bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of the Accuracy of the GNSS RO Temperature Data for Climate Monitoring over Africa
Authors: Sa’i Ibrahim Usman , Musa Tajul Ariffin , Aleem Kamorudeen , Youngu Terwase Tosin , Obadaki Yusuf , Anom Wan Aris , Nasara Mohammed Abdu 
Published: May 2024

Abstract

Africa is facing significant impacts from temperature and climate change, with a pronounced warming trend surpassing the global average over the past century. This trend is reshaping climates and ecosystems, leading to increased temperatures, more frequent heatwaves, and altered precipitation patterns across different regions. Severe weather events like droughts, cyclones, and floods pose risks to human lives and well-being. The decline in radiosonde stations across Africa and the lack of collocated meteorological sensors at a majority of GNSS ground-based stations present substantial hurdles in effectively monitoring and responding to climate change in the region. This study thus evaluates the validity of temperature data based on the GNSS Radio Occultation (RO) technique as an alternative to the in-situ radiosonde observations for climate change monitoring over Africa. Three datasets which include GNSS RO, Radiosonde, and ERA5, were analyzed using Python programming, focusing on temperature as the key variable. The validation process involved the use of ten (10) different performance metrics for assessing temperature data from the datasets, including NRMSE (%), Bias (mm), SDR, MAE, ACC, VC, MEF, RI, -squared, and SD Residuals (mm). Most of these metrics exhibited improved performance when dealing with a temperature discrepancy of approximately 1K, although a few stations showed weak or no correlation with certain metrics. Some stations displayed temperature differences as high as 7K due to the number of Radio Occultation Events (ROE) around the stations or problematic Radiosonde data, while most stations exhibited temperature variances of around 1K. These findings suggest that the GNSS RO technique could be considered for Africa due to the current status of the Radiosonde stations over the region.
Potential Plant-to-Plant Transmission: Shared Endophytic Bacterial Community between Ziziphus lotus and its Parasite Cuscuta epithymum
Authors: Radouane Nabil , Errafii Khaoula , Mouhib Salma , SiMhand Khadija Ait , Legeay Jean , Hijri Mohamed 
Published: May 2024

Abstract

Microbiota associated with host–parasite relationships offer an opportunity to explore interactions among plants, parasites, and microbes, thereby contributing to the overall complexity of community structures. The dynamics of ecological interactions between parasitic plants and their hosts in arid environments remain largely understudied, especially in Africa. This study aimed to examine the bacterial communities of Cuscuta epithymum L. (clover dodder), an epiphytic parasitic plant, and its host, Ziziphus lotus L. (jujuba),in an arid environment. Our goal was to uncover the ecological complexities of microbial communities within the framework of plant–plant interactions. We conducted a comprehensive analysis of the bacterial composition and diversity within populations of the C. epithymum parasite, the infected- and non-infected jujuba host, and their interface at the shoots of the host. This involved amplicon sequencing, targeting the V5–V6 regions of the 16S rRNA gene. A total of 5680 amplicon sequence variants (ASVs) were identified, with Pseudomonadota, Bacillota, and Actinobacteriota being prevalent phyla. Among the bacterial communities, three genera were dominant: Cutibacterium, Staphylococcus, and Acinetobacter. Interestingly, analyses of alpha- and beta-diversities revealed no significant difference between jujuba and its parasite, suggesting a shared shoot endophytic bacteriome. This finding advances our comprehension of microbial communities linked to plant–parasite interactions in the arid environments of Africa. Further studies on functional diversity and elucidation of the mechanisms by which bacterial communities transfer between host and parasite are needed.
Human liver organoids are susceptible to Plasmodium vivax infection
Authors: Nitaramorn Norapat , Kobpornchai Phorntida , Tongkrajang Nongnat , Chaisri Urai , Imwong Mallika , Kulkeaw Kasem 
Published: May 2024

Abstract

The eradication of Plasmodium vivax malaria iscomplicated due to the presence of hypnozoites, the hidden dormant form of the parasite that is present in the liver. Currently available drug regimens are effective at killing hypnozoites but cause side effects and are difficult to administer. Studies testing drugs for liver-stage malaria remain rare and mainly relyon the use of cancerous or immortalized hepatic cells and primary hepatocytes. Here, we examined the feasibility of using an emerging organoid platform to model liver-stage vivax malaria. Hepatic endoderm cells, endothelial progenitor cells and mesenchymal cells were generated from human induced pluripotent stem cells and self-assembled intoliver organoids. These liver organoids resemble mature hepatocytes in terms of albumin secretion, fat and glycogen storage and cytochrome activity. Following the invasion of P. vivaxsporozoites, the expression levels of Plasmodium 18S RNA transcripts were upregulated. Changes in the transcript levels of genes involved in cholesterol synthesis were also observed. Thus, stem cell-derived liver organoids are susceptible to infection with P. vivax sporozoites, paving the way for studies on the mechanism of hypnozoite formation and testing of possible hypnozoitocidal drugs.
Exploring winter diet, gut microbiota and parasitism in caribou using multi-marker metabarcoding of fecal DNA
Authors: Nagati Mélissande , Bergeron Marie-Josée , Gagné Patrick , Arsenault André , Droit Arnaud , Wilson Paul , Pittoello Gigi , Manseau Micheline , Martineau Christine 
Published: May 2024

Abstract

In conservation strategies, getting precise and repeatable information on the species’ diet and health without relying on invasive or laborious methods is challenging. Here, we developed an efficient and non-invasive workflow for the sequencing and analysis of four taxonomic markers from fecal DNA to characterize the gut microbiota, parasites, and plants and lichens composing the winter diet of caribou (Rangifer tarandus), Canada's most iconic endangered species. Sequencing of the 18S rRNA gene of eukaryotes from seven locations in Manitoba and Saskatchewan, Canada, allowed for the detection of several parasites in caribou feces but provided limited information about plants and lichens - only algal symbionts were detected. An improved sensitivity and higher taxonomic resolution for plants and lichens was achieved through the sequencing of the ITS2 region, which revealed a rich winter diet in caribou as well as differences among sampling locations. Sequencing of the 16S rRNA gene of prokaryotes highlighted the relationships between the gut microbiota and both the diet and parasites. Overall, our results showed the potential of this multi-marker DNA metabarcoding workflow as an efficient tool to generate relevant information on the diet and health of caribou populations and provide insights into the species biology and ecology.
Linking explainable artificial intelligence and soil moisture dynamics in a machine learning streamflow model
Authors: Ley Alexander , Bormann Helge , Casper Markus 
Published: May 2024

ABSTRACT

Machine learning algorithms are increasingly applied in hydrological studies with promising results. However, these algorithms generally lack the ability for easy interpretability of the results by users. In this study, we compare six different explainable artificial intelligence (XAI) algorithms that help understand the effect of input data on the simulation results. The methods are explored on two distinct approaches for streamflow modeling using a long short-term memory (LSTM) model: a single model approach using only meteorological forcing data and a regional approach including also static catchment attributes. To gain further insight into the internal dynamics of the LSTM models, the relationship between cell states and soil moisture is investigated. A strong correlation suggests that the LSTM models inherently capture the concept of soil moisture as a catchment-scale storage mechanism. The XAI methods are applied to derive a timestep of influence, revealing how many days of input data are relevant for the model output. All XAI methods result in similar seasonal patterns in the timestep of influence, suggesting that the methods are comparable. Setting soil moisture dynamics in context to seasonal development of the timestep of influence suggests resetting LSTM as soon as soil moisture saturation occurs.
Ensemble modelling of ice volume dynamics of Chhota Shigri Glacier in Himachal Pradesh from 2017 to 2022
Authors: Sinha Diksha , Singh Hemant , Varade Divyesh 
Published: May 2024

ABSTRACT
Glaciers are the source of freshwater for many perennial rivers around the world. Out of 215,000 glaciers apart from the polar ice sheets, the Himalayas constitute about 54,000 glaciers and are often referred to as the third pole on the Earth. In recent decades, the Himalayan glaciers have been experiencing increased recession as a consequence of climate change. Subsequently, understanding the dynamics of glacier ice parameters and volume becomes significant. In this study, an ensemble model of laminar-flow-based and basal-shear-stress-based models on the Chhota Shigri Glacier was investigated to understand the dynamics of glacier ice thickness over six years, from 2017 to 2022. The glacier volume was determined from the ensembled ice thickness. Our results indicate that the ensemble model yields the minimum ice thickness measurement of 102 ± 17.38 m and the maximum of 112 ± 19.04 m for the years 2017 and 2019, respectively. The estimated results show a correlation of 81% with a global ice thickness dataset. The ensemble approach provides better estimates for ice thickness accounting for more parameters affecting the glacier dynamics. From 2017 to 2022, the Chhota Shigri Glacier volume has been observed to show a slightly negative trend.
Point-of-use chlorine residuals and disinfection byproduct occurrences in rural households served by public water utilities in Appalachian Virginia
Authors: Rasheduzzaman Md , O'Connell Bethesda , Krometis Leigh-Anne , Brown Teresa , Cohen Alasdair 
Published: May 2024

ABSTRACT
We characterized concentrations of trihalomethanes (THMs), a measure of disinfection byproducts (DBPs), in tap water samples collected from households with utility-supplied water in two rural counties in Appalachian Virginia, and assessed associations with pH, free chlorine, and metal ions which can impact THM formation. Free chlorine concentrations in all samples (n = 27 homes) complied with EPA drinking water guidelines, though 7% (n = 2) of first draw samples and 11% (n = 3) of 5-min flushed-tap water samples exceeded the US Safe Drinking Water Act (SDWA) maximum contaminant level (MCL) for THM (80 ppb). Regression analyses showed that free chlorine and pH were positively associated with the formation of THM levels above SDWA MCLs (OR = 1.04, p = 0.97 and OR = 1.74, p = 0.79, respectively), while temperature was negatively associated (OR = 0.78, p = 0.38). Of the eight utilities serving study households, samples from water served by three different utilities exceeded the EPA MCL for THM. Overall, these findings do not indicate substantial exposures to DBPs for rural households with utility-supplied water in this region of southwest Virginia. However, given the observed variability in THM concentrations between and across utilities, and established adverse health impacts associated with chronic and acute DBP exposure, more research on DBPs in rural Central Appalachia is warranted.
Patterns of Prescription Medication Use Before Diagnosis of Early Age-Onset Colorectal Cancer: Population-Based Descriptive Study
Authors: Cheng Vienna , Sayre Eric C , Cheng Vicki , Garg Ria , Gill Sharlene , Farooq Ameer , De Vera Mary A 
Published: May 2024

Background
Colorectal cancer (CRC) is estimated to be the fourth most common cancer diagnosis in Canada (except for nonmelanoma skin cancers) and the second and third leading cause of cancer-related death in male and female individuals, respectively.

Objective
The rising incidence of early age-onset colorectal cancer (EAO-CRC; diagnosis at less than 50 years) calls for a better understanding of patients’ pathway to diagnosis. Therefore, we evaluated patterns of prescription medication use before EAO-CRC diagnosis.

Methods
We used linked administrative health databases in British Columbia (BC), Canada, to identify individuals diagnosed with EAO-CRC between January 1, 2010, and December 31, 2016 (hereinafter referred to as “cases”), along with cancer-free controls (1:10), matched by age and sex. We identified all prescriptions dispensed from community pharmacies during the year prior to diagnosis and used the Anatomical Therapeutic Chemical Classification system Level 3 to group prescriptions according to the drug class. A parallel assessment was conducted for individuals diagnosed with average age-onset CRC (diagnosis at age 50 years and older).

Results
We included 1001 EAO-CRC cases (n=450, 45% female participants; mean 41.0, SD 6.1 years), and 12,989 prescriptions were filled in the year before diagnosis by 797 (79.7%) individuals. Top-filled drugs were antidepressants (first; n=1698, 13.1%). Drugs for peptic ulcer disease and gastroesophageal reflux disease (third; n=795, 6.1%) were more likely filled by EAO-CRC cases than controls (odds ratio [OR] 1.4, 95% CI 1.2-1.7) and with more frequent fills (OR 1.8, 95% CI 1.7-1.9). We noted similar patterns for topical agents for hemorrhoids and anal fissures, which were more likely filled by EAO-CRC cases than controls (OR 7.4, 95% CI 5.8-9.4) and with more frequent fills (OR 15.6, 95% CI 13.1-18.6).

Conclusions
We observed frequent prescription medication use in the year before diagnosis of EAO-CRC, including for drugs to treat commonly reported symptoms of EAO-CRC.
The Distribution and Associated Factors of HIV/AIDS Among Youths in Guangxi, China, From 2014 to 2021: Bayesian Spatiotemporal Analysis
Authors: Li Juntong , Zhang Runxi , Lan Guanghua , Lin Mei , Tan Shengkui , Zhu Qiuying , Chen Huanhuan , Huang Jinghua , Ding Dongni , Li Chunying , Ruan Yuhua , Wang Na 
Published: May 2024

Abstract

Background
In recent years, the number of HIV/AIDS cases among youth has increased year by year around the world. A spatial and temporal analysis of these AIDS cases is necessary for the development of youth AIDS prevention and control policies.

Objective
This study aimed to analyze the spatial and temporal distribution and associated factors of HIV/AIDS among youth in Guangxi as an example.

Methods
The reported HIV/AIDS cases of youths aged 15‐24 years in Guangxi from January 2014 to December 2021 were extracted from the Chinese Comprehensive Response Information Management System of HIV/AIDS. Data on population, economy, and health resources were obtained from the Guangxi Statistical Yearbook. The ArcGIS (version 10.8; ESRI Inc) software was used to describe the spatial distribution of AIDS incidence among youths in Guangxi. A Bayesian spatiotemporal model was used to analyze the distribution and associated factors of HIV/AIDS, such as gross domestic product per capita, population density, number of health technicians, and road mileage per unit area.

Results
From 2014 to 2021, a total of 4638 cases of HIV/AIDS infection among youths were reported in Guangxi. The reported incidence of HIV/AIDS cases among youths in Guangxi increased from 9.13/100,000 in 2014 to 11.15/100,000 in 2019 and then plummeted to a low of 8.37/100,000 in 2020, followed by a small increase to 9.66/100,000 in 2021. The districts (counties) with relatively high HIV/AIDS prevalence among youths were Xixiangtang, Xingning, Qingxiu, Chengzhong, and Diecai. The reported incidence of HIV/AIDS among youths was negatively significantly associated with road mileage per unit area (km) at a posterior mean of −0.510 (95% CI −0.818 to 0.209). It was positively associated with population density (100 persons) at a posterior mean of 0.025 (95% CI 0.012‐0.038), with the number of health technicians (100 persons) having a posterior mean of 0.007 (95% CI 0.004‐0.009).

Conclusions
In Guangxi, current HIV and AIDS prevention and control among young people should focus on areas with a high risk of disease. It is suggested to strengthen the allocation of AIDS health resources and balance urban development and AIDS prevention. In addition, AIDS awareness, detection, and intervention among Guangxi youths need to be strengthened.
Preconception Care Interventions for Adolescents and Young Adults to Prevent Adverse Maternal and Child Health Outcomes: Protocol for an Evidence Gap Map
Authors: Padhani Zahra Ali , Tessema Gizachew A , Avery Jodie C , Rahim Komal Abdul , Boyle Jacqueline A , Meherali Salima , Salam Rehana A , Lassi Zohra S 
Published: May 2024

Background
Preconception is the period before a young woman or woman conceives, which draws attention to understanding how her health condition and certain risk factors affect her and her baby’s health once she becomes pregnant. Adolescence and youth represent a life-course continuum between childhood and adulthood, in which the prepregnancy phase lacks sufficient research.

Objective
The aim of the study is to identify, map, and describe existing empirical evidence on preconception interventions that enhance health outcomes for adolescents, young adults, and their offspring.

Methods
We will conduct an evidence gap map (EGM) activity following the Campbell guidelines by populating searches identified from electronic databases such as MEDLINE, Embase, CINAHL, and Cochrane Library. We will include interventional studies and reviews of interventional studies that report the impact of preconception interventions for adolescents and young adults (aged 10 to 25 years) on adverse maternal, perinatal, and child health outcomes. All studies will undergo title or abstract and full-text screening on Covidence software (Veritas Health Innovation). All included studies will be coded using the Evidence for Policy and Practice Information (EPPI) Reviewer software (EPPI Centre, UCL Social Research Institute, University College London). Cochrane Risk of Bias tool 2.0 and Assessing the Methodological Quality of Systematic Reviews-2 (AMSTAR-2) tool will be used to assess the quality of the included trials and reviews. A 2D graphical EGM will be developed using the EPPI Mapper software (version 2.2.4; EPPI Centre, UCL Social Research Institute, University College London).

Results
This EGM exercise began in July 2023. Through electronic search, 131,031 publications were identified after deduplication, and after the full-text screening, 18 studies (124 papers) were included in the review. We plan to submit the paper to a peer-reviewed journal once it is finalized, with an expected completion date in May 2024.

Conclusions
This study will facilitate the prioritization of future research and allocation of funding while also suggesting interventions that may improve maternal, perinatal, and child health outcomes.

International Registered Report Identifier (IRRID)
DERR1-10.2196/56052
Derivation and Validation of a Machine Learning Model for the Prevention of Unplanned Dialysis
Authors: Klamrowski Martin M. , Klein Ran , McCudden Christopher , Green James R. , Rashidi Babak , White Christine A. , Oliver Matthew J. , Molnar Amber O. , Edwards Cedric , Ramsay Tim , Akbari Ayub , Hundemer Gregory L. 
Published: May 2024

Key Points

Nearly half of all patients with CKD who progress to kidney failure initiate dialysis in an unplanned fashion, which is associated with poor outcomes.Machine learning models using routinely collected data can accurately predict 6- to 12-month kidney failure risk among the population with advanced CKD.These machine learning models retrospectively deliver advanced warning on a substantial proportion of unplanned dialysis events.

Background
Approximately half of all patients with advanced CKD who progress to kidney failure initiate dialysis in an unplanned fashion, which is associated with high morbidity, mortality, and health care costs. A novel prediction model designed to identify patients with advanced CKD who are at high risk for developing kidney failure over short time frames (6–12 months) may help reduce the rates of unplanned dialysis and improve the quality of transitions from CKD to kidney failure.

Methods
We performed a retrospective study using machine learning random forest algorithms incorporating routinely collected age and sex data along with time-varying trends in laboratory measurements to derive and validate 6- and 12-month kidney failure risk prediction models in the population with advanced CKD. The models were comprehensively characterized in three independent cohorts in Ontario, Canada—derived in a cohort of 1849 consecutive patients with advanced CKD (mean [SD] age 66 [15] years, eGFR 19 [7] ml/min per 1.73 m2) and validated in two external advanced CKD cohorts (n=1356; age 69 [14] years, eGFR 22 [7] ml/min per 1.73 m2).

Results
Across all cohorts, 55% of patients experienced kidney failure, of whom 35% involved unplanned dialysis. The 6- and 12-month models demonstrated excellent discrimination with area under the receiver operating characteristic curve of 0.88 (95% confidence interval [CI], 0.87 to 0.89) and 0.87 (95% CI, 0.86 to 0.87) along with high probabilistic accuracy with the Brier scores of 0.10 (95% CI, 0.09 to 0.10) and 0.14 (95% CI, 0.13 to 0.14), respectively. The models were also well calibrated and delivered timely alerts on a significant number of patients who ultimately initiated dialysis in an unplanned fashion. Similar results were found upon external validation testing.

Conclusions
These machine learning models using routinely collected patient data accurately predict near-future kidney failure risk among the population with advanced CKD and retrospectively deliver advanced warning on a substantial proportion of unplanned dialysis events. Optimal implementation strategies still need to be elucidated.
The Semantic Features of Noun-verb Metaphorical Compound verbs in Mandarin Chinese
Authors: ZHEN Xiyu 
Published: May 2024

As a closed category, noun-verb metaphorical compound verbs are not productive but still frequently used in Mandarin Chinese. The internal relationship between the morphemes is subordinate, often with the noun morphemes suggesting the vehicles of metaphor processes and the verb morphemes indicating the tenors. Even though these compounds are already formed through metaphor, their meanings can further develop through metaphor and thereby gain new metaphorical meanings. In addition, we examine the usages and semantic features of two metaphorical compound verbs can-shi and jing-tun through a corpus-based collocation study to tease out people’s internal understanding of their meanings.