Complex interactions between diverse mobile genetic elements drive the evolution of metal-resistant bacterial genomes.

In this study, we compared the genomes of three metal-resistant bacteria isolated from mercury-contaminated soil. We identified diverse and novel MGEs with evidence of multiple LGT events shaping their genomic structure and heavy metal resistance. Among the three metal-resistant strains, Sphingobium sp SA2 and Sphingopyxis sp SE2 were resistant to multiple metals including mercury, cadmium, copper, zinc and lead. Pseudoxanthomonas sp SE1 showed resistance to mercury only. Whole genome sequencing by Illumina and Oxford Nanopore technologies was undertaken to obtain comprehensive genomic data. The Sphingobium and Sphingopyxis strains contained multiple chromosomes and plasmids, whereas the Pseudoxanthomonas strain contained one circular chromosome. Consistent with their metal resistance profiles, the strains of Sphingobium and Sphingopyxis contained a higher quantity of diverse metal resistance genes across their chromosomes and plasmids compared to the single-metal resistant Pseudoxanthomonas SE1. In all three strains, metal resistance genes were principally associated with various novel MGEs including genomic islands (GIs), integrative conjugative elements (ICEs), transposons, insertion sequences (IS), recombinase in trio (RIT) elements and group II introns, indicating their importance in facilitating metal resistance adaptation in a contaminated environment. In the Pseudoxanthomonas strain, metal resistance regions were largely situated on a GI. The chromosomes of the strains of Sphingobium and Sphingopyxis contained multiple metal resistance regions, which were likely acquired by several GIs, ICEs, numerous IS elements, several Tn3 family transposons and RIT elements. Two of the plasmids of Sphingobium were impacted by Tn3 family transposons and ISs likely integrating metal resistance genes. The two plasmids of Sphingopyxis harboured transposons, IS elements, an RIT element and a group II intron. This study provides a comprehensive annotation of complex genomic regions of metal resistance associated with novel MGEs. It highlights the critical importance of LGT in the evolution of metal resistance of bacteria in contaminated environments.

The Pregnancy, Arsenic, and Immune Response (PAIR) Study in rural northern Bangladesh.

BACKGROUND: Arsenic exposure and micronutrient deficiencies may alter immune reactivity to influenza vaccination in pregnant women, transplacental transfer of maternal antibodies to the foetus, and maternal and infant acute morbidity. OBJECTIVES: The Pregnancy, Arsenic, and Immune Response (PAIR) Study was designed to assess whether arsenic exposure and micronutrient deficiencies alter maternal and newborn immunity and acute morbidity following maternal seasonal influenza vaccination during pregnancy. POPULATION: The PAIR Study recruited pregnant women across a large rural study area in Gaibandha District, northern Bangladesh, 2018-2019. DESIGN: Prospective, longitudinal pregnancy and birth cohort. METHODS: We conducted home visits to enrol pregnant women in the late first or early second trimester (11-17 weeks of gestational age). Women received a quadrivalent seasonal inactivated influenza vaccine at enrolment. Follow-up included up to 13 visits between enrolment and 3 months postpartum. Arsenic was measured in drinking water and maternal urine. Micronutrient deficiencies were assessed using plasma biomarkers. Vaccine-specific antibody titres were measured in maternal and infant serum. Weekly telephone surveillance ascertained acute morbidity symptoms in women and infants. PRELIMINARY RESULTS: We enrolled 784 pregnant women between October 2018 and March 2019. Of 784 women who enrolled, 736 (93.9%) delivered live births and 551 (70.3%) completed follow-up visits to 3 months postpartum. Arsenic was detected (≥0.02 µg/L) in 99.7% of water specimens collected from participants at enrolment. The medians (interquartile ranges) of water and urinary arsenic at enrolment were 5.1 (0.5, 25.1) µg/L and 33.1 (19.6, 56.5) µg/L, respectively. Water and urinary arsenic were strongly correlated (Spearman's ⍴ = 0.72) among women with water arsenic ≥ median but weakly correlated (⍴ = 0.17) among women with water arsenic < median. CONCLUSIONS: The PAIR Study is well positioned to examine the effects of low-moderate arsenic exposure and micronutrient deficiencies on immune outcomes in women and infants. REGISTRATION: NCT03930017.

Anthropometric measures and arsenic methylation among pregnant women in rural northern Bangladesh.

INTRODUCTION: Arsenic methylation converts inorganic arsenic (iAs) to monomethyl (MMA) and dimethyl (DMA) arsenic compounds. Body mass index (BMI) has been positively associated with arsenic methylation efficiency (higher DMA%) in adults, but evidence in pregnancy is inconsistent. We estimated associations between anthropometric measures and arsenic methylation among pregnant women in rural northern Bangladesh. METHODS: We enrolled pregnant women (n = 784) (median [IQR] gestational week: 14 [13, 15]) in Gaibandha District, Bangladesh from 2018 to 2019. Anthropometric measures were BMI, subscapular and triceps skinfold thicknesses, and mid-upper arm circumference (MUAC), fat area (MUAFA), and muscle area (MUAMA). Arsenic methylation measures were urinary iAs, MMA, and DMA divided by their sum and multiplied by 100 (iAs%, MMA%, and DMA%), primary methylation index (MMA/iAs; PMI), and secondary methylation index (DMA/MMA; SMI). In complete cases (n = 765 [97.6%]), we fitted linear, beta, and Dirichlet regression models to estimate cross-sectional differences in iAs%, MMA%, DMA%, PMI, and SMI per IQR-unit difference in each anthropometric measure, adjusting for drinking water arsenic, age, gestational age, education, living standards index, and plasma folate, vitamin B12, and homocysteine. RESULTS: Median (IQR) BMI, subscapular skinfold thickness, triceps skinfold thickness, MUAC, MUAFA, and MUAMA were 21.5 (19.4, 23.8) kg/m2, 17.9 (13.2, 24.2) mm, 14.2 (10.2, 18.7) mm, 25.9 (23.8, 28.0) cm, 15.3 (10.5, 20.3) cm2, and 29.9 (25.6, 34.2) cm2, respectively. Median (IQR) iAs%, MMA%, DMA%, PMI, and SMI were 12.0 (9.3, 15.2)%, 6.6 (5.3, 8.3)%, 81.0 (77.1, 84.6)%, 0.6 (0.4, 0.7), and 12.2 (9.3, 15.7), respectively. In both unadjusted and adjusted linear models, all anthropometric measures were negatively associated with iAs%, MMA%, and PMI and positively associated with DMA% and SMI. For example, fully adjusted mean differences (95% CI) in DMA% per IQR-unit difference in BMI, subscapular skinfolds thickness, triceps skinfold thickness, MUAC, MUAFA, and MUAMA were 1.72 (1.16, 2.28), 1.58 (0.95, 2.21), 1.74 (1.11, 2.37), 1.45 (0.85, 2.06), 1.70 (1.08, 2.31), and 0.70 (0.13, 1.27) pp, respectively. CONCLUSIONS: Anthropometric measures were positively associated with arsenic methylation efficiency among pregnant women in the early second trimester.

Functional dairy products as a source of bioactive peptides and probiotics: current trends and future prospectives.

Milk is an incredibly healthy food world-wide. However, the 'lactase deficient' individuals cannot digest milk's carbohydrate lactose. A large part of the world population is depriving of highly beneficial milk proteins like casein, lactoalbumin, lactoglobulin, etc. due to lactose intolerance. Production of functional foods and bioactive peptides from milk with natural antioxidants and the addition of probiotics could be the best alternative to extend the use of milk functionalities. Among different probiotics, the lactic acid bacteria (LAB) like Lactobacillus delbrueckii sub sp. bulgaricus, Streptococcus thermophilus and some species of Bifidobacteria and their metabolites (paraprobiotics and postbiotics) have been given more preference to add in milk-derived functional foods. These species are generally considered as heat-tolerant, highly proteolytic, and peptidolytic towards milk proteins and they liberate smaller molecules of bioactive peptides during fermentation and other processes that stimulate the enzyme lactase to help people in digestion of milk carbohydrate lactose. Moreover, the incorporation of natural antioxidants in yoghurt and other dairy products prevents the rancidity of milk fat. The level of bioactive peptides produced in milk-derived functional foods can be determined by capillary zone electrophoresis, mass spectrometry, fractionation, and other modern assessment techniques. Commercial production of functional probiotic products with bioactive peptides could significantly contribute to reduce milk spoilage, enhance health benefits as well as the growth of the agro-processing industry.

Reversible Proton-Coupled Reduction of an Iron Nitrosyl Porphyrin within [DBU-H]+-Based Protic Ionic Liquid Nanodomains.

The reduction of [Fe(OEP)(NO)] has been studied in the presence of aprotic room-temperature ionic liquids (RTIL) and protic (PIL) ionic liquids dissolved within a molecular solvent (MS). The cyclic voltammetric results showed the formation of RTIL nanodomains at low concentrations of the RTIL/PIL solutions. The pKa values of the two PILs studied (i.e., trialkylammonium and [DBU-H]+-based ionic liquids) differed by four units in THF. While voltammetry in solutions containing all three RTILs showed similar potential shifts of the first reduction of [Fe(OEP)(NO)] to [Fe(OEP)(NO)]- at low concentrations, significant differences were observed at higher concentrations for the ammonium PIL. The trialkylammonium cation had previously been shown to protonate the {FeNO}8 species at room temperature. Visible and infrared spectroelectrochemistry revealed that the [DBU-H]+-based PIL formed hydrogen bonds with [Fe(OEP)(NO)]- rather than formally protonating it. Despite these differences, both PILs were able to efficiently reduce the nitrosyl species to the hydroxylamine complex, which could be further reduced to ammonia. On the voltammetric time scale and when the switching potential was positive of the Fe(II)/Fe(I) potential, the hydroxylamine complex was re-oxidized back to the NO complex via direct oxidation of the coordinated hydroxylamine at low scan rates or initial oxidation of the ferrous porphyrin at high scan rates. The results of this work show that, while [DBU-H]+ does not protonate electrochemically generated [Fe(OEP)(NO)]-, it still plays an important role in efficiently reducing the nitroxyl ligand via a series of proton-coupled electron transfer steps to generate hydroxylamine and eventually ammonia. The overall reaction rates were independent of the PIL concentration, consistent with the nanodomain formation being important to the reduction process.

Barriers and enablers to routine register data collection for newborns and mothers: EN-BIRTH multi-country validation study.

BACKGROUND: Policymakers need regular high-quality coverage data on care around the time of birth to accelerate progress for ending preventable maternal and newborn deaths and stillbirths. With increasing facility births, routine Health Management Information System (HMIS) data have potential to track coverage. Identifying barriers and enablers faced by frontline health workers recording HMIS source data in registers is important to improve data for use. METHODS: The EN-BIRTH study was a mixed-methods observational study in five hospitals in Bangladesh, Nepal and Tanzania to assess measurement validity for selected Every Newborn coverage indicators. We described data elements required in labour ward registers to track these indicators. To evaluate barriers and enablers for correct recording of data in registers, we designed three interview tools: a) semi-structured in-depth interview (IDI) guide b) semi-structured focus group discussion (FGD) guide, and c) checklist assessing care-to-documentation. We interviewed two groups of respondents (January 2018-March 2019): hospital nurse-midwives and doctors who fill ward registers after birth (n = 40 IDI and n = 5 FGD); and data collectors (n = 65). Qualitative data were analysed thematically by categorising pre-identified codes. Common emerging themes of barriers or enablers across all five hospitals were identified relating to three conceptual framework categories. RESULTS: Similar themes emerged as both barriers and enablers. First, register design was recognised as crucial, yet perceived as complex, and not always standardised for necessary data elements. Second, register filling was performed by over-stretched nurse-midwives with variable training, limited supervision, and availability of logistical resources. Documentation complexity across parallel documents was time-consuming and delayed because of low staff numbers. Complete data were valued more than correct data. Third, use of register data included clinical handover and monthly reporting, but little feedback was given from data users. CONCLUSION: Health workers invest major time recording register data for maternal and newborn core health indicators. Improving data quality requires standardised register designs streamlined to capture only necessary data elements. Consistent implementation processes are also needed. Two-way feedback between HMIS levels is critical to improve performance and accurately track progress towards agreed health goals.

Conversion Characteristics of Some Major Cannabinoids from Hemp (Cannabis sativa L.) Raw Materials by New Rapid Simultaneous Analysis Method.

This study was carried out to develop a high-performance liquid chromatography method for short-time analysis of the main cannabinoids in the inflorescence of hemp (Cannabis sativa L.). We also performed decarboxylation of the raw material using our advanced analysis technique. In this study, the UV spectrum was considered to analyze each of the four common cannabinoids, solvents, and samples, where the uniform elution of acidic cannabinoids without peak tailing and acids was tested. Optimal results were obtained when readings were taken at a wavelength of 220 nm using water and methanol containing trifluoroacetic acid as mobile phases in a solvent gradient system. The established conditions were further validated by system suitability, linearity, precision, detection limit, and quantitation limit tests. The decarboxylation index (DT50) confirmed that Δ9-THCA decarboxylated faster than CBDA, and both maintained a linear relationship with time and temperature. In addition, the loss of cannabidiol was better prevented during the decarboxylation process in the natural state than in the extracted state.

Possible sources of ambient PM10 inside Jadavpur University Campus, Kolkata.

High concentration of particulates in the university and research institutional campus can affect cognitive performance of students and researchers. However, studies on ambient particulate concentration in the campus of universities or research institutes are scarce. The ambient concentration of PM10 was measured in the campus of Jadavpur University, Kolkata, during two different seasons (S1: Post-monsoon; S2: Winter) to identify major sources of pollutant here. Significant seasonal variation of ambient PM10 was recorded in the campus. The average ambient PM10 concentration was recorded higher in S2 compared to S1 of the study period. Morphological characteristics of PM10 during the study period suggest that the roundness of particles was in the range of 0.66 to 0.68, whilst the mean spherical diameter suggests most of the PM10 particles were < 2.5 µ diameter. Based on factorial analysis, three factors were generated which includes factor 1: soil, building material and coal burning particles (53.76% of the variance); factor 2: particles from coal combustion (29.89% of the variance) and factor 3: particles from transport emission (16.33% of the variance). The study suggests that it is important to stop burning coal, reduce vehicular emission and reduce road dust resuspension around the campus to maintain the ambient PM10 concentration within the university campus during the post-monsoon and winter months.

Infrared Spectroelectrochemistry of Iron-Nitrosyl Triarylcorroles. Implications for Ligand Noninnocence.

Recent DFT calculations have suggested that iron nitrosyl triarylcorrole complexes have substantial {FeNO}7-corrole•2- character. With this formulation, reduction of Fe(C)(NO) complexes, where C = triarylcorrole, should be centered on the corrole macrocycle rather than on the {FeNO}7 moiety. To verify this proposition, visible and infrared spectroelectrochemical studies of Fe(C)(NO) were carried out and the results were interpreted using DFT (B3LYP/STO-TZP) calculations. The first reduction of Fe(C)(NO) led to significant changes in the Soret and Q-band regions of the visible spectrum as well as to a significant downshift in the νNO and changes in the corrole vibrational frequencies. DFT calculations, which showed that the electron was mostly added to the corrole ligand (85%), were also able to predict the observed shifts in the νNO and corrole bands upon reduction. These results underscore the importance of monitoring both the corrole and nitrosyl vibrations in ascertaining the site of reduction. By contrast, the visible spectroelectrochemistry of the second reduction revealed only minor changes in the Soret band upon reduction, consistent with the reduction of the FeNO moiety.

Assessment of nutrients effect on the bioaccessibility of Cd and Cu in contaminated soil.

Soil is considered as a sink for heavy metals. Human health is severely affected by the continuous intake of toxic heavy metals even in a very low concentration. In the present experiment, we determined the influence of nutritional status including control (fasted condition), glucose (fed state), plant protein (fed state), animal protein (fed state) and calcium (fed state) on soil cadmium (Cd) and copper (Cu) bioaccessibility using physiologically-based extraction test (PBET) method together with simulator of the human intestinal microbial ecosystem (SHIME) model. The bioaccessibility of Cd was 1.06-73.58%, 0.44-54.79% and 0-17.78% and Cu was 3.81-67.32%, 4.98-71.14%, and 0-17.54% in the phase-I, phase-II and Phase-III respectively (in this study gastric phase, small intestinal phase and colon phase were considered as phase-I, phase-II and Phase-III respectively). The outcomes showed that, the average Cd bioaccessibility was higher with animal protein addition compared with other treatments in different phases. So, the effect of animal protein on Cd bioaccessibility was higher than other treatments in the phase-I, phase-II and phase-III. Due to the addition of plant protein, the higher average bioaccessibility of Cu was noticed in phase-I and phase-II in comparison to other treatments. However, in phase-III, the higher average bioaccessibility of Cu was found due to control treatment comparing with other treatments. Therefore, the influence of plant protein was higher than other nutrients on Cu bioaccessibility in the phase-I and phase-II. Moreover, other nutrients showed variable influence on Cd and Cu bioaccessibility. So, nutritional status has a significant effect on bioaccessibility as well as human health risk assessment.

Proton Transfer versus Hydrogen Bonding in a Reduced Iron Porphyrin Nitrosyl Complex.

The 1H NMR spectra of Fe(OEP)(HNO), which was formed from Fe(OEP)(NO)- in the presence of 3,5-dichlorophenol, were studied as a function of temperature. The chemical shift of the HNO proton showed a unique behavior which could be explained based on the equilibrium between the protonated complex, Fe(OEP)(HNO), and the hydrogen-bonded complex, Fe(OEP)(NO)-···HOPh. This equilibrium was consistent with UV/visible spectroscopy and the voltammetric data. UV/visible stopped-flow experiments showed that the hydrogen-bonded complex, which was formed when weak acids such as phenol were added, and the Fe(OEP)(HNO) complex were quite similar. In addition to the HNO proton resonance, the meso-resonances were consistent with the proposed equilibrium. Density functional theory calculations of various Fe(OEP)(NO)-/Fe(OEP)(HNO) species were calculated, and the results were consistent with experimental data.

Redox and Spectroscopic Properties of Iron Porphyrin Nitroxyl in the Presence of Weak Acids.

The spectroelectrochemistry and voltammetry of Fe(OEP) (NO) in the presence of substituted phenols was studied. Cyclic voltammetry showed that two closely spaced waves were observed for the reduction of Fe(OEP) (NO) in the presence of substituted phenols. The first wave was a single electron reduction under voltammetric conditions. The second wave was kinetically controlled, multielectron process. Visible spectroelectrochemistry of Fe(OEP) (NO) in the presence of substituted phenols showed that three species were present during the electrolysis. Additional spectroscopic studies indicated that the two reduction species were Fe(OEP) (HNO) and Fe(OEP)(H2NOH). The Fe(OEP) (HNO) species, which can be generated chemically, was stable over a period of hours. Additional acid did not lead to further protonation. Proton NMR spectroscopy confirmed the Fe(OEP) (HNO) species could be deprotonated under basic conditions. The third species, Fe(OEP)(H2NOH), was generated by the further reduction of the chemically generated Fe(OEP) (HNO) complex. Both the Fe(OEP) (HNO) and Fe(OEP)(H2NOH) complexes could be slowly oxidized back to Fe(OEP) (NO). At millimolar concentrations of Fe(OEP) (HNO), there was no evidence for the disproportionation of Fe(OEP) (HNO) to Fe(OEP) (NO) and H2 in the presence of substituted phenols. Nor was there evidence for the generation of N2O. The FTIR spectroelectrochemistry showed changes in the infrared spectra in the presence of substituted phenols, but no isotopic sensitive bands were observed for the reduced species between 1450 and 1200 cm-1. This may be because the νNO band shifted into a region (1500-1450 cm-1) where it would be difficult to observe.

In-situ particle analysis with heterogeneous background: a machine learning approach.

We propose a novel framework that combines state-of-the-art deep learning approaches with pre- and post-processing algorithms for particle detection in complex/heterogeneous backgrounds common in the manufacturing domain. Traditional methods, like size analyzers and those based on dilution, image processing, or deep learning, typically excel with homogeneous backgrounds. Yet, they often fall short in accurately detecting particles against the intricate and varied backgrounds characteristic of heterogeneous particle-substrate (HPS) interfaces in manufacturing. To address this, we've developed a flexible framework designed to detect particles in diverse environments and input types. Our modular framework hinges on model selection and AI-guided particle detection as its core, with preprocessing and postprocessing as integral components, creating a four-step process. This system is versatile, allowing for various preprocessing, AI model selections, and post-processing strategies. We demonstrate this with an entrainment-based particle delivery method, transferring various particles onto substrates that mimic the HPS interface. By altering particle and substrate properties (e.g., material type, size, roughness, shape) and process parameters (e.g., capillary number) during particle entrainment, we capture images under different ambient lighting conditions, introducing a range of HPS background complexities. In the preprocessing phase, we apply image enhancement and sharpening techniques to improve detection accuracy. Specifically, image enhancement adjusts the dynamic range and histogram, while sharpening increases contrast by combining the high pass filter output with the base image. We introduce an image classifier model (based on the type of heterogeneity), employing Transfer Learning with MobileNet as a Model Selector, to identify the most appropriate AI model (i.e., YOLO model) for analyzing each specific image, thereby enhancing detection accuracy across particle-substrate variations. Following image classification based on heterogeneity, the relevant YOLO model is employed for particle identification, with a distinct YOLO model generated for each heterogeneity type, improving overall classification performance. In the post-processing phase, domain knowledge is used to minimize false positives. Our analysis indicates that the AI-guided framework maintains consistent precision and recall across various HPS conditions, with the harmonic mean of these metrics comparable to those of individual AI model outcomes. This tool shows potential for advancing in-situ process monitoring across multiple manufacturing operations, including high-density powder-based 3D printing, powder metallurgy, extreme environment coatings, particle categorization, and semiconductor manufacturing.

Youth's climate consciousness: unraveling the Dengue-climate connection in Bangladesh.

Background: Climate change affects the transmission of vector-borne diseases like dengue, posing a substantial public health threat. Bangladesh, with its favorable conditions for Dengue transmission, has experienced periodic outbreaks. This study explores the relationship between climate change knowledge, perceptions of the Dengue-climate link, and the associated factors among Bangladeshi youth. Methods: In the Dhaka district of Bangladesh, a cross-sectional study was conducted between September and October 2023, involving face-to-face interviews with 1,358 participants. Convenient (non-probability) sampling was utilized for participant selection. Data collection involved the administration of a semi-structured questionnaire encompassing informed consent, socio-demographic information, and inquiries pertaining to climate change-related knowledge (13 items) and perception (11 items). Data analysis utilized STATA (Version 15.0) and SPSS (Version 26.0). Results: The mean scores for knowledge and perceptions were determined to be 7.10 ± 3.20 (out of 13) and 26.60 ± 4.12 (out of 33) respectively. Participants had a mean age of 22.02 ± 1.58 years. The study revealed that unmarried status, living in a nuclear family, being a non-smoker, good self-perception of physical health, regular sleep patterns, moderate social media usage, older age, unemployment, and daily media consumption are factors associated with higher knowledge and perception regarding the Dengue-climate change link. Moreover, a positive association was observed between knowledge of climate change and favorable attitudes toward the Dengue-climate connection. Conclusion: This study underscores the importance of tailored climate change education for youth in Bangladesh and highlights key variables influencing their knowledge and perceptions. Notably, there exists a positive association between climate change knowledge and favorable attitudes toward the Dengue-climate connection. These insights underscore the importance of targeted educational campaigns and policy interventions aimed at enhancing climate consciousness among the youth population, thereby fostering proactive measures to mitigate the impact of Dengue fever in the context of climate change.

Dietary Acrylamide: A Detailed Review on Formation, Detection, Mitigation, and Its Health Impacts.

In today's fast-paced world, people increasingly rely on a variety of processed foods due to their busy lifestyles. The enhanced flavors, vibrant colors, and ease of accessibility at reasonable prices have made ready-to-eat foods the easiest and simplest choice to satiate hunger, especially those that undergo thermal processing. However, these foods often contain an unsaturated amide called 'Acrylamide', known by its chemical name 2-propenamide, which is a contaminant formed when a carbohydrate- or protein-rich food product is thermally processed at more than 120 °C through methods like frying, baking, or roasting. Consuming foods with elevated levels of acrylamide can induce harmful toxicity such as neurotoxicity, hepatoxicity, cardiovascular toxicity, reproductive toxicity, and prenatal and postnatal toxicity. This review delves into the major pathways and factors influencing acrylamide formation in food, discusses its adverse effects on human health, and explores recent techniques for the detection and mitigation of acrylamide in food. This review could be of interest to a wide audience in the food industry that manufactures processed foods. A multi-faceted strategy is necessary to identify and resolve the factors responsible for the browning of food, ensure safety standards, and preserve essential food quality traits.

Intimate partner violence and excess fertility among women of reproductive age in Malawi.

PURPOSE: Gender inequity and adverse health outcomes continue to be of concern among women in sub-Saharan Africa. We determined prevalence of intimate partner violence and excess fertility (having more children than desired) in reproductive age women in Malawi. We also explored factors associated with these outcomes and with spousal fertility intentions. PATIENTS AND METHODS: In a cross-sectional study, a total of 360 women and 410 men were recruited using multi-stage sampling from communities in a peri-urban setting in Blantyre District, Southern Malawi in 2021. Women and men were separately interviewed by trained study workers using a structured questionnaire. In addition to descriptive analyses, we used univariate and multivariate logistic regression models to assess associations of risk factors with the outcomes of intimate partner violence and excess fertility. RESULTS: Among women, lifetime prevalence of intimate partner violence was 23.1%, and excess fertility was experienced by 25.6%. Intimate partner violence was associated with male partners alcohol consumption (adjusted odds ratio 2.13; P = 0.019). Women were more likely to report excess fertility if they were older (adjusted odds ratio 2.0, P<0.001, for a 5-year increase). Alcohol consumption by the male partner (adjusted odds ratio 2.14; P = 0.025) and women being able to refuse sex with their male partner (adjusted odds ratio 0.50; P = 0.036) were associated with discordant fertility preferences. CONCLUSIONS: Intimate partner violence, excess fertility, and social and health inequities continue to be prevalent in Malawi. These data suggest the underlying proximal and distal factors associated with these adverse outcomes such as alcohol consumption may be addressed through education, couple interactive communication, and community dialogue. To ensure sustainability and effectiveness, strong leadership involvement, both governmental and non-governmental, is needed.

Effect of Light Quality on Seed Potato (Solanum tuberose L.) Tuberization When Aeroponically Grown in a Controlled Greenhouse.

A plant factory equipped with artificial lights is a comparatively new concept when growing seed potatoes (Solanum tuberosum L.) for minituber production. The shortage of disease-free potato seed tubers is a key challenge to producing quality potatoes. Quality seed tuber production all year round in a controlled environment under an artificial light condition was the main purpose of this study. The present study was conducted in a plant factory to investigate the effects of distinct spectrum compositions of LEDs on potato tuberization when grown in an aeroponic system. The study was equipped with eight LED light combinations: L1 = red: blue: green (70 + 25 + 5), L2 = red: blue: green (70 + 20 + 10), L3 = red: blue: green (70 + 15 + 15), L4 = red: blue: green (70 + 10 + 20), L5 = red: blue: far-red (70 + 25 + 5), L6 = red: blue: far-red (70 + 20 + 10), L7 = red: blue: far-red (70 + 15 + 15), L8 = red: blue: far-red (70 + 10 + 20), and L9 = natural light with 300 µmol m-2 s-1 of irradiance, 16/8 h day/night, 65% relative humidity, while natural light was used as the control treatment. According to the findings, treatment L4 recorded a higher tuber number (31/plant), tuber size (>3 g); (9.26 ± 3.01), and GA3 content, along with better plant growth characteristics. Moreover, treatment L4 recorded a significantly increased trend in the stem diameter (11.08 ± 0.25), leaf number (25.32 ± 1.2), leaf width (19 ± 0.81), root length (49 ± 2.1), and stolon length (49.62 ± 2.05) compared to the control (L9). However, the L9 treatment showed the best performance in plant fresh weight (67.16 ± 4.06 g) and plant dry weight (4.46 ± 0.08 g). In addition, photosynthetic pigments (Chl a) (0.096 ± 0.00 mg g-1, 0.093 ± 0.00 mg g-1) were found to be the highest in the L1 and L2 treatments, respectively. However, Chl b and TCL recorded the best results in treatment L4. Finally, with consideration of the plant growth and tuber yield performance, treatment L4 was found to have the best spectral composition to grow quality seed potato tubers.

An insight on sources and biodegradation of bioplastics: a review.

Durability and affordability are two main reasons for the widespread consumption of plastic in the world. However, the inability of these materials to undergo degradation has become a significant threat to the environment and human health To address this issue, bioplastics have emerged as a promising alternative. Bioplastics are obtained from renewable and sustainable biomass and have a lower carbon footprint and emit fewer greenhouse gases than petroleum-based plastics. The use of these bioplastics sourced from renewable biomass can also reduce the dependency on fossil fuels, which are limited in availability. This review provides an elaborate comparison of biodegradation rates of potential bioplastics in soil from various sources such as biomass, microorganisms, and monomers. These bioplastics show great potential as a replacement for conventional plastics due to their biodegradable and diverse properties.

Verbal and Social Autopsy of Adult Deaths and Adult Care-Seeking Pattern in Mozambique, 2019-2020.

In sub-Saharan Africa, recent data about causes of adult death and care-seeking during illnesses are limited. This analysis examines adult deaths using verbal and social autopsy data from a nationally and provincially representative sample registration system in Mozambique. Causes of death among those 18 years and older were assigned using the InSilicoVA algorithm, and underlying social causes were examined using the pathway to survival model. Care-seeking was analyzed in different groups to determine if care was sought from formal providers (doctor, nurse/midwife, and trained community health worker) or other providers (traditional provider, family member, and pharmacist), using χ2 tests and multinomial regression models. Among the 4,040 adult deaths reported during 2019-2020, the major causes were HIV (17%), cancer (13%), injury (10%), cardiovascular diseases (9%), pneumonia (7%), tuberculosis (5%), and maternal causes (3%). Formal care-seeking was more likely among adults who had primary or higher level education (relative risk ratio [RRR]: 1.6, P < 0.001; RRR: 1.7, P < 0.01), were married (RRR: 1.3, P < 0.01), and had highest household wealth (RRR: 3.1, P < 0.001). Formal care-seeking was less likely among adults who were male (RRR: 0.7, P < 0.001), had social capital (RRR: 0.7, P < 0.05), or resided in the southern region (RRR: 0.4, P < 0.001). Information about adult causes of death is useful for formulating policy and for developing, monitoring, and evaluating programs to improve adult health in Mozambique. Care-seeking-related information helps identify barriers for seeking care from formal health providers while emphasizing the need for generating local resources and strengthening outreach health systems service delivery.

Artificial Intelligence-Driven Image Analysis of Bacterial Cells and Biofilms.

The current study explores an artificial intelligence framework for measuring the structural features from microscopy images of the bacterial biofilms. Desulfovibrio alaskensis G20 (DA-G20) grown on mild steel surfaces is used as a model for sulfate reducing bacteria that are implicated in microbiologically influenced corrosion problems. Our goal is to automate the process of extracting the geometrical properties of the DA-G20 cells from the scanning electron microscopy (SEM) images, which is otherwise a laborious and costly process. These geometric properties are a biofilm phenotype that allow us to understand how the biofilm structurally adapts to the surface properties of the underlying metals, which can lead to better corrosion prevention solutions. We adapt two deep learning models: (a) a deep convolutional neural network (DCNN) model to achieve semantic segmentation of the cells, (d) a mask region-convolutional neural network (Mask R-CNN) model to achieve instance segmentation of the cells. These models are then integrated with moment invariants approach to measure the geometric characteristics of the segmented cells. Our numerical studies confirm that the Mask-RCNN and DCNN methods are 227x and 70x faster respectively, compared to the traditional method of manual identification and measurement of the cell geometric properties by the domain experts.