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This review aimed to examine the extent of Bangladesh’s COVID-19 preparedness and control measures up to 20 January 2021, and to draw some lessons for informing the current and future pandemic responses in Bangladesh in light of Vietnam’s responses, which had successfully controlled the pandemic. We performed a content analysis of data to identify similarities and critical discrepancies in epidemiological features and COVID-19 responses between the two countries. Findings indicated that Vietnam reported lower COVID-19 incidence (15 cases per million) and death rate (0.4 cases per million) than Bangladesh, with 3,129 cases per million and a death rate of 46 cases per million. Vietnam reported only 35 deaths, with 22 older individuals (>60 years) compared with 7,950 deaths in Bangladesh, with the highest death rate in older people (45%). An integrated approach combined with widespread contact tracing, better health investment, vaccine development, and strong political commitment enabled Vietnam to control the disease and mitigate its impacts. In contrast, Bangladesh seemed to adopt inadequate and untimely measures in the same domains, potentially contributing to relatively high COVID-19 infections and death rates. To control COVID-19 or inform responses to future pandemics, Bangladesh and similar countries can learn eight lessons from Vietnam. Such transferable responses could prepare health systems and populations for an appropriate global response to the next potential pandemic.

With the development of autonomous vehicles, localization and mapping technologies have become crucial to equip the vehicle with the appropriate knowledge for its operation. In this paper, we extend our previous work by prepossessing a localization and mapping architecture for autonomous vehicles that do not rely on GPS, particularly in environments such as tunnels, under bridges, urban canyons, and dense tree canopies. The proposed approach is of two parts. Firstly, a K-means algorithm is employed to extract features from LiDAR scenes to create a local map of each scan. Then, we concatenate the local maps to create a global map of the environment and facilitate data association between frames. Secondly, the main localization task is performed by an adaptive particle filter that works in four steps: (a) generation of particles around an initial state (provided by the GPS); (b) updating the particle positions by providing the motion (translation and rotation) of the vehicle using an inertial measurement device; (c) selection of the best candidate particles by observing at each timestamp the match rate (also called particle weight) of the local map (with the real-time distances to the objects) and the distances of the particles to the corresponding chunks of the global map; (d) averaging the selected particles to derive the estimated position, and, finally, using a resampling method on the particles to ensure the reliability of the position estimation. The performance of the newly proposed technique is investigated on different sequences of the Kitti and Pandaset raw data with different environmental setups, weather conditions, and seasonal changes. The obtained results validate the performance of the proposed approach in terms of speed and representativeness of the feature extraction for real-time localization in comparison with other state-of-the-art methods.

Abstract Although diatoms have been utilized as a cellular factory to produce biopharmaceuticals, recombinant proteins, and biofuels, only a few numbers of gene promoters are available. Therefore, the development of novel endogenous promoters is essential for the production of a range of bioactive substances. Here, we characterized the activities of endogenous promoters glyceraldehyde‐3‐phosphate dehydrogenase (GapC1) and glutamine synthetase (GS) of Phaeodactylum tricornutum using green fluorescent protein (GFP) under different culture conditions. Compared with the widely used fucoxanthin chlorophyll‐binding protein A (fcpA) promoter, the GS promoter constitutively drove the expression of GFP throughout all growth phases of P. tricornutum, regardless of culture conditions. Additionally, the GFP level driven by the GapC1 promoter was the highest at the log phase, similar to the fcpA promoter, and increased light and nitrogen‐starvation conditions reduced GFP levels by inhibiting promoter activity. These results suggested that the GS promoter could be utilized as a strong endogenous promoter for the genetic engineering of P. tricornutum.

Satellite images have been used extensively to identify the land use/land cover (LULC) changes in Bangladesh. However, no study has been conducted to classify LULC changes in the Dhaka Metropolitan Development Plan (DMDP) area using high-resolution commercial satellite images. The study aimed to simulate future LULC scenarios using RapidEye commercial images in the fastest-growing DMDP area. Support Vector Machine algorithm was applied to estimate the LULC scenarios for years 2012, 2015, and 2018. Cellular Automata machine learning algorithm was used to simulate the future LULC scenarios for 2025. The study result revealed that a significant net increase in the urban areas (UAs) by 15.52%, a remarkable decrease in sparse vegetation (SV) by 12.48%, and a transformation of 17.83% green cover (SV and dense vegetation) areas by 14.95% (8.9%/year) UAs were found from 2012 to 2018. Prediction results demonstrated that UAs would likely to be expanded by 53% and SV will be reduced by 13% (28% was in 2012) in 2025. The outcomes of this study will help the city authorities of DMDP in preparing a comprehensive micro-level urban development plan, where planned infrastructural development and supervision, land use planning, natural resource conservation, and environmental sustainability will be ensured.

Land Cover (LC) is going through a dramatic change due to rapid urbanization, especially in urban areas. The impervious land covers (built-up areas) are replacing the natural land covers (vegetation and waterbody) rapidly, which significantly contributes to the increase of Land Surface Temperature (LST). Increased LST deteriorates the meteorological condition in urban areas and causes Surface Urban Heat Island (SUHI) effect. The vulnerability of the SUHI effect can be described quantitatively and qualitatively by Urban Thermal Field Variance Index (UTFVI) phenomenon. The study investigates the changing pattern of the SUHI and its magnitude with Landsat TM/OLI time-series satellite imageries from 1988 to 2018 and establishes the relationship between LC change and LST variations in Chattogram city. The relationships are defined by correlation analysis, cross-section profiles, and Simple Linear Regression Models (SLRM). The results suggest that vegetation cover, water body, and bare-soil have decreased by 2%, 7%, and 10%, respectively, where the built-up area has increased by 19% in the study area during the study period. The average LST of the study area has increased by approximately 10 °C in the last 30 years. Weightage of the SUHI affected area has also increased over time due to its direct linkage with LST. No area was affected by the SUHI phenomenon in 1988, which was found more than 35% in 2018. Only 1.69% area was found under the strongest UTFVI phenomenon in 1988, which increased significantly by 27.53% in 2018. In statistical analysis, regression models are used to define LC and LST relationship for every LC type. The LC and LST relationship analyses demonstrate a significant positive correlation with the built-up area while it is negative with vegetation, waterbody, and bare soil. The findings of this study will help city officials and policymakers to prepare a sustainable urban land development plan to minimize the negative consequences of unplanned urbanization and heat stress-related issues.

The Padma river, for being dynamic, is subjected to frequent and irregular shifting, which creates various socioeconomic, ecological, and environmental threats. Besides, due to having seasonal influences, these threats become more intense during the monsoon period than the dry season. Considering these issues, the present study aims to investigate the spatiotemporal changes of the Padma river during 1988–2019 with seasonal variations, also simulating the changes till 2035 using multi-temporal satellite imageries. GIS and ARIMA model is used to perform spatiotemporal analysis and simulation, respectively. This study focused on the lateral shifting of 21 cross-sections along the Padma river channel flowing through 19 upazilas of six (06) districts in the northwest side of Bangladesh. The study finds that the width of the channel changes so frequently to its right and left sides during the last 31 years. The width increases in the summer season, indicating destruction of the river vicinity over time. The highest lateral shifting of the channel has also occurred at the Bagha and Daulatpur upazilas. The river is likely to be shifted more than 11 km and 13 km (winter and summer, respectively) in the next 16 years, along with the cross-section X10 at Bagha and Daulatpur upazila. Besides, the river channel's sinuosity has decreased till 2011 while it has increased suddenly in 2019. On the other hand, the braided index of the river has increased till 2011 and fell in 2019.

Heavy metal chromium (Cr) is considered to be a serious environmental contaminant due to its toxic effect on living organisms. To mitigate and reduce the negative impacts of Cr in rice plant, the effect of exogenous supplementary calcium was evaluated as it functions as a signaling molecule at cellular level. In this study, growth parameters, protein content, and membrane stability were found to be restored due to calcium under Cr stress. Further, Atomic absorption spectrophotometric analysis revealed that calcium inhibits Cr translocation from root to shoot in rice seedlings. This event was addressed by the enhanced accumulation of phytochelatin that leads to vacuolar sequestration of Cr in roots. Furthermore, increased activity of Catalase, Peroxidase, and Glutathione reductase along with elevated glutathione also assures that calcium enhances antioxidant defense mechanism to cope with Cr toxicity.

Globally, multiple factors have elevated the risk and contributed to the fast spread of COVID-19. Alongside this, unsolicited rumours and social stigma are believed to be two possible barriers to the effective prevention of the disease. Despite measures taken, rumours and social stigma related to COVID-19 tend to increase globally. Several studies document that rumours and social stigma may fuel the risk and rapid spread of COVID-19. However, how these rumours and social stigma act as barriers to the prevention of the COVID-19 outbreak remain unclear. This article aims to discuss how rumours and social stigma can undermine the preventive and clinical efforts to fight against the spread of COVID-19 and suggest potential policy implications for addressing rumours and social stigma and optimising preventive efforts. A narrative review of secondary sources of data, including published studies, grey literature and authentic press reports was conducted. The analysis indicates that unverified rumours associated with COVID-19 may weaken people’s preparedness for a new infectious disease by driving them to wrong treatment and preventing them from adhering to evidence-based medical suggestions and treatment. Findings also suggest that social stigma may reduce healthcare workers’ agency and self-respect to provide support, treatment and care for those with COVID-19. Social stigma may also constrain participation in screening, testing, quarantine, isolation, and treatment of the disease. This article offers six potential policy pathways and emphasises the national and international coordination of all stakeholders for addressing rumours and social stigma associated with COVID-19.

This paper introduces a procedure to compare the functional behaviour of individual units of electronic hardware of the same type. The primary use case for this method is to estimate the functional integrity of an unknown device unit based on the behaviour of a known and proven reference unit. This method is based on the so-called virtual sensor network (VSN) approach, where the output quantity of a physical sensor measurement is replicated by a virtual model output. In the present study, this approach is extended to model the functional behaviour of electronic hardware by a neural network (NN) with Long-Short-Term-Memory (LSTM) layers to encapsulate potential time-dependence of the signals. The proposed method is illustrated and validated on measurements from a remote-controlled drone, which is operated with two variants of controller hardware: a reference controller unit and a malfunctioning counterpart. It is demonstrated that the presented approach successfully identifies and describes the unexpected behaviour of the test device. In the presented case study, the model outputs a signal sample prediction in 0.14 ms and achieves a reconstruction accuracy of the validation data with a root mean square error (RMSE) below 0.04 relative to the data range. In addition, three self-protection features (multidimensional boundary-check, Mahalanobis distance, auxiliary autoencoder NN) are introduced to gauge the certainty of the VSN model output.

The performance of high strength structural lightweight concrete (LWC) using the palm wastes, oil palm shell (OPS) as well as palm oil clinker (POC) has been reported. Existing literatures used either OPS or POC individually for production of LWC. Each concept has their own advantages-disadvantages. In this study, both OPS and POC have been put together as coarse aggregate on the way to see the improvement of mechanical properties of waste based LWC. To achieve this purpose, regular coarse aggregate has been fully replaced by OPS and POC in the concrete. This structural grade lightweight concrete is named as palm shell and clinker concrete (PSCC). Attempts have been made with the series of OPS and POC mixture aimed at identifying for better performance. The quantity of OPS and POC mix has been varied as 30%, 40%, 50%, 60% and 70%. Mechanical properties of PSCC like density, workability, compressive strength at different ages, flexural strength, splitting tensile strength as well as modulus of elasticity have been evaluated. It is revealed that the proposed PSCC has extensive potential in terms of high compressive strength and good material behavior to perform as a better LWC. The study could offer structural lightweight concrete of compressive strength up to 46 MPa that is 31% higher than the control mix. The usage of 50% OPS to 50% POC coarse aggregate by vol. in the concrete mix is found to be the optimum mix. Furthermore, simple correlations have been developed which can easily predict compressive strength, splitting tensile strength, flexural strength, modulus of elasticity and ultrasonic pulse velocity of lightweight concrete.

Autonomous Vehicles (AVs) have the potential to solve many traffic problems, such as accidents, congestion and pollution. However, there are still challenges to overcome, for instance, AVs need to accurately perceive their environment to safely navigate in busy urban scenarios. The aim of this paper is to review recent articles on computer vision techniques that can be used to build an AV perception system. AV perception systems need to accurately detect non-static objects and predict their behaviour, as well as to detect static objects and recognise the information they are providing. This paper, in particular, focuses on the computer vision techniques used to detect pedestrians and vehicles. There have been many papers and reviews on pedestrians and vehicles detection so far. However, most of the past papers only reviewed pedestrian or vehicle detection separately. This review aims to present an overview of the AV systems in general, and then review and investigate several detection computer vision techniques for pedestrians and vehicles. The review concludes that both traditional and Deep Learning (DL) techniques have been used for pedestrian and vehicle detection; however, DL techniques have shown the best results. Although good detection results have been achieved for pedestrians and vehicles, the current algorithms still struggle to detect small, occluded, and truncated objects. In addition, there is limited research on how to improve detection performance in difficult light and weather conditions. Most of the algorithms have been tested on well-recognised datasets such as Caltech and KITTI; however, these datasets have their own limitations. Therefore, this paper recommends that future works should be implemented on more new challenging datasets, such as PIE and BDD100K.

Many advanced driver assistance systems (ADAS) are currently trying to utilise multi-sensor architectures, where the driver assistance algorithm receives data from a multitude of sensors. As mono-sensor systems cannot provide reliable and consistent readings under all circumstances because of errors and other limitations, fusing data from multiple sensors ensures that the environmental parameters are perceived correctly and reliably for most scenarios, thereby substantially improving the reliability of the multi-sensor-based automotive systems. This paper first highlights the significance of efficiently fusing data from multiple sensors in ADAS features. An emergency brake assist (EBA) system is showcased using multiple sensors, namely, a light detection and ranging (LiDAR) sensor and camera. The architectures of the proposed ‘centralised’ and ‘decentralised’ sensor fusion approaches for EBA are discussed along with their constituents, i.e., the detection algorithms, the fusion algorithm, and the tracking algorithm. The centralised and decentralised architectures are built and analytically compared, and the performance of these two fusion architectures for EBA are evaluated in terms of speed of execution, accuracy, and computational cost. While both fusion methods are seen to drive the EBA application at an acceptable frame rate (~20 fps or higher) on an Intel i5-based Ubuntu system, it was concluded through the experiments and analytical comparisons that the decentralised fusion-driven EBA leads to higher accuracy; however, it has the downside of a higher computational cost. The centralised fusion-driven EBA yields comparatively less accurate results, but with the benefits of a higher frame rate and lesser computational cost.

Background: Migraine is an important cause of headache and headache-related disabilities. It increases loss of working time, causes inability to carry out daily activities and disruption of family and social life. The pathophysiology of migraine is still poorly understood. On the other hand, the prevalence of obesity is constantly increasing worldwide. The consequence of overweight and obesity includes increased risk of diabetes mellitus, dyslipidemia, hypertension, cardiovascular disease and cancer. Objectives: This study was performed to assess the relationship between BMI and migraine by finding out the relationship between migraine frequency and duration in different BMI groups, comparing the socio-demographic variables in migraine and non-migraine patients and to find out the migraine related co-morbidities. Materials and Methods: This observational case-control study was conducted on 100 subjects aged 12–50 years in the Neurology Outpatient Department, Mymensingh Medical College Hospital, Mymensingh in the period of January 2011 to December 2012. Out of total subjects fifty migraine patients were selected as cases and fifty nonmigraineurs as controls. Subjects were then categorized in three groups based on BMI: 25. Collected data were compiled and appropriate analyses were done by using computer based software, Statistical Package for Social Sciences (SPSS) version 16.0. For statistical analysis one way ANOVA tests were done for comparing means of quantitative data and Chi-square tests were done for qualitative data. A p value 95%) of the study subjects were between 10 and 35 years of age. Mean age of case group was found 25.55 ± 5.87 and that of control was 25.53 ± 4.22 years. Case group contained 10 (20%) males and 40 (80%) females whereas control group had 14 (28%) males and 36 (72%) females. Number of female cases and controls were higher than that of male. In control group 30 (60%) were unmarried and 20 (40%) were married. There was no significant difference in the financial condition between case and control groups. Students and housewives occupied the largest number of study subjects who were unemployed. Regarding residence, rural and urban patients were equal in case group and in control group 29 (58%) were urban and 21 (42%) rural. Mean duration of headache was 8.9 ± 7.5, 5.8 ± 6.7, 9.6 ± 14.3 years in different BMI groups (25 respectively) in case group and 4.6 ± 5.3, 4.4 ± 3.4, 3.4 ± 1.4 years in control group respectively. There was significant difference in quality of headache. In migrainous group 58.6% in BMI 25 noted their headache as throbbing, in contrast most of the nonmigrainous described them as dull in nature. Mean frequency of headache per month was significantly higher in migraine group compared to non-migraine group (p=0.02). Regarding associated symptoms, nausea, vomiting, photophobia and phonophobia were observed significantly higher in migraine patients in BMI

ABSTRACT Bifidobacterium species are important commensals capable of dominating the infant gut microbiome, in part by producing acids that suppress growth of other taxa. Bifidobacterium species are less prone to possessing antimicrobial resistance (AMR) genes (ARGs) than other taxa that may colonize infants. Given that AMR is a growing public health crisis and ARGs are present in the gut microbiome of humans from early life, this study examines the correlation between a Bifidobacterium-dominated infant gut microbiome and AMR levels, measured by a culture-independent metagenomic approach both in early life and as infants become toddlers. In general, Bifidobacterium dominance is associated with a significant reduction in AMR in a Bangladeshi cohort, both in the number of acquired AMR genes present and in the abundance of AMR genes. However, by year 2, Bangladeshi infants had no significant differences in AMR related to their early-life Bifidobacterium levels. A generalized linear model including all infants in a previously published Swedish cohort found a significant negative association between log-transformed total AMR and Bifidobacterium levels, thus confirming the relationship between Bifidobacterium levels and AMR. In both cohorts, there was no change between early-life and later-life AMR abundance in high-Bifidobacterium infants but a significant reduction in AMR abundance in low-Bifidobacterium infants. These results support the hypothesis that early Bifidobacterium dominance of the infant gut microbiome may help reduce colonization by taxa containing ARGs. IMPORTANCE Infants are vulnerable to an array of infectious diseases, and as the gut microbiome may serve as a reservoir of AMR for pathogens, reducing the levels of AMR in infants is important to infant health. This study demonstrates that high levels of Bifidobacterium are associated with reduced levels of AMR in early life and suggests that probiotic interventions to increase infant Bifidobacterium levels have the potential to reduce AMR in infants. However, this effect is not sustained at year 2 of age in Bangladeshi infants, underscoring the need for more detailed studies of the biogeography and timing of infant AMR acquisition.

Background: Since the elimination of poliomyelitis from most part of the world Gullain-Barre' Syndrome (GBS) has been the leading cause of acute flaccid paralysis which leads to substantial morbidity and mortality. Though GBS has received a lot of attention in developed countries, there is a paucity of reports on the GBS from the developing world including Bangladesh. Objective: The objective of the study was to correlate clinical, cerebrospinal fluid (CSF) and electrophysiological findings of hospitalized Gullain-Barre´ syndrome patients for early diagnosis and appropriate management. Materials and Methods: A total of 47 clinically diagnosed GBS patients admitted in Neurology, Medicine and Pediatrics departments of Dhaka Medical College Hospital (DMCH) were included in this quasi-experimental study. Biochemical, cytological and bacteriological studies of CSF of these patients were done. Electrophysiological studies of all subjects were done and values were compared with upper and lower limits of normal. Results: In this study, antecedent event were present in 55.30% cases and upper respiratory infection (23.40%) and gastroenteritis (21.30%) were the commonest antecedent disorders. All the study patients had numbness or paresthesia and limb weakness, and muscle pain was in 44.7% cases, facial weakness in 36.2% cases, ophthalmoplegia or ptosis in 6.4% and bulbar involvement was in 6.4% cases. Most of the patients (95.7%) had deep tendon hypo/areflexia followed by respiratory distress (21.3%), and ataxia (19.1%). Majority of the study patients (57.4%) required one week time to develop maximum deficit. Maximum subjects (70.2%) had motor type GBS followed by sensorimotor type (21.3%), Miller-Fisher type (6.4%) and sensory type (2.1%). Eighty three percent of the study patients had CSF protein concentration >45 mg/dL with mean ± SD of 71.32 ± 20.20 mg/dL (37–112 mg/dL). The cell count in CSF was

As autonomous vehicles become more common on the roads, their advancement draws on safety concerns for vulnerable road users, such as pedestrians and cyclists. This paper presents a review of recent developments in pedestrian and cyclist detection and intent estimation to increase the safety of autonomous vehicles, for both the driver and other road users. Understanding the intentions of the pedestrian/cyclist enables the self-driving vehicle to take actions to avoid incidents. To make this possible, development of methods/techniques, such as deep learning (DL), for the autonomous vehicle will be explored. For example, the development of pedestrian detection has been significantly advanced using DL approaches, such as; Fast Region-Convolutional Neural Network (R-CNN) , Faster R-CNN and Single Shot Detector (SSD). Although DL has been around for several decades, the hardware to realise the techniques have only recently become viable. Using these DL methods for pedestrian and cyclist detection and applying it for the tracking, motion modelling and pose estimation can allow for a successful and accurate method of intent estimation for the vulnerable road users. Although there has been a growth in research surrounding the study of pedestrian detection using vision-based approaches, further attention should include focus on cyclist detection. To further improve safety for these vulnerable road users (VRUs), approaches such as sensor fusion and intent estimation should be investigated.

Introduction: Irritable Bowel Syndrome (IBS) and migraine frequently co-exist. Stress is a major contributing factor for both. Our medical students are subjected to stress related to the implicit responsibility of courses. But the prevalence of IBS, migraine and co-existing migraine in medical students is not known. Aim: To estimate the prevalence of migraine, IBS and coexisting IBS and migraine among medical students. A CrossSectional Survey. Materials and Methods: Self-reported questionnaire based study, was conducted in which migraine was defined according to International Headache Society (IHS) criteria while IBS by both Asian criteria and Rome III criteria. Both preclinical (n=142) and clinical students (n=151) of four medical colleges (government and private) of Dhaka and Sylhet district participated in the study. Statistical Analysis: Student's t-test and chi-square test were used to compare the distributions of continuous data and categorical data respectively with significance level set at 0.05 or less. Results: Among the 293 students (mean age 21.09 ± 2.24 years) volunteered in the study (Males= 177), 14 (4.8%, 11 males, 3 females, p = 0.175) met the criteria for IBS with comparable prevalence among preclinical and clinical (4.2% vs. 5.3%, p = 0.787) students from both private and government institutions (2.1% vs. 7.2%, p = 0.055). IBS-D was the most prevalent subtype (n = 8, M = 6) and abdominal pain relieved by defecation (n = 11), was the most prevalent symptom. Fifty percent (n = 7) of IBS patients considered their bowel habit as normal. Among the 221 (75.4%) students with headache, only 51 (17.4%, 20 males and 31 females, p = 0.001) were diagnosed of migraine, with comparable prevalence among preclinical and clinical students (16.2% vs. 18.5%, p = 0.645). Only 17 (33%) subjects with migraine had accompanying aura. Common triggers were stress (n = 43), lack of sleep (n = 42), and daily life events. Twelve (23.5%) subjects with migraine had migraineassociated frequent disability. Only two female students with IBS-D (14.3%) had concomitant IBS and migraine. Conclusion: IBS and concomitant migraine - IBS prevalence was found to be low in our medical students, but migraine prevalence corresponds to other countries as well as in medical students.

Peri-urban areas in the global south are experiencing over-exploitation and contamination of water resources as a result of rapid urbanisation. These problems relate to the ineffectiveness of the underlying institutions in this dynamic, multi-actor context. Institutions need to be considered during problem solving; however, peri-urban communities have limited insight into their institutional context. This research examines the extent to which problem solving capacity can be improved through gaming-simulation methods. A game-based approach is tested in a capacity building workshop with peri-urban communities in Khulna (Bangladesh). A role-playing game designed from game theory models is used to examine local drinking water problems through an institutional lens. Workshop evaluation shows that through role-play, participants learned about strategies in drinking water supply (in both the current and future scenarios) and about the potential to address water quality issues through cooperative groundwater monitoring. Results also show improved problem understanding with regards to institutions, actor strategies, and problem-solving constraints. Participants valued the interactive medium for comparing and evaluating strategies. This paper highlights limitations in game design and its implementation, and offers ways to address this in future applications.

This study investigates the flexural behaviour of reinforced concrete (RC) beams strengthened through the combined externally bonded and near-surface mounted (CEBNSM) technique. The externally bonded reinforcement (EBR) and near-surface mounted (NSM) techniques are popular strengthening solutions, although these methods often demonstrate premature debonding failure. The proposed CEBNSM technique increases the bond area of the concrete–carbon fibre reinforced polymer (CFRP) interface, which can delay the debonding failure. This technique is appropriate when any structure has a narrow cross-sectional width or is in need of additional flexural capacity that an individual technique or material cannot attain. An experimental test matrix was designed with one control and five strengthened RC beams to verify the performance of the proposed technique. The strengthening materials were CFRP bar as NSM reinforcement combined with CFRP fabric as EBR material. The test variables were the diameter of the NSM bars (8 and 10 mm), the thickness of the CFRP fabrics (one and two layers) and the U-wrap anchorage. The strengthened beams showed enhancement of ultimate load capacity, stiffness, cracking behaviour, and strain compatibility. The ultimate capacity of the CEBNSM-strengthened beams increased from 71% to 105% compared to that of the control beam. A simulation method based on the moment-rotation approach was also presented to predict the behaviour of CEBNSM-strengthened RC beams.

Oral premalignant disorders (OPMDs) are a group of potentially malignant conditions that pose a significant health burden globally. MicroRNAs (miRNAs), small non-coding RNA molecules, have emerged as crucial regulators of gene expression and have been implicated in various biological processes, including carcinogenesis. This review synthesizes existing knowledge to provide a comprehensive understanding of the molecular mechanisms underlying OPMDs and to highlight the potential of miRNAs as promising biomarkers and therapeutic targets. Additionally, this review seeks to explore the potential of miRNA-based diagnostic biomarkers for early detection of OPMDs in the current literature on miRNAs in OPMDs, examining their involvement in disease pathogenesis, diagnostic potential, and therapeutic implications. Dysregulated miRNAs can target genes involved in critical cellular processes, such as cell cycle regulation, apoptosis, and DNA repair, leading to disease progression. Notably, miR-21, miR-31, miR-135b, and miR-486-5p have shown promise as potential biomarkers for early detection of oral premalignant lesions. Furthermore, the paper discusses the therapeutic implications of miRNAs in OPMDs. Preclinical studies have demonstrated the efficacy of miRNA-targeted therapies, such as miRNA mimics and inhibitors, in suppressing the growth of oral premalignant lesions. Early-phase clinical trials have shown promising results, indicating the potential for personalized treatment approaches. The findings underscore the importance of understanding the molecular mechanisms underlying these disorders and provide insights for the development of improved diagnostic and therapeutic strategies. However, they pose certain limitations given their intrinsic variability in expression profiles, the need for optimized isolation and detection methods, and potential hurdles in transitioning from preclinical success to clinical applications. Thus, future clinical studies are warranted to fully exploit the potential of miRNAs in the management of OPMDs., (© 2024. The Author(s), under exclusive licence to The Society of The Nippon Dental University.)

Background: Exosomes are the smallest extracellular vesicles (30-150 nm) secreted by all cell types, including synovial fluid. However, because biological fluids are complex, heterogeneous, and contain contaminants, their isolation is difficult and time-consuming. Furthermore, the pathophysiology of osteoarthritis (OA) involves exosomes carrying complex components that cause macrophages to release chemokines and proinflammatory cytokines. This narrative review aims to provide in-depth insights into exosome biology, isolation techniques, role in OA pathophysiology, and potential role in future OA therapeutics., Methods: A literature search was conducted using PubMed, Scopus, and Web of Science databases for studies involving exosomes in the osteoarthritis using keywords "Exosomes" and "Osteoarthritis". Relevant articles in the last 15 years involving both human and animal models were included. Studies involving exosomes in other inflammatory diseases were excluded., Results: Despite some progress, conventional techniques for isolating exosomes remain laborious and difficult, requiring intricate and time-consuming procedures across various body fluids and sample origins. Moreover, exosomes are involved in various physiological processes associated with OA, like cartilage calcification, degradation of osteoarthritic joints, and inflammation., Conclusion: The process of achieving standardization, integration, and high throughput of exosome isolation equipment is challenging and time-consuming. The integration of various methodologies can be employed to effectively address specific issues by leveraging their complementary benefits. Exosomes have the potential to effectively repair damaged cartilage OA, reduce inflammation, and maintain a balance between the formation and breakdown of cartilage matrix, therefore showing promise as a therapeutic option for OA., Competing Interests: Conflict of interestThe author(s) declared no potential conflicts of interest with respect to research, authorship, and/or publication of this article., (© Indian Orthopaedics Association 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Inflammatory arthritis commonly initiates in the soft tissues lining the joint. This lining swells, as do the cells in it and inside the joint fluid, producing chemicals that induce inflammation signs such as heat, redness, and swelling. MicroRNA (miRNA), a subset of non-coding small RNA molecules, post-transcriptionally controls gene expression by targeting their messenger RNA. MiRNAs modulate approximately 1/3 of the human genome with their multiple targets. Recently, they have been extensively studied as key modulators of the innate and adaptive immune systems in diseases such as allergic disorders, types of cancer, and cardiovascular diseases. However, research on the different inflammatory joint diseases, such as rheumatoid arthritis, gout, Lyme disease, ankylosing spondylitis, and psoriatic arthritis, remains in its infancy. This review presents a deeper understanding of miRNA biogenesis and the functions of miRNAs in modulating the immune and inflammatory responses in the above-mentioned inflammatory joint diseases. According to the literature, it has been demonstrated that the development of inflammatory joint disorders is closely related to different miRNAs and their specific regulatory mechanisms. Furthermore, they may present as possible prognostic and diagnostic biomarkers for all diseases and may help in developing a therapeutic response. However, further studies are needed to determine whether manipulating miRNAs can influence the development and progression of inflammatory joint disorders.

"BAU-Insectv2" represents a novel agricultural dataset tailored for deep learning applications and biomedical image analysis focused on plant-insect interactions. This dataset encompasses a diverse collection of high-resolution images capturing intricate details of plant-insect interactions across various agricultural settings. Leveraging deep learning methodologies, this study aims to employ convolutional neural networks (CNN) and advanced image analysis techniques for precise insect detection, classification, and understanding of insect-related patterns within agricultural ecosystems. We mainly focus on addressing insect-related issues in South Asian crop cultivation. The dataset's extensive scope and high-quality imagery provide a robust foundation for developing and validating models capable of accurately identifying and analyzing diverse plant insects. The dataset's utility extends to biomedical image analysis, fostering interdisciplinary research avenues across agriculture and biomedical sciences. This dataset holds significant promise for advancing research in agricultural pest management, ecosystem dynamics, and biomedical image analysis techniques., (© 2024 The Author(s).)

MicroRNAs (miRNAs) are short, 19-23 nucleotide non-coding RNA molecules that regulate gene expression by silencing or degrading the target mRNA gene. Since their discovery in the nineties of the last century, they have emerged as key inflammatory regulators. Inflammation induces the synthesis of various miRNAs that modulate the expression of multiple molecules involved in orchestrating the inflammatory response. This review aims to provide an insight into the role of miRNAs as potential biomarkers, mediators, and potential therapeutic targets of dental pulp inflammation. A literature search was conducted using the keywords; biogenesis of microRNA, human dental pulp cells, pulpitis, and inflammation in PubMed and Scopus index databases for all the published articles dealing with the role of miRNAs in pulp inflammation in the last 10 years. According to the literature, there is a clear correlation between miRNAs and several physiological events, as well as their role as mediators of innate immune response and inflammation in dental pulp cells. Our narrative review stipulates that numerous miRNAs play a key role in modulating inflammation, delaying or enhancing cell repair, cell differentiation, and survival in dental pulp diseases. However, further studies are required for the validation of miRNAs as reliable biomarkers in dental pulp pathology and their targeted therapy., (© 2022. The Author(s), under exclusive licence to The Society of The Nippon Dental University.)

Breast cancer (BC) is the most common cancer type among women with a distinct clinical presentation, but the survival rate remains moderate despite advances in multimodal therapy. Consequently, a deeper understanding of the molecular etiology is required for the development of more effective treatments for BC. The relationship between inflammation and tumorigenesis is well established, and the activation of the pro-inflammatory transcription factor nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is frequently identified in BC. Constitutive NF-κB activation is linked to cell survival, metastasis, proliferation, and hormonal, chemo-, and radiotherapy resistance. Moreover, the crosstalk between NF-κB and other transcription factors is well documented. It is reported that vitamin C plays a key role in preventing and treating a number of pathological conditions, including cancer, when administered at remarkably high doses. Indeed, vitamin C can regulate the activation of NF-κB by inhibiting specific NF-κB-dependent genes and multiple stimuli. In this review, we examine the various NF-κB impacts on BC development. We also provide some insight into how the NF-κB network may be targeted as a potential vulnerability by using natural pro-oxidant therapies such as vitamin C.

MicroRNAs (miRNAs) are the small noncoding RNA molecules which regulate target gene expression posttranscriptionally. They are known to regulate key cellular processes like inflammation, cell differentiation, cell proliferation, and cell apoptosis across various ocular diseases. Due to their easier access, recent focus has been laid on the investigation of miRNA expression and their involvement in several conjunctival diseases. The aim of this narrative review is to provide understanding of the miRNAs and describe the current role of miRNAs as the mediators of the various conjunctival diseases. A literature search was made using PubMed, Scopus, and Web of Science databases for studies involving miRNAs in the conjunctival pathological conditions. Original articles in the last 10 years involving both human and animal models were included. Literature search retrieved 27 studies matching our criteria. Pertaining to the numerous literatures, there is a strong correlation between miRNA and the various pathological conditions that occur in the conjunctiva. miRNAs are involved in various physiological processes such as cell differentiation, proliferation, apoptosis, development, and inflammation by regulating various signaling pathways, genes, proteins, and mediators. Pterygium was the most studied conjunctival disease for miRNA involvement, whereas miRNA research in allergic conjunctivitis is still in its early stages. Our review provides deep insights into the various miRNAs playing an important role in the various conjunctival diseases. miRNAs do have the potential to serve as noninvasive biomarkers with diagnostic, prognostic, and therapeutic implications. However, multitudinous studies are required to validate miRNAs as the reliable biomarkers in conjunctival pathologies and its targeted therapy.

Vernal Keratoconjunctivitis (VKC) is a chronic conjunctival inflammatory condition that typically affects children. Extracellular microRNAs (miRNAs) are small noncoding RNA molecules, the expression of which is reported to regulate cellular processes implicated in several eye diseases. The aim of this preliminary study is to identify the miRNA expression profile in the tears of children with VKC vis-à-vis controls, and to statistically evaluate these miRNAs as potential diagnostic biomarkers of VKC. The study involved a VKC group and a control group. Tear specimens were collected using Schirmer's strips. RNA was isolated using miRNeasy Micro kit and quantification was performed using an Agilent Bioanalyzer RNA 6000 Nano kit and Small RNA kit. miRNA profiling was performed using the Agilent microarray technique. A total of 51 miRNAs (48 upregulated and three downregulated) were differentially expressed in the tears of children with VKC and controls. The three most significantly upregulated miRNAs were hsa-miR-1229-5p, hsa-miR-6821-5p, and hsa-miR-6800-5p, and the three most significantly downregulated miRNAs were hsa-miR-7975, hsa-miR-7977, and hsa-miR-1260a. All the upregulated miRNAs are potential diagnostic biomarkers of VKC pending validation due to their larger discriminatory area under the curve (AUC) values. miRNA target prediction analysis revealed multiple overlapping genes that are known to play a role in conjunctival inflammation. We identified a set of differentially expressed miRNAs in the tears of children with VKC that may play a role in VKC pathogenesis. This study serves as the platform study for future miRNA studies that will provide a deeper understanding of the pathophysiology of VKC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Syed, Shahidan, Shatriah and Zunaina.)

The gut microbiota is a critical mediator of nutrition and disease risk. Like most complex traits, the microbiome is under genetic regulation and differs between inbred strains of mice. We tested the effect of fecal microbiota transplantation (FMT) on obesity, and plasma glucose. For this study, we collected microbiota from 2 inbred strains of mice which differ in adiposity and glucose tolerance, C57BL/6J and WSB/EiJ. C57BL/6J female mice (n = 18) were first treated with antibiotics for 4 weeks to ablate the microbiota. Following ablation, the mice were transplanted with microbiota from a C57BL/6J or a WSB/EiJ mouse and clinical traits and plasma metabolomic profiles were interrogated at 2- and 4-weeks post-transplantation. Unexpectedly, the mice receiving WSB/EiJ microbiota increased adiposity but decreased plasma glucose. Metabolomic and 16S microbiota profiling indicated broad metabolic changes occurred during and after FMT. Detailed analysis of these interactions demonstrated specific microbiota-host metabolite interactions which may alter disease susceptibility.