharmacy, Jahangirnagar University, were used for the pharmacological experiments. Results: The drug decreased total ambulation and movement in the central region and standing up behavior and lowered emotional defecation. The drug also made the mice to take a shorter time to come out of the cage. Also, animals spent less time in open arm and the movement in the closed arm and locomotors reduced (p=0.003), where a number of rearing (p=0.04) behaviour indicating possible anxiolytic activity.  Also, no signs of anti-depressant activity were observed among SKC-treated group. Conclusion: We concluded that our drug showed no neurotoxic effect and it also showed some beneficial neuropharmacological properties

Paradigm shift in the management of the Sundarbans mangrove forest of Bangladesh: Issues and challenges

The Sundarbans is the largest continuous mangrove forest of the world, which is rich in both the floral and faunal diversity compared to other mangrove forests of the World. It has long historical records of forest conversion and management. The objectives of this study were to synthesis the management interventions for the Sundarbans and to find out the issues and challenges that encountered the management objectives. The conversion, management, and conservation efforts for the Sundarbans during the last 240 years can be grouped into four distinct time periods based on the outlook of resources use e.g. conversion for agriculture 1780 to 1875; timber production for revenue and control for theft 1876 to 1951; inventory based management 1952 to 1992; integrated management & co-management, and project-based overlapping management 1993-2020. This chronology of outlook was the journey towards the conservation of the Sundarbans ecosystem and also explains the importance of this ecosystem on the national to the regional and global scale. Finally, it was relished that involvement of local people/ community in the management in the form of co-management is now obvious for the protection, conservation, and management of the Sundarbans. However, there are some important issues and challenges that are related to the management of the Sundarbans. The important issues and challenges that are over-exploitation of resources, change in vegetation pattern, poor recruitment of important tree species, habitat degradation, invasive species, poaching and wildlife trafficking, salinity, extreme weather events, uncontrolled tourism, pollution, etc., which are dynamic in nature and need to pay strategic attention to the better protection and management of the Sundarbans ecosystem. It is believed that the findings of this study may contribute to adopting effective management interventions for the other mangrove forests of the world

Simultaneous Quantification of Vibrio metoecus and Vibrio cholerae with Its O1 Serogroup and Toxigenic Subpopulations in Environmental Reservoirs

Vibrio metoecus is a recently described aquatic bacterium and opportunistic pathogen, closely related to and often coexisting with Vibrio cholerae. To study the relative abundance and population dynamics of both species in aquatic environments of cholera-endemic and cholera-free regions, we developed a multiplex qPCR assay allowing simultaneous quantification of total V. metoecus and V. cholerae (including toxigenic and O1 serogroup) cells. The presence of V. metoecus was restricted to samples from regions that are not endemic for cholera, where it was found at 20% of the abundance of V. cholerae. In this environment, non-toxigenic O1 serogroup V. cholerae represents almost one-fifth of the total V. cholerae population. In contrast, toxigenic O1 serogroup V. cholerae was also present in low abundance on the coast of cholera-endemic regions, but sustained in relatively high proportions throughout the year in inland waters. The majority of cells from both Vibrio species were recovered from particles rather than free-living, indicating a potential preference for attached versus planktonic lifestyles. This research further elucidates the population dynamics underpinning V. cholerae and its closest relative in cholera-endemic and non-endemic regions through culture-independent quantification from environmental samples

Simultaneous quantification of vibrio metoecus and vibrio cholerae with its O1 serogroup and toxigenic subpopulations in environmental reservoirs

Vibrio metoecus is a recently described aquatic bacterium and opportunistic pathogen, closely related to and often coexisting with Vibrio cholerae. To study the relative abundance and population dynamics of both species in aquatic environments of cholera-endemic and cholera-free regions, we developed a multiplex qPCR assay allowing simultaneous quantification of total V. metoecus and V. cholerae (including toxigenic and O1 serogroup) cells. The presence of V. metoecus was restricted to samples from regions that are not endemic for cholera, where it was found at 20% of the abundance of V. cholerae. In this environment, non-toxigenic O1 serogroup V. cholerae represents almost one-fifth of the total V. cholerae population. In contrast, toxigenic O1 serogroup V. cholerae was also present in low abundance on the coast of cholera-endemic regions, but sustained in relatively high proportions throughout the year in inland waters. The majority of cells from both Vibrio species were recovered from particles rather than free-living, indicating a potential preference for attached versus planktonic lifestyles. This research further elucidates the population dynamics underpinning V. cholerae and its closest relative in cholera-endemic and non-endemic regions through culture-independent quantification from environmental samples.Published versio

Population Analysis of Vibrio cholerae in Aquatic Reservoirs Reveals a Novel Sister Species (Vibrio paracholerae sp. nov.) with a History of Association with Humans.

10.1128/AEM.00422-21Appl Environ Microbiol8717e0042221

Genomic attributes of Vibrio cholerae O1 responsible for 2022 massive cholera outbreak in Bangladesh.

In 2022, one of its worst cholera outbreaks began in Bangladesh and the icddr,b Dhaka hospital treated more than 1300 patients and ca. 42,000 diarrheal cases from March-1 to April-10, 20221. Here, we present genomic attributes of V. cholerae O1 responsible for the 2022 Dhaka outbreak and 960 7th pandemic El Tor (7PET) strains from 88 countries. Results show strains isolated during the Dhaka outbreak cluster with 7PET wave-3 global clade strains, but comprise subclade BD-1.2, for which the most recent common ancestor appears to be that responsible for recent endemic cholera in India. BD-1.2 strains are present in Bangladesh since 2016, but not establishing dominance over BD-2 lineage strains2 until 2018 and predominantly associated with endemic cholera. In conclusion, the recent shift in lineage and genetic attributes, including serotype switching of BD-1.2 from Ogawa to Inaba, may explain the increasing number of cholera cases in Bangladesh