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Zihao Liu, Ying Liang, Honghua Wang, Zhenhe Lu, Jinsheng Chen, Qiaodong Huang, Lei Sheng, Yinghong Ma, Huiying Du, Qingjuan GongDepartment of Pain Medicine, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China Abstract: Neuropathic pain is a common and refractory chronic pain that affects millions of people worldwide. Its underlying mechanisms are still unclear, but they may involve long noncoding RNAs (lncRNAs), which play crucial roles in a variety of biological functions, including nociception. We used microarrays to investigate the possible interactions between lncRNAs and neuropathic pain and identified 22,213 lncRNAs and 19,528 mRNAs in the spinal cord in a mouse model of spared nerve injury (SNI)-induced neuropathic pain. The abundance levels of 183 lncRNAs and 102 mRNAs were significantly modulated by both SNI and administration of minocycline. A quantitative real-time polymerase chain reaction analysis validated expression changes in three lncRNAs (NR_015491, ENSMUST00000174263, and ENSMUST00000146263). Class distribution analysis of differentially expressed lncRNAs revealed intergenic lncRNAs as the largest category. Functional analysis indicated that SNI-induced gene regulations might be involved in the activities of cytokines (IL17A and IL17F) and chemokines (CCL2, CCL5, and CCL7), whereas minocycline might exert a pain-alleviating effect on mice through actin binding, thereby regulating nociception by controlling the cytoskeleton. Thus, lncRNAs might be responsible for SNI-induced neuropathic pain and the attenuation caused by minocycline. Our study could implicate lncRNAs as potential targets for future treatment of neuropathic pain. Keywords: LncRNA, neuropathic pain, spinal cord, minocycline

Abstract Background Preoperative templating is an important step for total knee arthroplasty (TKA), facilitating hospital personnel in the anticipation and preparation of necessary surgical resources. Despite its importance, this process currently lacks automation. This study aimed to develop an artificial intelligence (AI) model to automate implant size prediction. Methods A total of 13,281 (2938 anteroposterior, 10,343 lateral) knee radiographs obtained from the authors’ institute were utilized for model training, with 2302 (1034 anteroposterior, 1268 lateral) images set apart for validation and testing. The templating AI model integrates a pipeline composed of multiple steps for automated implant size estimation. To predict implant size, anterioposterior (AP) and lateral radiograph predictions were merged, selecting the smaller of the predicted sizes to prevent implant overhang. The model’s size predictions were validated with 81 real TKA data set apart from the training data, and its accuracy was compared to that of manual templating by an orthopedic specialist. Predictions matching the actual implanted sizes were labeled “exact” and those within one size, “accurate.” The influence of patient characteristics on the model’s prediction accuracy was also analyzed. The measurement time elapsed for implant sizing was recorded for both the AI model and the orthopedic specialist. Implant position predicted by the model was validated by comparing insert locations with postoperative images. Results Compared with data from 81 actual TKA procedures, the model provided exact predictions for 39.5% of femoral and 43.2% of tibial components. Allowing a one-size margin of error, 88.9% of predictions were deemed “accurate” for both components. Interobserver reliability (Cohen’s kappa) were 0.60 and 0.70 for femoral and tibial implants, respectively, both classified as “substantial.” The orthopedic specialist produced results accurate within one-size margin of error in 95.1% and 100% of cases for femoral and tibial components, respectively. Interobserver reliability between the orthopedic specialist and ground truth was 0.76 and 0.8 for femoral and tibial components, respectively. The measurement time per case was 48.7 s for the AI model, compared with 97.5 s for the orthopedic specialist. Compared with postoperative radiographs, predicted implant position had an error of less than 4 mm on average. Conclusions An AI-based templating tool for TKA was successfully developed, demonstrating satisfactory accuracy and efficiency. Its application could significantly reduce the clinical workload in TKA preparation.

Abstract Purpose Total knee arthroplasty (TKA) is an effective treatment for advanced osteoarthritis, and achieving optimal outcomes can be challenging due to various influencing factors. Previous research has focused on identifying factors that affect postoperative functional outcomes. However, there is a paucity of studies predicting individual postoperative improvement following TKA. Therefore, a quantitative prediction model for individual patient outcomes is necessary. Materials and methods Demographic data, radiologic variables, intraoperative variables, and physical examination findings were collected from 976 patients undergoing TKA. Preoperative and 1-year postoperative Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores were assessed, and multivariate regression analysis was conducted to identify significant factors influencing one-year WOMAC scores and changes in WOMAC scores. A predictive model was developed on the basis of the findings. Results The predictive accuracy of the model for 1-year WOMAC scores was poor (all adjusted R 2 0.75). Preoperative WOMAC scores, sex, and postoperative knee range of motion significantly affected all pain, stiffness, and physical function aspects of the WOMAC scores (all P

Abstract Background Fine-grained classification deals with data with a large degree of similarity, such as cat or bird species, and similarly, knee osteoarthritis severity classification [Kellgren–Lawrence (KL) grading] is one such fine-grained classification task. Recently, a plug-in module (PIM) that can be integrated into convolutional neural-network-based or transformer-based networks has been shown to provide strong discriminative regions for fine-grained classification, with results that outperformed the previous deep learning models. PIM utilizes each pixel of an image as an independent feature and can subsequently better classify images with minor differences. It was hypothesized that, as a fine-grained classification task, knee osteoarthritis severity may be classified well using PIMs. The aim of the study was to develop this automated knee osteoarthritis classification model. Methods A deep learning model that classifies knee osteoarthritis severity of a radiograph was developed utilizing PIMs. A retrospective analysis on prospectively collected data was performed. The model was trained and developed using the Osteoarthritis Initiative dataset and was subsequently tested on an independent dataset, the Multicenter Osteoarthritis Study (test set size: 17,040). The final deep learning model was designed through an ensemble of four different PIMs. Results The accuracy of the model was 84%, 43%, 70%, 81%, and 96% for KL grade 0, 1, 2, 3, and 4, respectively, with an overall accuracy of 75.7%. Conclusions The ensemble of PIMs could classify knee osteoarthritis severity using simple radiographs with a fine accuracy. Although improvements will be needed in the future, the model has been proven to have the potential to be clinically useful.

Purpose: The objective of this study was to assess the frequency and management protocols for malignant tumors among cases referred for aeromedical consultation. Methods: The research analyzed data collected from aeromedical consultations conducted between January 2014 and December 2022. Parameters examined included demographic information such as sex, age, flight crew classification, and diagnosis. Results: Out of the cases reviewed, 31 patients were diagnosed with malignant tumors, with an average age at diagnosis of 38.5 years, and a male predominance of 26 cases. The most commonly diagnosed malignancies were thyroid cancer, lung cancer, kidney cancer, stomach cancer, and colon cancer. During the initial aeromedical consultation, 22 cases were temporarily grounded while 8 received waivers. Conclusion: Given the potential rise in malignant tumor incidence among flight crews due to advancements in medical technology facilitating early detection, it is imperative to emphasize regular check-ups and carefully evaluate aeromedical suitability for flying.

Abstract Electromyography (EMG) is considered a potential predictive tool for the severity of knee osteoarthritis (OA) symptoms and functional outcomes. Patient-reported outcome measures (PROMs), such as the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and visual analog scale (VAS), are used to determine the severity of knee OA. We aim to investigate muscle activation and co-contraction patterns through EMG from the lower extremity muscles of patients with advanced knee OA patients and evaluate the effectiveness of an interpretable machine-learning model to estimate the severity of knee OA according to the WOMAC (pain, stiffness, and physical function) and VAS using EMG gait features. To explore neuromuscular gait patterns with knee OA severity, EMG from rectus femoris, medial hamstring, tibialis anterior, and gastrocnemius muscles were recorded from 84 patients diagnosed with advanced knee OA during ground walking. Muscle activation patterns and co-activation indices were calculated over the gait cycle for pairs of medial and lateral muscles. We utilized machine-learning regression models to estimate the severity of knee OA symptoms according to the PROMs using muscle activity and co-contraction features. Additionally, we utilized the Shapley Additive Explanations (SHAP) to interpret the contribution of the EMG features to the regression model for estimation of knee OA severity according to WOMAC and VAS. Muscle activity and co-contraction patterns varied according to the functional limitations associated with knee OA severity according to VAS and WOMAC. The coefficient of determination of the cross-validated regression model is 0.85 for estimating WOMAC, 0.82 for pain, 0.85 for stiffness, and 0.85 for physical function, as well as VAS scores, utilizing the gait features. SHAP explanation revealed that greater co-contraction of lower extremity muscles during the weight acceptance and swing phases indicated more severe knee OA. The identified muscle co-activation patterns may be utilized as objective candidate outcomes to better understand the severity of knee OA.

Abstract Achieving efficient and large‐area organic solar modules via non‐halogenated solution processing is vital for the commercialization yet challenging. The primary hurdle is the conservation of the ideal film‐formation kinetics and bulk‐heterojunction (BHJ) morphology of large‐area organic solar cells (OSCs). A cutting‐edge non‐fullerene acceptor (NFA), Y6, shows efficient power conversion efficiencies (PCEs) when processed with toxic halogenated solvents, but exhibits poor solubility in non‐halogenated solvents, resulting in suboptimal morphology. Therefore, in this study, the impact of modifying the inner and outer side‐chains of Y6 on OSC performance is investigated. The study reveals that blending a polymer donor, PM6, with one of the modified NFAs, namely N‐HD, achieved an impressive PCE of 18.3% on a small‐area OSC. This modified NFA displays improved solubility in o‐xylene at room temperature, which facilitated the formation of a favorable BHJ morphology. A large‐area (55 cm2) sub‐module delivered an impressive PCE of 12.2% based on N‐HD using o‐xylene under ambient conditions. These findings underscore the significant impact of the modified Y6 derivatives on structural arrangements and film processing over a large‐area module at room temperature. Consequently, these results are poised to deepen the comprehension of the scaling challenges encountered in OSCs and may contribute to their commercialization.

This study was the first to document the fluctuations of nutritional constituents, antioxidant capacities, and physicochemical characteristics during the aging processes of red ginseng sprouts (RGS) and black ginseng sprouts (BGS) from dried ginseng sprouts (DGS). Total ginsenoside levels differed with 54.72 (DGS) → 57.15 (RGS) and 6.98 (BGS) mg/g, specifically, ginsenoside F2 and Rd2 in RGS remarkably increased with 1.97 → 5.88 and 2.41 → 5.49 mg/g, respectively. Phenolics increased dramatically as 297.02 → 1770.01 (6.0-fold); 1834.94 (6.2-fold) μg/g in DGS → RGS; BGS with abundance contents of benzoic acid (>15.3-fold), chlorogenic acid (>9.5-fold), and catechin (>4.2-fold), whereas amino acids markedly decreased (3686.81 → 1505.00; 364.64 mg/100 g), with arginine showing a significant decrease. Moreover, beneficial factors (total phenolic content: TPC; total flavonoid content: TFC; maillard reaction products: MRP) displayed increase tendencies (approximately 2.0-fold) with BGS > RGS > DGS, and antioxidant patterns significantly increased with potential capacities as follows: ABTS (48.3: DGS → 65.8: RGS; 70.2 %: BGS) > DPPH (18.5 → 44.6; 59.2 %) > hydroxyl (23.2 → 35.4; 39.9 %) > FRAP (0.6 → 1.8; 1.8 %) at 500 μg/mL. In particular, DNA protection exhibited excellent rates of 100 %, in the order of BGS (25 μg/mL) > RGS (50 μg/mL) > DGS (500 μg/mL). These findings suggest that processed ginseng sprouts can be excellent agents for natural antioxidants.

Background/Aims: Synchronous multiple gastric cancer (SMGC) accounts for approximately 6% to 14% of gastric cancer (GC) cases. This study aimed to identify risk factors for SMGC. Methods : A total of 14,603 patients diagnosed with GC were prospectively enrolled. Data including age, sex, body mass index, smoking, alcohol consumption, family history, p53 expression, microsatellite instability, cancer classification, lymph node metastasis, and treatment were collected. Risk factors were analyzed using logistic regression analysis between a single GC and SMGC. Results : The incidence of SMGC was 4.04%, and that of early GC (EGC) and advanced GC (AGC) was 5.43% and 3.11%, respectively. Patients with SMGC were older (65.33 years vs 61.75 years, p

Abstract Z-DNA, a well-known non-canonical form of DNA involved in gene regulation, is often found in gene promoters. Transposable elements (TEs), which make up 45% of the human genome, can move from one location to another within the genome. TEs play various biological roles in host organisms, and like Z-DNA, can influence transcriptional regulation near promoter regions. MicroRNAs (miRNAs) are a class of small non-coding RNA molecules that play a critical role in the regulation of gene expression. Although TEs can generate Z-DNA and miRNAs can bind to Z-DNA, how these factors affect gene transcription has yet to be elucidated. Here, we identified potential Z-DNA forming sequence (ZFS), including TE-derived ZFS, in the promoter of prostaglandin reductase 1 (PTGR1) by data analysis. The transcriptional activity of these ZFS in PTGR1 was confirmed using dual-luciferase reporter assays. In addition, we discovered a novel ZFS-binding miRNA (miR-6867-5p) that suppressed PTGR1 expression by targeting to ZFS. In conclusion, these findings suggest that ZFS, including TE-derived ZFS, can regulate PTGR1 gene expression and that miR-6867-5p can suppress PTGR1 by interacting with ZFS.

Abstract Background Achieving consistent accuracy in radiographic measurements across different equipment and protocols is challenging. This study evaluates an advanced deep learning (DL) model, building upon a precursor, for its proficiency in generating uniform and precise alignment measurements in full-leg radiographs irrespective of institutional imaging differences. Methods The enhanced DL model was trained on over 10,000 radiographs. Utilizing a segmented approach, it separately identified and evaluated regions of interest (ROIs) for the hip, knee, and ankle, subsequently integrating these regions. For external validation, 300 datasets from three distinct institutes with varied imaging protocols and equipment were employed. The study measured seven radiologic parameters: hip-knee-ankle angle, lateral distal femoral angle, medial proximal tibial angle, joint line convergence angle, weight-bearing line ratio, joint line obliquity angle, and lateral distal tibial angle. Measurements by the model were compared with an orthopedic specialist's evaluations using inter-observer and intra-observer intraclass correlation coefficients (ICCs). Additionally, the absolute error percentage in alignment measurements was assessed, and the processing duration for radiograph evaluation was recorded. Results The DL model exhibited excellent performance, achieving an inter-observer ICC between 0.936 and 0.997, on par with an orthopedic specialist, and an intra-observer ICC of 1.000. The model's consistency was robust across different institutional imaging protocols. Its accuracy was particularly notable in measuring the hip-knee-ankle angle, with no instances of absolute error exceeding 1.5 degrees. The enhanced model significantly improved processing speed, reducing the time by 30-fold from an initial 10–11 s to 300 ms. Conclusions The enhanced DL model demonstrated its ability for accurate, rapid alignment measurements in full-leg radiographs, regardless of protocol variations, signifying its potential for broad clinical and research applicability.

The most widely used material in electron transport layers (ETL) of inverted organic solar cells (iOSCs) is zinc oxide (ZnO). However, the brittleness, inorganic nature, surface defects, and photocatalytic activity of ZnO lead to poor stability in iOSCs. Herein, the light‐soaking and thermal stability of iOSCs are substantially improved by modifying ZnO surface with polyurethane diacrylate (SAR) or urethane acrylate (OCS)‐based ultraviolet (UV) resins. The UV resins significantly reduce the energy barrier, suppress surface defects, and improve interfacial contact between ZnO ETL and the organic photoactive layer. Notably, the SAR and OCS resins mitigate the photocatalytic activity of ZnO, electrical leakage, and interfacial resistance during photoaging of OSCs. As a result, iOSCs based on modified ZnOs retain over 80% of initial efficiency under 1 sun illumination for light soaking 1000 h. Furthermore, SAR and OCS resins on ZnO surfaces form a robust crosslinked network with excellent solvent resistant properties, which result in enhanced thermal stability. These results reveal that this simple and effective approach is a promising procedure to fabricate high‐performance iOSCs.

Background and Objectives: Neglected patellar dislocation in the presence of end-stage osteoarthritis (OA) is a rare condition characterized by the patella remaining laterally dislocated without reduction. Due to the scarcity of reported cases, the optimal management approach is still uncertain. However, primary total knee arthroplasty (TKA) can serve as an effective treatment option. This study aimed to present the clinical and radiological outcomes achieved using our surgical technique. Materials and Methods: A retrospective review of 12 knees in 8 patients with neglected patellar dislocation and end-stage OA who underwent primary TKA was conducted. The surgical procedure involved conventional TKA techniques (e.g., medial parapatellar arthrotomy) and additional procedures specific to the individual pathologies of neglected patellar dislocation (e.g., lateral release, medial plication, and quadriceps lengthening). Clinical outcomes, including patient-reported outcome measures (PROMs) (Knee Society Scores and the Western Ontario and McMaster Universities Osteoarthritis Index) and knee range of motion (ROM), were assessed preoperatively and two years postoperatively. Radiological measures including mechanical femorotibial angle and patellar tilt angle were assessed preoperatively and until the last follow-up examinations. Any complications were also reviewed. Results: There were significant improvements in all PROMs, knee ROM, and radiological outcomes, including mechanical femorotibial angle and patellar tilt angle (all p < 0.05). At a mean follow-up of 68 months, no major complications requiring revision surgery, including patellar dislocation, were reported. Conclusions: Primary TKA is an effective procedure for correcting various pathologies associated with neglected patellar dislocation in end-stage OA without necessitating additional bony procedures. Satisfactory clinical and radiological outcomes can be expected using pathology-specific procedures.

Recently, jellyfish venom has gained attention as a promising reservoir of pharmacologically active compounds, with potential applications in new drug development. In this investigation, novel peptides, isolated from the hydrolysates of Nemopilema nomurai jellyfish venom (NnV), demonstrate potent inhibitory activities against angiotensin-converting enzyme (ACE). Proteolytic enzymes—specifically, papain and protamex—were utilized for the hydrolysis under optimized enzymatic conditions, determined by assessing the degree of hydrolysis through the ninhydrin test. Comparative analyses revealed that papain treatment exhibited a notably higher degree of NnV hydrolysis compared to protamex treatment. ACE inhibitory activity was quantified using ACE kit-WST, indicating a substantial inhibitory effect of 76.31% for the papain-digested NnV crude hydrolysate, which was validated by captopril as a positive control. The separation of the NnV-hydrolysate using DEAE sepharose weak-anion-exchange chromatography revealed nine peaks under a 0–1 M NaCl stepwise gradient, with peak no. 3 displaying the highest ACE inhibition of 96%. The further purification of peak no. 3 through ODS-C18 column reverse-phase high-performance liquid chromatography resulted in five sub-peaks (3.1, 3.2, 3.3, 3.4, and 3.5), among which 3.2 exhibited the most significant inhibitory activity of 95.74%. The subsequent analysis of the active peak (3.2) using MALDI–TOF/MS identified two peptides with distinct molecular weights of 896.48 and 1227.651. The peptide sequence determined by MS/MS analysis revealed them as IVGRPLANG and IGDEPRHQYL. The docking studies of the two ACE-inhibitory peptides for ACE molecule demonstrated a binding affinity of −51.4 ± 2.5 and −62.3 ± 3.3 using the HADDOCK scoring function.

Background/Aims: There are few reports regarding mixed carcinoma, defined as a mixture of glandular and poorly cohesive components, in patients with gastric cancer (GC). The aim of this study was to evaluate the proportion and characteristics of mixed carcinoma in GC patients. Methods: A total of 7,215 patients diagnosed with GC at Seoul National University Bundang Hospital were enrolled from March 2011 to February 2020. GC was divided into four groups (well-moderately differentiated GC, poorly differentiated GC, poorly cohesive carcinoma, and mixed carcinoma). The proportion of each GC type and the clinicopathological features were analyzed and divided into early GC and advanced GC. Results: The proportion of mixed carcinoma was 10.9% (n=787). In early GC, submucosal invasion was the most common in poorly differentiated (53.7%), and mixed carcinoma ranked second (41.1%). Mixed carcinoma showed the highest proportion of lymph node metastasis in early GC (23.0%) and advanced GC (78.3%). In advanced GC, the rate of distant metastasis was 3.6% and 3.9% in well-moderately differentiated GC and mixed carcinoma, respectively, lower than that in poorly differentiated GC (6.4%) and poorly cohesive carcinoma (5.7%), without statistical significance. Conclusions: Mixed carcinoma was associated with lymph node metastasis compared to other histological GC subtypes. And it showed relatively common submucosal invasion in early GC, but the rates of venous invasion and distant metastasis were lower in advanced GC. Further research is needed to uncover the mechanism underlying these characteristics of mixed carcinoma (Trial registration number: NCT04973631).

Abstract The simple‐structural and volatile solid additive 1,4‐dibromobenzene (DBrB) can outperform organic solar cells (OSCs) fabricated with 1,4‐diiodobenzene and 1,4‐dichlorobenzene in terms of power conversion efficiency (PCE). A remarkable PCE of 17.0% has been achieved in a binary OSC based on DBrB‐optimized photoactive materials processed from non‐halogenated solvents, which is mainly attributed to the formation of a three‐dimensional interpenetrating network and the orderly arrangement of the photoactive materials by improving the intermolecular interaction. This optimized morphology enables efficient charge transfer/transport as well as suppressed charge recombination, resulting in the simultaneous increase in all photovoltaic parameters. More importantly, we demonstrate that non‐halogenated solvent‐processed DBrB enabled PM6:Y6‐HU OSCs with an impressive PCE of 18.6%, which is the highest efficiency yet reported for binary OSCs. This study suggests that the novel DBrB volatile solid additive is an effective approach to optimizing the morphology and thereby improves the photovoltaic performance of OSCs.

Objective Delirium is commonly reported from the inpatients with Coronavirus disease 2019 (COVID-19) infection. As delirium is closely associated with adverse clinical outcomes, prediction and prevention of delirium is critical. We developed a machine learning (ML) model to predict delirium in hospitalized patients with COVID-19 and to identify modifiable factors to prevent delirium. Methods The data set (n = 878) from four medical centers was constructed. Total of 78 predictors were included such as demographic characteristics, vital signs, laboratory results and medication, and the primary outcome was delirium occurrence during hospitalization. For analysis, the extreme gradient boosting (XGBoost) algorithm was applied, and the most influential factors were selected by recursive feature elimination. Among the indicators of performance for ML model, the area under the curve of the receiver operating characteristic (AUROC) curve was selected as the evaluation metric. Results Regarding the performance of developed delirium prediction model, the accuracy, precision, recall, F1 score, and the AUROC were calculated (0.944, 0.581, 0.421, 0.485, 0.873, respectively). The influential factors of delirium in this model included were mechanical ventilation, medication (antipsychotics, sedatives, ambroxol, piperacillin/tazobactam, acetaminophen, ceftriaxone, and propacetamol), and sodium ion concentration (all p

The current research was the first to prove the existence of fluctuations in the metabolite constituents and antioxidant properties in different organs (leaves, stems, and roots) of the mountain-cultivated ginseng (MCG) plant during a two-month maturation period. Four metabolites, including fatty acids, amino acids, ginsenosides, and phenolic phytochemicals, exhibited considerable differences in organs and maturation times with the following order: leaves > stems > roots. The predominant metabolite contents were found in leaves, with fatty acid (1057.9 mg/100 g) on 31 May, amino acid (1989.2 mg/100 g) on 13 July, ginsenosides (88.7 mg/g) on 31 May, and phenolic phytochemical (638.3 μg/g) on 31 May. Interestingly, ginsenoside content in leaves were highest, with 84.8 → 88.7 → 82.2 → 78.3 mg/g. Specifically, ginsenosides Re, Rd, and F2 showed abundant content ranging from 19.1 to 16.9 mg/g, 8.5 to 14.8 mg/g, and 9.5 to 13.1 mg/g, respectively. Phenolic phytochemicals exhibited remarkable differences in organs compared to maturation periods, with the highest total phenolic content and total flavonoid content recorded at 9.48 GAE and 1.30 RE mg/g in leaves on 31 May. The antioxidant capacities on radical, FRAP, and DNA protection differed significantly, with leaves on 31 May exhibiting the highest values: 88.4% (DPPH), 89.5% (ABTS), 0.84 OD593 nm (FRAP) at 500 μg/mL, and 100% DNA protection at 50 μg/mL. Furthermore, principal cluster analysis revealed metabolite variability as follows: ginsenoside (83.3%) > amino acid (71.8%) > phenolic phytochemical (61.1%) > fatty acid (58.8%). A clustering heatmap highlighted significant changes in metabolite components under the maturation times for each organ. Our findings suggest that MCG leaves on 31 May may be a potential source for developing nutraceuticals, offering highly beneficial components and strong antioxidants.

Abstract Background We sought to determine (1) the success rate of debridement, antibiotics, and implant retention (DAIR) for acute periprosthetic joint infection (PJI) of the knee in patients with acute postsurgical infection and in those with acute hematogenous infection via a multicenter study, (2) the factors related to the failure of DAIR for overall acute PJI and acute hematogenous PJI via subgroup analysis, and (3) whether the PJI recurrence patterns differed between the two groups over time after DAIR. Methods This retrospective multicenter study included 101 acute knee PJI. Acute postsurgical PJI was defined as PJI diagnosed

IntroductionSkin vaccination using dissolving microneedle patch (MNP) technology for transdermal delivery is a promising vaccine delivery strategy to overcome the limitations of the existing vaccine administration strategies using syringes. To improve the traditional microneedle mold fabrication technique, we introduced droplet extension (DEN) to reduce drug loss. Tuberculosis remains a major public health problem worldwide, and BCG revaccination had failed to increase the protective efficacy against tuberculosis. We developed an MNP with live Mycobacterium paragordonae (Mpg) (Mpg-MNP) as a candidate of tuberculosis booster vaccine in a heterologous prime-boost strategy to increase the BCG vaccine efficacy.Materials and methodsThe MNPs were fabricated by the DEN method on a polyvinyl alcohol mask film and hydrocolloid-adhesive sheet with microneedles composed of a mixture of mycobacteria and hyaluronic acid. We assessed the transdermal delivery efficiency by comparing the activation of the dermal immune system with that of subcutaneous injection. A BCG prime Mpg-MNP boost regimen was administered to a mouse model to evaluate the protective efficacy against M. tuberculosis.ResultsWe demonstrated the successful transdermal delivery achieved by Mpg-MNP compared with that observed with BCG-MNP or subcutaneous vaccination via an increased abundance of MHCII-expressing Langerin+ cells within the dermis that could migrate into draining lymph nodes to induce T-cell activation. In a BCG prime-boost regimen, Mpg-MNP was more protective than BCG-only immunization or BCG-MNP boost, resulting in a lower bacterial burden in the lungs of mice infected with virulent M. tuberculosis. Mpg-MNP-boosted mice showed higher serum levels of IgG than BCG-MNP-boosted mice. Furthermore, Ag85B-specific T-cells were activated after BCG priming and Mpg-MNP boost, indicating increased production of Th1-related cytokines in response to M. tuberculosis challenge, which is correlated with enhanced protective efficacy.DiscussionThe MNP fabricated by the DEN method maintained the viability of Mpg and achieved effective release in the dermis. Our data demonstrate a potential application of Mpg-MNP as a booster vaccine to enhance the efficacy of BCG vaccination against M. tuberculosis. This study produced the first MNP loaded with nontuberculous mycobacteria (NTM) to be used as a heterologous booster vaccine with verified protective efficacy against M. tuberculosis.

Abstract Background Postoperative delirium is a challenging complication due to its adverse outcome such as long hospital stay. The aims of this study were: 1) to identify preoperative risk factors of postoperative delirium following knee arthroplasty, and 2) to develop a machine-learning prediction model. Method A total of 3,980 patients from two hospitals were included in this study. The model was developed and trained with 1,931 patients from one hospital and externally validated with 2,049 patients from another hospital. Twenty preoperative variables were collected using electronic hospital records. Feature selection was conducted using the sequential feature selection (SFS). Extreme Gradient Boosting algorithm (XGBoost) model as a machine-learning classifier was applied to predict delirium. A tenfold-stratified area under the curve (AUC) served as the metric for variable selection and internal validation. Results The incidence rate of delirium was 4.9% (n = 196). The following seven key predictors of postoperative delirium were selected: age, serum albumin, number of hypnotics and sedatives drugs taken preoperatively, total number of drugs (any kinds of oral medication) taken preoperatively, neurologic disorders, depression, and fall-down risk (all p

Background and Objectives: Stable fixation is essential for successful healing after medial open wedge high tibial osteotomy (MOWHTO) to minimize the risk of non-union and correction loss. In Asians, potential complications such as D-hole screw osteotomy plane violation (D-hole violation) and inadequate plate fitting arise due to improper plate size. This study aimed to evaluate the risk factors for D-hole violation and compare the conventional anatomic (CA) plate with an individualized anatomic (IA) plate in MOWHTO procedures. Materials and Methods: A simulation study on D-hole violation using the CA plate was conducted, involving preoperative radiographs and CT scans of 64 lower extremities from 47 MOWHTO patients. Additionally, a randomized controlled study compared CA and IA plates in MOWHTO procedures with 34 patients (17 in the CA plate group; 18 in the IA plate group). Patient demographics, patient-reported outcome measures (PROMs), and radiological measures were analyzed. Results: In the simulation study, the rates of D-hole violation ranged from 20.3% to 59.4%, with an increase observed as the plate was distalized from 5 mm to 10 mm away from the joint line. Short stature was identified as an independent risk factor for D-hole violation (p < 0.001), with a cutoff value of 155.3 cm. In the randomized controlled study, no significant difference in PROMs and D-hole violation was observed between the CA plate and IA plate groups. However, the IA plate group showed better plate fitting compared to the CA plate group (p = 0.041). Conclusions: This study identified a high risk of D-hole screw osteotomy plane violations in MOWHTO procedures, particularly when the plate is positioned more distally and in individuals with a stature below 155.3 cm. It also revealed that individualized plates provide better tibial fitting compared to conventional anatomic plates, particularly in Asian populations where tibial morphology tends to be shorter than in Western populations. Therefore, evaluating patient stature and selecting tailored plates are essential to optimize plate positioning and minimize plate-related complications in MOWHTO procedures.

Background and Objectives: National joint registries report higher total knee arthroplasty (TKA) revision rates in posterior-stabilized (PS) systems compared to non-posterior-stabilized designs. The purpose of this study was to investigate the implant survivorship and clinical outcomes of an anatomic implant with a PS bearing. Materials and Methods: An early- to mid-term follow-up of a prospective, multi-center, non-controlled outcomes study of patients who received primary TKA between November 2014 and June 2017 was performed. A total of 800 cases using PS bearings that were implanted in 664 patients were monitored post-operatively for their implant survivorship and adverse events for up to five years. The Knee Society Knee and Function scores, patient satisfaction, the five-dimensional European Quality of Life questionnaire, and range of motion (ROM) were evaluated pre-operatively and post-operatively at six weeks, six months, one year, two years, three years, and five years. Results: The mean follow-up period was 3.7 ± 1.3 years, and the three-year implant survival rate was 99.3% (95% CI: 98.4%, 99.7%) with five revisions during the five-year follow-up. Patient satisfaction was 96.1% at six weeks and increased to 99.3% at one year. All patient-reported outcome measures significantly (p < 0.0001) increased up to the one-year follow-up and then remained stable up to the five-year follow-up. Conclusions: This study supports the excellent survivorship and patient-reported outcomes of the Persona® Knee system using cemented, fixed bearing, posterior-stabilized components with minimal complications at early- to mid-term follow-up in an international Asian population. Ongoing observations are being performed to investigate the mid- to long-term survivorship and clinical outcomes associated with this knee system.

Abstract Background Sarcopenia, an age-related loss of skeletal muscle mass and function, is correlated with adverse outcomes after some surgeries. This study examined the characteristics of sarcopenic patients undergoing primary total knee arthroplasty (TKA), and identified low muscle mass as an independent risk factor for postoperative TKA complications. Methods A retrospective cohort study examined 452 patients who underwent TKA. The skeletal muscle index (SMI) was obtained via bioelectrical impedance analysis (BIA), along with demographics, the Charlson Comorbidity Index, and medication, laboratory and operative data for 2018–2021. Patients were categorized into normal (n = 417) and sarcopenic (n = 35) groups using the SMI cut-off suggested by the Asian Working Group for Sarcopenia 2019 (males,

The current research was characterized on phenolic metabolite profile including six chemical structures (phenolic acid, luteolin, orientin, apigenin, isoscoparin, and tricin) in wheat seedlings using HPLC-Q-Orbitrap-MS/MS and NMR techniques. Our study was also was the first to demonstrate fluctuations of isolated nine phenolic contents and antioxidant properties in various cultivars of this species with different growth times. The antioxidant abilities differed significantly in the 80 % methanol extracts (600 μg/mL) according to cultivar and growth time, with the highest average activities (DPPH: 82 %; ABTS: 87 %) observed after 7 days. The isolated nine compositions exhibited considerable differences in cultivars and growth times, specifically, isoorientin (6) and isochaftoside (8) were observed the most abundant average contents (99.3; 64.3 mg/100 g), representing approximately 28.3 and 18.3 % (total content: 350.8 mg/100 g). Their total phenolics showed the highest rates (420.8 mg/100 g) at 7 days, followed by 9 → 5 → 12 → 14 days with 374.6 → 366.7 → 350.7 → 241.1 mg/100 g, as the rank orders of antioxidant effects. These findings suggest that wheat seedlings may be a potent source of functional agents.

Objectives: The treatment of infected knee arthritis in patients with coexisting joint destruction, including superimposed advanced arthritis or chronic osteomyelitis, is challenging. We investigated the outcomes of 2-stage primary total knee arthroplasty (TKA) for evolutive infected arthritis with coexistent joint destruction. Methods: We retrospectively reviewed the cases of 50 patients from 5 hospitals who presented with infected arthritis of the knee and were treated with 2-stage TKA: debridement and antibiotic-loaded articulating cement spacer (ALCS) insertion as the first stage and TKA as the second stage. We recorded demographics, laboratory results, and radiographic findings including Kellgren-Lawrence classification (KL) for knee arthritis. Outcomes including infection eradication, knee range of motion (ROM), and patient-reported outcome measures were evaluated. Results: The patient cohort had a mean age of 71.8 years (range, 40–86); they were followed for an average of 4.1 years (range, 2.2–13.3). Also, 40 patients showed KL grade 4, whereas 10 patients showed grade 3. A pathogen was identified in 38 cases (73.1%); methicillin-resistant staphylococci infections (N = 16) and Candida spp infections (N = 7) were the 2 most common types. Constrained prostheses were used in 10 cases (20%). Stem augmentations were used in 15 cases (36.0%) and block augmentations were used in 8 cases (19.0%). One patient had recurrent infection after TKA, so the eradication rate was 98%. After 2-stage TKA, the mean knee ROM was 119.4° (range, 80°–140°) and the mean Knee Society (KS) knee score was 90.4, the average KS function score was 84.7, the average Hospital for Special Surgery (HSS) score was 87.2, and the average Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score was 16.7. The KS function scores (P = .029) and the WOMAC scores (P = .022) were significantly better in 17 patients who underwent ALCS insertion within 30 days of infection diagnosis compared to the other 33 patients. Conclusions: The 2-stage primary TKA for patients with infected knee arthritis with coexisting joint destruction showed satisfactory outcomes with a low infection recurrence. However, constrained prostheses or augmentation use may be necessary. Notably, some functional scores were better in the group that underwent ALCS insertion relatively early after the infection diagnosis.

Introduction Low-dose radiation therapy (LDRT) for osteoarthritis (OA) has been performed for several decades. However, supporting evidence from randomised studies using modern methodologies is lacking, and a recently published randomised study failed to show the significant benefit of LDRT. The presented trial aims to evaluate the efficacy and safety of LDRT for patients with knee OA.Methods and analysis This prospective, multicentre, randomised trial will be conducted in the Republic of Korea. A total of 114 participants will be randomly assigned (1:1:1) to receive sham irradiation, 0.3 Gy/6 fractions of LDRT or 3 Gy/6 fractions of LDRT. Key inclusion criteria are primary knee OA with Kellgren-Lawrence grade 2–3 and visual analogue scale 50–90 when walking at the baseline. The primary endpoint is the rate of responders at 4 months after LDRT according to the OARSI-OMERACT criteria. Concomitant use of analgesics is prohibited until the primary efficacy evaluation is scheduled.Ethics and dissemination Currently, approval from the Ministry of Food and Drug Safety of the Republic of Korea and the institutional review board of each participating hospital has been obtained. Patient enrolment began in October 2022 and is ongoing at three participating sites. The results will be disseminated to academic audiences and the public via publication in an international peer-reviewed journal and presentation at conferences. This trial will provide valuable information on the safety and efficacy of LDRT for patients with knee OA.Trial registration number NCT05562271.

Objectives: We investigated whether nanopore 16S amplicon sequencing is capable of bacterial identification in patients with knee prosthetic joint infection (PJI), and we compared its efficacy with conventional culture studies. Methods: In total, 36 patients who had clinical manifestation suspected of PJI were enrolled in this study. To begin, synovial fluids were aspirated from the affected knee using aseptic technique and tissues specimens were obtained during the surgery. Next, DNA was extracted from the synovial fluid or tissues, and 16S rDNA PCR was performed. In PCR positive cases, nanopore amplicon sequencing was then performed for up to 3 h. The results of amplicon sequencing were compared to those of conventional culture studies. Results: Of the 36 patients enrolled, 22 were classified as true infections according to the MSIS criteria whereas 14 were considered uninfected. Among the 22 PJI cases, 19 cases were culture positive (CP-PJI) while three cases were culture negative (CN-PJI). In 14 of 19 (73.7 %) CP- PJI cases, 16S sequencing identified concordant bacteria with conventional culture studies with a significantly shorter turnaround time. In some cases, nanopore 16S sequencing was superior to culture studies in the species-level identification of pathogen and detection of polymicrobial infections. Altogether, in the majority of PJI candidate patients (32 of 36, 88.9 %), 16S sequencing achieved identical results to cultures studies with a significantly reduced turnaround time (100.9 ± 32.5 h vs. 10.8 ± 7.7 h, p

BackgroundDelirium is a neuropsychiatric condition strongly associated with poor clinical outcomes such as high mortality and long hospitalization. In the patients with Coronavirus disease 2019 (COVID-19), delirium is common and it is considered as one of the risk factors for mortality. For those admitted to negative-pressure isolation units, a reliable, validated and contact-free delirium screening tool is required.Materials and methodsWe prospectively recruited eligible patients from multiple medical centers in South Korea. Delirium was evaluated using the Confusion Assessment Method (CAM) and 4‘A’s Test (4AT). The attentional component of the 4AT was modified such that respondents are required to count days, rather than months, backward in Korean. Blinded medical staff evaluated all patients and determined whether their symptoms met the delirium criteria of the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5). An independent population of COVID-19 patients was used to validate the 4AT as a remote delirium screening tool. We calculated the area under the receiver operating characteristic curve (AUC).ResultsOut of 286 general inpatients, 28 (9.8%) inpatients had delirium. In this population, the patients with delirium were significantly older (p = 0.018) than the patients without delirium, and higher proportion of males were included in the delirium group (p < 0.001). The AUC of the 4AT was 0.992 [95% confidence interval (CI) 0.983–1.000] and the optimal cutoff was at 3. Of the independent COVID-19 patients, 13 of 108 (12.0%) had delirium. Demographically, the COVID-19 patients who had delirium only differed in employment status (p = 0.047) from the COVID-19 patients who did not have delirium. The AUC for remote screening using the 4AT was 0.996 (0.989–1.000). The optimal cutoff of this population was also at 3.ConclusionThe modified K-4AT had acceptable reliability and validity when used to screen inpatients for delirium. More importantly, the 4AT efficiently screened for delirium during remote evaluations of COVID-19 patients, and the optimal cutoff was 3. The protocol presented herein can be used for remote screening of delirium using the 4AT.

Abstract Purpose Even today, total knee arthroplasty (TKA) is associated with venous thromboembolism (VTE). The purpose of our study is to report the incidence of postoperative VTE and to compare the efficacy of commonly used orally administered antithrombotic agents. Materials and methods Seven hundred ad ninety-nine patients who underwent primary TKA were retrospectively reviewed. The patients were prescribed one of three antithrombotic agents: aspirin (n = 168), rivaroxaban (n = 117), or apixaban (n = 514). Before surgery, patient demographics and risk factors were matched via propensity scoring. After surgery, all three groups took the agent for 7 days and underwent ultrasonography to check for VTE. Results The overall incidence of postoperative VTE was 15.4% (123/799). Only one patient developed symptomatic VTE. Female sex and staged bilateral TKA were risk factors for postoperative VTE. The postoperative VTE rates in the aspirin, rivaroxaban, and apixaban groups were 16.2%, 6.0%, and 17.1%, respectively, significantly lower in the rivaroxaban group (p

The purposes of this study were to develop a cruciate-retaining total knee arthroplasty musculoskeletal model, which enables the adjustment of ligament length and implant alignment; validate the model; and evaluate the effects of varus/valgus alignment adjustment and unbalanced medial/lateral ligament laxity during gait. A cruciate-retaining total knee arthroplasty musculoskeletal model was constructed and validated against the in vivo contact forces. This model was transformed to 2° varus/valgus alignment of femoral or tibial replacement models and 2° medial/lateral laxity models. The contact forces and ligament tensions of the adjusted models were calculated. The contact forces in the model showed good agreement with the in vivo contact forces. Valgus replacement alignment with balanced ligament models showed a lower contact force at the medial compartment than at the neutral alignment model, whereas the varus replacement alignment with balanced ligament models showed a greater contact force at the medial compartment and medial/posterior cruciate ligament tension. The medial laxity with neutral alignment model showed a similar contact force with decreased medial ligament tension compared to the balanced neutral alignment model, whereas the lateral laxity with the neutral alignment model showed a greater contact force and decreased lateral ligament tension. The cruciate-retaining total knee arthroplasty model was validated using in vivo contact forces (r = 0.939) Two degrees of valgus alignment adjustment with balanced ligament or neutral alignment with 2° of medial laxity can be safe without increasing contact force or ligament tension compared to neutral alignment with a balanced extension gap. However, 2° of varus alignment adjustment with balanced ligament or neutral alignment with 2° of lateral laxity may be unfavorable due to the overloading of the joints and knee ligaments.

Aging is a major risk factor for hypertension and atherosclerosis, and vascular smooth muscle cell (VSMC) senescence can promote aging‐related vascular diseases. Sirtuin‐1 (SIRT1) and AMP‐activated protein kinase (AMPK) were previously reported to modulate vascular senescence; however, its effects have not been well characterized. To determine the nature of the interaction between SIRT1 and AMPK in VSMC senescence, we investigated the effects of SRT1720 on its downstream targets of SIRT1 and the phosphorylation of AMPKα at Ser485. During Adriamycin‐induced VSMC senescence, SRT1720 increased the activity of SIRT1 and AMPKα phosphorylation at Ser485 via the cAMP–protein kinase A (PKA) pathway. Telomere length and telomerase reverse transcriptase expression were increased by SIRT1 activation with SRT1720. Taken together, these data show that activation of the SIRT1/cAMP–PKA/p‐AMPKα (Ser485) pathway may be an effective antisenescence mechanism for VSMCs.

Knee osteoarthritis (KOA) is a leading cause of disability among elderly adults, and it causes pain and discomfort and limits the functional independence of such adults. The aim of this study was the development of an automated classification model for KOA, based on the Kellgren-Lawrence (KL) grading system, using radiographic imaging and gait analysis data. Gait features highly associated with the radiological severity of KOA identified from our previous study, in addition to radiographic image features extracted from a deep learning network, namely, Inception-ResNet-v2, were exploited using a support vector machine for KOA multi-classification. The area under the curve (AUC) of the receiver operating characteristic curve from KL Grades 0-4 were 0.93, 0.82, 0.83, 0.88, and 0.97, respectively. The sensitivity, precision, and F1-score of the model were 0.70, 0.76, and 0.71, respectively. The proposed model outperformed a common deep learning approach that is based on using only radiographic images as the input data. This result indicates that gait data and radiographic images are complementary with respect to KOA classification, and the use of both data can improve the accuracy of the automated diagnosis of multiclass KOA.

Abstract Purpose The aim of this study was to compare the following three analgesic methods after Total knee arthroplasty (TKA): intravenous patient‐controlled analgesia (IV‐PCA), continuous adductor canal block (C‐ACB), and intravenous patient‐controlled analgesia combined with single shot adductor canal block (PCA + sACB). Methods Records of 482 patients undergoing primary TKA from September 2019 to September 2020 were analyzed. Patients were divided into three pain control groups: IV‐PCA (n = 180), C‐ACB (n = 173) and PCA + sACB (n = 129). Single shot adductor canal block was performed 24 h after surgery in the PCA + sACB group. Rescue opioid consumption, breakthrough pain, pain numerical rating scale (NRS), and anti‐emetics administration were measured from postoperative day (POD) 1 to POD 5. Results Rescue opioid consumption was less in C‐ACB or PCA + sACB group than in the IV‐PCA group at POD1 (p 5) than the IV‐PCA group at POD1 (p = 0.007). On POD2, C‐ACB was statistically superior to IV‐PCA (p = 0.011) in terms of breakthrough pain. Postoperative pain NRS was lower in the C‐ACB and PCA + sACB groups than in the IV‐PCA group (p = 0.025 and p = 0.019, respectively). The total number of anti‐emetics consumption was lower in C‐ACB and PCA + sACB groups than in the IV‐PCA group (p = 0.003 and p = 0.002, respectively). Conclusion PCA + sACB not only reduced patients’ need for rescue opioids, but also decreased the number of breakthrough pain and anti‐emetics compared to IV‐PCA in early postoperative days after TKA. However, C‐ACB and PCA + sACB did not differ significantly in analgesic efficacy or opioid‐related side effects. PCA + sACB can be as effective as C‐ACB for patients undergoing TKA. Level of evidence Retrospective cohort study, level III.

Jellyfish stings can result in local tissue damage and systemic pathophysiological sequelae. Despite constant occurrences of jellyfish stings in oceans throughout the world, the toxinological assessment of these jellyfish envenomations has not been adequately reported in quantitative as well as in qualitative measurements. Herein, we have examined and compared the in vivo toxic effects and pathophysiologic alterations using experimental animal models for two representative stinging jellyfish classes, i.e., Cubozoa and Scyphozoa. For this study, mice were administered with venom extracts of either Carybdea brevipedalia (Cnidaria: Cubozoa) or Nemopilema nomurai (Cnidaria: Scyphozoa). From the intraperitoneal (IP) administration study, the median lethal doses leading to the deaths of mice 24 h post-treatment after (LD50) for C. brevipedalia venom (CbV) and N. nomurai venom (NnV) were 0.905 and 4.4697 mg/kg, respectively. The acute toxicity (i.e., lethality) of CbV was much higher with a significantly accelerated time to death value compared with those of NnV. The edematogenic activity induced by CbV was considerably (83.57/25 = 3.343-fold) greater than NnV. For the evaluation of their dermal toxicities, the epidermis, dermis, subcutaneous tissues, and skeletal muscles were evaluated toxinologically/histopathologically following the intradermal administration of the venoms. The minimal hemorrhagic doses (MHD) of the venoms were found to be 55.6 and 83.4 μg/mouse for CbV and NnV, respectively. Furthermore, the CbV injection resulted in extensive alterations of mouse dermal tissues, including severe edema, and hemorrhagic/necrotic lesions, with the minimum necrotizing dose (MND) of 95.42 µg/kg body weight. The skin damaging effects of CbV appeared to be considerably greater, compared with those of NnV (MND = 177.99 µg/kg). The present results indicate that the toxicities and pathophysiologic effects of jellyfish venom extracts may vary from species to species. As predicted from the previous reports on these jellyfish envenomations, the crude venom extracts of C. brevipedalia exhibit much more potent toxicity than that of N. nomurai in the present study. These observations may contribute to our understanding of the toxicities of jellyfish venoms, as well as their mode of toxinological actions, which might be helpful for establishing the therapeutic strategies of jellyfish stings.

Background and Objectives: The number of patients who undergo multiple operations on a knee is increasing. The objective of this study was to develop a deep learning algorithm that could detect 17 different surgical implants on plain knee radiographs. Materials and Methods: An internal dataset consisted of 5206 plain knee antero-posterior X-rays from a single, tertiary institute for model development. An external set contained 238 X-rays from another tertiary institute. A total of 17 different types of implants including total knee arthroplasty, unicompartmental knee arthroplasty, plate, and screw were labeled. The internal dataset was approximately split into a train set, a validation set, and an internal test set at a ratio of 7:1:2. You Only look Once (YOLO) was selected as the detection network. Model performances with the validation set, internal test set, and external test set were compared. Results: Total accuracy, total sensitivity, total specificity value of the validation set, internal test set, and external test set were (0.978, 0.768, 0.999), (0.953, 0.810, 0.990), and (0.956, 0.493, 0.975), respectively. Means ± standard deviations (SDs) of diagonal components of confusion matrix for these three subsets were 0.858 ± 0.242, 0.852 ± 0.182, and 0.576 ± 0.312, respectively. True positive rate of total knee arthroplasty, the most dominant class of the dataset, was higher than 0.99 with internal subsets and 0.96 with an external test set. Conclusion: Implant identification on plain knee radiographs could be automated using a deep learning technique. The detection algorithm dealt with overlapping cases while maintaining high accuracy on total knee arthroplasty. This could be applied in future research that analyzes X-ray images with deep learning, which would help prompt decision-making in clinics.

Although various quality by design (QbD) approaches have been used to establish a design space to obtain robust drug formulation and process parameters, the effect of excipient variability on the design space and drug product quality is unclear. In this study, the effect of microcrystalline cellulose (MCC) variability on drug product quality was examined using a design space for immediate-release tablets of amlodipine besylate. MCC variability was assessed by altering the manufacturer and grade. The formulation was developed by employing the QbD approach, which was optimized using a D-optimal mixture design. Using 36 different MCCs, the effect of MCC variability on the design space was assessed. The design space was shifted by different manufacturers and grades of MCC, which resulted in associations between the physicochemical properties of MCC and critical quality attributes (CQAs). The correlation between the physicochemical properties of MCCs and CQAs was assessed through a statistical analysis. A predictive model correlating the physicochemical properties of MCCs with dissolution was established using an artificial neural network (ANN). The ANN model accurately predicted dissolution with low absolute and relative errors. The present study described a comprehensive QbD approach, statistical analysis, and ANN to comprehend and manage the effect of excipient variability on the design space.

The current study was to understand how process variables of high shear wet granulations affect physical properties of granules and tablets. The knowledge gained was intended to be used for Quality-by-Design based process design and optimization. The variables were selected based on the risk assessment as impeller speed, liquid addition rate, and wet massing time. Formulation compositions were kept constant to minimize their influence on granules properties. Multiple linear regression models were built providing understanding of the impact of each variable on granule hardness, Carr's index, tablet tensile strength, surface mean diameter of granules, and compression behavior. The experimental results showed that the impact of impeller speed was more dominant compared to wet massing time and water addition rate. The results also revealed that quality of granules and tablets could be optimized by adjusting specific process variables (impeller speed 1193 rpm, water spray rate 3.7 ml/min, and wet massing time 2.84 min). Overall desirability was 0.84 suggesting that the response values were closer to the target one. The SEM image of granules showed that spherical and smooth granules produced at higher impeller speed, whereas rough and irregular shape granules at lower speed. Moreover, multivariate data analysis demonstrated that impeller speed and massing time had strong correlation with the granule and tablet properties. In overall, the combined experimental design and principal component analysis approach allowed to better understand the correlation between process variables and granules and tablet attributes. Keywords: Experimental design, Principal component analysis, High shear granulation, Process parameter

We previously demonstrated that Nemopilema nomurai jellyfish venom metalloproteinases (JVMPs) play a key role in the toxicities induced by N. nomurai venom (NnV), including dermotoxicity, cytotoxicity, and lethality. In this study, we identified two full-length JVMP cDNA and genomic DNA sequences: JVMP17-1 and JVMP17-2. The full-length cDNA of JVMP17-1 and 17-2 contains 1614 and 1578 nucleotides (nt) that encode 536 and 525 amino acids, respectively. Putative peptidoglycan (PG) binding, zinc-dependent metalloproteinase, and hemopexin domains were identified. BLAST analysis of JVMP17-1 showed 42, 41, 37, and 37% identity with Hydra vulgaris, Acropora digitifera, Megachile rotundata, and Apis mellifera venom metalloproteinases, respectively. JVMP17-2 shared 38 and 36% identity with H. vulgaris and A. digitifera, respectively. Alignment results of JVMP17-1 and 17-2 with other metalloproteinases suggest that the PG domain, the tissue inhibitor of metalloproteinase (TIMP)-binding surfaces, active sites, and metal (ion)-binding sites are highly conserved. The present study reports the gene cloning of metalloproteinase enzymes from jellyfish species for the first time. We hope these results can expand our knowledge of metalloproteinase components and their roles in the pathogenesis of jellyfish envenomation.