bluuebunny/crossref_metadata_2025_split huggingface dataset:
Declining hip fracture burden in Sweden 1998–2019 and consequences for projections through 2050
Authors: Michaëlsson Karl , Baron John A. , Byberg Liisa , Larsson Susanna C. , Melhus Håkan , Gedeborg Rolf 
Published: January 2024

AbstractWe aimed to estimate the absolute and age-standardized number of hip fractures in Sweden during the past two decades to produce time trends and future projections. We used nationwide register data from 1998 to 2019 and a validated algorithm to calculate the annual absolute and age-standardized number of incident hip fractures over time. The total hip fracture burden was 335,399 incident events over the 22 years, with a change from 16,180 in 1998 to 13,929 in 2019, a 14% decrease. One decade after the index hip fracture event, 80% of the patients had died, and 11% had a new hip fracture. After considering the steady growth of the older population, the decline in the age-standardized number of hip fractures from 1998 through 2019 was 29.2% (95% CI 28.1–30.2%) in women and 29.3% (95% CI 27.5–30.7%) in men. With a continued similar reduction in hip fracture incidence, we can predict that 14,800 hip fractures will occur in 2034 and 12,000 in 2050 despite doubling the oldest old (≥ 80 years). Without an algorithm, a naïve estimate of the total number of hip fractures over the study period was 539,947, with a second 10-year hip fracture risk of 35%. We note an ongoing decline in the absolute and age-standardized actual number of hip fractures in Sweden, with consequences for future projections.
Apalutamide versus bicalutamide in combination with androgen deprivation therapy for metastatic hormone sensitive prostate cancer
Authors: Ueda Takashi , Shiraishi Takumi , Miyashita Masatsugu , Kayukawa Naruhiro , Gabata Yusuke , Sako Satoshi , Ogura Ryota , Fujihara Atsuko , Okihara Koji , Ukimura Osamu 
Published: January 2024

AbstractThe objective of this study is to compare the efficacy of apalutamide and bicalutamide in combination with androgen deprivation therapy in patients with metastatic hormone-sensitive prostate cancer (mHSPC). We retrospectively collected the data of about 330 patients with metastatic hormone-sensitive prostate cancer at our hospital and affiliated hospitals between December 2013 and August 2023. Sixty-one patients were administered apalutamide (240 mg/day) with androgen deprivation therapy (group A), and 269 patients were administered bicalutamide (80 mg/day) with androgen deprivation therapy (group B). Propensity score matching was used to adjust for clinical background factors between the two groups. PSA progression-free survival and overall survival were significantly longer in group A than in group B among the matched patients. Apalutamide therapy was a significant independent factor for OS in matched patients. The second progression-free survival of group A was significantly longer than that of group B in matched patients. Patients treated with apalutamide achieved ≥ 90% PSA decline from baseline faster and in larger numbers than those with bicalutamide. Apalutamide combined with ADT may be superior to bicalutamide alone in terms of OS and PSA-PFS in patients with mHSPC.
The death rate of COVID-19 infection in different SARS-CoV-2 variants was related to C-reactive protein gene polymorphisms
Authors: Sadeghi Mofrad Sahar , Boozarjomehri Amnieh Shayan , Pakzad Mohammad Reza , Zardadi Mina , Ghazanfari Jajin Morteza , Anvari Enayat , Moghaddam Sina , Fateh Abolfazl 
Published: January 2024

AbstractThe serum level of C-reactive protein (CRP) is a significant independent risk factor for Coronavirus disease 2019 (COVID-19). A link was found between serum CRP and genetic diversity within the CRP gene in earlier research. This study examined whether CRP rs1205 and rs1800947 polymorphisms were associated with COVID-19 mortality among various severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) variants. We genotyped CRP rs1205 and rs1800947 polymorphisms in 2023 deceased and 2307 recovered patients using the polymerase chain reaction-restriction fragment length polymorphism method. There was a significant difference between the recovered and the deceased patients in terms of the minor allele frequency of CRP rs1205 T and rs1800947 G. In all three variants, COVID-19 mortality rates were associated with CRP rs1800947 GG genotype. Furthermore, CRP rs1205 CC and rs1800947 GG genotypes showed higher CRP levels. It was found that the G-T haplotype was prevalent in all SARS-CoV-2 variants. The C–C and C–T haplotypes were statistically significant in Delta and Omicron BA.5 variants, respectively. In conclusion, polymorphisms within the CRP gene may relate to serum CRP levels and mortality among COVID-19 patients. In order to verify the utility of CRP polymorphism correlation in predicting COVID-19 mortality, a replication of these results is needed.
Real-time fluorescence-guided adhesiolysis with indocyanine green in intra-abdominal surgery (with video)
Authors: Chen Qiangxing , Cai Yu , Cheng Ke , Chen Zixin , Li Jun , Wu Shangdi , Peng Bing 
Published: January 2024

AbstractIntra-abdominal adhesions have consistently posed a challenge for surgeons during procedures. This study aims to investigate the feasibility of utilizing indocyanine green (ICG) in conjunction with near-infrared imaging for the detection of intra-abdominal adhesions. In vitro, we analyzed factors affecting ICG fluorescence. We divided SD rats into groups to study ICG excretion in different digestive tract regions. Additionally, we reviewed surgical videos from previous cholecystectomy cases, categorizing them by ICG injection timing and assessing fluorescence imaging in various digestive tract regions. Finally, we preoperatively injected ICG into two cholecystectomized patients with abdominal adhesions, guiding intraoperative adhesiolysis with near-infrared fluorescence imaging. In vitro, we observed a significant influence of protein and ICG concentrations on ICG fluorescence intensity. Our rat experiments unveiled a strong and highly significant correlation (Kendall’s tau-b = 1, P < 0.001) between the timing of ICG injection and the farthest point of intestinal fluorescence. A retrospective case analysis further validated this finding (Kendall’s tau-b = 0.967, P < 0.001). Under the guidance of fluorescence navigation, two cholecystectomized patients with intra-abdominal adhesions successfully underwent adhesiolysis, and no postoperative complications occurred. The intraoperative combination of ICG with near-infrared fluorescence imaging effectively enhances the visibility of the liver, bile ducts, and various segments of the gastrointestinal tract while providing real-time navigation. This real-time fluorescence guidance has the potential to aid surgeons in the dissection of intra-abdominal adhesions.
An experimental and numerical study of the strength development of layered cemented tailings backfill
Authors: Chiloane Nhleko Monique , Sengani Fhatuwani , Mulenga Francois 
Published: January 2024

AbstractThe behaviour of a stratified backfilled stope in terms of strength development and stress distribution has not been well established in the field of rock engineering. Yet, the mining industries with massive ore bodies are looking into high production with a high standard of safety which is mainly governed by large excavation with backfill as a support system. It is difficult to fill these large excavations at one time. Therefore, a subsequent backfilling of the stope layer by layering is adopted, which results in a layered backfill structure. The purpose of this study was to explore the strength development, stress distribution and deformation across the stope supported by both layered and non-layered backfill. It has been observed that the backfill support system gain its strength with time, however, the layered backfill support system loses its strength when more layers are introduced, this is due to the shearing effect around the interfaces of the backfill layers. The impact of layering was validated by 3D numerical simulation. It is therefore concluded that non layered backfill support system are more suitable for stoping mining methods rather than layered support system.
Machine learning models for early prediction of potassium lowering effectiveness and adverse events in patients with hyperkalemia
Authors: Huang Wei , Zhu Jian-Yong , Song Cong-Ying , Lu Yuan-Qiang 
Published: January 2024

AbstractThe aim of this study was to develop a model for early prediction of adverse events and treatment effectiveness in patients with hyperkalemia. We collected clinical data from patients with hyperkalemia in the First Hospital of Zhejiang University School of Medicine between 2015 and 2021. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to analyze the predictors on the full dataset. We randomly divided the data into a training group and a validation group, and used LASSO to filter variables in the training set. Six machine learning methods were used to develop the models. The best model was selected based on the area under the curve (AUC). Shapley additive exPlanations (SHAP) values were used to explain the best model. A total of 1074 patients with hyperkalemia were finally enrolled. Diastolic blood pressure (DBP), breathing, oxygen saturation (SPO2), Glasgow coma score (GCS), liver disease, oliguria, blood sodium, international standardized ratio (ISR), and initial blood potassium were the predictors of the occurrence of adverse events; peripheral edema, estimated glomerular filtration rate (eGFR), blood sodium, actual base residual, and initial blood potassium were the predictors of therapeutic effect. Extreme gradient boosting (XGBoost) model achieved the best performance (adverse events: AUC = 0.87; therapeutic effect: AUC = 0.75). A model based on clinical characteristics was developed and validated with good performance.
EPYC functions as a novel prognostic biomarker for pancreatic cancer
Authors: Yang Zhen , Li Honglin , Hao Jie , Mei Hanwei , Qiu Minghan , Wang Huaqing , Gao Ming 
Published: January 2024

AbstractPancreatic cancer (PC) has become a worldwide challenge attributed to its difficult early diagnosis and rapid progression. Treatments continue to be limited besides surgical resection. Hence, we aimed to discover novel biological signatures as clinically effective therapeutic targets for PC via the mining of public tumor databases. We found that epiphycan (EPYC) could function as an independent risk factor to predict the poor prognosis in PC based on integrated bioinformatics analysis. We downloaded associated PC data profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) online websites, then applied the software Rstudio to filter out genes under the strict criteria. After the batch survival analysis using Log-rank test and univariate cox regression, we obtained 39 candidate genes. Subsequently, we narrowed the scope to 8 genes by establishing a Lasso regression model. Eventually, we focused on 2 genes (EPYC and MET) by further building a multivariate cox regression model. Given that the role of EPYC in PC remains obscure, we then performed a series of molecular functional experiments, including RT-qPCR, CCK8, EdU, colony formation, Transwell, western blot, cell live-dead staining, subcutaneous tumor formation, to enhance our insight into its underlying molecular mechanisms. The above results demonstrated that EPYC was highly expressed in PC cell lines and could promote the proliferation of PCs via PI3K-AKT signaling pathway in vivo and in vitro. We arrived at a conclusion that EPYC was expected to be a biological neo-biomarker for PC followed by being a potential therapeutic target.
Effects of AST-120 on mortality in patients with chronic kidney disease modeled by artificial intelligence or traditional statistical analysis
Authors: Lee Chia-Lin , Liu Wei‑Ju , Tsai Shang-Feng 
Published: January 2024

AbstractChronic kidney disease (CKD) imposes a substantial burden, and patient prognosis remains grim. The impact of AST-120 (AST-120) on the survival of CKD patients lacks a consensus. This study aims to investigate the effects of AST-120 usage on the survival of CKD patients and explore the utility of artificial intelligence models for decision-making. We conducted a retrospective analysis of CKD patients receiving care in the pre-end-stage renal disease (ESRD) program at Taichung Veterans General Hospital from 2000 to 2019. We employed Cox regression models to evaluate the relationship between AST-120 use and patient survival, both before and after propensity score matching. Subsequently, we employed Deep Neural Network (DNN) and Extreme Gradient Boosting (XGBoost) models to assess their performance in predicting AST-120's impact on patient survival. Among the 2584 patients in our cohort, 2199 did not use AST-120, while 385 patients received AST-120. AST-120 users exhibited significantly lower mortality rates compared to non-AST-120 users (13.51% vs. 37.88%, p < 0.0001) and a reduced prevalence of ESRD (44.16% vs. 53.17%, p = 0.0005). Propensity score matching at 1:1 and 1:2 revealed no significant differences, except for dialysis and all-cause mortality, where AST-120 users exhibited significantly lower all-cause mortality (p < 0.0001), with a hazard ratio (HR) of 0.395 (95% CI = 0.295–0.522). This difference remained statistically significant even after propensity matching. In terms of model performance, the XGBoost model demonstrated the highest accuracy (0.72), specificity (0.90), and positive predictive value (0.48), while the logistic regression model showed the highest sensitivity (0.63) and negative predictive value (0.84). The area under the curve (AUC) values for logistic regression, DNN, and XGBoost were 0.73, 0.73, and 0.69, respectively, indicating similar predictive capabilities for mortality. In this cohort of CKD patients, the use of AST-120 is significantly associated with reduced mortality. However, the performance of artificial intelligence models in predicting the impact of AST-120 is not superior to statistical analysis using the current architecture and algorithm.
Synergistic observation of FY-4A&4B to estimate CO concentration in China: combining interpretable machine learning to reveal the influencing mechanisms of CO variations
Authors: Chen Bin , Hu Jiashun , Wang Yixuan 
Published: January 2024

AbstractAccurately estimating the concentration of carbon monoxide (CO) with high spatiotemporal resolution is crucial for assessing its meteorological-environmental-health impacts. Although machine learning models have high predictive ability in environmental research, there are relatively few explanations for model outputs. Utilizing the top-of-atmosphere radiation data of China’s new generation geostationary satellites (FY-4A and FY-4B) and interpretable machine learning models, the 24-hour near-surface CO concentrations in China was conducted (resolution: 1 hour, 0.04°). The model improved by 6.6% when using the all-sky dataset (cloud-contained model, R2 = 0.759) compared to the clear-sky dataset (cloud-removed model). The interpretability analysis of the CO estimation model used two methods, namely ante-hoc (model feature importance) and post-hoc (SHapley Additive exPlanations). The importance of daytime meteorological factors increased by 51% compared to nighttime. Combining partial dependency plots, the impact of key meteorological factors on CO was elucidated to gain a deeper understanding of the spatiotemporal variations of CO.
Role of PLK1/NUMB/NOTCH in epithelial-mesenchymal transition in human melanoma
Authors: Chhabra Gagan , Singh Chandra K. , Ndiaye Mary A. , Su Shengqin , Shirley Carl A. , Ahmad Nihal 
Published: January 2024

AbstractPolo-like kinase 1 (PLK1), a serine/threonine kinase, is overexpressed in melanoma and its expression has been associated with poor disease prognosis. PLK1 has been shown to interact with NUMB, a NOTCH antagonist. However, the exact role of PLK1, NUMB, and NOTCH signaling in epithelial-mesenchymal transition (EMT) in melanoma progression is unclear. In this study, Affymetrix microarray analysis was performed to determine differentially expressed genes following shRNA-mediated knockdown of PLK1 in human melanoma cells that showed significant modulations in EMT and metastasis-related genes. Using multiple PLK1-modulated melanoma cell lines, we found that PLK1 is involved in the regulation of cell migration, invasion, and EMT via its kinase activity and NOTCH activation. In vitro kinase assay and mass spectrometry analysis demonstrated a previously unknown PLK1 phosphorylation site (Ser413) on NUMB. Overexpression of non-phosphorylatable (S413A) and phosphomimetic (S413D) mutants of NUMB in melanoma cells implicated the involvement of NUMB-S413 phosphorylation in cell migration and invasion, which was independent of NOTCH activation. To determine the clinical relevance of these findings, immunohistochemistry was performed using melanoma tissue microarray, which indicated a strong positive correlation between PLK1 and N-cadherin, a protein required for successful EMT. These findings were supported by TCGA analysis, where expression of high PLK1 with low NUMB or high NOTCH or N-cadherin showed a significant decrease in survival of melanoma patients. Overall, these results suggest a potential role of PLK1 in EMT, migration, and invasion of melanoma cells. Our findings support the therapeutic targeting of PLK1, NUMB, and NOTCH for melanoma management.
Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure
Authors: Lee Eunjung , Ito Saki , Miranda William R. , Lopez-Jimenez Francisco , Kane Garvan C. , Asirvatham Samuel J. , Noseworthy Peter A. , Friedman Paul A. , Carter Rickey E. , Borlaug Barry A. , Attia Zachi I. , Oh Jae K. 
Published: January 2024

AbstractAssessment of left ventricular diastolic function plays a major role in the diagnosis and prognosis of cardiac diseases, including heart failure with preserved ejection fraction. We aimed to develop an artificial intelligence (AI)-enabled electrocardiogram (ECG) model to identify echocardiographically determined diastolic dysfunction and increased filling pressure. We trained, validated, and tested an AI-enabled ECG in 98,736, 21,963, and 98,763 patients, respectively, who had an ECG and echocardiographic diastolic function assessment within 14 days with no exclusion criteria. It was also tested in 55,248 patients with indeterminate diastolic function by echocardiography. The model was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve, and its prognostic performance was compared to echocardiography. The AUC for detecting increased filling pressure was 0.911. The AUCs to identify diastolic dysfunction grades ≥1, ≥2, and 3 were 0.847, 0.911, and 0.943, respectively. During a median follow-up of 5.9 years, 20,223 (20.5%) died. Patients with increased filling pressure predicted by AI-ECG had higher mortality than those with normal filling pressure, after adjusting for age, sex, and comorbidities in the test group (hazard ratio (HR) 1.7, 95% CI 1.645–1.757) similar to echocardiography and in the indeterminate group (HR 1.34, 95% CI 1.298–1.383). An AI-enabled ECG identifies increased filling pressure and diastolic function grades with a good prognostic value similar to echocardiography. AI-ECG is a simple and promising tool to enhance the detection of diseases associated with diastolic dysfunction and increased diastolic filling pressure.
Genetic effects on variability in visual aesthetic evaluations are partially shared across visual domains
Authors: Bignardi Giacomo , Smit Dirk J. A. , Vessel Edward A. , Trupp MacKenzie D. , Ticini Luca F. , Fisher Simon E. , Polderman Tinca J. C. 
Published: January 2024

AbstractThe aesthetic values that individuals place on visual images are formed and shaped over a lifetime. However, whether the formation of visual aesthetic value is solely influenced by environmental exposure is still a matter of debate. Here, we considered differences in aesthetic value emerging across three visual domains: abstract images, scenes, and faces. We examined variability in two major dimensions of ordinary aesthetic experiences: taste-typicality and evaluation-bias. We build on two samples from the Australian Twin Registry where 1547 and 1231 monozygotic and dizygotic twins originally rated visual images belonging to the three domains. Genetic influences explained 26% to 41% of the variance in taste-typicality and evaluation-bias. Multivariate analyses showed that genetic effects were partially shared across visual domains. Results indicate that the heritability of major dimensions of aesthetic evaluations is comparable to that of other complex social traits, albeit lower than for other complex cognitive traits. The exception was taste-typicality for abstract images, for which we found only shared and unique environmental influences. Our study reveals that diverse sources of genetic and environmental variation influence the formation of aesthetic value across distinct visual domains and provides improved metrics to assess inter-individual differences in aesthetic value.
σE of Streptomyces coelicolor can function both as a direct activator or repressor of transcription
Authors: Pospíšil Jiří , Schwarz Marek , Ziková Alice , Vítovská Dragana , Hradilová Miluše , Kolář Michal , Křenková Alena , Hubálek Martin , Krásný Libor , Vohradský Jiří 
Published: January 2024

Abstractσ factors are considered as positive regulators of gene expression. Here we reveal the opposite, inhibitory role of these proteins. We used a combination of molecular biology methods and computational modeling to analyze the regulatory activity of the extracytoplasmic σE factor from Streptomyces coelicolor. The direct activator/repressor function of σE was then explored by experimental analysis of selected promoter regions in vivo. Additionally, the σE interactome was defined. Taken together, the results characterize σE, its regulation, regulon, and suggest its direct inhibitory function (as a repressor) in gene expression, a phenomenon that may be common also to other σ factors and organisms.
Mendelian randomization identifies circulating proteins as biomarkers for age at menarche and age at natural menopause
Authors: Yazdanpanah Nahid , Jumentier Basile , Yazdanpanah Mojgan , Ong Ken K. , Perry John R. B. , Manousaki Despoina 
Published: January 2024

AbstractAge at menarche (AAM) and age at natural menopause (ANM) are highly heritable traits and have been linked to various health outcomes. We aimed to identify circulating proteins associated with altered ANM and AAM using an unbiased two-sample Mendelian randomization (MR) and colocalization approach. By testing causal effects of 1,271 proteins on AAM, we identified 22 proteins causally associated with AAM in MR, among which 13 proteins (GCKR, FOXO3, SEMA3G, PATE4, AZGP1, NEGR1, LHB, DLK1, ANXA2, YWHAB, DNAJB12, RMDN1 and HPGDS) colocalized. Among 1,349 proteins tested for causal association with ANM using MR, we identified 19 causal proteins among which 7 proteins (CPNE1, TYMP, DNER, ADAMTS13, LCT, ARL and PLXNA1) colocalized. Follow-up pathway and gene enrichment analyses demonstrated links between AAM-related proteins and obesity and diabetes, and between AAM and ANM-related proteins and various types of cancer. In conclusion, we identified proteomic signatures of reproductive ageing in women, highlighting biological processes at both ends of the reproductive lifespan.