bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comparison of machine learning models and Cox proportional hazards models regarding their ability to predict the risk of gastrointestinal cancer based on metabolic syndrome and its components
Authors: Tran Tao Thi , Lee Jeonghee , Gunathilake Madhawa , Kim Junetae , Kim Sun-Young , Cho Hyunsoon , Kim Jeongseon 
Published: March 2023

BackgroundLittle is known about applying machine learning (ML) techniques to identify the important variables contributing to the occurrence of gastrointestinal (GI) cancer in epidemiological studies. We aimed to compare different ML models to a Cox proportional hazards (CPH) model regarding their ability to predict the risk of GI cancer based on metabolic syndrome (MetS) and its components.MethodsA total of 41,837 participants were included in a prospective cohort study. Incident cancer cases were identified by following up with participants until December 2019. We used CPH, random survival forest (RSF), survival trees (ST), gradient boosting (GB), survival support vector machine (SSVM), and extra survival trees (EST) models to explore the impact of MetS on GI cancer prediction. We used the C-index and integrated Brier score (IBS) to compare the models.ResultsIn all, 540 incident GI cancer cases were identified. The GB and SSVM models exhibited comparable performance to the CPH model concerning the C-index (0.725). We also recorded a similar IBS for all models (0.017). Fasting glucose and waist circumference were considered important predictors.ConclusionsOur study found comparably good performance concerning the C-index for the ML models and CPH model. This finding suggests that ML models may be considered another method for survival analysis when the CPH model’s conditions are not satisfied.
A systematic review and meta-analysis evaluating the impact of antibiotic use on the clinical outcomes of cancer patients treated with immune checkpoint inhibitors
Authors: Crespin Athéna , Le Bescop Clément , de Gunzburg Jean , Vitry Fabien , Zalcman Gérard , Cervesi Julie , Bandinelli Pierre-Alain 
Published: March 2023

BackgroundImmune checkpoint inhibitors (ICIs) have considerably improved patient outcomes in various cancer types, but their efficacy remains poorly predictable among patients. The intestinal microbiome, whose balance and composition can be significantly altered by antibiotic use, has recently emerged as a factor that may modulate ICI efficacy. The objective of this systematic review and meta-analysis is to investigate the impact of antibiotics on the clinical outcomes of cancer patients treated with ICIs.MethodsPubMed and major oncology conference proceedings were systematically searched to identify all studies reporting associations between antibiotic use and at least one of the following endpoints: Overall Survival (OS), Progression-Free Survival (PFS), Objective Response Rate (ORR) and Progressive Disease (PD) Rate. Pooled Hazard Ratios (HRs) for OS and PFS, and pooled Odds Ratios (ORs) for ORR and PD were calculated. Subgroup analyses on survival outcomes were also performed to investigate the potential differential effect of antibiotics according to cancer types and antibiotic exposure time windows.Results107 articles reporting data for 123 independent cohorts were included, representing a total of 41,663 patients among whom 11,785 (28%) received antibiotics around ICI initiation. The pooled HRs for OS and PFS were respectively of 1.61 [95% Confidence Interval (CI) 1.48-1.76] and 1.45 [95% CI 1.32-1.60], confirming that antibiotic use was significantly associated with shorter survival. This negative association was observed consistently across all cancer types for OS and depending on the cancer type for PFS. The loss of survival was particularly strong when antibiotics were received shortly before or after ICI initiation. The pooled ORs for ORR and PD were respectively of 0.59 [95% CI 0.47-0.76] and 1.86 [95% CI 1.41-2.46], suggesting that antibiotic use was significantly associated with worse treatment-related outcomes.ConclusionAs it is not ethically feasible to conduct interventional, randomized, controlled trials in which antibiotics would be administered to cancer patients treated with ICIs to demonstrate their deleterious impactversuscontrol, prospective observational studies and interventional trials involving microbiome modifiers are crucially needed to uncover the role of microbiome and improve patient outcomes. Such studies will reduce the existing publication bias by allowing analyses on more homogeneous populations, especially in terms of treatments received, which is not possible at this stage given the current state of the field. In the meantime, antibiotic prescription should be cautiously considered in cancer patients receiving ICIs.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42019145675.
Hepatocellular carcinoma subtypes based on metabolic pathways reveals potential therapeutic targets
Authors: He Zehua , Chen Qingfeng , He Wanrong , Cao Junyue , Yao Shunhan , Huang Qingqiang , Zheng Yu 
Published: March 2023

IntroductionHepatocellular carcinoma (HCC) is an aggressive malignancy with steadily increasing incidence rates worldwide and poor therapeutic outcomes. Studies show that metabolic reprogramming plays a key role in tumor genesis and progression. In this study, we analyzed the metabolic heterogeneity of epithelial cells in the HCC and screened for potential biomarkers.MethodsThe hepatic single-cell RNA sequencing (scRNA-seq) datasets of HCC patients and healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Based on data intergration and measurement of differences among groups, the metabolic epithelial cell subpopulations were identified. The single-cell metabolic pathway was analyzed and the myeloid subpopulations were identified. Cell-cell interaction analysis and single-cell proliferation analysis were performed. The gene expression profiles of HCC patients were obtained from the GSE14520 dataset of GEO and TCGA-LIHC cohort of the UCSC Xena website. Immune analysis was performed. The differentially expressed genes (DEGs) were identified and functionally annotated. Tumor tissues from HCC patients were probed with anti-ALDOA, anti-CD68, anti-CD163, anti-CD4 and anti-FOXP3 antibodies. Results We analyzed the scRNA-seq data from 48 HCC patients and 14 healthy controls. The epithelial cells were significantly enriched in HCC patients compared to the controls (p = 0.011). The epithelial cells from HCC patients were classified into two metabolism-related subpopulations (MRSs) – pertaining to amino acid metabolism (MRS1) and glycolysis (MRS2). Depending on the abundance of these metabolic subpopulations, the HCC patients were also classified into the MRS1 and MRS2 subtype distinct prognoses and immune infiltration. The MRS2 group had significantly worse clinical outcomes and more inflamed tumor microenvironment (TME), as well as a stronger crosstalk between MRS2 cells and immune subpopulations that resulted in an immunosuppressive TME. We also detected high expression levels of ALDOA in the MRS2 cells and HCC tissues. In the clinical cohort, HCC patients with higher ALDOA expression showed greater enrichment of immunosuppressive cells including M2 macrophages and T regulatory cells.DiscussionThe glycolytic subtype of HCC cells with high ALDOA expression is associated with an immunosuppressive TME and predicts worse clinical outcomes, providing new insights into the metabolism and prognosis of HCC.
How smart is artificial intelligence in organs delineation? Testing a CE and FDA-approved Deep-Learning tool using multiple expert contours delineated on planning CT images
Authors: Strolin Silvia , Santoro Miriam , Paolani Giulia , Ammendolia Ilario , Arcelli Alessandra , Benini Anna , Bisello Silvia , Cardano Raffaele , Cavallini Letizia , Deraco Elisa , Donati Costanza Maria , Galietta Erika , Galuppi Andrea , Guido Alessandra , Ferioli Martina , Laghi Viola , Medici Federica , Ntreta Maria , Razganiayeva Natalya , Siepe Giambattista , Tolento Giorgio , Vallerossa Daria , Zamagni Alice , Morganti Alessio Giuseppe , Strigari Lidia 
Published: March 2023

BackgroundA CE- and FDA-approved cloud-based Deep learning (DL)-tool for automatic organs at risk (OARs) and clinical target volumes segmentation on computer tomography images is available. Before its implementation in the clinical practice, an independent external validation was conducted.MethodsAt least a senior and two in training Radiation Oncologists (ROs) manually contoured the volumes of interest (VOIs) for 6 tumoral sites. The auto-segmented contours were retrieved from the DL-tool and, if needed, manually corrected by ROs. The level of ROs satisfaction and the duration of contouring were registered. Relative volume differences, similarity indices, satisfactory grades, and time saved were analyzed using a semi-automatic tool.ResultsSeven thousand seven hundred sixty-five VOIs were delineated on the CT images of 111 representative patients. The median (range) time for manual VOIs delineation, DL-based segmentation, and subsequent manual corrections were 25.0 (8.0-115.0), 2.3 (1.2-8) and 10.0 minutes (0.3-46.3), respectively. The overall time for VOIs retrieving and modification was statistically significantly lower than for manual contouring (p&lt;0.001). The DL-tool was generally appreciated by ROs, with 44% of vote 4 (well done) and 43% of vote 5 (very well done), correlated with the saved time (p&lt;0.001). The relative volume differences and similarity indexes suggested a better inter-agreement of manually adjusted DL-based VOIs than manually segmented ones.ConclusionsThe application of the DL-tool resulted satisfactory, especially in complex delineation cases, improving the ROs inter-agreement of delineated VOIs and saving time.
Gradual deterioration of fatty liver disease to liver cancer via inhibition of AMPK signaling pathways involved in energy-dependent disorders, cellular aging, and chronic inflammation
Authors: Meng Sha-Sha , Gu Hong-Wei , Zhang Ting , Li Yu-Sang , Tang He-Bin 
Published: March 2023

IntroductionHepatocellular carcinoma (HCC) is the most prevalent primary liver cancer kind. According to recent research, a fatty liver increases the risk of hepatocellular cancer. Nevertheless, the AMPK signaling pathway is crucial. In addition, 5’-AMP-activated protein kinase (AMPK) is strongly linked to alterations in the tumor microenvironment, such as inflammation, hypoxia, and aging. The objective of this study is to evaluate the impact of the AMPK signaling pathway on the progression of fatty liver to HCC.MethodsIn this study, we established a mouse liver cancer model using high-fat diets and nano-nitrosamines (nano-DEN). In addition, we employed a transcriptomic technique to identify all mRNAs detected in liver samples at the 25th weekexpression of proteins linked with the LKB1-AMPK-mTOR signaling pathway, inflammation, aging, and hypoxia was studied in microarrays of liver cancer tissues from mice and humans. These proteins included p-AMPK, LKB1, mTOR, COX-2, β-catenin, HMGB1, p16, and HIF-1α.ResultsData were collected at different times in the liver as well as in cancerous and paracancerous regions and analyzed by a multispectral imaging system. The results showed that most of the genes in the AMPK signaling pathway were downregulated. Prakk1 expression was upregulated compared to control group but downregulated in the cancerous regions compared to the paracancerous regions. Stk11 expression was downregulated in the cancerous regions. Mtor expression was upregulated in the cancerous regions. During liver cancer formation, deletion of LKB1 in the LKB1-AMPK-mTOR signaling pathway reduces phosphorylation of AMPK. It contributed to the upregulation of mTOR, which further led to the upregulation of HIF1α. In addition, the expression of β-catenin, COX-2, and HMGB1 were upregulated, as well as the expression of p16 was downregulated.DiscussionThese findings suggest that changes in the AMPK signaling pathway exacerbate the deterioration of disrupted energy metabolism, chronic inflammation, hypoxia, and cellular aging in the tumor microenvironment, promoting the development of fatty liver into liver cancer.
Intrafraction tumor motion monitoring and dose reconstruction for liver pencil beam scanning proton therapy
Authors: Nankali Saber , Worm Esben Schjødt , Thomsen Jakob Borup , Stick Line Bjerregaard , Bertholet Jenny , Høyer Morten , Weber Britta , Mortensen Hanna Rahbek , Poulsen Per Rugaard 
Published: March 2023

BackgroundPencil beam scanning (PBS) proton therapy can provide highly conformal target dose distributions and healthy tissue sparing. However, proton therapy of hepatocellular carcinoma (HCC) is prone to dosimetrical uncertainties induced by respiratory motion. This study aims to develop intra-treatment tumor motion monitoring during respiratory gated proton therapy and combine it with motion-including dose reconstruction to estimate the delivered tumor doses for individual HCC treatment fractions.MethodsThree HCC-patients were planned to receive 58 GyRBE (n=2) or 67.5 GyRBE (n=1) of exhale respiratory gated PBS proton therapy in 15 fractions. The treatment planning was based on the exhale phase of a 4-dimensional CT scan. Daily setup was based on cone-beam CT (CBCT) imaging of three implanted fiducial markers. An external marker block (RPM) on the patient’s abdomen was used for exhale gating in free breathing. This study was based on 5 fractions (patient 1), 1 fraction (patient 2) and 6 fractions (patient 3) where a post-treatment control CBCT was available. After treatment, segmented 2D marker positions in the post-treatment CBCT projections provided the estimated 3D motion trajectory during the CBCT by a probability-based method. An external-internal correlation model (ECM) that estimated the tumor motion from the RPM motion was built from the synchronized RPM signal and marker motion in the CBCT. The ECM was then used to estimate intra-treatment tumor motion. Finally, the motion-including CTV dose was estimated using a dose reconstruction method that emulates tumor motion in beam’s eye view as lateral spot shifts and in-depth motion as changes in the proton beam energy. The CTV homogeneity index (HI) The CTV homogeneity index (HI) was calculated as D2% − D98%D50% ×100%.ResultsThe tumor position during spot delivery had a root-mean-square error of 1.3 mm in left-right, 2.8 mm in cranio-caudal and 1.7 mm in anterior-posterior directions compared to the planned position. On average, the CTV HI was larger than planned by 3.7%-points (range: 1.0-6.6%-points) for individual fractions and by 0.7%-points (range: 0.3-1.1%-points) for the average dose of 5 or 6 fractions.ConclusionsA method to estimate internal tumor motion and reconstruct the motion-including fraction dose for PBS proton therapy of HCC was developed and demonstrated successfully clinically.
Nondestructive label-free detection of peritumoral white matter damage using cross-polarization optical coherence tomography
Authors: Achkasova Ksenia A. , Moiseev Alexander A. , Yashin Konstantin S. , Kiseleva Elena B. , Bederina Evgenia L. , Loginova Maria M. , Medyanik Igor A. , Gelikonov Grigory V. , Zagaynova Elena V. , Gladkova Natalia D. 
Published: March 2023

IntroductionTo improve the quality of brain tumor resections, it is important to differentiate zones with myelinated fibers destruction from tumor tissue and normal white matter. Optical coherence tomography (OCT) is a promising tool for brain tissue visualization and in the present study, we demonstrate the ability of cross-polarization (CP) OCT to detect damaged white matter and differentiate it from normal and tumor tissues.Materials and methodsThe study was performed on 215 samples of brain tissue obtained from 57 patients with brain tumors. The analysis of the obtained OCT data included three stages: 1) visual analysis of structural OCT images; 2) quantitative assessment based on attenuation coefficients estimation in co- and cross-polarizations; 3) building of color-coded maps with subsequent visual analysis. The defining characteristics of structural CP OCT images and color-coded maps were determined for each studied tissue type, and then two classification tests were passed by 8 blinded respondents after a training.ResultsVisual assessment of structural CP OCT images allows detecting white matter areas with damaged myelinated fibers and differentiate them from normal white matter and tumor tissue. Attenuation coefficients also allow distinguishing all studied brain tissue types, while it was found that damage to myelinated fibers leads to a statistically significant decrease in the values of attenuation coefficients compared to normal white matter. Nevertheless, the use of color-coded optical maps looks more promising as it combines the objectivity of optical coefficient and clarity of the visual assessment, which leads to the increase of the diagnostic accuracy of the method compared to visual analysis of structural OCT images.ConclusionsAlteration of myelinated fibers causes changes in the scattering properties of the white matter, which gets reflected in the nature of the received CP OCT signal. Visual assessment of structural CP OCT images and color-coded maps allows differentiating studied tissue types from each other, while usage of color-coded maps demonstrates higher diagnostic accuracy values in comparison with structural images (F-score = 0.85-0.86 and 0.81, respectively). Thus, the results of the study confirm the potential of using OCT as a neuronavigation tool during resections of brain tumors.
Prenatal marijuana exposure and visual perception in toddlers: Evidence of a sensory processing deficit
Authors: Bailey Beth A. , Osborne Jahla B. 
Published: March 2023

BackgroundResearch has identified a link between prenatal marijuana exposure and multiple outcomes in children, including cognitive development. Several studies have found specific differences in sensory processing and attention, with visual perception especially impacted in school age children. The current study explored whether this effect is evident at an earlier age, and thus our goal was to investigate the relationship between in-utero marijuana exposure and sensory processing capabilities in toddlers. We hypothesized that in-utero marijuana exposure throughout pregnancy would specifically predict visual sensory hyperactivity in children as young as 15 months of age.MethodsParticipants were 225 15-month-old children whose mothers were recruited during pregnancy. Substance exposure was prospectively collected and biochemically verified, with marijuana coded as no exposure, 1st trimester exposure only, or exposure throughout pregnancy. The Infant Toddler Sensory Profile evaluated 5 domains of sensory processing (visual, auditory, tactile, vestibular, oral).ResultsPrenatal marijuana exposure throughout pregnancy, but not when limited to the first trimester, predicted a two-fold increased likelihood of scoring in a range indicating high levels of seeking out and potentially over-attending to visual stimulation after controlling for potentially confounding factors including other prenatal exposures. Marijuana exposure was not significantly related to other processing domains.ConclusionResults indicate that links previously identified between prenatal marijuana exposure and visual function and attention may already be evident at 15 months of age, and also suggest an impact related to continuous/later pregnancy exposure. Our findings, as well as those from previous studies, all suggest visual processing differences for exposed children, differences that may predict emerging issues with visual attention and habituation. As legalization of marijuana continues to increase, further research is clearly needed to examine specific teratologic effects associated with use during pregnancy.
Cost-effectiveness analysis of PD-1 inhibitors combined with chemotherapy as first-line therapy for advanced esophageal squamous-cell carcinoma in China
Authors: Liu Shixian , Dou Lei , Li Shunping 
Published: March 2023

Objective: This study was aimed to investigate the cost-effectiveness of all available programmed death 1 (PD-1) inhibitors combined with chemotherapy in the first-line treatment of advanced esophageal squamous-cell carcinoma (ESCC) from the Chinese healthcare system perspective.Methods: A partitioned survival model with a 3-week cycle and a 10-year time horizon was constructed based on a network meta-analysis. The survival data and utility values were derived from clinical trials, and the direct medical costs were collected from public drug bidding database and published literature. Total costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) were calculated. Scenario, one-way and probabilistic sensitivity analyses were performed to assess the uncertainty around model parameters.Results: Compared with mono-chemotherapy, toripalimab, sintilimab and camrelizumab plus chemotherapy were cost-effective treatment regimens, while serplulimab, pembrolizumab and nivolumab plus chemotherapy were not cost-effective options. Toripalimab plus chemotherapy provided the highest QALYs of 0.95 with the lower cost of $8,110.53 compared to other competing alternatives. The robustness of the base-case results was confirmed by scenario and one-way sensitivity analysis. At a willingness-to-pay threshold of three times per capita gross domestic product ($38,351.20) in 2021, the probability of toripalimab plus chemotherapy being the optimal option was 74.25% compared with other six competing alternatives.Conclusion: Toripalimab plus chemotherapy represented the most cost-effective option as the first-line therapy for advanced ESCC patients in China.
Prenatal exposure to acetaminophen and adolescent assessment of behavior: Discrepancies by age and reporter
Authors: Smith-Webb Rashida S. , Barnard-Mayers Ruby , Werler Martha M. , Parker Samantha E. 
Published: March 2023

Acetaminophen, which is one of the most commonly used medications during pregnancy, has been linked to adverse neurodevelopmental outcomes among offspring during childhood. Less is known about associations with outcomes occurring later in adolescence.Methods: We conducted a follow-up study of children born between 1996 and 2002. Data on illnesses and medications, including acetaminophen, during pregnancy were collected through a standardized interview after delivery. Behavioral assessments were conducted at two subsequent time points, childhood (ages 5–10) and adolescence (ages 11–17). Outcomes examined included internalizing, externalizing, and total behavior problems based on the parent-completed Child Behavior Checklist (CBCL), the teacher-completed Teacher Report Form (TRF), and the youth-completed Youth Self Report (YSR, adolescent follow-up only). Adjusted linear regression models were used to calculate mean differences (MD) and 95% confidence intervals (95% CI) in T-scores comparing those with prenatal acetaminophen exposure to those without. Stabilized inverse probability weights were used to account for attrition.Results: Among the 216 mother-child dyads with completed parent and teacher behavioral assessments at both childhood and adolescence, prenatal acetaminophen exposure was not associated with behavioral problems according to either parent or teacher assessments. Modest increases in externalizing and total behavior problems were observed according to youth report (MD: 1.9). Compared to associations observed during the childhood follow-up, associations at adolescence were attenuated according to parent-report.Conclusion: Reported associations between prenatal acetaminophen exposure and behavioral outcomes were not consistent over time nor between reporters.