Characterization of Mycobacterium orygis, Mycobacterium bovis, and Mycobacterium caprae Infections in Humans in Western Canada.

Epidemiologic research on zoonotic tuberculosis historically used Mycobacterium bovis as a surrogate measure, however, increased reports of human tuberculosis caused by other animal-associated Mycobacterium tuberculosis complex members like Mycobacterium orygis necessitates their inclusion. We performed a retrospective cohort study including persons infected with any animal-lineage M. tuberculosis complex species in Alberta, Canada, from January 1995 to July 2021, identifying 42 patients (20 M. bovis, 21 M. orygis, one M. caprae). Demographic, epidemiologic and clinical characteristics were compared against persons with culture-confirmed M. tuberculosis infection. The proportion of culture-positive infections caused by M. orygis increased continuously from 2016-2020. Significantly more females at a higher median age were impacted by M. orygis, with all patients originating from South Asia. M. bovis caused significantly more extra-pulmonary disease, and disproportionately impacted young females, particularly those pregnant or post-partum. All infections were acquired abroad. These findings can aid in developing targeted public health interventions.

Differential patterns of reproductive and lifestyle risk factors for breast cancer according to birth cohorts among women in China, Japan and Korea.

BACKGROUND: The birth cohort effect has been suggested to influence the rate of breast cancer incidence and the trends of associated reproductive and lifestyle factors. We conducted a cohort study to determine whether a differential pattern of associations exists between certain factors and breast cancer risk based on birth cohorts. METHODS: This was a cohort study using pooled data from 12 cohort studies. We analysed associations between reproductive (menarche age, menopause age, parity and age at first delivery) and lifestyle (smoking and alcohol consumption) factors and breast cancer risk. We obtained hazard ratios (HRs) with 95% confidence intervals (CIs) using the Cox proportional hazard regression analysis on the 1920s, 1930s, 1940s and 1950s birth cohorts. RESULTS: Parity was found to lower the risk of breast cancer in the older but not in the younger birth cohort, whereas lifestyle factors showed associations with breast cancer risk only among the participants born in the 1950s. In the younger birth cohort group, the effect size was lower for parous women compared to the other cohort groups (HR [95% CI] 0.86 [0.66-1.13] compared to 0.60 [0.49-0.73], 0.46 [0.38-0.56] and 0.62 [0.51-0.77]). Meanwhile, a higher effect size was found for smoking (1.45 [1.14-1.84] compared to 1.25 [0.99-1.58], 1.06 [0.85-1.32] and 0.86 [0.69-1.08]) and alcohol consumption (1.22 [1.01-1.48] compared to 1.10 [0.90-1.33], 1.15 [0.96-1.38], and 1.07 [0.91-1.26]). CONCLUSION: We observed different associations of parity, smoking and alcohol consumption with breast cancer risk across various birth cohorts.

Association between reproductive factors with lung cancer incidence and mortality: A pooled analysis of over 308,000 females in the Asia cohort consortium.

Previous studies have investigated the association between reproductive factors and lung cancer risk; however, findings have been inconsistent. In order to assess this association among Asian women, a total of 308,949 female participants from 11 prospective cohorts and four Asian countries (Japan, Korea, China, and Singapore) were included. Cox proportional hazards regression models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CIs). A total of 3,119 primary lung cancer cases and 2247 lung cancer deaths were identified with a mean follow-up of 16.4 years. Parous women had a lower risk of lung cancer incidence and mortality as compared with nulliparous women, with HRs of 0.82 (95% CI = 0.70-0.96) and 0.78 (95% CI = 0.65-0.94). The protective association of parity and lung cancer incidence was greater among ever-smokers (HR = 0.66, 95% CI = 0.49-0.87) than in never-smokers (HR = 0.90, 95% CI = 0.74-1.09) (P-interaction = 0.029). Compared with age at first delivery ≤20 years, older age at first delivery (21-25, ≥26 years) was associated with a lower risk of lung cancer incidence and mortality. Women who ever used hormone replacements had a higher likelihood of developing non-small cell lung cancer (HR = 1.31, 95% CI = 1.02-1.68), compared to those who never used hormone replacements. Future studies are needed to assess the underlying mechanisms, the relationships within these female reproductive factors, and the potential changes in smoking habits over time.

Association of female reproductive and hormonal factors with gallbladder cancer risk in Asia: A pooled analysis of the Asia Cohort Consortium.

The female predominance of gallbladder cancer (GBC) has led to a hypothesis regarding the hormone-related aetiology of GBC. We aimed to investigate the association between female reproductive factors and GBC risk, considering birth cohorts of Asian women. We conducted a pooled analysis of 331,323 women from 12 cohorts across 4 countries (China, Japan, Korea, and Singapore) in the Asia Cohort Consortium. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) to assess the association between reproductive factors (age at menarche, parity, age at first delivery, breastfeeding, and age at menopause) and GBC risk. We observed that a later age at menarche was associated with an increased risk of GBC (HR 1.4, 95% CI 1.16-1.70 for 17 years and older vs. 13-14 years), especially among the cohort born in 1940 and later (HR 2.5, 95% CI 1.50-4.35). Among the cohort born before 1940, women with a later age at first delivery showed an increased risk of GBC (HR 1.56, 95% CI 1.08-2.24 for 31 years of age and older vs. 20 years of age and younger). Other reproductive factors did not show a clear association with GBC risk. Later ages at menarche and at first delivery were associated with a higher risk of GBC, and these associations varied by birth cohort.

Obesity is associated with biliary tract cancer mortality and incidence: A pooled analysis of 21 cohort studies in the Asia Cohort Consortium.

Body fatness is considered a probable risk factor for biliary tract cancer (BTC), whereas cholelithiasis is an established factor. Nevertheless, although obesity is an established risk factor for cholelithiasis, previous studies of the association of body mass index (BMI) and BTC did not take the effect of cholelithiasis fully into account. To better understand the effect of BMI on BTC, we conducted a pooled analysis using population-based cohort studies in Asians. In total, 905 530 subjects from 21 cohort studies participating in the Asia Cohort Consortium were included. BMI was categorized into four groups: underweight (<18.5 kg/m2 ); normal (18.5-22.9 kg/m2 ); overweight (23-24.9 kg/m2 ); and obese (25+ kg/m2 ). The association between BMI and BTC incidence and mortality was assessed using hazard ratios (HR) and 95% confidence intervals (CIs) by Cox regression models with shared frailty. Mediation analysis was used to decompose the association into a direct and an indirect (mediated) effect. Compared to normal BMI, high BMI was associated with BTC mortality (HR 1.19 [CI 1.02-1.38] for males, HR 1.30 [1.14-1.49] for females). Cholelithiasis had significant interaction with BMI on BTC risk. BMI was associated with BTC risk directly and through cholelithiasis in females, whereas the association was unclear in males. When cholelithiasis was present, BMI was not associated with BTC death in either males or females. BMI was associated with BTC death among females without cholelithiasis. This study suggests BMI is associated with BTC mortality in Asians. Cholelithiasis appears to contribute to the association; and moreover, obesity appears to increase BTC risk without cholelithiasis.

Identification of natural antimicrobial peptides mimetic to inhibit Ca2+ influx DDX3X activity for blocking dengue viral infectivity.

Viruses are microscopic biological entities that can quickly invade and multiply in a living organism. Each year, over 36,000 people die and nearly 400 million are infected with the dengue virus (DENV). Despite dengue being an endemic disease, no targeted and effective antiviral peptide resource is available against the dengue species. Antiviral peptides (AVPs) have shown tremendous ability to fight against different viruses. Accelerating antiviral drug discovery is crucial, particularly for RNA viruses. DDX3X, a vital cell component, supports viral translation and interacts with TRPV4, regulating viral RNA metabolism and infectivity. Its diverse signaling pathway makes it a potential therapeutic target. Our study focuses on inhibiting viral RNA translation by blocking the activity of the target gene and the TRPV4-mediated Ca2+ cation channel. Six major proteins from camel milk were first extracted and split with the enzyme pepsin. The antiviral properties were then analyzed using online bioinformatics programs, including AVPpred, Meta-iAVP, AMPfun, and ENNAVIA. The stability of the complex was assessed using MD simulation, MM/GBSA, and principal component analysis. Cytotoxicity evaluations were conducted using COPid and ToxinPred. The top ten AVPs, determined by optimal scores, were selected and saved for docking studies with the GalaxyPepDock tools. Bioinformatics analyses revealed that the peptides had very short hydrogen bond distances (1.8 to 3.6 Å) near the active site of the target protein. Approximately 76% of the peptide residues were 5-11 amino acids long. Additionally, the identified peptide candidates exhibited desirable properties for potential therapeutic agents, including a net positive charge, moderate toxicity, hydrophilicity, and selectivity. In conclusion, this computational study provides promising insights for discovering peptide-based therapeutic agents against DENV.

Unveiling the biofloc culture potential: Harnessing immune functions for resilience of shrimp and resistance against AHPND -causing Vibrio parahaemolyticus infection.

In shrimp aquaculture, disease mitigation may be accomplished by reducing the virulence of the pathogen or by boosting the shrimp's immunity. Biofloc technology is an innovative system that improves the health and resistance of shrimp to microbial infections while providing a viable option for maintaining the quality of culture water through efficient nutrient recycling. This review aimed at demonstrating the efficacy of the biofloc system in boosting the immune responses and protective processes of shrimp against Vibrio parahaemolyticus infection, which is known to cause Acute Hepatopancreatic Necrosis Disease (AHPND). Numerous studies have revealed that the biofloc system promotes the immunological capability of shrimp by raising multiple immune -related genes e.g. prophenoloxidase, serine proteinase gene, ras-related nuclear gene and penaeidinexpression and cellular and humoral responses such as hyperaemia, prophenoloxidase activity, superoxide dismutase activity, phagocytic activity; the protection and survival of shrimp when faced with a challenge from the V. parahaemolyticus strain have been enhanced. Furthermore, the use of the biofloc system improves water quality parameters and potentially bolstering their immune and overall health to effectively resist diseases; hence, promotes the growth of shrimp. The present review suggests that biofloc can serve as an effective therapy for both preventing and supporting the management of probable AHPND infection in shrimp culture. This approach exhibits potential for the progress of sustainable shrimp farming, higher productivity, and improved shrimp health.

Family history and gastric cancer incidence and mortality in Asia: a pooled analysis of more than half a million participants.

BACKGROUND: The family history of gastric cancer holds important implications for cancer surveillance and prevention, yet existing evidence predominantly comes from case-control studies. We aimed to investigate the association between family history of gastric cancer and gastric cancer risk overall and by various subtypes in Asians in a prospective study. METHODS: We included 12 prospective cohorts with 550,508 participants in the Asia Cohort Consortium. Cox proportional hazard regression was used to estimate study-specific adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between family history of gastric cancer and gastric cancer incidence and mortality, then pooled using random-effects meta-analyses. Stratified analyses were performed for the anatomical subsites and histological subtypes. RESULTS: During the mean follow-up of 15.6 years, 2258 incident gastric cancers and 5194 gastric cancer deaths occurred. The risk of incident gastric cancer was higher in individuals with a family history of gastric cancer (HR 1.44, 95% CI 1.32-1.58), similarly in males (1.44, 1.31-1.59) and females (1.45, 1.23-1.70). Family history of gastric cancer was associated with both cardia (HR 1.26, 95% CI 1.00-1.60) and non-cardia subsites (1.49, 1.35-1.65), and with intestinal- (1.48, 1.30-1.70) and diffuse-type (1.59, 1.35-1.87) gastric cancer incidence. Positive associations were also found for gastric cancer mortality (HR 1.30, 95% CI 1.19-1.41). CONCLUSIONS: In this largest prospective study to date on family history and gastric cancer, a familial background of gastric cancer increased the risk of gastric cancer in the Asian population. Targeted education, screening, and intervention in these high-risk groups may reduce the burden of gastric cancer.

Enhanced Robot Motion Block of A-Star Algorithm for Robotic Path Planning.

An optimized robot path-planning algorithm is required for various aspects of robot movements in applications. The efficacy of the robot path-planning model is vulnerable to the number of search nodes, path cost, and time complexity. The conventional A-star (A*) algorithm outperforms other grid-based algorithms because of its heuristic approach. However, the performance of the conventional A* algorithm is suboptimal for the time, space, and number of search nodes, depending on the robot motion block (RMB). To address these challenges, this paper proposes an optimal RMB with an adaptive cost function to improve performance. The proposed adaptive cost function keeps track of the goal node and adaptively calculates the movement costs for quickly arriving at the goal node. Incorporating the adaptive cost function with a selected optimal RMB significantly reduces the searches of less impactful and redundant nodes, which improves the performance of the A* algorithm in terms of the number of search nodes and time complexity. To validate the performance and robustness of the proposed model, an extensive experiment was conducted. In the experiment, an open-source dataset featuring various types of grid maps was customized to incorporate the multiple map sizes and sets of source-to-destination nodes. According to the experiments, the proposed method demonstrated a remarkable improvement of 93.98% in the number of search nodes and 98.94% in time complexity compared to the conventional A* algorithm. The proposed model outperforms other state-of-the-art algorithms by keeping the path cost largely comparable. Additionally, an ROS experiment using a robot and lidar sensor data shows the improvement of the proposed method in a simulated laboratory environment.

A Robust Deep Feature Extraction Method for Human Activity Recognition Using a Wavelet Based Spectral Visualisation Technique.

Human Activity Recognition (HAR), alongside Ambient Assisted Living (AAL), are integral components of smart homes, sports, surveillance, and investigation activities. To recognize daily activities, researchers are focusing on lightweight, cost-effective, wearable sensor-based technologies as traditional vision-based technologies lack elderly privacy, a fundamental right of every human. However, it is challenging to extract potential features from 1D multi-sensor data. Thus, this research focuses on extracting distinguishable patterns and deep features from spectral images by time-frequency-domain analysis of 1D multi-sensor data. Wearable sensor data, particularly accelerator and gyroscope data, act as input signals of different daily activities, and provide potential information using time-frequency analysis. This potential time series information is mapped into spectral images through a process called use of 'scalograms', derived from the continuous wavelet transform. The deep activity features are extracted from the activity image using deep learning models such as CNN, MobileNetV3, ResNet, and GoogleNet and subsequently classified using a conventional classifier. To validate the proposed model, SisFall and PAMAP2 benchmark datasets are used. Based on the experimental results, this proposed model shows the optimal performance for activity recognition obtaining an accuracy of 98.4% for SisFall and 98.1% for PAMAP2, using Morlet as the mother wavelet with ResNet-101 and a softmax classifier, and outperforms state-of-the-art algorithms.

Whole genome sequencing-based identification of human tuberculosis caused by animal-lineage Mycobacterium orygis.

A recently described member of the Mycobacterium tuberculosis complex (MTBC) is Mycobacterium orygis, which can cause disease primarily in animals but also in humans. Although M. orygis has been reported from different geographic regions around the world, due to a lack of proper identification techniques, the contribution of this emerging pathogen to the global burden of zoonotic tuberculosis is not fully understood. In the present work, we report single nucleotide polymorphism (SNP) analysis using whole genome sequencing (WGS) that can accurately identify M. orygis and differentiate it from other members of the MTBC species. WGS-based SNP analysis was performed for 61 isolates from different provinces in Canada that were identified as M. orygis. A total of 56 M. orygis sequences from the public databases were also included in the analysis. Several unique SNPs in the gyrB, PPE55, Rv2042c, leuS, mmpL6, and mmpS6 genes were used to determine their effectiveness as genetic markers for the identification of M. orygis. To the best of our knowledge, five of these SNPs, viz., gyrB 277 (A→G), gyrB 1478 (T→C), leuS 1064 (A→T), mmpL6 486 (T→C), and mmpS6 334 (C→G), are reported for the first time in this study. Our results also revealed several SNPs specific to other species within MTBC. The phylogenetic analysis shows that the studied genomes were genetically diverse and clustered with M. orygis sequences of human and animal origin reported from different geographic locations. Therefore, the present study provides a new insight into the high-confidence identification of M. orygis from MTBC species based on WGS data, which can be useful for reference and diagnostic laboratories.

A systematic review from basics to omics on bacteriophage applications in poultry production and processing.

The growing human population is currently facing an unprecedented challenge on global food production and sustainability. Despite recognizing poultry as one of the most successful and rapidly growing food industries to address this challenge; poultry health and safety remain major issues that entail immediate attention. Bacterial diseases including colibacillosis, salmonellosis, and necrotic enteritis have become increasingly prevalent during poultry production. Likewise, outbreaks caused by consumption of undercooked poultry products contaminated with zoonotic bacterial pathogens such as Salmonella, Campylobacter and Listeria, are a serious public health concern. With antimicrobial resistance problem and restricted use of antibiotics in food producing animals, bacteriophages are increasingly recognized as an attractive natural antibacterial alternative. Bacteriophages have recently shown promising results to treat diseases in poultry, reduce contamination of carcasses, and enhance the safety of poultry products. Omics technologies have been successfully employed to accurately characterize bacteriophages and their genes/proteins important for interaction with bacterial hosts. In this review, the potential of using lytic bacteriophages to mitigate the risk of major poultry-associated bacterial pathogens are explored. This study also explores challenges associated with the adoption of this technology by industries. Furthermore, the impact of omics approaches on studying bacteriophages, their host interaction and applications is discussed.

Comparison of simplicity, convenience, safety, and cost-effectiveness between use of insulin pen devices and disposable plastic syringes by patients with type 2 diabetes mellitus: a cross-sectional study from Bangladesh.

INTRODUCTION: Insulin pen devices and disposable plastic insulin syringes are two common tools for insulin administration. This study aims to compare the simplicity, convenience, safety, and cost-effectiveness of insulin pens versus syringe devices in patients with type 2 diabetes mellitus (T2DM). METHODS: A cross-sectional study was conducted at 14 diabetes clinics throughout Bangladesh from November 2021 to April 2022 among adults with T2DM injecting insulin by pen devices or disposable insulin syringes at least once a day for at least one year by purposive sampling. The simplicity, convenience, and safety of insulin devices were assessed using a structured questionnaire, and the study subjects were scored based on their answers; higher scores indicated a poorer response. Total scores for simplicity, convenience, and safety were obtained by adding the scores for relevant components. Their average monthly medical expense and cost of insulin therapy were recorded. The median values of the total scores and monthly expenses were compared between pen devices and disposable syringe users. RESULTS: 737 subjects were evaluated; 406 were pen users, and 331 were vial syringe users. The pen users had lower median scores for simplicity [6.0 (5.0-8.0) vs. 7.0 (5.0-9.0), p = 0.002], convenience [4.0 (3.0-6.0) vs. 5.0 (4.0-6.0), p < 0.001], and safety [7.0 (6.0-8.0) vs. 7.0 (6.0-9.0), p = 0.008] than vial syringe users. Pen devices were more expensive than vial syringes in terms of average medical expense per month [BDT 5000 (3500-7000) vs. 3000 (2000-5000), p < 0.001], the total cost of insulin therapy per month [BDT 2000 (1500-3000) vs. 1200 (800-1700), p < 0.001] and cost per unit of insulin used [BDT 2.08 (1.39-2.78) vs. 0.96 (0.64-1.39), p < 0.001]. Non-significant differences in favor of pens were observed in HbA1c levels [8.7 (7.8-10) vs. 8.9 (7.9-10)%, p = 0.607] and proportions of subjects having HbA1c < 7% (6.9 vs. 6.3%, p = 0.991). CONCLUSION: Insulin pens are simpler, more convenient, and safe but more expensive than vial syringes. Glycemic control is comparable between pen and syringe users. Long-term follow-up studies are needed to determine the clinical and economic impacts of such benefits of insulin pens.

Status of lipid control in Bangladeshi subjects with type 2 diabetes mellitus on lipid-lowering drugs: a multicenter, facility-based, cross-sectional study.

BACKGROUND: Achievement of lipid targets is crucial in patients with type 2 diabetes mellitus (T2DM) to mitigate the risk of cardiovascular diseases (CVD). Data on lipid-control status among patients with T2DM in Bangladesh are scarce. This study was conducted to determine the lipid-control status among patients with T2DM who were on lipid-lowering drugs in the country. METHODS: This cross-sectional study was conducted in the diabetes outpatient departments of several tertiary hospitals in Bangladesh from January 2022 to December 2022. Adults of both sexes diagnosed with T2DM for at least one year and were on the lipid-lowering drug(s) for a minimum of 3 months were included in the study by consecutive sampling. Patients' data were collected by face-to-face interviews, and blood samples were collected for fasting lipid profile. The lipid target was set at < 200 mg/dL for total cholesterol (TC), < 150 mg/dL for triglyceride (TG), < 100 mg/dL for low-density lipoprotein cholesterol (LDL-C), > 40 mg/dL for high-density lipoprotein cholesterol (HDL-C), and < 160 mg/dL for non-HDL cholesterol (non-HDL-C). RESULT: Three thousand sixty patients (age 44.7 ± 13.3 years, female 57%) with T2DM were evaluated. Overall, almost 81% of the study subjects achieved the LDL-C target. Besides, TC, TG, HDL-C, and non-HDL-C targets were achieved by 40.8, 21.6, 66.3, and 44.1% of patients, respectively. However, all the lipid parameters were under control in only 8.8% of patients. Almost 77.6% of the patients with ischemic heart disease, 81.5% of patients with stroke, and 65% of patients with CKD had LDL levels < 70 mg/dL. Only 10.03% achieved the HbA1c target of < 7%. 7.4% of patients achieved both HbA1c < 7% and LDL < 100 mg/dL and 5% achieved both HbA1c < 7% and LDL < 70 mg/dL. Advanced age (aOR 0.97, 95% CI 0.96, 0.98, p < 0.001), longstanding T2DM (aOR 0.53, 95% CI 0.39, 0.72, p < 0.001), and non-statin therapy (aOR 0.25, 95% CI 0.16, 0.37, p < 0.001) were negatively associated with lipid control (LDL < 100 mg/dL) while using oral hypoglycemic drugs or insulin (aOR 2.01, 95% CI 1.45, 2.77, p < 0.001) and having cardiovascular comorbidity (aOR 3.92, 95% CI 3.00, 5.12, p < 0.001) were positively associated with lipid control. CONCLUSION: Though most patients with T2DM achieved their target LDL level, the prevalence of both glycemic and overall lipid control was low in our study despite lipid-lowering therapy.

Atypical protein kinase C iota (PKCλ/ι) ensures mammalian development by establishing the maternal-fetal exchange interface.

In utero mammalian development relies on the establishment of the maternal-fetal exchange interface, which ensures transportation of nutrients and gases between the mother and the fetus. This exchange interface is established via development of multinucleated syncytiotrophoblast cells (SynTs) during placentation. In mice, SynTs develop via differentiation of the trophoblast stem cell-like progenitor cells (TSPCs) of the placenta primordium, and in humans, SynTs are developed via differentiation of villous cytotrophoblast (CTB) progenitors. Despite the critical need in pregnancy progression, conserved signaling mechanisms that ensure SynT development are poorly understood. Herein, we show that atypical protein kinase C iota (PKCλ/ι) plays an essential role in establishing the SynT differentiation program in trophoblast progenitors. Loss of PKCλ/ι in the mouse TSPCs abrogates SynT development, leading to embryonic death at approximately embryonic day 9.0 (E9.0). We also show that PKCλ/ι-mediated priming of trophoblast progenitors for SynT differentiation is a conserved event during human placentation. PKCλ/ι is selectively expressed in the first-trimester CTBs of a developing human placenta. Furthermore, loss of PKCλ/ι in CTB-derived human trophoblast stem cells (human TSCs) impairs their SynT differentiation potential both in vitro and after transplantation in immunocompromised mice. Our mechanistic analyses indicate that PKCλ/ι signaling maintains expression of GCM1, GATA2, and PPARγ, which are key transcription factors to instigate SynT differentiation programs in both mouse and human trophoblast progenitors. Our study uncovers a conserved molecular mechanism, in which PKCλ/ι signaling regulates establishment of the maternal-fetal exchange surface by promoting trophoblast progenitor-to-SynT transition during placentation.

Mutual Information-Driven Feature Reduction for Hyperspectral Image Classification.

A hyperspectral image (HSI), which contains a number of contiguous and narrow spectral wavelength bands, is a valuable source of data for ground cover examinations. Classification using the entire original HSI suffers from the "curse of dimensionality" problem because (i) the image bands are highly correlated both spectrally and spatially, (ii) not every band can carry equal information, (iii) there is a lack of enough training samples for some classes, and (iv) the overall computational cost is high. Therefore, effective feature (band) reduction is necessary through feature extraction (FE) and/or feature selection (FS) for improving the classification in a cost-effective manner. Principal component analysis (PCA) is a frequently adopted unsupervised FE method in HSI classification. Nevertheless, its performance worsens when the dataset is noisy, and the computational cost becomes high. Consequently, this study first proposed an efficient FE approach using a normalized mutual information (NMI)-based band grouping strategy, where the classical PCA was applied to each band subgroup for intrinsic FE. Finally, the subspace of the most effective features was generated by the NMI-based minimum redundancy and maximum relevance (mRMR) FS criteria. The subspace of features was then classified using the kernel support vector machine. Two real HSIs collected by the AVIRIS and HYDICE sensors were used in an experiment. The experimental results demonstrated that the proposed feature reduction approach significantly improved the classification performance. It achieved the highest overall classification accuracy of 94.93% for the AVIRIS dataset and 99.026% for the HYDICE dataset. Moreover, the proposed approach reduced the computational cost compared with the studied methods.

Equity in access to safely managed sanitation and prevalence of diarrheal diseases in Bangladesh: a national and sub-national analysis.

BACKGROUND: In Bangladesh, safely managed sanitation (SMS) coverage is low, and diarrheal disease is a significant health problem. This study estimated the inequality in access to SMS facilities at the national and sub-national levels and assessed the prevalence of diarrheal diseases in connection with these improved facilities. METHODS: Data were extracted from the Bangladesh Demographic and Health Survey, conducted during 2017-2018. SMS was defined as using an improved sanitation facility, which designed to hygienically separate excreta from human contact and include the use of a flush toilet connected to piped sewer system, septic tank, ventilated improved pit latrine, pit latrine with a slab, and composting toilet. The slope index of inequality (SII) and multi-level regression models were used for inequality and risk factors of SMS respectively. RESULTS: The national coverage of SMS was 44.0% (45.3% and 43.5% in urban and rural areas, respectively). At the sub-national level, the lowest and highest coverage of SMS was observed in Mymensingh (32.9%) and Chittagong (54.1%) divisions, respectively. The national level SII indicated that wealthy households had access to higher SMS by 60.8 percentage points than poor households. Additionally, greater inequality was observed in rural areas, which was 71.9 percentage points higher in the richest households than in the poorest households. The coverage gap between the rich and poor was highest in the Sylhet division (85.3 percentage points higher in rich than in poor) and lowest in Dhaka (34.9 percentage points). Old and highly educated household heads and richest households had better access to higher levels of adequate sanitation. After adjusting for confounding variables, the prevalence of diarrheal disease was 14.0% lower in the SMS user group than in their counterparts. CONCLUSION: Substantial inequalities in access to SMS exist at both national and sub-national levels of Bangladesh, with the prevalence of diarrhea being lower among SMS users. These findings may help to prioritize resources for reducing inequality and expanding the coverage of improved sanitation in Bangladesh.

Effects of litter from antimicrobial-fed broiler chickens on soil bacterial community structure and diversity.

This study examined changes in soil bacterial community composition and diversity in response to fertilization with litter from chickens fed a diet without antibiotics and with bambermycin, penicillin, bacitracin, salinomycin, or mix of salinomycin and bacitracin. Litter (27.5 T/ha) was applied to 24 agricultural plots in the Fraser Valley of British Columbia. Nonfertilized plots were used as a negative control. Soil samples collected from the studied plots were used to quantify Escherichia coli by plate counts, and Clostridium perfringens by qPCR. The 16S rRNA gene sequencing was performed for microbiota analysis. Following litter application in December, the population size of E. coli was 5.4 log CFU/g; however, regardless of treatments, the results revealed 5.2 and 1.4 log CFU/g of E. coli in soil sampled in January and March, respectively. Fertilization with litter from antibiotic-treated birds increased (P < 0.05) the relative abundance of Proteobacteria, Actinobacteria, and Firmicutes in soil, but decreased Acidobacteria and Verrucomicrobia groups. The alpha diversity parameters were higher (P < 0.05) in nonfertilized soil compared to the fertilized ones, suggesting that litter application was a major factor in shaping the soil bacterial communities. These results may help develop efficient litter management strategies like composting, autoclaving, or anaerobic digestion of poultry litter before application to land for preservation of soil health and crop productivity.

Unknown Object Detection Using a One-Class Support Vector Machine for a Cloud-Robot System.

Inter-robot communication and high computational power are challenging issues for deploying indoor mobile robot applications with sensor data processing. Thus, this paper presents an efficient cloud-based multirobot framework with inter-robot communication and high computational power to deploy autonomous mobile robots for indoor applications. Deployment of usable indoor service robots requires uninterrupted movement and enhanced robot vision with a robust classification of objects and obstacles using vision sensor data in the indoor environment. However, state-of-the-art methods face degraded indoor object and obstacle recognition for multiobject vision frames and unknown objects in complex and dynamic environments. From these points of view, this paper proposes a new object segmentation model to separate objects from a multiobject robotic view-frame. In addition, we present a support vector data description (SVDD)-based one-class support vector machine for detecting unknown objects in an outlier detection fashion for the classification model. A cloud-based convolutional neural network (CNN) model with a SoftMax classifier is used for training and identification of objects in the environment, and an incremental learning method is introduced for adding unknown objects to the robot knowledge. A cloud-robot architecture is implemented using a Node-RED environment to validate the proposed model. A benchmarked object image dataset from an open resource repository and images captured from the lab environment were used to train the models. The proposed model showed good object detection and identification results. The performance of the model was compared with three state-of-the-art models and was found to outperform them. Moreover, the usability of the proposed system was enhanced by the unknown object detection, incremental learning, and cloud-based framework.

The Ameliorative Effect of Dexamethasone on the Development of Autoimmune Lung Injury and Mediastinal Fat-Associated Lymphoid Clusters in an Autoimmune Disease Mouse Model.

In our previous study, we revealed the ameliorative therapeutic effect of dexamethasone (Dex) for Lupus nephritis lesions in the MRL/MpJ-Fas lpr/lpr (Lpr) mouse model. The female Lpr mice developed a greater number of mediastinal fat-associated lymphoid clusters (MFALCs) and inflammatory lung lesions compared to the male mice. However, the effect of Dex, an immunosuppressive drug, on both lung lesions and the development of MFALCs in Lpr mice has not been identified yet. Therefore, in this study, we compared the development of lung lesions and MFALCs in female Lpr mice that received either saline (saline group "SG") or dexamethasone (dexamethasone group "DG") in drinking water as a daily dose along with weekly intraperitoneal injections for 10 weeks. Compared to the SG group, the DG group showed a significant reduction in the levels of serum anti-dsDNA antibodies, the size of MFALCs, the degree of lung injury, the area of high endothelial venules (HEVs), and the number of proliferating and immune cells in both MFALCs and the lungs. A significant positive correlation was observed between the size of MFALCs and the cellular aggregation in the lungs of Lpr mice. Therefore, this study confirmed the ameliorative effect of Dex on the development of lung injury and MFALCs via their regressive effect on both immune cells' proliferative activity and the development of HEVs. Furthermore, the reprogramming of MFALCs by targeting immune cells and HEVs may provide a therapeutic strategy for autoimmune-disease-associated lung injury.