Extracting Multiple Worries From Breast Cancer Patient Blogs Using Multilabel Classification With the Natural Language Processing Model Bidirectional Encoder Representations From Transformers: Infodemiology Study of Blogs

Background: Patients with breast cancer have a variety of worries and need multifaceted information support. Their accumulated posts on social media contain rich descriptions of their daily worries concerning issues such as treatment, family, and finances. It is important to identify these issues to help patients with breast cancer to resolve their worries and obtain reliable information. Objective: This study aimed to extract and classify multiple worries from text generated by patients with breast cancer using Bidirectional Encoder Representations From Transformers (BERT), a context-aware natural language processing model. Methods: A total of 2272 blog posts by patients with breast cancer in Japan were collected. Five worry labels, “treatment,” “physical,” “psychological,” “work/financial,” and “family/friends,” were defined and assigned to each post. Multiple labels were allowed. To assess the label criteria, 50 blog posts were randomly selected and annotated by two researchers with medical knowledge. After the interannotator agreement had been assessed by means of Cohen kappa, one researcher annotated all the blogs. A multilabel classifier that simultaneously predicts five worries in a text was developed using BERT. This classifier was fine-tuned by using the posts as input and adding a classification layer to the pretrained BERT. The performance was evaluated for precision using the average of 5-fold cross-validation results. Results: Among the blog posts, 477 included “treatment,” 1138 included “physical,” 673 included “psychological,” 312 included “work/financial,” and 283 included “family/friends.” The interannotator agreement values were 0.67 for “treatment,” 0.76 for “physical,” 0.56 for “psychological,” 0.73 for “work/financial,” and 0.73 for “family/friends,” indicating a high degree of agreement. Among all blog posts, 544 contained no label, 892 contained one label, and 836 contained multiple labels. It was found that the worries varied from user to user, and the worries posted by the same user changed over time. The model performed well, though prediction performance differed for each label. The values of precision were 0.59 for “treatment,” 0.82 for “physical,” 0.64 for “psychological,” 0.67 for “work/financial,” and 0.58 for “family/friends.” The higher the interannotator agreement and the greater the number of posts, the higher the precision tended to be. Conclusions: This study showed that the BERT model can extract multiple worries from text generated from patients with breast cancer. This is the first application of a multilabel classifier using the BERT model to extract multiple worries from patient-generated text. The results will be helpful to identify breast cancer patients’ worries and give them timely social support

Identification of hand-foot syndrome from cancer patients’ blog posts: BERT-based deep-learning approach to detect potential adverse drug reaction symptoms

Early detection and management of adverse drug reactions (ADRs) is crucial for improving patients’ quality of life. Hand-foot syndrome (HFS) is one of the most problematic ADRs for cancer patients. Recently, an increasing number of patients post their daily experiences to internet community, for example in blogs, where potential ADR signals not captured through routine clinic visits can be described. Therefore, this study aimed to identify patients with potential ADRs, focusing on HFS, from internet blogs by using natural language processing (NLP) deep-learning methods. From 10,646 blog posts, written in Japanese by cancer patients, 149 HFS-positive sentences were extracted after pre-processing, annotation and scrutiny by a certified oncology pharmacist. The HFS-positive sentences described not only HFS typical expressions like “pain" or “spoon nail”, but also patient-derived unique expressions like onomatopoeic ones. The dataset was divided at a 4 to 1 ratio and used to train and evaluate three NLP deep-learning models: long short-term memory (LSTM), bidirectional LSTM and bidirectional encoder representations from transformers (BERT). The BERT model gave the best performance with precision 0.63, recall 0.82 and f1 score 0.71 in the HFS user identification task. Our results demonstrate that this NLP deep-learning model can successfully identify patients with potential HFS from blog posts, where patients’ real wordings on symptoms or impacts on their daily lives are described. Thus, it should be feasible to utilize patient-generated text data to improve ADR management for individual patients

Characterization of Nutrient Intake in Biopsy-Confirmed NAFLD Patients

Objectives: Weight loss improves the liver pathophysiological status of nonalcoholic fatty liver disease (NAFLD) patients. However, there are few studies that investigate the accurate relationships between nutritional intake and disease progression in NAFLD patients. Methods: A total of 37 biopsy-confirmed NAFLD patients were enrolled in this study. Clinical and nutritional control data of 5074 persons were obtained from the National Institute of Health and Nutrition. Each NAFLD subject recorded dietary intake for seven consecutive days using a dietary questionnaire and photographs of each meal. A dietitian analyzed and quantified the nutritional data in each patient. We further analyzed the nutritional intake of NAFLD patients in three groups according to the following criteria: (1) liver fibrosis degree (advanced, early), (2) gender (male, female), and (3) body mass index (BMI) (high, low). Results: Excesses or deficiencies of multiple nutrients were found in NAFLD patients compared with control subjects. In addition, there were variations in nutritional intake. (1) The intake of vitamins A, B6, and E, pantothenic acid, soluble dietary fiber, and salt was lower in the advanced fibrosis group than in the early fibrosis group. (2) Fat intake was higher in male patients, and dietary fiber intake was lower in both male and female patients compared with control subjects. (3) Saturated fatty acid intake was higher, and copper and vitamin E intakes were lower in patients with high BMI than with low BMI. Conclusions: Our study demonstrates that differences were found in some nutrient intake of NAFLD patients and controls and according to the severity of the conditions (liver fibrosis degree, BMI)

Involvement of chondroitin sulfate synthase-3 (chondroitin synthase-2) in chondroitin polymerization through its interaction with chondroitin synthase-1 or chondroitin-polymerizing factor

Previously, we have demonstrated that co-expression of ChSy-1 (chondroitin synthase-1), with ChPF (chondroitin-polymerizing factor) resulted in a marked augmentation of glycosyltransferase activities and the expression of the chondroitin polymerase activity of ChSy-1. These results prompted us to evaluate the effects of co-expression of the recently cloned CSS3 (chondroitin sulfate synthase-3) with ChPF, because ChSy-1 and CSS3 have similar properties, i.e. they possess GalNAcT-II (N-acetylgalactosaminyltransferase-II) and GlcAT-II (glucuronyltransferase-II) activities responsible for the elongation of CS (chondroitin sulfate) chains but cannot polymerize chondroitin chains by themselves. Co-expressed CSS3 and ChPF showed not only substantial GalNAcT-II and GlcAT-II activities but also chondroitin polymerase activity. Interestingly, co-expressed ChSy-1 and CSS3 also exhibited polymerase activity. The chain length of chondroitin formed by the co-expressed proteins in various combinations was different. In addition, interactions between any two of ChSy-1, CSS3 and ChPF were demonstrated by pull-down assays. Moreover, overexpression of CSS3 increased the amount of CS in HeLa cells, while the RNA interference of CSS3 resulted in a reduction in the amount of CS in the cells. Altogether these results suggest that chondroitin polymerization is achieved by multiple combinations of ChSy-1, CSS3 and ChPF. Based on these characteristics, we have renamed CSS3 ChSy-2 (chondroitin synthase-2)

Prediction of Nonalcoholic Fatty Liver Disease Using Noninvasive and Non-Imaging Procedures in Japanese Health Checkup Examinees

Access to imaging is limited for diagnosing nonalcoholic fatty liver disease (NAFLD) in general populations. This study evaluated the diagnostic performance of noninvasive and nonimaging indexes to predict NAFLD in the general Japanese population. Health checkup examinees without hepatitis virus infection or habitual alcohol drinking were included. Fatty liver was diagnosed by ultrasonography. The hepatic steatosis index (HSI), Zhejiang University (ZJU) index, and fatty liver index (FLI) were determined, and risk of advanced liver fibrosis was evaluated by the fibrosis-4 index. NAFLD was diagnosed in 1935 (28.0%) of the 6927 subjects. The area under the receiver operating characteristic (AUROC) curve of the HSI, ZJU index, and FLI was 0.874, 0.886, and 0.884, respectively. The AUROC of the ZJU index (p p = 0.002) was significantly greater than that for the HSI. In subjects with a high risk of advanced fibrosis, the sensitivity of the HSI, ZJU index, and FLI were 88.8%, 94.4%, and 83.3% with a low cut-off value and the specificity was 98.5%, 100%, and 100% with a high cut-off value. In conclusion, all indexes were useful to diagnose NAFLD in the general Japanese population and in subjects with potentially advanced liver fibrosis

Prediction of Nonalcoholic Fatty Liver Disease Using Noninvasive and Non-Imaging Procedures in Japanese Health Checkup Examinees

Access to imaging is limited for diagnosing nonalcoholic fatty liver disease (NAFLD) in general populations. This study evaluated the diagnostic performance of noninvasive and nonimaging indexes to predict NAFLD in the general Japanese population. Health checkup examinees without hepatitis virus infection or habitual alcohol drinking were included. Fatty liver was diagnosed by ultrasonography. The hepatic steatosis index (HSI), Zhejiang University (ZJU) index, and fatty liver index (FLI) were determined, and risk of advanced liver fibrosis was evaluated by the fibrosis-4 index. NAFLD was diagnosed in 1935 (28.0%) of the 6927 subjects. The area under the receiver operating characteristic (AUROC) curve of the HSI, ZJU index, and FLI was 0.874, 0.886, and 0.884, respectively. The AUROC of the ZJU index (p < 0.001) and FLI (p = 0.002) was significantly greater than that for the HSI. In subjects with a high risk of advanced fibrosis, the sensitivity of the HSI, ZJU index, and FLI were 88.8%, 94.4%, and 83.3% with a low cut-off value and the specificity was 98.5%, 100%, and 100% with a high cut-off value. In conclusion, all indexes were useful to diagnose NAFLD in the general Japanese population and in subjects with potentially advanced liver fibrosis

Rapid glucose sensing by protein kinase A for insulin exocytosis in mouse pancreatic islets

The role of protein kinase A (PKA) in insulin exocytosis was investigated with the use of two-photon excitation imaging of mouse islets of Langerhans. Inhibitors of PKA selectively reduced the number of exocytic events during the initial period (< 250 s) of the first phase of glucose-induced exocytosis (GIE), without affecting the second phase, in intact islets or small clusters of islet cells. The PKA inhibitors did not reduce the extent of the glucose-induced increase in [Ca(2+)](i). The actions of glucose and PKA in Ca(2+)-induced insulin exocytosis (CIE) triggered by photolysis of a caged-Ca(2+) compound, which resulted in large increases in [Ca(2+)](i) and thereby bypassed the ATP-sensitive K(+) channel-dependent mechanism of glucose sensing, were therefore studied. A high concentration (20 mm) of glucose potentiated CIE within 1 min, and this effect was blocked by inhibitors of PKA. This PKA-dependent action of glucose required glucose metabolism, given that increasing the intracellular concentration of cAMP by treatment with forskolin potentiated CIE only at the high glucose concentration. Finally, PKA appeared to reduce the frequency of ‘kiss-and-run’ exocytic events and to promote full-fusion events during GIE. These data indicate that a PKA-dependent mechanism of glucose sensing, which is operative even at the basal level of PKA activity, plays an important role specifically in the first phase of GIE, and they suggest that the action of PKA is mediated at the level of the fusion reaction