bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the Palynology of Coleus Lour. (Lamiaceae) from an Evolutionary Perspective
Authors: Nani Thaís Furtado , Chaves Ana Luisa Arantes , Calvelli João Vitor Barbosa , Barbosa Sandro , Davide Lisete Chamma 
Published: November 2024

Abstract

Coleus Lour. is known for its medicinal properties. However, this genus faces taxonomic challenges due to the aggregation of species formerly classified under Plectranthus L'Hér., resulting in numerous synonyms. To support the current taxonomic circumscription, this research focused on the pollen evaluation of Coleus species from both palynotaxonomic and evolutionary perspectives. Seventeen species were examined, including three for which novel data are presented in this study: Coleus amboinicus Lour., C. barbatus (Andrews) Benth. ex G.Don, and C. neochilus (Schltr.) Codd. The pollen grains were acetolyzed and examined using scanning electron microscopy. A similarity dendrogram was constructed based on pollen morphometric data. The phylogeny was developed using Bayesian inference with the aim of mapping the evolution of pollen size and morphology. The similarity dendrogram revealed six distinct pollen groups, differing in ornamentation (rugulate, reticulate, and bireticulate, with perforations and/or granules) and shape (prolate-spheroidal, prolate, subprolate, and oblate). Ancestral state reconstruction indicates that the most recent common ancestor of Coleus likely had subprolate pollen approximately 35 µm in size (polar axis), with an initial rapid diversification in grain size followed by a period of stabilization. Despite the current scarcity of pollen data, Coleus demonstrates significant potential for further palynological studies.
Triple-drug antibiotic therapy for disseminated nocardial abscess in the mediastinum and brain of an immunocompetent patient: a case report
Authors: Zhang Yue , Qi Zhongchun , Li Hua , Gao Hui 
Published: November 2024

Abstract

Background Nocardia are widely present in nature and considered opportunistic pathogens. First discovered by Edmond Nocard in 1888, they are gram-positive aerobic bacteria belonging to the class of Actinomycetes, an order of rod-shaped bacteria. Nocardia can result in hematogenous spread infection through the ruptured skin or respiratory tract when the host's immune system is compromised. Currently, 119 species of Nocardia have been identified, with 54 capable of causing infections in humans. Nocardial brain abscesses are a rare intracranial lesion, accounting for only 2% of all brain abscesses. This article reports a successfully cured case of mediastinal Nocardiainfection with disseminated brain abscess. The patient was initially admitted with suspected brain metastasis from lung cancer. The purpose of this report is to provide insight into the diagnosis and treatment of this disease.
Case presentation The patient presented with intermittent chills, shivering, and fever, with the highest temperature of 39˚C, accompanied by shoulder and back pain, dizziness, and headaches. A chest-enhanced computed tomography (CT) revealed multiple enhanced nodulars in the bilateral hilum and mediastinum. A head-enhanced CT revealed scattered multiple ring-enhanced nodules in both cerebral hemispheres and the left cerebrum, accompanied by extensive surrounding edema. The mediastinal puncture tissue culture confirmed the growth of Nocardia. After a thorough multidisciplinary discussion (MDT) to rule out the possibility of mediastinal and intracranial metastatic tumors, we promptly initiated treatment with a three-drug antibiotic regimen consisting of imipenem/cilastatin sodium, linezolid dextrose, and Trimethoprim-sulfamethoxazole (TMP-SMX). The patient ultimately achieved complete remission.
Conclusions People engaged in agricultural work should be alert to central nervous system infection caused by Nocardia and brain metastatic tumors for identification. Typical imaging findings contribute to the early diagnosis of nocardial abscesses. Vital for prompt treatment.
Sex-specific Body Composition Features Impacting Survival Outcomes in Surgically Managed Clear Cell Renal Cell Carcinoma
Authors: Jamadi Robab Hassanvand , Stretch Cynthia , Armstrong Victoria , Bathe Mathias T. , Tzameli Iphigenia , Pashos Evanthia , Li Junjie , Bezy Olivier , Baracos Vickie E. , Bathe Oliver F. 
Published: November 2024

Abstract

Purpose: Body composition phenotypes were investigated in 200 patients with clear cell renal cell carcinoma (ccRCC), focusing on muscularity, adiposity, and fat distribution. The goal was to identify prognostic body composition features in ccRCC and their clinical correlates.
Materials and Methods: A cohort of 200 patients with resected ccRCC and available CT scans annotated by The Cancer Genome Atlas was studied. Computed tomography (CT) scans were acquired from The Cancer Imaging Archive, then a single axial image landmarked at the third lumbar vertebra (L3) was analyzed for cross sectional area and radiodensity of skeletal muscle and adipose tissue. The relationships of various body composition features with other clinical factors and with overall survival (OS) were evaluated.
Results: There were sex-related differences in body composition phenotype. High subcutaneous fat density (SFD) was uncommon in females. In males, the most common features that co-existed were low subcutaneous adipose tissue (SAT) and high SFD. In females, sarcopenia and low muscle radiodensity (myosteatosis) were the most frequently co-existent features. On univariate analysis, sarcopenia, low SAT, high SFD and myosteatosis were associated with shorter OS. On multivariate analysis, sarcopenia is associated with shorter OS (HR 1.9, P=0.05), and high SFD also associated with shorter OS (HR 2.06, P=0.04). Sarcopenia was associated with more advanced disease, but high SFD was not.
Conclusions: Body composition features in males and females with ccRCC differ significantly. Sarcopenia and increased SFD are prognostic in ccRCC. Further studies are required to understand the pathogenesis of ccRCC-associated changes in body composition.
Convective weather characterization and prediction using Machine Learning algorithms: analysis for Amazon Region
Authors: Bueno Humberto Campos , Bonnet Suzanna Maria , França Gutemberg Borges 
Published: November 2024

Abstract

This study presents an objective tool for predicting convective storms (CS) in the Terminal Maneuverer Area of Manaus (TMA-Manaus), Amazon, Brazil, using Machine Learning (ML) algorithms. The occurrence and severity of CS events were characterized by atmospheric discharges (AD) using thresholds. The prediction models leverage AD thresholds as target and 12Z radiosonde data as predictors. The AD climatology between 2012 and 2017 for TMA-Manaus revealed that AD occurs in every month of the year, in this period there were only in 21 days without lightning. The analysis of feature importance for classifying CS stages revealed that the Showalter index, Bulk Richardson Number, Convective Available Potential Energy, Lifted index, and Equilibrium Level are the most relevant thermodynamic indices for classifying the convective state in the region. Results indicate that, for a small amount of AD (69/day), the mean POD and FAR for the ten selected models were 0.92±0.06 and 0.19±0.01, respectively. The QDA algorithm showed the best performance with a POD of 0.99 and a FAR of 0.19. However, as the AD threshold increased up to 5,000 AD per day, a decrease in model performance was observed, because SevereCS is rare compared to CS. The findings suggest that ML models using radiosonde data as predictors are only capable of predicting the occurrence or not of CS with relative accuracy, but the models are not capable of classifying whether it will be severe. The development of this tool marks a significant step towards improving the accuracy and timeliness of CS forecasts, thereby enhancing safety and efficiency of flights in the region.
Valuing water provisioning services in England: A regionalized application of the System of Environmental Economic Accounting--Ecosystem Accounting framework in the context of Natural Capital Accounting
Authors: Bogra Shelly 
Published: November 2024

Abstract

This research provides the first comprehensive physical water-use tables for England at the regional level, within the framework of the System of Environmental-Economic Accounting for Water (SEEA-Water). These tables quantify both the flows and values associated with the beneficiaries. The key novelties include: (i) development of ``first experimental quantification" of `green water' associated with agriculture and forestry in England, lacking in official statistics (ii) attributing biomass and forestry provisioning valuation to water-services appropriated by the land under these services, and (iii) first estimates of monetary valuation based on `Non-Tidal Surface Water' and `Ground water' used in other sectors of England, thus going beyond the monetary valuation of `Public water supply' use reported in official statistics. The study also offers insights on discounted valuation of water-provisioning' role in agricultural and forestry produce. Key limitation is lack of condition metrics at regional level, owing to lack of water-quality and water-pollution accounting at the regional scale. Key areas for future investigations include: provision of recent statistics of water-abstraction for England; segregation of recreational services related to water-based cultural service; disclosure of monetary valuations of regional abstraction licenses granted for uses other than `Public Water Supply'; disclosure of methodological reports enabling valuation of water ecosystem services; including information on different discounting rates, time-period; information on return-flows to enable development of water-supply accounts and degradation and/or depletion of local reservoirs; and provision of latest water-use, water-supply, and water-pollution statistics for England and other regions of the UK, namely, Scotland, Wales, and Northern-Ireland, among others.
Impact of a homegardening intervention on crop diversity: Results from a cluster-randomized trial in Bangladesh
Authors: Gabrysch Sabine , Kehlenbeck Katja , Waid Jillian , Lambrecht Nathalie , Wendt Amanda , Ali Masum 
Published: November 2024

Abstract

Homegardening has the potential to improve access to nutrient-dense foods. We evaluate the impact of a large Homestead Food Production intervention on crop species richness and homegarden management as pathway outcomes of the ‘Food and Agricultural Approaches to Reducing Malnutrition’ (FAARM) cluster‐randomized trial (NCT025‐05711) in rural North-eastern Bangladesh. Ninety-six settlements were allocated 1:1 to intervention (1337 women) and control arm (1368 women). During the three-year intervention (2015-2018) women received vegetable seeds and training in homegardening, poultry rearing, and nutrition. We assessed number and type of harvested garden crop species at baseline and every four months during and after the intervention, totalling 12 survey rounds. Impacts were measured overall and by year using mixed-effects linear regression. In its final year, the intervention increased the number of harvested vegetable species by 4.3 and total crop species by 6.3, more than double over control. We also saw sizable changes in production practices. Impacts were present in all seasons, consistent across gradients of wealth and education and maintained up to 2.5 years post-intervention when they seemed to spill over to controls. This study provides rigorous evidence that homegardening can have sustained positive impacts on year-round diversity of nutrient-rich garden crops produced by households.
Effectiveness of a School-Based Multimodal Intervention on Promoting Healthy Lifestyle Behaviours Among Schoolchildren. Previene-Cádiz Study.
Authors: Aragón-Martín Rubén , Gómez-Sánchez María del Mar , Martínez-Nieto José Manuel , Schwarz-Rodríguez Mónica , Rodríguez-Martín Amelia , Jiménez-Pavón David 
Published: November 2024

Abstract

Background
Childhood obesity is a global health concern with significant implications for long-term health outcomes. To address this issue, this study aimed to evaluate the effectiveness of a school-based multimodal intervention targeting healthy lifestyle behaviours among schoolchildren in the province of Cádiz. Methods: A quasi-experimental design was employed to compare outcomes between the experimental and control groups. The study sample consisted of 833 schoolchildren between 8 and 9 years of age who were enrolled in the third grade of primary education from 25 schools in the province of Cádiz. The intervention adopted a multimodal approach, targeting students, their families, and educational institutions, and was implemented over a 6-month period. The students participated in a healthy educational programme of 10 sessions and were provided with two workbooks to use at home with their families. Additionally, parents attended three training courses aimed at improving their children's lifestyle behaviours. The intervention aimed to achieve significant improvements in body composition, physical fitness, physical activity levels, sedentary behaviours, dietary patterns, and sleep patterns. Two statistical tests were conducted to compare groups before and after the intervention. First, the Mann‒Whitney U test was used for numerical variables, and second, the delta of the study variables was calculated, and a difference‒in-differences analysis was performed. Numerical delta variables were analysed via the Mann‒Whitney U test, and categorical delta variables were analysed via the chi‒square test. Results: The results suggested that the intervention produced moderate and variable effects in promoting healthier lifestyle behaviours among schoolchildren. While improvements were noted in the experimental group compared with the control group, these improvements did not fully meet the initial expectations. Conclusions: This outcome underscores the need for further research and adjustments in implementation, such as the integration of specialised external personnel to support teachers, embedding the intervention into the school curriculum, and extending its duration throughout an entire academic year. This study contributes valuable insights into childhood obesity prevention and intervention strategies, paving the way for future research aimed at promoting the health and well-being of children worldwide.
Sub-Femtomolar Drug Monitoring via Co-Calibration Mechanism with Nanoconfined DNA Probes
Authors: Li Fengyu , Chen Yonghuan , Li Xiuying , Yue Xinru , Yu Weihua , Shi Yuesen , He Zilong , Wang Yuanfeng , Huang Yu , Xia Fan 
Published: November 2024

Abstract

Synthetic drugs have fundamentally reshaped the illicit drug market due to their low cost, ease of production, and rapid manufacturing processes. However, current drug detection methods, reliant on complex instruments, face limited applicability and often neglect the influence of pH fluctuations, leading to potential bias and unreliable results. Herein, we proposed co-calibration mechanism of DNA probes in nanoconfined channel to achieve significantly enhanced target signal recognition in sweat range pH 3.0 ~ 8.0. The limit of detection (LOD) lows to 3.58 fM in artificial sweat with wide linear response range103 ~ 108 fM. Compared to the single DNA probe, the co-calibrated dual-DNA probes exhibits a broader linear response range, primarily attributed to the synergistic effects of surface wettability regulation and the hydrion capture in nanoconfined channel, which in turn reduces signal interference in proton transport. The linear response range has doubled, and the detection sensitivity has improved by 4 ~ 5 orders of magnitude compared to existing drug detection methods. This co-calibration strategy expands the application scope of aptamer-based composite probes, offering a novel approach for ultra-sensitive drug detection and showing significant potential in sweat sensing and drug monitoring fields.
Kitchen waste as a source of liquid bio fertilizer: its effect on growth, physiology of Green gram (Cicer arietinum L.) and Mungbean (Vigna radiata L.) cultivars
Authors: Chaudhari Pandurang Gourya , Chaudhary* Indra Jeet 
Published: November 2024

Abstract

The worldwide increasing human population caused problems to the food security and land for agriculture. Population growth also increase the pollution in environment especially waste generation from anthropogenic activities. Therefore, it is essential task for researchers and farmers to waste management and agricultural productivity improvement. The chemical fertilizers improve more crop productions but it damages both environmental ecology and human health with great severity. Therefore, researchers focus on bio-waste based technology for agricultural productivity and maintain soil fertility. Being a fundamental part of organic farming, biofertilizers are important for preserving soil fertility and sustainability because they fix atmospheric dinitrogen (N=N), mobilize fixed macro and micronutrients, or change insoluble P in the soil into forms that plants can use. sustaining soil structure and nutrient availability while increasing the uptake of N, P, K, and micronutrients. Presented study conducted for liquid bio fertilizer preparation from kitchen waste and its impacts on agricultural plants. Resultants the kitchen waste found the good sources of nutrients such as NPK and its application increased plant growth and physiology. Higher concentration of liquid fertilizer shows higher increment of plants growth and developments as compared to control plants. Nowadays, liquid biofertilizer technology has greater advantages than traditional carrier-based biofertilizer technology. Its help to waste management and crops yields. Therefore, various kitchen waste was used for this study. It will help waste management and soil fertility. The study may helpful for segregation of kitchen waste for good source of liquid fertilizer. Presented study will be helpful for sustainable waste management and economic growth. Study will also play a vital role for maintaining the soil health and pollution control technique.
Top 10 Potato Varieties in Maine and Their Resistances to Common Diseases
Authors: Ozturk I. K. , Andrade M.H.M.L. , Hao J. , Qu X. , Porter G.A. 
Published: November 2024

Abstract

Potato production is frequently challenged by many diseases that can affect crop yield and quality, and growers need to implement various disease management strategies to prevent disease losses. One of the best such strategies is selecting disease resistant varieties, and to this end potato breeding programs perform disease resistance screenings every year. Some of the disease resistance data is publicly available, however, some are in internal potato breeding program reports. This study aims to provide a summary of disease resistance profiles of the top 10 Maine potato varieties against common diseases such as late blight, early blight, three strains of Potato virus Y (PVY), Potato leafroll virus (PLRV), Verticillium wilt, and soft rot caused by Dickeya and Pectobacterium species. The results indicate notable differences in disease resistance among the varieties, providing valuable insights for potato growers in Maine as well in other states.
Clinical Features, Prognostic Factors, and Pattern of Failure in H3 G34-Mutant Diffuse Hemispheric Glioma: A Multi-Institutional Experience and Meta-Analysis
Authors: Tlais Dana , Roach Jordan T. , Tinkle Christopher L. , Zhang Qunyu , Li Xiaoyu , Lin Tong , Mostafa Ayatullah , Moreira Daniel C. , McNall-Knapp Rene Y. , Rush Sarah Z. , Le Brian H. , Sinno Sara , Agarwal Apeksha , Ginn Kevin F. , Green Richard M. , Partap Sonia , Onar-Thomas Arzu , Bag Asim K. , Chiang Jason 
Published: November 2024

Abstract

Background:
H3 G34-mutant diffuse hemispheric glioma (DHG) is an aggressive tumor with a poor prognosis. We investigated the relationship between patient outcomes and molecular characteristics, extent of resection, and temozolomide (TMZ) use. Additionally, we reviewed the patterns of treatment failure.
Methods:
Retrospective multi-institutional review of clinical, imaging, and molecular characteristics of 38 patients with newly diagnosed H3 G34-mutant DHG, supplemented by a meta-analysis.
Results:
The median age was 14 years (8–28 years). The median progression-free survival (PFS) was 0.6 years (95% CI 0.4–1.2 years), and the median overall survival (OS) was 1.8 years (95% CI 1.1-3.0 years). Gross total resection (GTR) was associated with improved PFS (p = 0.0078) compared to non-GTR. Twenty-two patients (57.9%) received frontline TMZ and had improved PFS compared to those without (p = 0.0034). Of the evaluable patients with progressive disease, 78% progressed within the high-dose RT field. MGMT promoter methylation was not significantly associated with PFS/OS or TMZ efficacy (33 evaluable cases, n = 19 with MGMT silencing, n = 14 without). PDGFRA amplification (n = 10) was associated with inferior OS (p = 0.0443), and CDKN2A homozygous deletion (n = 16) was associated with inferior PFS (p = 0.0204). In the meta-analysis cohort (n = 252), GTR/near-total resection had significantly better PFS (p < 0.0001) and OS (p < 0.0001), and MGMT promoter methylation was not associated with PFS/OS.
Conclusions:
In our cohort, MGMT promoter methylation was not a prognostic factor and was not associated with TMZ utility. The resection extent and TMZ use were associated with improved survival outcomes. As most treatment failures occurred within the high-dose RT field, extended fields are not warranted.
Flood impact assessment in remote areas using machine learning, SAR, and GIS: a case study of Ngabang District, Indonesia
Authors: Sampurno Joko , Putra Muhammad Ghaza Eka , Faryuni Irfana Diah , Adriat Riza 
Published: November 2024

ABSTRACT

Flooding in remote regions presents significant challenges due to data scarcity, complicating impact assessment and mitigation efforts. This research delineates an integrated methodology for quantifying flood impacts in such contexts. By leveraging machine-learning algorithms, Sentinel-1 synthetic aperture radar (SAR) imagery was combined with digital elevation model data and river proximity metrics to predict and accurately demarcate flood extents. Geographic information systems overlay techniques were then employed for spatial analysis of the floods’ impacts on population and infrastructural assets. The methodology was applied in a case study in Ngabang District, Indonesia, demonstrating its utility. Analysis using decision tree, random forest (RF), and gradient boosting machine models provided critical insights into flood prediction factors. The RF model was chosen as the best, successfully identified flood-prone regions, achieving an accuracy of 0.94 and a Kappa of 0.87 on the testing data, demonstrating its robustness. The flood map showed significant impacts, affecting 373.81 hectares, 10,706 people, 1,500 buildings, and 15 km of roads. This study highlights the importance of proximity, elevation, SAR imagery, and iterative model improvements in flood prediction, offering valuable insights for flood management and mitigation efforts in data-scarce regions.