Neighborhood deprivation is not associated with abortion consideration or completion in patients with fetal myelomeningocele.

OBJECTIVE: The objective of this study was to evaluate whether patient-level neighborhood deprivation index (NDI) was associated with termination of pregnancy consideration and completion in patients presenting with fetal myelomeningocele. METHODS: This was a retrospective cohort analysis of patients with fetal myelomeningocele presenting to a fetal treatment center (FTC) in Illinois between 2018 and 2024. The exposure was NDI calculated from patient zip codes. The NDI was analyzed as both a dichotomous and ordinal exposure. The co-primary outcomes were abortion consideration prior to FTC consultation, ascertained by nurse intake, and abortion completion after consultation. Bivariate and log-binomial regression analyses were performed. Covariates were selected based on p < 0.10 on bivariate analyses. Otherwise, p < 0.05 indicated statistical significance. RESULTS: A total of 157 participants were included. Evaluation of neighborhood deprivation as a dichotomous exposure revealed no association with abortion consideration or completion. AdditionallLy, no association was found on log binomial modeling after controlling for gestational age at presentation to the FTC and maternal race or ethnicity for abortion consideration (aRR 0.87, 95% CI 0.59-1.28) or completion (aRR 0.86, 95% CI 0.59-1.28). These results were similar when treating the NDI as an ordinal exposure. CONCLUSIONS: Contrary to our hypothesis, NDI is not associated with abortion consideration or completion in patients with fetal myelomeningocele.

Anxiety and its risk factors among non-Japanese residents living in Japan undergoing COVID-19 situation: A cross-sectional survey.

INTRODUCTION: In the context of collective efforts taken in Japan to control the spread of COVID-19, the state of emergency and social distancing have caused a negative impact on the mental health of all residents, including foreign communities in Japan. This study aimed to evaluate the level of anxiety and its associated factors among non-Japanese residents residing in Japan during the COVID-19 pandemic. METHODS: A web-based survey in 13 languages was conducted among non-Japanese residents living in Japan during the COVID-19 situation. The State-Trait Anxiety Inventory assessed the level of anxiety-State (STAI-S) scores prorated from its six-item version. The multivariable logistic regression using the Akaike Information Criterion (AIC) method was performed to identify the associated factors of anxiety among participants. RESULTS: From January to March 2021, we collected 392 responses. A total of 357 valid responses were analyzed. 54.6% of participants suffered from clinically significant anxiety (CSA). In multivariable logistic model analysis, the CSA status or the high level of anxiety was associated with three factors, including having troubles/difficulties in learning or working, decreased sleep duration, and decreased overall physical health (p<0.05). CONCLUSION: Our study suggests several possible risk factors of anxiety among non-Japanese residents living in Japan undergoing the COVID-19 pandemic, including the troubles or difficulties in learning or working, the decrease in sleep duration, and the decrease in overall physical health.

Situation Analysis and Recommendations for the Biosecurity Status of Dairy Farms in Punjab, India: A Cross-Sectional Survey.

Farm biosecurity is an important herd management strategy to assure infection prevention and animal health. The present study aimed to evaluate the implementation of biosecurity measures on dairy farms in Punjab, India, using the standardized Biocheck.UGent™ scoring system. Convenience sampling was used to select 94 dairy farms, comprising both cattle and buffaloes, with a mean herd size of 74.8 animals. The study found that the mean external and internal biosecurity scores for the selected dairy farms were 45.4% and 43.7%, respectively. Among the subcategories, the highest external biosecurity score was observed for 'vermin control and other animals' (63%), and the highest internal biosecurity score was observed for 'adult cattle management' (76.6%). Whereas the lowest score for external biosecurity was observed for 'purchase and reproduction' (30.6%), and the lowest score for internal biosecurity was observed for 'health management' (33.6%). The overall mean biosecurity score of the present study was 44.8%, which was lower than the overall mean global score of 52%. The correlation analysis indicated a positive correlation between herd size and overall biosecurity scores, indicating that larger farms had, on average, higher biosecurity scores. Based on these results, it can be concluded that the implementation of biosecurity measures on dairy farms in Punjab needs improvement, especially in the subcategories of 'purchase and reproduction' and 'health management'. Further research to identify the factors influencing the implementation of biosecurity measures on dairy farms in the region is recommended.

BSEMS-A Blockchain-Based Smart Energy Measurement System.

The modern world's increasing reliance on automated systems for everyday tasks has resulted in a corresponding rise in power consumption. The demand is further augmented by increased sales of electric vehicles, smart cities, smart transportation, etc. This growing dependence underscores the critical necessity for a robust smart energy measurement and management system to ensure a continuous and efficient power supply. However, implementing such a system presents a set of challenges, particularly concerning the transparency, security, and trustworthiness of data storage and retrieval. Blockchain technology offers an innovative solution in the form of a distributed ledger, which guarantees secure and transparent transaction storage and retrieval. This research introduces a blockchain-based system, utilising Hyperledger Fabric and smart contracts, designed for the secure storage and retrieval of consumers' energy consumption data. Finally, a user-friendly web portal was designed and developed using the node.js framework, offering an accessible and intuitive interface to monitor and manage energy consumption effectively.

Low level of tonic interferon signalling is associated with enhanced susceptibility to SARS-CoV-2 variants of concern in human lung organoids.

There is tremendous heterogeneity in the severity of COVID-19 disease in the human population, and the mechanisms governing the development of severe disease remain incompletely understood. The emergence of SARS-CoV-2 variants of concern (VOC) Delta (B.1.617.2) and Omicron (B.1.1.529) further compounded this heterogeneity. Virus replication and host cell damage in the distal lung is often associated with severe clinical disease, making this an important site to consider when evaluating pathogenicity of SARS-CoV-2 VOCs. Using distal human lung organoids (hLOs) derived from multiple human donors, we compared the fitness and pathogenicity of SARS-CoV-2 VOC Delta and Omicron, along with an ancestral clade B variant D614G, and evaluated donor-dependent differences in susceptibility to infection. We observed substantial attenuation of Omicron in hLOs and demonstrated enhanced susceptibility to Omicron and D614G replication in hLOs from one donor. Transcriptomic analysis revealed that increased susceptibility to SARS-CoV-2 infection in these hLOs was associated with reduced tonic interferon signaling activity at baseline. We show that hLOs can be used to model heterogeneity of SARS-CoV-2 pathogenesis in humans, and propose that variability in tonic interferon signaling set point may impact susceptibility to SARS-CoV-2 VOCs and subsequent COVID-19 disease progression.

Impact of climate extreme events and their causality on maize yield in South Africa.

Extreme climate events can have a significant negative impact on maize productivity, resulting in food scarcity and socioeconomic losses. Thus, quantifying their effect is needed for developing future adaptation and mitigation strategies, especially for countries relying on maize as a staple crop, such as South Africa. While several studies have analyzed the impact of climate extremes on maize yields in South Africa, little is known on the quantitative contribution of combined extreme events to maize yield variability and the causality link of extreme events. This study uses existing stress indices to investigate temporal and spatial patterns of heatwaves, drought, and extreme precipitation during maize growing season between 1986/87 and 2015/16 for South Africa provinces and at national level and quantifies their contribution to yield variability. A causal discovery algorithm was applied to investigate the causal relationship among extreme events. At the province and national levels, heatwaves and extreme precipitation showed no significant trend. However, drought severity increased in several provinces. The modified Combined Stress Index (CSIm) model showed that the maize yield nationwide was associated with drought events (explaining 25% of maize yield variability). Heatwaves has significant influence on maize yield variability (35%) in Free State. In North West province, the maize yield variability (46%) was sensitive to the combination of drought and extreme precipitation. The causal analysis suggests that the occurrence of heatwaves intensified drought, while a causal link between heatwaves and extreme precipitation was not detected. The presented findings provide a deeper insight into the sensitivity of yield data to climate extremes and serve as a basis for future studies on maize yield anomalies.

Evaluation of Cordyceps militaris steroids as anti-inflammatory agents to combat the Covid-19 cytokine storm: a bioinformatics and structure-based drug designing approach.

Since the SARS-CoV-2 epidemic, researchers have been working on figuring out ways to tackle multi-organ failure and hyperinflation, which are brought on by a cytokine storm. Angiotensin-converting enzyme 2 (ACE2), a SARS-CoV-2 spike glycoprotein's cellular receptor, is involved in complicated molecular processes that result in hyperinflammation. Cordyceps militaris is one of the traditional Chinese medicines that is used as an immune booster, and it has exhibited efficacy in lowering blood glucose levels, seminal emissions, and infertility. In the current study, we explored the potential of Cordyceps militaris steroids as key agents in managing the anger of cytokine storm in Covid-19 using network ethnopharmacological techniques and structure-based drug designing approaches. The steroids present in Cordyceps militaris were initially screened against the targets involved in inflammatory pathways. The results revealed that out of 16 steroids, 5 may be effective against 17 inflammatory pathways by targeting 11 pathological proteins. Among the five steroids, beta-sitosterol, Cholest-5-en-3ß-ol, 3ß, and 7α-Dihydroxycholest-5-ene were found to interact with thrombin (F2), an important protein reported to reduce the severity of inflammatory mediators and Cholest-4-en-3-one was found to target Glucocorticoid receptor (NR3C1). The top docked steroid displayed key interactions with both targets, which retained key interactions throughout the 100 ns simulation period. These compounds were also shown high binding free energy scores in water swap studies. Based on obtained results the current study suggests the use of Cordyceps militaris as an add-on therapy that may reduce the progression of inflammatory co-morbidities among patients infected with SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

A systematic literature review for APT detection and Effective Cyber Situational Awareness (ECSA) conceptual model.

Advancements in computing technology and the growing number of devices (e.g., computers, mobile) connected to networks have contributed to an increase in the amount of data transmitted between devices. These data are exposed to various types of cyberattacks, one of which is advanced persistent threats (APTs). APTs are stealthy and focus on sophisticated, specific targets. One reason for the detection failure of APTs is the nature of the attack pattern, which changes rapidly based on advancements in hacking. The need for future researchers to understand the gap in the literature regarding APT detection and to explore improved detection techniques has become crucial. Thus, this systematic literature review (SLR) examines the different approaches used to detect APT attacks directed at the network system in terms of approach and assessment metrics. The SLR includes papers on computer, mobile, and internet of things (IoT) technologies. We performed an SLR by searching six leading scientific databases to identify 75 studies that were published from 2012 to 2022. The findings from the SLR are discussed in terms of the literature's research gaps, and the study provides essential recommendations for designing a model for early APT detection. We propose a conceptual model known as the Effective Cyber Situational Awareness Model to Detect and Predict Mobile APTs (ECSA-tDP-MAPT), designed to effectively detect and predict APT attacks on mobile network traffic.

DownScaleBench for developing and applying a deep learning based urban climate downscaling- first results for high-resolution urban precipitation climatology over Austin, Texas.

Cities need climate information to develop resilient infrastructure and for adaptation decisions. The information desired is at the order of magnitudes finer scales relative to what is typically available from climate analysis and future projections. Urban downscaling refers to developing such climate information at the city (order of 1 - 10 km) and neighborhood (order of 0.1 - 1 km) resolutions from coarser climate products. Developing these higher resolution (finer grid spacing) data needed for assessments typically covering multiyear climatology of past data and future projections is complex and computationally expensive for traditional physics-based dynamical models. In this study, we develop and adopt a novel approach for urban downscaling by generating a general-purpose operator using deep learning. This 'DownScaleBench' tool can aid the process of downscaling to any location. The DownScaleBench has been generalized for both in situ (ground- based) and satellite or reanalysis gridded data. The algorithm employs an iterative super-resolution convolutional neural network (Iterative SRCNN) over the city. We apply this for the development of a high-resolution gridded precipitation product (300 m) from a relatively coarse (10 km) satellite-based product (JAXA GsMAP). The high-resolution gridded precipitation datasets is compared against insitu observations for past heavy rain events over Austin, Texas, and shows marked improvement relative to the coarser datasets relative to cubic interpolation as a baseline. The creation of this Downscaling Bench has implications for generating high-resolution gridded urban meteorological datasets and aiding the planning process for climate-ready cities.

Epithelioid myofibroblastoma with concurrent presentation of LCIS and DCIS.

Myofibroblastoma (MFB) of the breast is a rare benign neoplasm of the mammary stroma. Several morphologic variants have been described in the literature, which can create diagnostic challenges for pathologists, in particular the epithelioid variant of MFB, which can mimic invasive lobular carcinoma. We report a case of a 72-year-old female who presented for a painless breast lump and was later found to have 2 lesions on imaging, with 1 lesion corresponding to the palpable lump and the other lying in a different quadrant. Core-needle biopsies demonstrated ductal carcinoma in-situ at both lesional sites with what was originally felt to be an invasive lobular carcinoma at the lesional site which did not correspond to the palpable lump. After mastectomy, with more complete visualization microscopically of the lesional area originally felt to be an invasive lobular carcinoma, the final pathology was consistent with a MFB, predominantly epithelioid variant, in addition to ductal carcinoma in-situ and lobular carcinoma in-situ. In this paper we describe the imaging findings of an epithelioid MFB and how its nonspecific nature necessitates close communication between the radiologist and pathologist to make the correct diagnosis.

Identification of natural peptides from "PlantPepDB" database as anti-SARS-CoV-2 agents: A protein-protein docking approach.

Background: A global pandemic owing to COVID-19 infection has created havoc in the entire world. The etiological agent responsible for this viral outbreak is classified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Still, there's no specific drug or preventive medication to treat SARS-CoV-2. This study was designed to demonstrate the efficacy of some anti-viral peptides obtained from a plant database i.e., PlantPepDB as potential ACE-2-Spike (S) protein complex neutralizers using a structure-based drug designing approach. Method: A total of 83 anti-viral plant peptides were screened from a peptide database i.e. PlantPepDB based on their reported anti-viral activities against various viral strains. In order to screen peptides that may potentially interfere with ACE-2 and S complex formation, molecular docking studies were conducted using the flare module of Cresset software and subsequently, analysed the crucial interactions between the peptides and S complexes and ACE-2/S complex. Herein, the interactions and docking scores obtained for ACE-2/S complex were considered as references. The S-peptides complexes which displayed superior interactions and docking scores than reference complex i.e., ACE2-S were considered as final hits. The Molecular dynamics studies were conducted for a period of 30 ns for each of the final hit/S complex to understand the interaction stability and binding mechanism of designed peptides. Results: The molecular docking results revealed that five peptides including Cycloviolacin Y3, Cycloviolacin Y1, White cloud bean defensin, Putative defensin 3.1, and Defensin D1 showed superior docking scores (i.e. -1372.5 kJ/mol to -1232.6 kJ/mol) when docked at the ACE2 binding site of S-protein than score obtained for the complex of ACE-2 and S protein i.e. -1183.4 kJ/mol. Moreover, these top five peptides manifested key interactions required to prevent the binding of S protein with ACE2. The molecular dynamics simulation study revealed that two of these five peptides i.e. Cycloviolacin Y3 and Cycloviolacin Y1 displayed minimal RMSD fluctuations. Conclusions: The current structure-based drug-designing approach shows the possible role of anti-viral plant peptides as potential molecules to be explored at the initial stage of viral pathogenesis.

Hepatic Dystrophic Calcification Secondary to Transarterial Chemoembolization: Case Report and Review of Literature.

Hepatocellular carcinoma (HCC) is a common malignancy usually treated with surgery. Patients who are not suitable for surgery undergo transarterial chemoembolization (TACE) which involves injecting anti-cancer drugs and embolizing agents into the hepatic artery. Although it is a relatively safe procedure with minor side effects, TACE can rarely cause dystrophic calcification in the liver. We report a case of a 58-year-old female who presented with right-sided chest pain. The patient had been previously treated for HCC with a TACE procedure. A chest x-ray revealed hepatic calcification which was likely secondary to the prior TACE. This case study emphasizes the significance of considering TACE as a potential cause of hepatic dystrophic calcification.

Histopathology and SARS-CoV-2 Cellular Localization in Eye Tissues of COVID-19 Autopsies.

Ophthalmic manifestations and tissue tropism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported in association with coronavirus disease 2019 (COVID-19), but the pathology and cellular localization of SARS-CoV-2 are not well characterized. The objective of this study was to evaluate macroscopic and microscopic changes and investigate cellular localization of SARS-CoV-2 across ocular tissues at autopsy. Ocular tissues were obtained from 25 patients with COVID-19 at autopsy. SARS-CoV-2 nucleocapsid gene RNA was previously quantified by droplet digital PCR from one eye. Herein, contralateral eyes from 21 patients were fixed in formalin and subject to histopathologic examination. Sections of the droplet digital PCR-positive eyes from four other patients were evaluated by in situ hybridization to determine the cellular localization of SARS-CoV-2 spike gene RNA. Histopathologic abnormalities, including cytoid bodies, vascular changes, and retinal edema, with minimal or no inflammation in ocular tissues were observed in all 21 cases evaluated. In situ hybridization localized SARS-CoV-2 RNA to neuronal cells of the retinal inner and outer layers, ganglion cells, corneal epithelia, scleral fibroblasts, and oligodendrocytes of the optic nerve. In conclusion, a range of common histopathologic alterations were identified within ocular tissue, and SARS-CoV-2 RNA was localized to multiple cell types. Further studies will be required to determine whether the alterations observed were caused by SARS-CoV-2 infection, the host immune response, and/or preexisting comorbidities.

Recognizing invasive breast carcinoma of no special type with medullary pattern.

Invasive breast carcinoma of no special type (IBC-NST) with medullary pattern is an uncommon histologic type of invasive breast carcinoma. It is associated with high-grade, poorly differentiated tumor cells that form large sheets of irregular confluent tumor cells associated with a prominent lymphocytic infiltrate. Patients with IBC-NST with medullary pattern are often postmenopausal women with a high body mass index and multiparity. We report the case of a 71-year-old woman who presented for routine screening mammography and breast mass suspicious for malignancy, initially thought to be invasive ductal carcinoma with an associated prominent lymphoid infiltrate. However, it was ultimately diagnosed as IBC-NST with medullary pattern, and radiologic imaging (particularly ultrasound and mammography) along with pathology review were critical in making the diagnosis. We make the case of the importance of radiographic imaging in diagnosing this condition, as the prognosis of IBC-NST with medullary pattern is typically more favorable compared to IBC-NST.

Successful lung transplantation using an allograft from a COVID-19-recovered donor: a potential role for subgenomic RNA to guide organ utilization.

Although the risk of SARS-CoV-2 transmission through lung transplantation from acutely infected donors is high, the risks of virus transmission and long-term lung allograft outcomes are not as well described when using pulmonary organs from COVID-19-recovered donors. We describe successful lung transplantation for a COVID-19-related lung injury using lungs from a COVID-19-recovered donor who was retrospectively found to have detectable genomic SARS-CoV-2 RNA in the lung tissue by multiple highly sensitive assays. However, SARS-CoV-2 subgenomic RNA (sgRNA), a marker of viral replication, was not detectable in the donor respiratory tissues. One year after lung transplantation, the recipient has a good functional status, walking 1 mile several times per week without the need for supplemental oxygen and without any evidence of donor-derived SARS-CoV-2 transmission. Our findings highlight the limitations of current clinical laboratory diagnostic assays in detecting the persistence of SARS-CoV-2 RNA in the lung tissue. The persistence of SARS-CoV-2 RNA in the donor tissue did not appear to represent active viral replication via sgRNA testing and, most importantly, did not negatively impact the allograft outcome in the first year after lung transplantation. sgRNA is easily performed and may be a useful assay for assessing viral infectivity in organs from donors with a recent infection.

SARS-CoV-2 infection and persistence in the human body and brain at autopsy.

Coronavirus disease 2019 (COVID-19) is known to cause multi-organ dysfunction1-3 during acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with some patients experiencing prolonged symptoms, termed post-acute sequelae of SARS-CoV-2 (refs. 4,5). However, the burden of infection outside the respiratory tract and time to viral clearance are not well characterized, particularly in the brain3,6-14. Here we carried out complete autopsies on 44 patients who died with COVID-19, with extensive sampling of the central nervous system in 11 of these patients, to map and quantify the distribution, replication and cell-type specificity of SARS-CoV-2 across the human body, including the brain, from acute infection to more than seven months following symptom onset. We show that SARS-CoV-2 is widely distributed, predominantly among patients who died with severe COVID-19, and that virus replication is present in multiple respiratory and non-respiratory tissues, including the brain, early in infection. Further, we detected persistent SARS-CoV-2 RNA in multiple anatomic sites, including throughout the brain, as late as 230 days following symptom onset in one case. Despite extensive distribution of SARS-CoV-2 RNA throughout the body, we observed little evidence of inflammation or direct viral cytopathology outside the respiratory tract. Our data indicate that in some patients SARS-CoV-2 can cause systemic infection and persist in the body for months.

SARS-CoV-2 Omicron BA.1 and BA.2 are attenuated in rhesus macaques as compared to Delta.

Since the emergence of SARS-CoV-2, five different variants of concern (VOCs) have been identified: Alpha, Beta, Gamma, Delta, and Omicron. Because of confounding factors in the human population, such as preexisting immunity, comparing severity of disease caused by different VOCs is challenging. Here, we investigate disease progression in the rhesus macaque model upon inoculation with the Delta, Omicron BA.1, and Omicron BA.2 VOCs. Disease severity in rhesus macaques inoculated with Omicron BA.1 or BA.2 was lower than those inoculated with Delta and resulted in significantly lower viral loads in nasal swabs, bronchial cytology brush samples, and lung tissue in rhesus macaques. Cytokines and chemokines were up-regulated in nasosorption samples of Delta animals compared to Omicron BA.1 and BA.2 animals. Overall, these data suggest that, in rhesus macaques, Omicron replicates to lower levels than the Delta VOC, resulting in reduced clinical disease.

Network Analysis Guided Designing of Multi-Targeted Anti-Fungal Agents: Synthesis and Biological Evaluation.

During the ongoing pandemic, there have been increasing reports of invasive fungal disease (IFD), particularly among immunocompromised populations. Candida albicans is one of the most common clinical pathogenic microorganisms which have become a serious health threat to population either infected with Covid-19 or on treatment with immunosuppressant's/broad-range antibiotics. Currently, benzothiazole is a well explored scaffold for anti-fungal activity, especially mercapto substituted benzothiazoles. It is reported that exploring the 2nd position of benzothiazoles yield improved anti-fungal molecules. Therefore, in the current study, lead optimization approach using bioisosteric replacement protocol was followed to improve the anti-fungal activity of an already reported benzothiazole derivative, N-(1,3-benzothiazole-2-yl)-2-(pyridine-3-ylformohydrazido) acetamide. To rationally identify the putative anti-candida targets of this derivative, network analysis was carried out. Complexes of designed compounds and identified putative targets were further analyzed for the docking interactions and their consequent retention after the completion of exhaustive MD simulations. Top seven designed compounds were synthesized and evaluated for in-vitro anti-fungal property against Candida, which indicated that compounds 1.2c and 1.2f possess improved and comparable anti-fungal activity to N-(1,3-benzothiazole-2-yl)-2-(pyridine-3-ylformohydrazido) acetamide and Nystatin, respectively.