Characteristics and clinical outcomes of breast cancer in young BRCA carriers according to tumor histology

BACKGROUND

Young women with breast cancer (BC) have an increased chance of carrying germline BRCA pathogenic variants (PVs). Limited data exist on the prognostic impact of tumor histology (i.e. ductal versus lobular) in hereditary breast cancer.

METHODS

This multicenter retrospective cohort study included women aged ≤40 years with early-stage breast cancer diagnosed between January 2000 and December 2020 and known to carry germline PVs in BRCA1/2. Histology was locally assessed in each center. The Kaplan-Meier method and Cox regression analysis were used to assess disease-free survival and overall survival.

RESULTS

Of 4628 patients included from 78 centers worldwide, 3969 (86%) had pure ductal, 135 (3%) pure lobular, and 524 (11%) other histologies. Compared with ductal tumors, lobular tumors were more often grade 1/2 (57.7% versus 22.1%), stage III (29.6% versus 18.5%), and luminal A-like (42.2% versus 12.2%). Lobular tumors were more often associated with BRCA2 PVs (71.1% BRCA2), while ductal tumors were more often associated with BRCA1 PVs (65.7% BRCA1). Patients with lobular tumors more often had mastectomy (68.9% versus 58.3%), and less often received chemotherapy (83.7% versus 92.9%). With a median follow-up of 7.8 years, no significant differences were observed in disease-free survival (adjusted hazard ratio 1.01, 95% confidence interval 0.74-1.37) or overall survival (hazard ratio 0.96, 95% confidence interval 0.62-1.50) between patients with ductal versus lobular tumors. No significant survival differences were observed according to specific BRCA gene, breast cancer subtype, or body mass index.

CONCLUSIONS

In this large global cohort of young BRCA carriers with breast cancer, the incidence of pure lobular histology was low and associated with higher disease stage at diagnosis, luminal-like disease and BRCA2 PVs. Histology did not appear to impact prognosis.

Impact of hormone receptor status and tumor subtypes of breast cancer in young BRCA carriers

BACKGROUND

Hormone receptor expression is a known positive prognostic and predictive factor in breast cancer; however, limited evidence exists on its prognostic impact on prognosis of young patients harboring a pathogenic variant (PV) in the BRCA1 and/or BRCA2 genes.

PATIENTS AND METHODS

This international, multicenter, retrospective cohort study included young patients (aged ≤40 years) diagnosed with invasive breast cancer and harboring germline PVs in BRCA genes. We investigated the impact of hormone receptor status on clinical behavior and outcomes of breast cancer. Outcomes of interest [disease-free survival (DFS), breast cancer-specific survival (BCSS), and overall survival (OS)] were first investigated according to hormone receptor expression (positive versus negative), and then according to breast cancer subtype [luminal A-like versus luminal B-like versus triple-negative versus human epidermal growth factor receptor 2 (HER2)-positive breast cancer].

RESULTS

From 78 centers worldwide, 4709 BRCA carriers were included, of whom 2143 (45.5%) had hormone receptor-positive and 2566 (54.5%) hormone receptor-negative breast cancer. Median follow-up was 7.9 years. The rate of distant recurrences was higher in patients with hormone receptor-positive disease (13.1% versus 9.6%, P < 0.001), while the rate of second primary breast cancer was lower (9.1% versus 14.7%, P < 0.001) compared to patients with hormone receptor-negative disease. The 8-year DFS was 65.8% and 63.4% in patients with hormone receptor-positive and negative disease, respectively. The hazard ratio of hormone receptor-positive versus negative disease changed over time for DFS, BCSS, and OS (P < 0.05 for interaction of hormone receptor status and survival time). Patients with luminal A-like breast cancer had the worst long-term prognosis in terms of DFS compared to all the other subgroups (8-year DFS: 60.8% in luminal A-like versus 63.5% in triple-negative versus 65.5% in HER2-positive and 69.7% in luminal B-like subtype).

CONCLUSIONS

In young BRCA carriers, differences in recurrence pattern and second primary breast cancer among hormone receptor-positive versus negative disease warrant consideration in counseling patients on treatment, follow-up, and risk-reducing surgery.

Deep Learning-Based Facial and Skeletal Transformations for Surgical Planning

The increasing application of virtual surgical planning (VSP) in orthognathic surgery implies a critical need for accurate prediction of facial and skeletal shapes. The craniofacial relationship in patients with dentofacial deformities is still not understood, and transformations between facial and skeletal shapes remain a challenging task due to intricate anatomical structures and nonlinear relationships between the facial soft tissue and bones. In this study, a novel bidirectional 3-dimensional (3D) deep learning framework, named P2P-ConvGC, was developed and validated based on a large-scale data set for accurate subject-specific transformations between facial and skeletal shapes. Specifically, the 2-stage point-sampling strategy was used to generate multiple nonoverlapping point subsets to represent high-resolution facial and skeletal shapes. Facial and skeletal point subsets were separately input into the prediction system to predict the corresponding skeletal and facial point subsets via the skeletal prediction subnetwork and facial prediction subnetwork. For quantitative evaluation, the accuracy was calculated with shape errors and landmark errors between the predicted skeleton or face with corresponding ground truths. The shape error was calculated by comparing the predicted point sets with the ground truths, with P2P-ConvGC outperforming existing state-of-the-art algorithms including P2P-Net, P2P-ASNL, and P2P-Conv. The total landmark errors (Euclidean distances of craniomaxillofacial landmarks) of P2P-ConvGC in the upper skull, mandible, and facial soft tissues were 1.964 ± 0.904 mm, 2.398 ± 1.174 mm, and 2.226 ± 0.774 mm, respectively. Furthermore, the clinical feasibility of the bidirectional model was validated using a clinical cohort. The result demonstrated its prediction ability with average surface deviation errors of 0.895 ± 0.175 mm for facial prediction and 0.906 ± 0.082 mm for skeletal prediction. To conclude, our proposed model achieved good performance on the subject-specific prediction of facial and skeletal shapes and showed clinical application potential in postoperative facial prediction and VSP for orthognathic surgery.

Association of Diagnostic Discrepancy with Length of Stay and Mortality in Congestive Heart Failure Patients Admitted to the Emergency Department

The goal of this study was to analyze diagnostic discrepancies between emergency department (ED) and hospital discharge diagnoses in patients with congestive heart failure admitted to the ED. Using a synthetic dataset from the Department of Veterans Affairs, the patients' primary diagnoses were compared at two levels: diagnostic category and body system. With 12,621 patients and 24,235 admission cases, the study found a 58% mismatch rate at the category level, which was reduced to 30% at the body system level. Diagnostic categories associated with higher levels of mismatch included aplastic anemia, pneumonia, and bacterial infections. In contrast, diagnostic categories associated with lower levels of mismatch included alcohol-related disorders, COVID-19, cardiac dysrhythmias, and gastrointestinal hemorrhage. Further investigation revealed that diagnostic mismatches are associated with longer hospital stays and higher mortality rates. These findings highlight the importance of reducing diagnostic uncertainty, particularly in specific diagnostic categories and body systems, to improve patient care following ED admission.

Individual connectivity-based parcellations reflect functional properties of human auditory cortex

Neuroimaging studies of the functional organization of human auditory cortex have focused on group-level analyses to identify tendencies that represent the typical brain. Here, we mapped auditory areas of the human superior temporal cortex (STC) in 30 participants by combining functional network analysis and 1-mm isotropic resolution 7T functional magnetic resonance imaging (fMRI). Two resting-state fMRI sessions, and one or two auditory and audiovisual speech localizer sessions, were collected on 3-4 separate days. We generated a set of functional network-based parcellations from these data. Solutions with 4, 6, and 11 networks were selected for closer examination based on local maxima of Dice and Silhouette values. The resulting parcellation of auditory cortices showed high intraindividual reproducibility both between resting state sessions (Dice coefficient: 69-78%) and between resting state and task sessions (Dice coefficient: 62-73%). This demonstrates that auditory areas in STC can be reliably segmented into functional subareas. The interindividual variability was significantly larger than intraindividual variability (Dice coefficient: 57%-68%, p<0.001), indicating that the parcellations also captured meaningful interindividual variability. The individual-specific parcellations yielded the highest alignment with task response topographies, suggesting that individual variability in parcellations reflects individual variability in auditory function. Connectional homogeneity within networks was also highest for the individual-specific parcellations. Furthermore, the similarity in the functional parcellations was not explainable by the similarity of macroanatomical properties of auditory cortex. Our findings suggest that individual-level parcellations capture meaningful idiosyncrasies in auditory cortex organization.

[Clinical observation on the treatment of ossification of the posterior longitudinal ligament of the cervical spine using 3D printed self-stable zero-profile artificial vertebral body]

Objective: To observe the clinical efficacy of a 3D printed self-stable zero-profile artificial vertebral body for anterior cervical corpectomy decompression and fusion in the treatment of ossification of the posterior longitudinal ligament (OPLL) of the cervical spine. Methods: In this prospective randomized controlled trial, patients diagnosed with OPLL in Luohe Central Hospital from January to July 2022 were divided into a zero-profile group (3D printed self-stable zero-profile artificial vertebral body was used for internal fixation and fusion after anterior cervical subtotal decompression,) and titanium-mesh group (titanium-mesh and titanium plate were used for internal fixation and fusion after anterior cervical subtotal decompression) according to envelope random method. Operation time, intraoperative blood loss, Japanese Orthopaedic Association (JOA) score and improvement rate, incidence of postoperative prosthesis subsidence, and bone graft fusion were recorded and compared between the two groups. Results: Finally, 21 patients in the zero notch group and 20 patients in the titanium mesh group were included in the study and were followed-up. In the zero-profile group, there were 16 males and 5 females, aged (48.0±12.7) years. In the titanium-mesh group, there were 14 males and 6 females, aged (49.8±10.2) years. All the 41 patients successfully completed the operation. In the zero-profile group, the surgical time was (50.04±8.45) minutes, the blood loss was (95.38±26.07) ml and the hospitalization cost was (42.32±6.12) thousand yuan. In the titanium-mesh group, the surgical time was (59.20±11.95) minutes, the blood loss was (93.10±27.86) ml and the hospitalization cost was (42.10±6.71) thousand yuan. The surgical time in the zero-profile group was shorter than that in the titanium-mesh group (P=0.007), and there was no statistically significant difference in blood loss and hospitalization costs between the two groups (both P>0.05). The 41 patients were followed-up for (14.29±1.45) months. Four cases (20.0%) in the titanium mesh group experienced swallowing difficulties and 0 cases in the zero incision group, the difference between the two groups was statistically significant (P=0.048). No intraoperative hematoma, spinal cord nerve recompression, airway crisis, incision infection complications, and no steel plate or screw breakage or displacement occurred after surgery. At the last follow-up, all cases had bone fusion. At the follow-up of 12 months after surgery, the JOA score of the zero incision group increased from preoperative (10.33±1.71) points to (15.47±0.81) points, with an improvement rate of 76.1%±15.7%; the JOA score of the titanium mesh group increased from (10.30±1.75) points to (15.30±0.92) points, with an improvement rate of 73.2%±16.7%; there was no statistically significant difference in improvement rate between the two groups (P=0.580). At the follow-up of 12 months after surgery, 1 case (4.8%) in the zero incision group and 8 cases (40.0%) in the titanium mesh group experienced implant sinking, and the difference between the two groups was statistically significant (P=0.009). Conclusion: Compared with titanium-mesh, 3D printed self-stable zero-profile artificial vertebral body for the treatment of OPLL of the cervical spine can achieve good surgical efficacy, shorter surgical time, lower incidence of postoperative chronic swallowing discomfort, and can provide a better bone material bonding interface and be less prone to prosthesis settlement.

Identifying Determinants of Survival Disparities in Multiple Myeloma Patients Using Electronic Health Record Data

Multiple myeloma (MM) is one of the most common hematological malignancies. The goal of this study was to analyze the sociodemographic, economic, and genetic characteristics of long-term and short-term survival of multiple myeloma patients using EHR data from an academic medical center in New York City. The de-identified analytical dataset comprised 2,111 patients with MM who were stratified based on the length of survival into two groups. Demographic variables, cancer stage, income level, and genetic mutations were analyzed using descriptive statistics and logistic regression. Age, race, and cancer stage were all significant factors that affected the length of survival of multiple myeloma patients. In contrast, gender and income level were not significant factors based on the multivariate adjusted analysis. Older adults, African American patients, and patients who were diagnosed with stage III of multiple myeloma were the people most likely to exhibit short-term survival after the MM diagnosis.

Machine Learning Approaches for Exercise Exertion Level Classification Using Data from Wearable Physiologic Monitors

This research aimed to develop a model for real-time prediction of aerobic exercise exertion levels. ECG signals were registered during 16-minute cycling exercises. Perceived ratings of exertion (RPE) were collected each minute from the study participants. Based on the reported RPE, each consecutive minute of the exercise was assigned to the "high exertion" or "low exertion" class. The characteristics of heart rate variability (HRV) in time and frequency domains were used as predictive features. The top ten ranked predictive features were selected using the minimum redundancy maximum relevance (mRMR) algorithm. The support vector machine demonstrated the highest accuracy with an F1 score of 82%.

[Efficacy and safety of chimeric antigen receptor T-cell therapy followed by allogeneic hematopoietic stem cell transplantation in 21 patients with Ph-like acute lymphoblastic leukemia]

Objective: To evaluate the efficacy and safety of chimeric antigen receptor T-cell (CAR-T) therapy followed by allogeneic hematopoietic stem cell transplantation (allo-HSCT) in patients with Ph-like acute lymphoblastic leukemia (Ph-ALL) . Methods: Patients with Ph-ALL who underwent CAR-T therapy followed by allo-HSCT from March 2018 to August 2023 at the First Affiliated Hospital of Soochow University were included, and their clinical data were retrospectively analyzed. Results: Of the 21 patients, 14 were male and 7 were female. The median age at the time of CAR-T therapy was 22 (6-50) years. Seven patients had ABL1-like rearrangements, and 14 had JAK-STAT rearrangements. Prior to CAR-T therapy, 12 patients experienced hematologic relapse; 7 were multiparameter flow cytometry minimal residual disease (MFC-MRD) -positive and 2 were MFC-MRD-negative. CAR-T cells were derived from patients' autologous lymphocytes. Nine patients were treated with CD19 CAR-T cells, and 12 were treated with CD19/CD22 CAR-T cells. After assessment on day 28 after CAR-T therapy, 95.2% of the patients achieved complete remission, with an MRD-negative remission rate of 75%. Nineteen patients developed grade 0-2 cytokine release syndrome (CRS) and 2 patients suffered grade 3 CRS, all cases of which resolved after treatment. All patients underwent allo-HSCT after CAR-T therapy. The median time from CAR-T therapy to allo-HSCT was 63 (38-114) days. Five patients experienced relapse after CAR-T therapy, including four with hematologic relapse and one with molecular relapse. The 3-year overall survival (OS) rates in the ABL1 and JAK-STAT groups were (83.3±15.2) % and (66.6±17.2) %, respectively (P=0.68) . The 3-year relapse-free survival (RFS) rates were (50.0±20.4) % and (55.6±15.4) % in the ABL1 and JAK-STAT groups, respectively. There was no significant difference in 3-year OS or RFS between the two groups. Conclusions: CAR-T therapy followed by allo-HSCT leads to rapid remission in most patients with Ph-ALL and prolongs leukemia-free survival.

Exercise Exertion Level Prediction Using Data from Wearable Physiologic Monitors

This study aims to develop machine learning (ML) algorithms to predict exercise exertion levels using physiological parameters collected from wearable devices. Real-time ECG, oxygen saturation, pulse rate, and revolutions per minute (RPM) data were collected at three intensity levels during a 16-minute cycling exercise. Parallel to this, throughout each exercise session, the study subjects' ratings of perceived exertion (RPE) were gathered once per minute. Each 16-minute exercise session was divided into a total of eight 2-minute windows. Each exercise window was labeled as "high exertion," or "low exertion" classes based on the self-reported RPEs. For each window, the gathered ECG data were used to derive the heart rate variability (HRV) features in the temporal and frequency domains. Additionally, each window's averaged RPMs, heart rate, and oxygen saturation levels were calculated to form all the predictive features. The minimum redundancy maximum relevance algorithm was used to choose the best predictive features. Top selected features were then used to assess the accuracy of ten ML classifiers to predict the next window's exertion level. The k-nearest neighbors (KNN) model showed the highest accuracy of 85.7% and the highest F1 score of 83%. An ensemble model showed the highest area under the curve (AUC) of 0.92. The suggested method can be used to automatically track perceived exercise exertion in real-time.

Quality of reporting of integrative Chinese and Western medicine intervention in randomized controlled trials of ulcerative colitis: a review

BACKGROUND

Integrative Chinese and Western medicine (ICWM) is commonly used for the treatment of ulcerative colitis (UC) in clinical practice. However, it is unclear whether the details of ICWM interventions, such as selection rationale, implementation design, and potential interactions, were adequately reported. Therefore, this study aimed to assess the quality of reporting in the ICWM interventional randomized controlled trials (RCTs) of UC and to identify the common problems if any.

METHODS

Through a search of 10 international electronic databases, we identified RCTs of UC with ICWM interventions published in English or Chinese from the inception date of each database up to 16 June 2023. Literature screening was strictly conducted based on the inclusion and exclusion criteria of the Population, Concept, and Context (PCC) framework. The general characteristics of the included studies were described. The quality of reporting was assessed according to three checklists, including the CONSORT (Consolidated Standards of Reporting Trials) with 36 items (except for one item 1b about abstract), the CONSORT for Abstracts (17 items), and a self-designed ICWM-related checklist (27 items covering design rationale, intervention details, outcome assessments, and analysis). The reporting scores of RCTs published before and after 2010 were compared.

RESULTS

A total of 1458 eligible RCTs were included. For the reporting compliance, the median score (interquartile ranges) of the CONSORT (72 score in total), the CONSORT for Abstract (34 score), and ICWM-related (54 score) items was 21 (18-25), 13 (12-15), and 18 (15-21), respectively. Although the time period comparisons showed that reporting quality of included publications improved significantly after the CONSORT 2010 issued (P < 0.01), more than 50% of items were evaluated as poor quality (reporting rate < 65%) among each checklist, especially in the CONSORT for Abstract and ICWM-specific items.

CONCLUSION

Although CONSORT appears to have enhanced the reporting of RCTs in UC, the quality of ICWM specifics is variable and in need of improvement. Reporting guidelines of the ICWM recommendations should be developed to improve their quality.

Using Electronic Medical Records and Clinical Notes to Predict the Outcome of Opioid Treatment Program

Opioid addiction is a serious public health problem in the US, and this study aimed to explore how natural language processing (NLP) can be used to identify factors that contribute to distress in individuals with opioid addiction, and then use this information along with structured data to predict the outcome of opioid treatment programs (OTP). The study analyzed medical records data and clinical notes of 1,364 patients, out of which 136 succeeded in the program and 1,228 failed. The results showed that several factors influenced the success of patients in the program, including sex, race, education, employment, secondary substance, tobacco use, and type of residences. XGBoost with down sampling was the best model. The accuracy of the model was 0.71 and the AUC score was 0.64. The study highlights the importance of using both structured and unstructured data to evaluate the effectiveness of OTP.

Exercise Exertion Levels Prediction Based on Real-Time Wearable Physiological Signal Monitoring

The real-time revolutions per minute (RPM) data, ECG signal, pulse rate, and oxygen saturation levels were collected during 16-minute cycling exercises. In parallel, ratings of perceived exertion (RPE) were collected each minute from the study participants. A 2-minute moving window, with one minute shift, was applied to each 16-minute exercise session to divide it into a total of fifteen 2-minute windows. Based on the self-reported RPE, each exercise window was labeled as "high exertion" or "low exertion" classes. The heart rate variability (HRV) characteristics in time and frequency domains were extracted from the collected ECG signals for each window. In addition, collected oxygen saturation levels, pulse rate, and RPMs were averaged for each window. The best predictive features were then selected using the minimum redundancy maximum relevance (mRMR) algorithm. Top selected features were then used to assess the accuracy of five ML classifiers to predict the level of exertion. The Naïve Bayes model demonstrated the best performance with an accuracy of 80% and an F1 score of 79%.

[Structural changes of the frontal cortex in depressed mice are associated with decreased expression of brain-derived neurotrophic factor]

OBJECTIVE

To investigate the changes in gray matter volume in depressive-like mice and explore the possible mechanism.

METHODS

Twenty-four 6-week-old C57 mice were randomized equally into control group and model group, and the mice in the model group were subjected to chronic unpredictable mild stimulation (CUMS) for 35 days. Magnetic resonance imaging was performed to examine structural changes of the grey matter volume in depressive-like mice. The expression of brain-derived neurotrophic factor (BDNF) in the grey matter of the mice was detected using Western blotting and immunofluorescence staining.

RESULTS

Compared with the control mice, the mice with CUMS showed significantly decreased central walking distance in the open field test (P < 0.05) and increased immobile time in forced swimming test (P < 0.05). Magnetic resonance imaging showed that the volume of the frontal cortex was significantly decreased in CUMS mice (P < 0.001, when the mass level was greater than or equal to 10 756, the FDRc was corrected with P=0.05). Western blotting showed that the expression of mature BDNF in the frontal cortex was significantly decreased in CUMS mice (P < 0.05), and its expression began to decrease after the exposure to CUMS as shown by immunofluorescence staining. The volume of different clusters obtained by voxel-based morphometry (VBM) analysis was correlated with the expression level of mature BDNF detected by Western blotting (P < 0.05).

CONCLUSION

The decrease of frontal cortex volume after CUMS is related with the reduction of mature BDNF expression in the frontal cortex.

[Advances in clinical application of electrical impedance tomography to evaluate pulmonary perfusion in critically ill patients]

Lung perfusion monitoring can provide accurate information on changes in pulmonary blood flow in critically ill patients, and thus help guide clinical diagnosis and treatment. However, due to inconveniences such as patient transport, conventional imaging techniques are unable to meet the demand for real-time monitoring of lung perfusion, more convenient and reliable real-time functional imaging techniques should be developed to optimise cardiopulmonary management in critically ill patients. Electrical impedance tomography (EIT) is a non-invasive, radiation-free, bedside functional imaging technique that can be used to assess lung perfusion in patients with acute respiratory distress syndrome, pulmonary embolisms and other conditions, thereby assisting with the diagnosis of disease, the adjustment of treatment protocols, and the assessment of treatment outcomes. In this review, we focused on advances in EIT for lung perfusion monitoring in critically ill patients.

Automated Classification of Exercise Exertion Levels Based on Real-Time Wearable Physiological Signal Monitoring

This study aimed to build machine learning (ML) algorithms for the automated classification of cycling exercise exertion levels using data from wearable devices. The best predictive features were selected using the minimum redundancy maximum relevance algorithm (mRMR). Top selected features were then used to build and assess the accuracy of five ML classifiers to predict the level of exertion. The Naïve Bayes showed the best F1 score of 79%. The proposed approach may be used for real-time monitoring of exercise exertion.

[Analysis of the status of excess heart age and its risk factors among residents aged 35 to 64 years in China]

Objective: To analyze the status of excess heart age and its risk factors among Chinese residents aged 35 to 64 years. Methods: The study subjects were Chinese residents aged 35 to 64 years who completed the heart age assessment by WeChat official account"Heart Strengthening Action"through the internet from January 2018 to April 2021. Information such as age, gender, body mass index (BMI), blood pressure, total cholesterol (TC), smoking history, and diabetes history was collected. The heart age and excess heart age were calculated according to the characteristics of individual cardiovascular risk factors and the heart aging was defined as excess heart age≥5 years and 10 years respectively. The heart age and standardization rate were calculated respectively based on the population standardization of the 7th census in 2021.CA trend test was used to analyze the changing trend of excess heart age rate and population attributable risk (PAR) was used to calculate the contribution of risk factors. Results: The mean age of 429 047 subjects was 49.25±8.66 years. The male accounted for 51.17% (219 558/429 047) and the excess heart age was 7.00 (0.00, 11.00) years. The excess heart age rate defined by excess heart age≥5 years and≥10 years was 57.02% (the standardized rate was 56.83%) and 38.02% (the standardized rate was 37.88%) respectively. With the increase of the age and number of risk factors, the excess heart age rate of the two definitions showed an upward trend according to the result of the trend test analysis (P<0.001). The top two risk factors of the PAR for excess heart age were overweight or obese and smoking. Among them, the male was smoking and overweight or obese, while the female was overweight or obese and having hypercholesterolemia. Conclusion: The excess heart age rate is high in Chinese residents aged 35 to 64 years and the contribution of overweight or obese, smoking and having hypercholesterolemia ranks high.

Mechanism of Qingre Huoxue Fang treatment on inhibiting angiogenesis of rheumatoid arthritis based on network pharmacology and in vitro experiments

This study aimed to explore the mechanism of Qingre Huoxue Fang (QRHXF) treatment on anti-angiogenesis in rheumatoid arthritis (RA) based on network pharmacology and in vitro experiments. We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Therapeutic Target (TTD) database to extract the active components of QRHXF and potential targets for regulating angiogenesis. First, we used Cytoscape bioinformatics software to construct the network of QRHXF-angiogenesis and screened the potential targets. Then, we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the potential core targets. In addition, enzyme-linked immune assay and Western blot were used for in vitro validation and to verify the effects of different concentrations of QRHXF on the expression levels of the vascular endothelial growth factor receptor type 1 (VEGFR-1) and VEGFR-2 cytokines and phosphoinositide 3-kinase (PI3k) and Ak strain transforming (Akt) proteins in human umbilical vein endothelial cells (HUVECs). In results, we screened 179 core QRHXF antiangiogenic targets, including vascular endothelial growth factor (VEGF) cytokines. Enrichment analysis showed that the targets were enriched in 56 core signaling pathways, including PI3k and Akt. In vitro experiments showed that the migration distance and square, adhesion optical density (OD) values, and the number of branch points in tube formation significantly decreased in the QRHXF group compared with the induced group (P<0.01). Notably, the serum levels of VEGFR-1 and VEGFR-2 were lower compared with the induced group (P<0.05 or P<0.01). In addition, the expressions of PI3K and p-Akt proteins were decreased in the middle- and high doses groups (P<0.01). This study's results suggest that the downstream mechanism of QRHXF anti-angiogenesis might inhibit the PI3K-Akt signalling pathway and downregulate VEGF-1 and VEGF-2.

Mechanism of Qingre Huoxue Fang treatment on inhibiting angiogenesis of rheumatoid arthritis based on network pharmacology and in vitro experiments

This study aimed to explore the mechanism of Qingre Huoxue Fang (QRHXF) treatment on anti-angiogenesis in rheumatoid arthritis (RA) based on network pharmacology and in vitro experiments. We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Therapeutic Target (TTD) database to extract the active components of QRHXF and potential targets for regulating angiogenesis. First, we used Cytoscape bioinformatics software to construct the network of QRHXF-angiogenesis and screened the potential targets. Then, we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the potential core targets. In addition, enzyme-linked immune assay and Western blot were used for in vitro validation and to verify the effects of different concentrations of QRHXF on the expression levels of the vascular endothelial growth factor receptor type 1 (VEGFR-1) and VEGFR-2 cytokines and phosphoinositide 3-kinase (PI3k) and Ak strain transforming (Akt) proteins in human umbilical vein endothelial cells (HUVECs). In results, we screened 179 core QRHXF antiangiogenic targets, including vascular endothelial growth factor (VEGF) cytokines. Enrichment analysis showed that the targets were enriched in 56 core signaling pathways, including PI3k and Akt. In vitro experiments showed that the migration distance and square, adhesion optical density (OD) values, and the number of branch points in tube formation significantly decreased in the QRHXF group compared with the induced group (P<0.01). Notably, the serum levels of VEGFR-1 and VEGFR-2 were lower compared with the induced group (P<0.05 or P<0.01). In addition, the expressions of PI3K and p-Akt proteins were decreased in the middle- and high doses groups (P<0.01). This study's results suggest that the downstream mechanism of QRHXF anti-angiogenesis might inhibit the PI3K-Akt signalling pathway and downregulate VEGF-1 and VEGF-2.

Development and Evaluation of Wireless Interfaces to Monitor and Control Cycling Exercise During Home Telerehabilitation

Purpose

This paper focuses on developing and testing three versions of interactive bike (iBikE) interfaces for remote monitoring and control of cycling exercise sessions to promote upper and lower limb rehabilitation.

Methods

Two versions of the system, which consisted of a portable bike and a tablet PC, were designed to communicate through either Bluetooth low energy (BLE) or Wi-Fi interfaces for real-time monitoring of exercise progress by both the users and their clinical team. The third version of the iBikE system consisted of a motorized bike and a tablet PC. It utilized conventional Bluetooth to implement remote control of the motorized bike's speed during an exercise session as well as to provide real-time visualization of the exercise progress. We developed three customized tablet PC apps with similar user interfaces but different communication protocols for all the platforms to provide a graphical representation of exercise progress. The same microcontroller unit (MCU), ESP-32, was used in all the systems.

Results

Each system was tested in 1-minute exercise sessions at various speeds. To evaluate the accuracy of the measured data, in addition to reading speed values from the iBikE app, the cycling speed of the bikes was measured continuously using a tachometer. The mean differences of averaged RPMs for both data sets were calculated. The calculated values were 0.38 ± 0.03, 0.25 ± 0.27, and 6.7 ± 3.3 for the BLE system, the Wi-Fi system, and the conventional Bluetooth system, respectively.

Conclusion

All interfaces provided sufficient accuracy for use in telerehabilitation.

Telemonitoring of Home-Based Biking Exercise: Assessment of Wireless Interfaces

BACKGROUND

Telerehabiliation has been shown to have great potential in expanding access to rehabilitation services, enhancing patients' quality of life, and improving clinical outcomes. Stationary biking exercise can serve as an effective aerobic component of home-based physical rehabilitation programs. Remote monitoring of biking exercise provides necessary safeguards to ensure exercise adherence and safety in patients' homes. The scalability of the current remote monitoring of biking exercise solutions is impeded by the high cost that limits patient access to these services, especially among older adults with chronic health conditions.

OBJECTIVE

The aim of this project was to design and test two low-cost wireless interfaces for the telemonitoring of home-based biking exercise.

METHODS

We designed an interactive biking system (iBikE) that comprises a tablet PC and a low-cost bike. Two wireless interfaces to monitor the revolutions per minute (RPM) were built and tested. The first version of the iBikE system uses Bluetooth Low Energy (BLE) to send information from the iBikE to the PC tablet, and the second version uses a Wi-Fi network for communication. Both systems provide patients and their clinical teams the capability to monitor exercise progress in real time using a simple graphical representation. The bike can be used for upper or lower limb rehabilitation. We developed two tablet applications with the same graphical user interfaces between the application and the bike sensors but with different communication protocols (BLE and Wi-Fi). For testing purposes, healthy adults were asked to use an arm bike for three separate subsessions (1 minute each at a slow, medium, and fast pace) with a 1-minute resting gap. While collecting speed values from the iBikE application, we used a tachometer to continuously measure the speed of the bikes during each subsession. Collected data were later used to assess the accuracy of the measured data from the iBikE system.

RESULTS

Collected RPM data in each subsession (slow, medium, and fast) from the iBikE and tachometer were further divided into 4 categories, including RPM in every 10-second bin (6 bins), RPM in every 20-second bin (3 bins), RPM in every 30-second bin (2 bins), and RPM in each 1-minute subsession (60 seconds, 1 bin). For each bin, the mean difference (iBikE and tachometer) was then calculated and averaged for all bins in each subsession. We saw a decreasing trend in the mean RPM difference from the 10-second to the 1-minute measurement. For the 10-second measurements during the slow and fast cycling, the mean discrepancy between the wireless interface and tachometer was 0.67 (SD 0.24) and 1.22 (SD 0.67) for the BLE iBike, and 0.66 (SD 0.48) and 0.87 (SD 0.91) for the Wi-Fi iBike system, respectively. For the 1-minute measurements during the slow and fast cycling, the mean discrepancy between the wireless interface and tachometer was 0.32 (SD 0.26) and 0.66 (SD 0.83) for the BLE iBike, and 0.21 (SD 0.21) and 0.47 (SD 0.52) for the Wi-Fi iBike system, respectively.

CONCLUSIONS

We concluded that a low-cost wireless interface provides the necessary accuracy for the telemonitoring of home-based biking exercise.