Richterstrauss4073

e. setting exponential activations in the first layer, can significantly improve the robustness and interpretabilty of learned representations directly in convolutional filters and indirectly with attribution methods.

The aim was to reveal the everyday impact of living with RA in people not treated with advanced therapies (i.e. biologic or targeted synthetic DMARDs).

People with RA, with disease duration >2 years, not currently treated with advanced therapies, completed an online survey promoted by the National Rheumatoid Arthritis Society. Items covered demographics, current treatment, RA flare frequency, the Rheumatoid Arthritis Impact of Disease (RAID) tool and questions reflecting work status and ability. Descriptive and multivariable regression analyses were performed.

There were 612 responses from patients having a mean age of 59 years, 88% female, 37.7% with disease duration 2-5 years and 27.9% with disease duration 5-10 years. In the last year, 90% reported an RA flare, with more than six flares in 23%. A RAID patient acceptable state was recorded in 12.4%. Each of the seven domains was scored in the high range by >50% respondents; 74.3% scored sleep problems and 72% fatigue in the high range. A need to change working hours was reported by 70%. Multivariable analyses revealed that increasing difficulties with daily physical activities, reduced emotional and physical well-being in the past week were all significantly associated with pain, number of flares and ability to cope (

 < 0.005). The RAID score was significantly predictive of the number of flares.

Patients not currently treated with advanced therapies experience profound difficulties in everyday living with RA, across a broad range of measures. We advocate that patient-reported measures be used to facilitate holistic care, addressing inflammation and other consequences of RA on everyday life.

Patients not currently treated with advanced therapies experience profound difficulties in everyday living with RA, across a broad range of measures. We advocate that patient-reported measures be used to facilitate holistic care, addressing inflammation and other consequences of RA on everyday life.The literature knowledge panels developed and implemented in PubChem are described. These help to uncover and summarize important relationships between chemicals, genes, proteins, and diseases by analyzing co-occurrences of terms in biomedical literature abstracts. Named entities in PubMed records are matched with chemical names in PubChem, disease names in Medical Subject Headings (MeSH), and gene/protein names in popular gene/protein information resources, and the most closely related entities are identified using statistical analysis and relevance-based sampling. Knowledge panels for the co-occurrence of chemical, disease, and gene/protein entities are included in PubChem Compound, Protein, and Gene pages, summarizing these in a compact form. Statistical methods for removing redundancy and estimating relevance scores are discussed, along with benefits and pitfalls of relying on automated (i.e., not human-curated) methods operating on data from multiple heterogeneous sources.Chemical patents are an essential source of information about novel chemicals and chemical reactions. However, with the increasing volume of such patents, mining information about these chemicals and chemical reactions has become a time-intensive and laborious endeavor. In this study, we present a system to extract chemical reaction events from patents automatically. BMS-986158 supplier Our approach consists of two steps 1) named entity recognition (NER)-the automatic identification of chemical reaction parameters from the corresponding text, and 2) event extraction (EE)-the automatic classifying and linking of entities based on their relationships to each other. For our NER system, we evaluate bidirectional long short-term memory (BiLSTM)-based and bidirectional encoder representations from transformer (BERT)-based methods. For our EE system, we evaluate BERT-based, convolutional neural network (CNN)-based, and rule-based methods. We evaluate our NER and EE components independently and as an end-to-end system, reporting the precision, recall, and F 1 score. Our results show that the BiLSTM-based method performed best at identifying the entities, and the CNN-based method performed best at extracting events.

Androgen receptor (AR) signaling is important in prostate cancer progression, and therapies that target this pathway have been the mainstay of treatment for advanced disease for over 70 years. Tumors eventually progress despite castration through a number of well-characterized mechanisms; however, little is known about what determines the magnitude of response to short-term pathway inhibition.

We evaluated a novel combination of AR-targeting therapies (degarelix, abiraterone, and bicalutamide) and noted that the objective patient response to therapy was highly variable. To investigate what was driving treatment resistance in poorly responding patients, as a secondary outcome we comprehensively characterized pre- and post-treatment samples using both whole-genome and RNA sequencing.

We find that resistance following short-term treatment differs molecularly from typical progressive castration-resistant disease, associated with transcriptional reprogramming, to a transitional epithelial-to-mesenchymal transition (EMT) phenotype rather than an upregulation of AR signaling. Unexpectedly, tolerance to therapy appears to be the default state, with treatment response correlating with the prevalence of tumor cells deficient for

, a key regulator of EMT reprogramming.

We show that EMT characterizes acutely resistant prostate tumors and that deletion of

, a key transcriptional regulator of EMT, correlates with clinical response.

We show that EMT characterizes acutely resistant prostate tumors and that deletion of SNAI2, a key transcriptional regulator of EMT, correlates with clinical response.

Breast cancer risks for

and

pathogenic variant (PV) carriers are modified by an 86-single nucleotide polymorphism polygenic risk score (PRS) and individual clinical factors. Here, we describe comprehensive risk prediction models for women of European ancestry combining PV status, PRS, and individual clinical variables.

This study included deidentified clinical records from 358,095 women of European ancestry who received testing with a multigene panel (September 2013 to November 2019). Model development included

PV carriers (n = 4,286),

PV carriers (n = 2,666), and women negative for other breast cancer risk gene PVs (n = 351,143). Odds ratios (ORs) were calculated using multivariable logistic regression with adjustment for familial cancer history. Risk estimates incorporating PV status, PRS, and Tyrer-Cuzick v7.02 were calculated using a Fixed-Stratified method that accounts for correlations between risk factors. Stratification of PV carriers into risk categories on the basis of remaining lifetime risk (RLR) was assessed in independent cohorts of PV carriers.

ORs for association of PV status with breast cancer were 2.01 (95% CI, 1.88 to 2.16) and 1.83 (95% CI, 1.68 to 2.00) for

and

PV carriers, respectively. ORs for PRS per one standard deviation were 1.51 (95% CI, 1.37 to 1.66) and 1.45 (95% CI, 1.30 to 1.64) in

and

PV carriers, respectively. Using the combined model (PRS plus Tyrer-Cuzick plus PV status), RLR was low (≤ 20%) for 24.2% of

PV carriers, medium (20%-50%) for 63.8%, and high (> 50%) for 12.0%. Among

PV carriers, RLR was low for 31.5% of patients, medium for 58.5%, and high for 9.7%.

In

and

PV carriers, risk assessment including PRS, Tyrer-Cuzick, and PV status has the potential for more precise direction of screening and prevention strategies.

In CHEK2 and ATM PV carriers, risk assessment including PRS, Tyrer-Cuzick, and PV status has the potential for more precise direction of screening and prevention strategies.

Graft choice for pediatric anterior cruciate ligament reconstruction (ACLR) is determined by several factors. There is limited information on the use and outcomes of allograft ACLR in pediatric patients. The purpose of this systematic review and meta-analysis was to quantify reported failure rates of allograft versus autograft ACLR in patients ≤19 years of age with ≥2 years of follow-up. We hypothesized that there would be higher rates of failure for allograft compared with autograft ACLR in this population.

PubMed/MEDLINE and Embase databases were systematically searched for literature regarding allograft and autograft ACLR in pediatric/adolescent patients. Articles were included if they described a cohort of patients with average age of ≤19 years, had a minimum of 2 years of follow-up, described graft failure as an outcome, and had a Level of Evidence grade of I to III. Qualitative review and quantitative meta-analysis were performed to compare graft failure rates. A random-effects model was created to ed a significantly higher failure rate for allograft compared with autograft ACLR in this patient population. Additional studies are needed to improve the understanding of variables associated with the high ACLR failure rate among pediatric and adolescent patients.

Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.Single nucleotide polymorphisms in genes encoding microRNAs (miRNA-SNPs) may affect the maturation steps of miRNAs or target mRNA recognition, leading to changes in the expression of target mRNAs to cause gain- or loss-of-function changes. Several miRNA-SNPs are known to be associated with the risk of diseases such as cancer. The purpose of this study was to comprehensively determine the miRNA-SNPs in Japanese individuals to evaluate the differences in allele frequencies between ethnicities by comparing data from the global population in the 1000 Genomes Project and differences between healthy subjects and cancer patients. We performed next-generation sequencing targeting genes encoding 1809 pre-miRNAs. As a result, 403 miRNA-SNPs (146 miRNA-SNPs per subject on average) were identified in 28 healthy Japanese subjects. We observed significant differences in the allele frequencies between ethnicities in 33 of the 403 miRNA-SNPs. The numbers of miRNA-SNPs per subject in 44 non-small cell lung cancer (NSCLC), 33 colorectal cancer (CRC), and 15 soft tissue sarcoma (STS) patients were almost equal to those in healthy subjects. Significant differences in allele frequencies were observed for 14, 11, and 9 miRNA-SNPs in NSCLC, CRC, and STS patients compared with the frequencies in healthy subjects, suggesting that these SNPs can be biomarkers of risk for each type of cancer assessed. In summary, we comprehensively characterized miRNA-SNPs in Japanese individuals and found differences in allele frequencies of several miRNA-SNPs between ethnicities and between healthy subjects and cancer patients. Studies investigating a larger number of subjects should be performed to confirm the potential of miRNA-SNPs as biomarkers of cancer risk.