bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epidemiological factors associated with the spatial distribution of two Rickettsia hosts in a locality of Yucatán, Mexico
Authors: Arroyo-Ramírez Abigail , Lugo-Caballero César , Reyes-Novelo Enrique , Noh-Pech Henry , Suárez-Galaz Alejandro , Panti-May Jesús Alonso , Rodríguez-Vivas R. Iván , Osorio-Primo Tana , Ruiz-Piña Hugo , Torres-Castro Marco 
Published: June 2024

Abstract

Rickettsioses caused by the spotted fever group (SFG) and typhus group (TG) are endemic in southeastern Mexico. Dogs and rodents can host several species of these bacteria, but little is known about the epidemiological factors that influence the infection risk in these mammals. This study aims to identify the frequency of Rickettsia SFG and TG infection in the studied animals, to determine the spatial distribution of the hosts, and to identify the factors associated with the infection risk. Genomic DNA was obtained from 66 dog blood samples and 36 rodent spleens collected in 48 dwellings from the rural locality of Ucú, Yucatan, Mexico. Rickettsia SFG or TG infection was determined using a multiplex semi-nested PCR (snPCR). The predictor variables for the infection risk in dogs and rodents were selected using generalized linear models (GLM) (p < 0.05). snPCR revealed Rickettsia DNA in 28.1% (18/64, 95% CI 17.6%-40.8%) of dogs and 27.8% (10/36, 95% CI 14.2%-45.2%) rodents. Only Rickettsia SFG was detected in dogs, while rodents hosted both Rickettsia TG and SFG. According to the corresponding GLM, dogs living in the interior area of Ucú have a lower risk of infection by Rickettsia SFG (RR = 0.14) than those living in the other areas. The presence of opossums (Didelphis sp.) in the dwelling increases the risk of Rickettsia TG infection in rodents (RR = 14), and the presence of SFG-infected dogs in the dwelling increases the risk of Rickettsia SFG infection in rodents (RR = 21).
Mini-consolidations or intermediate-dose cytarabine (IDAC) for the post-remission therapy of AML patients over 60. A retrospective study from the DATAML and SAL registries.
Authors: Récher Christian , Dumas Pierre-Yves , Bérard Emilie , Tavitian Suzanne , Leguay Thibault , GALTIER Jean , Alric Camille , Bidet Audrey , Delabesse Eric , Jean-Baptiste Rieu , VIAL Jean-Philippe , Vergez Francois , Luquet Isabelle , Klein Emilie , De Grande Anne-Charlotte , Sarry Audrey , Zukunft Sven , Platzbecker Uwe , Müller-Tidow Carsten , Baldus Claudia , Bornhauser Martin , Serve Hubert , Bertoli Sarah , Pigneux Arnaud , Röllig Christoph 
Published: June 2024

Abstract

According to current recommendations, older AML patients in first complete remission (CR) after induction chemotherapy should receive consolidation with intermediate-dose cytarabine (IDAC). However, no study has demonstrated the superiority of IDAC over other regimen. In this retrospective study, we compared the efficacy of mini-consolidations (idarubicin 8 mg/m² day 1, cytarabine 50 mg/m²/12 hours, day 1–5) and IDAC. Inclusion criteria were newly diagnosed AML, age > 60 years, first CR after induction and at least 1 cycle of consolidation. Of the 796 included patients, 322 patients received mini-consolidations and 474 patients received IDAC. Mini-consolidation patients were older, more often had de novo AML and unfavorable risk. The rate of allogeneic transplantation was higher in the IDAC group. The median number of cycles was higher in the mini-consolidation group (4 vs 2; P < 0.0001). Median relapse-free survival was 18 months with mini-consolidations and 12 months with IDAC (P = 0.0064). In multivariate analysis, the risk of relapse or death was significantly higher in the IDAC group (P = 0.004). Median OS was 36 vs. 31 months with mini-consolidations or IDAC, respectively (P = 0.46). In multivariate analysis, the consolidation regimen had no significant influence on OS (P = 0.43). In older AML patients, post-remission therapy with mini-consolidations represents an alternative to IDAC.
Unravelling wheat genotypic responses: insights into salinity stress tolerance in relation to oxidative stress, antioxidant mechanisms, osmolyte accumulation and grain quality parameters
Authors: Patwa Neha , Pandey Vanita , Gupta Om Parkash , Yadav Anita , Meena Mintu Ram , Ram Sewa , Singh Gyanendra 
Published: June 2024

Abstract

Background Salt stress is a prominent abiotic stressor that imposes constraints on grain yield and quality across various crops, including wheat (Triticum aestivum). This study focused on assessing the genetic diversity of 20 wheat genotypes categorized as tolerant, moderately tolerant, and sensitive with three genotypes of unknown tolerance. To address salinity stress-related problems, different morphophysiological, osmoprotectant, biochemical, yield, and grain quality-related parameters were analyzed under saline-sodic conditions.
Results The research findings revealed noteworthy variations among the genotypes in response to salinity stress. Greater accumulation of Na+ and lower K+ content were observed in response to salt stress in the sensitive varieties HD1941 and K9162. Proline, a stress indicator, exhibited significantly (p ≤ 0.05) greater accumulation in response to salinity stress, particularly in the tolerant cultivars KRL210 and KH65. Salt stress induced the most significant decrease (p ≤ 0.05) in spike length, thousand-grain weight, and hectolitre weight coupled with an increase in protein content in sensitive varieties such as K9162 and HD1941, resulting in diminished yield. Furthermore, salt-sensitive genotypes exhibited elevated protein content, reduced moisture, and increased sedimentation value.
Conclusion Correlation analysis of parameters under salinity stress showed that SOD, proline, and K+ contents can be used as the most efficient screening criteria for salinity stress during early developmental stages. Principal component analysis (PCA) revealed that DBW187, DBW303, and DBW222 varieties were tolerant to salinity stress and exhibited an effective antioxidant system against salinity. This study will facilitate salt-tolerant wheat breeding in terms of the identification of tolerant lines by screening for limited traits in a wide range of germplasms.
Strengthening the effectiveness of community health system: assessing the factors that enhance or constrain the delivery of health services within communities in Nigeria
Authors: Ozor Okechukwu , Etiaba Enyi , Onwujekwe Obinna 
Published: June 2024

Abstract

Introduction:
Sub-optimal community health service delivery (CHSD) has been a challenge constraining community health system (CHS) globally, especially in underdeveloped countries like Nigeria. This paper examined the key factors that either enhance or constrain CHSD in Nigeria at individual, community/facility and governmental levels while recommending evidence-based solutions for sustaining and improving CHSD within the framework of CHS.
Methods
Data was collected through a qualitative study undertaken in three states (Anambra, Akwa-Ibom and Kano) in Nigeria. Respondents were formal/informal health providers; community leaders and representatives of civil society organizations all purposively sampled. There were 90 in-depth interviews and 12 focus group discussions, which were audio-recorded, transcribed verbatim, and analyzed thematically using codes to identify key themes.
Results
Factors constraining CHSD at the individual level were: poor health seeking behavior and male dominance. At the community/facility level: superstitious/cultural beliefs and poor attitude of facility workers; at the governmental level were: inadequate financial support, embezzlement of funds, inadequate social amenities... Conversely, the enabling factors at the individual level were: community members participation, compassionate attitude of informal providers… At the community/facility level were: synergy between formal and informal providers; and support from community-based organizations and structures. At the governmental level were: government’s support to community-based formal/informal providers and clear line of communication.
Conclusions
CHSD through functional CHS can improve overall health systems strengthening and lead to improved community health. Policymakers should integrate CHSD in all program implementation and ultimately work with CHS as a veritable platform for effective community health service delivery.
Cerrado Calliphorids (Diptera, Insecta) Phenology’s in a Changing World
Authors: Mugnai Riccardo , Portela Ana Mara Nascimento , Milesi Silvia Vendruscolo , Silva Claudio Gonçalves 
Published: June 2024

Abstract

Calliphoridae is one of the most abundant families of flies of the order Diptera. Its importance is linked to different areas of knowledge, such as sanitary medicine, veterinary medicine, forensic entomology and ecology. Because of this, it is important to determine the factors that influence its distribution and phenology, allowing mitigation measures to be established. Furthermore, the information must be evaluated in the context of climate change, which can cause variations in population age and changes in distribution area. The present work aims to study the seasonal fluctuations and environmental factors that determine the species distribution found in a protected area in the state of Maranhão in northeastern Brazil. The distribution of Lucilia eximia (Wiedemann, 1819), Chrysomya albiceps (Wiedmann, 1819), Chrysomya megacephala(Fabricius, 1794), Hemilucilia benoisti (Séguy, 1925) and Hemiluciliasp. was related to vegetation coverage and limited by two main factors, humidity (60% lower limit) and temperature (30°C lower limit). Regarding seasonality, the species presented different phenologies, generally linked to the rainy season, with similar patterns between the genera and a population increase in periods of rain with intermediate intensity. This study contributes with new information about the interaction between environmental factors and phenology of five carrion fly species, providing insights into the interaction between environmental changes induced by climate change.
Towards transforming malaria vector surveillance using VectorBrain: a novel convolutional neural network for mosquito species, sex, and abdomen status identifications
Authors: Li Deming , Hegde Shruti , Kumar Aravind , Zacharias Atul , Mehta Parthvi , Muktineni Venkat , Srim Satwik , Patel Sunny , Suin Maitreya , Chellappa Rama , Acharya Soumyadipta 
Published: June 2024

Abstract

Malaria is a major public health concern, causing significant morbidity and mortality globally. Monitoring the local population density and diversity of the vectors transmitting malaria is critical to implementing targeted control strategies. However, the current manual identification of mosquitoes is a time-consuming and intensive task, posing challenges in low-resource areas like sub-Saharan Africa; in addition, existing automated identification methods lack scalability, mobile deployability, and field-test validity. To address these bottlenecks, a mosquito image database with fresh wild-caught specimens using basic smart phones is introduced, and we present a novel CNN-based architecture, VectorBrain, designed for identifying the species, sex, and abdomen status of a mosquito concurrently while being efficient and lightweight in computation and size. Overall, our proposed approach achieves 94.44±2% accuracy with a macro-averaged F1 score of 94.10±2% for the species classification,97.00±1% accuracy with a macro-averaged F1 score of 94.00±1% for the sex classification, and 83.20±3.1% accuracy with a macro-averaged F1 score of 80.54±3% for the abdominal status classification. VectorBrain running on local mobile devices, paired with a low-cost handheld imaging tool, is promising in transforming the mosquito vector surveillance programs by reducing the burden of expertise required and facilitating timely response based on accurate monitoring.
Urban expansion and the loss of agricultural lands and forest cover in Limbe, Cameroon
Authors: Enomah Lucy Deba , Acheampong Michael , Yu Qiuyan , Wilson Ismael , Tanyi Shirley , Muambo Kimberly Etombi 
Published: June 2024

Abstract

Using LULC change detection analysis, it is possible to identify changes due to urbanization, deforestation, or a natural disaster in an area. As the population growth and urbanization intensity increase, real time solutions for the effects of urbanization on land use are required to assess its implications on food security and livelihood. The study seeks to identify and quantify recent LULC changes in Limbe, Cameroon, and to measure rates of conversion between agricultural, forest, and urban lands between 1986 to 2020 using remote sensing and GIS. The classification result reveals that 2020 image has the highest overall accuracy of 94.6 while 2002 image have an overall accuracy of 89.2%. The overall gain for agriculture was approximately 4.6km2, urban has an overall gain of nearly 12.7 km2 while the overall loss for forest was − 16.9km2 during this period. Much of the land area previously occupied by forest is declining as pressures for urban area and new settlements increased. The study's findings have significant policy implications for sustainable land-use and cover practices. The results offer significant perspectives for researchers and decision makers who are interested in environmentally conscious development and sustainable land use.
A Novel ODMC Model for Malaria Blood Smear Classification using Deep Feature Fusion and Optimization
Authors: Iftikhar Saman , Imran Talha , ElAmir Malak , Fatima Kiran , Saeed Ammar , Alansari Noof Abdulaziz 
Published: June 2024

Abstract

Malaria poses an enormous threat to humanity with ever increasing cases annually. The research in the field of medical is contributing quite a lot in providing methods for premature diagnosis of malaria. Apart from medical research, information technology is also playing a vital role in proposing efficient methods for malaria diagnosis. To minimize the manual interference and boost the diagnosis accuracy, the automated systems are under study lately. An ensemble deep learning scheme is proposed in this paper with the fusion of features obtained by two state-of-the-art pre-trained deep Convolutional Neural Networks (CNN) models ResNet101 and SqueezeNet for the classification of malaria blood smears from red blood cells. A handcrafted feature extractor Local Binary Patterns (LBP) is also implemented along with the fused deep model features to deduce texture features of infected regions within image for better discrimination. Linear Discriminant Analysis (LDA) is employed for feature selection and optimization. At the end, the selected features are classified using a set of classifiers. The proposed Optimized Deep Malaria Classifier (ODMC) model achieved 99.73% accuracy with exceptional time efficiency.
Study of Influence of Preexisting Pain on the Body's Response to External Pain Stimuli
Authors: Ozek Burcu , Lu Zhenyuan , Radhakrishnan Srinivasan , Kamarthi Sagar 
Published: June 2024

Abstract

The assessment of pain severity is essential for effective pain treatment. In clinical settings, pain intensity assessment relies on self-reporting methods, which are subjective to individuals and impractical for non-communicative or critically ill patients. In literature, there have been numerous attempts to objectively measure pain. In these studies, participants experience only one source of pain, which is not always the case in patients' medical conditions. In this study, our objective is to investigate the hypothesis that an individual's physiological response to external pain differs depending on experiencing preexisting pain. The underlying premise is that the body may exhibit different physiological responses to an external pain stimulus, depending on the intensity of the preexisting pain. To assess this hypothesis, we recruited 39 healthy subjects aged 22-37; among them, 23 were female, and 16 were male. Physiological signals - Electrodermal Activity and Electromyography - were recorded while participants underwent a combination of heat pain and cold stimuli. Through statistical analysis, we confirmed the hypothesis that the body exhibits different physiological responses to an external pain stimulus when influenced by preexisting pain. We identified key features of physiological signals (e.g., statistics and distributions) that significantly differ in response to new pain stimuli.
RETRACTED: Enhanced Crop LAI Estimation via Random Forest Regression: Bayesian Optimization and Feature Selection Approach
Authors: Zhang Jun , Wu Qiang , Liu Cuiping , Xiong Shuping , Yang Hao , Chang Shenglong , Fu Yuanyuan , Yang Mohan , Yang Guijun , Ma Xinming , Cheng Jinpeng 
Published: June 2024

Abstract

The authors have requested that this preprint be removed from Research Square.
Comparative study of serum 6-hydroxy-5-methoxyindole-2-carboxylic acid, 5-S-cysteinyl-dopa, and lactate dehydrogenase levels as markers for malignant melanoma
Authors: Umemura Hiroshi , Takiwaki Masaki , Kikutani Yoshikuni , Fukuzawa Seketsu , Abe Kentaro , Fujino Kiyotaka , Sugihara Satoru , Tachibana Kota , Morizane Shin , Yamasaki Osamu 
Published: June 2024

Abstract

Background
With the development of novel therapies for advanced malignant melanoma (MM), biomarkers that can accurately reflect the progression of MM are needed. Recently, we have developed a method to measure the serum levels of 6-hydroxy-5-methoxyindole-2-carboxylic acid (6H5MI2C), a melanin-related metabolite, using mass spectrometry and reported that it may be a potential marker for MM.
Objective
In the present study, we compared the usefulness of serum levels of 6H5MI2C, 5-S-cysteinyl-dopa (5-S-CD), and lactate dehydrogenase (LD) as tumor markers for MM (n = 63).
Results
Among the three markers, only 6H5MI2C was significantly elevated in the metastatic group (stages III and IV) compared to the non-metastatic group (stages 0 to II). Additionally, 6H5MI2C with a cut-off level of 1.00 ng/mL showed higher sensitivity for metastatic MM than 5-S-CD and LD.
Conclusions
Thus, serum 6H5MI2C level has the potential to be a good marker for MM in comparison to 5-S-CD and LD.
Concordant and Discordant Breast Density Patterns by Different approaches for Assessing Breast Density and Breast Cancer Risk
Authors: Cho Yoosun , Park Eun Kyung , Chang Yoosoo , Kwon Mi-ri , Kim Eun Young , Kim Minjeong , Park Boyoung , Lee Sanghyup , Jeong Han Eol , Kim Ki Hwan , Kim Tae Soo , Lee Hyeonsoo , Kwon Ria , Lim Ga-Young , Choi JunHyeok , Kook Shin Ho , Ryu Seungho 
Published: June 2024

Abstract

Purpose
To examine the discrepancy in breast density assessments by radiologists, LIBRA software, and AI algorithm and their association with breast cancer risk.
Methods
Among 74,610 Korean women aged ≥ 34 years, who underwent screening mammography, density estimates obtained from both LIBRA and the AI algorithm were compared to radiologists using BI-RADS density categories (A–D, designating C and D as dense breasts). The breast cancer risks were compared according to concordant or discordant dense breasts identified by radiologists, LIBRA, and AI. Cox-proportional hazards models were used to determine adjusted hazard ratios (aHRs) [95% confidence intervals (CIs)].
Results
During a median follow-up of 9.9 years, 479 breast cancer cases developed. Compared to the reference non-dense breast group, the aHRs (95% CIs) for breast cancer were 2.37 (1.68–3.36) for radiologist-classified dense breasts, 1.30 (1.05–1.62) for LIBRA, and 2.55 (1.84–3.56) for AI. For different combinations of breast density assessment, aHRs (95% CI) for breast cancer were 2.40 (1.69–3.41) for radiologist-dense/LIBRA-non-dense, 11.99 (1.64–87.62) for radiologist-non-dense/LIBRA-dense, and 2.99 (1.99–4.50) for both dense breasts, compared to concordant non-dense breasts. Similar trends were observed with radiologists/AI classification: the aHRs (95% CI) were 1.79 (1.02–3.12) for radiologist-dense/AI-non-dense, 2.43 (1.24–4.78) for radiologist-non-dense/AI-dense, and 3.23 (2.15–4.86) for both dense breasts.
Conclusion
The risk of breast cancer was highest in concordant dense breasts. Discordant dense breast cases also had a significantly higher risk of breast cancer, especially when identified as dense by either AI or LIBRA, but not radiologists, compared to concordant non-dense breast cases.
Harnessing light-activated gallium porphyrins to combat intracellular Staphylococcus aureus in dermatitis: Insights from a simplified model.
Authors: Szymczak Klaudia , Rychłowski Michał , Zhang Lei , Nakonieczna Joanna 
Published: June 2024

Abstract

Staphylococcus aureus (S. aureus) can survive inside nonprofessional phagocytes such as keratinocytes, enabling it to evade antibiotics and cause recurrent infections once treatment stops. New antibacterial strategies to eliminate intracellular, multidrug-resistant bacteria are needed. This study used a keratinocyte model infected with methicillin-resistant S. aureus (MRSA) to test light-activated compounds, specifically heme-mimetic gallium (III) porphyrin (Ga3+CHP) and visible light, known as antimicrobial photodynamic inactivation (aPDI), for eliminating intracellular MRSA. Ga3+CHP was found to accumulate more in infected cells, particularly within lysosomal structures where MRSA resides. Flow cytometry and fluorescence microscopy revealed significant colocalization of MRSA and Ga3+CHP. Under aPDI, MRSA showed reduced adhesion to host cells and a 70% reduction in GFP signal from intracellular bacteria. Additionally, light-activated Ga3+CHP significantly decreased extracellular bacteria, reducing further infection potential. This study is the first to analyze aPDI toxicity in real time within an infection model, demonstrating that this method is neither cytotoxic nor phototoxic.
Evaluating the sensitivity of a chronic plant bioassay relative to an independently derived predicted no effect thresholds to support risk assessment of very hydrophobic organic chemicals
Authors: Redman Aaron , Paumen Miriam Leon , Letinski Daniel , Kelley Barbara , Sutherland Cary , Hedgpeth Bryan , Butler Josh , Prince Roger , Bragin Gail , Smith Abraham 
Published: June 2024

Abstract

Environmental risk assessments require high quality toxicity data to establish protective thresholds. The chronic effects of very hydrophobic organic compounds (VHOCs) in soils are often difficult to determine because multiple processes (e.g. sorption, volatilization, biodegradation) can complicate the interpretation of results. We have developed a standardized soil dosing and aging procedure for assessing bioavailability of high logKow VHOCs in a synthetic soil surrogate, and then used it to evaluate the toxicity of high logKow VHOCs across a range of test substance concentrations and soil organic carbon content. The soil preparation protocol resulted in relatively stable freely dissolved concentrations of test substance compared to bulk soil concentrations with some losses likely due to volatility and biodegradation. This dosing method wasused in a chronic terrestrial plant toxicity bioassay to evaluate the potential toxicity of VHOCs on complex reproductive endpoints like inflorescence and seed bud formation. Testing included common hydrocarbons and three very hydrophobic lubricant substances (logKow > 10). The toxicity data were used to evaluate existing predicted no effect concentrations (PNEC) that had originally been derived without these higher order chronic plant endpoints. The initial exposure concentrations were set at the independently-derived PNECs to provide an independent validation of the PNEC framework. This evaluation was performed to expand the domain of applicability of the PNEC to VHOCs and for the chronic terrestrial plant endpoints. We saw no effects on plant biomass or inflorescence production at these low exposure concentrations, demonstrating that the established PNEC is protective of long term plant health. The results of the present study confirm that the new dosing method is fit for purpose, and that the existing PNEC framework can be extended to chronic plant endpoints for VHOCs.