Early osteoarthritis diagnosis based on near-infrared spectroscopy combined with aquaphotomics.

Osteoarthritis (OA) is the most common joint disease and the leading cause of disability in elderly individuals. Despite rapid advances in imaging techniques, early OA diagnosis remains a clinical challenge. In the present study, the feasibility of early OA diagnosis was explored via near-infrared spectroscopy (NIRS) combined with aquaphotomics. Synovial fluid samples from 65 cases of OA categorized as mild, moderate, and severe according to theKellgrenandLawrence classification criteria were analyzed via NIRS. The 1st overtone of water (1300-1600 nm) was considered as the research object for an aquaphotomics model, and aquagrams of the mild, moderate, and severe OA cases were generated using 12 water absorption patterns for early OA diagnosis.The aquaphotomics results exhibited clear differences in the region of 1300-1500 nm, and the number of hydrogen bonds of different water species (1412,1424, 1482, and 1496 nm) evidently correlated with OA occurrence and development. With OA progression, the absorption intensity of water molecules without hydrogen bonds (1412 nm/1424 nm) became stronger, while the absorption intensity of water molecules with four hydrogen bonds (1482 nm/1496 nm) decreased.These results together reveal that the established accurate and rapid early OA diagnosis model based on NIRS combined with aquaphotomics is effective and feasible, and that the number of hydrogen bonds can be used as a biomarker for early OA diagnosis.

HSP90-regulated CHIP/TRIM21/p21 Axis Involves in the Senescence of Osteosarcoma Cells.

BACKGROUND: OS is the most frequent malignant bone tumor with a poor prognosis. TRIM21 has been reported to play a critical role in OS by regulating the expression of the TXNIP/p21 axis and inhibiting the senescence of OS cells. AIM: Investigation of the molecular mechanism of tripartite motif 21 (TRIM21) in osteosarcoma (OS) would shed light on the understanding of the pathogenesis of OS. OBJECTIVE: This study aimed to explore the mechanism regulating the protein stability of TRIM21 in the process of OS senescence. METHODS: Human U2 OS cells were used to establish stable cells overexpressing TRIM21 (induced by Dox) or knocking down TRIM21. The co-immunoprecipitation (co-IP) assay was used to examine the interaction between TRIM21 and HSP90. Immunofluorescence (IF) assay was used to observe colocalization in OS cells. Western blot analysis was applied to detect the protein expression, and quantitative real-time PCR (qRT-PCR) assay was used to test the mRNA expression of corresponding genes. SA-ß-gal staining was used to evaluate OS senescence. RESULTS: In this study, we verified the interaction between HSP90 and TRIM21 using a co-IP assay. Knockdown or inhibition of HSP90 with its inhibitor 17-AAG accelerated the degradation of TRIM21 by the proteasome in OS cells. CHIP E3 ligase mediated this degradation of TRIM21, with the knockdown of CHIP rescuing the downregulation of TRIM21 induced by 17-AAG. TRIM21 inhibited OS senescence and downregulated the expression of senescence marker p21, while CHIP exhibited an opposite regulatory role on p21 expression. CONCLUSION: Taken together, our results demonstrated that HSP90 is responsible for the stabilization of TRIM21 in OS and that the CHIP/TRIM21/p21 axis controlled by HSP90 affects the senescence of OS cells.

Intraarterial Thrombolytic Treatment for Visual Deficits Caused by Hyaluronic Acid Filler: Efficacy, Safety, and Prognostic Factors.

BACKGROUND: The benefits of intraarterial thrombolytic treatment (IATT) in reversing hyaluronic acid (HA)-related visual deficits remain unclear. This study aimed to report a 5-year experience in the treatment of visual deficits resulting from HA embolization by IATT in a tertiary medical center. METHODS: From December of 2015 to June of 2021, the medical records of consecutive patients with HA-related visual deficits who underwent IATT were reviewed retrospectively. The demographics, clinical features, imaging data, treatment details, and follow-up results of the patients were analyzed. RESULTS: A total of 72 consecutive patients were analyzed, including five men (6.9%) men and 67 women (3.1%), aged 29.3 ± 7.6 years (range, 17 to 50 years). Thirty-two patients (44.4%) showed preserved visual acuity, and 40 (55.6%) exhibited no light perception on admission. Ocular motility disorders were detected in 63 patients (87.5%), ptosis was detected in 61 patients (84.7%), and facial skin changes were detected in 54 patients (75%). The technical success rate of IATT was 100%, with successful recanalization of the occlusive artery. No procedure-related complications were detected, and all skin injuries, ptosis, and ocular motility disorders were healed. Improved visual acuity was detected in 26 cases (36.1%). In the binary logistic regression model, only preoperative preserved visual acuity was independently associated with a good outcome. CONCLUSIONS: IATT for selective patients with HA-related visual deficits is efficient and safe. Preoperative preserved visual acuity was independently associated with a good outcome after IATT. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.

Tophaceous gouty arthritis with spondylolysis: a case report.

Spinal gout is a rare occurrence, and the combination of gout with lumbar spondylolysis has not been reported. We present a unique case involving a 29-year-old male who complained of low back pain for 1 month. Computed tomography and magnetic resonance imaging revealed articular subchondral erosions and a mass in the left L5-S1 facet joints. Initially treated for a spinal infection, the patient subsequently underwent lumbar spinal canal decompression and fusion, achieving complete relief. Postoperative pathology confirmed the spinal lesions to be tophaceous gout. Dual-energy CT or biopsy can assist in confirming the diagnosis. This report discusses another rare case of tophaceous gouty arthritis with spondylolysis to be added to the literature.

Autism screening: an unsupervised machine learning approach.

Early screening of autism spectrum disorders (ASD) is a key area of research in healthcare. Currently artificial intelligence (AI)-driven approaches are used to improve the process of autism diagnosis using computer-aided diagnosis (CAD) systems. One of the issues related to autism diagnosis and screening data is the reliance of the predictions primarily on scores provided by medical screening methods which can be biased depending on how the scores are calculated. We attempt to reduce this bias by assessing the performance of the predictions related to the screening process using a new model that consists of a Self-Organizing Map (SOM) with classification algorithms. The SOM is employed prior to the diagnostic process to derive a new class label using clusters learnt from the independent features; these clusters are related to communication, repetitive traits, and social traits in the input dataset. Then, the new clusters are compared with existing class labels in the dataset to refine and eliminate any inconsistencies. Lastly, the refined dataset is utilised to derive classification systems for autism diagnosis. The new model was evaluated against a real-life autism screening dataset that consists of over 2000 instances of cases and controls. The results based on the refined dataset show that the proposed method achieves significantly higher accuracy, precision, and recall for the classification models derived when compared to models derived from the original dataset.

The correlation of everyday cognition test scores and the progression of Alzheimer's disease: a data analytics study.

The process of diagnosing dementia conditions, especially Alzheimer's disease, and the cognitive tests that are involved in this process, are important areas of study. Everyday Cognition (ECog) is one test that can be used as part of Alzheimer's disease diagnosis to measure cognitive decline in different areas. In this study, we investigate two versions of the ECog test: the study partner reported version (ECogSP), and the patient reported version (ECogPT). We compare these, using statistical analysis and machine learning techniques, to create classification models to demonstrate the progression in ECog scores over time by using the Alzheimer's Disease Neuroimaging Initiative longitudinal data repository (ADNI); participants are classed with having normal cognition, mild cognitive impairment, or Alzheimer's disease. We found that participants who are diagnosed with Alzheimer's disease at baseline, or during a subsequent visit, tend to self-report consistent ECogPT scores over time indicating no change in cognitive ability. However, study partners tend to report higher and increasing ECogSP scores on behalf of participants in the same diagnosis category; this would indicate a degradation in the participant's cognitive ability over time, consistent with the progress of Alzheimer's disease.

Multifactorial Deep Learning Reveals Pan-Cancer Genomic Tumor Clusters with Distinct Immunogenomic Landscape and Response to Immunotherapy.

PURPOSE: Tumor genomic features have been of particular interest because of their potential impact on the tumor immune microenvironment and response to immunotherapy. Due to the substantial heterogeneity, an integrative approach incorporating diverse molecular features is needed to characterize immunologic features underlying primary resistance to immunotherapy and for the establishment of novel predictive biomarkers. EXPERIMENTAL DESIGN: We developed a pan-cancer deep machine learning model integrating tumor mutation burden, microsatellite instability, and somatic copy-number alterations to classify tumors of different types into different genomic clusters, and assessed the immune microenvironment in each genomic cluster and the association of each genomic cluster with response to immunotherapy. RESULTS: Our model grouped 8,646 tumors of 29 cancer types from The Cancer Genome Atlas into four genomic clusters. Analysis of RNA-sequencing data revealed distinct immune microenvironment in tumors of each genomic class. Furthermore, applying this model to tumors from two melanoma immunotherapy clinical cohorts demonstrated that patients with melanoma of different genomic classes achieved different benefit from immunotherapy. Interestingly, tumors in cluster 4 demonstrated a cold immune microenvironment and lack of benefit from immunotherapy despite high microsatellite instability burden. CONCLUSIONS: Our study provides a proof for principle that deep learning modeling may have the potential to discover intrinsic statistical cross-modality correlations of multifactorial input data to dissect the molecular mechanisms underlying primary resistance to immunotherapy, which likely involves multiple factors from both the tumor and host at different molecular levels.

Characterization of Calibrated Gelatin Sponge Particles in a Rabbit Renal Embolization Model.

PURPOSE: To evaluate the level of artery occlusion, degradation periods, tissue response and vessel recanalization of calibrated gelatin sponge particles after segmental renal artery embolization. MATERIALS AND METHODS: Superselective embolization of 14 adult rabbits was performed with calibrated gelatin sponge particles (150-350 µm). Two rabbits were killed immediately after the procedure (day 0). One pair of rabbits was killed on each of the following days: 1, 3, 7, 14, 28 and 56. One rabbit from each pair underwent CT angiography before embolization and killing. The pathologic changes of the embolized renal parenchyma and embolic characteristics of calibrated gelatin sponge particles were evaluated histologically and angiographically. RESULTS: Calibrated gelatin sponge particles were distally located in interlobular artery with a dense packing on day 0. The level of occlusion paralleled the size of the particles. Partial degradation of the particles was observed on day 3, and complete degradation was observed on day 14. Vessel recanalization was observed through both CTA and histological analysis starting on day 3. Vascular inflammation responding to gelatin sponge particles was mild and subsided with the degradation of the particles. On day 28 and day 56, attenuation of embolized vessels occurred due to marked intimal proliferation, and vascular occlusion developed. CONCLUSIONS: Gelatin sponge particles of 150-350 µm produced dense and distal embolization, and were resorbed before day 14 with a mild tissue reaction. Vessel recanalization occurred secondary to the resorption of gelatin sponge particles, but permanent vascular occlusion developed due to marked intimal hyperplasia after day 28.