Browse Articles

Altered metabolic profiles in colon and rectal cancer

Flexible Organic Crystalline Fibers and Loops with Strong Second Harmonic Generation

Emergence to dominance: Estimating time to dominance of SARS-CoV-2 variants using nonlinear statistical models

Background/Objective : Relative proportion of cases in a multi-strain pandemic like the COVID-19 pandemic provides insight on how fast a newly emergent variant dominates the infected population. However, the behavior of relative proportion of emerging variants is an understudied field. We investigated the emerging behavior of dominant COVID-19 variants using nonlinear statistical methods and calculated the time to dominance of each variant. Method : We used a phenomenological approach to model national- and regional-level variant share data from the national genomic surveillance system provided by the Centers for Disease Control and Prevention to determine the best model to describe the emergence of two recent dominant variants of the SARS-CoV-2 virus: XBB.1.5 and JN.1. The proportions were modeled using logistic, Weibull, and generalized additive models. Model performance was evaluated using the Akaike Information Criteria (AIC) and the root mean square error (RMSE). Findings : The Weibull model performed the worst out of all three approaches. The generalized additive model approach slightly outperformed the logistic model based on fit statistics, but lacked in interpretability compared to the logistic model. These models were then used to estimate the time elapsed from emergence to dominance in the infected population, denoted by the time to dominance (TTD). All three models yielded similar TTD estimates. The XBB.1.5 variant was found to dominate the population faster compared to the JN.1 variant, especially in HHS Region 2 (New York) where the XBB.1.5 was believed to emerge. This research expounds on how emerging viral strains transition to dominance, informing public health interventions against future emergent COVID-19 variants and other infectious diseases.

Simultaneous determination of lesinurad and co-administered drugs used in management of gout comorbidities to uncover potential pharmacokinetic interaction in rat plasma

Abstract Gout is one of the most prevalent forms of arthritis that is usually accompanied by other comorbidities. For this reason, multiple drugs are routinely prescribed for gout patients, which may affect the clinical course outcomes, and increase the risk of drug-drug interactions. This work presents a novel, simple, and sensitive high performance liquid chromatography (HPLC) method for the simultaneous determination of lesinurad (LES) and other co-administered drugs that are subject to potential pharmacokinetic interactions such as etoricoxib (ETC), eplerenone (EPL), and amiodarone (AMD) in rat plasma. Moreover, a pharmacokinetic study was conducted by co-administration of LES and ETC to rats to assess any possible alteration in their pharmacokinetic profiles and the obtained samples were analyzed using the developed method. Chromatographic separation was achieved using a gradient elution of a mobile phase consisting of acetonitrile and potassium dihydrogen orthophosphate buffer, pH 4.2 on a Zorbax Eclipse Plus C18 (4.6 × 250 mm, 5 μm particle size) column. The developed method exhibits adequate sensitivity with a LLOQ of 100 ng/mL and was successfully validated as per the FDA bioanalytical guidelines and was found to be linear over the range from 100 to 50,000 ng/mL for all the selected drugs. The results of the pharmacokinetic study showed an increase in the area under the curve (AUC) of each of the two drugs (LES and ETC) following the repeated administration of the other. This raises concerns of the possible renal injurious effect of ETC when co-prescribed with LES. Moreover, this work uncovers the necessity for therapeutic dose adjustment or increased clinical vigilance for side effects and/or lack of efficacy upon concomitant administration of the selected drugs to gout patients.

Donor–Acceptor Nanohoops: Impact of the Ratio and Arrangement of the Fluorenone and Carbazole Moieties

Understanding patterns of loneliness in older long-term care users using natural language processing with free text case notes

Loneliness and social isolation are distressing for individuals and predictors of mortality, yet data on their impact on publicly funded long-term care is limited. Using recent advances in natural language processing (NLP), we analysed pseudonymised administrative records containing 1.1 million free-text case notes about 3,046 older adults recorded in a London council between 2008 and 2020. We applied three NLP methods—document-term matrices, pre-trained embeddings, and transformer-based models—to identify loneliness or social isolation. The best-performing model, a bidirectional transformer, achieved an F1 score of 0.92 on a test set of unseen sentences. Using this model, we generated predictions for the full dataset and assessed construct validity through comparison with survey data and the literature. Our measure is associated with expected characteristics, such as living alone and impaired memory, and is a strong predictor of social inclusion services. Approximately 43% of individuals had a sentence indicating loneliness or isolation in their case notes at their initial care assessment, comparable to survey-based estimates. Unlike surveys, our indicator is linked to other administrative data, enabling development of models of service use with loneliness or isolation as independent variables. An open-source version of the model is available in a GitHub repository.

An improved and advanced method for dehazing coal mine dust images

Ti-catalyzed 1,2-Diamination of Alkynes Using 1,1-Disubstituted Hydrazines

Integrating soil and crop metrics with precision agriculture: Pusa N Doctor app for sustainable nitrogen management in maize

Efficient nitrogen (N) management is critical for sustaining high maize yields while minimizing environmental impacts, as conventional practices often lead to N losses, greenhouse gas emissions, and reduced eco-efficiency. To address these challenges, the “Pusa N Doctor” app was developed using dark green colour index (DGCI) for precision N management in maize. The app was further validated in experiment conducted with three N rates- 0 kg/ha (N0PK), 50 kg/ha (N0PK), and 75 kg/ha (N75PK) as basal, along with two splits of N at 35 and 45 DAS as per app (N50PK+App and N75PK+App) and GSTM (N50PK + GSTM and N75PK+GSTM). The plant height, leaf area index, and plant N concentration was highest in N75PK+App. The highest crop growth rate between 0-30 DAS was observed in the N75PK+App treatment (9.97 g/m²/day). Conversely, the maximum relative growth rate between 30-60 DAS was in the N50PK+App, while the lowest was in N75PK+App. The highest harvest index of 35.13% was in N50PK+App. Except for N75PK+App and recommended dose of fertilizer (RDF), the partial N balance was close to 1, with a minimum value of 0.87 in N75PK+App. The lowest virtual N was in N50PK+App (0.45), while in N75PK+App it was 2.16 times higher than RDF. All N fertilized treatments except N50PK+App witnessed increased cost of cultivation over RDF. N50PK+App had 29.5% lower GHGI of N2O, with 11.6% and 13.3% higher energy and GHG-based eco-efficiency respectively than RDF. Thus, applying 50 kg N as basal along with its 2 splitting as per Pusa N Doctor, optimizes maize-growth, N use efficiency, eco-efficiency, and reduces GHG emissions.

Association of PIV value with early mortality in ICU patients with sepsis-associated acute kidney injury from the MIMIC IV database

Enantioselective Hydrodifluoroalkylation of Alkenes with Conformationally Tuned Peptidyl Hydrogen Atom Transfer Catalysts

Correction: Metabolite changes during developmental transitions in Adonis amurensis Regel et Radde flowers: Insights from HPLC-MS analysis

Research on the extrusion characteristics for the geometry of materials in material extrusion process using heating syringe

Mechanism of Unexpected <i>In-Trans</i> Post-PKS Polyketide Reduction in Cochliodone Biosynthesis

Human sensory-like neuron surfaceome analysis

Acral and triggerable pain is a hallmark of diseases involving small nerve fiber impairment, yet the underlying cellular mechanisms remain elusive. A key role is attributed to pain-related proteins located within the neuronal plasma membrane of nociceptive neurons. To explore this, we employed human induced pluripotent stem cell-derived sensory-like neurons and enriched their surface proteins by biotinylation. Samples from three independent cell differentiations were analyzed via liquid chromatography tandem mass spectrometry. Detected proteins were categorized by cellular location and function, followed by generating an interaction network for deregulated surface proteins. Gene expression of selected proteins was quantified using real-time PCR. A comparative analysis was performed between a patient with Fabry disease (FD) and a healthy control, which we used as model system. We successfully extracted surfaceome proteins from human sensory-like neurons, revealing deregulation of 48 surface proteins in FD-derived neurons. Among the candidates with potential involvement in pain pathophysiology were CACNA2D3, GPM6A, EGFR, and ABCA7. Despite the lack of gene expression differences in these candidates, the interaction network indicated compromised neuronal network integrity. Our approach successfully enabled the extraction and comprehensive analysis of the surfaceome from human sensory-like neurons, establishing a novel methodological framework for investigating human sensory-like neuron biology and cellular disease mechanisms.

An efficient fire detection algorithm based on Mamba space state linear attention

Reduced occludin expression is related to unfavorable tumor phenotype and poor prognosis in many different tumor types: A tissue microarray study on 16,870 tumors

Occludin is a key component of tight junctions. Reduced occludin expression has been linked to cancer progression in individual tumor types, but a comprehensive and standardized analysis across human tumor types is lacking. To study the prevalence and clinical relevance of occludin expression in cancer, a tissue microarray containing 16,870 samples from 148 different tumor types and 608 samples of 76 different normal tissue types was analyzed by immunohistochemistry. Occludin immunostaining was observed in 10,746 (76.6%) of 14,017 analyzable tumors, including 18.9% with weak, 16.2% with moderate, and 41.6% with strong staining intensity. Occludin positivity was found in 134 of 148 tumor categories and was most frequent in adenocarcinomas (37.5-100%) and neuroendocrine neoplasms (67.9-100%), less common in squamous cell carcinomas (23.8-93%) and in malignant mesotheliomas (up to 48.1%), and rare in Non-Hodgkin’s lymphomas (1-2%) and most mesenchymal tumors. Reduced occludin staining was linked to adverse tumor features in several tumor types, including colorectal adenocarcinoma (advanced pT stage, p &lt; 0.0001; L1 status, p = 0.0384; absence of microsatellite instability, p &lt; 0.0001), pancreatic adenocarcinoma (advanced pT stage, p = 0.005), clear cell renal cell carcinoma (high ISUP grade, p &lt; 0.0001; advanced pT stage, p &lt; 0.0001; high UICC stage, p &lt; 0.0001; distant metastasis, p = 0.0422; shortened overall or recurrence-free survival, p ≤ 0.0116), papillary renal cell carcinoma (high pT stage, p &lt; 0.0001; high UICC stage, p = 0.0228; distant metastasis, p = 0.0338; shortened recurrence-free survival, p = 0.006), and serous high-grade ovarian cancer (advanced pT stage, p = 0.0133). Occludin staining was unrelated to parameters of tumor aggressiveness in breast, gastric, endometrial, and thyroidal cancer. Our data demonstrate significant levels of occludin expression in many different tumor entities and identify reduced occludin expression as a potentially useful prognostic feature in several tumor entities.

Equivalent elastic model of splitting grouting reinforcement in weak strata

Molecularly Responsive Aptamer-Functionalized Hydrogel for Continuous Plasmonic Biomonitoring

A study on the evolution of original sites of fortifications from the perspective of Historic Urban Landscape: Cases of Paris, Beijing, and Moscow

The Historic Urban Landscape theory underscores the importance of historical stratification processes in shaping the overall value of urban heritage. Building on this perspective, this study examines the stratification and evolution of the original sites of fortifications in Paris, Beijing, and Moscow, three global cities. First, historical research is conducted to identify the key moments of significant changes and their contextual backgrounds in these cities’ original sites of fortifications. Second, quantitative analysis is applied to calculate the changes in functional proportions across different periods. The findings reveal that, although the timing of major transformations varies among the three cities, all have undergone three distinct stages: demolition and planning, development and construction, and reflection and renewal. This evolutionary process is closely tied to the urbanization trajectories of each city, with the driving forces exhibiting notable commonalities and patterns.