bluuebunny/crossref_metadata_2025_split huggingface dataset:
Expanding the clinical spectrum of biglycan-related Meester-Loeys syndrome
Authors: Meester Josephina A. N. , Hebert Anne , Bastiaansen Maaike , Rabaut Laura , Bastianen Jarl , Boeckx Nele , Ashcroft Kathryn , Atwal Paldeep S. , Benichou Antoine , Billon Clarisse , Blankensteijn Jan D. , Brennan Paul , Bucks Stephanie A. , Campbell Ian M. , Conrad Solène , Curtis Stephanie L. , Dasouki Majed , Dent Carolyn L. , Eden James , Goel Himanshu , Hartill Verity , Houweling Arjan C. , Isidor Bertrand , Jackson Nicola , Koopman Pieter , Korpioja Anita , Kraatari-Tiri Minna , Kuulavainen Liina , Lee Kelvin , Low Karen J. , Lu Alan C. , McManus Morgan L. , Oakley Stephen P. , Oliver James , Organ Nicole M. , Overwater Eline , Revencu Nicole , Trainer Alison H. , Trivedi Bhavya , Turner Claire L. S. , Whittington Rebecca , Zankl Andreas , Zentner Dominica , Van Laer Lut , Verstraeten Aline , Loeys Bart L. 
Published: March 2024

AbstractPathogenic loss-of-function variants in BGN, an X-linked gene encoding biglycan, are associated with Meester-Loeys syndrome (MRLS), a thoracic aortic aneurysm/dissection syndrome. Since the initial publication of five probands in 2017, we have considerably expanded our MRLS cohort to a total of 18 probands (16 males and 2 females). Segregation analyses identified 36 additional BGN variant-harboring family members (9 males and 27 females). The identified BGN variants were shown to lead to loss-of-function by cDNA and Western Blot analyses of skin fibroblasts or were strongly predicted to lead to loss-of-function based on the nature of the variant. No (likely) pathogenic missense variants without additional (predicted) splice effects were identified. Interestingly, a male proband with a deletion spanning the coding sequence of BGN and the 5’ untranslated region of the downstream gene (ATP2B3) presented with a more severe skeletal phenotype. This may possibly be explained by expressional activation of the downstream ATPase ATP2B3 (normally repressed in skin fibroblasts) driven by the remnant BGN promotor. This study highlights that aneurysms and dissections in MRLS extend beyond the thoracic aorta, affecting the entire arterial tree, and cardiovascular symptoms may coincide with non-specific connective tissue features. Furthermore, the clinical presentation is more severe and penetrant in males compared to females. Extensive analysis at RNA, cDNA, and/or protein level is recommended to prove a loss-of-function effect before determining the pathogenicity of identified BGN missense and non-canonical splice variants. In conclusion, distinct mechanisms may underlie the wide phenotypic spectrum of MRLS patients carrying loss-of-function variants in BGN.
A near-complete genome assembly of Monochamus alternatus a major vector beetle of pinewood nematode
Authors: Xing Longsheng , Liu Bo , Yu Dunyang , Tang Xuan , Sun Jianghua , Zhang Bin 
Published: March 2024

AbstractThe Japanese sawyer beetle, Monochamus alternatus, is not only one of the most important wood boring pest itself, but also a major vector of the invasive pinewood nematode (PWN), which is the causal agent of the devastative pine wilt disease (PWD) and threats the global pine forest. Here, we present a near-complete genome of M. alternatus at the chromosome level. The assembled genome was 792.05 Mb with contig N50 length of 55.99 Mb, which is the largest N50 size among the sequenced Coleoptera insects currently. 99.57% of sequence was anchored onto ten pseudochromosomes (one X-chromosome and nine autosomes), and the final genome harbored only 13 gaps. BUSCO evaluation revealed the presence of 99.0% of complete core genes. Thus, our genome assembly represented the highest-contiguity genome assembly as well as high completeness in insects so far. We identified 20,471 protein-coding genes, of which 20,070 (98.04%) were functionally annotated. The genome assembly of M. alternatus provides a valuable resource for exploring the evolution of the symbiosis between PWN and the vector insects.
Comparative evaluation of non-invasive tests for risk stratification for cause specific mortality in at-risk population of hepatic fibrosis
Authors: Park Huiyul , Yoon Eileen L. , Kim Mimi , Kim Hye-Lin , Kim Mi Kyung , Kim Yu-Mi , Jun Dae Won 
Published: March 2024

AbstractOur study aimed to conduct a comparative evaluation of various noninvasive tests (NITs) for risk stratification in at-risk population for non-alcoholic fatty liver disease (NAFLD), focusing on cardiovascular and liver-related mortality. A total of 21,715 adults aged 40 years and older were enrolled at baseline. The mean follow-up period was 12.39 years. Three types of NITs (fibrosis-4 index [FIB-4], NAFLD fibrosis score [NFS], and steatosis-associated fibrosis estimator [SAFE] score) were used. When using the low cut-off as a 'rule-out' strategy, there were no significant differences in cardiovascular mortality between the 'rule-out' (low-risk) group and the 'rule-in' (intermediate- or high-risk) group based on FIB-4 (aHR = 1.029, P = 0.845) or NFS (aHR = 0.839, P = 0.271) classification. However, the SAFE score exhibited higher sensitivity in predicting cardiovascular mortality compared to FIB-4 or NFS (73.3% in SAFE score vs. 29.6% in FIB-4 or 21.3% in NFS). Only the SAFE score could effectively differentiate the risk between low- and intermediate- or high-risk groups for all types of mortality (all P values for aHR < 0.001). The low cutoff value of the SAFE score discriminated not only liver-related mortality but also identified the cardiovascular high-risk group in the community cohort.
Antimicrobial resistance burden pre and post-COVID-19 pandemic with mapping the multidrug resistance in Egypt: a comparative cross-sectional study
Authors: Abdelaziz Abdelmoneim Shaimaa , Mohamed Ghazy Ramy , Anwar Sultan Eman , Hassaan Mahmoud A. , Anwar Mahgoub Mohamed 
Published: March 2024

AbstractOveruse of antibiotics during coronavirus disease 2019 (COVID-19) in an attempt to reduce COVID-19 mortality in the short term may have contributed to long-term mortality from antimicrobial resistance (AMR). The aim of this study was to evaluate the impact of the COVID-19 pandemic on AMR in Egypt and map the distribution of multidrug-resistant (MDR) and extensive drug-resistant (XDR) across Egypt. Through a multicenter cross-sectional study 2430 culture results were collected in 2019 and 2022 pre and post-COVID-19 pandemic in Egypt, including 400 Klebsiella pneumoniae, 760 Escherichia coli, 650 Acinetobacter baumannii, and 620 Methicillin-resistantstaphylococcus aureus (MRSA) culture results. MDR and XDR culture results distribution across Egypt was highlighted through the geographic information system. Mixed effect logistic regression models and sub-group analysis were performed according to the type of specimens to test the impact of COVID-19 on resistance. Adjusted analysis demonstrated K. pneumoniae resistance has increased against quinolones and carbapenems (P < 0.001). Resistance of E. coli has increased significantly against imipenem and meropenem. While E.coli susceptibility has increased to cefoxitin, levofloxacin, and ciprofloxacin. A. baumannii resistance has increased more than double against ceftazidime, cefepime, and piperacillin-tazobactam (P < 0.001). MRSA reserved its susceptibility to vancomycin and linezolid. MDR K. pneumoniae and A. baumannii have increased post-COVID-19 from 67% to 94% and from 79% to 98%, respectively (P < 0.001). XDR K. pneumoniae and A. baumannii have increased from 6% to 46%, and from 47% to 69%, respectively (P < 0.001). COVID-19 has changed the profile of AMR in Egypt so that urgent action is required to mitigate this threat and preserve our capacity to face infections in future decades.
Cancer incidence trends in New York State and associations with common population-level exposures 2010–2018: an ecological study
Authors: Yuan Haokun , Kehm Rebecca D. , Daaboul Josephine M. , Lloyd Susan E. , McDonald Jasmine A. , Mu Lina , Tehranifar Parisa , Zhang Kai , Terry Mary Beth , Yang Wan 
Published: March 2024

AbstractThe impact of common environmental exposures in combinations with socioeconomic and lifestyle factors on cancer development, particularly for young adults, remains understudied. Here, we leveraged environmental and cancer incidence data collected in New York State at the county level to examine the association between 31 exposures and 10 common cancers (i.e., lung and bronchus, thyroid, colorectal, kidney and renal pelvis, melanoma, non-Hodgkin lymphoma, and leukemia for both sexes; corpus uteri and female breast cancer; prostate cancer), for three age groups (25–49, 50–69, and 70–84 year-olds). For each cancer, we stratified by age group and sex, and applied regression models to examine the associations with multiple exposures simultaneously. The models included 642,013 incident cancer cases during 2010–2018 and found risk factors consistent with previous reports (e.g., smoking and physical inactivity). Models also found positive associations between ambient air pollutants (ozone and PM2.5) and prostate cancer, female breast cancer, and melanoma of the skin across multiple population strata. Additionally, the models were able to better explain the variation in cancer incidence data among 25–49 year-olds than the two older age groups. These findings support the impact of common environmental exposures on cancer development, particularly for younger age groups.
Timing and impact of percutaneous endoscopic gastrostomy insertion in patients with amyotrophic lateral sclerosis: a comprehensive analysis
Authors: Son Bugyeong , Lee Jisu , Ryu Soorack , Park Yongsoon , Kim Seung Hyun 
Published: March 2024

AbstractDysphagia is common in amyotrophic lateral sclerosis (ALS) patients, often requiring percutaneous endoscopic gastrostomy (PEG) for enteral nutrition. We retrospectively analyzed data from 188 Korean patients with ALS who underwent PEG tube insertion at five-time points: symptom onset (t1), diagnosis (t2), recommended time for gastrostomy (t3), PEG insertion (t4), and one-year post-insertion (t5). The recommended time point for gastrostomy (T-rec for gastrostomy) was defined as the earlier time point between a weight loss of more than 10% and advanced dysphagia indicated by the ALSFRS-R swallowing subscore of 2 or less. The T-rec for gastrostomy was reached at 22 months after symptom onset, followed by PEG insertion at 30 months, resulting in an 8-month delay. During the delay, the ALSFRS-R declined most rapidly at 1.7 points/month, compared to 0.8 points/month from symptom onset to diagnosis, 0.7 points/month from diagnosis to T-rec for gastrostomy, and 0.6 points/month after the PEG insertion. It is crucial to discuss PEG insertion before significant weight loss or severe dysphagia occurs and minimize the delay between the recommended time for gastrostomy and the actual PEG insertion. A stratified and individualized multidisciplinary team approach with careful symptom monitoring and proactive management plans, including early PEG insertion, should be prioritized to improve patient outcomes.
GeneAI 3.0: powerful, novel, generalized hybrid and ensemble deep learning frameworks for miRNA species classification of stationary patterns from nucleotides
Authors: Singh Jaskaran , Khanna Narendra N. , Rout Ranjeet K. , Singh Narpinder , Laird John R. , Singh Inder M. , Kalra Mannudeep K. , Mantella Laura E. , Johri Amer M. , Isenovic Esma R. , Fouda Mostafa M. , Saba Luca , Fatemi Mostafa , Suri Jasjit S. 
Published: March 2024

AbstractDue to the intricate relationship between the small non-coding ribonucleic acid (miRNA) sequences, the classification of miRNA species, namely Human, Gorilla, Rat, and Mouse is challenging. Previous methods are not robust and accurate. In this study, we present AtheroPoint’s GeneAI 3.0, a powerful, novel, and generalized method for extracting features from the fixed patterns of purines and pyrimidines in each miRNA sequence in ensemble paradigms in machine learning (EML) and convolutional neural network (CNN)-based deep learning (EDL) frameworks. GeneAI 3.0 utilized fiveconventional(Entropy, Dissimilarity, Energy, Homogeneity, and Contrast), and threecontemporary(Shannon entropy, Hurst exponent, Fractal dimension) features, to generate acompositefeature set from given miRNA sequences which were then passed into our ML and DL classification framework. A set of 11 new classifiers was designed consisting of 5 EML and 6 EDL for binary/multiclass classification. It was benchmarked against 9 solo ML (SML), 6 solo DL (SDL), 12 hybrid DL (HDL) models, resulting in a total of 11 + 27 = 38 models were designed. Four hypotheses were formulated and validated using explainable AI (XAI) as well as reliability/statistical tests. The order of the mean performance using accuracy (ACC)/area-under-the-curve (AUC) of the 24 DL classifiers was: EDL > HDL > SDL. The mean performance of EDL models with CNN layers was superior to that without CNN layers by 0.73%/0.92%. Mean performance of EML models was superior to SML models with improvements of ACC/AUC by 6.24%/6.46%. EDL models performed significantly better than EML models, with a mean increase in ACC/AUC of 7.09%/6.96%. The GeneAI 3.0 tool produced expected XAI feature plots, and the statistical tests showed significantp-values. Ensemble models with composite features are highly effective and generalized models for effectively classifying miRNA sequences.
Impacts of cobalt and zinc on improving peanuts nutrient uptake, yield and irrigation water use efficiency under different irrigation levels
Authors: Elshamly Ayman M. S. , Nassar Saad M. A. 
Published: March 2024

AbstractThe knowledge of proper fertigation across various irrigation levels is necessary for maximizing peanut yield and irrigation use efficiency in arid areas, and it also can effectively alleviate the risk of nutrient deficiency induced by water stress. This study evaluated the effectiveness of cobalt combined with two zinc application methods on peanut nutrient uptake, yield, and irrigation water use efficiency across varying irrigation levels. A split-split plot experiment was carried out in 2021 and 2022. Three peanut gross water requirement (GWR) levels (100%, 80%, and 60%) were designated for main plots. Subplots featured plants treated with either 0 or 7.5 mg L−1 of cobalt. The sub-sub plots assessed chelated zinc effects at rates of 0 and 2 g L−1 via foliar and soil applications. In comparison to the control (100% GWR), nutrient uptake decreased, with sodium being the exception, and there was an increase in soil pH at 60% GWR. The results showed also significant reductions in yield and water use by approximately 60.3% and 38.1%, respectively. At this irrigation level, applying zinc via soil, either alone or combined with cobalt, led to significant yield increases of 89.7% and 191.3% relative to the control. Also, it’s crucial to note that cobalt application negatively affected iron and copper at 60% GWR, but this impact was lessened with soil-applied zinc. Hence, under a similar circumstance, treating stressed peanut plants with additional foliar applications of iron + copper and applying zinc via soil, could enhance nutrient uptake and improve yield. On the other hand, at 80% GWR, a combination of foliar-applied zinc and cobalt, had a tremendous impact on the absorption of (nitrogen, phosphorus, magnesium, and zinc), resulting in enhanced agronomic traits and decreased water losses. Additionally, at this irrigation level, foliar zinc application alone yielded a 32.4% increase compared to the 80% GWR control. When combined with cobalt, there was a 70.0% surge in water use. Based on this knowledge, the study suggests using 80% GWR and treating peanut plants with a combination of foliar-applied zinc and cobalt. This strategy aids plants in countering the adverse effects of water stress, ultimately leading to enhanced yield and irrigation water use efficiency.
Synthesis of castor oil/PEG as textile softener
Authors: Fahmy H. M. , Amr A. 
Published: March 2024

AbstractNew castor oil/polyethylene glycol (CAO/PEG) hybrids were synthesized by reacting of CAO with PEG 300, 600, 1000, 2000 or 4000, in presence of ammonium per sulfate (APS) as an initiator. The optimum conditions to synthesis such hybrids are: PEG/CAO weight ratio, 35%; APS/PEG weight ratio, 15%; reaction temperature, 80 °C; and reaction time, 60 min. Only the hybrids based on PEG 1000 and 2000 formed oil in water stable emulsions. Treating cotton fabric samples with easy care finishing formulation containing 40 g/L of the synthesized hybrids emulsions results in an enhancement in softness, tensile strength, whiteness index, and stiffness along with a reduction in nitrogen content, wrinkle recovery angle, and wettability properties of treated fabric, compared to that sample finished in absence of that emulsions. The chemical structure of the synthesized CAO/PEG1000 hybrid was confirmed via the FTIR and 1HNMRanalysis whereas the TEM analysis showed that the particles size of that hybrid emulsion is in the range of 27–105 nm. Moreover, such hybrid emulsion treated fabric surface was characterized via SEM and EDX analysis. Furthermore, treating dyed samples with the nominated hybrid emulsion improves the color strength of that samples but keeps the washing fastness, wet rubbing fastness as well as alkaline perspiration fastness of the dyed/finished samples unchanged. The wet rubbing fastness and alkaline perspiration fastness of all the dyed/finished samples were enhanced while the light fastness of such samples decreased.
Dimensionality reduction for images of IoT using machine learning
Authors: Ali Ibrahim , Wassif Khaled , Bayomi Hanaa 
Published: March 2024

AbstractSensors, wearables, mobile devices, and other Internet of Things (IoT) devices are becoming increasingly integrated into all aspects of our lives. They are capable of gathering enormous amounts of data, such as image data, which can then be sent to the cloud for processing. However, this results in an increase in network traffic and latency. To overcome these difficulties, edge computing has been proposed as a paradigm for computing that brings processing closer to the location where data is produced. This paper explores the merging of cloud and edge computing for IoT and investigates approaches using machine learning for dimensionality reduction of images on the edge, employing the autoencoder deep learning-based approach and principal component analysis (PCA). The encoded data is then sent to the cloud server, where it is used directly for any machine learning task without significantly impacting the accuracy of the data processed in the cloud. The proposed approach has been evaluated on an object detection task using a set of 4000 images randomly chosen from three datasets: COCO, human detection, and HDA datasets. Results show that a 77% reduction in data did not have a significant impact on the object detection task’s accuracy.
Present-day thermal and water activity environment of the Mars Sample Return collection
Authors: Zorzano Maria-Paz , Martínez Germán , Polkko Jouni , Tamppari Leslie K. , Newman Claire , Savijärvi Hannu , Goreva Yulia , Viúdez-Moreiras Daniel , Bertrand Tanguy , Smith Michael , Hausrath Elisabeth M. , Siljeström Sandra , Benison Kathleen , Bosak Tanja , Czaja Andrew D. , Debaille Vinciane , Herd Christopher D. K. , Mayhew Lisa , Sephton Mark A. , Shuster David , Simon Justin I. , Weiss Benjamin , Randazzo Nicolas , Mandon Lucia , Brown Adrian , Hecht Michael H. , Martínez-Frías Jesús 
Published: March 2024

AbstractThe Mars Sample Return mission intends to retrieve a sealed collection of rocks, regolith, and atmosphere sampled from Jezero Crater, Mars, by the NASA Perseverance rover mission. For all life-related research, it is necessary to evaluate water availability in the samples and on Mars. Within the first Martian year, Perseverance has acquired an estimated total mass of 355 g of rocks and regolith, and 38 μmoles of Martian atmospheric gas. Using in-situ observations acquired by the Perseverance rover, we show that the present-day environmental conditions at Jezero allow for the hydration of sulfates, chlorides, and perchlorates and the occasional formation of frost as well as a diurnal atmospheric-surface water exchange of 0.5–10 g water per m2 (assuming a well-mixed atmosphere). At night, when the temperature drops below 190 K, the surface water activity can exceed 0.5, the lowest limit for cell reproduction. During the day, when the temperature is above the cell replication limit of 245 K, water activity is less than 0.02. The environmental conditions at the surface of Jezero Crater, where these samples were acquired, are incompatible with the cell replication limits currently known on Earth.
Prismatic adaptation coupled with cognitive training as novel treatment for developmental dyslexia: a randomized controlled trial
Authors: Conte Giulia , Quadrana Lauro , Zotti Lilian , Di Garbo Agnese , Oliveri Massimiliano 
Published: March 2024

AbstractDespite intense and costly treatments, developmental dyslexia (DD) often persists into adulthood. Several brain skills unrelated to speech sound processing (i.e., phonology), including the spatial distribution of visual attention, are abnormal in DD and may represent possible treatment targets. This study explores the efficacy in DD of rightward prismatic adaptation (rPA), a visuomotor adaptation technique that enables visuo-attentive recalibration through shifts in the visual field induced by prismatic goggles. A digital intervention of rPA plus cognitive training was delivered weekly over 10 weeks to adolescents with DD (aged 13–17) assigned either to treatment (N = 35) or waitlist (N = 35) group. Efficacy was evaluated by repeated measures MANOVA assessing changes in working memory index (WMI), processing speed index (PSI), text reading speed, and words/pseudowords reading accuracy. rPA treatment was significantly more effective than waitlist (p ≤ 0.001; ηp2 = 0.815). WMI, PSI, and reading speed increased in the intervention group only (p ≤ 0.001, ηp2 = 0.67; p ≤ 0.001, ηp2 = 0.58; p ≤ 0.001, ηp2 = 0.29, respectively). Although modest change was detected for words and pseudowords accuracy in the waitlist group only (words: p ≤ 0.001, d = 0.17, pseudowords: p = 0.028; d = 0.27), between-group differences were non-significant. rPA-coupled cognitive training enhances cognitive and reading abilities in adolescents with DD. This innovative approach could have implications for early remedial treatment.