Evaluation of Aflatoxins and Heavy Metals Exposure in the Local Feeds of Fish and Shrimp in Bangladesh.

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

Whole genome sequence of denitrifying bacterium Stutzerimonas stutzeri strain NGHE31, collected from an eutrophic wetland in Sunamganj, Bangladesh, following the 2017 flash floods.

Here, we report the whole genome sequence of Stutzerimonas stutzeri strain NGHE31, isolated from Dekhar Haor, following the 2017 flash flood that resulted in mass die-offs of local wildlife. The predicted genome size is 4,434,670 bp, with 63.97% GC content, 4,035 coding sequences, 3 rRNAs, and 50 tRNAs.

Ambient Processed rGO/Ti3CNTx MXene Thin Film with High Oxidation Stability, Photosensitivity, and Self-Cleaning Potential.

Solution-based processing offers advantages for producing thin films due to scalability, low cost, simplicity, and benignity to the environment. Here, we develop conductive and photoactivated self-cleaning reduced graphene oxide (rGO)/Ti3CNTx MXene thin films via spin coating under ambient conditions. The addition of a thin rGO layer on top of Ti3CNTx resulted in up to 45-fold improvement in the environmental stability of the film compared to the bare Ti3CNTx film. The optimized rGO/Ti3CNTx thin film exhibits an optical transmittance of 74% in the visible region of the spectrum and a sheet resistance of 19 kΩ/sq. The rGO/Ti3CNTx films show high rhodamine B discoloration activity upon light irradiation. Under UV irradiation, the electrically conductive MXene in combination with in situ formed semiconducting titanium oxide induces photogenerated charge carriers, which could potentially be used in photocatalysis. On the other hand, due to film transparency, white light irradiation can bleach the adsorbed dye via photolysis. This study opens the door for using MXene thin films as multifunctional coatings with conductive and potentially self-cleaning properties.

Immunomodulatory Role of Vitamin D on Gut Microbiome in Children.

Vitamin D plays a role in regulating the immune system and can be linked to the alteration of the gut microbiome, which leads to several immunological diseases. This systematic review aims to explore the relationship between Vitamin D and children's gut microbiome, as well as its impact towards the immune system. We have systematically collated relevant studies from different databases concerning changes in the gut microbiome of children from infants to 18 years old associated with Vitamin D and the immunological pathways. The studies utilized 16S rRNA sequencing analysis of fecal matter with or without Vitamin D supplementation and Vitamin D levels. Ten studies were selected for the review, among which eight studies showed significant alterations in the gut microbiome related to Vitamin D supplementation or Vitamin D levels. The taxa of the phylum Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria are the most altered in these studies. The alteration of the taxa alters the Th1 and Th2 pathways and changes the immune response. We will discuss how Vitamin D may contribute to the activation of immune pathways via its effects on intestinal barrier function, microbiome composition, and/or direct effects on immune responses. In conclusion, the studies examined in this review have provided evidence that Vitamin D levels may have an impact on the composition of children's gut microbiomes.

Snapshot multispectral imaging using a diffractive optical network.

Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network-based multispectral imaging system trained using deep learning to create a virtual spectral filter array at the output image field-of-view. This diffractive multispectral imager performs spatially-coherent imaging over a large spectrum, and at the same time, routes a pre-determined set of spectral channels onto an array of pixels at the output plane, converting a monochrome focal-plane array or image sensor into a multispectral imaging device without any spectral filters or image recovery algorithms. Furthermore, the spectral responsivity of this diffractive multispectral imager is not sensitive to input polarization states. Through numerical simulations, we present different diffractive network designs that achieve snapshot multispectral imaging with 4, 9 and 16 unique spectral bands within the visible spectrum, based on passive spatially-structured diffractive surfaces, with a compact design that axially spans ~72λm, where λm is the mean wavelength of the spectral band of interest. Moreover, we experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network that creates at its output image plane a spatially repeating virtual spectral filter array with 2 × 2 = 4 unique bands at terahertz spectrum. Due to their compact form factor and computation-free, power-efficient and polarization-insensitive forward operation, diffractive multispectral imagers can be transformative for various imaging and sensing applications and be used at different parts of the electromagnetic spectrum where high-density and wide-area multispectral pixel arrays are not widely available.

Genome-wide investigation of SnRK2 gene family in two jute species: Corchorus olitorius and Corchorus capsularis.

BACKGROUND: Sucrose non-fermenting-1 (SNF1)-related protein kinase 2 (SnRK2), a plant-specific serine/threonine kinase family, is associated with metabolic responses, including abscisic acid signaling under biotic and abiotic stresses. So far, no information on a genome-wide investigation and stress-mediated expression profiling of jute SnRK2 is available. Recent whole-genome sequencing of two Corchorus species prompted to identify and characterize this SnRK2 gene family. RESULT: We identified seven SnRK2 genes of each of Corchorus olitorius (Co) and C. capsularis (Cc) genomes, with similar physico-molecular properties and sub-group patterns of other models and related crops. In both species, the SnRK2 gene family showed an evolutionarily distinct trend. Highly variable C-terminal and conserved N-terminal regions were observed. Co- and CcSnRK2.3, Co- and CcSnRk2.5, Co- and CcSnRk2.7, and Co- and CcSnRK2.8 were upregulated in response to drought and salinity stresses. In waterlogging conditions, Co- and CcSnRk2.6 and Co- and CcSnRK2.8 showed higher activity when exposed to hypoxic conditions. Expression analysis in different plant parts showed that SnRK2.5 in both Corchorus species is highly expressed in fiber cells providing evidence of the role of fiber formation. CONCLUSION: This is the first comprehensive study of SnRK2 genes in both Corchorus species. All seven genes identified in this study showed an almost similar pattern of gene structures and molecular properties. Gene expression patterns of these genes varied depending on the plant parts and in response to abiotic stresses.

Super-resolution image display using diffractive decoders.

High-resolution image projection over a large field of view (FOV) is hindered by the restricted space-bandwidth product (SBP) of wavefront modulators. We report a deep learning-enabled diffractive display based on a jointly trained pair of an electronic encoder and a diffractive decoder to synthesize/project super-resolved images using low-resolution wavefront modulators. The digital encoder rapidly preprocesses the high-resolution images so that their spatial information is encoded into low-resolution patterns, projected via a low SBP wavefront modulator. The diffractive decoder processes these low-resolution patterns using transmissive layers structured using deep learning to all-optically synthesize/project super-resolved images at its output FOV. This diffractive image display can achieve a super-resolution factor of ~4, increasing the SBP by ~16-fold. We experimentally validate its success using 3D-printed diffractive decoders that operate at the terahertz spectrum. This diffractive image decoder can be scaled to operate at visible wavelengths and used to design large SBP displays that are compact, low power, and computationally efficient.

COVID-19 pandemic ramifications on residential Smart homes energy use load profiles.

The COVID-19 pandemic has significantly affected people's behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre- and post-COVID-19 pandemic times. The weekend usage patterns look similar pre- and post-COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.

A Novel and Robust Approach to Detect Tuberculosis Using Transfer Learning.

Deep learning has emerged as a promising technique for a variety of elements of infectious disease monitoring and detection, including tuberculosis. We built a deep convolutional neural network (CNN) model to assess the generalizability of the deep learning model using a publicly accessible tuberculosis dataset. This study was able to reliably detect tuberculosis (TB) from chest X-ray images by utilizing image preprocessing, data augmentation, and deep learning classification techniques. Four distinct deep CNNs (Xception, InceptionV3, InceptionResNetV2, and MobileNetV2) were trained, validated, and evaluated for the classification of tuberculosis and nontuberculosis cases using transfer learning from their pretrained starting weights. With an F1-score of 99 percent, InceptionResNetV2 had the highest accuracy. This research is more accurate than earlier published work. Additionally, it outperforms all other models in terms of reliability. The suggested approach, with its state-of-the-art performance, may be helpful for computer-assisted rapid TB detection.

International High-Risk Clones Among Extended-Spectrum ß-Lactamase-Producing Escherichia coli in Dhaka, Bangladesh.

Background: Escherichia coli is a major extended-spectrum ß-lactamase (ESBL)-producing organism responsible for the rapid spread of antimicrobial resistance (AMR) that has compromised our ability to treat infections. Baseline data on population structure, virulence, and resistance mechanisms in E. coli lineages from developing countries such as Bangladesh are lacking. Methods: Whole-genome sequencing was performed for 46 ESBL-E. coli isolates cultured from patient samples at the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b)-Dhaka. Sequence data were analyzed to glean details of AMR, virulence, and phylogenetic and molecular markers of E. coli lineages. Results: Genome comparison revealed presence of all major high-risk clones including sequence type 131 (ST131) (46%), ST405 (13%), ST648 (7%), ST410 (4.3%), ST38 (2%), ST73 (2%), and ST1193 (2%). The predominant ESBL gene and plasmid combination were bla CTX - M - 15 and FII-FIA-FIB detected in diverse E. coli phylogroups and STs. The bla NDM - 5 (9%) gene was present in prominent E. coli STs. One (2%) mcr-1-positive ST1011 E. coli, coharboring bla CTXM - 55 gene, was detected. The extraintestinal pathogenic E. coli genotype was associated with specific E. coli lineages. The single nucleotide polymorphism (SNP)-based genome phylogeny largely showed correlation with phylogroups, serogroups, and fimH types. Majority of these isolates were susceptible to amikacin (93%), imipenem (93%), and nitrofurantoin (83%). Conclusion: Our study reveals a high diversity of E. coli lineages among ESBL-producing E. coli from Dhaka. This study suggests ongoing circulation of ST131 and all major non-ST131 high-risk clones that are strongly associated with cephalosporin resistance and virulence genes. These findings warrant prospective monitoring of high-risk clones, which would otherwise worsen the AMR crises.

Perturbations in nitric oxide homeostasis promote Arabidopsis disease susceptibility towards Phytophthora parasitica.

Phytophthora species can infect hundreds of different plants, including many important crops, causing a number of agriculturally relevant diseases. A key feature of attempted pathogen infection is the rapid production of the redox active molecule nitric oxide (NO). However, the potential role(s) of NO in plant resistance against Phytophthora is relatively unexplored. Here we show that the level of NO accumulation is crucial for basal resistance in Arabidopsis against Phytophthora parasitica. Counterintuitively, both relatively low or relatively high NO accumulation leads to reduced resistance against P. parasitica. S-nitrosylation, the addition of a NO group to a protein cysteine thiol to form an S-nitrosothiol, is an important route for NO bioactivity and this process is regulated predominantly by S-nitrosoglutathione reductase 1 (GSNOR1). Loss-of-function mutations in GSNOR1 disable both salicylic acid accumulation and associated signalling, and also the production of reactive oxygen species, leading to susceptibility towards P. parasitica. Significantly, we also demonstrate that secreted proteins from P. parasitica can inhibit Arabidopsis GSNOR1 activity.

Transporter associated with antigen processing 1 (TAP1) expression and prognostic analysis in breast, lung, liver, and ovarian cancer.

Transporter associated with antigen processing 1 (TAP1) is a transporter protein that represent tumor antigen in the MHC I or HLA complex. Any defect in the TAP1 gene resulting in inadequate tumor tracking. TAP1 influences multidrug resistance (MDR) in human cancer cell lines and hinders the treatment during chemotherapeutic. The association of TAP1 in cancer progression remains mostly unknown and further study of the gene in relation with cancer need to conduct. Thus, the study has designed to analyze the association between the TAP1 with cancer by computationally. The expression pattern of the gene has determined by using ONCOMINE, GENT2, and GEPIA2 online platforms. The protein level of TAP1 was examined by the help of Human Protein Atlas. Samples with different clinical outcomes were investigated to evaluate the expression and promoter methylation in cancer vs. normal tissues by using UALCAN server. The copy number alteration, mutation frequency, and expression level of the gene in different cancer were analyzed by using cBioPortal server. The PrognoScan and KM plotter platforms were used to perform the survival analysis and represented graphically. Additionally, pathway and gene ontology (GO) features correlated to the TAP1 gene were analyzed and presented by bar charts. After arranging the data in a single panel like correlating expression to prognosis, mutational and alterations characteristic, and pathways analysis, we observed some interesting insights that emphasized the importance of the gene in cancer progression. The study found the relationship between the TAP1 expression pattern and prognosis in different cancer tissues and shows how TAP1 affects the clinical characteristics. The analytical data presented in the study is vital to learn about the effect of TAP1 in tumor tissue, where previously studies showing contradicting expression of TAP1 in cancer tissue. The analyzed data can also be utilized further to evade the threats against chemotherapy. Overall, the study provided a new aspect to consider the role of TAP1 gene in cancer progression and survival status. KEY MESSAGES: • This study demonstrated, for the first time, a correlation between the TAP1 gene and tumor progression. • An upregulation of TAP1 mRNA was demonstrated in various cancer types. • This study reported a significant negative correlation for TAP1 gene expression and the survival rate in different cancer types.