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.

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.

Leveraging textual information for social media news categorization and sentiment analysis.

The rise of social media has changed how people view connections. Machine Learning (ML)-based sentiment analysis and news categorization help understand emotions and access news. However, most studies focus on complex models requiring heavy resources and slowing inference times, making deployment difficult in resource-limited environments. In this paper, we process both structured and unstructured data, determining the polarity of text using the TextBlob scheme to determine the sentiment of news headlines. We propose a Stochastic Gradient Descent (SGD)-based Ridge classifier (RC) for blending SGDR with an advanced string processing technique to effectively classify news articles. Additionally, we explore existing supervised and unsupervised ML algorithms to gauge the effectiveness of our SGDR classifier. The scalability and generalization capability of SGD and L2 regularization techniques in RCs to handle overfitting and balance bias and variance provide the proposed SGDR with better classification capability. Experimental results highlight that our string processing pipeline significantly boosts the performance of all ML models. Notably, our ensemble SGDR classifier surpasses all state-of-the-art ML algorithms, achieving an impressive 98.12% accuracy. McNemar's significance tests reveal that our SGDR classifier achieves a 1% significance level improvement over K-Nearest Neighbor, Decision Tree, and AdaBoost and a 5% significance level improvement over other algorithms. These findings underscore the superior proficiency of linear models in news categorization compared to tree-based and nonlinear counterparts. This study contributes valuable insights into the efficacy of the proposed methodology, elucidating its potential for news categorization and sentiment analysis.

Trends and projections of age-appropriate vaccination coverage in 41 low- and middle- income countries in Asia and Sub-Saharan Africa, 2000-2030.

Introduction: Routine immunization programs have focused on increasing vaccination coverage, which is equally important for decreasing vaccine-preventable diseases (VPDs), particularly in low- and lower-middle-income countries (LMICs). We estimated the trends and projections of age-appropriate vaccination coverage at the regional and national levels, as well as place of residence and wealth index in LMICs. Methods: In total, 174 nationally representative household surveys from 2000 to 2020 from 41 LMICs were included in this study. Bayesian hierarchical regression models were used to estimate trends and projections of age-appropriate vaccination. Results: The trend in coverage of age-appropriate Bacillus Calmette-Guérin (BCG), third dose of diphtheria, tetanus, and pertussis (DTP3), third dose of polio (polio3), and measles-containing vaccine (MCV) increased rapidly from 2000 to 2020 in LMICs. Findings indicate substantial increases at the regional and national levels, and by area of residence and socioeconomic status between 2000 and 2030. The largest rise was observed in East Africa, followed by South and Southeast Asia. However, out of the 41 countries, only 10 countries are estimated to achieve 90% coverage of the BCG vaccine by 2030, five of DTP3, three of polio3, and none of MCV. Additionally, by 2030, wider pro-urban and -rich inequalities are expected in several African countries. Conclusion: Significant progress in age-appropriate vaccination coverage has been made in LMICs from 2000 to 2020. Despite this, projections show many countries will not meet the 2030 coverage goals, with persistent urban-rural and socioeconomic disparities. Therefore, LMICs must prioritize underperforming areas and reduce inequalities through stronger health systems and increased community engagement to ensure high coverage and equitable vaccine access.

Advances in Smart Photovoltaic Textiles.

Energy harvesting textiles have emerged as a promising solution to sustainably power wearable electronics. Textile-based solar cells (SCs) interconnected with on-body electronics have emerged to meet such needs. These technologies are lightweight, flexible, and easy to transport while leveraging the abundant natural sunlight in an eco-friendly way. In this Review, we comprehensively explore the working mechanisms, diverse types, and advanced fabrication strategies of photovoltaic textiles. Furthermore, we provide a detailed analysis of the recent progress made in various types of photovoltaic textiles, emphasizing their electrochemical performance. The focal point of this review centers on smart photovoltaic textiles for wearable electronic applications. Finally, we offer insights and perspectives on potential solutions to overcome the existing limitations of textile-based photovoltaics to promote their industrial commercialization.

Qualitative assessment of regular and premium gasoline available in Bangladesh markets.

Assessing the quality of fuel is essential to comprehend its impact on the environment and human health. In this study, the evaluation of fuel quality standards at the consumer level was conducted by analyzing the motor fuels in Khulna, Bangladesh. A total of 32 samples of petrol (regular gasoline), and octane (premium gasoline) were collected from the fuel stations in the Khulna City Corporation area and analyzed with an FTIR-Fuel Analyzer. Fuel properties, such as research octane number (RON), motor octane number (MON), ethanol content, olefins content, and oxygen content were analyzed. For petrol, the average RON, MON, olefins, and oxygen content were 95.34, 85.70, 8.23 %v/v, and 0.78 %m/m, respectively, and for octane, they were 96.96, 85.39, 1.25 %v/v, and 0.09 %m/m, respectively. Almost all of these parameters complied with both Bangladesh standard and Euro 5 fuel specifications, and those that did not comply were very close to their standard values. However, benzene concentration, which was not specified in Bangladesh Standard, was the most alarming metric for octane since none of the samples matched the Euro 5 fuel specifications of the maximum concentration of 1 %v/v benzene; on average it was 3.70 %v/v. Although petrol benzene content (average 1.50 %v/v) was not as bad as it was for octane, it was still nowhere near good enough, with only 25% of the samples within the recommended level among the studied sample. This information holds significance in establishing the fuel profile and facilitating the identification of distinct samples linked to adulteration. Therefore, the analysis of motor fuel qualities is essential for maintaining the environment, human health, and the economy of a country.

METTL3 shapes m6A epitranscriptomic landscape for successful human placentation.

Methyltransferase-like 3 (METTL3), the catalytic enzyme of methyltransferase complex for m6A methylation of RNA, is essential for mammalian development. However, the importance of METTL3 in human placentation remains largely unexplored. Here, we show that a fine balance of METTL3 function in trophoblast cells is essential for successful human placentation. Both loss-of and gain-in METTL3 functions are associated with adverse human pregnancies. A subset of recurrent pregnancy losses and preterm pregnancies are often associated with loss of METTL3 expression in trophoblast progenitors. In contrast, METTL3 is induced in pregnancies associated with fetal growth restriction (FGR). Our loss of function analyses showed that METTL3 is essential for the maintenance of human TSC self-renewal and their differentiation to extravillous trophoblast cells (EVTs). In contrast, loss of METTL3 in human TSCs promotes syncytiotrophoblast (STB) development. Global analyses of RNA m6A modification and METTL3-RNA interaction in human TSCs showed that METTL3 regulates m6A modifications on the mRNA molecules of critical trophoblast regulators, including GATA2, GATA3, TEAD1, TEAD4, WWTR1, YAP1, TFAP2C and ASCL2, and loss of METTL3 leads to depletion of mRNA molecules of these critical regulators. Importantly, conditional deletion of Mettl3 in trophoblast progenitors of an early post-implantation mouse embryo also leads to arrested self-renewal. Hence, our findings indicate that METLL3 is a conserved epitranscriptomic governor in trophoblast progenitors and ensures successful placentation by regulating their self-renewal and dictating their differentiation fate.

Diabetes and gastric cancer incidence and mortality in the Asia Cohort Consortium: A pooled analysis of more than a half million participants.

BACKGROUND: Evidence suggests a possible link between diabetes and gastric cancer risk, but the findings remain inconclusive, with limited studies in the Asian population. We aimed to assess the impact of diabetes and diabetes duration on the development of gastric cancer overall, by anatomical and histological subtypes. METHODS: A pooled analysis was conducted using 12 prospective studies included in the Asia Cohort Consortium. Among 558 981 participants (median age 52), after a median follow-up of 14.9 years and 10.5 years, 8556 incident primary gastric cancers and 8058 gastric cancer deaths occurred, respectively. Cox proportional hazard regression models were used to estimate study-specific hazard ratios (HRs) and 95% confidence intervals (CIs) and pooled using random-effects meta-analyses. RESULTS: Diabetes was associated with an increased incidence of overall gastric cancer (HR 1.15, 95% CI 1.06-1.25). The risk association did not differ significantly by sex (women vs men: HR 1.31, 95% CI 1.07-1.60 vs 1.12, 1.01-1.23), anatomical subsites (noncardia vs cardia: 1.14, 1.02-1.28 vs 1.17, 0.77-1.78) and histological subtypes (intestinal vs diffuse: 1.22, 1.02-1.46 vs 1.00, 0.62-1.61). Gastric cancer risk increased significantly during the first decade following diabetes diagnosis (HR 4.70, 95% CI 3.77-5.86), and decreased with time (nonlinear p < .01). Positive associations between diabetes and gastric cancer mortality were observed (HR 1.15, 95% CI 1.03-1.28) but attenuated after a 2-year time lag. CONCLUSION: Diabetes was associated with an increased gastric cancer incidence regardless of sex, anatomical subsite, or subtypes of gastric cancer. The risk of gastric cancer was particularly high during the first decade following diabetes diagnosis.

Appearance of tolerance-induction and non-inflammatory SARS-CoV-2 spike-specific IgG4 antibodies after COVID-19 booster vaccinations.

Background: Understanding the characteristics of the humoral immune responses following COVID-19 vaccinations is crucial for refining vaccination strategies and predicting immune responses to emerging SARS-CoV-2 variants. Methods: A longitudinal analysis of SARS-CoV-2 spike receptor binding domain (RBD) specific IgG antibody responses, encompassing IgG subclasses IgG1, IgG2, IgG3, and IgG4 was performed. Participants received four mRNA vaccine doses (group 1; n=10) or two ChAdOx1 nCoV-19 and two mRNA booster doses (group 2; n=19) in Bangladesh over two years. Results: Findings demonstrate robust IgG responses after primary Covishield or mRNA doses; declining to baseline within six months. First mRNA booster restored and surpassed primary IgG responses but waned after six months. Surprisingly, a second mRNA booster did not increase IgG levels further. Comprehensive IgG subclass analysis showed primary Covishield/mRNA vaccination generated predominantly IgG1 responses with limited IgG2/IgG3, Remarkably, IgG4 responses exhibited a distinct pattern. IgG4 remained undetectable initially but increased extensively six months after the second mRNA dose, eventually replacing IgG1 after the 3rd/4th mRNA doses. Conversely, initial Covishield recipients lack IgG4, surged post-second mRNA booster. Notably, mRNA-vaccinated individuals displayed earlier, robust IgG4 levels post first mRNA booster versus Covishield counterparts. IgG1 to IgG4 ratios decreased with increasing doses, most pronounced with four mRNA doses. This study highlights IgG response kinetics, influenced by vaccine type and doses, impacting immunological tolerance and IgG4 induction, shaping future vaccination strategies. Conclusions: This study highlights the dynamics of IgG responses dependent on vaccine type and number of doses, leading to immunological tolerance and IgG4 induction, and shaping future vaccination strategies.