bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications
Authors: Levey Daniel F. , Galimberti Marco , Deak Joseph D. , Wendt Frank R. , Bhattacharya Arjun , Koller Dora , Harrington Kelly M. , Quaden Rachel , Johnson Emma C. , Gupta Priya , Biradar Mahantesh , Lam Max , Cooke Megan , Rajagopal Veera M. , Empke Stefany L. L. , Zhou Hang , Nunez Yaira Z. , Kranzler Henry R. , Edenberg Howard J. , Agrawal Arpana , Smoller Jordan W. , Lencz Todd , Hougaard David M. , Børglum Anders D. , Demontis Ditte ,   Veterans Affairs Million Veteran Program, Gaziano J. Michael , Gandal Michael J. , Polimanti Renato , Stein Murray B. , Gelernter Joel 
Published: November 2023

AbstractAs recreational use of cannabis is being decriminalized in many places and medical use widely sanctioned, there are growing concerns about increases in cannabis use disorder (CanUD), which is associated with numerous medical comorbidities. Here we performed a genome-wide association study of CanUD in the Million Veteran Program (MVP), followed by meta-analysis in 1,054,365 individuals (ncases = 64,314) from four broad ancestries designated by the reference panel used for assignment (European n = 886,025, African n = 123,208, admixed American n = 38,289 and East Asian n = 6,843). Population-specific methods were applied to calculate single nucleotide polymorphism-based heritability within each ancestry. Statistically significant single nucleotide polymorphism-based heritability for CanUD was observed in all but the smallest population (East Asian). We discovered genome-wide significant loci unique to each ancestry: 22 in European, 2 each in African and East Asian, and 1 in admixed American ancestries. A genetically informed causal relationship analysis indicated a possible effect of genetic liability for CanUD on lung cancer risk, suggesting potential unanticipated future medical and psychiatric public health consequences that require further study to disentangle from other known risk factors such as cigarette smoking.
Comparison of percutaneous vertebroplasty and conservative treatment for one level thoracolumbar osteoporotic compression fracture in a 3-year study
Authors: Xie Yanchun , Gu Hongwen , Wei Yongcun , Xuan Anwu , Yu Hailong 
Published: November 2023

AbstractThe efficacy of Mesh optimized versus standard percutaneous vertebroplasty (PVP) for osteoporotic vertebral compression fractures. Grid optimization (102 cases; 38 men, 64 women aged 67.3 ± 8.5) and traditional PVP groups (94 cases) were identified from 196 PVP patients treated from May 2016 to 2019. The optimal puncture site and angle forced bone cement into both groups before surgery. The main indexes were operation time, X-ray fluoroscopy times, bone cement injection volume, leakage, VAS, and injured vertebrae height. Preoperative general data were equivalent between groups (P > 0.05). All patients survived surgery without spinal cord injury, incision infection, pulmonary embolism, or death. The mesh optimization group had improved operation time (34.8 ± 6.5 min), fluoroscopy times (29.5 ± 5.5), bone cement injection volume (5.3 ± 2.1 ml), and bone cement permeability greater (3.9 percent; 4/98) than the standard PVP group (P < 0.05). Similarly, the grid optimization group had superior VAS scores (1.1 ± 0.6; 1.0 ± 0.3; and 0.9 ± 0.2) than the standard PVP group at 3 days, 3 months, and the last follow-up visit (P < 0.05). On day three after surgery, both had similar heights of injured vertebra's anterior and middle edges (P > 0.05). However, in the mesh optimization group, measurements improved to 1.8 ± 0.4 mm and (1.8 ± 0.3) mm by month three and to 1.7 ± 0.3 mm at last follow-up (P < 0.05). Mesh-optimized PVP with a mesh locator treats osteoporotic vertebral compression fractures more safely and effectively than regular PVP.
Phonon-mediated superconductivity in $${\text{Mg}}_{{1 - x}} {\text{Mo}}_{x} {\text{B}}_{2}$$ compounds: a crystal prediction via cluster expansion and particle-swarm optimization
Authors: Tsuppayakorn-aek Prutthipong , Luo Wei , Ahuja Rajeev , Bovornratanaraks Thiti 
Published: November 2023

AbstractInvestigating superconductivity represents one of the most significant phenomena in the field of condensed matter physics. Our simulations aim to elucidate the structures in the metallic state of Mg1−xMoxB2, which is essential for predicting their superconducting properties. By employing a first-principle cluster expansion and particle-swarm optimization, we have predicted the structures of Mg1−xMoxB2 ternary alloys, including Mg0.667Mo0.333B2, Mg0.5Mo0.5B2, and Mg0.333Mo0.667B2, and have determined their thermodynamically stable configurations under both atmospheric and high-pressure conditions. To investigate the potential for superconductivity in these structures, we have conducted a detailed examination of electronic properties that are pertinent to determining the superconducting state. Regarding superconducting properties, Mg0.333Mo0.667B2 exhibits superconductivity with a critical temperature (Tc) of 7.4 K at ambient pressure. These findings suggest that the theoretically predicted structures in Mg/Mo-substituted metal borides could play a significant role in synthesis and offer valuable insights into superconducting materials.
Complete mitochondrial genome analyses confirm that bat Polychromophilus and ungulate Plasmodium constitute a distinct clade independent of other Plasmodium species
Authors: Poofery Juthathip , Ngamprasertwong Thongchai , Narapakdeesakul Duriyang , Arnuphapprasert Apinya , Nugraheni Yudhi Ratna , Thanee Suchansa , Asada Masahito , Kaneko Osamu , Kaewthamasorn Morakot 
Published: November 2023

AbstractIn recent phylogenetic studies, bat Polychromophilus and ungulate Plasmodium, two relatively understudied haemosporidian parasites within the Apicomplexa phylum, have often been overlooked. Instead, the focus has been primarily on haemosporidian parasites in primates, rodents, and birds. Several phylogenetic analyses of bat Polychromophilus have relied on limited datasets and short informative DNA sequences. As a result of these inherent limitations, the substantiation of their evolutionary stance has encountered a diminished degree of robust validation. This study successfully obtained complete mitochondrial genome sequences from 11 Polychromophilus parasites originating from Hipposideros gentilis and Myotis siligoensis bats for the first time. Additionally, the authors have sequenced the apicoplast caseinolytic protease C genes from Polychromophilus murinus and a potentially new Polychromophilus species. These mitochondrial genomes range in length from 5994 to 6001 bp and consist of three protein-coding genes (PCGs), seven small subunit ribosomal RNA genes (SSU rRNA), 12 large subunit ribosomal RNA genes (LSU rRNA), and seven miscellaneous RNA genes. Phylogenetic analyses using Bayesian Inference and Maximum Likelihood methods indicated robust support for the grouping of ungulate Plasmodium and bat Polychromophilus in a single clade separate from other Plasmodium spp., confirming previous reports, albeit with stronger evidence in this study. The divergence between Polychromophilus in bats and Plasmodium in ungulates occurred approximately 29.61 to 55.77 million years ago (Mya), with a node age estimated at 40.63 Mya. These findings highlight that the genus Plasmodium, which includes species found in ungulates, birds, reptiles, and other mammals, does not form a monophyletic group. By incorporating Polychromophilus in bats and Plasmodium in ungulates, this study contributes significantly to understanding the phylogenetic relationships within the Haemosporida order. It provides valuable insights into the evolutionary history and interconnections among these diverse parasites, thereby expanding knowledge in this field.
Numerical analysis of 40 MW HTS motor electromagnetic characteristics for ship electric propulsion
Authors: Bo Kai , Chen Junquan , Jiang Yapeng , Wang Dong 
Published: November 2023

AbstractIn recent years, with the development of ship electric propulsion system, High Temperature Superconducting (HTS) motors have gained attention as a promising potential resolution due to their high-power density and the progression of cryogenic refrigeration technology. We present an electromagnetic characteristics numerical analysis of 40 MW, 120 rpm, HTS synchronous motor which is a semi-superconducting motor: in fact, it has a superconducting rotor composed of YBCO material and a conventional stator. Combining electric resistivity variation of rotor copper shielding sleeve in low temperature environment and YBCO coil critical current, the electromagnetic behavior of the 40 MW HTS synchronous motor is analyzed with non-ferromagnetic stator support structure. To assess the effects of varying stator winding currents and thickness on eddy current losses of the copper shielding sleeve, calculations were done, and a preliminary discussion was initiated. This study has certain reference significance for electromagnetic design and optimization of multi-ten MW HTS motors, especially used in ship electric propulsion system.
Development of a proteomic signature associated with severe disease for patients with COVID-19 using data from 5 multicenter, randomized, controlled, and prospective studies
Authors: Castro-Pearson Sandra , Samorodnitsky Sarah , Yang Kaifeng , Lotfi-Emran Sahar , Ingraham Nicholas E. , Bramante Carolyn , Jones Emma K. , Greising Sarah , Yu Meng , Steffen Brian T. , Svensson Julia , Åhlberg Eric , Österberg Björn , Wacker David , Guan Weihua , Puskarich Michael , Smed-Sörensen Anna , Lusczek Elizabeth , Safo Sandra E. , Tignanelli Christopher J. 
Published: November 2023

AbstractSignificant progress has been made in preventing severe COVID-19 disease through the development of vaccines. However, we still lack a validated baseline predictive biologic signature for the development of more severe disease in both outpatients and inpatients infected with SARS-CoV-2. The objective of this study was to develop and externally validate, via 5 international outpatient and inpatient trials and/or prospective cohort studies, a novel baseline proteomic signature, which predicts the development of moderate or severe (vs mild) disease in patients with COVID-19 from a proteomic analysis of 7000 + proteins. The secondary objective was exploratory, to identify (1) individual baseline protein levels and/or (2) protein level changes within the first 2 weeks of acute infection that are associated with the development of moderate/severe (vs mild) disease. For model development, samples collected from 2 randomized controlled trials were used. Plasma was isolated and the SomaLogic SomaScan platform was used to characterize protein levels for 7301 proteins of interest for all studies. We dichotomized 113 patients as having mild or moderate/severe COVID-19 disease. An elastic net approach was used to develop a predictive proteomic signature. For validation, we applied our signature to data from three independent prospective biomarker studies. We found 4110 proteins measured at baseline that significantly differed between patients with mild COVID-19 and those with moderate/severe COVID-19 after adjusting for multiple hypothesis testing. Baseline protein expression was associated with predicted disease severity with an error rate of 4.7% (AUC = 0.964). We also found that five proteins (Afamin, I-309, NKG2A, PRS57, LIPK) and patient age serve as a signature that separates patients with mild COVID-19 and patients with moderate/severe COVID-19 with an error rate of 1.77% (AUC = 0.9804). This panel was validated using data from 3 external studies with AUCs of 0.764 (Harvard University), 0.696 (University of Colorado), and 0.893 (Karolinska Institutet). In this study we developed and externally validated a baseline COVID-19 proteomic signature associated with disease severity for potential use in both outpatients and inpatients with COVID-19.
Leveraging diverse cell-death patterns to predict the prognosis, immunotherapy and drug sensitivity of clear cell renal cell carcinoma
Authors: Zhang Xi , Zhang Mingcong , Song Lebin , Wang Shuai , Wei Xiyi , Shao Wenchuan , Song Ninghong 
Published: November 2023

AbstractClear cell renal cell carcinoma (ccRCC) poses clinical challenges due to its varied prognosis, tumor microenvironment attributes, and responses to immunotherapy. We established a novel Programmed Cell Death-related Signature (PRS) for ccRCC assessment, derived through the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. We validated PRS using the E-MTAB-1980 dataset and created PCD-related clusters via non-negative matrix factorization (NMF). Our investigation included an in-depth analysis of immune infiltration scores using various algorithms. Additionally, we integrated data from the Cancer Immunome Atlas (TCIA) for ccRCC immunotherapy insights and leveraged the Genomics of Drug Sensitivity in Cancer (GDSC) database to assess drug sensitivity models. We complemented our findings with single-cell sequencing data and employed the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and qRT-PCR to compare gene expression profiles between cancerous and paracancerous tissues. PRS serves as a valuable tool for prognostication, immune characterization, tumor mutation burden estimation, immunotherapy response prediction, and drug sensitivity assessment in ccRCC. We identify five genes with significant roles in cancer promotion and three genes with cancer-suppressive properties, further validated by qRT-PCR and CPTAC analyses, showcasing gene expression differences in ccRCC tissues. Our study introduces an innovative PCD model that amalgamates diverse cell death patterns to provide accurate predictions for clinical outcomes, mutational profiles, and immune characteristics in ccRCC. Our findings hold promise for advancing personalized treatment strategies in ccRCC patients.
Optimal wave reflection as a mechanism for seagrass self-organization
Authors: van de Vijsel Roeland C. , Hernández-García Emilio , Orfila Alejandro , Gomila Damià 
Published: November 2023

AbstractEcosystems threatened by climate change can boost their resilience by developing spatial patterns. Spatially regular patterns in wave-exposed seagrass meadows are attributed to self-organization, yet underlying mechanisms are not well understood. Here, we show that these patterns could emerge from feedbacks between wave reflection and seagrass-induced bedform growth. We derive a theoretical model for surface waves propagating over a growing seagrass bed. Wave-induced bed shear stress shapes bedforms which, in turn, trigger wave reflection. Numerical simulations show seagrass pattern development once wave forcing exceeds a critical amplitude. In line with Mediterranean Sea field observations, these patterns have half the wavelength of the forcing waves. Our results raise the hypothesis that pattern formation optimizes the potential of seagrass meadows to reflect wave energy, and a clear direction for future field campaigns. If wave-reflecting pattern formation increases ecosystem resilience under globally intensifying wave climates, these ecosystems may inspire nature-based coastal protection measures.
Unlearned adaptive responses to heterospecific referential alarm calls in two bird species from separate evolutionary lineages
Authors: Ha Jungmoon , Lee Keesan , Yang Eunjeong , Kim Woojoo , Song Hokyung , Hwang Injae , Lee-Cruz Larisa , Park Jinseok , Song Jihyeon , Park Chan-ryul , Lee Wooshin , Jablonski Piotr , Lee Sang-im 
Published: November 2023

AbstractThe interspecific responses to alarm signals may be based on unlearned mechanisms but research is often constrained by the difficulties in differentiating between unlearned and learned responses in natural situations. In a field study of two Paridae species, Parus minor and Sittiparus varius, who originated from a common ancestor 8 million years ago, we found a considerable degree of between-species overlap in acoustic properties of referential snake-alarm calls. Playback of these calls triggered unlearned adaptive fledging behavior in conspecific and heterospecific naive nestlings, suggesting a between-species overlap in the hypothetical unlearned neural templates involved in nestlings’ reactions to alarm calls in both species. This suggests that similar calls and similar unlearned sensitivity might have been present in the common ancestor of the two species, and possibly in the ancestor of the whole family Paridae that originated 10–15 million years ago in Asian regions rich in snakes.
Viral load of SARS-CoV-2 in surgical smoke in minimally invasive and open surgery: a single-center prospective clinical trial
Authors: Cizmic Amila , Eichel Vanessa M. , Weidner Niklas M. , Wise Philipp A. , Müller Felix , Rompen Ingmar F. , Bartenschlager Ralf , Schnitzler Paul , Nickel Felix , Müller-Stich Beat P. 
Published: November 2023

AbstractAt the beginning of the COVID-19 pandemic, it was assumed that SARS-CoV-2 could be transmitted through surgical smoke generated by electrocauterization. Minimally invasive surgery (MIS) was targeted due to potentially higher concentrations of the SARS-CoV-2 particles in the pneumoperitoneum. Some surgical societies even recommended open surgery instead of MIS to prevent the potential spread of SARS-CoV-2 from the pneumoperitoneum. This study aimed to detect SARS-CoV-2 in surgical smoke during open and MIS. Patients with SARS-CoV-2 infection who underwent open surgery or MIS at Heidelberg University Hospital were included in the study. A control group of patients without SARS-CoV-2 infection undergoing MIS or open surgery was included for comparison. The trial was approved by the Ethics Committee of Heidelberg University Medical School (S-098/2021). The following samples were collected: nasopharyngeal and intraabdominal swabs, blood, urine, surgical smoke, and air samples from the operating room. An SKC BioSampler was used to sample the surgical smoke from the pneumoperitoneum during MIS and the approximate surgical field during open surgery in 15 ml of sterilized phosphate-buffered saline. An RT-PCR test was performed on all collected samples to detect SARS-CoV-2 viral particles. Twelve patients with proven SARS-CoV-2 infection underwent open abdominal surgery. Two SARS-CoV-2-positive patients underwent an MIS procedure. The control group included 24 patients: 12 underwent open surgery and 12 MIS. One intraabdominal swab in a patient with SARS-CoV-2 infection was positive for SARS-CoV-2. However, during both open surgery and MIS, none of the surgical smoke samples showed any detectable viral particles of SARS-CoV-2. The air samples collected at the end of the surgical procedure showed no viral particles of SARS-CoV-2. Major complications (CD ≥ IIIa) were more often observed in SARS-CoV-2 positive patients (10 vs. 4, p = 0.001). This study showed no detectable viral particles of SARS-CoV-2 in surgical smoke sampled during MIS and open surgery. Thus, the discussed risk of transmission of SARS-CoV-2 via surgical smoke could not be confirmed in the present study.
BrachySound: machine learning based assessment of respiratory sounds in dogs
Authors: Oren Ariel , Türkcü Jana D. , Meller Sebastian , Lazebnik Teddy , Wiegel Pia , Mach Rebekka , Volk Holger A. , Zamansky Anna 
Published: November 2023

AbstractThe early and accurate diagnosis of brachycephalic obstructive airway syndrome (BOAS) in dogs is pivotal for effective treatment and enhanced canine well-being. Owners often do underestimate the severity of BOAS in their dogs. In addition, traditional diagnostic methods, which include pharyngolaryngeal auscultation, are often compromised by subjectivity, are time-intensive and depend on the veterinary surgeon’s experience. Hence, new fast, reliable assessment methods for BOAS are required. The aim of the current study was to use machine learning techniques to bridge this scientific gap. In this study, machine learning models were employed to objectively analyze 366 audio samples from 69 Pugs and 79 other brachycephalic breeds, recorded with an electronic stethoscope during a 15-min standardized exercise test. In classifying the BOAS test results as to whether the dog is affected or not, our models achieved a peak accuracy of 0.85, using subsets from the Pugs dataset. For predictions of the BOAS results from recordings at rest in Pugs and various brachycephalic breeds, accuracies of 0.68 and 0.65 were observed, respectively. Notably, the detection of laryngeal sounds achieved an F1 score of 0.80. These results highlight the potential of machine learning models to significantly streamline the examination process, offering a more objective assessment than traditional methods. This research indicates a turning point towards a data-driven, objective, and efficient approach in canine health assessment, fostering standardized and objective BOAS diagnostics.
The effect of model complexity on the human center of mass estimation using the statically equivalent serial chain technique
Authors: Chebel Elie , Tunc Burcu 
Published: November 2023

AbstractEstimating the human center of mass (CoM) has long been recognized as a highly complex process. A relatively recent and noteworthy technique for CoM estimation that has gained popularity is the statically equivalent serial chain (SESC). This technique employs a remodeling of the human skeleton as a serial chain where the end effector represents the CoM location. In this study, we aimed to evaluate the impact of model complexity on the estimation capability of the SESC technique. To achieve this, we designed and rigorously assessed four distinct models with varying complexities against the static center of pressure (CoP) as reference, by quantifying both the root-mean-square (RMS) and correlation metrics. In addition, the Bland–Altman analysis was utilized to quantify the agreement between the estimations and reference values. The findings revealed that increasing the model complexity significantly improved CoM estimation quality up to a specific threshold. The maximum observed RMS difference among the models reached 9.85 mm. However, the application and task context should be considered, as less complex models still provided satisfactory estimation performance. In conclusion, the evaluation of model complexity demonstrated its impact on CoM estimation using the SESC technique, providing insights into the trade-off between accuracy and complexity in practical applications.