Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction Model of Tumor Regression Grade for Advanced Gastric Cancer After Preoperative Chemotherapy

Background Preoperative chemotherapy (PCT) has been considered an important treatment for advanced gastric cancer (AGC). The tumor regression grade (TRG) system is an effective tool for the assessment of patient responses to PCT. Pathological complete response (TRG = 0) of the primary tumor is an excellent predictor of better prognosis. However, which patients could achieve pathological complete response (TRG = 0) after chemotherapy is still unknown. The study aimed to find predictors of TRG = 0 in AGC. Methods A total of 304 patients with advanced gastric cancer from July 2009 to November 2018 were enrolled retrospectively. All patients were randomly assigned (2:1) to training and internal validation groups. In addition, 124 AGC patients receiving PCT from December 2018 to June 2020 were included prospectively in the external validation cohort. A prediction model for TRG = 0 was established based on four predictors in the training group and was validated in the internal and external validation groups. Results Through univariate and multivariate analyses, we found that CA199, CA724, tumor differentiation and short axis of the largest regional lymph node (LNmax) were independent predictors of TRG = 0. Based on the four predictors, we established a prediction model for TRG = 0. The AUC values of the prediction model in the training, internal and external validation groups were 0.84, 0.73 and 0.82, respectively. Conclusions We found that CA199, CA724, tumor differentiation and LNmax were associated with pathological response in advanced gastric cancer. The prediction model could provide guidance for clinical work.
Prediction of the Growth Rate of Early-Stage Lung Adenocarcinoma by Radiomics

Objectives To investigate the value of imaging in predicting the growth rate of early lung adenocarcinoma. Methods From January 2012 to June 2018, 402 patients with pathology-confirmed lung adenocarcinoma who had two or more thin-layer CT follow-up images were retrospectively analyzed, involving 407 nodules. Two complete preoperative CT images and complete clinical data were evaluated. Training and validation sets were randomly assigned according to an 8:2 ratio. All cases were divided into fast-growing and slow-growing groups. Researchers extracted 1218 radiomics features from each volumetric region of interest (VOI). Then, radiomics features were selected by repeatability analysis and Analysis of Variance (ANOVA); Based on the Univariate and multivariate analyses, the significant radiographic features is selected in training set. A decision tree algorithm was conducted to establish the radiographic model, radiomics model and the combined radiographic-radiomics model. Model performance was assessed by the area under the curve (AUC) obtained by receiver operating characteristic (ROC) analysis. Results Sixty-two radiomics features and one radiographic features were selected for predicting the growth rate of pulmonary nodules. The combined radiographic-radiomics model (AUC 0.78) performed better than the radiographic model (0.727) and the radiomics model (0.710) in the validation set. Conclusions The model has good clinical application value and development prospects to predict the growth rate of early lung adenocarcinoma through the combined radiographic-radiomics model.
Case Report: Repeated Low-Dose Rituximab Treatment Is Effective in Relapsing Neuro Behçet's Disease

Neuro Behçet's disease (NBD) is a rare but most aggressive manifestation of Behçet's disease (BD) with a poor prognosis, and some patients even present a relapsing and treatment-resistant progressive course. In some relapsing NBD cases, traditional corticosteroids and immunosuppressive drugs show limited efficacy, while benefits of biological agents, such as anti-B-lymphocyte CD20 biological agent rituximab (RTX), gradually represent potential therapeutic advantages with clinical rapid remission and long-time maintenance. However, up to now, the optimal dosage of RTX in NBD is still elucidated. Here, we report two patients with relapsing NBD, despite continuous high dose steroids and sufficient azathioprine treatment, still presenting severe and relapsing meningoencephalitis or brainstem involvement. Repeated low-dose RTX (100 mg × 3/1 week apart, 100 mg repeated every 6 months) is then attempted with rapid recovery and sustained remission. The approach in our cases may expand therapeutic options and provide helpful references for relapsing NBD treatment.
A Parental Competence Scale: Dimensions and Their Association With Adolescent Outcomes

Positive family functioning during adolescence is usually studied analyzing parents' competences and children's relationship abilities. We present an instrument for the assessment of parental competence, which encompasses both educational style and transmission of values. The objective of the study was to analyze its factor structure and to assess its value in predicting adolescent outcomes. We recruited 2,459 high school students, aged 12–15, in 40 schools from Spain, Peru, Mexico, and Chile. They responded to the instrument and to other questions regarding lifestyles. Exploratory and confirmatory factor analyses were carried out in order to assess the internal structure of the instrument, and internal consistency of the resulting dimensions was calculated. Finally, regression analyses were performed to establish associations between the parenting dimensions and adolescent outcomes. Factor analyses showed a consistent structure, with good fit indices in the four countries. The final four factors include parenting styles (Warmth and Demandingness) and education in values (Fortitude and Privacy). Regression analyses showed associations with adolescent outcomes. For example, adolescents' life satisfaction was best predicted by Warmth and Education in fortitude. Practical implications are suggested.
Management and Quality Control of Large Neuroimaging Datasets: Developments From the Barcelonaβeta Brain Research Center

Recent decades have witnessed an increasing number of large to very large imaging studies, prominently in the field of neurodegenerative diseases. The datasets collected during these studies form essential resources for the research aiming at new biomarkers. Collecting, hosting, managing, processing, or reviewing those datasets is typically achieved through a local neuroinformatics infrastructure. In particular for organizations with their own imaging equipment, setting up such a system is still a hard task, and relying on cloud-based solutions, albeit promising, is not always possible. This paper proposes a practical model guided by core principles including user involvement, lightweight footprint, modularity, reusability, and facilitated data sharing. This model is based on the experience from an 8-year-old research center managing cohort research programs on Alzheimer’s disease. Such a model gave rise to an ecosystem of tools aiming at improved quality control through seamless automatic processes combined with a variety of code libraries, command line tools, graphical user interfaces, and instant messaging applets. The present ecosystem was shaped around XNAT and is composed of independently reusable modules that are freely available on GitLab/GitHub. This paradigm is scalable to the general community of researchers working with large neuroimaging datasets.
Psychometric Properties of the Persian Version of the Teasing Questionnaire 23

The current study was a cross-sectional research and aimed to investigate the factor structure, internal consistency, and validities of the Persian version of the Teasing Questionnaire-Revised (TQ-R). Forward and backward translations of the TQ-R were performed; face and content validities were determined based on comments by a sample of psychology students and specialists. Using the cluster sampling method, 290 participants were recruited, and 201 valid data (Mage = 23.53, SD = 3.53, 64.2% men) were analyzed. The factor structure was assessed by confirmatory and exploratory factor analysis (EFA). The result of the confirmatory factor analysis(es) did not confirm the proposed three, four, and five-factor models. EFA revealed four factors with 23 items, explaining 52.03% of the total variance. The internal consistency of the Persian version of Teasing Questionnaire 23 was in the excellent range (α = 0.92), and its expected associations with external correlates (e.g., depression and anxiety) supported the measure’s convergent validity. The findings indicated that the Persian version of the TQ-R has sound psychometric properties and can be used as a valid and reliable tool in research and clinical outcomes.
Roles of Neuropeptides, VIP and AVP, in the Mammalian Central Circadian Clock

In mammals, the central circadian clock is located in the suprachiasmatic nucleus (SCN) of the hypothalamus. Individual SCN cells exhibit intrinsic oscillations, and their circadian period and robustness are different cell by cell in the absence of cellular coupling, indicating that cellular coupling is important for coherent circadian rhythms in the SCN. Several neuropeptides such as arginine vasopressin (AVP) and vasoactive intestinal polypeptide (VIP) are expressed in the SCN, where these neuropeptides function as synchronizers and are important for entrainment to environmental light and for determining the circadian period. These neuropeptides are also related to developmental changes of the circadian system of the SCN. Transcription factors are required for the formation of neuropeptide-related neuronal networks. Although VIP is critical for synchrony of circadian rhythms in the neonatal SCN, it is not required for synchrony in the embryonic SCN. During postnatal development, the clock genes cryptochrome (Cry)1 and Cry2 are involved in the maturation of cellular networks, and AVP is involved in SCN networks. This mini-review focuses on the functional roles of neuropeptides in the SCN based on recent findings in the literature.
Circulating Interleukins and Risk of Multiple Sclerosis: A Mendelian Randomization Study

Background Previous research have implicated critical roles of systemic inflammation in the development of Multiple Sclerosis (MS). But the causal relationship between interleukins (ILs) and MS has not been fully elucidated. Objective In this study, we applied Mendelian randomization (MR) approaches to address the causal associations between genetically determined circulating levels of ILs and the risk of MS. Methods Genetic instruments for circulating IL-1 receptor antagonist (IL-1Ra), IL-2 receptor α subunit (IL-2Rα), IL-6, IL-16, IL-17, and IL-18 were obtained from recently published genome-wide association studies (GWAS). Summary-level data for MS were obtained from the International Multiple Sclerosis Genetics Consortium. MR analyses were performed using the R software (version 3.6.1, The R Foundation) and the TwoSampleMR package. Results Genetic predisposition to higher circulating levels of IL-2Rα were significantly associated with MS risk. The odds ratio (OR) was 1.22 (95% confidence interval [CI], 1.12–1.32; p < 0.001) per one standard deviation increase in circulating IL-2Rα levels. There was a suggestive association of circulating IL-1Ra with MS risk (OR, 0.94; 95% CI, 0.88–0.99; p = 0.027). The other ILs were not associated with the outcome. Conclusion Our results indicated that circulating IL-2Rα was causally associated with risk of MS.
Case Report: Histological and Histomorphometrical Results of a 3-D Printed Biphasic Calcium Phosphate Ceramic 7 Years After Insertion in a Human Maxillary Alveolar Ridge

Introduction: Dental implant placement can be challenging when insufficient bone volume is present and bone augmentation procedures are indicated. The purpose was to assess clinically and histologically a specimen of 30%HA-60%β-TCP BCP 3D-printed scaffold, after 7-years. Case Description: The patient underwent bone regeneration of maxillary buccal plate with 3D-printed biphasic-HA block in 2013. After 7-years, a specimen of the regenerated bone was harvested and processed to perform microCT and histomorphometrical analyses. Results: The microarchitecture study performed by microCT in the test-biopsy showed that biomaterial volume decreased more than 23% and that newly-formed bone volume represented more than 57% of the overall mineralized tissue. Comparing with unloaded controls or peri-dental bone, Test-sample appeared much more mineralized and bulky. Histological evaluation showed complete integration of the scaffold and signs of particles degradation. The percentage of bone, biomaterials and soft tissues was, respectively, 59.2, 25.6, and 15.2%. Under polarized light microscopy, the biomaterial was surrounded by lamellar bone. These results indicate that, while unloaded jaws mimicked the typical osteoporotic microarchitecture after 1-year without loading, the BCP helped to preserve a correct microarchitecture after 7-years. Conclusions: BCP 3D-printed scaffolds represent a suitable solution for bone regeneration: they can lead to straightforward and less time-consuming surgery, and to bone preservation.
Analysis of Swarm Satellite Magnetic Field Data Before the 2016 Ecuador (Mw = 7.8) Earthquake Based on Non-negative Matrix Factorization

In this paper, based on non-negative matrix factorization (NMF), we analyzed the ionosphere magnetic field data of the Swarm Alpha satellite before the 2016 (Mw = 7. 8) Ecuador earthquake (April 16, 0.35°N, 79.93°W), including the whole data collected under quiet and disturbed geomagnetic conditions. The data from each track were decomposed into basis features and their corresponding weights. We found that the energy and entropy of one of the weight components were more concentrated inside the earthquake-sensitive area, which meant that this weight component was more likely to reflect the activity inside the earthquake-sensitive area. We focused on this weight component and used five times the root mean square (RMS) to extract the anomalies. We found that for this weight component, the cumulative number of tracks, which had anomalies inside the earthquake-sensitive area, showed accelerated growth before the Ecuador earthquake and recovered to linear growth after the earthquake. To verify that the accelerated cumulative anomaly was possibly associated with the earthquake, we excluded the influence of the geomagnetic activity and plasma bubble. Through the random earthquake study and low-seismicity period study, we found that the accelerated cumulative anomaly was not obtained by chance. Moreover, we observed that the cumulative Benioff strain S, which reflected the lithosphere activity, had acceleration behavior similar to the accelerated cumulative anomaly of the ionosphere magnetic field, which suggested that the anomaly that we obtained was possibly associated with the Ecuador earthquake and could be described by one of the Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) models.
Analysis of Tumor Microenvironment Characteristics in Bladder Cancer: Implications for Immune Checkpoint Inhibitor Therapy

The tumor microenvironment (TME) plays a crucial role in cancer progression and recent evidence has clarified its clinical significance in predicting outcomes and efficacy. However, there are no studies on the systematic analysis of TME characteristics in bladder cancer. In this study, we comprehensively evaluated the TME invasion pattern of bladder cancer in 1,889 patients, defined three different TME phenotypes, and found that different subtypes were associated with the clinical prognosis and pathological characteristics of bladder cancer. We further explored the signaling pathways, cancer-immunity cycle, copy number, and somatic mutation differences among the different subtypes and used the principal component analysis algorithm to calculate the immune cell (IC) score, a tool for comprehensive evaluation of TME. Univariate and multivariate Cox regression analyses showed that ICscore is a reliable and independent prognostic biomarker. In addition, the use of anti-programmed death-ligand (PD-L1) treatment cohort, receiver operating characteristic (ROC) curve, Tumor Immune Dysfunction and Exclusion (TIDE), Subnetwork Mappings in Alignment of Pathways (SubMAP), and other algorithms confirmed that ICscore is a reliable prognostic biomarker for immune checkpoint inhibitor response. Patients with higher ICscore showed a significant therapeutic advantage in immunotherapy. In conclusion, this study improves our understanding of the characteristics of TME infiltration in bladder cancer and provides guidance for more effective personalized immunotherapy strategies.
Using the Health Belief Model to Understand Age Differences in Perceptions and Responses to the COVID-19 Pandemic

COVID-19 severity and mortality risk are greater for older adults whereas economic impact is deeper for younger adults. Using the Health Belief Model (HBM) as a framework, this study used a web-based survey to examine how perceived COVID-19 susceptibility and severity and perceived efficacy of recommended health behaviors varied by age group and were related to the adoption of health behaviors. Proportional odds logistic regression was used to examine the relationship between age group and perceived COVID-19 susceptibility, severity, impact, and health behavior efficacy and adoption. Structural equation modeling based on HBM constructs examined the relationships between health beliefs and behaviors. Data from 820 participants (Ontario, Canada) were analyzed (age: 42.7, 16.2 years; 79% women). Middle-aged and older adults reported greater concerns about the personal risk of hospitalization and mortality, economic impact, and social impact of COVID-19 than young adults. Middle-aged adults also reported greatest concern for other age groups. Adoption and perceived efficacy of health behaviors was similar across age groups with few exceptions. Both middle-aged and older-adults were more likely to perceive their own and each other's age groups as responding adequately to COVID-19 compared to young adults. Structural equation modeling indicated perceived benefits of health behaviors were the primary driver of behavior uptake, with socioeconomic factors and perceived severity and susceptibility indirectly associated with uptake through their influence on perceived benefits. Overall, these results suggest adoption of health behaviors is very high with few differences between age groups, despite differences in perceived impact of COVID-19. Public health communications should focus on the benefits of health behaviors to drive adoption.
Upregulated IL-32 Expression And Reduced Gut Short Chain Fatty Acid Caproic Acid in People Living With HIV With Subclinical Atherosclerosis

Despite the success of antiretroviral therapy (ART), people living with HIV (PLWH) are still at higher risk for cardiovascular diseases (CVDs) that are mediated by chronic inflammation. Identification of novel inflammatory mediators with the inherent potential to be used as CVD biomarkers and also as therapeutic targets is critically needed for better risk stratification and disease management in PLWH. Here, we investigated the expression and potential role of the multi-isoform proinflammatory cytokine IL-32 in subclinical atherosclerosis in PLWH (n=49 with subclinical atherosclerosis and n=30 without) and HIV- controls (n=25 with subclinical atherosclerosis and n=24 without). While expression of all tested IL-32 isoforms (α, β, γ, D, ϵ, and θ) was significantly higher in peripheral blood from PLWH compared to HIV- controls, IL-32D and IL-32θ isoforms were further upregulated in HIV+ individuals with coronary artery atherosclerosis compared to their counterparts without. Upregulation of these two isoforms was associated with increased plasma levels of IL-18 and IL-1β and downregulation of the atheroprotective protein TRAIL, which together composed a unique atherosclerotic inflammatory signature specific for PLWH compared to HIV- controls. Logistic regression analysis demonstrated that modulation of these inflammatory variables was independent of age, smoking, and statin treatment. Furthermore, our in vitro functional data linked IL-32 to macrophage activation and production of IL-18 and downregulation of TRAIL, a mechanism previously shown to be associated with impaired cholesterol metabolism and atherosclerosis. Finally, increased expression of IL-32 isoforms in PLWH with subclinical atherosclerosis was associated with altered gut microbiome (increased pathogenic bacteria; Rothia and Eggerthella species) and lower abundance of the gut metabolite short-chain fatty acid (SCFA) caproic acid, measured in fecal samples from the study participants. Importantly, caproic acid diminished the production of IL-32, IL-18, and IL-1β in human PBMCs in response to bacterial LPS stimulation. In conclusion, our studies identified an HIV-specific atherosclerotic inflammatory signature including specific IL-32 isoforms, which is regulated by the SCFA caproic acid and that may lead to new potential therapies to prevent CVD in ART-treated PLWH.
Graph Gamma Process Linear Dynamical Systems

We introduce graph gamma process (GGP) linear dynamical systems to model real-valued multivariate time series. GGP generates S latent states that are shared by K diﬀerent communities, each of which is characterized by its own pattern of activation probabilities imposed on a S × S directed sparse graph, and allow both S and K to grow without bound. For temporal pattern discovery, the latent representation under the model is used to de-compose the time series into a parsimonious set of multivariate sub-sequences generated by formed communities. In each sub-sequence, diﬀerent data dimensions often share similar temporal patterns but may exhibit distinct magnitudes, and hence allowing the superposition of all sub-sequences to exhibit diverse behaviors at diﬀerent data dimensions. On both synthetic and real-world time series, the proposed nonparametric Bayesian dynamic models, which are initialized at random, consistently exhibit good predictive performance in comparison to a variety of baseline models, revealing interpretable latent state transition patterns and decomposing the time series into distinctly behaved sub-sequences.
Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function

Efficiently finding First-order Nash Equilibria (FNE) in zero-sum games can be challenging, even in a two-player setting. This work proposes an algorithm for finding the FNEs of a two-player zero-sum game, in which the local cost functions can be non-convex, and the players only have access to local stochastic gradients. The proposed approach is based on reformulating the problem of interest as minimizing the Regularized Nikaido-Isoda (RNI) function. We show that the global minima of the RNI correspond to the set of FNEs, and that for certain classes of non-convex games the RNI minimization problem becomes convex. Moreover, we introduce a first-order (stochastic) optimization method, and establish its convergence to a neighborhood of a stationary solution of the RNI objective. The key in the analysis is to properly control the bias between the local stochastic gradient and the true one. Although the RNI function has been used in analyzing convex games, to our knowledge, this is the first time that the properties of the RNI formulation have been exploited to find FNEs for non-convex games in a stochastic setting.