[Simultaneous determination of 31 banned veterinary drugs during egg-laying period in poultry eggs by ultra performance liquid chromatography-tandem mass spectrometry].

The consumption of poultry eggs has increased in recent years owing to the abundance of production and improvements in living standards. Thus, the safety requirements of poultry eggs have gradually increased. At present, few reports on analytical methods to determine banned veterinary drugs during egg-laying period in poultry eggs have been published. Therefore, establishing high-throughput and efficient screening methods to monitor banned veterinary drugs during egg-laying period is imperative. In this study, an analytical method based on ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) combined with QuEChERS-based techniques was developed for the simultaneous determination of 31 banned veterinary drugs encompassing nine drug classes (macrolides, antipyretic and analgesic drugs, sulfonamides, antibacterial synergists, anticoccidials, antinematodes, quinolones, tetracyclines, amphenicols) in different types of poultry eggs. The main factors affecting the response, recovery, and sensitivity of the method, such as the extraction solvent, purification adsorbent, LC separation conditions, and MS/MS parameters, were optimized during sample pretreatment and instrumental analysis. The 31 veterinary drug residues in 2.00 g eggs were extracted with 2 mL of 0.1 mol/L ethylene diamine tetraacetic acid disodium solution and 8 mL 3% acetic acid acetonitrile solution, and salted out with 2 g of sodium chloride. After centrifugation, 5 mL of the supernatant was cleaned-up using the QuEChERS method with 100 mg of octadecylsilane-bonded silica gel (C18), 50 mg of N-propylethylenediamine (PSA), and 50 mg of NH2-based sorbents. After nitrogen blowing and redissolution, the 31 target analytes were separated on a Waters CORTECS UPLC C18 analytical chromatographic column (150 mm×2.1 mm, 1.8 µm) at a flow rate, column temperature, and injection volume of 0.4 mL/min, 30 ℃, and 5 µL, respectively. Among these analytes, 26 analytes were acquired in dynamic multiple reaction monitoring (MRM) mode under positive electrospray ionization (ESI+) conditions using (A) 5 mmol/L ammonium acetate (pH 4.5) and (B) acetonitrile as mobile phases. The gradient elution program was as follows: 0-2.0 min, 12%B-30%B; 2.0-7.5 min, 30%B-50%B; 7.5-10.0 min, 50%B; 10.0-10.1 min, 50%B-100%B; 10.1-12.0 min, 100%B; 12.0-12.1 min, 100%B-12%B; The five other target analytes were acquired in MRM mode under negative electrospray ionization (ESI-) conditions using (A) H2O and (B) acetonitrile as mobile phases. The gradient elution program was as follows: 0-2.0 min, 12%B-40%B; 2.0-6.0 min, 40%B-80%B; 6.0-6.1 min, 80%B-100%B; 6.1-8.0 min, 100%B; 8.0-8.1 min, 100%B-12%B. Matrix-matched external standard calibration was used for quantification. The results showed that all the compounds had good linear relationships within their respective ranges, with correlation coefficients of >0.99. The limits of detection (LODs) and quantitation (LOQs) were 0.3-3.0 µg/kg and 1.0-10.0 µg/kg, respectively. The average recoveries of the 31 banned veterinary drugs spiked at three levels (LOQ, maximum residue limit (MRL), and 2MRL) in poultry eggs ranged from 61.2% to 105.7%, and the relative standard deviations (RSDs) ranged from 1.8% to 17.6%. The developed method was used to detect and analyze banned veterinary drugs in 30 commercial poultry egg samples, including 20 eggs, 5 duck eggs, and 5 goose eggs. Enrofloxacin was detected in one egg with a content of 12.3 µg/kg. The proposed method is simple, economical, practical, and capable of the simultaneous determination of multiple classes of banned veterinary drugs in poultry eggs.

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid.

Due to theintricate and interdependent nature of the smart grid, it has encountered an increasing number of security threats in recent years. Currently, conventional security measures such as firewalls, intrusion detection, and malicious detection technologies offer specific protection based on their unique perspectives. However, as the types and concealment of attacksincrease, these measures struggle to detect them promptly and respond accordingly. In order to meet the social demand for the accuracy and computation speed of the power network security risk evaluation model, the study develops a fusion power network security risk evaluation algorithm by fusing the flash search algorithm with the support vector machine. This algorithm is then used as the foundation for building an improved power network security risk evaluation model based on the fusion algorithm.The study's improved algorithm's accuracy is 96.2%, which is higher than the accuracy of the other comparative algorithms; its error rate is 3.8%, which is lower than the error rate of the other comparative algorithms; and its loss function curve convergence is quicker than that of the other algorithms.The risk evaluation model's accuracy is 97.8%, which is higher than the accuracy of other comparative models; the error rate is 1.9%, which is lower than the error rate of other comparative models; the computing time of the improved power network security risk evaluation model is 4.4 s, which is lower than the computing time of other comparative models; and its expert score is high. These findings are supported by empirical analysis of the improved power network security risk evaluation model proposed in the study. According to the study's findings, the fusion algorithm and the upgraded power network security risk evaluation model outperform other approaches in terms of accuracy and processing speed. This allows the study's maintenance staff to better meet the needs of the community by assisting them in identifying potential security hazards early on and taking the necessary preventative and remedial action to ensure the power system's continued safe operation.

Golden-flower fungus (Eurotiwm Cristatum) presents fungal flower aroma as well as accelerates the aging of white tea (Shoumei).

Golden-flower fungus (Eurotiwm Cristatum, EC) is widely inoculated in dark tea to endow a typical fungal floral aroma. Recently, Golden Flower White Tea (GFWT), prepared by transplanting EC-mediated fermentation to white tea (Shoumei, SM) to reform the roughness and coarseness, has attracted much attention attributed to coordinated flavor. However, the bio-chemistry reactions between EC and SM, along with origination of composited aroma are still unclear. Thus, the rejected EC, GFWT leaves and stems after EC removal were separated by layer-by-layer stripping following sensory evaluation, volatiles and microstructure analysis to uncover aroma formation mechanism. In GFWT, EC presents fungal flower aroma rather than contribution of extracellular enzymes secreted by fungus in Fu brick tea. Moreover, the short "flowering process" (7 days) endows SM with a stale, jujube, and sweet aroma, which is regarded as the typical characteristic of aged white tea. This inspires EC-mediated fermentation as a promising rapid aging process.

Limitations and modifications in the clinical application of calcium sulfate.

Calcium sulfate and calcium sulfate-based biomaterials have been widely used in non-load-bearing bone defects for hundreds of years due to their superior biocompatibility, biodegradability, and non-toxicity. However, lower compressive strength and rapid degradation rate are the main limitations in clinical applications. Excessive absorption causes a sharp increase in sulfate ion and calcium ion concentrations around the bone defect site, resulting in delayed wound healing and hypercalcemia. In addition, the space between calcium sulfate and the host bone, resulting from excessively rapid absorption, has adverse effects on bone healing or fusion techniques. This issue has been recognized and addressed. The lack of sufficient mechanical strength makes it challenging to use calcium sulfate and calcium sulfate-based biomaterials in load-bearing areas. To overcome these defects, the introduction of various inorganic additives, such as calcium carbonate, calcium phosphate, and calcium silicate, into calcium sulfate is an effective measure. Inorganic materials with different physical and chemical properties can greatly improve the properties of calcium sulfate composites. For example, the hydrolysis products of calcium carbonate are alkaline substances that can buffer the acidic environment caused by the degradation of calcium sulfate; calcium phosphate has poor degradation, which can effectively avoid the excessive absorption of calcium sulfate; and calcium silicate can promote the compressive strength and stimulate new bone formation. The purpose of this review is to review the poor properties of calcium sulfate and its complications in clinical application and to explore the effect of various inorganic additives on the physicochemical properties and biological properties of calcium sulfate.

Application of chiral stationary phases for the separation of vitamin A acetate isomers.

The separation of vitamin A acetate isomers is essential for quality assurance of e.g. nutrition supplements, cosmetics, and pharmaceutical ingredients. High performance liquid chromatography (HPLC) is currently the most suitable analytical method for tackling this challenging separation task. However, the existing methods based on normal phase chromatography (NPC) are poorly reproducible due to the typical disadvantages of NPC, such as long equilibration times and fluctuation in retention factors. A new reversed phase method developed in our labs allows the separation of the isomers applying a chiral stationary phase (CSP). This phase consists of an immobilized polysaccharide which can be used in every chromatographic mode. However, they are not typically used in reversed phase mode. Through the screening of various stationary phases with different polysaccharide based chiral selectors, the choice of the ideal stationary phase could be confirmed, allowing to draw conclusions about the retention mechanism. The CSP Chiralpak IG-3 was found to be the most suitable among the examined. Regarding the separation mechanism, the spatial helical structure of the polysaccharide derivatives was confirmed to be of particular significance. In addition to the stationary phase, the mobile phase was tested for optimization regarding composition, gradient parameters as well as temperature using chromatographic method optimization software for the sake of method robustness.

Microfluidic strategies for biomimetic lung chip establishment and SARS-CoV2 study.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), characterized by its high fatality rate and contagious nature, has led to significant morbidity and mortality worldwide, significantly impacting both our daily lives and public health. The respiratory pathway serves as the primary route for SARS-CoV2 propagation within the human body, with the lung acting as the initial target organ. Simultaneously, the lung functions as a protective barrier, preventing the entry of viruses into the bloodstream through the alveolar-capillary barrier. Bioengineered microfluidic lung chips, utilizing advanced near-to-native technologies, offer a novel perspective for comprehending the intricate workings of human lungs and facilitating the discovery of anti-coronavirus drugs to combat the challenges posed by coronavirus disease 2019 (COVID-19). This review aims to introduce the key elements and design types of artificial lung chips that closely resemble in vivo-like niches in terms of both structure and function. Furthermore, quantitative and qualitative techniques for evaluating the functionality of the alveolar-capillary barrier are summarized, confirming the successful construction of lung chip systems through engineering approaches. The prospects and persistent challenges associated with establishing next-generation artificial lung models to meet the demands of virology studies are also discussed.

Silicone rubber sealed channel induced self-healing of large bone defects: Where is the limit of self-healing of bone?

Background: Large defects of long tubular bones due to severe trauma, bone tumor resection, or osteomyelitis debridement are challenging in orthopedics. Bone non-union and other complications often lead to serious consequences. At present, autologous bone graft is still the gold standard for the treatment of large bone defects. However, autologous bone graft sources are limited. Silicon rubber (SR) materials are widely used in biomedical fields, due to their safety and biocompatibility, and even shown to induce nerve regeneration. Materials and methods: We extracted rat bone marrow mesenchymal stem cells (BMMSCs) in vitro and verified the biocompatibility of silicone rubber through cell experiments. Then we designed a rabbit radius critical sized bone defect model to verify the effect of silicone rubber sealed channel inducing bone repair in vivo. Results: SR sealed channel could prevent the fibrous tissue from entering the fracture end and forming bone nonunion, thereby inducing self-healing of long tubular bone through endochondral osteogenesis. The hematoma tissue formed in the early stage was rich in osteogenesis and angiogenesis related proteins, and gradually turned into vascularization and endochondral osteogenesis, and finally realized bone regeneration. Conclusions: In summary, our study proved that SR sealed channel could prevent the fibrous tissue from entering the fracture end and induce self-healing of long tubular bone through endochondral osteogenesis. In this process, the sealed environment provided by the SR channel was key, and this might indicate that the limit of self-healing of bone exceeded the previously thought. The translational potential of this article: This study investigated a new concept to induce the self-healing of large bone defects. It could avoid trauma caused by autologous bone extraction and possible rejection reactions caused by bone graft materials. Further research based on this study, including the innovation of induction materials, might invent a new type of bone inducing production, which could bring convenience to patients. We believed that this study had significant meaning for the treatment of large bone defects in clinical practice.

Neuron Navigator 1 (Nav1) regulates the response to cocaine in mice.

Genetic variation accounts for much of the risk for developing a substance use disorder, but the underlying genetic factors and their genetic effector mechanisms are mostly unknown. Inbred mouse strains exhibit substantial and heritable differences in the extent of voluntary cocaine self-administration. Computational genetic analysis of cocaine self-administration data obtained from twenty-one inbred strains identified Nav1, a member of the neuron navigator family that regulates dendrite formation and axonal guidance, as a candidate gene. To test this genetic hypothesis, we generated and characterized Nav1 knockout mice. Consistent with the genetic prediction, Nav1 knockout mice exhibited increased voluntary cocaine intake and had increased motivation for cocaine consumption. Immunohistochemistry, electrophysiology, and transcriptomic studies were performed as a starting point for investigating the mechanism for the Nav1 knockout effect. Nav1 knockout mice had a reduced inhibitory synapse density in their cortex, increased excitatory synaptic transmission in their cortex and hippocampus, and increased excitatory neurons in a deep cortical layer. Collectively, our results indicate that Nav1 regulates the response to cocaine, and we identified Nav1 knockout induced changes in the excitatory and inhibitory synaptic balance in the cortex and hippocampus that could contribute to this effect.

Theoretical studies of magneto-optical Kerr and Faraday effects in two-dimensional second-order topological insulators.

Optical approaches are useful for studying the electronic and spin structure of materials. Here, based on the tight-binding model and linear response theory, we investigate the magneto-optical Kerr and Faraday effects in two-dimensional second-order topological insulators (SOTI) with external magnetization. We find that orbital-dependent Zeeman term induces band crossings for SOTI phase, which are absent for trivial phase. In the weak-magnetization regime, these crossings give rise to giant jumps (peaks) of Kerr and Faraday angles (ellipticity) for SOTI phase. In the strong-magnetization regime, we find that two nearly flat bands are formed at the high-symmetry point of Brillouin zone of SOTI phase. These flat bands give rise to two successive giant jumps (peaks) of Kerr and Faraday angles (ellipticity). These phenomena provide new possibilities to characterize and detect the two-dimensional SOTI phase.

Anthocyanin metabolism and its differential regulation in purple tea (Camellia sinensis).

Tea plants (Camellia sinensis) typically contain high-flavonoid phytochemicals like catechins. Recently, new tea cultivars with unique purple-colored leaves have gained attention. These purple tea cultivars are enriched with anthocyanin, which provides an interesting perspective for studying the metabolic flux of the flavonoid pathway. An increasing number of studies are focusing on the leaf color formation of purple tea and this review aims to summarize the latest progress made on the composition and accumulation of anthocyanins in tea plants. In addition, the regulation mechanism in its synthesis will be discussed and a hypothetical regulation model for leaf color transformation during growth will be proposed. Some novel insights are presented to facilitate future in-depth studies of purple tea to provide a theoretical basis for targeted breeding programs in leaf color.

Lumbar Extensor and Flexor Muscle Structural Changes in Young Female Nurses with Chronic Bilateral Non-Specific Low Back Pain: A Case-Control Study.

BACKGROUND: Muscle structural studies on non-specific low back pain in young female nurses are rare. This study aimed to investigate the changes of lumbar extensor and flexor muscle cross-sectional area and fatty infiltration in young female nurses with chronic bilateral non-specific low back pain by lumbar spine magnetic resonance imaging to speculate on the possible pathogenesis. METHODS: The magnetic resonance imaging (MRI) data of 58 female nurses with chronic bilateral non-specific low back pain and 60 healthy female controls were analyzed retrospectively. The lumbar extensor and flexor muscle cross-sectional area/intervertebral disc cross-sectional area ratio, as well as magnetic resonance imaging signal intensity of lumbar extensor (erector spinae; multifidus) and flexor muscles (psoas muscle) were measured, calculated and compared between nurses and healthy controls by independent samples t-test. In addition, each mean MRI signal intensity of lumbar extensor or flexor muscles in nurses at different anatomical segments from lumbar vertebrae 2 (L2)-L3 to L5-sacral vertebrae 1 (S1) was also compared, and one-way Analysis of Variance (ANOVA) analyzed the mean MRI signal intensity between muscles in nurses with multiple comparisons. RESULTS: There was no significant difference in lumbar extensor and flexor muscle cross-sectional area/intervertebral disc cross-sectional area ratio between nurses with chronic bilateral non-specific low back pain and healthy controls, p > 0.01. The magnetic resonance imaging signal intensity in lumbar extensor and flexor muscle was significantly higher in nurses with chronic bilateral non-specific low back pain than in healthy controls, p < 0.01. The MRI signal intensity of lumbar extensor muscle at the lower lumbar segments was higher than at the upper ones. The magnetic resonance imaging signal intensity of the extensor muscle (erector spinae; multifidus) was significantly higher than that of the flexor muscle (psoas muscle), p < 0.01. CONCLUSIONS: This study showed that young nurses with chronic bilateral non-specific low back pain have lumbar extensor and flexor muscle fatty infiltration without muscle atrophy. We hypothesized that muscle fatty infiltration may occur prior to muscle atrophy. Therefore, the high fatty infiltration of the lumbar extensor and flexor muscle may be a cause or a result of chronic bilateral non-specific low back pain in young nurses.

Ultrasound image-based deep learning to assist in diagnosing gross extrathyroidal extension thyroid cancer: a retrospective multicenter study.

Background: The presence of gross extrathyroidal extension (ETE) in thyroid cancer will affect the prognosis of patients, but imaging examination cannot provide a reliable diagnosis for it. This study was conducted to develop a deep learning (DL) model for localization and evaluation of thyroid cancer nodules in ultrasound images before surgery for the presence of gross ETE. Methods: From January 2016 to December 2021 grayscale ultrasound images of 806 thyroid cancer nodules (4451 images) from 4 medical centers were retrospectively analyzed, including 517 no gross ETE nodules and 289 gross ETE nodules. 283 no gross ETE nodules and 158 gross ETE nodules were randomly selected from the internal dataset to form a training set and validation set (2914 images), and a multitask DL model was constructed for diagnosing gross ETE. In addition, the clinical model and the clinical and DL combined model were constructed. In the internal test set [974 images (139 no gross ETE nodules and 83 gross ETE nodules)] and the external test set [563 images (95 no gross ETE nodules and 48 gross ETE nodules)], the diagnostic performance of DL model was verified based on the pathological results. And then, compared the results with the diagnosis by 2 senior and 2 junior radiologists. Findings: In the internal test set, DL model demonstrated the highest AUC (0.91; 95% CI: 0.87, 0.96), which was significantly higher than that of two senior radiologists [(AUC, 0.78; 95% CI: 0.71, 0.85; P < 0.001) and (AUC, 0.76; 95% CI: 0.70, 0.83; P < 0.001)] and two juniors radiologists [(AUC, 0.65; 95% CI: 0.58, 0.73; P < 0.001) and (AUC, 0.69; 95% CI: 0.62, 0.77; P < 0.001)]. DL model was significantly higher than clinical model [(AUC, 0.84; 95% CI: 0.79, 0.89; P = 0.019)], but there was no significant difference between DL model and clinical and DL combined model [(AUC, 0.94; 95% CI: 0.91, 0.97; P = 0.143)]. In the external test set, DL model also demonstrated the highest AUC (0.88, 95% CI: 0.81, 0.94), which was significantly higher than that of one of senior radiologists [(AUC, 0.75; 95% CI: 0.66, 0.84; P = 0.008) and (AUC, 0.81; 95% CI: 0.72, 0.89; P = 0.152)] and two junior radiologists [(AUC, 0.72; 95% CI: 0.62, 0.81; P = 0.002) and (AUC, 0.67; 95 CI: 0.57, 0.77; P < 0.001]. There was no significant difference between DL model and clinical model [(AUC, 0.85; 95% CI: 0.79, 0.91; P = 0.516)] and clinical + DL model [(AUC, 0.92; 95% CI: 0.87, 0.96; P = 0.093)]. Using DL model, the diagnostic ability of two junior radiologists was significantly improved. Interpretation: The DL model based on ultrasound imaging is a simple and helpful tool for preoperative diagnosis of gross ETE thyroid cancer, and its diagnostic performance is equivalent to or even better than that of senior radiologists. Funding: Jiangxi Provincial Natural Science Foundation (20224BAB216079), the Key Research and Development Program of Jiangxi Province (20181BBG70031), and the Interdisciplinary Innovation Fund of Natural Science, Nanchang University (9167-28220007-YB2110).

Polysaccharides from Fu brick tea ameliorate obesity by modulating gut microbiota and gut microbiota-related short chain fatty acid and amino acid metabolism.

Fu brick tea (FBT) is a traditional tea manufactured by solid-state fermentation of tea leaves (Camellia sinensis). Although anti-obesity effects have been reported for FBT, the associated role of FBT polysaccharides (PSs) and the underlying mechanisms remain unknown. In this study, we found that FBTPSs inhibited obesity, hyperlipidemia, and inflammation; improved intestinal barrier function; and alleviated gut microbiota dysbiosis in high-fat diet-fed rats. Akkermansia muciniphila, Bacteroides, Parasutterella, Desulfovibrio, and Blautia were the core microbes regulated by FBTPSs. FBTPSs regulated the production of gut microbiota-related metabolites, including short-chain fatty acids (SCFAs), branched-chain amino acids, and aromatic amino acids throughout the development of obesity, and regulated the SCFA-GPR signaling pathway. FBTPS-treated fecal microbiota transplant ameliorated obesity, alleviated gut microbiota dysbiosis, and improved gut microbiota-associated metabolites, suggesting that the anti-obesity effect of FBTPSs was gut microbiota-dependent. FBTPSs may serve as novel prebiotic agents for the treatment of obesity and dysbiosis of gut microbiota.

Effects of exogenous melatonin on body mass and thermogenesis in red-backed vole (Eothenomys miletus) between Kunming and Dali regions.

Melatonin (MEL) is an indole hormone synthesized and secreted by the pineal gland at night, which is involved in the regulation of body mass and thermogenesis in small mammals. To test the effects of exogenous MEL on body mass and thermogenic ability in two different red-backed vole (Eothenomys miletus) populations from two different regions (Kunming [KM] and Dali [DL]) with different annual variation in climatic variables, such as temperature, sunshine and rainfall. we traced the changes of energy balance in E. miletus from KM and DL, which were placed at 25 ± 1°C with photoperiod of 12 L:12 D, intraperitoneal injection of MEL was performed daily for 28 days. The results showed that body mass and food intake were significantly decreased, while resting metabolic rate (RMR) and nonshivering thermogenesis (NST) were significantly increased after MEL injection; Contents of total protein, mitochondrial protein, the activities of cytochrome C oxidase (COX) and α-glycerophosphate oxidase (α-PGO) in liver and brown adipose tissue (BAT) were enhanced; the activity of thyroxin 5'-deiodinase (T4 5'-DII) and uncoupling protein 1 (UCP1) in BAT were also increased. Serum leptin, triiodothyronine (T3 ) levels and T3 /T4 ratio were significantly increased, thyroxine (T4 ) levels was significantly decreased. Moreover, body mass and food intake in E. miletus from KM were higher than those from DL, but RMR and NST were lower than those from DL. Changes of body mass, food intake and thermogenic activity of KM were higher than those of DL when exposed to injection of MEL, indicating that E. miletus in KM were more sensitive to MEL. Furthermore, MEL was involved in the regulation of body mass and thermogenesis in E. miletus between KM and DL.

Major pathological remissions in a patient with stage IIIA nonsmall cell lung cancer after neoadjuvant tislelizumab combined with chemotherapy: a case report and literature review.

INTRODUCTION: Currently, there are few reports of patients with locally advanced lung cancer achieving a clinical complete response by medical treatment. Preoperative neoadjuvant immunotherapy combined with chemotherapy is an option for patients with unresectable, locally advanced nonsmall cell lung cancer (NSCLC) which is of great potential, and may change traditional treatment paradigms. There are relatively few large-scale, high-quality randomized-controlled trials yet, and limitations such as short postoperative follow-up period and immature disease-free survival and overall survival data still persist. Thus, evidence-based medical evidence is urgently needed. It is worthy to explore the further treatment of patients who achieved complete response after initial treatment, though lacking of evidence by now. CASE PRESENTATION: We report a stage IIIA lung squamous cell carcinoma case who achieved a major pathologic remission after neoadjuvant treatment with tislelizumab and chemotherapy. CONCLUSION: Our case study contributes to the existing evidence on the feasibility, efficacy and safety of neoadjuvant immunotherapy combined with chemotherapy in locally advanced unresectable NSCLC.

Successful real-world application of an osteoarthritis classification deep-learning model using 9210 knees-An orthopedic surgeon's view.

This study aimed to evaluate the performance of a deep-learning model to evaluate knee osteoarthritis using Kellgren-Lawrence grading in real-life knee radiographs. A deep convolutional neural network model was trained using 8964 knee radiographs from the osteoarthritis initiative (OAI), including 962 testing set images. Another 246 knee radiographs from the Far Eastern Memorial Hospital were used for external validation. The OAI testing set and external validation images were evaluated by experienced specialists, two orthopedic surgeons, and a musculoskeletal radiologist. The accuracy, interobserver agreement, F1 score, precision, recall, specificity, and ability to identify surgical candidates were used to compare the performances of the model and specialists. Attention maps illustrated the interpretability of the model classification. The model had a 78% accuracy and consistent interobserver agreement for the OAI (model-surgeon 1 К = 0.80, model-surgeon 2 К = 0.84, model-radiologist К = 0.86) and external validation (model-surgeon 1 К = 0.81, model-surgeon 2 К = 0.82, model-radiologist К = 0.83) images. A lower interobserver agreement was found in the images misclassified by the model (model-surgeon 1 К = 0.57, model-surgeon 2 К = 0.47, model-radiologist К = 0.65). The model performed better than specialists in identifying surgical candidates (Kellgren-Lawrence Stages 3 and 4) with an F1 score of 0.923. Our model not only had comparable results with specialists with respect to the ability to identify surgical candidates but also performed consistently with open database and real-life radiographs. We believe the controversy of the misclassified knee osteoarthritis images was based on a significantly lower interobserver agreement.

A prognostic model based on DNA methylation-related gene expression for predicting overall survival in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) continues to increase in morbidity and mortality among all types of cancer. DNA methylation, an important epigenetic modification, is associated with cancer occurrence and progression. The objective of this study was to establish a model based on DNA methylation risk scores for identifying new potential therapeutic targets in HCC and preventing cancer progression. Methods: Transcriptomic, clinical, and DNA methylation data on 374 tumor tissues and 50 adjacent normal tissues were downloaded from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma database. The gene expression profiles of the GSE54236 liver cancer dataset, which contains data on 161 liver tissue samples, were obtained from the Gene Expression Omnibus database. We analyzed the relationship between DNA methylation and gene expression levels after identifying the differentially methylated and expressed genes. Then, we developed and validated a risk score model based on the DNA methylation-driven genes. A tissue array consisting of 30 human hepatocellular carcinoma samples and adjacent normal tissues was used to assess the protein and mRNA expression levels of the marker genes by immunohistochemistry and qRT-PCR, respectively. Results: Three methylation-related differential genes were identified in our study: GLS, MEX3B, and GNA14. The results revealed that their DNA methylation levels were negatively correlated with local gene expression regulation. The gene methylation levels correlated strongly with the prognosis of patients with liver cancer. This was confirmed by qRT-PCR and immunohistochemical verification of the expression of these genes or proteins in tumors and adjacent tissues. These results revealed the relationship between the level of relevant gene methylation and the prognosis of patients with liver cancer as well as the underlying cellular and biological mechanisms. This allows our gene signature to provide more accurate and appropriate predictions for clinical applications. Conclusion: Through bioinformatics analysis and experimental validation, we obtained three DNA methylation marker: GLS, MEX3B, and GNA14. This helps to predict the prognosis and may be a potential therapeutic target for HCC patients.

Endoscopic mucosal resection-precutting vs conventional endoscopic mucosal resection for sessile colorectal polyps sized 10-20 mm.

BACKGROUND: The optimal method to remove sessile colorectal lesions sized 10-20 mm remains uncertain. Piecemeal and incomplete resection are major limitations in current practice, such as endoscopic mucosal resection (EMR) and cold or hot snare polypectomy. Recently, EMR with circumferential precutting (EMR-P) has emerged as an effective technique, but the quality of current evidence in comparative studies of conventional EMR (CEMR) and EMR-P is limited. AIM: To investigate whether EMR-P is superior to CEMR in removing sessile colorectal polyps. METHODS: This multicenter randomized controlled trial involved seven medical institutions in China. Patients with colorectal polyps sized 10-20 mm were enrolled and randomly assigned to undergo EMR-P or CEMR. EMR-P was performed following submucosal injection, and a circumferential mucosa incision (precutting) was conducted using a snare tip. Primary outcomes included a comparison of the rates of en bloc and R0 resection, defined as one-piece resection and one-piece resection with histologically assessed clear margins, respectively. RESULTS: A total of 110 patients in the EMR-P group and 110 patients in the CEMR group were finally evaluated. In the per-protocol analysis, the proportion of en bloc resections was 94.3% [95% confidence interval (CI): 88.2%-97.4%] in the EMR-P group and 86% (95%CI: 78.2%-91.3%) in the CEMR group (P = 0.041), while subgroup analysis showed that for lesions > 15 mm, EMR-P also resulted in a higher en bloc resection rate (92.0% vs 58.8% P = 0.029). The proportion of R0 resections was 81.1% (95%CI: 72.6%-87.4%) in the EMR-P group and 76.6% (95%CI: 68.8%-84.4%) in the CEMR group (P = 0.521). The EMR-P group showed a longer median procedure time (6.4 vs 3.0 min; P < 0.001). No significant difference was found in the proportion of patients with adverse events (EMR-P: 9.1%; CEMR: 6.4%; P = 0.449). CONCLUSION: In this study, EMR-P served as an alternative to CEMR for removing nonpedunculated colorectal polyps sized 10-20 mm, particularly polyps > 15 mm in diameter, with higher R0 and en bloc resection rates and without increasing adverse events. However, EMR-P required a relatively longer procedure time than CEMR. Considering its potential benefits for en bloc and R0 resection, EMR-P may be a promising technique in colorectal polyp resection.

Training a Deep Contextualized Language Model for International Classification of Diseases, 10th Revision Classification via Federated Learning: Model Development and Validation Study.

BACKGROUND: The automatic coding of clinical text documents by using the International Classification of Diseases, 10th Revision (ICD-10) can be performed for statistical analyses and reimbursements. With the development of natural language processing models, new transformer architectures with attention mechanisms have outperformed previous models. Although multicenter training may increase a model's performance and external validity, the privacy of clinical documents should be protected. We used federated learning to train a model with multicenter data, without sharing data per se. OBJECTIVE: This study aims to train a classification model via federated learning for ICD-10 multilabel classification. METHODS: Text data from discharge notes in electronic medical records were collected from the following three medical centers: Far Eastern Memorial Hospital, National Taiwan University Hospital, and Taipei Veterans General Hospital. After comparing the performance of different variants of bidirectional encoder representations from transformers (BERT), PubMedBERT was chosen for the word embeddings. With regard to preprocessing, the nonalphanumeric characters were retained because the model's performance decreased after the removal of these characters. To explain the outputs of our model, we added a label attention mechanism to the model architecture. The model was trained with data from each of the three hospitals separately and via federated learning. The models trained via federated learning and the models trained with local data were compared on a testing set that was composed of data from the three hospitals. The micro F1 score was used to evaluate model performance across all 3 centers. RESULTS: The F1 scores of PubMedBERT, RoBERTa (Robustly Optimized BERT Pretraining Approach), ClinicalBERT, and BioBERT (BERT for Biomedical Text Mining) were 0.735, 0.692, 0.711, and 0.721, respectively. The F1 score of the model that retained nonalphanumeric characters was 0.8120, whereas the F1 score after removing these characters was 0.7875-a decrease of 0.0245 (3.11%). The F1 scores on the testing set were 0.6142, 0.4472, 0.5353, and 0.2522 for the federated learning, Far Eastern Memorial Hospital, National Taiwan University Hospital, and Taipei Veterans General Hospital models, respectively. The explainable predictions were displayed with highlighted input words via the label attention architecture. CONCLUSIONS: Federated learning was used to train the ICD-10 classification model on multicenter clinical text while protecting data privacy. The model's performance was better than that of models that were trained locally.