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SCOPE: Inflammatory bowel disease (IBD) is a chronic intestinal inflammatory condition of unknown etiology, although recent evidence suggests that it is caused by an excessive immune response to mucosal antigens. We determined the anti-inflammatory properties of novel compound DJ-X-013 in vitro in lipopolysaccharide (LPS)-induced macrophages and in an in vivo dextran sodium sulfate (DSS)-induced model of colitis. METHODS AND RESULTS: To evaluate the anti-inflammatory properties of DJ-X-013, we used LPS-activated RAW 264.7 macrophages in vitro and a DSS-induced experimental model of colitis in vivo. We examine cellular morphology, and tissue architecture by histology, flow cytometry, RT-qPCR, multiplex, and immunoblot analysis to perform cellular and molecular studies. DJ-X-013 treatment altered cell morphology and expression of inflammatory cytokines in LPS-activated macrophages as compared to cells treated with LPS alone. DJ-X-013 also impeded the migration of RAW 264.7 macrophages by modulating cytoskeletal organization and suppressed the expression of NF-κB and inflammatory markers as compared to LPS alone. DJ-X-013 treatment improved body weight, and colon length and attenuated inflammation in the colon of DSS-induced colitis. Intriguingly, DSS-challenged mice treated with DJ-X-013 induced the numbers of myeloid-derived suppressor cells (MDSCs), dendritic cells (DCs), and natural killer T cells (NKT) in the colon lamina propria (LP) relative to DSS. DJ-X-013 also reduced the influx of neutrophils, TNF-α producing macrophages, restricted the number of Th17 cells, and suppressed inflammatory cytokines and NF-κB in the LP relative to DSS. CONCLUSION: DJ-X-013 is proposed to be a therapeutic strategy for ameliorating inflammation and experimental colitis.

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Technology integration is becoming pervasive in the polytechnic institutes of Bangladesh. Many institutions opted for a blended learning approach to deliver their education. This approach drives the transformation of education towards more digitalization and obliges students to thrive in using technology in the learning process. However, many students lack technical competency and more importantly are deprived of having modern devices in their households. In particular, how students perceive technology and how it affects their learning experience and satisfaction is crucial for effective learning. This area of research is still unexplored in the context of TVET Bangladesh. This study attempts to investigate what are the factors that affect the students' perceived satisfaction with the usage of technology and to what extent students are satisfied with the way technology is being used in their learning process. A quantitative research method using an online survey was conducted across Bangladesh and a total of 847 polytechnic students from 16 polytechnic institutes were recruited through non-probability convenience sampling technique. A structural equation modelling (SEM) and independent multivariate analysis of variance (MANOVA) were employed for the data analysis. The results revealed that self-efficacy positively influenced attitude, and attitude positively influenced social interaction. In contrast, attitude negatively influenced perceived satisfaction. This study can help educators implement strategies such as providing scaffolding, promoting self-directed learning, and commemorating student successes to build self-efficacy and a positive attitude towards technology acceptance.

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The groundwater (GW) resource plays a central role in securing water supply in the coastal region of Bangladesh and therefore the future sustainability of this valuable resource is crucial for the area. However, there is limited research on the driving factors and prediction of phosphate concentration in groundwater. In this work, geostatistical modeling, self-organizing maps (SOM) and data-driven algorithms were combined to determine the driving factors and predict GW phosphate content in coastal multi-aquifers in southern Bangladesh. The SOM analysis identified three distinct spatial patterns: K+Na+pH, Ca2+Mg2+NO3-, and HCO3-SO42-PO43-F-. Four data-driven algorithms, including CatBoost, Gradient Boosting Machine (GBM), Long Short-Term Memory (LSTM), and Support Vector Regression (SVR) were used to predict phosphate concentration in GW using 380 samples and 15 prediction parameters. Forecasting accuracy was evaluated using RMSE, R2, RAE, CC, and MAE. Phosphate dissolution and saltwater intrusion, along with phosphorus fertilizers, increase PO43- content in GW. Using input parameters selected by multicollinearity and SOM, the CatBoost model showed exceptional performance in both training (RMSE = 0.002, MAE = 0.001, R2 = 0.999, RAE = 0.057, CC = 1.00) and testing (RMSE = 0.001, MAE = 0.002, R2 = 0.989, RAE = 0.057, CC = 0.998). Na+, K+, and Mg2+ significantly influenced prediction accuracy. The uncertainty study revealed a low standard error for the CatBoost model, indicating robustness and consistency. Semi-variogram models confirmed that the most influential attributes showed weak dependence, suggesting that agricultural runoff increases the heterogeneity of PO43- distribution in GW. These findings are crucial for developing conservation and strategic plans for sustainable utilization of coastal GW resources.

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This study focuses on Bangladeshi university entrance test-taking students mental health problems and explores the geographical distribution of these problems using GIS technique. A cross-sectional survey was conducted among 1523 university entrance test-taking students. Data were collected on participants' socio-demographic characteristics, COVID-19-related factors, admission tests, depression, and anxiety. Chi-square tests and logistic regression were performed using SPSS software. GIS mapping was used to visualize the distribution of mental health problems across districts using ArcGIS. The study found that the prevalence rates of depression and anxiety among university entrance examinees were 53.8% and 33.2%, respectively. Males exhibited higher rates of depression and anxiety compared to females, while repeat test-taking students were more susceptible to these mental health issues compared to first-time test-takers. Factors such as urban residence, personal/familial COVID-19 infections, and COVID-19 deaths in close relationships were associated with increased mental health problems. District-based distribution showed no significant variation in depression, but anxiety varied significantly. Post-hoc GIS analysis revealed variations in the distribution of depression and anxiety among males, as well as variations in anxiety distribution based on student status across districts. This study emphasizes the high prevalence of depression and anxiety among university entrance examinees, emphasizing the importance of addressing mental health risks in this population. It also suggests the need for reforms in the university entrance test-taking system to reduce psychological problems and advocates for a more inclusive approach to student admissions to alleviate mental health burdens.

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Educational Data Mining (EDM) holds promise in uncovering insights from educational data to predict and enhance students' performance. This paper presents an advanced EDM system tailored for classifying and improving tertiary students' programming skills. Our approach emphasizes effective feature engineering, appropriate classification techniques, and the integration of Explainable Artificial Intelligence (XAI) to elucidate model decisions. Through rigorous experimentation, including an ablation study and evaluation of six machine learning algorithms, we introduce a novel ensemble method, Stacking-SRDA, which outperforms others in accuracy, precision, recall, f1-score, ROC curve, and McNemar test. Leveraging XAI tools, we provide insights into model interpretability. Additionally, we propose a system for identifying skill gaps in programming among weaker students, offering tailored recommendations for skill enhancement.

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Objectives: Household hygiene and food safety are essential parts of food security; better food safety and hygiene will help reduce the chances of illness for young children and family members rarely studied in the selected area of coastal Bangladesh. The study aimed to discover the knowledge, attitude, and practice levels for cleanliness, hygiene, and food safety in the household. Methods: In this study, we employed a cross-sectional survey with simple random sampling to collect data from 384 childbearing mothers. The survey used the pretested, validated, and standardized (knowledge, attitude, and practice) questionnaire-model-based interview guide. Results: According to our study analysis, the knowledge, attitude, and practice scores among mothers were inadequate for household cleanliness and hygiene management. In the area context, knowledge efficiency was related to family type (joint and nuclear). Family economic conditions strongly influenced mothers' attitudes and behavior toward knowledge, attitude, and practice score. Unemployed and illiterate mothers have lower knowledge, attitude, and practice scores. Educated mothers have better knowledge, attitude, and practice score compared to illiterate mothers (p < 0.014). Nuclear family knowledge, attitude, and practice attitude was much greater (p < 0.04) and wealthier families showed better practice (p < 0.001) toward cleanliness and food safety in the household level. Conclusions: The study discovered the mothers' and household members' attention need to improve the knowledge, attitude, and practice toward proper hygiene and food safety at the household level of marginalized populations in coastal Bangladesh.

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Cancer cells communicate within the tumor microenvironment (TME) through extracellular vesicles (EVs), which act as crucial messengers in intercellular communication, transporting biomolecules to facilitate cancer progression. Ubiquitin-like 3 (UBL3) facilitates protein sorting into small EVs as a post-translational modifier. However, the effect of UBL3 overexpression in EV-mediated protein secretion has not been investigated yet. This study aimed to investigate the effect of UBL3 overexpression in enhancing EV-mediated Achilles protein secretion in MDA-MB-231 (MM) cells by a dual-reporter system integrating Akaluc and Achilles tagged with Ubiquitin where self-cleaving P2A linker connects Akaluc and Achilles. MM cells stably expressing Ubiquitin-Akaluc-P2A-Achilles (Ubi-Aka/Achi) were generated. In our study, both the bioluminescence of Ubiquitin-Akaluc (Ubi-Aka) and the fluorescence of Achilles secretion were observed. The intensity of Ubi-Aka was thirty times lower, while the Achilles was four times lower than the intensity of corresponding cells. The ratio of Ubi-Aka and Achilles in conditioned media (CM) was 7.5. They were also detected within EVs using an EV uptake luciferase assay and fluorescence imaging. To investigate the effect of the UBL3 overexpression in CM, Ubi-Aka/Achi was transiently transfected into MM-UBL3-KO, MM, and MM-Flag-UBL3 cells. We found that the relative fluorescence expression of Achilles in CM of MM-UBL3-KO, MM, and MM-Flag-UBL3 cells was 30 %, 28 %, and 45 %, respectively. These findings demonstrated that UBL3 overexpression enhances EV-mediated Achilles protein secretion in CM of MM cells. Targeting UBL3 could lead to novel therapies for cancer metastasis by reducing the secretion of pro-metastatic proteins, thereby inhibiting disease progression.

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Optical fiber Raman and surface-enhanced Raman scattering (SERS) probes hold great promise for in vivo biosensing and in situ monitoring of hostile environments. However, the silica Raman scattering background generated within the optical fiber increases in proportion to the length of the fiber, and it can swamp the signal from the target analyte. While filtering can be applied at the distal end of the fiber, the use of bulk optical elements has limited probe miniaturization to a diameter of 600 µm, which in turn limits the potential applications. To overcome this limitation, femtosecond laser micromachining was used to fabricate a prototype micro-optical filter, which was directly integrated on the tip of a 125 µm diameter double-clad fiber (DCF) probe. The outer surface of the microfilter was further modified with a nanostructured, SERS-active, plasmonic film that was used to demonstrate proof-of-concept performance with thiophenol as a test analyte. With further optimization of the associated spectroscopic system, this ultra-compact microprobe shows great promise for Raman and SERS optical fiber sensing.

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Pathogen-responsive immune-related genes (resistance genes [R-genes]) and hormones are crucial mediators of systemic acquired resistance (SAR). However, their integrated functions in regulating SAR signaling components in local and distal leaves remain largely unknown. To characterize SAR in the Xanthomonas campestris pv. campestris (Xcc)-Brassica napus pathosystem, the responses of R-genes, (leaf and phloem) hormone levels, H2O2 levels, and Ca2+ signaling-related genes were assessed in local and distal leaves of plants exposed to four Xcc-treatments: Non-inoculation (control), only secondary Xcc-inoculation in distal leaves (C-Xcc), only primary Xcc-inoculation in local leaves (Xcc), and both primary and secondary Xcc-inoculation (X-Xcc). The primary Xcc-inoculation provoked disease symptoms as evidenced by enlarged destructive necrosis in the local leaves of Xcc and X-Xcc plants 7 days post-inoculation. Comparing visual symptoms in distal leaves 5 days post-secondary inoculation, yellowish necrotic lesions were clearly observed in non Xcc-primed plants (C-Xcc), whereas no visual symptom was developed in Xcc-primed plants (X-Xcc), demonstrating SAR. Pathogen resistance in X-Xcc plants was characterized by distinct upregulations in expression of the PAMP-triggered immunity (PTI)-related kinase-encoding gene, BIK1, the (CC-NB-LRR-type) R-gene, ZAR1, and its signaling-related gene, NDR1, with a concurrent enhancement of the kinase-encoding gene, MAPK6, and a depression of the (TIR-NB-LRR-type) R-gene, TAO1, and its signaling-related gene, SGT1, in distal leaves. Further, in X-Xcc plants, higher salicylic acid (SA) and jasmonic acid (JA) levels, both in phloem and distal leaves, were accompanied by enhanced expressions of the SA-signaling gene, NPR3, the JA-signaling genes, LOX2 and PDF1.2, and the Ca2+-signaling genes, CAS and CBP60g. However, in distal leaves of C-Xcc plants, an increase in SA level resulted in an antagonistic depression of JA, which enhanced only SA-dependent signaling, EDS1 and NPR1. These results demonstrate that primary Xcc-inoculation in local leaves induces resistance to subsequent pathogen attack by upregulating BIK1-ZAR1-mediated synergistic interactions with SA and JA signaling as a crucial component of SAR.

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The gig economy (temporary, contract, and freelance online jobs rather than permanent positions) is a component of the fourth industrial revolution and preview of future work. The rise of digital platforms has increased career opportunities and income potential, particularly for women. Yet, the sex-disaggregated evidence regarding platform usage, employment characteristics, and working motivations and satisfaction remains untapped. Using data from a quantitative survey of Bangladeshi gig workers (242 men and 201 women) conducted in 2022, this paper addresses these gaps between male and female workers. The gig economy appears to be gender-segregated across digital platform usages and working categories. Women tend to prioritize digital work options for managing multiple responsibilities, while men are often driven by the potential for higher income. This study conceptually utilized the two-factor theory and empirically ordered a probit model to identify gender differences in job satisfaction. Job satisfaction was significantly increased by work-life balance, monthly income, and social-media connection, while an increase in working hours, complexity in payment systems, and unstable networks all led to a decrease in job satisfaction. The findings have implications for the future growth of the gig economy, provide new insights into gender differences in job satisfaction, and underscore the need for gender-sensitive policies in the online labor market.

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Mass spectrometry imaging (MSI) is essential for visualizing drug distribution, metabolites, and significant biomolecules in pharmacokinetic studies. This study mainly focuses on imipramine, a tricyclic antidepressant that affects endogenous metabolite concentrations. The aim was to use atmospheric pressure matrix-assisted laser desorption/ionization (AP-MALDI)-MSI combined with different dimensionality reduction methods to examine the distribution and impact of imipramine on endogenous metabolites in the brains of treated wild-type mice. Brain sections from both control and imipramine-treated mice underwent AP-MALDI-MSI. Dimensionality reduction methods, including principal component analysis, multivariate curve resolution, and sparse autoencoder (SAE), were employed to extract valuable information from the MSI data. Only the SAE method identified phosphorylcholine (ChoP) as a potential marker distinguishing between the control and treated mice brains. Additionally, a significant decrease in ChoP accumulation was observed in the cerebellum, hypothalamus, thalamus, midbrain, caudate putamen, and striatum ventral regions of the treated mice brains. The application of dimensionality reduction methods, particularly the SAE method, to the AP-MALDI-MSI data is a novel approach for peak selection in AP-MALDI-MSI data analysis. This study revealed a significant decrease in ChoP in imipramine-treated mice brains.

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Vertically aligned ZnO nanorods (NRs) were grown hydrothermally on the wide bandgap (∼3.86 - 4.04 eV) seed layers (SLs) of grain size ∼162 ± 35 nm, prepared using ball-milled derived ZnO powder. The synthesized ZnO NRs were further decorated with ZnS nanocrystals to achieve a ZnO NR-ZnS core-shell (CS)-like nano-scaffolds by a subsequent hydrothermal synthesis at 70 °C for 1 h. UV-Vis-NIR spectroscopy, x-ray diffractometry (XRD), Raman spectroscopy and Field emission scanning electron microscopy (FESEM) coupled with Energy dispersive x-ray spectroscopy (EDX) analyses confirmed the formation of ZnS atop the vertically aligned ZnO NR arrays of ∼1.79 ± 0.17µm length and ∼165 ± 27 nm diameter. Transmission electron microscopy (TEM)/EDX analyses revealed that vertically aligned ZnO NRs (core dia. ∼181 ± 12 nm) arrays are conformally coated by an ultrathin ZnS (∼25 ± 7 nm) shell layer with a preferential ZnS{111}/ZnO{10-10}-like partial epitaxy. The ZnO NRs exhibited a sharp band edge near ∼384 nm having optical bandgap energy (Eg) of ∼3.23 eV. However, the ZnO NR-ZnS CS exhibited double absorption bands atEg∼ 3.20 eV (ZnO-core) andEg∼ 3.78 eV (ZnS-shell). The ZnS{111}/ZnO{10-10}-nano-scaffolds could be utilized to facilitate the enhanced absorption of UV photons as well as the radial junction formation between the Pb-free perovskite absorber and ZnS/ZnO NRs layers.

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This study analyzed spatiotemporal variation and long-term trends in water quality indicators and trophic state conditions in an Asian temperate reservoir, Juam Reservoir (JR), and developed models that forecast algal chlorophyll (CHL-a) over a period of 30 years, 1993-2022. The analysis revealed that there were longitudinal gradients in water quality indicators along the reservoir, with notable influences from tributaries and seasonal variations in nutrient regimes and suspended solids. The empirical model showed phosphorus was found to be the key determinant of algal biomass, while suspended solids played a significant role in regulating water transparency. The trophic state indices indicated varying levels of trophic status, ranging from mesotrophic to eutrophic. Eutrophic states were particularly observed in zones after the summer monsoons, indicating a heightened risk of algal blooms, which were more prevalent in flood years. The analysis of trophic state index deviation suggested that phosphorus availability strongly influences the reservoir trophic status, with several episodes of non-algal turbidity at each site during Mon. Increases in non-algal turbidity were more prevalent during the monsoon in flood years. This study also highlighted overall long-term trends in certain water quality parameters, albeit with indications of shifting pollution sources towards non-biodegradable organic matter. According to the machine learning tests, a random forest (RF) model strongly predicted CHL-a (R2 = 0.72, p < 0.01), except for algal biomass peaks (>60 µg/L), compared to all other models. Overall, our research suggests that CHL-a and trophic variation are primarily regulated by the monsoon intensity and predicted well by the machine learning RF model.

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Introduction: Cardiovascular diseases (CVDs) stand as the foremost contributor to global mortality, claiming roughly 17.9 million lives each year, constituting 32.1% of total fatalities. Their impact is notably profound in economies such as Bangladesh, exacting a substantial economic burden. Consequently, grasping the landscape of knowledge, attitudes, and practices is essential for timely identification and prevention strategies. Methods: This cross-sectional study, carried out between January and May 2023 in the rural regions of Zirani, Savar Upazila, Dhaka, Bangladesh, utilized convenient sampling and conducted face-to-face interviews using a semi-structured questionnaire. It encompassed socio-demographic factors, as well as knowledge, attitudes, and practices concerning CVDs. Data analysis employed descriptive statistics, chi-square tests, and regression analyses, utilizing both the R programming language and SPSS (Version 26). Result: A total of 424 participants aged 60 years and above were included. The majority were male (60.8%), and the mean age was 71.21 ± 9.21 years, 57.3% were between 60 and 70 years old. Factors such as education, monthly family income, high blood pressure, diabetes, and non-smoking. Were significantly associated with higher knowledge, attitudes and practices scores. Conclusion: This study illuminates CVD-related KAP among rural Older Individuals in Bangladesh, revealing significant associations between factors such as education, monthly family income, high blood pressure, and non-smoking, with higher scores in knowledge, attitudes, and practices regarding cardiovascular health. These insights underscore the importance of addressing socio-economic factors and health behaviors in developing targeted interventions for the prevention and management of cardiovascular diseases in this demographic.

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Climate change impacts crop production worldwide, and coastal regions are particularly vulnerable to its adverse effects. Given the projected rise in temperature and shifting precipitation patterns, it is crucial to examine the current challenges faced by farmers in coastal Bangladesh. Using Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs), we assessed the perceptions and experiences of farmers and stakeholders regarding the existing agricultural practices, the challenges they face in crop cultivation, and the adoption of climate-adaptive practices in 2 sub-districts in the southeastern coastal region of Bangladesh. Moreover, using the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Terrestrial Water Storage Index (STI), we assessed the frequency and intensity of different climatic conditions in these two sub-districts. Results show that 100% of the respondents reported an increase in dry climatic conditions, the occurrence of untimely precipitation, and a decline in irrigation water during the cropping season. All the respondents in the FGDs expressed a loss of crop production because of these climate-induced disturbances. Despite these challenges, farmers have been implementing several climate-adaptive practices. Among the 9 mentioned climate-adaptive practices, 50% of FGD respondents utilize organic fertilizers, 42% cultivate heat- and drought-resilient crop varieties, use improved irrigation and harvest rainwater, and 25% cultivate integrated crops. The results of quantitative analysis of 3- and 6-month SPEI and STI values show that this region experienced frequent and intense dry climatic conditions during the growing-season, which supports the farmers' and stakeholders' concern about the increasing occurrence of droughts during crop growing periods. The results suggest that despite adopting climate-resilient practices under increasing growing-season droughts, farmers require support from the government and NGOs in capacity-building training and input support (e.g., stress-resilient seeds). This study holds practical implications for government, NGOs, and policymakers for ensuring sustainable agricultural productivity in the coastal region of Bangladesh.

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This study aims to comprehensively assess the presence of aflatoxins, pervasive fungal toxins, and heavy metals (lead, chromium, cadmium) in the local feed of fish and shrimp. Forty-eight samples of the fish and shrimp feed were collected from the Dhaka and Sathkhira districts of Bangladesh respectively. Aflatoxins (B1, B2, G1, G2) were analyzed by high-performance liquid chromatography (HPLC) with fluorescence detector, and atomic absorption spectrophotometry (AAS) was used for the heavy metal detection after sample digestion. The standard analytical methods of the Association of Official Analytical Chemists were followed for analyzing the proximate composition of the feed samples. The findings revealed the high toxic concentration of total aflatoxins particularly in fish feed (196.25 µg/kg). Concurrently, varying concentrations of heavy metals, including lead (Pb) and chromium (Cr), were detected, with the highest levels found in shrimp feed at 3.324 and 174.6 mg/kg, respectively. In comparison, highest contamination of cadmium (Cd) was found in fish feed at 0.398 mg/kg. The outcomes are growing concerns regarding the quality of locally sourced feed and emphasizing the need for prompt corrective actions. Otherwise, neglecting this concern may lead to the possibility of both fish and, ultimately, humans who consume them being vulnerable to the absorption and accumulation of these assessed toxic compounds.

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Cholesterol is a primary lipid molecule in the brain that contains one-fourth of the total body cholesterol. Abnormal cholesterol homeostasis is associated with neurodegenerative disorders. Mass spectrometry imaging (MSI) technique is a powerful tool for studying lipidomics and metabolomics. Among the MSI techniques, desorption electrospray ionization-MSI (DESI-MSI) has been used advantageously to study brain lipidomics due to its soft and ambient ionization nature. However, brain cholesterol is poorly ionized. To this end, we have developed a new method for detecting brain cholesterol by DESI-MSI using low-temperature plasma (LTP) pretreatment as an ionization enhancement. In this method, the brain sections were treated with LTP for 1 and 2 min prior to DESI-MSI analyses. Interestingly, the MS signal intensity of cholesterol (at m/z 369.35 [M + H - H2O]+) was more than 2-fold higher in the 1 min LTP-treated brain section compared to the untreated section. In addition, we detected cholesterol, more specifically excluding isomers by targeted-DESI-MSI in multiple reaction monitoring (MRM) mode and similar results were observed: the signal intensity of each cholesterol transition (m/z 369.4 → 95.1, 109.1, 135.1, 147.1, and 161.1) was increased by more than 2-fold due to 1 min LTP treatment. Cholesterol showed characteristic distributions in the fiber tract region, including the corpus callosum and anterior commissure, anterior part of the brain where LTP markedly (p < 0.001) enhanced the cholesterol intensity. In addition, the distributions of some unknown analytes were exclusively detected in the LTP-treated section. Our study revealed LTP pretreatment as a potential strategy to ionize molecules that show poor ionization efficiency in the MSI technique.

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Textile industries are now focusing on sustainable issues in manufacturing operations to save the environment. The study focuses on the use of cotton fibers (recycled) sourced from fabric (knitted) waste (pre-consumer) to manufacture elastic yarn (dual-core) for denim fabric. The study involves the production of yarns (dual-core) using a redesigned ring spinning method with different elastomeric components, including T400® (Polyethylene terephthalate)/Polytrimethylene terephthalate), Polybutylene terephthalate (PBT), Polyester (PES), Lycra® (elastane), virgin cotton and cotton (recycled) fiber. The study investigates various yarn (Ne 18/1) characteristics such as strength, IPI (imperfection index), elongation %, unevenness %, and hairiness. It is noticed that the elongation and strength of recycled yarn (double core) are lower and IPI (Imperfection index), unevenness %, and hairiness values are higher than 100 % cotton (virgin) yarn (double core). One-way ANOVA (statistical analysis) is employed to assess the significance of differences among yarns manufactured from various core materials and found significant variation for all characteristics. Additionally, the article introduces the MOORA (multi-objective optimization based on ratio analysis) technique as a decision-making tool to determine the best yarn among three alternatives (PES yarn, PBT yarn, and T400 yarn) based on their properties, considering attributes and finding T400 filament containing yarn as the best option. The study introduces a sustainable approach using recycled cotton in yarn (double core) production and employs decision-making tools to assess and rank the performance of different yarn alternatives.

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Knowledge of gender-specific drug distributions in different organs are of great importance for personalized medicine and reducing toxicity. However, such drug distributions have not been well studied. In this study, we investigated potential differences in the distribution of imipramine and chloroquine, as well as their metabolites, between male and female kidneys. Kidneys were collected from mice treated with imipramine or chloroquine and then subjected to atmospheric pressure matrix-assisted laser desorption ionization-mass spectrometry imaging (AP-MALDI-MSI). We observed differential distributions of the drugs and their metabolites between male and female kidneys. Imipramine showed prominent distributions in the cortex and medulla in male and female kidneys, respectively. Desipramine, one of the metabolites of imipramine, showed significantly higher (*** p < 0.001) distributions in the medulla of the male kidney compared to that of the female kidney. Chloroquine and its metabolites were accumulated in the pelvis of both male and female kidneys. Interestingly, they showed a characteristic distribution in the medulla of the female kidney, while almost no distributions were observed in the same areas of the male kidney. For the first time, our study revealed that the distributions of imipramine, chloroquine, and their metabolites were different in male and female kidneys.

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