Segmentation of Knee Bones for Osteoarthritis Assessment: A Comparative Analysis of Supervised, Few-Shot, and Zero-Shot Learning Approaches

Knee osteoarthritis is a degenerative joint disease that induces chronic pain and disability. Bone morphological analysis is a promising tool to understand the mechanical aspect of this disorder. This study proposes a 2D bone morphological analysis using manually segmented bones to explore morphological features related to distinct pain conditions. Furthermore, six semantic segmentation algorithms are assessed for extracting femur and tibia bones from X-ray images. Our analysis reveals that the morphology of the femur undergoes significant changes in instances where pain worsens. Conversely, improvements in pain may not manifest pronounced alterations in bone shape. The few-shot-learning-based algorithm, UniverSeg, demonstrated superior segmentation results with Dice scores of 99.69% for femur and 99.60% for tibia. Regarding pain condition classification, the zero-shot-learning-based algorithm, CP-SAM, achieved the highest accuracy at 66% among all models. UniverSeg is recommended for automatic knee bone segmentation, while SAM models show potential with prompt encoder modifications for optimized outcomes. These findings highlight the effectiveness of few-shot learning for semantic segmentation and the potential of zero-shot learning in enhancing classification models for knee osteoarthritis diagnosis

Transfer learning-assisted 3D deep learning models for knee osteoarthritis detection: Data from the osteoarthritis initiative

Knee osteoarthritis is one of the most common musculoskeletal diseases and is usually diagnosed with medical imaging techniques. Conventionally, case identification using plain radiography is practiced. However, we acknowledge that knee osteoarthritis is a 3D complexity; hence, magnetic resonance imaging will be the ideal modality to reveal the hidden osteoarthritis features from a three-dimensional view. In this work, the feasibility of well-known convolutional neural network (CNN) structures (ResNet, DenseNet, VGG, and AlexNet) to distinguish knees with and without osteoarthritis (OA) is investigated. Using 3D convolutional layers, we demonstrated the potential of 3D convolutional neural networks of 13 different architectures in knee osteoarthritis diagnosis. We used transfer learning by transforming 2D pre-trained weights into 3D as initial weights for the training of the 3D models. The performance of the models was compared and evaluated based on the performance metrics [balanced accuracy, precision, F1 score, and area under receiver operating characteristic (AUC) curve]. This study suggested that transfer learning indeed enhanced the performance of the models, especially for ResNet and DenseNet models. Transfer learning-based models presented promising results, with ResNet34 achieving the best overall accuracy of 0.875 and an F1 score of 0.871. The results also showed that shallow networks yielded better performance than deeper neural networks, demonstrated by ResNet18, DenseNet121, and VGG11 with AUC values of 0.945, 0.914, and 0.928, respectively. This encourages the application of clinical diagnostic aid for knee osteoarthritis using 3DCNN even in limited hardware conditions

Feasibility of an interprofessional collaborative osteoporosis screening programme in Malaysia

Background Population screening for osteoporosis using bone mineral density scan is not feasible in Malaysia as this test is costly. Hence, there is a need to develop a more efficient method to screen for osteoporosis.Objectives To determine the feasibility of an interprofessional collaborative osteoporosis screening programme (IPC-OSP). Methods Postmenopausal women aged ≥ 50 years, who had not been diagnosed with osteoporosis were recruited from a primary care clinic from June to August 2014. Patients were assessed for their osteoporosis risk and were counselled on prevention methods. Patients at risk were referred to the doctor with a recommendation for a bone mineral density (BMD) scan. Results Fifty out of 55 patients were recruited (response rate = 90.9%). A total 26/50 (52.0%) went for a bone mineral density scan, none were osteoporotic, 17/50 (34%) were osteopenic, 2/50 (4.0%), were started on osteoporosis medications and 14/50 (28%) modified their lifestyle to improve bone health or started on calcium supplements. Osteoporosis knowledge significantly increased from baseline to month two (46.3 ± 21.4 vs. 79.1 ± 14.3, p < 0.001). Patients had a satisfaction score of 89.8 ± 12.4. Follow-up rates were 83.9% and 100% at months 1 (BMD appointment) and 2 (phone follow up), respectively. The intervention was successfully coordinated. Data entry was determined to be viable based on the researchers’ experience. Conclusion The interprofessional collaborative osteoporosis screening programme was found to be feasible in Malaysia. © 2020, Springer Nature Switzerland AG

Multiplatform genome-wide identification and modeling of functional human estrogen receptor binding sites

BACKGROUND: Transcription factor binding sites (TFBS) impart specificity to cellular transcriptional responses and have largely been defined by consensus motifs derived from a handful of validated sites. The low specificity of the computational predictions of TFBSs has been attributed to ubiquity of the motifs and the relaxed sequence requirements for binding. We posited that the inadequacy is due to limited input of empirically verified sites, and demonstrated a multiplatform approach to constructing a robust model. RESULTS: Using the TFBS for the estrogen receptor (ER)α (estrogen response element [ERE]) as a model system, we extracted EREs from multiple molecular and genomic platforms whose binding to ERα has been experimentally confirmed or rejected. In silico analyses revealed significant sequence information flanking the standard binding consensus, discriminating ERE-like sequences that bind ERα from those that are nonbinders. We extended the ERE consensus by three bases, bearing a terminal G at the third position 3' and an initiator C at the third position 5', which were further validated using surface plasmon resonance spectroscopy. Our functional human ERE prediction algorithm (h-ERE) outperformed existing predictive algorithms and produced fewer than 5% false negatives upon experimental validation. CONCLUSION: Building upon a larger experimentally validated ERE set, the h-ERE algorithm is able to demarcate better the universe of ERE-like sequences that are potential ER binders. Only 14% of the predicted optimal binding sites were utilized under the experimental conditions employed, pointing to other selective criteria not related to EREs. Other factors, in addition to primary nucleotide sequence, will ultimately determine binding site selection

Peripheral proinsulin expression controls low-avidity proinsulin-reactive CD8 T Cells in type 1 diabetes

Low-avidity autoreactive CD8 T cells (CTLs) escape from thymic negative selection, and peripheral tolerance mechanisms are essential for their regulation. We report the role of proinsulin (PI) expression on the development and activation of insulin-specific CTLs in the NOD mouse model of type 1 diabetes. We studied insulin B-chain–specific CTL from different T-cell receptor transgenic mice (G9Cα−/−) expressing normal PI1 and PI2 or altered PI expression levels. In the absence of PI2 (Ins2−/−), CTL in pancreatic lymph nodes (PLNs) were more activated, and male G9Cα−/− mice developed T1D. Furthermore, when the insulin-specific CTLs developed in transgenic mice lacking their specific PI epitope, the CTLs demonstrated increased cytotoxicity and proliferation in vitro and in vivo in the PLNs after adoptive transfer into NOD recipients. Dendritic cell–stimulated proliferation of insulin-specific T cells was reduced in the presence of lymph node stromal cells (LNSCs) from NOD mice but not from mice lacking the PI epitope. Our study shows that LNSCs regulate CTL activation and suggests that exposure to PI in the periphery is very important in maintenance of tolerance of autoreactive T cells. This is relevant for human type 1 diabetes and has implications for the use of antigen-specific therapy in tolerance induction

Medical Students’ Attitudes toward Abortion Education: Malaysian Perspective

Abortion is a serious public health issue, and it poses high risks to the health and life of women. Yet safe abortion services are not readily available because few doctors are trained to provide such services. Many doctors are unaware of laws pertaining to abortion. This article reports survey findings on Malaysian medical students’ attitudes toward abortion education and presents a case for including abortion education in medical schools. Methods and Results A survey on knowledge of and attitudes toward abortion among medical students was conducted in two public universities and a private university in Malaysia in 2011. A total of 1,060 students returned the completed questionnaires. The survey covered about 90% of medical students in Years 1, 3, and 5 in the three universities. About 90% of the students wanted more training on the general knowledge and legal aspects of abortion, and pre-and post-abortion counseling. Overall, 75.9% and 81.0% of the students were in favor of including in medical education the training on surgical abortion techniques and medical abortion, respectively. Only 2.4% and 1.7% were opposed to the inclusion of training of these two methods in the curriculum. The remaining respondents were neutral in their stand. Desire for more abortion education was associated with students’ pro-choice index, their intention to provide abortion services in future practice, and year of study. However, students’ attitudes toward abortion were not significantly associated with gender, type of university, or ethnicity. Conclusions Most students wanted more training on abortion. Some students also expressed their intention to provide abortion counseling and services in their future practice. Their desire for more training on abortion should be taken into account in the new curriculum. Abortion education is an important step towards making available safe abortion services to enable women to exercise their reproductive rights

The development and validation of the Satisfaction Questionnaire for Osteoporosis Prevention in Malaysia

Purpose: To develop and validate the English version of the Satisfaction Questionnaire for Osteoporosis Prevention (SQOP) in Malaysia.Methods: The SQOP was modified from the Osteoporosis Patient Satisfaction Questionnaire and developed based on literature review and patient interviews. Face and content validity were established via an expert panel. The SQOP consists of two sections: clinical services and types of counseling. There were 23 items in total, each with a five-point Likert-type response. Satisfaction score was calculated by converting the total score to a percentage. A higher score indicates higher satisfaction. English speaking, non-osteoporotic, postmenopausal women aged ≥50 years were included in the study. Participants were randomized to either the control or intervention group. Intervention participants were provided counseling, whereas control participants received none. Participants answered the SQOP at baseline and 2 weeks later.Results: A total of 140 participants were recruited (control group: n=70; intervention group: n=70). No significant differences were found in any demographic aspects. Exploratory factor analysis extracted seven domains. Cronbach’s a for the domains ranged from 0.531–0.812. All 23 items were highly correlated using Spearman’s correlation coefficient 0.469–0.996 (

A comparison of six osteoporosis risk assessment tools among postmenopausal women in Kuala Lumpur, Malaysia

ObjectivesTo compare and assess the performance of 6 osteoporosis risk assessment tools for screening osteoporosis in Malaysian postmenopausal women.MethodsSix osteoporosis risk assessments tools (the Simple Calculated Osteoporosis Risk Estimation [SCORE], the Osteoporosis Risk Assessment Instrument, the Age Bulk One or Never Estrogen, the body weight, the Malaysian Osteoporosis Screening Tool, and the Osteoporosis Self-Assessment Tool for Asians) were used to screen postmenopausal women who had not been previously diagnosed with osteoporosis/osteopenia. These women also underwent a dual-energy X-ray absorptiometry (DXA) scan to confirm the absence or presence of osteoporosis.ResultsA total of 164/224 participants were recruited (response rate, 73.2%), of which only 150/164 (91.5%) completed their DXA scan. Sixteen participants (10.7%) were found to have osteoporosis, whilst 65/150 (43.3%) were found to have osteopenia. Using precision-recall curves, the recall of the tools ranged from 0.50 to 1.00, whilst precision ranged from 0.04 to 0.14. The area under the curve (AUC) ranged from 0.027 to 0.161. The SCORE had the best balance between recall (1.00), precision (0.04–0.12), and AUC (0.072–0.161).ConclusionsWe found that the SCORE had the best balance between recall, precision, and AUC among the 6 screening tools that were compared among Malaysian postmenopausal women

In Vitro and In Vivo Anti-Angiogenic Activities of Panduratin A

Targeting angiogenesis has emerged as an attractive and promising strategy in anti-cancer therapeutic development. The present study investigates the anti-angiogenic potential of Panduratin A (PA), a natural chalcone isolated from Boesenbergia rotunda by using both in vitro and in vivo assays.PA exerted selective cytotoxicity on human umbilical vein endothelial cells (HUVECs) with IC(50) value of 6.91 ± 0.85 µM when compared to human normal fibroblast and normal liver epithelial cells. Assessment of the growth kinetics by cell impedance-based Real-Time Cell Analyzer showed that PA induced both cytotoxic and cytostatic effects on HUVECs, depending on the concentration used. Results also showed that PA suppressed VEGF-induced survival and proliferation of HUVECs. Furthermore, endothelial cell migration, invasion, and morphogenesis or tube formation demonstrated significant time- and dose-dependent inhibition by PA. PA also suppressed matrix metalloproteinase-2 (MMP-2) secretion and attenuated its activation to intermediate and active MMP-2. In addition, PA suppressed F-actin stress fiber formation to prevent migration of the endothelial cells. More importantly, anti-angiogenic potential of PA was also evidenced in two in vivo models. PA inhibited neo-vessels formation in murine Matrigel plugs, and angiogenesis in zebrafish embryos.Taken together, our study demonstrated the distinctive anti-angiogenic properties of PA, both in vitro and in vivo. This report thus reveals another biological activity of PA in addition to its reported anti-inflammatory and anti-cancer activities, suggestive of PA's potential for development as an anti-angiogenic agent for cancer therapy

RAB27A promotes melanoma cell invasion and metastasis via regulation of pro-invasive exosomes

Despite recent advances in targeted and immune-based therapies, advanced stage melanoma remains a clinical challenge with a poor prognosis. Understanding the genes and cellular processes that drive progression and metastasis is critical for identifying new therapeutic strategies. Here, we found that the GTPase RAB27A was overexpressed in a subset of melanomas, which correlated with poor patient survival. Loss of RAB27A expression in melanoma cell lines inhibited 3D spheroid invasion and cell motility in vitro, and spontaneous metastasis in vivo. The reduced invasion phenotype was rescued by RAB27A-replete exosomes, but not RAB27A-knockdown exosomes, indicating that RAB27A is responsible for the generation of pro-invasive exosomes. Furthermore, while RAB27A loss did not alter the number of exosomes secreted, it did change exosome size and altered the composition and abundance of exosomal proteins, some of which are known to regulate cancer cell movement. Our data suggest that RAB27A promotes the biogenesis of a distinct pro-invasive exosome population. These findings support RAB27A as a key cancer regulator, as well as a potential prognostic marker and therapeutic target in melanoma