bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global burden of NAFLD and chronic liver disease among adolescents and young adults
Authors: Paik James M. , Kabbara Khaled , Eberly Katherine E. , Younossi Youssef , Henry Linda , Younossi Zobair M. 
Published: November 2021

Abstract

Background and Aim
The causes of chronic liver disease (CLD) among adults have changed. Data are lacking on trends among youth. We determined the trends and changes in the global burden of CLD among adolescents and young adults using Global Burden of Disease (GBD) data (2009–2019).

Approach and Results
The GBD study estimation methods were used to assess CLD prevalence, incidence, and deaths (21 GBD regions). Annual percent change (APC) calculation by joinpoint regression modeling. Age groups were 15–19, 20–24, and 25–29 years old. Globally in 2019, the 15–29 group accounted for 17.2% (0.29 billion) of CLD prevalent cases, 11.2% (n = 232,072) CLD incident cases, and 3.8% (n = 55,515) CLD deaths. Between 2009 and 2019, CLD prevalence rate increased annually among 25–29 (APC = +0.41%, p < 0.001); remained stable among 20–24 (APC = +0.02%, p = 0.582); and decreased among 15–19 (APC = −2.13%, p < 0.001). CLD prevalence increases were driven by the proportion with NAFLD (15–19: 40.8% to 52.9%, p < 0.001); 20–24: 57.6% to 62.7%, p < 0.001); and 25–29: 66.9% to 70.1%, p < 0.001); the proportion with HBV decreased across all age groups. NAFLD prevalence worsening trend (APC ≥ 0%) was global. Overall CLD death rate decreased annually in all age groups, driven by the decrease in the proportion with HBV [aged 15–19 (from 5.90% to 5.20%, p < 0.001); aged 20–24 (from 18.62% to 16.37%, p < 0.001); and aged 25–29 (from 28.69% to 25.28%, p < 0.001)]; from 2015 to 2019, CLD death rate for HCV (APC = +1.46%) and NAFLD (APC = +2.26%) increased.

Conclusions
Over the past decade, the causes of CLD among 15–29‐year‐olds have shifted: viral hepatitis remains the most common cause of CLD deaths, but the global burden of HBV incidence is decreasing, whereas NAFLD is the main driver for increased CLD incidence.
Are peatlands in different states with respect to their thermodynamic behaviour? A simple test of peatland energy and entropy budgets
Authors: Worrall Fred , Morrison Ross , Evans Chris , Kaduk Joerg , Page Susan , Cumming Alex , Rayment Mark , Kettridge Nicholas 
Published: November 2021

AbstractWhilst all ecosystems must obey the second law of thermodynamics, these physical bounds and controls on ecosystem evolution and development are largely ignored across the ecohydrological literature. To unravel the importance of these underlying restraints on ecosystem form and function, and their power to inform our scientific understanding, we have calculated the entropy budget of a range of peat ecosystems. We hypothesize that less disturbed peatlands are ‘near equilibrium’ with respect to the second law of thermodynamics and thus respond to change by minimizing entropy production. This ‘near equilibrium’ state is best achieved by limiting evaporative losses. Alternatively, peatlands ‘far‐from‐equilibrium’ respond to a change in energy inputs by maximizing entropy production which is best achieved by increasing evapotranspiration. To test these alternatives this study examined the energy balance time series from seven peatlands across a disturbance gradient. We estimate the entropy budgets for each and determine how a change in net radiation (ΔRn) was transferred to a change in latent heat flux (ΔλE). The study showed that: (i) The transfer of net radiation to latent heat differed significantly between peatlands. One group transferred up to 64% of the change in net radiation to a change in latent heat flux, while the second transferred as little as 27%. (ii) Sites that transferred the most energy to latent heat flux were those that produced the greatest entropy. The study shows that an ecosystem could be ‘near equilibrium’ rather than ‘far from equilibrium’.
Pazopanib with 5‐FU and oxaliplatin as first line therapy in advanced gastric cancer: A randomized phase‐II study—The PaFLO trial. A study of the Arbeitsgemeinschaft Internistische Onkologie AIO‐STO‐0510
Authors: Högner Anica , Al‐Batran Salah‐Eddin , Siveke Jens T. , Lorenz Mario , Bartels Prisca , Breithaupt Kirstin , Malfertheiner Peter , Homann Nils , Stein Alexander , Gläser Dietrich , Tamm Ingo , Hinke Axel , Vogel Arndt , Thuss‐Patience Peter ,   PaFLO investigators
Published: November 2021

AbstractVEGF inhibition in gastric cancer has a proven benefit in the second line setting. Pazopanib, an oral tyrosine kinase inhibitor, selectively inhibits VEGFR‐1, ‐2 and ‐3, c‐kit and PDGF‐R resulting in inhibition of angiogenesis. This open‐label randomized phase II trial (2:1) investigated the efficacy of combining pazopanib with FLO (5‐fluorouracil, oxaliplatin) vs FLO alone (internal control arm) as first‐line treatment in patients with advanced adenocarcinoma of the stomach and gastroesophageal junction (GEJ). Eighty‐seven patients were randomized and 78 patients were eligible and evaluable (PaFLO arm 51 patients, FLO arm 27 patients). The PFS rate at 6 months (primary endpoint) was 34% in the PaFLO arm vs 30% in the FLO arm. Comparing PaFLO with FLO median PFS was 4.66 months (95% confidence interval [CI] 2.87‐6.46) vs 4.47 months (95% CI 1.79‐7.14) (95% CI, hazard ratio [HR] 0.96 (0.60‐1.55), P = .882 [exploratory]); median OS was 10.19 months (95% CI 5.46‐14.92) vs 7.33 months (95% CI 4.93‐9.73), (95% CI HR 1.01 [0.62‐1.65], P = .953, exploratory), disease control rate was 72% vs 59%. PaFLO was well tolerable, toxicities were slightly higher in the PaFLO arm. Major adverse events were loss of appetite, nausea, fatigue, diarrhea, neutropenia and thrombocytopenia. Adding pazopanib to chemotherapy shows signs of efficacy but no major improvement in this randomized phase 2 trial. The PFS at 6 months in both arms was lower than expected from the literature. Biomarkers identifying subgroups who benefit and novel combinations are needed. ClinicalTrials.gov: NCT01503372.
Sialic acids in gynecological cancer development and progression: Impact on diagnosis and treatment
Authors: Berghuis Anna Y. , Pijnenborg Johan F. A. , Boltje Thomas J. , Pijnenborg Johanna M. A. 
Published: November 2021

AbstractGynecological cancers are in the top 10 of most common cancers in women. Survival and outcome are strongly related to the stage at diagnosis. Therefore, early diagnosis is essential in reducing morbidity and mortality. The high mortality rate of gynecological cancers can mainly be attributed to ovarian cancer (OC). OC is commonly diagnosed at an advanced stage due to a lack of proper screening tools allowing early detection. Endometrial cancer (EC) on the contrary, is mostly diagnosed at an early stage and has, in general, better outcomes. The incidence of nonendometrioid EC has increased in the last decade, displaying a shared tumor biology with OC and consequently significantly worse outcome. New approaches allowing detection of gynecological cancers in an early stage are therefore desired. Recent studies on cancer biology have shown the relevance of altered glycosylation in the occurrence and progression of cancer. The aberrant expression of sialic acid, a specific carbohydrate terminating glycoproteins and glycolipids on the cell‐surface, is frequently correlated with malignancy. We aimed to determine the current understanding of sialic acid function in different gynecological cancers to identify the gaps in knowledge and its potential use for new diagnostic and therapeutic avenues. Therefore we performed a review on current literature focusing on studies where sialylation was linked to gynecological cancers. The identified studies showed elevated levels of sialic acid in serum, tissue and sialylated antigens in most patients with gynecological cancers, underlining its potential for diagnosis.
Statin use and incidence and mortality of breast and gynecology cancer: A cohort study using the National Health Insurance claims database
Authors: Kim Dong‐Sook , Ahn Hyeong Sik , Kim Hyun Jung 
Published: November 2021

AbstractPrevious studies have reported inconsistent findings concerning the impact of statin use on cancer prevention. Our study examined the association between statin use and cancer incidence and mortality related to breast and gynecologic cancers in South Korea. A population‐based cohort study was conducted using the National Health Insurance claims database. Women aged 45 to 70 years old who had taken statins for at least 6 months were compared to statin non‐users of the same age from January 2005 to June 2013. The primary outcomes were cancer incidence and mortality related to breast cancer, total gynecologic cancers, cervix uteri cancer and ovarian cancer. Cox proportional hazards regression was conducted to calculate the adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs). Out of 587 705 women, there were 3591 cases of breast cancer, 2239 cases of gynecologic cancers and 565 breast and total gynecologic cancer deaths during 7.6 person‐years. The aHRs for the association between the risk of each cancer and statin use were 0.88 (95% CI 0.79‐0.97) for breast cancer and 0.83 (95% CI 0.67‐0.99) for cervix uteri cancer. Statin use was associated with decreased breast cancer mortality (HR = 0.65, 95% CI 0.43‐0.99) and total gynecologic cancer mortality (HR = 0.70, 95% CI 0.50‐0.98). A dose‐response relationship was only found for all‐cancer mortality. Statin use for at least 6 months was significantly associated with a lower risk of breast and cervix uteri cancer incidence, and with lower mortality of breast and gynecologic cancers. Further research on these associations will be needed.
BAG3 induces fibroblasts to release key cytokines involved in pancreatic cell migration
Authors: Dufrusine Beatrice , Damiani Verena , Capone Emily , Pieragostino Damiana , Dainese Enrico , De Marco Margot , Reppucci Francesca , Turco Maria C. , Rosati Alessandra , Marzullo Liberato , Sala Gianluca , Sallese Michele , De Laurenzi Vincenzo 
Published: November 2021

AbstractPancreatic ductal adenoma carcinoma (PDAC) is considered one of the deadliest solid cancers as it is usually diagnosed in advanced stages and has a poor response to treatment. The enormous effort made in the last 2 decades in the oncology field has not led to significant progress in improving early diagnosis or therapy for PDAC. The stroma of PDAC plays an active role in tumour initiation and progression and includes immune cells and stromal cells. We previously reported that Bcl2‐associated athanogene (BAG3) secreted by PDAC cells activates tumour‐associated macrophages to promote tumour growth. The disruption of this tumour–stroma axis by the anti‐BAG3 H2L4 therapeutic antibody is sufficient to delay tumour growth and limit metastatic spreading in different PDAC preclinical models. In the present study, we examined the role of BAG3 to activate human fibroblasts (HF) in releasing cytokines capable of supporting tumour progression. Treatment of fibroblasts with recombinant BAG3 induced important changes in the organisation of the cytoskeleton of these cells and stimulated the production of interleukin‐6, monocyte chemoattractant protein‐1/C–C motif chemokine ligand 2, and hepatocyte growth factor. Specifically, we observed that BAG3 triggered a depolymerisation of microtubules at the periphery of the cell while they were conserved in the perinuclear area. Conversely, the vimentin‐based intermediate filaments increased and spread to the edges of the cells. Finally, the conditioned medium (CM) collected from BAG3‐treated HF promoted the survival, proliferation, and migration of the PDAC cells. Blocking of the PDAC‐fibroblast axis by the H2L4 therapeutic anti‐BAG3 antibody, resulted in inhibition of cytokine release and, consequently, the inhibition of the migratory phenotype conferred by the CM to PDAC cells.
CIFDock: A novel CHARMM‐based flexible receptor–flexible ligand docking protocol
Authors: Vankayala Sai L. , Warrensford Luke C. , Pittman Amanda R. , Pollard Benjamin C. , Kearns Fiona L. , Larkin Joseph D. , Woodcock H. Lee 
Published: November 2021

AbstractDocking studies play a critical role in the current workflow of drug discovery. However, limitations may often arise through factors including inadequate ligand sampling, a lack of protein flexibility, scoring function inadequacies (e.g., due to metals, co‐factors, etc.), and difficulty in retaining explicit water molecules. Herein, we present a novel CHARMM‐based induced fit docking (CIFDock) workflow that can circumvent these limitations by employing all‐atom force fields coupled to enhanced sampling molecular dynamics procedures. Self‐guided Langevin dynamics simulations are used to effectively sample relevant ligand conformations, side chain orientations, crystal water positions, and active site residue motion. Protein flexibility is further enhanced by dynamic sampling of side chain orientations using an expandable rotamer library. Steps in the procedure consisting of fixing individual components (e.g., the ligand) while sampling the other components (e.g., the residues in the active site of the protein) allow for the complex to adapt to conformational changes. Ultimately, all components of the complex—the protein, ligand, and waters—are sampled simultaneously and unrestrained with SGLD to capture any induced fit effects. This modular flexible docking procedure is automated using CHARMM scripting, interfaced with SLURM array processing, and parallelized to use the desired number of processors. We validated the CIFDock procedure by performing cross‐docking studies using a data set comprised of 21 pharmaceutically relevant proteins. Five variants of the CHARMM‐based SWISSDOCK scoring functions were created to quantify the results of the final generated poses. Results obtained were comparable to, or in some cases improved upon, commercial docking program data.
Comprehensive analysis of N6‐methyladenosine‐related long non‐coding RNAs for prognosis prediction in liver hepatocellular carcinoma
Authors: Zhu Hong‐Xu , Lu Wen‐Jie , Zhu Wei‐Ping , Yu Song 
Published: November 2021

AbstractBackgroundLiver hepatocellular carcinoma (LIHC) is a lethal cancer. This study aimed to identify the N6‐methyladenosine (m6A)‐targeted long non‐coding RNA (lncRNA) related to LIHC prognosis and to develop an m6A‐targeted lncRNA model for prognosis prediction in LIHC.MethodsThe expression matrix of mRNA and lncRNA was obtained, and differentially expressed (DE) mRNAs and lncRNAs between tumor and normal samples were identified. Univariate Cox and pathway enrichment analyses were performed on the m6A‐targeted lncRNAs and the LIHC prognosis‐related m6A‐targeted lncRNAs. Prognostic analysis, immune infiltration, and gene DE analyses were performed on LIHC subgroups, which were obtained from unsupervised clustering analysis. Additionally, a multi‐factor Cox analysis was used to construct a prognostic risk model based on the lncRNAs from the LASSO Cox model. Univariate and multivariate Cox analyses were used to assess prognostic independence.ResultsA total of 5031 significant DEmRNAs and 292 significant DElncRNAs were screened, and 72 LIHC‐specific m6A‐targeted binding lncRNAs were screened. Moreover, a total of 29 LIHC prognosis‐related m6A‐targeted lncRNAs were obtained and enriched in cytoskeletal, spliceosome, and cell cycle pathways. An 11‐m6A‐lncRNA prognostic model was constructed and verified; the top 10 lncRNAs included LINC00152, RP6‐65G23.3, RP11‐620J15.3, RP11‐290F5.1, RP11‐147L13.13, RP11‐923I11.6, AC092171.4, KB‐1460A1.5, LINC00339, and RP11‐119D9.1. Additionally, the two LIHC subgroups, Cluster 1 and Cluster 2, showed significant differences in the immune microenvironment, m6A enzyme genes, and prognosis of LIHC.ConclusionThe m6A‐lncRNA prognostic model accurately and effectively predicted the prognostic survival of LIHC. Immune cells, immune checkpoints (ICs), and m6A enzyme genes could act as novel therapeutic targets for LIHC.
Ensemble classification of autism spectrum disorder using structural magnetic resonance imaging features
Authors: Zhang‐James Yanli , Buitelaar Jan K. ,   The ENIGMA‐ASD Working Group, van Rooij Daan , Faraone Stephen V. 
Published: November 2021

AbstractBackgroundAutism spectrum disorder (ASD) is characterized by a spectrum of social and communication impairments and rigid and stereotyped behaviors that have a neurodevelopmental origin. Although many imaging studies have reported structural and functional alterations in multiple brain regions, clinically useful diagnostic imaging biomarkers for ASD remain unavailable.MethodsIn this study, we applied machine learning (ML) models to regional volumetric and cortical thickness data from the largest structural magnetic resonance imaging (sMRI) dataset available from the Enhancing Neuro Imaging Genetics Through Meta‐Analysis (ENIGMA) consortium (1833 subjects with ASD and 1838 without ASD; age range: 1.5–64; average age: 15.6; male/female ratio: 4.2:1).ResultsThe highest classification accuracy on a hold‐out test set was achieved using a stacked Extra Tree Classifier. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.62 (95% confidence interval [CI]: 0.57, 0.68) and the area under the precision‐recall curve was 0.58. Learning curve analysis showed the good fit of the model and suggests that more training examples will not likely benefit model performance.ConclusionsOur results suggest that sMRI volumetric and cortical thickness data alone may not provide clinically sufficient useful diagnostic biomarkers for ASD. Developing clinically useful imaging classifiers for ASD will benefit from combining other data modalities or feature types, such as functional MRI data and raw images that can leverage other machine learning (ML) techniques such as convolutional neural networks.
Gender diversity and senior leadership in academic dentistry: Female representation at the dean position in the United States
Authors: Bompolaki Despoina , Pokala Sai Vishnu , Koka Sreenivas 
Published: November 2021

AbstractPurpose/objectivesThe purpose of this study was to calculate the male to female dean ratio in the US dental schools, assess whether the dean's gender is affected by specific school characteristics (such as geographic location or class size), and determine whether the dean's gender affects the percent of women in the school leadership team.MethodsEach US school's website was reviewed to capture the name and gender of each dean and others holding assistant, associate or vice dean positions. All data were entered in an Excel database (Microsoft Excel 2016) and analyzed using a statistical analysis software program (IBM SPSS Statistics, v26; IBM Corp). The level of significance was set to α = 0.05.ResultsThe male to female dean ratio (approximately 5:1) differed significantly from the hypothesized ratio 1:1 (z = 5.22, p < 0.001). Mean class size (χ2 = 0.869, p = 0.351) and school funding source (χ2 = 0.430, p = 0.512) did not differ between schools with a male versus female dean. The percentage of women in the school's leadership team was higher in schools with a female dean (U = 151, p = 0.004).ConclusionsIn the US dental schools, there is one female dean for every five deans who are male, indicating underrepresentation of women at the highest role in academic leadership. Schools with female deans tend to have more women in other administrative roles as well. Change is needed in order to promote equity, diversity, and inclusion in academic dentistry.
Improving Sensitivity of Arterial Spin Labeling Perfusion MRI in Alzheimer's Disease Using Transfer Learning of Deep Learning‐Based ASL Denoising
Authors: Zhang Lei , Xie Danfeng , Li Yiran , Camargo Aldo , Song Donghui , Lu Tong , Jeudy Jean , Dreizin David , Melhem Elias R. , Wang Ze ,   Alzheimer's Disease Neuroimaging Initiative
Published: November 2021

BackgroundArterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) denoising through deep learning (DL) often faces insufficient training data from patients. One solution is to train DL models using healthy subjects' data which are more widely available and transfer them to patients' data.PurposeTo evaluate the transferability of a DL‐based ASL MRI denoising method (DLASL).Study TypeRetrospective.SubjectsFour hundred and twenty‐eight subjects (189 females) from three cohorts.Field Strength/Sequence3 T two‐dimensional (2D) echo‐planar imaging (EPI)‐based pseudo‐continuous ASL (PCASL) and 2D EPI‐based pulsed ASL (PASL) sequences.AssessmentDLASL was trained using young healthy adults' PCASL data (Dataset 1: 250/30 subjects as training/validation set) and was directly transferred (DTF) to PCASL data from Dataset 2 (45 subjects test set) of normal controls (NC) and Alzheimer's disease (AD) groups. DLASL was fine‐tuned (DLASLFT) and tested on PASL data from Dataset 3 (103 subjects test set) of NC and AD. An existing non‐DL method (NonDL) was used for comparison. Cerebral blood flow (CBF) images from ASL MRI were compared between NC and AD to assess characteristic hypoperfusion (lower CBF) patterns in AD. CBF image quality and CBF map sensitivity for detecting hypoperfusion using peak t‐value and suprathreshold cluster size are outcome measures.Statistical TestsPaired t‐test, two‐sample t‐test, one‐way analysis of variance, and Tukey honestly significant difference, and linear mixed‐effects models were used. P < 0.05 was considered statistically significant.ResultsMean contrast‐to‐noise ratio (CNR) of Dataset 2 showed that DTF outperformed NonDL (AD: 3.38 vs. 2.64, NC: 3.80 vs. 3.36). On Dataset 3, DLASLFT outperformed NonDL measured by mean CNR (AD: 2.45 vs. 1.87, NC: 2.54 vs. 2.17) and mean radiologic score (2.86 vs. 2.44). Image quality improvement was significant on both test sets. DTF and DLASLFT improved sensitivity for detecting AD‐related hypoperfusion patterns compared with NonDL.Data ConclusionWe demonstrated the DLASL's transferability across different ASL sequences and different populations.Level of Evidence3Technical EfficacyStage 2