bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multivariate canonical correlation analysis identifies additional genetic variants for chronic kidney disease
Authors: Osborne Amy J. , Bierzynska Agnieszka , Colby Elizabeth , Andag Uwe , Kalra Philip A. , Radresa Olivier , Skroblin Philipp , Taal Maarten W. , Welsh Gavin I. , Saleem Moin A. , Campbell Colin 
Published: March 2024

AbstractChronic kidney diseases (CKD) have genetic associations with kidney function. Univariate genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), two complementary kidney function markers. However, it is unknown whether additional SNPs for kidney function can be identified by multivariate statistical analysis. To address this, we applied canonical correlation analysis (CCA), a multivariate method, to two individual-level CKD genotype datasets, and metaCCA to two published GWAS summary statistics datasets. We identified SNPs previously associated with kidney function by published univariate GWASs with high replication rates, validating the metaCCA method. We then extended discovery and identified previously unreported lead SNPs for both kidney function markers, jointly. These showed expression quantitative trait loci (eQTL) colocalisation with genes having significant differential expression between CKD and healthy individuals. Several of these identified lead missense SNPs were predicted to have a functional impact, including in SLC14A2. We also identified previously unreported lead SNPs that showed significant correlation with both kidney function markers, jointly, in the European ancestry CKDGen, National Unified Renal Translational Research Enterprise (NURTuRE)-CKD and Salford Kidney Study (SKS) datasets. Of these, rs3094060 colocalised with FLOT1 gene expression and was significantly more common in CKD cases in both NURTURE-CKD and SKS, than in the general population. Overall, by using multivariate analysis by CCA, we identified additional SNPs and genes for both kidney function and CKD, that can be prioritised for further CKD analyses.
Antigen identification strategies and preclinical evaluation models for advancing tuberculosis vaccine development
Authors: Chugh Saurabh , Bahal Ritika Kar , Dhiman Rohan , Singh Ramandeep 
Published: March 2024

AbstractIn its myriad devastating forms, Tuberculosis (TB) has existed for centuries, and humanity is still affected by it. Mycobacterium tuberculosis (M. tuberculosis), the causative agent of TB, was the foremost killer among infectious agents until the COVID-19 pandemic. One of the key healthcare strategies available to reduce the risk of TB is immunization with bacilli Calmette-Guerin (BCG). Although BCG has been widely used to protect against TB, reports show that BCG confers highly variable efficacy (0-80%) against adult pulmonary TB. Unwavering efforts have been made over the past 20 years to develop and evaluate new TB vaccine candidates. The failure of conventional preclinical animal models to fully recapitulate human response to TB, as also seen for the failure of MVA85A in clinical trials, signifies the need to develop better preclinical models for TB vaccine evaluation. In the present review article, we outline various approaches used to identify protective mycobacterial antigens and recent advancements in preclinical models for assessing the efficacy of candidate TB vaccines.
De novo transcriptome for Chiloscyllium griseum, a long-tail carpet shark of the Indian waters
Authors: Harshan Pooja , Sukumaran Sandhya , Gopalakrishnan A. 
Published: March 2024

AbstractSharks have thrived in the oceans for 400 million years, experienced five extinctions and evolved into today’s apex predators. However, enormous genome size, poor karyotyping and limited tissue sampling options are the bottlenecks in shark research. Sharks of the family Orectolobiformes act as model species in transcriptome research with exceptionally high reproductive fecundity, catch prominence and oviparity. The present study illustrates a de novo transcriptome for an adult grey bamboo shark, Chiloscyllium griseum (Chondrichthyes; Hemiscyllidae) using paired-end RNA sequencing. Around 150 million short Illumina reads were obtained from five different tissues and assembled using the Trinity assembler. 70,647 hits on Uniprot by BLASTX was obtained after the transcriptome annotation. The data generated serve as a basis for transcriptome-based population genetic studies and open up new avenues in the field of comparative transcriptomics and conservation biology.
High resolution spatiotemporal modeling of long term anthropogenic nutrient discharge in China
Authors: Zhang Haoran , Sun Huihang , Zhao Ruikun , Tian Yu , Meng Yiming 
Published: March 2024

AbstractHigh-resolution integration of large-scale and long-term anthropogenic nutrient discharge data is crucial for understanding the spatiotemporal evolution of pollution and identifying intervention points for pollution mitigation. Here, we establish the MEANS-ST1.0 dataset, which has a high spatiotemporal resolution and encompasses anthropogenic nutrient discharge data collected in China from 1980 to 2020. The dataset includes five components, namely, urban residential, rural residential, industrial, crop farming, and livestock farming, with a spatial resolution of 1 km and a temporal resolution of monthly. The data are available in three formats, namely, GeoTIFF, NetCDF and Excel, catering to GIS users, researchers and policymakers in various application scenarios, such as visualization and modelling. Additionally, rigorous quality control was performed on the dataset, and its reliability was confirmed through cross-scale validation and literature comparisons at the national and regional levels. These data offer valuable insights for further modelling the interactions between humans and the environment and the construction of a digital Earth.
A database of in situ water temperatures for large inland lakes across the coterminous United States
Authors: Sorensen Troy , Espey Eamon , Kelley John G. W. , Kessler James , Gronewold Andrew D. 
Published: March 2024

AbstractWater temperature dynamics in large inland lakes are interrelated with internal lake physics, ecosystem function, and adjacent land surface meteorology and climatology. Models for simulating and forecasting lake temperatures often rely on remote sensing and in situ data for validation. In situ monitoring platforms have the benefit of providing relatively precise measurements at multiple lake depths, but are often sparser (temporally and spatially) than remote sensing data. Here, we address the challenge of synthesizing in situ lake temperature data by creating a standardized database of near-surface and subsurface measurements from 134 sites across 29 large North American lakes, with the primary goal of supporting an ongoing lake model validation study. We utilize data sources ranging from federal agency repositories to local monitoring group samples, with a collective historical record spanning January 1, 2000 through December 31, 2022. Our database has direct utility for validating simulations and forecasts from operational numerical weather prediction systems in large lakes whose extensive surface area may significantly influence nearby weather and climate patterns.
24-hour average PM2.5 concentration caused by aircraft in Chinese airports from Jan. 2006 to Dec. 2023
Authors: Cui Qiang , Jia Zike , Liu Yujie , Wang Yu , Li Ye 
Published: March 2024

AbstractSince 2006, the rapid development of China’s aviation industry has been accompanied by a significant increase in one of its emissions, namely, PM2.5, which poses a substantial threat to human health. However, little data is describing the PM2.5 concentration caused by aircraft activities. This study addresses this gap by initially computing the monthly PM2.5 emissions of the landing-take-off (LTO) stage from Jan. 2006 to Dec. 2023 for 175 Chinese airports, employing the modified BFFM2-FOA-FPM method. Subsequently, the study uses the Gaussian diffusion model to measure the 24-hour average PM2.5 concentration resulting from flight activities at each airport. This study mainly draws the following conclusions: Between 2006 and 2023, the highest recorded PM2.5 concentration data at all airports was observed in 2018, reaching 5.7985 micrograms per cubic meter, while the lowest point was recorded in 2022, at 2.0574 micrograms per cubic meter. Moreover, airports with higher emissions are predominantly located in densely populated and economically vibrant regions such as Beijing, Shanghai, Guangzhou, Chengdu, and Shenzhen.
FishSNP: a high quality cross-species SNP database of fishes
Authors: Zhang Lei , Li Heng , Shi Mijuan , Ren Keyi , Zhang Wanting , Cheng Yingyin , Wang Yaping , Xia Xiao-Qin 
Published: March 2024

AbstractThe progress of aquaculture heavily depends on the efficient utilization of diverse genetic resources to enhance production efficiency and maximize profitability. Single nucleotide polymorphisms (SNPs) have been widely used in the study of aquaculture genomics, genetics, and breeding research since they are the most prevalent molecular markers on the genome. Currently, a large number of SNP markers from cultured fish species are scattered in individual studies, making querying complicated and data reuse problematic. We compiled relevant SNP data from literature and public databases to create a fish SNP database, FishSNP (http://bioinfo.ihb.ac.cn/fishsnp), and also used a unified analysis pipeline to process raw data that the author of the literature did not perform SNP calling on to obtain SNPs with high reliability. This database presently contains 45,690,243 (45 million) nonredundant SNP data for 13 fish species, with 30,288,958 (30 million) of those being high-quality SNPs. The main function of FishSNP is to search, browse, annotate and download SNPs, which provide researchers various and comprehensive associated information.
Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function
Authors: Vazquez-Guerrero Patricia , Tuladhar Rohisha , Psychalinos Costas , Elwakil Ahmed , Chacron Maurice J. , Santamaria Fidel 
Published: March 2024

AbstractThere is an increasing need to implement neuromorphic systems that are both energetically and computationally efficient. There is also great interest in using electric elements with memory, memelements, that can implement complex neuronal functions intrinsically. A feature not widely incorporated in neuromorphic systems is history-dependent action potential time adaptation which is widely seen in real cells. Previous theoretical work shows that power-law history dependent spike time adaptation, seen in several brain areas and species, can be modeled with fractional order differential equations. Here, we show that fractional order spiking neurons can be implemented using super-capacitors. The super-capacitors have fractional order derivative and memcapacitive properties. We implemented two circuits, a leaky integrate and fire and a Hodgkin–Huxley. Both circuits show power-law spiking time adaptation and optimal coding properties. The spiking dynamics reproduced previously published computer simulations. However, the fractional order Hodgkin–Huxley circuit showed novel dynamics consistent with criticality. We compared the responses of this circuit to recordings from neurons in the weakly-electric fish that have previously been shown to perform fractional order differentiation of their sensory input. The criticality seen in the circuit was confirmed in spontaneous recordings in the live fish. Furthermore, the circuit also predicted long-lasting stimulation that was also corroborated experimentally. Our work shows that fractional order memcapacitors provide intrinsic memory dependence that could allow implementation of computationally efficient neuromorphic devices. Memcapacitors are static elements that consume less energy than the most widely studied memristors, thus allowing the realization of energetically efficient neuromorphic devices.
A Koopman operator-based prediction algorithm and its application to COVID-19 pandemic and influenza cases
Authors: Mezić Igor , Drmač Zlatko , Črnjarić Nelida , Maćešić Senka , Fonoberova Maria , Mohr Ryan , Avila Allan M. , Manojlović Iva , Andrejčuk Aleksandr 
Published: March 2024

AbstractFuture state prediction for nonlinear dynamical systems is a challenging task. Classical prediction theory is based on a, typically long, sequence of prior observations and is rooted in assumptions on statistical stationarity of the underlying stochastic process. These algorithms have trouble predicting chaotic dynamics, “Black Swans” (events which have never previously been seen in the observed data), or systems where the underlying driving process fundamentally changes. In this paper we develop (1) a global and local prediction algorithm that can handle these types of systems, (2) a method of switching between local and global prediction, and (3) a retouching method that tracks what predictions would have been if the underlying dynamics had not changed and uses these predictions when the underlying process reverts back to the original dynamics. The methodology is rooted in Koopman operator theory from dynamical systems. An advantage is that it is model-free, purely data-driven and adapts organically to changes in the system. While we showcase the algorithms on predicting the number of infected cases for COVID-19 and influenza cases, we emphasize that this is a general prediction methodology that has applications far outside of epidemiology.
Mortality reduction and cumulative excess incidence (CEI) in the prostate-specific antigen (PSA) screening era
Authors: McLaughlin Patrick W. , Cousins Matthew M. , Tsodikov Alex , Soni Payal D. , Crook Juanita M. 
Published: March 2024

AbstractThe extent to which PSA screening is related to prostate cancer mortality reduction in the United States (US) is controversial. US Surveillance, Epidemiology, and End Results Program (SEER) data from 1980 to 2016 were examined to assess the relationship between prostate cancer mortality and cumulative excess incidence (CEI) in the PSA screening era and to clarify the impact of race on this relationship. CEI was considered as a surrogate for the intensity of prostate cancer screening with PSA testing and subsequent biopsy as appropriate. Data from 163,982,733 person-years diagnosed with 544,058 prostate cancers (9 registries, 9% of US population) were examined. Strong inverse linear relationships were noted between CEI and prostate cancer mortality, and 317,356 prostate cancer deaths were avoided. Eight regions of the US demonstrated prostate cancer mortality reduction of 46.0–63.7%. On a per population basis, the lives of more black men than white men were saved in three of four registries with sufficient black populations for comparison. Factor(s) independent of CEI (potential effects of treatment advances) explained 14.6% of the mortality benefit (p-value = 0.3357) while there was a significant main effect of CEI (effect = −0.0064; CI: [−0.0088, −0.0040]; p-value < 0.0001). Therefore, there is a strong relationship between CEI and prostate cancer mortality reduction that was not related to factors independent of screening utilization. Minority populations have experienced large mortality reductions in the context of PSA mass utilization.
Classical cannabinoid receptors as target in cancer-induced bone pain: a systematic review, meta-analysis and bioinformatics validation
Authors: Zeng Feier , Wade Abbie , Harbert Kade , Patel Shrina , Holley Joshua S. , Dehghanpuor Cornelia K. , Hopwood Thomas , Marino Silvia , Sophocleous Antonia , Idris Aymen I. 
Published: March 2024

AbstractTo test the hypothesis that genetic and pharmacological modulation of the classical cannabinoid type 1 (CB1) and 2 (CB2) receptors attenuate cancer-induced bone pain, we searched Medline, Web of Science and Scopus for relevant skeletal and non-skeletal cancer studies from inception to July 28, 2022. We identified 29 animal and 35 human studies. In mice, a meta-analysis of pooled studies showed that treatment of osteolysis-bearing males with the endocannabinoids AEA and 2-AG (mean difference [MD] − 24.83, 95% confidence interval [95%CI] − 34.89, − 14.76, p < 0.00001) or the synthetic cannabinoid (CB) agonists ACPA, WIN55,212-2, CP55,940 (CB1/2-non-selective) and AM1241 (CB2-selective) (MD − 28.73, 95%CI − 45.43, − 12.02, p = 0.0008) are associated with significant reduction in paw withdrawal frequency. Consistently, the synthetic agonists AM1241 and JWH015 (CB2-selective) increased paw withdrawal threshold (MD 0.89, 95%CI 0.79, 0.99, p < 0.00001), and ACEA (CB1-selective), AM1241 and JWH015 (CB2-selective) reduced spontaneous flinches (MD − 4.85, 95%CI − 6.74, − 2.96, p < 0. 00001) in osteolysis-bearing male mice. In rats, significant increase in paw withdrawal threshold is associated with the administration of ACEA and WIN55,212-2 (CB1/2-non-selective), JWH015 and AM1241 (CB2-selective) in osteolysis-bearing females (MD 8.18, 95%CI 6.14, 10.21, p < 0.00001), and treatment with AM1241 (CB2-selective) increased paw withdrawal thermal latency in males (mean difference [MD]: 3.94, 95%CI 2.13, 5.75, p < 0.0001), confirming the analgesic capabilities of CB1/2 ligands in rodents. In human, treatment of cancer patients with medical cannabis (standardized MD − 0.19, 95%CI − 0.35, − 0.02, p = 0.03) and the plant-derived delta-9-THC (20 mg) (MD 3.29, CI 2.24, 4.33, p < 0.00001) or its synthetic derivative NIB (4 mg) (MD 2.55, 95%CI 1.58, 3.51, p < 0.00001) are associated with reduction in pain intensity. Bioinformatics validation of KEGG, GO and MPO pathway, function and process enrichment analysis of mouse, rat and human data revealed that CB1 and CB2 receptors are enriched in a cocktail of nociceptive and sensory perception, inflammatory, immune-modulatory, and cancer pathways. Thus, we cautiously conclude that pharmacological modulators of CB1/2 receptors show promise in the treatment of cancer-induced bone pain, however further assessment of their effects on bone pain in genetically engineered animal models and cancer patients is warranted.
Hospitalizations for coronavirus disease 2019: an analysis of the occurrence waves
Authors: Garbin Juliana Rodrigues Tovar , Leite Franciéle Marabotti Costa , Dell’Antonio Cristiano Soares Silva , Dell’Antonio Larissa Soares , dos Santos Ana Paula Brioschi , Lopes-Júnior Luís Carlos 
Published: March 2024

AbstractThe pandemic has been characterized by several waves defined by viral strains responsible for the predominance of infections. We aimed to analyze the mean length of hospital stay for patients with COVID-19 during the first three waves of the pandemic and its distribution according to sociodemographic and clinical variables. This retrospective study used the notifications of patients hospitalized for COVID-19 in a Brazilian state during the period of the three waves of the disease as the data source. There were 13,910 hospitalizations for confirmed COVID-19 cases. The first wave was the longest, with 4101 (29.5%) hospitalizations, while the third, although shorter, had a higher number of hospitalized patients (N = 6960). The average length of stay in the hospital in all waves was associated with age groups up to 60 years old., elementary, high school and higher education, residents of the periurban area Regarding the presence of comorbidities, there was a statistically significant difference in the mean number of days of hospitalization among patients with chronic cardiovascular disease and obesity (P < 0.001). In conclusion, the COVID-19 pandemic has been distinctly revealed among the waves.
Apis mellifera filamentous virus from a honey bee gut microbiome survey in Hungary
Authors: Papp Márton , Tóth Adrienn Gréta , Békési László , Farkas Róbert , Makrai László , Maróti Gergely , Solymosi Norbert 
Published: March 2024

AbstractIn Hungary, as part of a nationwide, climatically balanced survey for a next-generation sequencing-based study of the honey bee (Apis mellifera) gut microbiome, repeated sampling was carried out during the honey production season (March and May 2019). Among other findings, the presence of Apis mellifera filamentous virus (AmFV) was detected in all samples, some at very high levels. AmFV-derived reads were more abundant in the March samples than in the May samples. In March, a higher abundance of AmFV-originated reads was identified in samples collected from warmer areas compared to those collected from cooler areas. A lower proportion of AmFV-derived reads were identified in samples collected in March from the wetter areas than those collected from the drier areas. AmFV-read abundance in samples collected in May showed no significant differences between groups based on either environmental temperature or precipitation. The AmFV abundance correlated negatively with Bartonella apihabitans, Bartonella choladocola, and positively with Frischella perrara, Gilliamella apicola, Gilliamella sp. ESL0443, Lactobacillus apis, Lactobacillus kullabergensis, Lactobacillus sp. IBH004. De novo metagenome assembly of four samples resulted in almost the complete AmFV genome. According to phylogenetic analysis based on DNA polymerase, the Hungarian strains are closest to the strain CH-05 isolated in Switzerland.
Desert date seed extract-loaded chitosan nanoparticles ameliorate hyperglycemia and insulin deficiency through the reduction in oxidative stress and inflammation
Authors: Farid Alyaa , Ahmed Alaa , Alaa Olaya , Safwat Gehan 
Published: March 2024

AbstractPlants represents a huge source of bioactive materials that have been used since the old times in the treatment of many diseases.Balanites aegyptiaca, known as desert date, has been used in treatment of fever, diabetes and bacterial infection. Desert dates contains a hard seed that resembles 50–60% of the fruit. The seed extract contains many fatty acids, amino acids and other bioactive materials that gives the extract its antioxidant and anti-inflammatory properties. The study aimed to useBalanitesseed extract-loaded chitosan nanoparticles (SeEx-C NPs) for the treatment of streptozotocin (STZ)-induced diabetes in male Sprague Dawley rats. Animals were divided into two main divisions (healthy and diabetic rats). Each division contained seven groups (5 rats/group): control untreated group I, SeEx treated group II and group III (10 and 20 mg/kg b.w., respectively), C NPs treated group IV and group V (10 and 20 mg/kg b.w., respectively) and SeEx-C NPs treated group VI and group VII (10 and 20 mg/kg b.w., respectively). The therapeutical effects of SeEx-C NPs were evaluated through biochemical and immunological assessments in rats’ pancreases. The results showed that SeEx-C NPs (10 and 20 mg/kg b.w.) reduced the oxidative stress and inflammation in rats’ pancreases allowing the islets neogenesis. The loading of SeEx on C NPs allowed the delivery of fatty acids (oleic, lauric and myristic acid), amino acids (lysine, leucine, phenylalanine and valine) and minerals to pancreatic beta-cells in a sustainable manner. SeEx-C NPs administration successfully increased insulin secretion, allowed pancreatic islets neogenesis and reduced oxidative stress and inflammation.