Assessment of Automated Identification of Phases in Videos of Total Hip Arthroplasty Using Deep Learning Techniques.

Background: As the population ages, the rates of hip diseases and fragility fractures are increasing, making total hip arthroplasty (THA) one of the best methods for treating elderly patients. With the increasing number of THA surgeries and diverse surgical methods, there is a need for standard evaluation protocols. This study aimed to use deep learning algorithms to classify THA videos and evaluate the accuracy of the labelling of these videos. Methods: In our study, we manually annotated 7 phases in THA, including skin incision, broaching, exposure of acetabulum, acetabular reaming, acetabular cup positioning, femoral stem insertion, and skin closure. Within each phase, a second trained annotator marked the beginning and end of instrument usages, such as the skin blade, forceps, Bovie, suction device, suture material, retractor, rasp, femoral stem, acetabular reamer, head trial, and real head. Results: In our study, we utilized YOLOv3 to collect 540 operating images of THA procedures and create a scene annotation model. The results of our study showed relatively high accuracy in the clear classification of surgical techniques such as skin incision and closure, broaching, acetabular reaming, and femoral stem insertion, with a mean average precision (mAP) of 0.75 or higher. Most of the equipment showed good accuracy of mAP 0.7 or higher, except for the suction device, suture material, and retractor. Conclusions: Scene annotation for the instrument and phases in THA using deep learning techniques may provide potentially useful tools for subsequent documentation, assessment of skills, and feedback.

Analysis of Changes in Sleep Quality and Patterns after Hip Fracture Using Real Evidence of Artificial Intelligence Linked (REAL) Hip Cohort Data.

Background and Objectives: Hip fractures are commonly found in elderly patients, and often result in chronic pain and decreased physical function, as well as worsening of overall health. It is known that early surgical intervention during the acute phase and rehabilitation are important for improving clinical outcomes for these patients. However, the importance of management for improving the quality of life of these patients is becoming more emphasized. Studies on changes in sleep patterns after hip fractures are rare overseas. Therefore, the aim of this study is to investigate the prevalence of sleep disturbance in patients with hip fractures and to analyze the changes in sleep disturbance after surgery by comparing the preoperative and postoperative results. Materials and Methods: During the period from August 2022 to January 2023, patients who underwent surgical treatment for hip fractures and were recruited into the REAL Hip Cohort were selected as research subjects. The sleep survey was conducted using the Pittsburgh Sleep Quality Index (PSQI). The PSQI is composed of 18 questions, each divided into areas of sleep quality, sleep latency, duration, efficiency, disturbance, use of medication, and daytime dysfunction. Each area is scored 0-3 points and the total is 0-21. A score greater than five indicates sleep disorder. The PSQI was surveyed during hospitalization and three months after surgery for post-fracture sleep status. To analyze changes before and after the fracture, paired T-tests and chi-square tests were performed. Results: From August 2022 to January 2023, a total of 40 patients who were recruited into the REAL Hip Cohort responded to the PSQI survey. The average age was 77.4 years and 36 were female. Sleep quality worsened from 0.75 ± 1.0 before surgery to 1.4 ± 1.0 three months after surgery (p = 0.019), and sleep efficiency also worsened from 0.4 ± 0.6 to 1.4 ± 1.0 (p < 0.001). The PSQI increased from an average of 5.2 ± 2.8 before surgery to 8.2 ± 4.2 three months after surgery (p = 0.007), and the number of patients who could be diagnosed with sleep disorders also increased from 12 (40%) to 24 (60%) (p = 0.030). Conclusions: A decline in overall sleep status was observed in patients in a survey on sleep patterns three months after hip fracture. Additional management is needed to improve their sleep patterns.

Unraveling the maternal and paternal origins of allotetraploid Vigna reflexo-pilosa.

The genomic structures of Vigna hirtella Ridl. and Vigna trinervia (B.Heyne ex Wight & Arn.) Tateishi & Maxted, key ancestral species of the allotetraploid Vigna reflexo-pilosa var. glabra (Roxb.) N.Tomooka & Maxted, remain poorly understood. This study presents a comprehensive genomic comparison of these species to deepen our knowledge of their evolutionary trajectories. By comparing the genomic profiles of V. hirtella and V. trinervia with those of V. reflexo-pilosa, we investigate the complex genomic mechanisms underlying allopolyploid evolution within the genus Vigna. Comparison of the chloroplast genome revealed that V. trinervia is closely related to V. reflexo-pilosa. De novo assembly of the whole genome, followed by synteny analysis and Ks value calculations, confirms that V. trinervia is closely related to the A genome of V. reflexo-pilosa, and V. hirtella to its B genome. Furthermore, the comparative analyses reveal that V. reflexo-pilosa retains residual signatures of a previous polyploidization event, particularly evident in higher gene family copy numbers. Our research provides genomic evidence for polyploidization within the genus Vigna and identifies potential donor species of allotetraploid species using de novo assembly techniques. Given the Southeast Asian distribution of both V. hirtella and V. trinervia, natural hybridization between these species, with V. trinervia as the maternal ancestor and V. hirtella as the paternal donor, seems plausible.

Sophora genomes provide insight into the evolution of alkaloid metabolites along with small-scale gene duplication.

The genus Sophora (Fabaceae) includes medicinal plants that have been used in East Asian countries since antiquity. Sophora flavescens is a perennial herb indigenous to China, India, Japan, Korea, and Russia. Its dried roots have antioxidant, anti-inflammatory, antibacterial, apoptosis-modulating, and antitumor efficacy. The congeneric S. koreensis is endemic to Korea and its genome is less than half the size of that of S. flavescens. Nevertheless, this discrepancy can be used to assemble and validate the S. flavescens genome. A comparative genomic study of the two genomes can disclose the recent evolutionary divergence of the polymorphic phenotypic profiles of these species. Here, we used the PacBio sequencing platform to sequence and assemble the S. koreensis and S. flavescens genomes. We inferred that it was mainly small-scale duplication that occurred in S. flavescens. A KEGG analysis revealed pathways that might regulate the pharmacologically important secondary metabolites in S. flavescens and S. koreensis. The genome assemblies of Sophora spp. could be used in comparative genomics and data mining for various plant natural products.

Correlation between Harris hip score and gait analysis through artificial intelligence pose estimation in patients after total hip arthroplasty.

BACKGROUND: Recently, open pose estimation using artificial intelligence (AI) has enabled the analysis of time series of human movements through digital video inputs. Analyzing a person's actual movement as a digitized image would give objectivity in evaluating a person's physical function. In the present study, we investigated the relationship of AI camera-based open pose estimation with Harris Hip Score (HHS) developed for patient-reported outcome (PRO) of hip joint function. METHOD: HHS evaluation and pose estimation using AI camera were performed for a total of 56 patients after total hip arthroplasty in Gyeongsang National University Hospital. Joint angles and gait parameters were analyzed by extracting joint points from time-series data of the patient's movements. A total of 65 parameters were from raw data of the lower extremity. Principal component analysis (PCA) was used to find main parameters. K-means cluster, X-squared test, Random forest, and mean decrease Gini (MDG) graph were also applied. RESULTS: The train model showed 75% prediction accuracy and the test model showed 81.8% reality prediction accuracy in Random forest. "Anklerang_max", "kneeankle_diff", and "anklerang_rl" showed the top 3 Gini importance score in the Mean Decrease Gini (MDG) graph. CONCLUSION: The present study shows that pose estimation data using AI camera is related to HHS by presenting associated gait parameters. In addition, our results suggest that ankle angle associated parameters could be key factors of gait analysis in patients who undergo total hip arthroplasty.

Integrative analyses of genes related to femoral head osteonecrosis: an umbrella review of systematic reviews and meta-analyses of observational studies.

BACKGROUND: Femoral head osteonecrosis (FHON) is a worldwide challenging clinical topic. Steroid use is one of the main etiologies of FHON. There are several genetic variants associated with FHON. Therefore, the purpose of this umbrella review was to provide a comprehensive summary of a meta-analysis and systematic review of genetic variations associated with nonsteroidal and steroid-induced FHON. METHODS: The eligible studies were selected from the PubMed and MEDLINE databases for the collection of diverse systematic meta-analyses and reviews. The genetic main effect score was assigned using the Human Genome Epidemiology Network's Venice criteria to assess the cumulative evidence on the effects of a single nucleotide polymorphism (SNP) on FHON. RESULTS: Eight articles reported the meta-analysis of candidate SNP-based studies covering eight genes and 13 genetic variants. In the nonsteroid-induced FHON genetic variants including rs2012390 and rs11225394 in MMP8, rs1800629 and rs361525 in tumor necrosis factor (TNF)-α, VNTR in intron 4, rs1799983 and rs2070744 in endothelial nitric oxide synthase (eNOS), rs2010963 in vascular endothelial growth factor (VEGF), and rs6025 in factor V showed significance in each reference. The steroid-induced FHON genetic variants including rs693 and rs1042031 in apolipoprotein (Apo)B, rs1045642 in ABCB1, and rs1799889 in PAI-1 showed significance in each reference. CONCLUSION: Based on the systematic review conducted in this study, we organized the genomes associated with FHON and looked at each contribution. Our results could give an integrative approach for understanding the mechanism of FHON etiology. It is expected that these results could contribute to the strategy of prediagnosis, evaluating the individual risk of nonsteroid-induced and steroid-induced FHON. LEVEL OF EVIDENCE: Level I.

Differential gene expression profile by RNA sequencing study of elderly osteoporotic hip fracture patients with sarcopenia.

BACKGROUND: The purpose of this study was to report the RNA sequencing profile according to the presence or absence of sarcopenia in elderly patients with osteoporotic hip fracture. Therefore, an important genetic factor candidate for sarcopenia causing hip fracture in elderly with osteoporosis has been identified. METHODS: The patient group involved subjects over 65 years who had undergone hip fracture surgery. Among 323 hip fracture (HF) patients identified from May 2017 to December 2019, 162 HF patients (90 non-sarcopenia and 72 sarcopenia groups), excluding subjects with high energy trauma and non-osteoporosis, were finally included in the analysis. For RNA sequencing, each patient with hand grip strength (HGS) values in the top 10% were enrolled in the control group and with the bottom 10% in the patient group. After excluding patients with poor tissue quality, 6 patients and 5 patients were selected for sarcopenia and non-sarcopenia groups, respectively. For qPCR validation, each patient with HGS values in the top 20% and bottom 20% was enrolled in the control and patient groups, respectively. After excluding patients with poor tissue quality, 12 patients and 12 patients were enrolled in the sarcopenia and non-sarcopenia groups, respectively. Sarcopenia was defined according to the Asia Working Group for Sarcopenia (AWGS) criteria for low muscle strength (hand grip strength below 18 â€‹kg in women and 28 â€‹kg in men) and low muscle mass (SMI below 5.4 â€‹kg/m2 in women and 7.0 â€‹kg/m2 in men). The libraries were prepared for 100 bp paired-end sequencing using TruSeq Stranded mRNA Sample Preparation Kit (Illumina, CA, USA). The gene expression counts were supplied to Deseq2 to extract possible gene sets as differentially expressed genes (DEG) that discriminate between sarcopenia and non-sarcopenia groups that were carefully assigned by clinical observation. For the classification of the candidate genes from DEG analysis, we used the public databases; gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Quantitative real-time PCR was performed for validation. RESULTS: Samples collected were subjected to RNAseq using the Illumina platform. A total of 11 samples from both sarcopenia and non-sarcopenia groups were sequenced. Fifteen genes (RUNX 1, NGFR, CH3L1, BCL3, PLA2G2A, MYBPH, TEP1, SEMA6B, CSPG4, ACSL5, SLC25A3, NDUFB5, CYC1, ACAT1, and TCAP) were identified as differentially expressed genes (DEG) in both the groups.In the qPCR results, the expression levels of SLC25A3 and TCAP gene in the OS group were significantly lower than in the non-OS groups whereas an increase in RUNX1 mRNA level was observed in the OS samples (p â€‹< â€‹0.05). CONCLUSIONS: In summary, this study detected gene expression difference according to the presence or absence of sarcopenia in elderly osteoporosis female patients with hip fracture. We have also identified 15 important genes (RUNX 1, NGFR, CH3L1, BCL3, PLA2G2A, MYBPH, TEP1, SEMA6B, CSPG4, ACSL5, SLC25A3, NDUFB5, CYC1, ACAT1, TCAP), a few GO categories and biological pathways that may be associated with the osteosarcopenia. Our study may provide effective means for the prevention, diagnosis and treatment sarcopenia in elderly osteoporosis female patients. THE TRANSLATIONAL POTENTIAL OF THIS ARTICLE: These findings provide a novel insight into the effects of aging on the response in women with postmenopausal osteoporosis. Further studies are underway to identify the specific signalling pathways involved. These results reveal potential therapeutic targets that could aid the regenerative capacity of aging skeletal muscle.

Machine learning-based identification of hip arthroplasty designs.

BACKGROUND: The purposes of this study were to develop a machine learning-based implant recognition program and to verify its accuracy. METHODS: Postoperative anteroposterior (AP) X-rays (≥300 dpi) were collected of patients who underwent total hip arthroplasty. X-rays with a wire or plate added and those without a true anteroposterior view were excluded. A total of 170 X-ray images of hip implants from 29 brands were collected from five hospitals and a Google image search. These collected images were manually reorganised to ensure appropriate labelling. Collected images were preprocessed to have grey-scaled pixels with histogram equalisation for efficient training. Images varied by +10/-10°, and 3606 unique images derived from the original 170 images were created for training. Discussion of the validation set being derived 25% of training set. The recognition model structure consisted of two steps: object detection and clustering. Model training was performed with Keras deep learning platform. RESULTS: The 170 X-ray images of hip implants were used to build a stem detection model using YOLOv3. Manually labelled images were successfully trained into the stem detection model. Evaluation of 58 newly labelled X-ray images showed highly accurate stem detection (mean average precision > 0.99). Fully connected layers generated 29 class outputs. After training, a receiver operating characteristic curve was generated with a test set containing 25% of all stem-cropped images, yielding an area under the curve of 0.99. CONCLUSION: Femoral stem identification in patients with total hip arthroplasty was very accurate. This technology could be used to collect large-scale implant information. THE TRANSLATIONAL POTENTIAL OF THIS ARTICLE: This program has the following clinical relevance. First, we can prepare the implants needed for revision surgery by identifying the old types of implants. Second, it can be used to diagnose peripheral osteolysis or periprosthetic fracture by further developing the ability to sensitise implant detection. Third, an automated implant detection system will help organise imaging data systematically and easily for arthroplasty registry construction.

p38 Stabilizes Snail by Suppressing DYRK2-Mediated Phosphorylation That Is Required for GSK3ß-ßTrCP-Induced Snail Degradation.

Snail is a key regulator of epithelial-mesenchymal transition (EMT), which is a major step in tumor metastasis. Although the induction of Snail transcription precedes EMT, posttranslational regulation, especially phosphorylation of Snail, is critical for determining Snail protein levels or stability, subcellular localization, and the ability to induce EMT. To date, several kinases are known that enhance the stability of Snail by preventing its ubiquitination; however, the molecular mechanism(s) underlying this are still unclear. Here, we identified p38 MAPK as a crucial posttranslational regulator that enhances the stability of Snail. p38 directly phosphorylated Snail at Ser107, and this effectively suppressed DYRK2-mediated Ser104 phosphorylation, which is critical for GSK3ß-dependent Snail phosphorylation and ßTrCP-mediated Snail ubiquitination and degradation. Importantly, functional studies and analysis of clinical samples established a crucial role for the p38-Snail axis in regulating ovarian cancer EMT and metastasis. These results indicate the potential therapeutic value of targeting the p38-Snail axis in ovarian cancer. SIGNIFICANCE: These findings identify p38 MAPK as a novel regulator of Snail protein stability and potential therapeutic target in ovarian cancer.