CodonBERT: a BERT-based architecture tailored for codon optimization using the cross-attention mechanism.

MOTIVATION: Due to the varying delivery methods of messenger RNA (mRNA) vaccines, codon optimization plays a critical role in vaccine design to improve the stability and expression of proteins in specific tissues. Considering the many-to-one relationship between synonymous codons and amino acids, the number of mRNA sequences encoding the same amino acid sequence could be enormous. Finding stable and highly expressed mRNA sequences from the vast sequence space using in silico methods can generally be viewed as a path-search problem or a machine translation problem. However, current deep learning-based methods inspired by machine translation may have some limitations, such as recurrent neural networks (RNNs), which have a weak ability to capture the long-term dependencies of codon preferences. RESULTS: We develop a BERT-based architecture that uses the cross-attention mechanism for codon optimization. In CodonBERT, the codon sequence is randomly masked with each codon serving as a key and a value. In the meantime, the amino acid sequence is used as the query. CodonBERT was trained on high-expression transcripts from Human Protein Atlas mixed with different proportions of high codon adaptation index (CAI) codon sequences. The result showed that CodonBERT can effectively capture the long-term dependencies between codons and amino acids, suggesting that it can be used as a customized training framework for specific optimization targets. AVAILABILITY: CodonBERT is freely available on https://github.com/FPPGroup/CodonBERT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Terf2ip deficiency accelerates non-alcoholic steatohepatitis through regulating lipophagy and fatty acid oxidation via Sirt1/AMPK pathway.

BACKGROUND & AIMS: Our previous study has demonstrated that Telomeric repeat-binding factor 2-interacting protein 1(Terf2ip), played an important role in hepatic ischemia reperfusion injury. This study is aimed to explore the function and mechanism of Terf2ip in non-alcoholic steatohepatitis (NASH). METHODS: The expression of Terf2ip was detected in liver tissue samples obtained from patients diagnosed with NASH. Mice NASH models were constructed by fed with high-fat diet (HFD) or methionine/choline deficient diet (MCD) in Terf2ip knockout and wild type (WT) mice. To further investigate the role of Terf2ip in NASH, adeno-associated viruses (AAV)-Terf2ip was administrated to mice. RESULTS: We observed a significant down-regulation of Terf2ip levels in the livers of NASH patients and mice NASH models. Terf2ip deficiency was associated with an exacerbation of hepatic steatosis in mice under HFD or MCD. Additionally, Terf2ip deficiency impaired lipophagy and fatty acid oxidation (FAO) in NASH models. Mechanically, we discovered that Terf2ip bound to the promoter region of Sirt1 to regulate Sirt1/AMPK pathway activation. As a result, Terf2ip deficiency was shown to inhibit lipophagy through the AMPK pathway, while the activation of Sirt1 alleviated steatohepatitis in the livers of mice. Finally, re-expression of Terf2ip in hepatocyes alleviated liver steatosis, inflammation, and restored lipophagy. CONCLUSIONS: These results revealed that Terf2ip played a protective role in the progression of NASH through regulating lipophagy and FAO by binding to Sirt1 promoter. Our findings provided a potential therapeutic target for the treatment of NASH.

A benchmark for evaluation of structure-based online tools for antibody-antigen binding affinity.

The prediction of binding affinity changes caused by missense mutations can elucidate antigen-antibody interactions. A few accessible structure-based online computational tools have been proposed. However, selecting suitable software for particular research is challenging, especially research on the SARS-CoV-2 spike protein with antibodies. Therefore, benchmarking of the mutation-diverse SARS-CoV-2 datasets is critical. Here, we collected the datasets including 1216 variants about the changes in binding affinity of antigens from 22 complexes for SARS-CoV-2 S proteins and 22 monoclonal antibodies as well as applied them to evaluate the performance of seven binding affinity prediction tools. The tested tools' Pearson correlations between predicted and measured changes in binding affinity were between -0.158 and 0.657, while accuracy in classification tasks on predicting increasing or decreasing affinity ranged from 0.444 to 0.834. These tools performed relatively better on predicting single mutations, especially at epitope sites, whereas poor performance on extremely decreasing affinity. The tested tools were relatively insensitive to the experimental techniques used to obtain structures of complexes. In summary, we constructed a list of datasets and evaluated a range of structure-based online prediction tools that will explicate relevant processes of antigen-antibody interactions and enhance the computational design of therapeutic monoclonal antibodies.

DeepSS2GO: protein function prediction from secondary structure.

Predicting protein function is crucial for understanding biological life processes, preventing diseases and developing new drug targets. In recent years, methods based on sequence, structure and biological networks for protein function annotation have been extensively researched. Although obtaining a protein in three-dimensional structure through experimental or computational methods enhances the accuracy of function prediction, the sheer volume of proteins sequenced by high-throughput technologies presents a significant challenge. To address this issue, we introduce a deep neural network model DeepSS2GO (Secondary Structure to Gene Ontology). It is a predictor incorporating secondary structure features along with primary sequence and homology information. The algorithm expertly combines the speed of sequence-based information with the accuracy of structure-based features while streamlining the redundant data in primary sequences and bypassing the time-consuming challenges of tertiary structure analysis. The results show that the prediction performance surpasses state-of-the-art algorithms. It has the ability to predict key functions by effectively utilizing secondary structure information, rather than broadly predicting general Gene Ontology terms. Additionally, DeepSS2GO predicts five times faster than advanced algorithms, making it highly applicable to massive sequencing data. The source code and trained models are available at https://github.com/orca233/DeepSS2GO.

Veno-arterial extracorporeal membrane oxygenation reduces myocardial and mitochondrial damage in acute myocardial infarction.

BACKGROUND: Myocardial infarction (MI) is a common cardiovascular disease with a high fatality rate once accompanied by cardiogenic shock. The efficacy of extracorporeal membrane oxygenation (ECMO) in treating myocardial infarction is controversial. METHODS: MI was induced by ligating the left anterior descending artery in adult male rats. Groups were defined as follows: MI group, reperfusion for 90 min after 30 min of left anterior descending artery (LAD) occlusion; MI + ECMO group, reperfusion and ECMO were performed for 90 min immediately after 30 min of LAD occlusion; prolonged MI + ECMO group, ECMO was used immediately after 30 minutes of occlusion with persistent occlusion of the LAD for an additional 30 minutes, followed by 90 minutes of reperfusion. The myocardial infarct size and mitochondrial morphology and function data were collected and compared of each group. RESULTS: The ECMO groups had a smaller myocardial infarct size and larger percentage ejection fraction. Compared with the prolonged MI + ECMO group, the immediate reperfusion group had a lower percentage of infarct size (63.28% versus 17.97% versus 31.22%, MI versus MI + ECMO versus prolonged MI + ECMO). Mitochondria isolated from the ischemic zone showed an intact mitochondrial structure, including fewer voids and broken crists, and preserved activity of mitochondrial complex II and complex IV in ECMO groups. CONCLUSIONS: ECMO support in myocardial infarction can reduce myocardial injury despite delayed coronary reperfusion.

Effective dose of intranasal remimazolam for preoperative sedation in preschool children: a dose-finding study using Dixon's up-and-down method.

Background: Most preschool children are distressed during anesthesia induction. While current pharmacological methods are useful, there is a need for further optimization to an "ideal" standard. Remimazolam is an ultra-short-acting benzodiazepine, and intranasal remimazolam for pre-induction sedation may be promising. Methods: This study included 32 preschool children who underwent short and minor surgery between October 2022 and January 2023. After pretreatment with lidocaine, remimazolam was administered to both nostrils using a mucosal atomizer device. The University of Michigan Sedation Score (UMSS) was assessed for sedation 6, 9, 12, 15, and 20 min after intranasal atomization. We used Dixon's up-and-down method, and probit and isotonic regressions to determine the 50% effective dose (ED50) and 95% effective dose (ED95) of intranasal remimazolam for pre-induction sedation. Results: Twenty-nine pediatric patients were included in the final analysis. The ED50 and ED95 of intranasal remimazolam for successful pre-induction sedation, when processed via probit analysis, were 0.65 (95% confidence interval [CI], 0.59-0.71) and 0.78 mg/kg (95% CI, 0.72-1.07), respectively. In contrast, when processed by isotonic regression, they were 0.65 (95% CI: 0.58-0.72 mg/kg) and 0.78 mg/kg (95% CI: 0.69-1.08 mg/kg), respectively. At 6 min after intranasal remimazolam treatment, 81.2% (13/16) of "positive" participants were successfully sedated with a UMSS ≧ 1. All the "positive" participants were successfully sedated within 9 min. Conclusion: Intranasal remimazolam is feasible for preschool children with a short onset time. For successful pre-induction sedation, the ED50 and ED95 of intranasal remimazolam were 0.65 and 0.78 mg/kg, respectively.

Soil properties constrain forest understory plant distributions along an elevation gradient.

Projections of spatial biodiversity dynamics under climate warming are often based on models including only climate variables, and when non-climatic factors (e.g. soil) are included, data are often at much coarser spatial resolutions than those experienced by plants. Field studies along elevation gradients permit the gathering of detailed soil data, while still covering a wide climatic gradient. Here, an intensive field survey of four spring forest herbs along an elevation gradient showed that soil properties had substantial impacts on the occurrence/abundance of all species, and that soil effects were more pronounced at higher elevations. For Trillium erectum and Claytonia caroliniana, very infrequent occurrences at high elevation were strongly associated with rare microsites with high pH or nutrients. In a seven-year transplant experiment with T. erectum, we found that individuals grew to much smaller sizes at high than low elevation, suggesting that environmental factors rather than dispersal limitation constrain the species' upper range limit, despite substantial warming in recent decades. Our study demonstrates that soil factors interact strongly with climate to determine plant range limits along climatic gradients. Unsuitable soils for plants at high elevations or latitudes may represent an important constraint on future plant migration and biodiversity change. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Non-traumatic osteonecrosis of the femoral head induced by steroid and alcohol exposure is associated with intestinal flora alterations and metabolomic profiles.

OBJECTIVE: Osteonecrosis of the femoral head (ONFH) is a severe disease that primarily affects the middle-aged population, imposing a significant economic and social burden. Recent research has linked the progression of non-traumatic osteonecrosis of the femoral head (NONFH) to the composition of the gut microbiota. Steroids and alcohol are considered major contributing factors. However, the relationship between NONFH caused by two etiologies and the microbiota remains unclear. In this study, we examined the gut microbiota and fecal metabolic phenotypes of two groups of patients, and analyzed potential differences in the pathogenic mechanisms from both the microbial and metabolic perspectives. METHODS: Utilizing fecal samples from 68 NONFH patients (32 steroid-induced, 36 alcohol-induced), high-throughput 16 S rDNA sequencing and liquid chromatography with tandem mass spectrometry (LC-MS/MS) metabolomics analyses were conducted. Univariate and multivariate analyses were applied to the omics data, employing linear discriminant analysis effect size to identify potential biomarkers. Additionally, functional annotation of differential metabolites and associated pathways was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Subsequently, Spearman correlation analysis was employed to assess the potential correlations between differential gut microbiota and metabolites. RESULTS: High-throughput 16 S rDNA sequencing revealed significant gut microbial differences. At the genus level, the alcohol group had higher Lactobacillus and Roseburia, while the steroid group had more Megasphaera and Akkermansia. LC-MS/MS metabolomic analysis indicates significant differences in fecal metabolites between steroid- and alcohol-induced ONFH patients. Alcohol-induced ONFH (AONFH) showed elevated levels of L-Lysine and Oxoglutaric acid, while steroid-induced ONFH(SONFH) had increased Gluconic acid and Phosphoric acid. KEGG annotation revealed 10 pathways with metabolite differences between AONFH and SONFH patients. Correlation analysis revealed the association between differential gut flora and differential metabolites. CONCLUSIONS: Our results suggest that hormones and alcohol can induce changes in the gut microbiota, leading to alterations in fecal metabolites. These changes, driven by different pathways, contribute to the progression of the disease. The study opens new research directions for understanding the pathogenic mechanisms of hormone- or alcohol-induced NONFH, suggesting that differentiated preventive and therapeutic approaches may be needed for NONFH caused by different triggers.

UPLC-ESI-MS/MS-Based Analysis of Various Edible Rosa Fruits Concerning Secondary Metabolites and Evaluation of Their Antioxidant Activities.

The genus Rosa is globally popular with well-established applications since it has a high edible and medicinal value. However, relatively limited research has been conducted on the composition and quality of wild Rosa fruits. The present study aimed to compare the properties and chemical components of five wild edible Rosa fruits, Rosa roxburghii, Rosa sterilis, Rosa laevigata, Rosa davurica, and Rosa sericea. The UPLC-ESI-MS/MS approach identified the key metabolites among the five Rosa fruits as flavonoids, phenolic acids, and organic acids. The main differential metabolites among the five fruits are flavonoids (22.29-45.13%), phenolic acids (17-22.27%), and terpenoids (7.7-24%), respectively. In total, 125 compounds served as potential markers for the five Rosa species. Differential metabolic pathways of five Rosa fruits were analyzed using the KEGG approach. Rosa laevigata fruits showed the highest total polysaccharide (TPS) content of 64.48 g/100 g. All the five Rosa extracts effectively decreased the levels of malondialdehyde while increasing the activities of superoxide dismutase and glutathione peroxidase in the H2O2-induced HaCaT cell model, demonstrating high potential for antioxidant development. Our findings suggest that the five studied Rosa fruits exhibit biological activity and edible value worth further exploration.

Deep Learning Imaging Reconstruction Algorithm for Carotid Dual Energy CT Angiography: Opportunistic Evaluation of Cervical Intervertebral Discs-A Preliminary Study.

Thus, the aim of this study is to evaluate the performance of deep learning imaging reconstruction (DLIR) algorithm in different image sets derived from carotid dual-energy computed tomography angiography (DECTA) for evaluating cervical intervertebral discs (IVDs) and compare them with those reconstructed using adaptive statistical iterative reconstruction-Veo (ASiR-V). Forty-two patients who underwent carotid DECTA were included in this retrospective analysis. Three types of image sets (70 keV, water-iodine, and water-calcium) were reconstructed using 50% ASiR-V and DLIR at medium and high levels (DLIR-M and DLIR-H). The diagnostic acceptability and conspicuity of IVDs were assessed using a 5-point scale. Hounsfield Units (HU) and water concentration (WC) values of the IVDs; standard deviation (SD); and coefficient of variation (CV) were calculated. Measurement parameters of the 50% ASIR-V, DLIR-M, and DLIR-H groups were compared. The DLIR-H group showed higher scores for diagnostic acceptability and conspicuity, as well as lower SD values for HU and WC than the ASiR-V and DLIR-M groups for the 70 keV and water-iodine image sets (all p < .001). However, there was no significant difference in scores and SD among the three groups for the water-calcium image set (all p > .005). The water-calcium image set showed better diagnostic accuracy for evaluating IVDs compared to the other image sets. The inter-rater agreement using ASiR-V, DLIR-M, and DLIR-H was good for the 70 keV image set, excellent for the water-iodine and water-calcium image sets. DLIR improved the visualization of IVDs in the 70 keV and water-iodine image sets. However, its improvement on color-coded water-calcium image set was limited.

Pilot validation of on-field STR typing and human identity testing by MinION nanopore sequencing.

Nanopore sequencing technology has broad application prospects in forensic medicine due to its small size, portability, fast speed, real-time result analysis capabilities, single-molecule sequencing abilities, and simple operation. Here, we demonstrate for the first time that nanopore sequencing platforms can be used to identify individuals in the field. Through scientific and reasonable design, a nanopore MinION MK1B device and other auxiliary devices are integrated into a portable detection box conducive to individual identification at the accident site. Individual identification of 12 samples could be completed within approximately 24 h by jointly detecting 23 short tandem repeat (STR) loci. Through double-blinded experiments, the genotypes of 49 samples were successfully determined, and the accuracy of the STR genotyping was verified by the gold standard. Specifically, the typing success rate for 1150 genotypes was 95.3%, and the accuracy rate was 86.87%. Although this study focused primarily on demonstrating the feasibility of full-process testing, it can be optimistically predicted that further improvements in bioinformatics workflows and nanopore sequencing technology will help enhance the feasibility of Oxford Nanopore Technologies equipment for real-time individual identification at accident sites.

Loss of macrophage TSC1 exacerbates sterile inflammatory liver injury through inhibiting the AKT/MST1/NRF2 signaling pathway.

Tuberous sclerosis complex 1 (TSC1) plays important roles in regulating innate immunity. However, the precise role of TSC1 in macrophages in the regulation of oxidative stress response and hepatic inflammation in liver ischemia/reperfusion injury (I/R) remains unknown. In a mouse model of liver I/R injury, deletion of myeloid-specific TSC1 inhibited AKT and MST1 phosphorylation, and decreased NRF2 accumulation, whereas activated TLR4/NF-κB pathway, leading to increased hepatic inflammation. Adoptive transfer of AKT- or MST1-overexpressing macrophages, or Keap1 disruption in myeloid-specific TSC1-knockout mice promoted NRF2 activation but reduced TLR4 activity and mitigated I/R-induced liver inflammation. Mechanistically, TSC1 in macrophages promoted AKT and MST1 phosphorylation, and protected NRF2 from Keap1-mediated ubiquitination. Furthermore, overexpression AKT or MST1 in TSC1-knockout macrophages upregulated NRF2 expression, downregulated TLR4/NF-κB, resulting in reduced inflammatory factors, ROS and inflammatory cytokine-mediated hepatocyte apoptosis. Strikingly, TSC1 induction in NRF2-deficient macrophages failed to reverse the TLR4/NF-κB activity and production of pro-inflammatory factors. Conclusions: Macrophage TSC1 promoted the activation of the AKT/MST1 signaling pathway, increased NRF2 levels via reducing Keap1-mediated ubiquitination, and modulated oxidative stress-driven inflammatory responses in liver I/R injury. Our findings underscore the critical role of macrophage TSC1 as a novel regulator of innate immunity and imply the therapeutic potential for the treatment of sterile liver inflammation in transplant recipients. Schematic illustration of macrophage TSC1-mediated AKT/MST1/NRF2 signaling pathway in I/R-triggered liver inflammation. Macrophage TSC1 can be activated in I/R-stressed livers. TSC1 activation promotes phosphorylation of AKT and MST1, which in turn increases NRF2 expression and inhibits ROS production and TLR4/NF-κB activation, resulting in reduced hepatocellular apoptosis in I/R-triggered liver injury.

A matched case-control study of early cervical spondylotic myelopathy based on diffusion magnetic resonance imaging.

BACKGROUND: Early cervical spondylotic myelopathy (CSM) is challenging to diagnose and easily missed. Diffusion MRI (dMRI) has the potential to identify early CSM. METHODS: Using diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI), a 1:1 matched case-control study was conducted to evaluate the potential of dMRI in identifying early CSM and assessing uncompressed segments of CSM patients. CSM patients and volunteers were matched by age and spinal location. The differences in dMRI parameters between groups were assessed by the paired t-test, the multicollinearity of the dMRI parameters was evaluated by the variance inflation factor (VIF), and the value of dMRI parameters in distinguishing controls from CSM patients was determined by logistic regression. The univariate t-test was used to analyse differences between CSM patients and volunteers in adjacent uncompressed areas. RESULTS: In total, 56 CSM patients and 56 control volunteers were included. Paired t-tests revealed significant differences in nine dMRI parameters between groups. Multicollinearity calculated through VIF and combined with logistic regression showed that the orientation division index (ODI) was significantly positively correlated (r = 2.12, p = 0.035), and the anisotropic water fraction (AWF) was significantly negatively correlated (r = -0.98, p = 0.015). The fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), isotropic volume fraction (ISOVF), ODI, and AWF were significantly different in the upper and lower uncompressed areas at all ages. CONCLUSION: dMRI can noninvasively identify early CSM patients and potentially identify the extent of CSM lesions involving the cervical spinal cord. CRITICAL RELEVANCE STATEMENT: Diffusion MRI (dMRI) can identify early cervical spondylotic myelopathy (CSM) and has the potential to help determine the extent of CSM involvement. The application of dMRI can help screen for early CSM and develop clinical surgical and rehabilitation treatment plans. KEY POINTS: • Diffusion MRI can differentiate between normal and early-stage cervical spondylotic myelopathy patients. • Diffusion MRI has the ability to identify the extent of spinal cord involvement in cervical spondylotic myelopathy. • Diffusion MRI enables the early screening of cervical spondylotic myelopathy and helps guide clinical treatment.

Prevalence, contemporary trends and associated factors of potentially inappropriate prescription of edoxaban in real-world clinical practice: A subanalysis of the SUNSHINE registry.

AIM: As the direct oral anticoagulant most recently approved in China, data pertaining to clinical edoxaban use are still scarce. This study investigated the prevalence of and contemporary trends in edoxaban prescription among Chinese patients as well as factors associated with its inappropriate use in a multicentre registry of patients treated in real-world clinical practice. METHODS: This real-world, prospective, multicentre and non-interventional study included 1005 inpatients treated with edoxaban. According to National Medical Products Administration and European Heart Rhythm Association guidelines, edoxaban therapy was determined to be appropriate or inappropriate in each case. RESULTS: The median patient age was 70.0 years (interquartile range 61.0-78.0 years) and 46.3% were women. Overall, 456 (45.4%) patients received inappropriate edoxaban therapy, and common issues included an inappropriately low dosage (183, 18.2%) or wrong drug selection (109, 10.8%), high dosage (73, 7.3%), unreasonable off-label use (49, 4.9%), contraindicated medication combinations (27, 2.7%) and incorrect administration timing (16, 1.6%). Several factors, such as age ≥75 years (odds ratio [OR] = 1.921, 95% confidence interval [CI] 1.355-2.723, P < 0.001), weight >60 kg (OR = 2.657, 95%CI 1.970-3.583, P < 0.001), severe renal insufficiency (OR = 1.988, 95% CI 1.043-3.790, P = 0.037), current anaemia (OR = 1.556, 95% CI 1.151-2.102, P = 0.004) and history of bleeding (OR = 2.931, 95% CI 1.605-5.351, P < 0.001) were associated with an increased risk of inappropriate edoxaban therapy, whereas factors associated with cardiovascular specialties, such as admission to a cardiovascular department (OR = 0.637, 95% CI 0.464-0.873, P = 0.005), dronedarone use (OR = 0.065, 95% CI 0.026-0.165, P < 0.001) and amiodarone use (OR = 0.365, 95% CI 0.209-0.637, P < 0.001) decreased this risk. CONCLUSION: In this real-world study, 45.4% of patients received an inappropriate treatment with edoxaban. Multiple clinical characteristics can help identify patients who should receive edoxaban. Further development and implantation of educational activities and management strategies are needed to ensure the correct use of edoxaban.

Predictive Value of the Diffusion Magnetic Resonance Imaging Technique for the Postoperative Outcome of Cervical Spondylotic Myelopathy.

BACKGROUND: Diffusion magnetic resonsance imaging (dMRI) can potentially predict the postoperative outcome of cervical spondylotic myelopathy (CSM). PURPOSE: To explore preoperative dMRI parameters to predict the postoperative outcome of CSM through multifactor correlation analysis. STUDY TYPE: Prospective. POPULATION: Post-surgery CSM patients; 102 total, 73 male (52.42 ± 10.60 years old) and 29 female (52.0 ± 11.45 years old). FIELD STRENGTH/SEQUENCE: 3.0 T/Turbo spin echo T1/T2-weighted, T2*-weighted multiecho gradient echo and dMRI. ASSESSMENT: Spinal cord function was evaluated using modified Japanese Orthopedic Association (mJOA) scoring at different time points: preoperative and 3, 6, and 12 months postoperative. Single-factor correlation and t test analyses were conducted based on fractional anisotropy (FA), mean diffusivity, intracellular volume fraction, isotropic volume fraction, orientation division index, increased signal intensity, compression ratio, age, sex, symptom duration and operation method, and multicollinearity was calculated. The linear quantile mixed model (LQMM) and the linear mixed-effects regression model (LMER) were used for multifactor correlation analysis using the combinations of the above variables. STATISTICAL TESTS: Distance correlation, Pearson's correlation, multiscale graph correlation and t tests were used for the single-factor correlation analyses. The variance inflation factor (VIF) was used to calculate multicollinearity. LQMM and LMER were used for multifactor correlation analyses. P < 0.05 was considered statistically significant. RESULTS: The single-factor correlation between all variables and the postoperative mJOA score was weak (all r < 0.3). The linear relationship was stronger than the nonlinear relationship, and there was no significant multicollinearity (VIF = 1.10-1.94). FA values in the LQMM and LMER models had a significant positive correlation with the mJOA score (r = 5.27-6.04), which was stronger than the other variables. DATA CONCLUSION: The FA value based on dMRI significantly positively correlated with CSM patient postoperative outcomes, helping to predict the surgical outcome and formulate a treatment plan before surgery. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Preliminary exploration of deep learning-assisted recognition of superior labrum anterior and posterior lesions in shoulder MR arthrography.

PURPOSE: MR arthrography (MRA) is the most accurate method for preoperatively diagnosing superior labrum anterior-posterior (SLAP) lesions, but diagnostic results can vary considerably due to factors such as experience. In this study, deep learning was used to facilitate the preliminary identification of SLAP lesions and compared with radiologists of different seniority. METHODS: MRA data from 636 patients were retrospectively collected, and all patients were classified as having/not having SLAP lesions according to shoulder arthroscopy. The SLAP-Net model was built and tested on 514 patients (dataset 1) and independently tested on data from two other MRI devices (122 patients, dataset 2). Manual diagnosis was performed by three radiologists with different seniority levels and compared with SLAP-Net outputs. Model performance was evaluated by the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), etc. McNemar's test was used to compare performance among models and between radiologists' models. The intraclass correlation coefficient (ICC) was used to assess the radiologists' reliability. p < 0.05 was considered statistically significant. RESULTS: SLAP-Net had AUC = 0.98 and accuracy = 0.96 for classification in dataset 1 and AUC = 0.92 and accuracy = 0.85 in dataset 2. In dataset 1, SLAP-Net had diagnostic performance similar to that of senior radiologists (p = 0.055) but higher than that of early- and mid-career radiologists (p = 0.025 and 0.011). In dataset 2, SLAP-Net had similar diagnostic performance to radiologists of all three seniority levels (p = 0.468, 0.289, and 0.495, respectively). CONCLUSIONS: Deep learning can be used to identify SLAP lesions upon initial MR arthrography examination. SLAP-Net performs comparably to senior radiologists.

A Smartphone Application-Based Remote Rehabilitation System for Post-Total Knee Arthroplasty Rehabilitation: A Randomized Controlled Trial.

BACKGROUND: Remote rehabilitation after total knee arthroplasty has gradually gained popularity in recent years. This study aimed to determine whether smartphone application-based remote rehabilitation could outperform home-based rehabilitation and outpatient guidance in terms of 12-week outcomes following primary unilateral total knee arthroplasty. METHODS: Patients who underwent primary unilateral total knee arthroplasty were recruited and randomly divided into a telerehabilitation group and a control group. A total of 100 patients were examined, with 50 each assigned to the telerehabilitation and control groups. In the telerehabilitation group, a telerehabilitation application was installed on the smartphones of the participants to allow postdischarge guidance. The primary outcomes were knee range of motion (ROM) at 12 weeks postoperatively. Secondary outcomes included the Western Ontario and McMaster Universities Osteoarthritis Index, Knee Society Score, The Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36), Five Times Sit-to-Stand Test (5xSST), Single-Leg Stance Test (SLST), satisfaction, rehabilitation costs, complication rate, and 90-day readmission rate. All outcomes were collected at 2, 6, and 12 weeks after surgery. RESULTS: At 12 weeks postoperatively, the telerehabilitation patients significantly outperformed the controls in terms of knee ROM (124 ± 8.7 versus 119 ± 5.5 P = .01), SF-36 (physiological function) (61.5 ± 20.3 versus 45.5 ± 18.1 P = .000), SF-36 (role-physical) (49.3 ± 41.5 versus 27.7 ± 28.9 P = .012), SLST (13.0 ± 9.1 versus 9.1 ± 5.9 P = .026), and 5xSST (17.7 ± 4.3 versus 19.4 ± 3.5 P = .043). No significant differences were found between groups in the Western Ontario and McMaster Universities Osteoarthritis Index score, Knee Society Score, rehabilitation costs, 90-day readmission rate, or incidence of adverse events. CONCLUSION: Our study showed that smartphone app-based remote rehabilitation worked better than home-based rehabilitation with outpatient guidance in terms of short-term results in ROM, SLST, and 5xSST.

Long Non-Coding RNA MALAT1 Protects Against Spinal Cord Injury via Suppressing microRNA-125b-5p Mediated Microglial M1 Polarization, Neuroinflammation, and Neural Apoptosis.

Our previous studies have discovered that long non-coding RNA (lncRNA) MALAT1 and its target microRNA-125b-5p (miR-125b-5p) are implicated in neurological diseases via regulating neuroinflammation and neuronal injury. This study aimed to further explore the relationship between lncRNA MALAT1 and miR-125b-5p, as well as their effect on microglial activation, neuroinflammation, and neural apoptosis in spinal cord injury (SCI). Primary microglia from Sprague Dawley rats were stimulated with lipopolysaccharide (LPS). Then, microglia were transfected with lncRNA MALAT1 overexpression or knock-down adenovirus-associated virus with or without miR-125b-5p mimic. The culture medium of microglia was incubated with primary neurons. SCI rats were established for in vivo validation. LncRNA MALAT1 expression was reduced by LPS treatment in a dose-dependent manner. LncRNA MALAT1 overexpression suppressed the microglial M1 polarization (decreased iNOS but increased ARG1), neuroinflammation (declined PTGS2, TNF-α, IL-1ß, and IL-6), and microglia-induced neural apoptosis (lower TUNEL positive cells and C-caspase3 but higher BCL2) under LPS treatment; its knock-down displayed the opposite trend. Moreover, lncRNA MALAT1 directly bound to and negatively regulated miR-125b-5p. MiR-125b-5p mimic promoted microglial M1 polarization, neuroinflammation, and microglia-induced neural apoptosis following LPS treatment; also, it could attenuate the effect of lncRNA MALAT1. Further in vivo study displayed that lncRNA MALAT1 overexpression elevated the Basso-Beattie-Bresnahan motor function score and improved neural injury. Also, in vivo validation indicated a similar effect of lncRNA MALAT1 on microglial polarization and neuroinflammation as in vitro. LncRNA MALAT1 improves SCI recovery via miR-125b-5p mediated microglial M1 polarization, neuroinflammation, and neural apoptosis.

Association between genetic variants of transmembrane transporters and susceptibility to anthracycline-induced cardiotoxicity: Current understanding and existing evidence.

Anthracyclines remain the cornerstone of numerous chemotherapeutic protocols, with beneficial effects against haematological malignancies and solid tumours. Unfortunately, the clinical usefulness of anthracyclines is compromised by the development of cardiotoxic side effects, leading to dose limitations or treatment discontinuation. There is no absolute linear correlation between the incidence of cardiotoxicity and the threshold dose, suggesting that genetic factors may modify the association between anthracyclines and cardiotoxicity risk. And the majority of single nucleotide polymorphisms (SNPs) associated with anthracycline pharmacogenomics were identified in the ATP-binding cassette (ABC) and solute carrier (SLC) transporters, generating increasing interest in the pharmacogenetic implications of their genetic variations for anthracycline-induced cardiotoxicity (AIC). This review focuses on the influence of SLC and ABC polymorphisms on AIC and highlights the prospects and clinical significance of pharmacogenetics for individualised preventive approaches.

Resting-state cortico-limbic functional connectivity pattern in panic disorder: Relationships with emotion regulation strategy use and symptom severity.

Cognitive reappraisal is an effective emotion regulation strategy involving prefrontal cortex (PFC) control of the amygdala. Its aberrant functioning is closely associated with panic disorder (PD). However, the resting-state functional connectivity (rsFC) between the PFC, implicated in cognitive reappraisal, and the amygdala in PD has not been studied. Thus, this study aims to investigate the rsFC patterns and their association with cognitive reappraisal and PD. This study involved 51 participants, including 26 untreated patients with PD and 25 healthy controls (HC). We evaluated the habit of cognitive reappraisal assessment and the severity of PD using neuropsychological and clinical measures. Resting-state fMRI was utilized to evaluate the rsFC pattern between the PFC, engaged in cognitive reappraisal, and the amygdala. Mediation analysis was performed to explore the role of this rsFC in the relationship between cognitive reappraisal and PD severity. PD patients showed reduced rsFC between the PFC and the amygdala compared to HC. This weakened rsFC was associated with the severity of PD symptoms. Moreover, cognitive reappraisal was negatively correlated with PD severity, and mediation analysis indicated that the rsFC of the PFC-amygdala played a mediating role in this association. Abnormal PFC-amygdala rsFC may play a pivotal role in PD development and/or manifestation and mediate the association between cognitive reappraisal and PD severity, potentially serving as a clinical indicator for monitoring and intervention.