Hollow Cathode Discharge Ionization Mass Spectrometry: Detection, Quantification and Gas Phase Ion-Molecule Reactions of Explosives and Related Compounds

Mass spectrometry (MS) has become an essential analytical method in every sector of science and technology. Because of its unique ability to provide direct molecular structure information on analytes, an extra method is rarely required. This review describes fabrication of a variable-pressure hollow cathode discharge (HCD) ion source for MS in detection, quantification and investigation of gas-phase ion molecule reactions of explosives and related compounds using air as a carrier gas. The HCD ion source has been designed in such a way that by altering the ion source pressures, the system can generate both HCD and conventional GD. This design enables for the selective detection and quantification of explosives at trace to ultra-trace levels. The pressure-dependent HCD ion source has also been used to investigate ion-molecule reactions in the gas phase of explosives and related compounds. The mechanism of ion formation in explosive reactions is also discussed.

Development of sustainable dual core-spun yarns using several filaments and recycled cotton sourced from pre-consumer fabric waste

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.

Green Synthesized Chitosan Nanoparticles for Controlling Multidrug-Resistant mecA- and blaZ-Positive Staphylococcus aureus and aadA1-Positive Escherichia coli

Antimicrobial resistance has recently been considered an emerging catastrophe globally. The public health and environmental threats were aggravated by the injudicious use of antibiotics in animal farming, aquaculture, and croup fields, etc. Consequently, failure of antibiotic therapies is common because of the emergence of multidrug-resistant (MDR) bacteria in the environment. Thus, the reduction in antibiotic spillage in the environment could be an important step for overcoming this situation. Bear in mind, this research was focused on the green synthesis of chitosan nanoparticles (ChiNPs) using Citrus lemon (Assam lemon) extract as a cross-linker and application in controlling MDR bacteria to reduce the antibiotic spillage in that sector. For evaluating antibacterial activity, Staphylococcus aureus and Escherichia coli were isolated from environmental specimens, and their multidrug-resistant pattern were identified both phenotypically by disk diffusion and genotypically by detecting methicillin- (mecA), penicillin- (blaZ), and streptomycin (aadA1)-resistance encoding genes. The inhibitory zone's diameter was employed as a parameter for determining the antibacterial effect against MDR bacteria revealing 30 ± 0.4 mm, 34 ± 0.2 mm, and 36 ± 0.8 mm zones of inhibition against methicillin- (mecA) and penicillin (blaZ)-resistant S. aureus, and streptomycin (aadA1)-resistant E. coli, respectively. The minimum inhibitory concentration at 0.31 mg/mL and minimum bactericidal concentration at 0.62 mg/mL of yielded ChiNPs were used as the broad-spectrum application against MDR bacteria. Finally, the biocompatibility of ChiNPs was confirmed by showing a negligible decrease in BHK-21 cell viability at doses less than 2 MIC, suggesting their potential for future application in antibiotic-free farming practices.

Urinary fatty acid biomarkers for prostate cancer detection

The lack of accuracy in the current prostate specific antigen (PSA) test for prostate cancer (PCa) screening causes around 60-75% of unnecessary prostate biopsies. Therefore, alternative diagnostic methods that have better accuracy and can prevent over-diagnosis of PCa are needed. Researchers have examined various potential biomarkers for PCa, and of those fatty acids (FAs) markers have received special attention due to their role in cancer metabolomics. It has been noted that PCa metabolism prefers FAs over glucose substrates for continued rapid proliferation. Hence, we proposed using a urinary FAs based model as a non-invasive alternative for PCa detection. Urine samples collected from 334 biopsy-designated PCa positive and 232 biopsy-designated PCa negative subjects were analyzed for FAs and lipid related compounds by stir bar sorptive extraction coupled with gas chromatography/mass spectrometry (SBSE-GC/MS). The dataset was split into the training (70%) and testing (30%) sets to develop and validate logit models and repeated for 100 runs of random data partitioning. Over the 100 runs, we confirmed the stability of the models and obtained optimal tuning parameters for developing the final FA based model. A PSA model using the values of the patients' PSA test results was constructed with the same cohort for the purpose of comparing the performances of the FA model against PSA test. The FA final model selected 20 FAs and rendered an AUC of 0.71 (95% CI = 0.67-0.75, sensitivity = 0.48, and specificity = 0.83). In comparison, the PSA model performed with an AUC of 0.51 (95% CI = 0.46-0.66, sensitivity = 0.44, and specificity = 0.71). The study supports the potential use of urinary FAs as a stable and non-invasive alternative test for PCa diagnosis.

Occurrence of ochratoxin A in breast milk and urine samples of nursing mothers in Bangladesh

The mycotoxin ochratoxin A (OTA) is a potent nephrotoxin with carcinogenic properties and, thus, of concern as a food contaminant. Since food contaminant data are scarce in Bangladesh, we applied human biomonitoring to gain more insights into OTA exposure in the country's population. OTA concentrations in human milk and urine samples of nursing mothers were determined with the aim to assess also exposure to this mycotoxin in breastfed infants. Breastfeeding mothers (n = 74) from three districts of Bangladesh (Sylhet, Cumilla, and Mymensingh region) participated in this study. They provided demographic data, along with breast milk and urine samples. OTA levels were measured by a competitive enzyme-linked immunosorbent assay (ELISA) with a detection limit of 60 ng/L for milk and 30 ng/L for urine.OTA was detected in 62.2% of all breast milk samples (mean 74.8 ± 49.0 ng/L, range < LOD-243.3 ng/L) and in 51.4% of all urine samples (mean 44.3 ± 63.5 ng/L, range < LOD-519.3 ng/L). The differences observed between regions for mean breast milk or for urinary OTA levels were relatively small. No significant correlation was observed between OTA levels in breast milk and food consumption patterns among nursing mothers. Regarding infant exposure, the estimated average daily intake of OTA for all was 15.0 ng/kg bw/day (range 4.5-45 ng/kg bw/day). In 34.5% of these infants, their estimated daily OTA intake exceeded a preliminary TDI value set by EFSA (17 ng/kg bw/day). The mean OTA intake was slightly higher (16.2 ± 7.8 ng/kg bw/day) in 1-2 months babies than in older infants (< 2 to 12 months), although the difference was not significant. Presence of OTA in most milk and urine samples of nursing mothers documents their widespread dietary mycotoxin exposure. Although based on a relatively small number of participants, the present analysis indicates non-negligible exposure of some nursed infants in Bangladesh. Therefore, further biomonitoring studies and investigations on major sources of OTA in food commodities are encouraged.

Aflatoxin M1 Analysis in Urine of Mill Workers in Bangladesh: A Pilot Study

Presence of aflatoxin B1 (AFB1) in food and feed is a serious problem, especially in developing countries. Human exposure to this carcinogenic mycotoxin can occur through dietary intake, but also through inhalation or dermal contact when handling and processing AFB1-contaminated crops. A suitable biomarker of AFB1 exposure by all routes is the occurrence of its hydroxylated metabolite aflatoxin M1 (AFM1) in urine. To assess mycotoxin exposure in mill workers in Bangladesh, we analyzed AFM1 levels in urine samples of this population group who may encounter both dietary and occupational AFB1 exposure. In this pilot study, a total of 76 participants (51 mill workers and 25 controls) were enrolled from the Sylhet region of Bangladesh. Urine samples were collected from people who worked in rice, wheat, maize and spice mills and from controls with no occupational contact to these materials. A questionnaire was used to collect information on basic characteristics and normal food habits of all participants. Levels of AFM1 in the urine samples were determined by a competitive enzyme linked immunosorbent assay. AFM1 was detected in 96.1% of mill workers' urine samples with a range of LOD (40) of 217.7 pg/mL and also in 92% of control subject's urine samples with a range of LOD of 307.0 pg/mL). The mean level of AFM1 in mill workers' urine (106.5 ± 35.0 pg/mL) was slightly lower than that of the control group (123.3 ± 52.4 pg/mL), whilst the mean AFM1 urinary level adjusted for creatinine was higher in mill workers (142.1 ± 126.1 pg/mg crea) than in the control group (98.5 ± 71.2 pg/mg crea). Yet, these differences in biomarker levels were not statistically significant. Slightly different mean urinary AFM1 levels were observed between maize mill, spice mill, rice mill, and wheat mill workers, yet biomarker values are based on a small number of individuals in these subgroups. No significant correlations were found between the study subjects' urine AFM1 levels and their consumption of some staple food items, except for a significant correlation observed between urinary biomarker levels and consumption of groundnuts. In conclusion, this pilot study revealed the frequent presence of AFM1 in the urine of mill workers in Bangladesh and those of concurrent controls with dietary AFB1 exposure only. The absence of a statistical difference in mean biomarker levels for workers and controls suggests that in the specific setting, no extra occupational exposure occurred. Yet, the high prevalence of non-negligible AFM1 levels in the collected urines encourage further studies in Bangladesh regarding aflatoxin exposure.

Morphometric and gut microbial evaluation of Tilapia (Oreochromis niloticus) fed on different levels of Moringa oleifera

Abstract In current study, different feeding levels of Moringa oleifera formulated diet was compared to analyze the growth performance, feed conversion ratio, feed conversion efficiency and gut microbiology of Oreochromis niloticus. The study was comprised of four treatment groups including 4%, 8% and 12% Moringa oleifera and one control group which was devoid of Moringa leaves. The experimental trial was conducted at the Zoology laboratory of Pakistan Institute of Applied and Social Sciences, (PIASS) Kasur. The physicochemical parameters of water such as temperature, dissolve oxygen, pH, total dissolved solids and salinity in all aquaria were found non-significantly different from each other. In control condition T1, the average weight gain was 14.89±16.90a grams, while average length gain was 11.52±7.444a cm. However, the total viable count on Eosin methylene blue was 7.4×107, 5.8×107 on Tryptic soy agar and 5.8×107on Nutrient agar. In T2, the average weight gain was 16.22±16.09b grams and average length gain was 12.97±7.79b cm. The total viable count on Eosin methylene blue was 7×107, 5.5×107 on Tryptic soy agar and 5.8×107on Nutrient agar. In T3, the average weight gain was 37.88±27.43c grams, while the average length gain was recorded as 16.48±12.56c cm. However, the total viable count for treatment 3 was 6.4×10 on Eosin methylene blue, 4.8×107 on Tryptic soy agar and 5.2×107on Nutrient agar. In T4, the average weight gain was 44.22±31.67d grams, while the average length gain was 15.25±10.49d cm. The total viable count was 4.3×107on Eosin methylene blue, 3.1×107 on Tryptic soy agar and 3.8×107 on Nutrient agar. The effect of Moringa oleifera on the growth of Oreochromis niloticus was found to be significant and 12% Moringa extract showed maximum length and weight gain and minimum feed conversion ratio with the least microbial count in fish intestine.

Effects of replacement of dietary fish oil with plant oil on growth performance and fatty acid composition of spinefoot rabbitfish, Siganus rivulatus

Abstract A 95-day feeding study was carried out to evaluate the impact of complete replacement of fish oil by plant oils in the growth performance, feed consumption fatty acid and body composition of juvenile rabbitfish, Siganus rivulatus. There were four treatments i.e., A (fish oil diet), (linseed oil diet), C (soybean meal oil diet) and D (sunflower oil diet). The experimental trial was conducted in twelve 1.5-m3 fiber glass tanks (n=3). Spinefoot rabbitfish juveniles had an average initial weight of 0.948 g ± 0.124 g and they were stocked at 50 fish per tank. Fish fed diet A showed significantly better growth rate, final body weight, and total body weight than fish fed on the other diets. Moreover, the best FCR was observed for diet A followed by diet C and diets B and D had the worst FCR. Fish body composition for crude protein, dry matter, ashes and gross energy at the end of the trial had not differed between the treatments. The highest polyunsaturated fatty acids (PUFA) was found in fish fed diet A followed in decreasing order by diets D, B, and C. Fish oil is a better dietary lipid source for Spinefoot rabbitfish juveniles, Siganus rivulatus, than plant oils. Among plant oils, soybean oil was better than linseed oil and sunflower oil as the main dietary fat source.

Size at sexual maturity estimation for 36 species captured by bottom and mid-water trawls from the marine habitat of Balochistan and Sindh in the Arabian Sea, Pakistan, using maximum length (Lmax) and logistic (L50) models

Abstract The aim of this study was to estimate the size at first sexual maturity (Lm) for 36 species belonging to 24 families from the marine habitat of Balochistan and Sindh in Arabian Sea, Pakistan through maximum length based an empirical and logistic model using commercial catch during June 2020 to May 2021. Individual total length (TL) was noted up to 0.1 cm using measuring broad. The Lm was calculated using two formulae; (i) log (Lm) = - 0.1246 + 0.9924 * log (Lmax) for Elasmobranchs and (ii) log (Lm) = -0.1189 + 0.9157* log (Lmax) for ray-finned fishes. The minimum Lm was recorded as 10.27 cm TL for Caranx malabaricus and 108.38 cm TL for Isurus oxyrinchus, respectively. Around Lm with 58.33% species were ranges from 19.00 cm to 25.00 cm TL. This study was estimated 16 newly Lm which is globally absent and rest 20 Lm are absent in the Arabian Sea (Pakistan coastal habitats). Therefore, the results will be helpful for the sustainable management and conservation of these marine fishes through the establishment of mesh size of trawl nets based on the size at sexual maturity (Lm).

Investigating the effects of storage conditions on urinary volatilomes for their reliability in disease diagnosis

BACKGROUND

Cancer detection presents challenges regarding invasiveness, cost, and reliability. As a result, exploring alternative diagnostic methods holds significant clinical importance. Urinary metabolomic profiling has emerged as a promising avenue; however, its application for cancer diagnosis may be influenced by sample preparation or storage conditions.

OBJECTIVE

This study aimed to assess the impact of sample storage and processing conditions on urinary volatile organic compounds (VOCs) profiles and establish a robust standard operating procedure (SOP) for such diagnostic applications.

METHODS

Five key variables were investigated: storage temperatures, durations, freeze-thaw cycles, sample collection conditions, and sample amounts. The analysis of VOCs involved stir bar sorptive extraction coupled with thermal desorption-gas chromatography/mass spectrometry (SBSE-TD-GC-MS), with compound identification facilitated by the National Institute of Standards and Technology Library (NIST). Extensive statistical analysis, including combined scatterplot and response surface (CSRS) plots, partial least squares-discriminant analysis (PLS-DA), and probability density function plots (PDFs), were employed to study the effects of the factors.

RESULTS

Our findings revealed that urine storage duration, sample amount, temperature, and fasting/non-fasting sample collection did not significantly impact urinary metabolite profiles. This suggests flexibility in urine sample collection conditions, enabling individuals to contribute samples under varying circumstances. However, the influence of freeze-thaw cycles was evident, as VOC profiles exhibited distinct clustering patterns based on the number of cycles. This emphasizes the effect of freeze-thaw cycles on the integrity of urinary profiles.

CONCLUSIONS

The developed SOP integrating SBSE-TD-GC-MS and statistical analyses can serve as a valuable tool for analyzing urinary organic compounds with minimal preparation and sensitive detection. The findings also support that urinary VOCs for cancer screening and diagnosis could be a feasible alternative offering a robust, non-invasive, and sensitive approach for cancer screening.

Assessment of quality of commercial hand sanitizers using Fourier transform infrared spectroscopy and gas chromatography

Since the beginning of the COVID-19 pandemic, the use and manufacture of alcohol-based hand sanitizers increased exponentially. Efficacy of hand sanitizers mainly depends on active ingredients like ethanol and isopropanol (IPA). Even though methanol is extremely hazardous to people, it is still illegally used in hand sanitizers in Bangladesh. Developing a quick and simple analytical method for detecting and quantifying ethanol/IPA/methanol is crucial. Here, Fourier transform infrared spectroscopy (FTIR) was used to identify and quantify alcohol content in commercially available hand sanitizers in a quick and easy way. Comparing the FTIR and GC data, provided quite similar results. Unlike previous studies by FTIR, C-H, CH₃-C-CH₃ stretching, and C-H bending vibrational modes were employed to construct analytical calibration curves to detect and quantify alcohol in hand sanitizers. According to FTIR and GC findings, ethanol and IPA content were found to be 43-82% and 40-69%, and 56-64% and 61-66%, respectively, whereas ethanol was labeled at 66-80% and IPA at 65-70%. FTIR and GC revealed methanol content ranging from 37 to 98 and 19 to 81%, respectively. Also, the FTIR was significantly faster than the GC. Therefore, FTIR can be used to commercially analyze the quality of hand sanitizers.•FTIR was used to identify and quantify alcohol content in commercially available hand sanitizers in a quick and easy way.•Comparing the FTIR and GC data, provided quite similar results.•Out of ten samples, five contained ethanol, three IPA, and two methanol.

Rapid, efficient, and green analytical technique for determination of fluorotelomer alcohol in water by stir bar sorptive extraction

Fluorotelomer alcohols (FTOHs) are one of the major classes of per- and polyfluoroalkyl substances (PFAS). Due to their potential toxicity, persistence, and ubiquitous presence in the environment, some common PFAS are voluntarily phased out; while FTOHs are used as alternatives to conventional PFAS. FTOHs are precursors of perfluorocarboxylic acids (PFCAs) and therefore they are commonly detected in water matrices, which eventually indicate PFAS contamination in drinking water supplies and thus a potential source of human exposure. Even though studies have been conducted nationwide to evaluate the degree of FTOHs in the water environment, robust monitoring is lacking because of the unavailability of simple and sustainable analytical extraction and detection methods. To fill the gap, we developed and validated a simple, rapid, minimal solvent use, no clean-up, and sensitive method for the determination of FTOHs in water by stir bar sorptive extraction (SBSE) coupled with thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Three commonly detected FTOHs (6:2 FTOH, 8:2 FTOH, and 10:2 FTOH) were selected as the model compounds. Factors such as extraction time, stirring speed, solvent composition, salt addition, and pH were investigated to achieve optimal extraction efficiency. This "green chemistry" based extraction provided good sensitivity and precision with low method limits of detection ranging from 2.16 ng/L to 16.7 ng/L and with an extraction recovery ranging 55%-111%. The developed method were tested on tap water, brackish water, and wastewater influent and effluent. 6:2 FTOH and 8:2 FTOH were detected in two wastewater samples at 78.0 and 34.8 ng/L, respectively. This optimized SBSE-TD-GC-MS method will be a valuable alternative to investigate FTOHs in water matrices.

Antibiotic Guidelines for Critically Ill Patients in Nigeria

BACKGROUND

It is well documented that inappropriate use of antimicrobials is the major driver of antimicrobial resistance. To combat this, antibiotic stewardship has been demonstrated to reduce antibiotic usage, decrease the prevalence of resistance, lead to significant economic gains and better patients' outcomes. In Nigeria, antimicrobial guidelines for critically ill patients in intensive care units (ICUs), with infections are scarce. We set out to develop antimicrobial guidelines for this category of patients.

METHODS

A committee of 12 experts, consisting of Clinical Microbiologists, Intensivists, Infectious Disease Physicians, Surgeons, and Anesthesiologists, collaborated to develop guidelines for managing infections in critically ill patients in Nigerian ICUs. The guidelines were based on evidence from published data and local prospective antibiograms from three ICUs in Lagos, Nigeria. The committee considered the availability of appropriate antimicrobial drugs in hospital formularies. Proposed recommendations were approved by consensus agreement among committee members.

RESULTS

Candida albicans and Pseudomonas aeruginosa were the most common microorganisms isolated from the 3 ICUs, followed by Klebsiella pneumoniae, Acinetobacter baumannii, and Escherichia coli. Targeted therapy is recognized as the best approach in patient management. Based on various antibiograms and publications from different hospitals across the country, amikacin is recommended as the most effective empiric antibiotic against Enterobacterales and A. baumannii, while colistin and polymixin B showed high efficacy against all bacteria. Amoxicillin-clavulanate or ceftriaxone was recommended as the first-choice drug for community-acquired (CA) CA-pneumonia while piperacillin-tazobactam + amikacin was recommended as first choice for the treatment of healthcare-associated (HA) HA-pneumonia. For ventilatorassociated pneumonia (VAP), the consensus for the drug of first choice was agreed as meropenem. Amoxycillin-clavulanate +clindamycin was the consensus choice for CAskin and soft tissue infection (SSIS) and piperacillin-tazobactam + metronidazole ±vancomycin for HA-SSIS. Ceftriaxone-tazobactam or piperacillin-tazobactam + gentamicin was consensus for CA-blood stream infections (BSI) with first choice+regimen for HA-BSI being meropenem/piperacillin-tazobactam +amikacin +fluconazole. For community-acquired urinary tract infection (UTI), first choice antibiotic was ciprofloxacin or ceftriaxone with a catheter-associated UTI (CAUTI) regimen of first choice being meropenem + fluconazole.

CONCLUSION

Data from a multicenter three ICU surveillance and antibiograms and publications from different hospitals in the country was used to produce this evidence-based Nigerian-specific antimicrobial treatment guidelines of critically ill patients in ICUs by a group of experts from different specialties in Nigeria. The implementation of this guideline will facilitate learning, continuous improvement of stewardship activities and provide a baseline for updating of guidelines to reflect evolving antibiotic needs.

Omics data analysis reveals common molecular basis of small cell lung cancer and COVID-19

The impact of COVID-19 infection on individuals with small cell lung cancer (SCLC) poses a serious threat. Unfortunately, the molecular basis of this severe comorbidity has yet to be elucidated. The present study addresses this gap utilizing publicly available omics data of COVID-19 and SCLC to explore the key molecules and associated pathways involved in the convergence of these diseases. Findings revealed 402 genes, that exhibited differential expression patterns in SCLC patients and also play a pivotal role in COVID-19 pathogenesis. Subsequent functional enrichment analyses identified relevant ontologies and pathways that are significantly associated with these genes, revealing important insights into their potential biological, molecular and cellular functions. The protein-protein interaction network, constructed under four combinatorial topological assessments, highlighted SMAD3, CAV1, PIK3R1, and FN1 as the primary components to this comorbidity. Our results suggest that these components significantly regulate this cross-talk triggering the PI3K-AKT and TGF-β signaling pathways. Lastly, this study made a multi-step computational attempt and identified corylifol A and ginkgetin from natural sources that can potentially inhibit these components. Therefore, the outcomes of this study offer novel perspectives on the common molecular mechanisms underlying SCLC and COVID-19 and present future opportunities for drug development.Communicated by Ramaswamy H. Sarma.

Black carbon derived PET plastic bottle waste and rice straw for sorption of Acid Red 27 dye: Machine learning approaches, kinetics, isotherm and thermodynamic studies

This study focuses on the probable use of PET waste black carbon (PETWBC) and rice straw black carbon (RSBC) as an adsorbent for Acid Red 27 (AR 27) adsorption. The prepared adsorbent is characterized by FE-SEM and FT-IR. Batch adsorption experiments were conducted with the influencing of different operational conditions namely time of contact (1-180 min), AR 27 concentration (5-70 mg/L), adsorbent dose (0.5-20 g/L), pH (2-10), and temperature (25-60°C). High coefficient value [PETWBC (R2 = 0.94), and RSBC (R2 = 0.97)] of process optimization model suggesting that this model was significant, where pH and adsorbent dose expressively stimulus removal efficiency including 99.88, and 99.89% for PETWBC, and RSBC at pH (2). Furthermore, the machine learning approaches (ANN and BB-RSM) revealed a good association between the tested and projected value. Pseudo-second-order was the well-suited kinetics, where Freundlich isotherm could explain better equilibrium adsorption data. Thermodynamic study shows AR 27 adsorption is favourable, endothermic, and spontaneous. Environmental friendliness properties are confirmed by desorption studies and satisfactory results also attain from real wastewater experiments. Finally, this study indicates that PETWBC and RSBC could be potential candidates for the adsorption of AR 27 from wastewater.

Carbon Coated Iron-Cobalt Nanoparticles for Magnetic Particle Imaging

Magnetic particle imaging (MPI) is an emerging imaging modality that provides direct and quantitative mapping of iron oxide tracers. To achieve high sensitivity and good spatial resolution images, a magnetic nanoparticle with a higher contrast intensity needs to be developed. Currently, a majority of MPIs being developed for potential clinical application are composed of iron oxide nanoparticles with a spherical shape. In this project, we intend to report development of high-performance carbon (C) coated iron-cobalt (FeCo) nanoparticles (FeCo/C) and investigate their feasibility as a MPI agent. We have synthesized FeCo/C through a facile and simple method at mild temperature that is safe, easy, and up-scalable. We studied the structural and functional relationships and biocompatibility of this MPI agent in vitro. However, to enhance the aqueous solubility and biocompatibility, the surface of FeCo/C was modified with polyethylene glycol (PEG). We found that variation in the ratio of Fe and Co plays a vital role in their physical properties and functionality. In vitro imaging confirms that the Fe3Co1/C nanoparticle has highly competitive MPI intensity compared to VivoTrax, a commercially available MPI agent. Confocal laser scanning microscopy imaging with Rhodamine B labeled FeCo/C displays cellular internalization by the A375 cancer cells. The in vitro toxicity analysis concludes that there is no significant toxicity of FeCo/C nanoparticles. Therefore, the newly developed MPI agent holds strong promise for biomedical imaging and could be further validated in vivo in small animals.

Domain Agnostic Post-Processing for QRS Detection Using Recurrent Neural Network

Deep-learning-based QRS-detection algorithms often require essential post-processing to refine the output prediction-stream for R-peak localisation. The post-processing involves basic signal-processing tasks including the removal of random noise in the model's prediction stream using a basic Salt and Pepper filter, as well as, tasks that use domain-specific thresholds, including a minimum QRS size, and a minimum or maximum R-R distance. These thresholds were found to vary among QRS-detection studies and empirically determined for the target dataset, which may have implications if the target dataset differs such as the drop of performance in unknown test datasets. Moreover, these studies, in general, fail to identify the relative strengths of deep-learning models and the post-processing to weigh them appropriately. This study identifies the domain-specific post-processing, as found in the QRS-detection literature, as three steps based on the required domain knowledge. It was found that the use of minimal domain-specific post-processing is often sufficient for most of the cases and the use of additional domain-specific refinement ensures superior performance, however, it makes the process biased towards the training data and lacks generalisability. As a remedy, a domain-agnostic automated post-processing is introduced where a separate recurrent neural network (RNN)-based model learns required post-processing from the output generated from a QRS-segmenting deep learning model, which is, to the best of our knowledge, the first of its kind. The RNN-based post-processing shows superiority over the domain-specific post-processing for most of the cases (with shallow variants of the QRS-segmenting model and datasets like TWADB) and lags behind for others but with a small margin ( ≤ 2%). The consistency of the RNN-based post-processor is an important characteristic which can be utilised in designing a stable and domain agnostic QRS detector.

Removal of hazardous textile dye from simulated wastewater by municipal organic solid waste charcoal using machine learning approaches: Kinetics, isotherm, and thermodynamics

This study focuses on the probable use of municipal organic solid waste charcoal (MOSWC) as an adsorbent for Methyl orange (MO) adsorption. The prepared MOSWC is characterized by FE-SEM and FT-IR. Batch adsorption experiments were conducted with the influencing of different operational conditions namely time of contact (1-180 min), adsorbate concentration (60-140 mg/L), adsorbent dose (1-5 g/L), pH (3-11), and temperature (25-60 °C). The high coefficient value (R2 = 0.96) of the process optimization model suggests that this model was significant, where pH and adsorbent dose expressively stimulus adsorption efficiency including 40.11 mg/g at pH (3), MO concentration (100 mg/L), and MOSWC dose (1 g/L). Furthermore, the machine learning approaches (ANN and BB-RSM) revealed a good association between the tested and projected values. The highest monolayer adsorption capacity of MO was 90.909 mg/g. Pseudo-second-order was the well-suited kinetics, where Langmuir isotherm could explain better for equilibrium adsorption data. Thermodynamic study shows MO adsorption is favourable, exothermic, and spontaneous. Finally, this study indicates that MOSWC could be a potential candidate for the adsorption of MO from wastewater.

Efficacy of surgeon-performed, intra-operative ultrasound scan for localisation of parathyroid adenomas in patients with primary hyperparathyroidism

BACKGROUND

In the UK, guidance recommends ultrasound scanning alone or in combination with sestamibi scintigraphy to guide surgery in patients with primary hyperparathyroidism. If an adenoma is localised on imaging, this can facilitate targeted or minimally invasive surgery. Surgeon-performed ultrasound scan on the operating table benefits from being performed on an anaesthetised patient with optimal positioning. The aim of this study was to investigate the efficacy of intra-operative, blinded, surgeon-performed ultrasound scan in localisation of parathyroid adenomas.

METHODS

Prospective data were collected on consecutive patients undergoing surgery for primary hyperparathyroidism at a single tertiary centre from November 2019 to June 2021. Patients underwent blinded, surgeon-performed ultrasound scan under general anaesthesia immediately prior to surgery. Localisation results from pre-operative imaging and surgeon-performed ultrasound scan were then compared with the intra-operative findings.

RESULTS

Forty-nine patients underwent surgery and were found to have single-gland disease. Sestamibi scintigraphy, radiologist-performed ultrasound scan and surgeon-performed ultrasound scan had sensitivities of 59.4, 43.75 and 73.8 per cent, respectively. Surgeon-performed ultrasound scan had a statistically significantly increased sensitivity compared with radiologist-performed ultrasound (p < 0.05).

CONCLUSION

Intra-operative, surgeon-performed ultrasound scan is effective in localising parathyroid adenomas and may be a useful adjunct to facilitate minimally invasive parathyroid surgery.

Flexible, stretchable, and single-molecule-sensitive SERS-active sensor for wearable biosensing applications

The development of wearable sensors for remote patient monitoring and personalized medicine has led to a revolution in biomedical technology. Plasmonic metasurfaces that enhance Raman scattering signals have recently gained attention as wearable sensors. However, finding a flexible, sensitive, and easy-to-fabricate metasurface has been a challenge for decades. In this paper, a novel wearable device, the flexible, stretchable, and single-molecule-sensetive SERS-active sensor, is proposed. This device offers an unprecedented SERS enhancement factor in the order of 1011, along with other long-desired characteristics for SERS applications such as a high scattering to absorption ratio (∼2.5) and a large hotspot volume (40 nm × 40 nm × 5 nm). To achieve flexibility, we use polydimethylsiloxane (PDMS) as the substrate, which is stable, transparent, and biologically compatible. Our numerical calculations show that the proposed sensor offers reliable SERS performance even under bending (up to 100° angles) or stretching (up to 50% stretch). The easy-to-fabricate and flexible nature of our sensor offers a promising avenue for developing highly sensitive wearable sensors for a range of applications, particularly in the field of personalized medicine and remote patient monitoring.

Impact of synthetic noise signature and physiologic ECG signal on designing ML-based ECG noise detection framework

Automatic signal analysis using artificial intelligence is getting popular in digital healthcare, such as ECG rhythm analysis, where ECG signals are collected from traditional ECG machines or wearable ECG sensors. However, the risk of using an automated system for ECG analysis when noise is present can lead to incorrect diagnosis or treatment decisions. A noise detector is crucial to minimise the risk of incorrect diagnosis. Machine learning (ML) models are used in ECG noise detection before clinical decision-making systems to mitigate false alarms. However, it is essential to prove the generalisation capability of the ML model in different situations. ML models performance is 50% lesser when the model is trained with synthetic and tested with physiologic ECG datasets compared to trained and tested with physiologic ECG datasets. This suggests that the ML model must be trained with physiologic ECG datasets rather than synthetic ones or add more various types of noise in synthetic ECG datasets that can mimic physiologic ECG.Clinical relevance- ML model trained with synthetic noisy ECG can increase the 50% misclassification rate in ECG noise detection compared to training with physiologic ECG datasets. The wrong classification of noise-free and noisy ECG will lead to misdiagnosis regarding the patient's condition, which could be a cause of death.

Modeling the path to >30% power conversion efficiency in perovskite solar cells with plasmonic nanoparticles

Mixed organic-inorganic halide perovskite solar cells (PSCs) are a promising technology with increasing power conversion efficiency (PCE), low-cost material constituents, simple scalability, and a low-temperature solution fabrication process. Recent developments have seen energy conversion efficiencies increase from 3.8% to over 20%. However, to further improve PCE and reach the target efficiency of over 30%, light absorption through plasmonic nanostructures is a promising approach. In this work, we present a thorough quantitative analysis of the absorption spectrum of a methylammonium lead iodide (CH₃NH₃PbI₃) perovskite solar cell using a nanoparticle (NP) array. Our multiphysics simulations using finite element methods (FEM) show that an array of Au nanospheres can increase average absorption >45%, compared to only 27.08% for the baseline structure without any NPs. Furthermore, we investigate the combined effect of engineered enhanced absorption on electrical and optical solar cell performance parameters using the one-dimensional solar cell capacitance software (SCAPS 1-D), which shows a PCE of ∼30.4%, significantly higher than the PCE of ∼21% for cells without NPs. Our findings demonstrate the potential of plasmonic perovskite research for next-generation optoelectronic technologies.

β-Glucan and Fatty Acid Based Mucoadhesive Carrier for Gastrointestinal Tract Specific Local and Sustained Drug Delivery

The oral route is considered the most convenient route of drug administration for both systemic and local delivery. Besides stability and transportation, another unmet but important issue regarding oral medication is retention duration within the specific region of the gastrointestinal (GI) tract. We hypothesize that an oral vehicle that can adhere and maintain retention within the stomach for a longer duration can be more effective to treat stomach-related diseases. Therefore, in this project, we developed a carrier that is highly specific to the stomach and maintains its retention for a longer duration. We developed a vehicle composed of β-Glucan And Docosahexaenoic Acid (GADA) to observe its affinity and specificity to the stomach. GADA forms a spherical-shaped particle with negative zeta potential values that vary based on the feed ratio of docosahexaenoic acid. Docosahexaenoic acid is an omega-3 fatty acid that has transporters and receptors throughout the GI tract, such as CD36, plasma membrane-associated fatty acid-binding protein (FABP (pm)), and a family of fatty acid transport proteins (FATP1-6). The in vitro studies and characterization data showed that GADA has the capability to carry a payload of hydrophobic molecules and specifically deliver the payload to the GI tract, exert its therapeutic effects, and help to maintain stability for more than 12 h in the gastric and intestinal fluid. The particle size and surface plasmon resonance (SPR) data showed that GADA has a strong binding affinity with mucin in the presence of simulated gastric fluids. We observed a comparatively higher drug release of lidocaine in gastric juice than that in intestinal fluids, demonstrating the influence of the pH values of the media on drug-release kinetics. In vivo and ex vivo imaging of mice demonstrated that GADA maintains its retention within the stomach for at least 4 hr. This stomach-specific oral vehicle holds strong promise to translate various injectable therapeutic drugs to oral form upon further optimizations.

Bioinformatics and cheminformatics approaches to identify pathways, molecular mechanisms and drug substances related to genetic basis of cervical cancer

Cervical cancer (CC) is a global threat to women and our knowledge is frighteningly little about its underlying genomic contributors. Our research aimed to understand the underlying molecular and genetic mechanisms of CC by integrating bioinformatics and network-based study. Transcriptomic analyses of three microarray datasets identified 218 common differentially expressed genes (DEGs) within control samples and CC specimens. KEGG pathway analysis revealed pathways in cell cycle, drug metabolism, DNA replication and the significant GO terms were cornification, proteolysis, cell division and DNA replication. Protein-protein interaction (PPI) network analysis identified 20 hub genes and survival analyses validated CDC45, MCM2, PCNA and TOP2A as CC biomarkers. Subsequently, 10 transcriptional factors (TFs) and 10 post-transcriptional regulators were detected through TFs-DEGs and miRNAs-DEGs regulatory network assessment. Finally, the CC biomarkers were subjected to a drug-gene relationship analysis to find the best target inhibitors. Standard cheminformatics method including in silico ADMET and molecular docking study substantiated PD0325901 and Selumetinib as the most potent candidate-drug for CC treatment. Overall, this meticulous study holds promises for further in vitro and in vivo research on CC diagnosis, prognosis and therapies. Communicated by Ramaswamy H. Sarma.

Receptor model-based sources and risks appraisal of potentially toxic elements in the urban soils of Bangladesh

Rapid urbanization and industrial development have prompted potentially toxic elements (PTEs) in urban soil in Bangladesh, which is a great concern for ecological and public health matters. The present study explored the receptor-based sources, probable human health and ecological risks of PTEs (As, Cd, Pb, Cr, Ni, and Cu) in the urban soil of the Jashore district, Bangladesh. The USEPA modified method 3050B and atomic absorption spectrophotometers were used to digest and evaluate the PTEs concentration in 71 soil samples collected from eleven different land use areas, respectively. The concentration ranges of As, Cd, Pb, Cr, Ni, and Cu in the studied soils were 1.8-18.09, 0.1-3.58, 0.4-113.26, 0.9-72.09, 2.1-68.23, and 3.82-212.57 mg/kg, respectively. The contamination factor (CF), pollution load index (PLI), and enrichment factor (EF) were applied to evaluate the ecological risk posed by PTEs in soils. Soil quality evaluation indices showed that Cd was a great contributor to soil pollution. The PLI values range was 0.48-2.82, indicating base levels to continuous soil degradation. The positive matrix factorization (PMF) model showed that As (50.3 %), Cd (38.8 %), Cu (64.7 %), Pb (81.8 %) and Ni (47.2 %) were derived from industrial sources and mixed anthropogenic sources, while Cr (78.1 %) from natural sources. The highest contamination was found in the metal workshop, followed by the industrial area, and brick filed site. Soil from all land use types revealed moderate to high ecological risk after evaluating probable ecological risks, and the descending order of single metal potential ecological risk was Cd > As > Pb > Cu > Ni > Cr. Ingestion was the primary route of exposure to potentially toxic elements for both adults and children from the study area soil. The overall non-cancer risk to human health is caused by PTEs for children (HI=0.65 ± 0.1) and adults (HI=0.09 ± 0.03) under USEPA safe limit (HI>1), while the cancer risks from exclusively ingesting As through soil were 2.10E-03 and 2.74E-04 for children and adults, respectively, exceeding the USEPA acceptable standard (>1E-04).

Cohort profile: the ESC EURObservational Research Programme Non-ST-segment elevation myocardial infraction (NSTEMI) Registry

AIMS

The European Society of Cardiology (ESC) EURObservational Research Programme (EORP) Non-ST-segment elevation myocardial infarction (NSTEMI) Registry aims to identify international patterns in NSTEMI management in clinical practice and outcomes against the 2015 ESC Guidelines for the management of acute coronary syndromes in patients presenting without ST-segment-elevation.

METHODS AND RESULTS

Consecutively hospitalised adult NSTEMI patients (n = 3620) were enrolled between 11 March 2019 and 6 March 2021, and individual patient data prospectively collected at 287 centres in 59 participating countries during a two-week enrolment period per centre. The registry collected data relating to baseline characteristics, major outcomes (in-hospital death, acute heart failure, cardiogenic shock, bleeding, stroke/transient ischaemic attack, and 30-day mortality) and guideline-recommended NSTEMI care interventions: electrocardiogram pre- or in-hospital, pre-hospitalization receipt of aspirin, echocardiography, coronary angiography, referral to cardiac rehabilitation, smoking cessation advice, dietary advice, and prescription on discharge of aspirin, P2Y12 inhibition, angiotensin converting enzyme inhibitor (ACEi)/angiotensin receptor blocker (ARB), beta-blocker, and statin.

CONCLUSION

The EORP NSTEMI Registry is an international, prospective registry of care and outcomes of patients treated for NSTEMI, which will provide unique insights into the contemporary management of hospitalised NSTEMI patients, compliance with ESC 2015 NSTEMI Guidelines, and identify potential barriers to optimal management of this common clinical presentation associated with significant morbidity and mortality.

How impact investing firms are responding to sustain and grow social economy enterprises in light of the COVID-19 pandemic

The COVID-19-induced disruptions have hardest hit social economy enterprises. While impact investing is considered a promising vehicle to stimulate and grow social economy enterprises, little is known about how impact investors are actually responding to sustain and grow social economy enterprises amidst the COVID-19 pandemic. We find that impact investors sacrifice additional financial returns in pandemic-focused impact investments where they see the potential for attaining significantly higher than usual social impact by protecting hundreds of vulnerable social economy enterprises and beneficiaries amidst the pandemic. We also find that guarantees are introduced as an innovative impact investment instrument to tackle the pandemic, although they have remained heavily underutilized. Furthermore, debt instruments tend to dominate in pandemic-focused impact investments. Finally, in response to the pandemic, impact investors emphasize developing and strengthening a supportive social impact ecosystem to protect both portfolio and non-portfolio social economy enterprises and their beneficiaries. We also explain how the impact investing market has evolved during pandemic times and how it might evolve post-pandemic to support social economy enterprises.

Source identification, contamination status and health risk assessment of heavy metals from road dusts in Dhaka, Bangladesh

In this study, concentrations of Cr, Mn, Ni, Cu, Zn, Cd and Pb were determined in road dusts collected from different locations in Dhaka to assess source, contamination status and health risk. Energy-dispersive X-ray fluorescence spectroscopy and energy-dispersive X-ray spectroscopy were used to determine Cr, Mn, Ni, Cu, Zn, Cd and Pb and their mean concentrations were 162.27 ± 29.46, 721.18 ± 180.14, 35.65 ± 12.55, 104.56 ± 128.33, 515.32 ± 321.90, BDL, and 342.82 ± 591.20 mg/kg, respectively. Among the heavy metals, highest concentrations of Cu, Zn and Pb were found at urban sites-7 (municipal waste dumping) and 8 (medical waste incineration). Highest concentration of Cr followed by Cu and Zn was found at site-5 (Tejgaon, urban). Principal component analysis revealed that anthropogenic activities are the potential sources for Cr, Ni, Cu, Zn and Pb while earth crust for Mn. Pollution index and pollution load index results suggested that all the sites were contaminated and/or degraded by Cr, Cu, Zn and Pb except sites-9 (urban), 10 (sub-urban), 11 (rural) while sites-7 and 8 (urban) were extremely degraded. For noncarcinogenic health risk, hazard quotient values for dermal were higher compared to that of inhalation/ingestion. Though hazard index values were less than 1 at all the sites, these were at least one order of magnitude higher for children group than that of adult group, thus the children group may face more noncarcinogenic health risk at sites-7 and 8. Values of incremental lifetime cancer risk were from 10^-9 to 10^-11 showed no carcinogenic health risk by road dusts contaminated with the heavy metals.

Human health risk ​and receptor model-oriented sources of heavy metal pollution in commonly consume vegetable and fish species of high Ganges river floodplain agro-ecological area, Bangladesh

This study was intended to assess heavy metal contents and sources in commonly consumed vegetables and fish collected from the Jashore district of Bangladesh and to evaluate the probable human health risks via the ingesting of those vegetables and fish species. A total of 130 vegetable and fish samples were analyzed for As, Mn, Cu, Cr, Ni, and Pb concentration by an atomic absorption spectrophotometer. Metals and metalloids like As, Pb, and Cr in vegetable species were greater than the maximum allowable concentration (MAC), while Pb and cu in fish species exceeded the MAC. Pollution evaluation index values were ranges from 0.40-10.35 and 1.53–2.78 for vegetable and fish species, respectively, indicating light to serious pollution. Lactuca sativa followed by Cucurbita moschata, Amaranthus gangeticus for vegetables and Channa punctate, Oreochromis mossambicus, followed by Dendrobranchiata for fish are the most contaminated food items. The positive matrix factorization model showed that As (81.9%), Ni (48%), Cr (49.6%), Mn (46%), Pb (44.3%), and Cu (44.4%) for vegetable species and As (86.9%), Ni (90.5%), Mn (67.6%), Pb (65.3%), Cr (57%) and Cu (46.2%) for fish species were resulting from agrochemical, atmospheric emission, irrigation, contaminated feed, and mixed sources. The self-organizing map and principle component analysis indicates three spatial patterns e.g., As–Mn–Cu, Pb–Cr, and Ni in vegetables and As–Mn–Cr, Cu–Ni, and Pb in fish samples. The THQ values for single elements were less than 1 (except As for vegetables and Pb for fish species) for all food items but the HI values for all of the vegetables (2.18E+00 to 2.04E+01) and fish (1.07E+00 to 9.39E+00) samples were exceeded the USEPA acceptable risk level (HI > 1E+00). While the cancer risks only induced by As for all vegetables and fish species, which exceeded the USEPA safe level (TCR>1E-04). Sensitivity analysis indicates that metal concentration was the most responsible factor for carcinogenic risk.

Ambient Ionization Mass Spectrometry: Application and Prospective

Mass spectrometry (MS) is a formidable analytical tool for the analysis of non-polar to polar compounds individually and/or from mixtures, providing information on the molecular weights and chemical structures of the analytes. During the last more than one-decade, ambient ionization mass spectrometry (AIMS) has developed quickly, producing a wide range of platforms and proving scientific improvements in a variety of domains, from biological imaging to quick quality control. These methods have made it possible to detect target analytes in real time without sample preparation in an open environment, and they can be connected to any MS system with an atmospheric pressure interface. They also have the ability to analyze explosives, illicit drugs, disease diagnostics, drugs in biological samples, adulterants in food and agricultural products, reaction progress, and environmental monitoring. The development of novel ambient ionization techniques, such as probe electrospray ionization, paper spray ionization, and fiber spray ionization, employed even at picolitre to femtolitre solution levels to provide femtogram to attogram levels of the target analytes. The special characteristic of this ambient ion source, which has been extensively used, is the noninvasive property of PESI of examination of biological real samples. The results in the current review supports the idea that AIMS has emerged as a pioneer in MS-based approaches and that methods will continue to be developed along with improvements to existing ones in the near future.

Interpretability and Optimisation of Convolutional Neural Networks Based on Sinc-Convolution

Interpretability often seeks domain-specific facts, which is understandable to human, from deep-learning (DL) or other machine-learning (ML) models of black-box nature. This is particularly important to establish transparency in ML model's inner-working and decision-making, so that a certain level of trust is achieved when a model is deployed in a sensitive and mission-critical context, such as health-care. Model-level transparency can be achieved when its components are transparent and are capable of explaining reason of a decision, for a given input, which can be linked to domain-knowledge. This study used convolutional neural network (CNN), with sinc-convolution as its constrained first-layer, to explore if such a model's decision-making can be explained, for a given task, by observing the sinc-convolution's sinc-kernels. These kernels work like band-pass filters, having only two parameters per kernel - lower and upper cutoff frequencies, and optimised through back-propagation. The optimised frequency-bands of sinc-kernels may provide domain-specific insights for a given task. For a given input instance, the effects of sinc-kernels was visualised by means of explanation vector, which may help to identify comparatively significant frequency-bands, that may provide domain-specific interpretation, for the given task. In addition, a CNN model was further optimised by considering the identified subset of prominent sinc frequency-bands as the constrained first-layer, which yielded comparable or better performance, as compared to its all sinc-bands counterpart, as well as, a classical CNN. A minimal CNN structure, achieved through such an optimisation process, may help design task-specific interpretable models. To the best of our knowledge, the idea of sinc-convolution layer's task-specific significant sinc-kernel-based network optimisation is the first of its kind. Additionally, the idea of explanation-vector-based joint time-frequency representation to analyse time-series signals is rare in the literature. The above concept was validated for two tasks, ECG beat-classification (five-class classification task), and R-peak localisation (sample-wise segmentation task).

Arsenic, iron, and manganese in groundwater and its associated human health risk assessment in the rural area of Jashore, Bangladesh

This study investigated groundwater pollution and potential human health risks from arsenic, iron, and manganese in the rural area of Jashore, Bangladesh. Study results show that the mean value of groundwater pH is 7.25 ± 0.31, with a mean conductivity of 633.94 ± 327.41 μs/cm, while about 73, 97, and 91% of groundwater samples exceeded the Bangladesh drinking water standard limits for As, Fe, and Mn, respectively. Groundwater pollution evaluation indices, including the heavy metal pollution index, the heavy metal evaluation index, the degree of contamination, and the Nemerow pollution index, show that approximately 97, 82, 100, and 100% of samples are in the high degree of pollution category, respectively. Spatial distribution exhibited that the study area is highly exposed to As (73%), Fe (82%), and Mn (46%). In the case of non-carcinogenic health risk via oral exposure, about 94% of samples suggest a high category of risk for infants, and 97% of samples are found to be at high risk for children and adults. The carcinogenic risk of arsenic via an oral exposure pathway suggests that approximately 97% of the samples are found to be at high risk for infants, and all of the samples are at high risk for both adults and children.

Clinical presentation, disease course, and outcome of COVID-19 in hospitalized patients with and without pre-existing cardiac disease: a cohort study across 18 countries

AIMS

Patients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality.

METHODS AND RESULTS

We used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existing heart disease and in-hospital mortality. A total of 16 511 patients with COVID-19 were included (21.1% aged 66-75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male, and often had other comorbid conditions when compared with those without. Mortality was higher in patients with cardiac disease (29.7%; n = 1545 vs. 15.9%; n = 1797). However, following multivariable adjustment, this difference was not significant [adjusted risk ratio (aRR) 1.08, 95% confidence interval (CI) 1.02-1.15; P = 0.12 (corrected for multiple testing)]. Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure (aRR 1.19, 95% CI 1.10-1.30; P < 0.018) particularly for severe (New York Heart Association class III/IV) heart failure (aRR 1.41, 95% CI 1.20-1.64; P < 0.018). None of the other heart disease subtypes, including ischaemic heart disease, remained significant after multivariable adjustment. Serious cardiac complications were diagnosed in <1% of patients.

CONCLUSION

Considerable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare during hospitalization.

The association between elevated lipid profile and liver enzymes: a study on Bangladeshi adults

Dyslipidemia, a major contributor to cardiovascular diseases, is rapidly increasing in Asian countries including Bangladesh. In addition to the cardiovascular system, abnormal lipid levels are also known to cause complications in renal and hepatic systems. The data regarding dyslipidemia and its relationship with liver enzymes are scarce for the Bangladeshi population. Therefore, this study was conducted to estimate the prevalence of dyslipidemia and determine the relationship between lipid profile and liver enzymes in Bangladeshi adults. A total of 405 participants (318 males and 87 females) were enrolled in the study. Serum levels of TG, TC, LDL, HDL and liver enzymes including ALT, AST, GGT and ALP were analyzed using standard methods. Dyslipidemia and liver function tests abnormalities were defined according to the international standard guidelines. The association between elevated lipid profile markers and liver enzyme abnormalities was assessed by logistic regression analysis. Overall, the prevalence of elevated TG, TC, LDL and low HDL were 30.9%, 23.7%, 26.2% and 78.8%, respectively. On the other hand, the prevalence of elevated liver enzymes ALT, AST, GGT and ALP were 18.8%, 21.6%, 12.9% and 21.9%, respectively. Dyslipidemia and liver enzyme abnormalities were higher in diabetic and hypertensive participants than in the healthy participants. About 61% of participants with dyslipidemia had at least one or more elevated liver enzymes. In regression analysis, an independent association was observed between serum GGT and all lipid components. In conclusion, a high prevalence of dyslipidemia and liver enzyme abnormalities were observed among the study participants. Of the four liver enzymes, the serum levels of GGT showed an independent association with all lipid components. Moreover, this study indicates that subjects with dyslipidemia often have a higher chance of having liver diseases than subjects with no dyslipidemia. However, large-scale prospective studies are needed to understand the underlying mechanisms of lipid-induced hepatic dysfunction in the Bangladeshi population.

Poly- and Perfluorinated Alkyl Substances in Air and Water from Dhaka, Bangladesh

Bangladesh hosts extensive textile manufacturing, for some of which per- and polyfluorinated alkyl substances (PFAS) have been used to impart water and dirt repellency, among other things. Textile waste emissions to the atmosphere and discharge into rivers and other bodies of water could present a significant concern for human and ecosystem health, but there is little information on PFAS in Bangladesh. To assess the presence of ionic PFAS and their precursors in air and water from Dhaka, Bangladesh, polyethylene sheets were deployed for 28 days as passive samplers for neutral PFAS in outdoor air and water, while ionic PFAS were measured from discrete water grabs. Fluorotelomer alcohols (FTOHs) were detected at almost all sites in air and water; the most frequently detected compound was 6:2 FTOH, ranging from below instrumental detection limits (<IDL) to 70 ng m^-3 in air and from <IDL to -19 ng L^-1 in water. Of the ionic PFAS, perfluorobutanoic acid (PFBA), perfluorohexanoic acid, perfluorooctanoic acid, perfluorohexane sulfonic acid, and perfluorooctane sulfonic acid dominated in frequency of detection and magnitude, with concentrations ranging from 1.8 to 19.0 ng L^-1 in surface waters. The prevalence of 6:2 FTOH and PFBA across sites probably reflects their use in textile manufacturing and could indicate the industry's switch to shorter-chain PFAS alternatives. Environ Toxicol Chem 2022;41:334-342. © 2021 SETAC.

Performance of a Convolutional Neural Network Derived from PPG Signal in Classifying Sleep Stages

Automatic sleep stage classification is vital for evaluating the quality of sleep. Conventionally, sleep is monitored using multiple physiological sensors that are uncomfortable for long-term monitoring and require expert intervention. In this study, we propose an automatic technique for multi-stage sleep classification using photoplethysmographic (PPG) signal. We have proposed a convolutional neural network (CNN) that learns directly from the PPG signal and classifies multiple sleep stages. We developed models for two- (Wake-Sleep), three- (Wake-NREMREM) and four- (Wake-Light sleep-Deep sleep-REM) stages of sleep classification. Our proposed approach shows an average classification accuracy of 96.30%, 95.96%, and 93.60% for two, three, and four stages, respectively. Experimental results show that the proposed CNN model outperforms existing state-of-the-art models (classical and deep learning) in the literature.

Gas phase ion-molecule reactions of nitroaromatic explosive compounds studied by hollow cathode discharge ionization-mass spectrometry

In this study, we have developed a variable pressure operating hollow cathode discharge (HCD) ion source to investigate the gas phase ion-molecule reactions of nitroaromatic explosive compounds. The developed HCD ion source coupled MS system has also been validated as an analytical method to analyze explosives at trace levels. The ion source was designed in such a way that the plasma can be generated alternatively at high pressure (~30 Torr), medium pressure (~5 Torr) and low pressure (~1 Torr) regions. The plasma contains a sufficient amount of reactant ions, electrons and excited species, thus the gaseous analyte molecules were efficiently ionized when they passed through the plasma. In the ion-molecule reactions of the nitroaromatic explosives, the discharge products of NO_x^- (x = 2,3), O₃ and HNO₃ originating from the plasma-excited air were suggested to contribute to the formation of mostly [M - H]^-, [M - NO]^-, [M+NO₃-HNO₂]^- and [M-NO+HNO₃]^- adduct ions at the higher ion source pressures (~5 and 28 Torr) while the electron rich plasma leads to the formation of molecular ion, M^-•, at the lower ion source pressure (~1 Torr). Formation of the hydride-adduct ions of the nitroaromatic compounds reveals the surface-assisted Birch type reduction in the HCD plasma. The variety of spectral patterns in the air-assisted glow discharge would be useful for high through-put detection of TNT and TNT-related explosives. An ambient helium dielectric barrier discharge (DBD) ion source was also used and gave identical mass spectra of the nitroaromatic explosive compounds to those observed by the HCD ion source, but did not give any hydride-adduct ions of the explosive compounds. Ion formation mechanism of these ions is also discussed.

Spike Density Quantitative Trait Loci Detection and Analysis in Tetraploid and Hexaploid Wheat Recombinant Inbred Line Populations

Spike density (SD) is an agronomically important character in wheat. In addition, an optimized spike structure is a key basis for high yields. Identification of quantitative trait loci (QTL) for SD has provided a genetic basis for constructing ideal spike morphologies in wheat. In this study, two recombinant inbred line (RIL) populations (tetraploid RIL AM and hexaploid RIL 20828/SY95-71 (2SY)) previously genotyped using the wheat55K SNP array were used to identify SD QTL. A total of 18 QTL were detected, and three were major and one was stably expressed (QSd.sau-2SY-7A.2, QSd.sau-AM-5A.2, QSd.sau-AM-7B, and QSd.sau-2SY-2D). They can explain up to 23.14, 19.97, 12.00, and 9.44% of phenotypic variation, respectively. QTL × environment and epistatic interactions for SD were further analyzed. In addition, pyramiding analysis further revealed that there were additive effects between QSd.sau-2SY-2D and QSd.sau-2SY-7A.2 in 2SY, and QSd.sau-AM-5A.2 and QSd.sau-AM-7B in AM. Pearson's correlation between SD and other agronomic traits, and effects of major or stable QTL on yield related traits indicated SD significantly impacted spike length (SL), spikelet number per spike (SNS) and kernel length (KL). Several genes related to spike development within the physical intervals of major or stable QTL were predicted and discussed. Collectively, our research identified QTL with potential applications for modern wheat breeding and broadening the genetic basis of SD.