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Objectives: Dengue emerged as a significant health threat in the endemic regions in recent years. However, inconsistent diagnostic accuracy in sequential dengue infections necessitate improved testing methods to ensure effective management of dengue cases. Here, we evaluated a portable, rapid, and sensitive molecular assay - Reverse Transcriptase Recombinase Polymerase Amplification Assay (RT-RAA) utilizing a mobile suitcase laboratory to detect infections in suspected dengue cases in Bangladesh., Method: 364 suspected dengue patients were enrolled in the study. Dengue cases were confirmed by a positive result from any of the four tests NS1 RDT, IgM RDT, qRT-PCR and RT-RAA assay. IgG RDT was performed to differentiate between primary and secondary dengue infections., Results: Of 364 suspected cases, 320 were confirmed dengue cases, with 55.94% classified as primary and 44.06% as secondary infections. Laboratory results showed comparable positivity rates between RT-RAA(78.8%) and NS1 RDT(77.1%) in primary dengue, followed by qRT-PCR(57.5%) and IgM RDT(12.8%). RT-RAA demonstrated superior positivity rates in secondary dengue(76.6%), surpassing RT-PCR(60.3%), NS1 RDT(27%), and IgM RDT (24.8%). Combining RT-RAA with NS1 RDT detected infections in 89.95% primary and 81.56% secondary dengue., Conclusion: The findings suggest complementing RT-RAA to NS1 RDT could significantly improve dengue detection rate, particularly for secondary infections., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Particle picking in cryo-electron tomograms (cryo-ET) is crucial for in situ structure detection of macro-molecules and protein complexes. The traditional template-matching-based approaches for particle picking suffer from template-specific biases and have low throughput. Given these problems, learning-based solutions are necessary for particle picking. However, the paucity of annotated data for training poses substantial challenges for such learning-based approaches. Moreover, preparing extensively annotated cryo-ET tomograms for particle picking is extremely time-consuming and burdensome. Addressing these challenges, we present TomoPicker, an annotation-efficient particle-picking approach that can effectively pick particles when only a minuscule portion (∼ 0.3 - 0.5%) of the total particles in a cellular cryo-ET dataset is provided for training. TomoPicker regards particle picking as a voxel classification problem and solves it with two different positive-unlabeled learning approaches. We evaluated our method on a benchmark cryo-ET dataset of eukaryotic cells, where we observed about 30% improvement by TomoPicker against the most recent state-of-the-art annotation efficient learning-based picking approaches.

The aerobic electron transfer chain builds a proton gradient by proton coupled electron transfer reactions through a series of proteins. Complex I is the first enzyme in the sequence. Here transfer of two electrons from NADH to quinone yields four protons pumped from the membrane N- (negative, higher pH) side to the P- (positive, lower pH) side. Protons move through three linear antiporter paths, with a few amino acids and waters providing the route; and through the E-channel, a complex of competing paths, with clusters of interconnected protonatable residues. Proton loading sites (PLS) transiently bind protons as they are transported from N- to P-compartments. PLS can be individual residues or extended clusters of residues. The program MCCE uses Monte Carlos sampling to analyze the E-channel proton binding in equilibrium with individual Molecular Dynamics snapshots from trajectories of Thermus thermuphillus Complex I in the apo, quinone and quinol bound states. At pH 7, the five E-channel subunits (Nqo4, Nqo7, Nqo8, Nqo10, and Nqo11) take >25,000 protonation microstates, each with different residues protonated. The microstate explosion is tamed by analyzing interconnected clusters of residues along the proton transfer paths. A proton is bound and released from a cluster of five coupled residues on the protein N-side and to six coupled residues in the protein center. Loaded microstates bind protons to sites closer to the P-side in the forward pumping direction. MCCE microstate analysis identifies strongly coupled proton binding amongst individual residues in the two PLS clusters., Competing Interests: Declaration of competing interest Marilyn Gunner reports financial support was provided by National Science Foundation. Marilyn Gunner reports financial support was provided by DOE. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

This work focused on removing iron with oxalic acid from red clay samples collected from Kapasia Upazila, Gazipur District, Bangladesh. To characterize the red clay, the study employed several techniques: particle size analysis, WDXRF (wavelength-dispersive X-ray fluorescence), AAS (atomic absorption spectroscopy), XRD (X-ray diffraction), TGA (thermogravimetric analysis), and FESEM (field emission scanning electron microscopy). Additionally, leaching experiments were conducted with varying concentrations of oxalic acid, temperatures and times. After leaching, the red clay composition changed significantly: SiO₂ increased from 53.6 % to 63.13 %, Fe₂O₃ decreased from 17.1 % to 3.64 %, Al₂O₃ remained relatively stable at 18 %-18.22 %, and other oxides showed minor variations. 78.71 % of the iron was removed at optimal leaching conditions (1.0 M oxalic acid, 100 °C, 150 min, and 250 rpm). Mineralogically, the red clay samples are composed of illite, kaolinite, quartz, feldspar, hematite and chlorite. Thermal analysis showed significant weight loss at temperatures between 300 and 600 °C. Ceramic trials were conducted at firing temperatures of 900 °C and 1100 °C to evaluate the mechanical properties of tiles. The results obtained showed significant improvements in red clay quality for ceramics. Being a low-cost and eco-friendly process, this becomes a very prominent alternative to conventional iron removal techniques and helps produce high-quality ceramic tiles, contributing towards economic growth in Bangladesh., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Arsenic (As) contamination in groundwater is emerging as a significant global concern, posing serious risks to the safety of drinking water and public health. To understand the release mechanisms, mobilization processes, spatial distribution, and probabilistic health risks of As in western Bangladesh, forty-seven samples were collected and analyzed using an atomic absorption spectrometer (AAS). The As concentrations in groundwater ranged from 1.97 to 697.4 μg L⁻ 1 (mean: 229.9), significantly exceeding recommended levels. The dominant hydrochemistry of As-enriched groundwater was Ca-Mg-HCO₃, with the primary sources of arsenic in groundwater being the dissolution of arsenic-bearing minerals in sediment and the recharge of aquifers from the Ganges River Basin. The assessment using the Entropy Water Quality Index revealed that the groundwater is unsuitable for drinking, with 89.36% (n = 42) of the samples surpassing the WHO's limit for arsenic. Rock-water interactions, including calcite dissolution and silicate weathering within the confined aquifer, predominantly influenced hydrochemical properties. The significant relationships among Fe, Mn, and As indicate that the reductive dissolution of FeOOH and/or MnOOH considerably contributes to the release of As from sediment into groundwater. Geochemical modeling analysis revealed that siderite and rhodochrosite precipitate into aquifer solids, suggesting a weak to moderate relationship among As, Fe, and Mn. The long residence time of groundwater, combined with the presence of a clayey aquitard, likely controls the mobilization of arsenic in the aquifer. For the first time, Monte Carlo simulations have been used in arsenic-prone areas to assess the severity of arsenic contamination in western Bangladesh. The analysis indicates that out of 100,000 people, 10 may develop cancer as a result of drinking arsenic-contaminated water, with children being more susceptible than adults., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objectives: As post kala-azar Dermal Leishmaniasis (PKDL) threatens the success of the Visceral Leishmaniasis (VL) elimination initiative, we aimed to investigate the PKDL burden, including an active search for PKDL in leprosy-negative skin lesion cases. We also investigated their health-seeking behavior and perceived level of stigma., Methods: This was a cross-sectional survey among inhabitants in the VL-endemic villages of the five most VL-endemic upazilas. VL experts trained medical officers in Upazila Health Complexes (UHCs) and leprosy facilities in PKDL management. Frontline workers conducted house-to-house surveys, referring PKDL suspects to designated centers. Data analysis involved Epi Info version 7 and IBM SPSS Statistics 25., Results: Among 472,435 screened individuals, 4022 had past VL (0.85 %). Among the screened population, 82 were PKDL suspects, and 62 PKDL cases were confirmed. The overall PKDL burden was 1.3 (95 % CI: 1.0-1.7) in the 10,000 population in the endemic villages. Male predominance and macular form of PKDL were observed. Thirty-nine PKDL patients perceived stigma of different levels. Only 27 of 62 (44 %) had received PKDL treatment. Medicine's unavailability and side effects were a major reason behind treatment interruption. Active screening among 137 leprosy-negative PKDL suspects yielded 10 (7.3 %) PKDL cases., Conclusion: The existence of PKDL cases in the VL endemic areas is a concern as those are inter-epidemic reservoirs. As per the WHO roadmap, the PKDL burden must be reduced by 70 % and 100 %, respectively, by 2026 and 2030. NKEP can take the current burden of 1.3 per 10,000 people in VL endemic villages as a baseline. Integrating active case detection for PKDL in leprosy hospitals and screening centers is feasible and worth deploying nationwide., Competing Interests: Declaration of competing interest The authors have no conflicts of interest associated with the material presented in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Cryogenic Electron Tomography (CryoET) is a useful imaging technology in structural biology that is hindered by its need for manual annotations, especially in particle picking. Recent works have endeavored to remedy this issue with few-shot learning or contrastive learning techniques. However, supervised training is still inevitable for them. We instead choose to leverage the power of existing 2D foundation models and present a novel, training-free framework, CryoSAM. In addition to prompt-based single-particle instance segmentation, our approach can automatically search for similar features, facilitating full tomogram semantic segmentation with only one prompt. CryoSAM is composed of two major parts: 1) a prompt-based 3D segmentation system that uses prompts to complete single-particle instance segmentation recursively with Cross-Plane Self-Prompting, and 2) a Hierarchical Feature Matching mechanism that efficiently matches relevant features with extracted tomogram features. They collaborate to enable the segmentation of all particles of one category with just one particle-specific prompt. Our experiments show that CryoSAM outperforms existing works by a significant margin and requires even fewer annotations in particle picking. Further visualizations demonstrate its ability when dealing with full tomogram segmentation for various subcellular structures. Our code is available at: https://github.com/xulabs/aitom.

In the delta region of Bangladesh, Sonneratia apetala , also known as Keora and mangrove apple, is widely recognized for its dual role as a source of both food and medicine. Seasonal S. apetala fruits were gathered from Hatiya, Noakhali, in October 2021. The samples were segregated into pericarps and seeds, then fractionated into methanol segments. The anti-proliferative activities of these samples against lung A549 cells were evaluated using the Trypan blue exclusion method. Additionally, High-Performance Liquid Chromatography (HPLC) was employed to quantify phenolic compounds, while standard protocols facilitated the identification of specific phytochemical constituents. Chemical profiling via Gas Chromatography-Mass Spectrometry (GC-MS) and the isolation and detection of bioactive compounds through column chromatography and Nuclear Magnetic Resonance (NMR) analysis were undertaken. The methanol fractions of the seeds and pericarp were found to contain carbohydrates, tannins, flavonoids, steroids, alkaloids, glycosides, and terpenoids, with the absence of saponins and anthraquinones. Notably, the anti-proliferative effect demonstrated statistical significance at a concentration of 300 μg/mL for both extracts. Furthermore, HPLC analysis identified and quantified six polyphenols: catechin hydrate, (-)-epicatechin, rutin hydrate, trans -ferulic acid, trans -cinnamic acid, myricetin, and kaempferol, with the following concentrations: 46.65 and 12.72; 349.29 and 140.39; 5.26 and 33.06; 10.35 and 29.28; ND and 11.93; and 10.03 and 7.90 mg/100 g in the methanol fraction of the seed and pericarp, respectively. GC-MS analysis of S. apetala fruit revealed five notable compounds with significant peak areas (%): 2-methyltetracosane, tetratetracontane, heptacosane, 1-chloro-2-hexyl-1-octanol, and phenol, 3,5-bis(1,1-dimethylethyl), exhibiting peak areas of 43.96, 35.8, and 15.95, respectively. Meanwhile, the notable peak in S. apetala seeds was 1,3-benzenedicarboxylic acid, bis(2-ethylhexyl) ester, with a peak area (%) of 100. These compounds are known for their anticancer and antioxidant properties. Therefore , S. apetala , particularly its seeds and fruits, shows promising potential for development into dietary supplements and functional foods., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

Tripartite resistance nodulation and cell division multidrug efflux pumps span the periplasm and are a major driver of multidrug resistance among Gram-negative bacteria. The periplasm provides a distinct environment between the inner and outer membranes of Gram-negative bacteria. Cations, such as Mg 2+ , become concentrated within the periplasm and, in contrast to the cytoplasm, its pH is sensitive to conditions outside the cell. Here, we reveal an interplay between Mg 2+ and pH in modulating the dynamics of the periplasmic adaptor protein, AcrA, and its function within the prototypical AcrAB-TolC multidrug efflux pump from Escherichia coli . In the absence of Mg 2+ , AcrA becomes increasingly plastic within acidic conditions, but when Mg 2+ is bound this is ameliorated, resulting in domain specific organisation in neutral to weakly acidic regimes. We establish a unique histidine residue directs these structural dynamics and is essential for sustaining pump efflux activity across acidic, neutral, and alkaline conditions. Overall, we propose Mg 2+ conserves the structural mobility of AcrA to ensure optimal AcrAB-TolC function within rapid changing environments commonly faced by the periplasm during bacterial infection and colonization. This work highlights that Mg 2+ is an important mechanistic component in this pump class and possibly across other periplasmic lipoproteins., Competing Interests: Competing interests The authors declare no competing interests.

Reliable separation of circulating tumor cells from blood cells is crucial for early cancer diagnosis and prognosis. Many conventional microfluidic platforms take advantage of the size difference between particles for their separation, which renders them impractical for sorting overlapping-sized cells. To address this concern, a hybrid inertial-dielectrophoretic microfluidic chip is proposed in this work for continuous and single-stage separation of lung cancer cell line A549 cells from white blood cells of overlapping size. The working mechanism of the proposed spiral microchannel embedded with planar interdigitated electrodes is validated against the experimental results. A numerical investigation is carried out over a range of flow conditions and electric field intensity to determine the separation efficiency and migration characteristics of the cell mixture. The results demonstrate the unique capability of the proposed microchannel to achieve high-throughput separation of cells at low applied voltages in both vertical and lateral directions. A significant lateral separation distance between the CTCs and the WBCs has been achieved, which allows for high-resolution and effective separation of cells. The separation resolution can be controlled by adjusting the strength of the applied electric field. Furthermore, the results demonstrate that the lateral separation distance is maximum at a voltage termed the critical voltage, which increases with the increase in the flow rate. The proposed microchannel and the developed technique can provide valuable insight into the development of a tunable and robust medical device for effective and high-throughput separation of cancer cells from the WBCs., (© 2024 The Authors. Biotechnology Progress published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers.)

Saltwater intrusion in the coastal areas of Bangladesh is a prevalent phenomenon. However, it is not conducive to activities such as irrigation, navigation, fish spawning and shelter, and industrial usage. The present study analyzed 45 water samples collected from 15 locations in coastal areas during three seasons: monsoon, pre-monsoon, and post-monsoon. The aim was to comprehend the seasonal variation in physicochemical parameters, including water temperature, pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), hardness, and concentrations of Na+, K+, Mg2+, Ca2+, Fe2+, HCO3-, PO43-, SO42-, and Cl-. Additionally, parameters essential for agriculture, such as soluble sodium percentage (SSP), sodium absorption ratio (SAR), magnesium absorption ratio (MAR), residual sodium carbonate (RSC), Kelly's ratio (KR), and permeability index (PI), were examined. Their respective values were found to be 63%, 16.83 mg/L, 34.92 mg/L, 145.44 mg/L, 1.28 mg/L, and 89.29%. The integrated water quality index was determined using entropy theory and principal component analysis (PCA). The resulting entropy water quality index (EWQI) and SAR of 49.56% and 63%, respectively, indicated that the samples are suitable for drinking but unsuitable for irrigation. These findings can assist policymakers in implementing the Bangladesh Deltaplan-2100, focusing on sustainable land management, fish cultivation, agricultural production, environmental preservation, water resource management, and environmental protection in the deltaic areas of Bangladesh. This research contributes to a deeper understanding of seasonal variations in the hydrochemistry and water quality of coastal rivers, aiding in the comprehension of salinity intrusion origins, mechanisms, and causes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Uddin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The quality of life (QoL) of cancer patients is of paramount concern due to the enduring effects of chemotherapy on the physical, emotional, spiritual, and social aspects of life. This study aims to examine the factors influencing QoL among cancer patients. A cross-sectional analysis encompassing 200 chemotherapy patients aged 18 and above was conducted, using self-reported surveys and clinical records. The results indicate higher social wellbeing and lower physical well-being scores. Significantly, patients in joint families, with income above Rs25,000, limited pre-diagnosis check-ups, over four chemotherapy cycles, showed better QoL. Engaging diversions like art and internet usage alleviated worries. Conversely, comorbidities correlated with lower FACT-G scores. QoL is still compromised, even with the developments of advanced cancer treatments. Managing mental, emotional, social, and physical health is vital. Future research should focus on evidence-based policies, innovative strategies, psychiatric assessments, mindfulness interventions, and exploring the impact of social interactions on QoL, aiming to enhance the wellbeing of newly diagnosed cancer patients.

Groundwater is a significant water resource for drinking and irrigation in Satkhira district, Bangladesh. The depletion of groundwater resources and deterioration in its quality are the results of the confluence of factors such as industrialization, intensive irrigation, and rapid population growth. For this reason, this study focused on the evaluation of tubewell water of six unions of Kaligonj upazila in Satkhira district, which is situated in the coastal southwest part of Bangladesh. Major and trace elemental concentrations were assimilated into positive matrix factorization (PMF) to identify potential sources and their respective contributions. Principal component analysis (PCA) revealed that groundwater salinization and manmade activities were the primary causes of heavy metals in the coastal groundwater. Its average pH value was found to be 7.5, while Dissolved oxygen, Total dissolved solids, salinity, and conductivity, with values ranging from 1.18 to 7.38 mg/L, 0.5-4.88 g/L, 0.4-5%, and 0.95 to 8.56 mS/cm, respectively. The total hardness average value was 561.7 mg/L, classified into the very hard water categories, which is why 90% of the tubewell water samples were unfit for household purposes. All samples had an excessive level of arsenic present. The iron concentration of fifteen (15) samples crossed the standard limit according to WHO 2011 value. Around 63% of the samples were of the Na + -K + -Cl - -SO 4 2- type, and about 72% were sodium-potassium and alkali types. 98% of samples were covered in chloride and bicarbonate. The findings showed that 45.83% of the groundwater samples had negative Chloroalkaline index (CAIs), while 54.16% had positive. The permeability index (PI) was an average of 73%, and residual sodium carbonate (RSC) averaged 260.2 mg/L, and the findings clearly showed that 80% of the samples weren't appropriate for irrigation. According to the sodium adsorption ratio (SAR) value, 65% of the samples fell into the unsuitable category. These calculations indicated a high overall salinity hazard in the study area, which may be caused by the intrusion of sea water given that the study area is close to the coastal region. Findings compared to standards revealed that the majority of the samples were deemed unfit for drinking and irrigation purposes. Hence, additional attention must be paid to this area to ensure the availability of drinkable water and to preserve sustainable farming practices., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Eleven trace metals (Cd, Cr, Fe, Mn, Cu, Ni, Co, Zn, As, Pb, and Ag) in sediments of Bangladesh's ship breaking area were measured by an atomic absorption spectrometer to determine origin, contamination extent, spatial distributions, and associated ecological and human health hazards. This study found considerable quantities of Pb, Cd, Mn, Zn, and Cu when compared with standards and high levels of Pb, Cd, Zn, Cu, As, and Ag contamination according to pollution evaluation indices. Different indices indicate most of the sampling sites were highly polluted. However, spatial distribution maps indicate that trace metals were predominantly deposited in the northern and southern region. The ecological risk index revealed that Cd has the highest while Pb and As had moderate risk. Based on the health index values, Zn for both adults and children were higher than the safe limit while Mn, Pb, Cr, As, Fe, Cu, Ni, and Co for children were close to the threshold. The mean total carcinogenic risk values of Cr, As, and Ni for children and Ni for adults exceeded the permissible threshold. The cancer risk possibilities were further assessed using Monte Carlo simulation. Most trace metals have anthropogenic origins, which were attributed to ship breaking activities., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

In plants and algae, the primary antenna protein bound to photosystem II is light-harvesting complex II (LHCII), a pigment-protein complex that binds eight chlorophyll (Chl) a molecules and six Chl b molecules. Chl a and Chl b differ only in that Chl a has a methyl group (-CH 3 ) on one of its pyrrole rings, while Chl b has a formyl group (-CHO) at that position. This blue-shifts the Chl b absorbance relative to Chl a . It is not known how the protein selectively binds the right Chl type at each site. Knowing the selection criteria would allow the design of light-harvesting complexes that bind different Chl types, modifying an organism to utilize the light of different wavelengths. The difference in the binding affinity of Chl a and Chl b in pea and spinach LHCII was calculated using multiconformation continuum electrostatics and free energy perturbation. Both methods have identified some Chl sites where the bound Chl type ( a or b ) has a significantly higher affinity, especially when the protein provides a hydrogen bond for the Chl b formyl group. However, the Chl a sites often have little calculated preference for one Chl type, so they are predicted to bind a mixture of Chl a and b . The electron density of the spinach LHCII was reanalyzed, which, however, confirmed that there is negligible Chl b in the Chl a -binding sites. It is suggested that the protein chooses the correct Chl type during folding, segregating the preferred Chl to the correct binding site.

Isolation and detection of circulating tumor cells (CTCs) hold significant importance for the early diagnosis of cancer and the assessment of therapeutic strategies. However, the scarcity of CTCs among peripheral blood cells presents a major challenge to their detection. Additionally, a similar size range between CTCs and white blood cells (WBCs) makes conventional microfluidic platforms inadequate for the isolation of CTCs. To overcome these challenges, in this study, a novel inertial-dielectrophoretic microfluidic channel for size-independent, single-stage separation of CTCs from WBCs has been presented. The proposed device utilizes a spiral microchannel embedded with interdigitated electrodes. A numerical model is developed and validated to investigate the influence of various parameters related to the channel design, fluid flow, and electrode configuration. It was found that optimal separation of CTCs could be obtained at a relatively low voltage, termed the critical voltage. Furthermore, at the critical voltage of 7.5 V, the hybrid microchannel is demonstrated to be capable of separating CTCs from different WBC subtypes including granulocytes, monocytes, T-, and B-lymphocytes. The unique capabilities of the hybrid spiral microchannel allow for this size-independent isolation of CTCs from a mixture of WBCs. Overall, the proposed technique can be readily utilized for continuous and high-throughput separation of cancer cells., (© 2023 Wiley-VCH GmbH.)

The study aimed to explore epidemiological, serological, and entomological aspects of visceral leishmaniasis (VL) in suspected new VL foci and assess the knowledge, attitude, and practices of the community living in the alleged new VL foci. The study investigated new visceral leishmaniasis (VL) cases reported between 2019 and 2020 in four sub-districts (Dharmapasha, Hakimpur, Islampur and Savar) where we tested 560 members using the rK39 rapid test and conducted vector collections in six neighbouring houses of the index cases to assess sandfly density and distribution, examined sandflies' infection, and determined the spatial relationship with VL infection. Furthermore, we highlighted the importance of early detection, and community awareness in controlling the spread of the disease. The study screened 1078 people from 231 households in the four sub-districts for fever, history of visceral leishmaniasis (VL), and PKDL-like skin lesions. Among sub-districts, positivity rate for rK39 rapid test was highest (3.5 %) in Savar. Sandflies were present across all areas except in Dharmapasha, but all 21 collected female P. argentipes sandflies were negative for Leishmania parasite DNA. We found one person from Islampur with a history of VL, and one from Islampur and another one from Savar had PKDL. After the awareness intervention, more people became familiar with VL infection (91.2 %), and their knowledge concerning sandflies being the vector of the disease and the risk of having VL increased significantly (30.1 %). The study found no active case in the suspected new foci, but some asymptomatic individuals were present. As sandfly vectors exist in these areas, the National Kala-azar Elimination Programme (NKEP) should consider these areas as kala-azar endemic and initiate control activities as per national guidelines., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

Background: COVID-19 has largely impacted the management of Visceral leishmaniasis (VL), like several other Neglected Tropical Diseases. The impact was particularly evident in Lower and Middle-Income countries where the already inadequate healthcare resources were diverted to managing the COVID-19 pandemic. Bangladesh achieved the elimination target for VL in 2016. To sustain this success, early diagnosis and treatment, effective vector control, and periodic surveillance are paramount. However, the specific control measures for VL in Bangladesh that were hampered during COVID-19 and their extent are unknown., Methods: This study aimed at identifying the gaps and challenges in the follow-up of treated VL patients by interviewing both the treated VL cases and their health service providers. We followed VL cases treated between 2019 and 2020 in five VL endemic subdistricts (upazilas) both retrospectively and prospectively to monitor clinical improvement, relapse, or other consequences. Moreover, interviews were conducted with the health service providers to assess the impact of COVID-19 on VL case detection, treatment, reporting, vector control operations, and logistic supply chain management., Results: There was no added delay for VL diagnosis; however, VL treatment initiation and reporting time increased almost two-fold due to COVID-19. Indoor Residual Spraying activity was significantly hampered due to a shortage of insecticides. Out of 44 enrolled and treated VL patients, two relapsed (4.5 %), two developed Para Kala-Azar Dermal Leishmaniasis (4.5 %), and three (6.8 %) Post Kala-Azar Dermal Leishmaniasis (PKDL). The health service providers highlighted patients` unwillingness to visit the hospital, financial constraints, and distance from the hospitals as the main reasons for missed follow-up visits (20.5 %). Building good communication in the community, awareness schemes, and incentive-based approaches were suggested as possible solutions to mitigate these problems., Conclusion: Long-term follow-up is required for the early detection and management of VL relapse and PKDL cases. Effective vector control measures, capacity development, and identification of new VL hotspots are pivotal in the VL endemic regions to sustain the elimination goal., Competing Interests: Declaration of Competing Interest We have no conflict of interest to declare., (Copyright © 2023. Published by Elsevier Ltd.)

Membrane efflux pumps play a major role in bacterial multidrug resistance. The tripartite multidrug efflux pump system from Escherichia coli, AcrAB-TolC, is a target for inhibition to lessen resistance development and restore antibiotic efficacy, with homologs in other ESKAPE pathogens. Here, we rationalize a mechanism of inhibition against the periplasmic adaptor protein, AcrA, using a combination of hydrogen/deuterium exchange mass spectrometry, cellular efflux assays, and molecular dynamics simulations. We define the structural dynamics of AcrA and find that an inhibitor can inflict long-range stabilisation across all four of its domains, whereas an interacting efflux substrate has minimal effect. Our results support a model where an inhibitor forms a molecular wedge within a cleft between the lipoyl and αβ barrel domains of AcrA, diminishing its conformational transmission of drug-evoked signals from AcrB to TolC. This work provides molecular insights into multidrug adaptor protein function which could be valuable for developing antimicrobial therapeutics., (© 2023. The Author(s).)

In this work, we address the problem of detecting anomalies in a certain laboratory automation setting. At first, we collect video images of liquid transfer in automated laboratory experiments. We mimic the real-world challenges of developing an anomaly detection model by considering two points. First, the size of the collected dataset is set to be relatively small compared to large-scale video datasets. Second, the dataset has a class imbalance problem where the majority of the collected videos are from abnormal events. Consequently, the existing learning-based video anomaly detection methods do not perform well. To this end, we develop a practical human-engineered feature extraction method to detect anomalies from the liquid transfer video images. Our simple yet effective method outperforms state-of-the-art anomaly detection methods with a notable margin. In particular, the proposed method provides 19% and 76% average improvement in AUC and Equal Error Rate, respectively. Our method also quantifies the anomalies and provides significant benefits for deployment in the real-world experimental setting., 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 © 2023 Sarker, Hakim, Dabouei, Uddin, Freyberg, MacWilliams, Kangas and Xu.)

Cryo-electron tomography can uniquely probe the native cellular environment for macromolecular structures. Tomograms feature complex data with densities of diverse, densely crowded macromolecular complexes, low signal-to-noise, and artifacts such as the missing wedge effect. Post-processing of this data generally involves isolating regions or particles of interest from tomograms, organizing them into related groups, and rendering final structures through subtomogram averaging. Template-matching and reference-based structure determination are popular analysis methods but are vulnerable to biases and can often require significant user input. Most importantly, these approaches cannot identify novel complexes that reside within the imaged cellular environment. To reliably extract and resolve structures of interest, efficient and unbiased approaches are therefore of great value. This review highlights notable computational software and discusses how they contribute to making automated structural pattern discovery a possibility. Perspectives emphasizing the importance of features for user-friendliness and accessibility are also presented., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Monkeypox has become a significant global challenge as the number of cases increases daily. Those infected with the disease often display various skin symptoms and can spread the infection through contamination. Recently, Machine Learning (ML) has shown potential in image-based diagnoses, such as detecting cancer, identifying tumor cells, and identifying coronavirus disease (COVID)-19 patients. Thus, ML could potentially be used to diagnose Monkeypox as well. In this study, we developed a Monkeypox diagnosis model using Generalization and Regularization-based Transfer Learning approaches (GRA-TLA) for binary and multiclass classification. We tested our proposed approach on ten different convolutional Neural Network (CNN) models in three separate studies. The preliminary computational results showed that our proposed approach, combined with Extreme Inception (Xception), was able to distinguish between individuals with and without Monkeypox with an accuracy ranging from 77% to 88% in Studies One and Two, while Residual Network (ResNet)-101 had the best performance for multiclass classification in Study Three, with an accuracy ranging from 84% to 99%. In addition, we found that our proposed approach was computationally efficient compared to existing TL approaches in terms of the number of parameters (NP) and Floating-Point Operations per Second (FLOPs) required. We also used Local Interpretable Model-Agnostic Explanations (LIME) to explain our model's predictions and feature extractions, providing a deeper understanding of the specific features that may indicate the onset of Monkeypox., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 Elsevier Ltd. All rights reserved.)

The reproductive stage of cotton ( Gossypium sp.) is highly sensitive to waterlogging. The identification of potential elite upland cotton ( Gossypium hirsutum ) cultivar(s) having higher waterlogging tolerance is crucial to expanding cotton cultivation in the low-lying areas. The present study was designed to investigate the effect of waterlogging on the reproductive development of four elite upland cotton cultivars, namely, Rupali-1, CB-12, CB-13, and DM-3, against four waterlogging durations (e.g., 0, 3, 6, and 9-day). Waterlogging stress significantly impacted morpho-physiological, biochemical, and yield attributes of cotton. Two cotton cultivars, e.g., CB-12 and Rupali-1, showed the lowest reduction in plant height (6 and 9%, respectively) and boll weight (8 and 5%, respectively) at the highest waterlogging duration of 9 days. Physiological and biochemical data revealed that higher leaf chlorophyll, proline, and relative water contents, and lower malondialdehyde contents, particularly in CB-12 and Rupali-1, were positively correlated with yield. Notably, CB-12 and Rupali-1 had higher seed cotton weight (90.34 and 83.10 g, respectively), lint weight (40.12 and 39.32 g, respectively), and seed weight (49.47 and 43.78 g, respectively) per plant than CB-13 and DM-3 in response to the highest duration of waterlogging of 9 days. Moreover, extensive multivariate analyses like Spearman correlation and the principle component analysis revealed that CB-12 and Rupali-1 had greater coefficients in yield and physiological attributes at 9-day waterlogging, whereas CB-13 and DM-3 were sensitive cultivars in response to the same levels of waterlogging. Thus, CB-12 and Rupali-1 might be well adapted to the low-lying waterlogging-prone areas for high and sustained yield.

T cell-centric immunotherapies have shown modest clinical benefit thus far for estrogen receptor-positive (ER + ) breast cancer. Despite accounting for 70% of all breast cancers, relatively little is known about the immunobiology of ER + breast cancer in women with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC). To investigate this, we performed phenotypic, transcriptional and functional analyses for a cohort of treatment-naive IDC (n = 94) and ILC (n = 87) tumors. We show that macrophages, and not T cells, are the predominant immune cells infiltrating the tumor bed and the most transcriptionally diverse cell subset between IDC and ILC. Analysis of cellular neighborhoods revealed an interplay between macrophages and T cells associated with longer disease-free survival in IDC but not ILC. Our datasets provide a rich resource for further interrogation into immune cell dynamics in ER + IDC and ILC and highlight macrophages as a potential target for ER + breast cancer., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Introduction: Few studies have reported antibiotic purchases from retail drug shops in relation to gender in low and middle-income countries (LMICs). Using a One Health approach, we aimed to examine gender dimensions of antibiotic purchases for humans and animals and use of prescriptions in retail drug shops in Bangladesh., Methods: We conducted customer observations in 20 drug shops in one rural and one urban area. Customer gender, antibiotic purchases, and prescription use were recorded during a four-hour observation (2 sessions of 2 hours) in each shop. We included drug shops selling human medicine (n = 15); animal medicine (n = 3), and shops selling both human and animal medicine (n = 2)., Results: Of 582 observations, 31.6% of drug shop customers were women. Women comprised almost half of customers (47.1%) in urban drug shops but only 17.2% of customers in rural drug shops (p < 0.001). Antibiotic purchases were more common in urban than rural shops (21.6% versus 12.2% of all transactions, p = 0.003). Only a quarter (26.0%) of customers who purchased antibiotics used a prescription. Prescription use for antibiotics was more likely among women than men (odds ratio (OR) = 4.04, 95% CI 1.55, 10.55) and more likely among urban compared to rural customers (OR = 4.31 95% CI 1.34, 13.84). After adjusting for urban-rural locality, women remained more likely to use a prescription than men (adjusted OR = 3.38, 95% CI 1.26, 9.09) but this was in part due to antibiotics bought by men for animals without prescription. Customers in drug shops selling animal medicine had the lowest use of prescriptions for antibiotics (4.8% of antibiotic purchases)., Conclusion: This study found that nearly three-quarters of all antibiotics sold were without prescription, including antibiotics on the list of critically important antimicrobials for human medicine. Men attending drug shops were more likely to purchase antibiotics without a prescription compared to women, while women customers were underrepresented in rural drug shops. Antibiotic stewardship initiatives in the community need to consider gender and urban-rural dimensions of drug shop uptake and prescription use for antibiotics in both human and animal medicine. Such initiatives could strengthen National Action Plans., (© 2023. The Author(s).)

The scarcity of freshwater in most of the megacities in the world is an important concern. In this regard, scientifically harvested rainwater could provide an effective measure to this crisis. In this attempt, we developed a cost-effective sensor-based automated first-flush rainwater harvesting system (RHS) to improve the freshwater scarcity and economic development of megacities like Dhaka, Bangladesh. To investigate the performance of the developed system, a suit of representative rainwater samples was systematically collected, preserved, and assessed between the months of July-December 2021 for water quality parameters such as physicochemical (pH, EC, TDS, DO, hardness, and alkalinity), anions (F - , Cl - , NO 2 - , NO 3 - , Br - , and SO 4 2- ), elemental (Ca, Mg, Cr, As, Cd, Hg, Pb, Be, Ni, Se, and Fe), and microbial contamination analysis. A Multiparameter digital meter and a titrimetric method were employed for measuring the physicochemical properties whereas elemental concentration was detected using an inductively coupled plasma-mass spectrometer and atomic absorption spectrometer. The changes in microbial contamination in the preserved rainwater were investigated from time to time during the whole experimental period. The findings showed that the mean pH (6.90) and concentrations (mg/L) of other concerning parameters such as TDS (15.5), DO (7.26), hardness (14.9), Cl - (3.59), NO 3 - (4.84), SO 4 2- (4.62), Fe (<0.2), Cr (0.086 μg/L), As (0.224 μg/L), Cd (0.260 μg/L), Hg (0.270 μg/L), and Pb (5.530 μg/L) in the harvested rainwater samples were below the WHO drinking water guidelines and literature data implying that the harvested rainwater derived from the developed RHS is completely safe for drinking and other uses even in respect to the microbial contamination (total bacterial counts: 0-15 CFU/mL, and total and fecal coliform less than 1.8 MPN/100 mL) for long storage. Hence, this technology has a huge opportunity to mitigate safe freshwater scarcity and groundwater depletion issues, especially in megacities such as Dhaka, Bangladesh., (© 2023 The Authors.)

Background: Flavonols are phytoconstituents of biological and medicinal importance. In addition to functioning as antioxidants, flavonols may play a role in antagonizing diabetes, cancer, cardiovascular disease, and viral and bacterial diseases. Quercetin, myricetin, kaempferol, and fisetin are the major dietary flavonols. Quercetin is a potent scavenger of free radicals, providing protection from free radical damage and oxidation-associated diseases., Main Body of the Abstract: An extensive literature review of specific databases (e.g., Pubmed, google scholar, science direct) were conducted using the keywords "flavonol," "quercetin," "antidiabetic," "antiviral," "anticancer," and "myricetin." Some studies concluded that quercetin is a promising antioxidant agent while kaempferol could be effective against human gastric cancer. In addition, kaempferol prevents apoptosis of pancreatic beta-cells via boosting the function and survival rate of the beta-cells, leading to increased insulin secretion. Flavonols also show potential as alternatives to conventional antibiotics, restricting viral infection by antagonizing the envelope proteins to block viral entry., Short Conclusion: There is substantial scientific evidence that high consumption of flavonols is associated with reduced risk of cancer and coronary diseases, free radical damage alleviation, tumor growth prevention, and insulin secretion improvement, among other diverse health benefits. Nevertheless, more studies are required to determine the appropriate dietary concentration, dose, and type of flavonol for a particular condition to prevent any adverse side effects., Competing Interests: Competing interestsThe authors declare that there are no competing interests., (© The Author(s) 2023.)

The rapidly declining fossil fuels are no longer able to meet the ever-increasing energy demand. Moreover, they are considered responsible for greenhouse gas (GHG) emission, contributing to the global warming. On the other hand, organic wastes, such as kitchen waste (KW) and poultry manure (PM), represent considerable pollution threat to the environment, if not properly managed. Therefore, anaerobic co-digestion of KW and PM could be a sustainable way of producing clean and renewable energy in the form of biogas while minimizing environmental impact. In this study, the anaerobic co-digestion of KW with PM was studied to assess the rate of cumulative biogas (CBG) production and methane percentage in four digester setups (D1, D2, D3, and D4) operated in batch mode. Each digester setup consisted of five parallelly connected laboratory-scale digesters having a capacity of 1 L each. The digester setups were fed with KW and PM at ratios of 1:0 (D1), 1:1 (D2), 2:1 (D3), and 3:1 (D4) at a constant loading rate of 300 mg/L with 50 gm cow manure (CM) as inoculum and were studied at both room temperature (28 °C) and mesophilic temperature (37 °C) over 24 days. The co-digestion of KW with PM demonstrated a synergistic effect which was evidenced by a 16% and 74% increase in CBG production and methane content, respectively, in D2 over D1. The D3 with 66.7% KW and 33.3% PM produced the highest CBG and methane percentage (396 ± 8 mL and 36%) at room temperature. At mesophilic condition, all the digesters showed better performance, and the highest CBG (920 ± 11 mL) and methane content (48%) were observed in D3. The study suggests that co-digestion of KW and PM at mesophilic condition might be a promising way to increase the production of biogas with better methane composition by ensuring nutrient balance, buffering capacity, and stability of the digester., Competing Interests: Conflict of interestThe authors declare no competing interests., (© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.)

Objectives: This research aimed to isolate, identify, and characterize a new strain of Bacillus cereus through different molecular biology approaches so that it could be further studied for therapeutic purposes against selective enteric pathogens., Materials and Methods: Pure isolates of B. cereus were prepared from buffalo yogurt samples in REMBA medium. Initially, the morphological, physiological, and biochemical properties were studied accordingly. Following the tests, the molecular identification for the strain identification was conducted through plasmid DNA extraction, PCR, agarose gel electrophoresis, and 16S rRNA sequencing up to 1.37 kb. Afterward, the antibiotic sensitivity [Epsilometer test (E-Test)] and antifungal activity were tested considering different concentrations. Being classified from the aforementioned tests, a comprehensive antimicrobial activity test was conducted using the cell-free-supernatant (CFS) of the test strain against selective enteric pathogens in humans in vitro . Besides, the different clusters of genes were identified and characterized for understanding the presumptive bacteriocins present in the CFS of the strain in silico, where molecular string properties were calculated. Finally, the evolutionary relationship among diversified bacteriocins synthesized by different Bacillus strains was studied to predict the CFS-containing bacteriocins of the new strain., Results: Purified isolates of B. cereus were Gram-positive rods and showed significant tolerance ( p < 0.0001) to different concentrations of pH, phenol, bile salt, and NaCl. 16S rRNA revealed the strain as LOCK 1002, which was strongly sensitive to all the antibiotics used and resistant to selective antifungal agents. The CFS of B. cereus LOCK 1002 was found to be a very promising antagonist to all the enteric pathogens used in the culture condition. Two gene clusters were predicted to be interconnected and responsible for different presumptive bacteriocins., Conclusion: The newly identified LOCK 1002 can be a very potent strain of B. cereus in use as an antimicrobial agent for having different bacteriocin coding gene clusters., Competing Interests: The authors are free from any type of competing intentions with others. The authors are very cordial to publish this manuscript and the consent is clear., (Copyright: © Journal of Advanced Veterinary and Animal Research.)

Nitrogen (N) is a highly essential macronutrient for plant root growth and grain yield (GY). To assess the relationship among N, root traits, and the yield of boro (dry season irrigated) rice, a pot experiment was performed in the Department of Agronomy, Bangladesh Agricultural University, Mymensingh, Bangladesh, during the boro rice season of 2020-2021. Three boro rice varieties, namely BRRI dhan29, Hira-2, and Binadhan-10, were planted at four N doses: 0 kg ha -1 (N 0 ), 70 kg ha -1 (N 70 ), 140 kg ha -1 (N 140 ), and 210 kg ha -1 (N 210 ). The experiment was conducted following a completely randomized design with three replicates. The varieties were evaluated for root number (RN), root length (RL), root volume (RV), root porosity (RP), leaf area index (LAI), total dry matter (TDM), and yield. The results indicated that the Binadhan-10, Hira-2, and BRRI dhan29 varieties produced better root characteristics under at the N 140 and N 210 levels. A substantial positive association was noticed between the grain yield and the root traits, except for root porosity. Based on the root traits and growth dynamics, Binadhan-10 performed the best at the N 140 level and produced the highest grain yield (26.96 g pot -1 ), followed by Hira-2 (26.35 g pot -1 ) and BRRI dhan29 (25.90 g pot -1 )., Competing Interests: The authors declare no conflict of interest.

The dataset of Bangladeshi sign language words (BdSLW) is rare. Though there are lots of datasets of BdSL sign alphabets, numbers, or characters, there are not enough datasets of sign words. This is the first dataset about sign words of BdSL according to the author(s) knowledge. So, this dataset is developed by collecting data from people. This is an image dataset. This dataset is a collection of 1105 images of sign words. A total of 11 sign word categories are selected which are important and daily use in our life. As this is an image dataset, so the images of sign words are taken by camera from the sign users of Bangladesh. Authors have gone to the individuals of sign users and captured images from them with their permission. Then the images are analyzed and segmented into the images which have quality such as no background, clear, bright, etc. This dataset is used for recognizing BdSL sign words., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

Aims: Psychrotrophs are extremophilic microorganisms that grow optimally in low temperature having many unique bioactive molecules of biotechnological applications. In this study, we characterized a pigment from an arctic bacterium with protective activity towards UV exposure., Methods and Results: The present research reports isolation and characterization of a psychrotrophic bacteria, RSAP2, from the soil sample of NyAlesund (78°56"N, 11°54"E), Svalbard, Norway. The strain showed closest 16S rRNA gene sequence similarity (99.9%) with Kocuria indica NIO-1021. RSAP2 is a Gram-positive, coccoid aerobe which produces a yellow pigment. The optimal parameters for pigment production while grown in LB medium were 3% (w/v) NaCl and 4 days of incubation of the culture at 20°C and pH 9 with shaking (180 rpm). The pigment was extracted in methanol and acetone (2:1) and further purified through column chromatography. It was characterized by mass spectrometry, UV-visible, fluorescence, IR, 1 H NMR, 13 C NMR spectroscopy and CHNS/O analysis. The pigment has a molecular weight of about 258 daltons and the molecular formula was determined as C 15 H 18 N 2 O 2 and is a quinoline derivative. We show that the pigment can protect Escherichia coli against UV-mediated mutagenesis. We further demonstrate that the pigment displays a significant antimicrobial effect and in sublethal concentrations it impairs biofilm formation ability of the model organism Staphylococcus aureus., Conclusions: The pigment of a psychrotrophic Arctic bacterium, most likely a strain of K. indica, was purified and its chemical structure was determined. The quinoline-based pigment has the ability to protect live cells from UV induced damage., Significance and Impact of Study: Analysis and characterization of this newly isolated quinoline-based pigment is a potential candidate for future application in skin care products., (© 2022 Society for Applied Microbiology.)

Optimization of compound permeation into Gram-negative bacteria is one of the most challenging tasks in the development of antibacterial agents. Two permeability barriers─the passive diffusion barrier of the outer membrane (OM) and active drug efflux─act synergistically to protect cells from the antibacterial action of compounds. In Escherichia coli ( E. coli ) and relatives, these two barriers sieve compounds based on different physicochemical properties that are defined by their interactions with OM porins and efflux pumps, respectively. In this study, we critically tested the hypothesis that the best substrates and inhibitors of efflux pumps are compounds that can effectively permeate the OM and are available at relatively high concentrations in the periplasm. For this purpose, we filtered a large subset of the ZINC15 database of commercially available compounds for compounds containing a primary amine, a chemical feature known to facilitate the uptake through E. coli general porins. The assembled library was screened by ensemble docking to AcrA, the periplasmic component of the AcrAB-TolC efflux pump, followed by experimental testing of the top predicted binders for antibacterial activities, efflux recognition, and inhibition. We found that the filtered primary amine library is a rich source of compounds with efflux-inhibiting activities and identified efflux pump inhibitors with novel chemical scaffolds effective against E. coli AcrAB-TolC and efflux pumps of multidrug-resistant clinical isolates of Acinetobacter baumannii . However, primary amines are not required for the recognition of compounds by efflux pumps and their efflux-inhibitory activities.

Cryo-Electron Tomography (cryo-ET) is an emerging 3D imaging technique which shows great potentials in structural biology research. One of the main challenges is to perform classification of macromolecules captured by cryo-ET. Recent efforts exploit deep learning to address this challenge. However, training reliable deep models usually requires a huge amount of labeled data in supervised fashion. Annotating cryo-ET data is arguably very expensive. Deep Active Learning (DAL) can be used to reduce labeling cost while not sacrificing the task performance too much. Nevertheless, most existing methods resort to auxiliary models or complex fashions (e.g. adversarial learning) for uncertainty estimation, the core of DAL. These models need to be highly customized for cryo-ET tasks which require 3D networks, and extra efforts are also indispensable for tuning these models, rendering a difficulty of deployment on cryo-ET tasks. To address these challenges, we propose a novel metric for data selection in DAL, which can also be leveraged as a regularizer of the empirical loss, further boosting the task model. We demonstrate the superiority of our method via extensive experiments on both simulated and real cryo-ET datasets. Our source Code and Appendix can be found at this URL .

Understanding the link between root morphological traits and yields is crucial for improving crop management. To evaluate this link, a pot experiment was conducted in the net house of the Department of Agronomy, Bangladesh Agricultural University, Mymensingh, Bangladesh during the boro (dry season irrigated) rice growing season of 2019-20. Thirteen cultivars, named BRRI dhan29, BRRI dhan58, BRRI dhan67, BRRI dhan74, BRRI dhan81, Binadhan-8, Binadhan-10, Hira-2, Tej gold, SL8H, Jagliboro, Rata boro, and Lakhai, were used following a completely randomized design (CRD) with three replications. The cultivars were screened for root number (RN), root length (RL), root volume (RV), root porosity (RP), leaf area index (LAI), total dry matter (TDM), and grain yield (GY). A considerable variation in root traits, LAI, and TDM were found among the studied cultivars, and the highest GY (26.26 g pot -1 )was found for Binahan-10. Thirteen cultivars were grouped into three clusters using hierarchical cluster analysis, where clusters 1, 2, and 3 assembled with 3, 5, and 5 cultivars, respectively. Considering all of the studied traits, Cluster 3 (Binadhan-10, Hira-2, BRRI dhan29, BRRI dhan58, and Tejgold) showed promise, followed by Cluster 2 (BRRI dhan81, BRRI dhan67, SL8H, BRRI dhan74, and Binadhan-8). Principal component analysis (PCA) revealed that the RV, RDW, RFW, TDM, and GY are effective traits for rice cultivation.

Background The coronavirus disease 2019 (COVID-19) disease triggered a worldwide health catastrophe. To deal with this deadly situation multiple vaccines were developed and a mass immunization program started globally. However, vaccine hesitancy was seen, especially among women of reproductive age, having concerns that the vaccine might affect their menstrual cycle. This study investigated the link between COVID-19 vaccination and menstrual abnormalities. It is essential for us to understand the effects of vaccines on menstruation as menstrual distress can have effects on everyday life, and mental and reproductive health. Methods A cross-sectional study was performed using self-administered online forms to collect data from all over Karachi. The sample included 384 females aged 18 years and above. The data were collected from November 2021 to February 2022. Results Majority of the participants were aged 21 years and had a normal body mass index (BMI). Most were moderately stressed (n=245) with 146 reporting menstrual changes post-vaccination. The difference between the post-vaccine menstruation affected (n=146) and the unaffected cohort (n=238) was significant. Other factors which likely contributed to the post-vaccine menstrual changes included Perceived Stress Scale (PSS) score, strenuous physical activity, and the pre-vaccine menstrual flow. Conclusions Among the women vaccinated for COVID-19, strenuous physical activity and high perceived stress levels affected the menstrual cycle. There is no denying that existing data are inadequate, which is one of the grounds for vaccination apprehension, particularly among menstruating women. To minimize this hesitation, the spread of disinformation about the vaccine's influence on the menstrual cycle must be avoided. In future research and clinical trials, menstruation-related side effects should also be investigated when developing vaccines., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2022, Sualeh et al.)

Macromolecular structure classification from cryo-electron tomography (cryo-ET) data is important for understanding macro-molecular dynamics. It has a wide range of applications and is essential in enhancing our knowledge of the sub-cellular environment. However, a major limitation has been insufficient labelled cryo-ET data. In this work, we use Contrastive Self-supervised Learning (CSSL) to improve the previous approaches for macromolecular structure classification from cryo-ET data with limited labels. We first pretrain an encoder with unlabelled data using CSSL and then fine-tune the pretrained weights on the downstream classification task. To this end, we design a cryo-ET domain-specific data-augmentation pipeline. The benefit of augmenting cryo-ET datasets is most prominent when the original dataset is limited in size. Overall, extensive experiments performed on real and simulated cryo-ET data in the semi-supervised learning setting demonstrate the effectiveness of our approach in macromolecular labeling and classification., 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 Gupta, He, Uddin, Zeng, Zhou, Zhang, Freyberg and Xu.)

Data breaches have become a formidable challenge for business operations in the twenty-first century. The emergence of big data in the ever-growing digital economy has created the necessity to secure critical organizational information. The lack of cybersecurity awareness exposes organizations to potential cyber threats. Thus, this research aims to identify the various dimensions of cybersecurity awareness capabilities. Drawing on the dynamic capabilities framework, the findings of the study show personnel (knowledge, attitude and learning), management (training, culture and strategic orientation) and infrastructure capabilities (technology and data governance) as thematic dimensions to tackle cybersecurity awareness challenges., (© The Author(s) 2022.)

The revolutionary technique cryoelectron tomography (cryo-ET) enables imaging of cellular structure and organization in a near-native environment at submolecular resolution, which is vital to subsequent data analysis and modeling. The conventional structure detection process first reconstructs the three-dimensional (3D) tomogram from a series of two-dimensional (2D) projections and then directly detects subcellular components found within the tomogram. However, this process is challenging due to potential structural information loss during the tomographic reconstruction and the limited scope of existing methods since most major state-of-the-art object detection methods are designed for 2D rather than 3D images. Therefore, in this article, as an alternative approach to complement the conventional process, we propose a novel 2D-to-3D framework that detects structures within 2D projection images before reconstructing the results back to 3D. We implemented the proposed framework as three specific algorithms for three individual tasks: semantic segmentation, edge detection, and object localization. As experimental validation of the 2D-to-3D framework for cryo-ET data, we applied the algorithms to the segmentation of mitochondrial calcium phosphate granules, detection of spherical edges, and localization of mitochondria. Quantitative and qualitative results show better performance for prediction tasks of segmentation on the 2D projections and promising performance on object localization and edge detection, paving the way for future studies in the exploration of cryo-ET for in situ structural biology.

Silicon (Si) application has great potential to improve salt tolerance in a variety of crop plants. However, it is unclear how Si influences the responses of contrasting rice cultivars when exposed to excessive salt. Here, we investigated the functions of Si in alleviating the negative effects of salt stress on two contrasting rice cultivars, namely BRRI dhan48 (salt-sensitive) and Binadhan-10 (salt-tolerant). Rice seedlings was pre-treated with three doses of Si (as silicic acid; 0, 1 and 2 mM) for 14 days at one-day interval before being exposed to salt stress (10 dSm -1 ) in a sustained water bath system. The results demonstrated that the seedlings of BRRI dhan48 and Binadhan-10, respectively exhibited substantial reductions in shoot height (16 and 9%), shoot fresh weight (64 and 43%) and shoot dry weight (50 and 39%) under salinity. Intriguingly, BRRI dhan48 pre-treated with 1 and 2 mM Si, respectively, showed a higher increase in shoot height (SH) (by 25.90 and 26.08%) as compared with Binadhan-10 (by 3 and 8%) under salt stress compared with their respective controls. Data revealed that a comparatively higher improvement in the growth performances of the salt-induced Si pre-treated BRRI dhan48 than that of Binadhan-10. For example, 1 and 2 mM of Si treatments significantly attributed to elevated leaf relative water content (RWC) (13 and 22%), proline (138 and 165%), chlorophyll a (42 and 44%), chlorophyll b (91 and 72%), total chlorophyll (58 and 53%) and carotenoids (33 and 29%), and recovery in the reductions of electrolyte leakage (13 and 21%), malondialdehyde content (23 and 30%) and shoot Na + /K + ratio (22 and 52%) in BRRI dhan48 compared with Si-untreated control plants under salt stress. In addition, we found salt-tolerant Binadhan-10 also had enhanced RWC (9 and 19%), proline (12 and 26%) with pre-treatment with 1 and 2 mM of Si, respectively, under salt stress, while no significant differences were noticed in the case of photosynthetic pigments and Na + /K + ratio. Our results showed that Si supplementation potentiated higher salt-tolerance ability in the salt-sensitive BRRI dhan48 as compared with salt-tolerant Binadhan-10. Thus, Si application could be highly beneficial in the growth recovery of the salinity-affected salt-sensitive high yielding rice cultivars in the saline-prone areas.

This study investigates the Covid-19 driven indiscriminate disposal of PPE wastes (mostly face mask and medical wastes) in Chittagong metropolitan area (CMA), Bangladesh. Based on the field monitoring, the mean PPE density (PPE/m 2 ± SD) was calculated to be 0.0226 ± 0.0145, 0.0164 ± 0.0122, and 0.0110 ± 0.00863 for July, August, and September 2021, respectively (during the peak time of Covid-19 in Bangladesh). Moreover, gross information on PPE waste generation in the city was calculated using several parameters such as population density, face mask acceptance rate by urban population, total Covid-19 confirmed cases, quarantined and isolated patients, corresponding medical waste generation rate (kg/bed/day), etc. Moreover, the waste generated due to face mask and other PPEs in the CMA during the whole Covid-19 period (April 4, 2020 to September 5, 2021) were calculated to be 64183.03 and 128695.75 tons, respectively. It has been observed that the negligence of general people, lack of awareness about environmental pollution, and poor municipal waste management practices are the root causes for the contamination of the dwelling environment by PPE wastes. As a result, new challenges have emerged in solid waste management, which necessitates the development of an appropriate waste management strategy. The ultimate policies and strategies may help to achieve the SDG goals 3, 6, 11, 12, 13, and 15, and increase public perception on the use and subsequent disposal of PPEs, especially face masks., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

In many real-life image analysis applications, particularly in biomedical research domains, the objects of interest undergo multiple transformations that alters their visual properties while keeping the semantic content unchanged. Disentangling images into semantic content factors and transformations can provide significant benefits into many domain-specific image analysis tasks. To this end, we propose a generic unsupervised framework, Harmony, that simultaneously and explicitly disentangles semantic content from multiple parameterized transformations. Harmony leverages a simple cross-contrastive learning framework with multiple explicitly parameterized latent representations to disentangle content from transformations. To demonstrate the efficacy of Harmony, we apply it to disentangle image semantic content from several parameterized transformations (rotation, translation, scaling, and contrast). Harmony achieves significantly improved disentanglement over the baseline models on several image datasets of diverse domains. With such disentanglement, Harmony is demonstrated to incentivize bioimage analysis research by modeling structural heterogeneity of macromolecules from cryo-ET images and learning transformation-invariant representations of protein particles from single-particle cryo-EM images. Harmony also performs very well in disentangling content from 3D transformations and can perform coarse and fast alignment of 3D cryo-ET subtomograms. Therefore, Harmony is generalizable to many other imaging domains and can potentially be extended to domains beyond imaging as well.

Deterministic lateral displacement (DLD) is a microfluidic method for the continuous separation of particles based on their size. There is growing interest in using DLD for harvesting circulating tumor cells from blood for further assays due to its low cost and robustness. While DLD is a powerful tool and development of high-throughput DLD separation devices holds great promise in cancer diagnostics and therapeutics, much of the experimental data analysis in DLD research still relies on error-prone and time-consuming manual processes. There is a strong need to automate data analysis in microfluidic devices to reduce human errors and the manual processing time. In this work, a reliable particle detection method is developed as the basis for the DLD separation analysis. Python and its available packages are used for machine vision techniques, along with existing identification methods and machine learning models. Three machine learning techniques are implemented and compared in the determination of the DLD separation mode. The program provides a significant reduction in video analysis time in DLD separation, achieving an overall particle detection accuracy of 97.86% with an average computation time of 25.274 s.

This study is aimed to apply dry anaerobic digestion (DAD) for methane (CH 4 ) enriched biogas production from unsorted organic municipal solid waste (MSW). Cumulative biogas production was monitored for 35 days of operation in batch digesters at fixed feedstock to inoculum (F/I) ratio 2. Anaerobic sludge (AS) and cow manure (CM) were used as inoculum in single and mixed modes. Several process parameters such as inoculum flow pattern (single layer, multilayer, and spiral), digestion temperature (25 to 40 °C), inoculation modes (single and mixed mode), and inoculation proportion (AS:CM = 1:1, 1:2, 1:3, and 2:1) were investigated to determine the optimum DAD conditions to maximize the CH 4 laden biogas yield. The study of inoculum flow pattern showed that digester with multilayer inoculum configuration generated the maximum 555 mL cumulative biogas with the production rate of 195 mL/day (at 25 °C). Biogas production rate and cumulative biogas production were found to increase with a rise in temperature and the maximum values of 380 mL/day and 1515 mL respectively were observed at 37 °C. The mixed mode of inoculation containing AS and CM augmented the biogas yield at previously optimized conditions. Final results showed that digester with multilayer inoculum flow pattern at 37 °C produced 1850 mL cumulative biogas with 1256.58 mL CH 4 /kg volatile solid (VS) when the mixed inoculum was used at the AS:CM-1:2 ratio. Biogas production with this significant amount of CH 4 justifies the use of the DAD process for energy (biogas) generation from widely available biomass feedstock (MSW), offering various advantages to the environment., (© 2022. The Author(s).)

The present study focuses on the indiscriminate disposal of personal protective equipment (PPEs) and resulting environmental contamination during the 3rd wave of COVID-19-driven global pandemic in the Chittagong metropolitan area, Bangladesh. Because of the very high rate of infection by the delta variant of this virus, the use of PPEs by the public is increased significantly to protect the ingestion/inhalation of respiratory droplets in the air. However, it is a matter of solicitude that general people throw away the PPEs to the dwelling environment unconsciously. With the increase of inappropriate disposal of PPEs (i.e., mostly the disposable face masks made from plastic microfibers), the possibility of transmission of the virus to the general public cannot be neglected completely. This is because this virus can survive for several days on the inanimate matter like plastics and fibers. At the same time, the result of environmental contamination by microplastic/microfiber has been widespread which eventually creates the worst impact on ecosystems and organisms. The present results may help to increase public perception of the use and subsequent disposal of PPEs, especially the face masks., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)