Intracranial inoculation rapidly induces Nipah virus encephalitis in Syrian hamsters.

Nipah virus (NiV) is a highly pathogenic Paramyxovirus associated with outbreaks in Malaysia, Bangladesh, and India with high mortality rates. NiV infection causes fatal respiratory and neurological disease. The majority of survivors suffer from long-term neurological sequelae or late onset and relapsed encephalitis. The pathogenesis of neurological disease is complex and has not been able to be studied in current animal models as they are skewed towards the development of lethal respiratory disease rather than neurological disease. Although NiV neurological disease can be observed in animal models, there is currently no model where the majority of animals consistently develop neurological disease. Here, we developed a new Syrian hamster (Mesocricetus auratus) model to mimic neurological disease in humans. Hamsters were inoculated intracranially in the cerebellomedullary cistern with different doses of NiV, strain Malaysia. Intracranial NiV inoculation in the cerebellomedullary cistern resulted in a rapid progression towards severe neurological disease requiring euthanasia. High Nipah viral loads were detected in the brains, and NiV spread from the CNS to the lungs. Histopathologic examination of the brain showed ischemic necrosis, often accompanied by marked edema and hemorrhage. NiV antigen was detected primarily in meninges and cerebellum, but rarely observed in brain parenchyma. These histological lesions were different from the typical lesions observed in NiV-infected humans. Thus, despite the consistent development of neurological disease, intracranial inoculation does not result in a model representative of NiV neurological disease.

The effects of selenium supplementation on lipid profile in adults: A systematic review and meta-analysis of randomized controlled trials.

INTRODUCTION: Dyslipidemia with a considerable progression rate is a primary risk factor for CVDs if left untreated. Dietary interventions have explored the health influences of selenium on lipid profiles in adults, yet the findings remain contentious. This study seeks to determine if selenium supplementation can positively modify the lipid profile (total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), very-low-density lipoprotein cholesterol (VLDL), and high-density lipoprotein cholesterol (HDL-C) in adults. METHODS: Using predefined keywords, we searched online databases, including Scopus, PubMed, Web of Science Core Collection, and Google Scholar, for relevant studies published from inception through July 2024. A random-effects meta-analysis was then employed to pool the weighted mean differences (WMD) and 95 % CI for outcomes assessed by a minimum of three studies. RESULTS: Initially 1205 studies were obtained out of which 25 RCTs were decided to be included for further analyses. Selenium supplementation reduced VLDL (WMD: -1.53; 95 % CI: -2.86, -0.20), but did not change TG (WMD: 1.12; 95 % CI: -4.51, 6.74), TC (WMD: -2.25; 95 % CI: -6.80, 2.29), LDL-C (WMD: 1.60; 95 % CI: -4.26, 7.46), and HDL-C levels (WMD: 0.98; 95 % CI: - 0.02, 1.98). CONCLUSION: Our study showed significantly reduced VLDL but limited effects were observed in other lipid indexes. More extensive RCTs are required globally to achieve a holistic comprehension of the connection between selenium and lipid profile.

Commensal Yeast Promotes Salmonella Typhimurium Virulence.

Enteric pathogens engage in complex interactions with the host and the resident microbiota to establish gut colonization. Although mechanistic interactions between enteric pathogens and bacterial commensals have been extensively studied, whether and how commensal fungi affect pathogenesis of enteric infections remains largely unknown. Here we show that colonization with the common human gut commensal fungus Candida albicans worsened infections with the enteric pathogen Salmonella enterica serovar Typhimurium. Presence of C. albicans in the mouse gut increased Salmonella cecum colonization and systemic dissemination. We investigated the underlying mechanism and found that Salmonella binds to C. albicans via Type 1 fimbriae and uses its Type 3 Secretion System (T3SS) to deliver effector proteins into C. albicans . A specific effector, SopB, was sufficient to manipulate C. albicans metabolism, triggering increased arginine biosynthesis in C. albicans and the release of millimolar amounts of arginine into the extracellular environment. The released arginine, in turn, induced T3SS expression in Salmonella , increasing its invasion of epithelial cells. C. albicans deficient in arginine production was unable to increase Salmonella virulence in vitro or in vivo . In addition to modulating pathogen invasion, arginine also directly influenced the host response to infection. Arginine-producing C. albicans dampened the inflammatory response during Salmonella infection, whereas C. albicans deficient in arginine production did not. Arginine supplementation in the absence of C. albicans increased the systemic spread of Salmonella and decreased the inflammatory response, phenocopying the presence of C. albicans . In summary, we identified C. albicans colonization as a susceptibility factor for disseminated Salmonella infection, and arginine as a central metabolite in the cross-kingdom interaction between fungi, bacteria, and host.

GLObal Building heights for Urban Studies (UT-GLOBUS) for city- and street- scale urban simulations: Development and first applications.

We introduce University of Texas - GLObal Building heights for Urban Studies (UT-GLOBUS), a dataset providing building heights and urban canopy parameters (UCPs) for more than 1200 city or locales worldwide. UT-GLOBUS combines open-source spaceborne altimetry (ICESat-2 and GEDI) and coarse-resolution urban canopy elevation data with a machine-learning model to estimate building-level information. Validation using LiDAR data from six U.S. cities showed UT-GLOBUS-derived building heights had a root mean squared error (RMSE) of 9.1 meters. Validation of mean building heights within 1-km2 grid cells, including data from Hamburg and Sydney, resulted in an RMSE of 7.8 meters. Testing the UCPs in the urban Weather Research and Forecasting (WRF-Urban) model resulted in a significant improvement (55% in RMSE) in intra-urban air temperature representation compared to the existing table-based local climate zone approach in Houston, TX. Additionally, we demonstrated the dataset's utility for simulating heat mitigation strategies and building energy consumption using WRF-Urban, with test cases in Chicago, IL, and Austin, TX. Street-scale mean radiant temperature simulations using the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model, incorporating UT-GLOBUS and LiDAR-derived building heights, confirmed the dataset's effectiveness in modeling human thermal comfort in Baltimore, MD (daytime RMSE = 2.85°C). Thus, UT-GLOBUS can be used for modeling urban hazards with significant socioeconomic and biometeorological risks, enabling finer scale urban climate simulations and overcoming previous limitations due to the lack of building information.

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.

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.

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.

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.