Miracle-dz/UniFAR-FTUs huggingface dataset:
Early Discontinuation of Endocrine Therapy and Recurrence of Breast Cancer among Premenopausal Women

Purpose: Premenopausal women diagnosed with estrogen receptor (ER)-positive breast cancer are prescribed 5–10 years of endocrine therapy to prevent or delay recurrence. In this study, we evaluated the association between early discontinuation of endocrine therapy and breast cancer recurrence in a cohort of premenopausal women. Experimental Design: We identified 4,503 patients with premenopausal ER-positive breast cancer who initiated adjuvant endocrine therapy and were registered in the Danish Breast Cancer Group clinical database (2002–2011). Women were excluded if they had a recurrence or were lost to follow-up less than 1.5 years after breast cancer surgery. Endocrine therapy was considered complete if the patient received at least 4.5 years of treatment or discontinued medication less than 6 months before recurrence. Exposure status was updated annually and modeled as a time-dependent variable. We accounted for baseline and time-varying confounders via time-varying weights, which we calculated from multivariable logistic regression models, and included in regression models to estimate HRs and 95% confidence intervals (CIs) associating early discontinuation with recurrence. Results: Over the study follow-up, 1,001 (22%) women discontinued endocrine therapy. We observed 202 (20%) recurrences among those who discontinued endocrine therapy, and 388 (11%) among those who completed the recommended treatment. The multivariable-adjusted estimated rate of recurrence was higher in women who discontinued endocrine therapy relative to those who completed their treatment (hazard ratio, 1.67; 95% CI, 1.25–2.14). Conclusions: These results highlight the importance of clinical follow-up and behavioral interventions that support persistence of adjuvant endocrine therapy to prevent breast cancer recurrence.
HIV-related enacted stigma and increase frequency of depressive symptoms among Thai and Cambodian adolescents and young adults with perinatal HIV

HIV-related enacted stigma and social problems may increase risk for depression and/or behavioral problems among adolescents and young adults with perinatal HIV(AYA-PHIV), yet few studies have explored stigma in AYA-PHIV residing in low-to-middle income regions, including Southeast Asia. We assessed HIV-related enacted stigma and social problems in AYA-PHIV who participated in the RESILIENCE study (clinicaltrials.gov identification: U19AI53741) in Thailand and Cambodia using specific questions during structured in-person interviews. Depression was measured by the Child Depression Inventory for children <15 years, or the Center for Epidemiologic Studies Depression Scales for youth ≥15 years); behavioral problems were measured by the Child Behavior Checklist (CBCL-caregiver report). Among 195 AYA-PHIV (median age 16.9 years), 25.6% reported a lifetime experience of enacted stigma, while 10.8% experienced social problems due to HIV infection. The frequency of depressive symptoms was nearly two-fold higher among AYA-PHIV with compared to those without HIV-related enacted stigma (34.7% vs. 16.0%, p = 0.005). Caregiver-reported behavioral problems were detected in 14.6% of all AYA-PHIV, with no differences between those with and without HIV-related enacted stigma. Low household income and caregiver mental health problems were independent risk factors for depressive symptoms; HIV-related enacted stigma was also associated with increased risk, warranting targeted services to support AYA-PHIV.
Blending Surface Segmentation and Editing for 3D Models

Recognizing and fitting shape primitives from underlying 3D models are key components of many computer graphics and computer vision applications. Although a vast number of structural recovery methods are available, they usually fail to identify blending surfaces, which corresponds to small transitional regions among relatively large primary patches. To address this issue, we present a novel approach for automatic segmentation and surface fitting with accurate geometric parameters from 3D models, especially mechanical parts. Overall, we formulate the structural segmentation as a Markov random field (MRF) labeling problem. In contrast to existing techniques, we first propose a new clustering algorithm to build superfacets by incorporating 3D local geometric information. This algorithm extracts the general quadric and rolling-ball blending regions, and improves the robustness of further segmentation. Next, we apply a specially designed MRF framework to efficiently partition the original model into different meaningful patches of known surface types by defining the multilabel energy function on the superfacets. Furthermore, we present an iterative optimization algorithm based on skeleton extraction to fit rolling-ball blending patches by recovering the parameters of the rolling center trajectories and ball radius. Experiments on different complex models demonstrate the effectiveness and robustness of the proposed method, and the superiority of our method is also verified through comparisons with state-of-the-art approaches. We further apply our algorithm in applications such as mesh editing by changing the radius of the rolling balls.
Cell-Free DNA-Methylation-Based Methods and Applications in Oncology

Liquid biopsy based on cell-free DNA (cfDNA) enables non-invasive dynamic assessment of disease status in patients with cancer, both in the early and advanced settings. The analysis of DNA-methylation (DNAm) from cfDNA samples holds great promise due to the intrinsic characteristics of DNAm being more prevalent, pervasive, and cell- and tumor-type specific than genomics, for which established cfDNA assays already exist. Herein, we report on recent advances on experimental strategies for the analysis of DNAm in cfDNA samples. We describe the main steps of DNAm-based analysis workflows, including pre-analytics of cfDNA samples, DNA treatment, assays for DNAm evaluation, and methods for data analysis. We report on protocols, biomolecular techniques, and computational strategies enabling DNAm evaluation in the context of cfDNA analysis, along with practical considerations on input sample requirements and costs. We provide an overview on existing studies exploiting cell-free DNAm biomarkers for the detection and monitoring of cancer in early and advanced settings, for the evaluation of drug resistance, and for the identification of the cell-of-origin of tumors. Finally, we report on DNAm-based tests approved for clinical use and summarize their performance in the context of liquid biopsy.
Ten cases of Mycobacterium avium subsp. hominissuis infections linked to equine abortions in Japan, 2018–2019

Abstract Bacterial placentitis in horses commonly results in abortion, premature birth or compromised neonatal foal health. Although mycobacterial infections are generally uncommon in horses, 10 equine abortion cases caused by Mycobacterium avium subsp. hominissuis (MAH) infections occurred between 2018 and 2019 in Japan. They occurred on seven Thoroughbred horse farms in the Hidaka district of Hokkaido, but direct contact among the mares on different farms was not recorded. Most cases were characterized by extensive pathological lesions of the placenta, which are not typical in cases of common pathogenic bacteria such as Streptococcus zooepidemicus and Escherichia coli. All abortions featured white–yellow exudates on the surface of the placenta. Mycobacterial granuloma formations were histologically found in the placenta and fetal organs, and acid‐fast bacteria were isolated from the placenta, fetal samples (heart, lung, liver, kidney, spleen and stomach contents) or uterine lavage fluid. The greatest number of bacteria was isolated from necrotic lesions on the placenta, which could be an important site for bacterial isolation in mycobacterial equine abortions. The isolates were identified as MAH based on internal genome sequences. In variable number tandem repeat analysis, all patterns of the strains were identical. Single nucleotide polymorphism analysis of the core genome grouped all strains in the II‐a/SC3 subcluster. Both results reveal that these strains share the same genetic background, suggesting that the horses had been infected by the same unknown contagious source.
Global strategy for the diagnosis and management of acute kidney injury in patients with liver cirrhosis

Abstract Acute kidney injury (AKI) is a clinical syndrome that complicates the course and worsens clinical outcomes in patients with chronic liver diseases. It is a common complication in hospitalised patients with liver cirrhosis, especially those with decompensated cirrhosis, associated with a high mortality rate. Considering its impact on patient prognosis, efforts should be made to diagnose and tailor therapeutic interventions for AKI at an early stage. In the past decade, a significant progress has been made to understand the key events and define major prognostic factors for the onset and progression of AKI in the cirrhotic population leading hepatologists to redefine the classic definition of hepatorenal syndrome and renal failure in this specific population.
Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening

Beta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural Networks, SANN). In order to evaluate the models’ accuracy and select the best classifiers among automatically generated SANNs, the Matthews correlation coefficient (MCC) was used. The application of the combination of maxHBint3 and SpMax8_Bhs descriptors leads to the highest predicting abilities of SANNs, as evidenced by the averaged test set prediction results (MCC = 0.748) calculated for ten different dataset splits. Additionally, the models were analyzed employing receiver operating characteristics (ROC) and cumulative gain charts. The thirteen final classifiers obtained as a result of the model development procedure were applied for a natural compounds collection available in the BIOFACQUIM database. As a result of this beta-glucosidase inhibitors screening, eight compounds were univocally classified as active by all SANNs.
idenPC-CAP: Identify protein complexes from weighted RNA-protein heterogeneous interaction networks using co-assemble partner relation

Protein complexes play important roles in most cellular processes. The available genome-wide protein-protein interaction (PPI) data make it possible for computational methods identifying protein complexes from PPI networks. However, PPI datasets usually contain a large ratio of false positive noise. Moreover, different types of biomolecules in a living cell cooperate to form a union interaction network. Because previous computational methods focus only on PPIs ignoring other types of biomolecule interactions, their predicted protein complexes often contain many false positive proteins. In this study, we develop a novel computational method idenPC-CAP to identify protein complexes from the RNA-protein heterogeneous interaction network consisting of RNA-RNA interactions, RNA-protein interactions and PPIs. By considering interactions among proteins and RNAs, the new method reduces the ratio of false positive proteins in predicted protein complexes. The experimental results demonstrate that idenPC-CAP outperforms the other state-of-the-art methods in this field.
Research on Virtual Synchronous Charge and Discharge Machine with Power Quality Control for EVs

Aiming at the problems of frequency stability and power quality degradation caused by the access of a large number of power electronic devices to the microgrid, a virtual synchronous charging and discharging motor control strategy with power quality control is proposed for electric vehicles. Firstly, aiming at the frequency stability of microgrid, the control strategy of virtual synchronous charging and discharging motor of electric vehicle is proposed, which combines the power side and load side virtual synchronous machine (VSM) technology with two-way power flow to make the charging and discharging motor have inertia damping in both directions and participate in the frequency control of microgrid. Secondly, model predictive control (MPC) is used to replace the traditional PI control of current loop, which simplifies the loop parameter design and improves the dynamic performance of the system. Then, aiming at the problem of power quality degradation in microgrid, a compensation loop is designed to suppress the harmonic current at the common connection point caused by nonlinear load. Finally, the model is built in Matlab/Simulink to verify the effectiveness of the proposed strategy.
Effects of Rivastigmine on Brain Functional Networks in Patients With Alzheimer Disease Based on the Graph Theory

Objective The aim of this study was to explore the effect of rivastigmine on brain function in Alzheimer disease (AD) by analyzing brain functional network based on the graph theory. Methods We enrolled 9 patients with mild to moderate AD who received rivastigmine treatment and 9 healthy controls (HC). Subsequently, we used resting-state functional magnetic resonance imaging data to establish the whole-brain functional network using a graph theory–based analysis. Furthermore, we compared systemic and local network indicators between pre- and posttreatment. Results Patients with AD exhibited a posttreatment increase in the Mini-Mental State Examination scores and a decrease in the Alzheimer's Disease Assessment Scale cognitive subscale scores and activities of daily living. The systemic network for HC and patients with AD had good pre- and posttreatment clustering coefficients. There was no change in the Cp, Lp, Gamma, Lambda, and Sigma in patients with AD. There were no significant between-group differences in the pre- and posttreatment systemic network measures. Regarding the regional network, patients with AD showed increased betweenness centrality in the bilateral caudate nucleus and right superior temporal pole after treatment with rivastigmine. However, there was no between-group difference in the pre- and posttreatment betweenness centrality of these regions. There were no significant correlations between regional network measure changes and clinical score alterations in patients with AD. Conclusions There are similar systemic network properties between patients with AD and HC. Rivastigmine cannot alter systemic network attributes in patients with AD. However, it improves the topological properties of regional networks and between-node information transmission in patients with AD.
The Efficacy of an Explicit Intervention Approach to Improve Past Tense Marking for Early School-Age Children With Developmental Language Disorder.

Purpose The aim of the study was to evaluate the efficacy of a theoretically motivated explicit intervention approach to improve regular past tense marking for early school-age children with developmental language disorder (DLD). Method Twenty-one children with DLD (ages 5;9-6;9 [years;months]) were included in a crossover randomized controlled trial (intervention, n = 10; waiting control, n = 11). Intervention included once-weekly sessions over 10 weeks using the SHAPE CODING system, in combination with a systematic cueing hierarchy to teach past tense marking. Once the first group completed intervention, the waiting control group crossed over to the intervention condition. The primary outcome was criterion-referenced measures of past tense marking with standardized measures of expressive and receptive grammar as the secondary outcome. Ancillary analyses on extension and behavioral control measures of morphosyntax were also conducted. Results There was a significant Time × Group interaction (p < .001) with a significant difference in pre-post intervention improvement in favor of the intervention group (p < .001, d = 3.03). Further analysis once both groups had received the intervention revealed no improvement for either group on past tense production during the 5-week pre-intervention period, significant improvement pre-post intervention (p < .001, d = 1.22), with gains maintained for 5 weeks postintervention. No significant differences were found on pre- to postintervention standardized measures of grammar, or on extension or control measures. Conclusions The efficacy of the theoretically motivated explicit grammar intervention was demonstrated. Results contribute to the evidence base supporting this intervention to improve past tense production in early school-age children with DLD, suggesting it is a viable option for clinicians to select when treating morphosyntactic difficulties for this population. Supplemental Material https://doi.org/10.23641/asha.13345202.
Internet-delivered cognitive behaviour therapy for adolescents with insomnia comorbid to psychiatric conditions: A non-randomised trial

Insomnia is highly prevalent among adolescents with psychiatric conditions and is known to aggravate psychiatric symptoms. Research on cognitive behaviour therapy for adolescents with comorbid insomnia (CBT-I) is still limited. The aim of this study was to investigate feasibility and preliminary effects of internet-delivered CBT for adolescents with insomnia comorbid to a psychiatric condition. Twenty-one patients (13–17 years) with comorbid insomnia were recruited from Child and Adolescent Psychiatry. All patients received 7 weeks of internet-delivered CBT-I with therapist support. Outcomes were assessed at baseline, post-treatment, and at a 4-month follow-up. The proportion of completed assessments was overall acceptable. Participants on average completed 4.48 (sd = 1.97) of the seven treatment modules and therapists on average spent 12.80 minutes (sd = 6.23) per patient and week. Results showed large statistically significant improvements on insomnia severity, sleep efficiency, sleep onset latency and sleep quality. Medium to large improvements were also seen on the psychiatric symptoms of depression, obsessive-compulsive symptoms, interpersonal sensitivity, paranoid ideation and psychoticism. These findings indicate that internet-delivered CBT is feasible and potentially promising for improving sleep and reducing psychiatric symptoms in adolescent psychiatric patients with insomnia and co-morbid psychiatric disorders. A larger randomised trial is warranted to verify these preliminary results.
Infection of Porphyromonas gingivalis Increases Phosphate-Induced Calcification of Vascular Smooth Muscle Cells

Accumulating evidence suggests a link between periodontal disease and cardiovascular diseases. Vascular calcification is the pathological precipitation of phosphate and calcium in the vasculature and is closely associated with increased cardiovascular risk and mortality. In this study, we have demonstrated that the infection with Porphyromonas gingivalis (P. gingivalis), one of the major periodontal pathogens, increases inorganic phosphate-induced vascular calcification through the phenotype transition, apoptosis, and matrix vesicle release of vascular smooth muscle cells. Moreover, P. gingivalis infection accelerated the phosphate-induced calcium deposition in cultured rat aorta ex vivo. Taken together, our findings indicate that P. gingivalis contributes to the periodontal infection-related vascular diseases associated with vascular calcification.
Protein-functionalized poly(ethylene glycol) hydrogels as scaffolds for monolayer organoid culture.

Stem cell-derived, organotypic in vitro models, known as organoids, have emerged as superior alternatives to traditional cell culture models due to their unparalleled ability to recreate complex physiological and pathophysiological processes. For this reason, they are attractive targets of tissue-engineering efforts, as constructs that include organoid technology would be expected to better simulate the many functions of the desired tissue or organ. While the 3D spheroidal architecture that is the default architecture of most organoid models may be preferred for some applications, 2D monolayer arrangements remain the preferred organization for many applications in tissue engineering. Therefore, in this work, we present a method to create monolayer organoid cultures on poly(ethylene glycol) (PEG) hydrogel scaffolds, using intestinal epithelial organoids (IEOs) as a proof-of-concept. Our process involves two steps: the hydrogel is first functionalized with a layer of poly(D-lysine) (PDL), which then allows the adsorption of pristine, unmodified basement membrane proteins. This approach successfully mediates the formation of IEO monolayer unlike conventional approaches that rely on covalent modification of the hydrogel surface with cell-adhesive peptides and basement membrane proteins. We show that these IEO monolayers recreate important physiological functions of the native intestinal epithelium including multi-lineage differentiation, apical-basal polarization, and the ability to model infections with human norovirus. We also show coating of a scaffold mimicking intestinal villous topography, resulting in a 3D IEO monolayer. We expect this protocol will be useful to researchers attempting to leverage the increased physiological relevance of organoid models to elevate the potential of their tissue-engineered constructs.
"The Canton Canon" Digital Library Based on Knowledge Graph -- Taking the Revolutionary Archives of Canton in the Republic of China as an Example

In order to more efficiently meet people’s in-depth needs for knowledge acquisition and research, and to more effectively develop and use "the Canton Canon" historical archives, we designed and constructed the Canton Revolutionary History Knowledge Graph based on the revolutionary archives of Canton during the Republic of China. We associated the knowledge graph with the document corpus, transformed and combined the traditional digital library from document information management to knowledge management, and proposed a double-Layer retrieval mode of the document corpus based on the knowledge graph. At the same time, we developed "the Canton Canon" digital library based on the knowledge graph, and introduced the design and application of the digital library. It provides a great example of how to use huge archives more efficiently and build a more open digital library. What’s more, it also opens up new ideas for the transformation of Chinese digital libraries from information management to knowledge management.