Recent advances and challenges in protein complex model accuracy estimation.

Estimation of model accuracy plays a crucial role in protein structure prediction, aiming to evaluate the quality of predicted protein structure models accurately and objectively. This process is not only key to screening candidate models that are close to the real structure, but also provides guidance for further optimization of protein structures. With the significant advancements made by AlphaFold2 in monomer structure, the problem of single-domain protein structure prediction has been widely solved. Correspondingly, the importance of assessing the quality of single-domain protein models decreased, and the research focus has shifted to estimation of model accuracy of protein complexes. In this review, our goal is to provide a comprehensive overview of the reference and statistical metrics, as well as representative methods, and the current challenges within four distinct facets (Topology Global Score, Interface Total Score, Interface Residue-Wise Score, and Tertiary Residue-Wise Score) in the field of complex EMA.

Differentiation of bone marrow mesenchymal stem cells into Leydig-like cells with testicular extract liquid in vitro.

Differentiation of Leydig cells plays a key role in male reproductive function. Bone marrow mesenchymal stem cells (BMSCs) have emerged as a potential cell source for generating Leydig-like cells due to their multipotent differentiation capacity and accessibility. This study aimed to investigate the morphological and genetic expression changes of BMSCs during differentiation into Leydig-like cells. Testicular extract liquid, which simulates the microenvironment in vivo, induced the third passage BMSCs differentiated into Leydig-like cells. Changes in cell morphology were observed by microscopy, the formation of lipid droplets of androgen precursor was identified by Oil Red Staining, and the expression of testicular specific genes 3ß-HSD and SF-1 in testicular stromal cells was detected by RT-qPCR. BMSCs isolated from the bone marrow of Sprague-Dawley (SD) rats were cultured for 3 generations and identified as qualified BMSCs in terms of morphology and cell surface markers. After 14 days of induction with testicular tissue lysate, lipid droplets appeared in the cytoplasm of P3 BMSCs by Oil Red O staining. RT-qPCR detection was performed on BMSCs on the 3rd, 7th, 14th, and 21st day after induction. Relative expression levels of 3ß-HSD mRNA significantly increased after 14 days of induction, while the relative expression of SF-1 mRNA increased after 14 days of induction but was not significant. BMSCs can differentiate into testicular interstitial cells with reserve androgen precursor lipid droplets after induction by testicular tissue lysate. The differentiation ability of BMSCs provides the potential to reconstruct the testicular microenvironment and is expected to fundamentally improve testicular function and provide new treatment options for abnormal spermatogenesis diseases.

Machine Learning for Predicting Risk and Prognosis of Acute Kidney Disease in Critically Ill Elderly Patients During Hospitalization: Internet-Based and Interpretable Model Study.

BACKGROUND: Acute kidney disease (AKD) affects more than half of critically ill elderly patients with acute kidney injury (AKI), which leads to worse short-term outcomes. OBJECTIVE: We aimed to establish 2 machine learning models to predict the risk and prognosis of AKD in the elderly and to deploy the models as online apps. METHODS: Data on elderly patients with AKI (n=3542) and AKD (n=2661) from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were used to develop 2 models for predicting the AKD risk and in-hospital mortality, respectively. Data collected from Xiangya Hospital of Central South University were for external validation. A bootstrap method was used for internal validation to obtain relatively stable results. We extracted the indicators within 24 hours of the first diagnosis of AKI and the fluctuation range of some indicators, namely delta (day 3 after AKI minus day 1), as features. Six machine learning algorithms were used for modeling; the area under the receiver operating characteristic curve (AUROC), decision curve analysis, and calibration curve for evaluating; Shapley additive explanation (SHAP) analysis for visually interpreting; and the Heroku platform for deploying the best-performing models as web-based apps. RESULTS: For the model of predicting the risk of AKD in elderly patients with AKI during hospitalization, the Light Gradient Boosting Machine (LightGBM) showed the best overall performance in the training (AUROC=0.844, 95% CI 0.831-0.857), internal validation (AUROC=0.853, 95% CI 0.841-0.865), and external (AUROC=0.755, 95% CI 0.699-0.811) cohorts. In addition, LightGBM performed well for the AKD prognostic prediction in the training (AUROC=0.861, 95% CI 0.843-0.878), internal validation (AUROC=0.868, 95% CI 0.851-0.885), and external (AUROC=0.746, 95% CI 0.673-0.820) cohorts. The models deployed as online prediction apps allowed users to predict and provide feedback to submit new data for model iteration. In the importance ranking and correlation visualization of the model's top 10 influencing factors conducted based on the SHAP value, partial dependence plots revealed the optimal cutoff of some interventionable indicators. The top 5 factors predicting the risk of AKD were creatinine on day 3, sepsis, delta blood urea nitrogen (BUN), diastolic blood pressure (DBP), and heart rate, while the top 5 factors determining in-hospital mortality were age, BUN on day 1, vasopressor use, BUN on day 3, and partial pressure of carbon dioxide (PaCO2). CONCLUSIONS: We developed and validated 2 online apps for predicting the risk of AKD and its prognostic mortality in elderly patients, respectively. The top 10 factors that influenced the AKD risk and mortality during hospitalization were identified and explained visually, which might provide useful applications for intelligent management and suggestions for future prospective research.

Preparation of PLCL/ECM nerve conduits by electrostatic spinning technique and evaluationin vitroandin vivo.

Objective. Artificial nerve scaffolds composed of polymers have attracted great attention as an alternative for autologous nerve grafts recently. Due to their poor bioactivity, satisfactory nerve repair could not be achieved. To solve this problem, we introduced extracellular matrix (ECM) to optimize the materials.Approach.In this study, the ECM extracted from porcine nerves was mixed with Poly(L-Lactide-co-ϵ-caprolactone) (PLCL), and the innovative PLCL/ECM nerve repair conduits were prepared by electrostatic spinning technology. The novel conduits were characterized by scanning electron microscopy (SEM), tensile properties, and suture retention strength test for micromorphology and mechanical strength. The biosafety and biocompatibility of PLCL/ECM nerve conduits were evaluated by cytotoxicity assay with Mouse fibroblast cells and cell adhesion assay with RSC 96 cells, and the effects of PLCL/ECM nerve conduits on the gene expression in Schwann cells was analyzed by real-time polymerase chain reaction (RT-PCR). Moreover, a 10 mm rat (Male Wistar rat) sciatic defect was bridged with a PLCL/ECM nerve conduit, and nerve regeneration was evaluated by walking track, mid-shank circumference, electrophysiology, and histomorphology analyses.Main results.The results showed that PLCL/ECM conduits have similar microstructure and mechanical strength compared with PLCL conduits. The cytotoxicity assay demonstrates better biosafety and biocompatibility of PLCL/ECM nerve conduits. And the cell adhesion assay further verifies that the addition of ECM is more beneficial to cell adhesion and proliferation. RT-PCR showed that the PLCL/ECM nerve conduit was more favorable to the gene expression of functional proteins of Schwann cells. Thein vivoresults indicated that PLCL/ECM nerve conduits possess excellent biocompatibility and exhibit a superior capacity to promote peripheral nerve repair.Significance.The addition of ECM significantly improved the biocompatibility and bioactivity of PLCL, while the PLCL/ECM nerve conduit gained the appropriate mechanical strength from PLCL, which has great potential for clinical repair of peripheral nerve injuries.

Machine learning for the early prediction of acute respiratory distress syndrome (ARDS) in patients with sepsis in the ICU based on clinical data.

Background: Acute respiratory distress syndrome (ARDS) is a fatal outcome of severe sepsis. Machine learning models are helpful for accurately predicting ARDS in patients with sepsis at an early stage. Objective: We aim to develop a machine-learning model for predicting ARDS in patients with sepsis in the intensive care unit (ICU). Methods: The initial clinical data of patients with sepsis admitted to the hospital (including population characteristics, clinical diagnosis, complications, and laboratory tests) were used to predict ARDS, and screen out the crucial variables. After comparing eight different algorithms, namely, XG boost, logistic regression, light GBM, random forest, GaussianNB, complement NB, support vector machine (SVM), and K nearest neighbors (KNN), rebuilding a prediction model with the best one. When remodeling with the best algorithm, 10% was randomly selected to test, and the remaining was trained for cross-validation. Using the area under the curve (AUC), sensitivity, accuracy, specificity, positive and negative predictive value, F1 score, kappa value, and clinical decision curve to evaluate the model's performance. Eventually, the application in the model illustrated by the SHAP package. Results: Ten critical features were screened utilizing the lasso method, namely, PaO2/PAO2, A-aDO2, PO2(T), CRP, gender, PO2, RDW, MCH, SG, and chlorine. The prior ranking of variables demonstrated that PaO2/PAO2 was the most significant variable. Among the eight algorithms, the performance of the Gaussian NB algorithm was significantly better than that of the others. After remodeling with the best algorithm, the AUC in the training and validation sets were 0.777 and 0.770, respectively, and the algorithm performed well in the test set (AUC = 0.781, accuracy = 78.6%, sensitivity = 82.4%, F1 score = 0.824). A comparison of the overlap factors with those of previous models revealed that the model we developed performs better. Conclusion: Sepsis-associated ARDS can be accurately predicted early via a machine learning model based on existing clinical data. These findings are helpful for accurate identification and improvement of the prognosis in patients with sepsis-associated ARDS.

Mechanism of salt tolerance in the endangered semi-mangrove plant Barringtonia racemosa: anatomical structure and photosynthetic and fluorescence characteristics.

To elucidate the mechanisms governing the salt tolerance of the endangered semi-mangrove plant Barringtonia racemosa, the biomass, photosynthetic and fluorescent characteristics, and anatomical structure of B. racemosa were studied under low, medium and high salt stress. The results showed that the stem dry weight, net photosynthetic rate, intercellular CO2 concentration, Fv/Fm, and ΦPSI of B. racemosa decreased under high salt stress, which led to a significant reduction in total dry weight. Stem dry weight was significantly positively correlated with the thickness of palisade tissue and significantly negatively correlated with the thickness of the epidermis of roots and xylem of stems. Therefore, a stable net photosynthetic rate and intercellular CO2 concentration, an increase in Fv/Fm and ΦPSI, an increase in or stable palisade tissue and spongy mesophyll of leaves and an increase in xylem thickness of the stem and epidermis, outer cortex, and stele diameter of roots could contribute to the salt tolerance of B. racemosa.

Enhancing neuroinduction activity of PLCL-based nerve conduits through native epineurium integration.

Autologous nerve grafts have been considered the gold standard for peripheral nerve grafts. However, due to drawbacks such as functional loss in the donor area and a shortage of donor sources, nerve conduits are increasingly being considered as an alternative approach. Polymer materials have been widely studied as nerve repair materials due to their excellent processing performance. However, their limited biocompatibility has restricted further clinical applications. The epineurium is a natural extra-neural wrapping structure. After undergoing decellularization, the epineurium not only reduces immune rejection but also retains certain bioactive components. In this study, decellularized epineurium (DEP) derived from the sciatic nerve of mammals was prepared, and a bilayer nerve conduit was created by electrospinning a poly (l-lactide-co-ε-caprolactone) (PLCL) membrane layer onto the outer surface of the DEP. Components of the DEP were examined; the physical properties and biosafety of the bilayer nerve conduit were evaluated; and the functionality of the nerve conduit was evaluated in rats. The results demonstrate that the developed bilayer nerve conduit exhibits excellent biocompatibility and mechanical properties. Furthermore, this bilayer nerve conduit shows significantly superior therapeutic effects for sciatic nerve defects in rats compared to the pure PLCL nerve conduit. In conclusion, this research provides a novel strategy for the design of nerve regeneration materials and holds promising potential for further clinical translation.

Refining the 8th edition TNM classification for EBV related nasopharyngeal carcinoma.

The AJCC/UICC TNM classification describes anatomic extent of tumor progression and guides treatment decisions. Our comprehensive analysis of 8,834 newly diagnosed patients with non-metastatic Epstein-Barr virus related nasopharyngeal carcinoma (NPC) from six Chinese centers indicates certain limitations in the current staging system. The 8th edition of the AJCC/UICC TNM classification inadequately differentiates patient outcomes, particularly between T2 and T3 categories and within the N classification. We propose reclassifying cases of T3 NPC with early skull-base invasion as T2, and elevating N1-N2 cases with grade 3 image-identified extranodal extension (ENE) to N3. Additionally, we suggest combining T2N0 with T1N0 into a single stage IA. For de novo metastatic (M1) NPC, we propose subdivisions of M1a, defined by 1-3 metastatic lesions without liver involvement, and M1b, characterized by >3 metastatic lesions or liver involvement. This proposal better reflects responses of NPC patients to the up-to-date treatments and their evolving risk profiles.

Meta-Analysis and Network Analysis Differentially Detect Various Pro-Inflammatory Mediators and Risk Factors for Type 2 Diabetes in the Elderly.

Type 2 diabetes (T2D) has a pathophysiological component that includes inflammation. Inflammation-sensitive marker measurement may be helpful in determining the risk of complications for both older T2D patients and the public. This study aimed to investigate the association between blood pro-inflammatory mediators and the characteristics of elderly patients with T2D using meta and network analyses. The Web of Science, Scopus, PubMed, and Cochrane Library databases were selected as study methodology. The Quality in Prognosis Studies (QUIPS) tool in the meta-analysis assessed the studies' methodological quality. The selected studies were statistically analyzed using the META-MAR tool based on the standardized mean difference (SMD). The selected studies included nine examinations involving 6399 old people [+>+55 years old, 65.9+±+4.09 (mean+±+SD)]. The meta-analysis showed that pro-inflammatory mediators (SMD 0.82) and patient-related variables [risk factors (SMD 0.71)] were significantly associated with T2D (p+<+0.05). Subgroup analysis revealed that tumor necrosis factor alpha (TNF-α; SMD 1.08), body mass index (SMD 0.64), high-density lipoprotein (HDL; SMD -0.61), body weight (SMD 0.50), and blood pressure (SMD 1.11) were factors significantly associated with T2D (p+<+0.05). Network analysis revealed that among patient characteristics, diastolic blood pressure and, among inflammatory mediators, leptin were the most closely associated factors with T2D in older adults. Moreover, network analysis showed that TNF-α and systolic blood pressure were most closely associated with leptin. Overall, alternate techniques, such as meta-analysis and network analysis, might identify different markers for T2D in older people. A therapeutic decision-making process needs to consider these differences in advance.

5-methylcytosine-mediated upregulation of circular RNA 0102913 augments malignant properties of colorectal cancer cells through a microRNA-571/Rac family small GTPase 2 axis.

Circular RNAs (circRNAs) are a class of stable non-coding RNAs that have emerged as key regulators in human diseases including cancer. This study investigates the role of circRNA_0102913 (circ_0102913) in malignant behavior of colorectal cancer (CRC) cells and the underpinning mechanisms. By analyzing CRC-related GSE197991, GSE159669, and GSE223001 datasets, we obtained circ_0102913 as an aberrantly upregulated circRNA in CRC. Increased circ_0102913 expression was detected in CRC tissues and cells. By querying multiple bioinformatics systems (circBank, Circular RNA Interactome, TargetScan, miRDIP, miRwalk, and miRDB), we identified microRNA-571 (miR-571) as a target of circ_0102913 and Rac family small GTPase 2 (RAC2) mRNA as a target of miR-571. Biotinylated-RNA pull-down and/or luciferase assays showed that circ_0102913 bound to miR-571 to restore the expression of RAC2 mRNA. Circ_0102913 silencing or miR-571 overexpression repressed proliferation, migration and invasion, and in vivo tumorigenesis abilities of CRC cells. However, the malignant properties of cells were restored by RAC2 overexpression. The increased circ_0102913 expression in CRC cells was attributed to increased 5-methylcytosine (m5C) modification levels. Silencing of NOP2/Sun RNA methyltransferase 5 reduced the m5C level and therefore reduced stability and expression of circ_0102913 expression in CRC cells. In conclusion, this study demonstrates that m5C-mediated upregulation of circ_0102913 augments malignant properties of CRC cells through a miR-571/RAC2 axis.

Recent Advances and Challenges in Protein Structure Prediction.

Artificial intelligence has made significant advances in the field of protein structure prediction in recent years. In particular, DeepMind's end-to-end model, AlphaFold2, has demonstrated the capability to predict three-dimensional structures of numerous unknown proteins with accuracy levels comparable to those of experimental methods. This breakthrough has opened up new possibilities for understanding protein structure and function as well as accelerating drug discovery and other applications in the field of biology and medicine. Despite the remarkable achievements of artificial intelligence in the field, there are still some challenges and limitations. In this Review, we discuss the recent progress and some of the challenges in protein structure prediction. These challenges include predicting multidomain protein structures, protein complex structures, multiple conformational states of proteins, and protein folding pathways. Furthermore, we highlight directions in which further improvements can be conducted.

Acupuncture Combined with Voice Training Improved Voice Function in Patients with Primary Muscular Tension Dysphonia (MTD): A Randomized, Three-Armed, Open-Label Clinical Trial.

Objective: This randomized controlled trial aimed to evaluate the clinical efficacy of acupuncture combined with voice training for treating patients with primary muscular tension dysphonia (MTD) (Qi stagnation and blood stasis type in traditional Chinese medicine). Methods: A total of 108 patients with primary MTD (Qi stagnation and blood stasis type) were recruited in this study. The participants were randomly divided into 3 equal groups: a test group and two control groups (control groups 1 and 2). An additional 38 participants without primary MTD were recruited as the healthy group. Control group 1 received acupuncture sessions 3 times per week on alternate days on the Hegu (LI 4), Taichong (LR 3), Open Voice No. 1 point, and Open Voice No. 2 points. Control group 2 received a 40-minute voice training session once weekly. The test group received both treatments. The total treatment course for all groups was 30 days. The healthy participants did not receive any interventions. The physiological and functional voice improvements after treatment were compared between all 3 MTD groups and healthy participants. The Voice Handicap Index (VHI-10), the VHI-10 emotional score, the Chinese Medicine Symptom Score Scale (TCM), and the Grade Roughness Breathiness Asthenia Strain (GRBAS) were used to evaluate the changes in the voice after treatment. A laryngeal muscle blood oxygen monitoring was used to measure the blood oxygen saturation (SO2) of the suprahyoid and infrahyoid muscles, and a stroboscopic laryngoscopy was used to measure the dysphonia severity index (DSI). Acoustic voice analysis was used to measure the maximum phonation time (MPT), the jitter, and the shimmer. Result: The SO2 levels of the laryngeal muscle were significantly higher in the healthy subjects than in pretreatment MTD patients and were correlated with the VHI-10 and DSI scores. A significant improvement in the physiological and functional scores, the total VHI-10, the GRBAS score, the voice acoustic analysis indices, MPT, jitter, shimmer, and DSI, was noted after treatment in all 3 MTD groups (P < 0.05). However, the posttreatment scores in the test group were significantly higher compared to control group 2, whose score were superior than that in control group 1 (P < 0.05). Both the test group and control group 1 showed a significant increase in the SO2 levels of the laryngeal muscles after treatment, where the test group had a higher elevation than control group 1. No significant difference was noted in the posttreatment SO2 of the laryngeal muscles in control group 2 (P > 0.05). Conclusion: Acupuncture monotherapy or in combination with voice training can reduce the anxiety emotion, relieve MTD-associated systemic symptoms, and increase the SO2 levels of the laryngeal muscle. This combination is a promising approach for the treatment of MTD. This trial is registered with ChiCTR2200061469.

The chromosome-level genome assembly of Fraxinus americana provides insights into the evolution of Oleaceae plants.

White ash (Fraxinus americana linn.) originates from the southeastern United States. It is a tall and fast-growing tree species with strong salt-alkali resistance and cold tolerance, making it an important reforestation species and widely planted worldwide. Here, we completed the chromosome-level reference genome assembly of F. americana based on Illumina, PacBio, and Hi-C reads, with a genome size of 878.98 Mb, an N50 of 3.27 Mb, and a heterozygosity rate of 0.3 %. Based on de novo prediction, transcriptome prediction, and homology-based protein prediction, we obtained 39,538 genes. Approximately 843.21 Mb of the assembly genome was composed of 37,928 annotated protein-coding genes, with a gene function annotation rate of 95.93 %. 99.94 % of the overlap clusters (877.44 Mb) were anchored to 23 chromosomes. Synteny analysis of F. americana and other Oleaceae plants showed that F. americana underwent frequent chromosome rearrangements. The amplification of the Ale transposons effectively promoted the genome size of F. americana. Compared with other Oleaceae plants, the Glutathione S-transferase (GST) gene family in the F. americana genome has undergone significant expansion, which may help F. americana cope with adverse natural environments. Furthermore, we found that key enzyme-coding gene families related to lignin biosynthesis were expanded and highly expressed in F. americana leaves. These key genes drive lignin synthesis and benefit F. americana in fast-growing, as well as resisting biotic and abiotic stress. Overall, the F. americana genome assembly provides insights into the evolution of Oleaceae plants and provides abundant resources for breeding and germplasm conservation of white ash.

Recent Advances in Protein Folding Pathway Prediction through Computational Methods.

The protein folding mechanisms are crucial to understanding the fundamental processes of life and solving many biological and medical problems. By studying the folding process, we can reveal how proteins achieve their biological functions through specific structures, providing insights into the treatment and prevention of diseases. With the advancement of AI technology in the field of protein structure prediction, computational methods have become increasingly important and promising for studying protein folding mechanisms. In this review, we retrospect the current progress in the field of protein folding mechanisms by computational methods from four perspectives: simulation of an inverse folding pathway from native state to unfolded state; prediction of early folding residues by machine learning; exploration of protein folding pathways through conformational sampling; prediction of protein folding intermediates based on templates. Finally, the challenges and future perspectives of the protein folding problem by computational methods are also discussed.

Magnetic Properties of the Soft Magnetic Composites Prepared Using Mixtures of Carbonyl Iron, FeSiCr, and FeSiAl Alloy Powders.

The effect of carbonyl iron powder, FeSiCr alloy powder, and annealed FeSiAl alloy powder, both individually and in binary combinations, on the density, microstructure, and magnetic properties (including permeability and power loss) of inductors manufactured by molding compaction was investigated in this study. The investigation demonstrates that hysteresis loss dominates power loss in the tested frequency range. Due to higher compacted density and reduced coercivity, adding 50% carbonyl iron powder to annealed powder resulted in the lowest hysteresis loss, allowing for domain wall movement. On the other hand, adding 50% FeSiCr alloy powder to annealed powder resulted in higher hysteresis loss due to impurity components hindering domain wall motion. Due to extreme plastic deformation, the carbonyl iron powder and FeSiCr alloy powder combinations displayed the most significant hysteresis loss. Eddy current loss followed the same trends as hysteresis loss in the mixtures. This study provides important insights for refining the soft magnetic composite design to obtain higher magnetic performance, while minimizing power loss.

Application of digital-intelligence technology in the processing of Chinese materia medica.

Processing of Chinese Materia Medica (PCMM) is the concentrated embodiment, which is the core of Chinese unique traditional pharmaceutical technology. The processing includes the preparation steps such as cleansing, cutting and stir-frying, to make certain impacts on the quality and efficacy of Chinese botanical drugs. The rapid development of new computer digital technologies, such as big data analysis, Internet of Things (IoT), blockchain and cloud computing artificial intelligence, has promoted the rapid development of traditional pharmaceutical manufacturing industry with digitalization and intellectualization. In this review, the application of digital intelligence technology in the PCMM was analyzed and discussed, which hopefully promoted the standardization of the process and secured the quality of botanical drugs decoction pieces. Through the intellectualization and the digitization of production, safety and effectiveness of clinical use of traditional Chinese medicine (TCM) decoction pieces were ensured. This review also provided a theoretical basis for further technical upgrading and high-quality development of TCM industry.

Hyperbaric Oxygen Therapy Inhibits Neuronal Ferroptosis After Spinal Cord Injury in Mice.

STUDY DESIGN: Basic science study investigating the potential molecular mechanisms of hyperbaric oxygen (HBO) therapy in mice with spinal cord injury (SCI). OBJECTIVE: We aimed to explore the intrinsic mechanisms of HBO for SCI through the lens of ferroptosis in the subacute phase. SUMMARY OF BACKGROUND DATA: HBO has been observed to facilitate the restoration of neurological function subsequent to SCI. Ferroptosis is a distinct cellular death mechanism that can be distinguished from apoptosis, necrosis, and autophagy. However, the precise relationship between these two phenomena remains poorly understood. METHODS: We established an SCI model and employed a range of techniques, including behavioral assessments, electron microscopy, immunofluorescence, RT-qPCR, Western blotting (WB), Glutathione (GSH) measurement, and iron assay, to investigate various aspects of HBO therapy on SCI in mice. These included analyzing mitochondrial morphology, neuronal count, GSH levels, iron levels, and the expression of genes (Acyl-CoA synthetase family member-2, Iron-responsive element-binding protein-2) and proteins (Glutathione peroxidase 4; system Xc-light chain) associated with ferroptosis. The study included three groups: Sham-operated, SCI, and HBO. Group comparisons were performed using one-way analysis of variance and one-way repeated measures analysis of variance, followed by Tukey's post hoc test. Statistical significance was set at a P < 0.05. RESULTS: Our findings revealed that HBO therapy significantly enhanced the recovery of lower limb motor function in mice following SCI in the subacute phase. This was accompanied by upregulated expression of GPX4 and system Xc-light chain proteins, elevated GSH levels, increased number of NeuN+ cells, decreased expression of the iron-responsive element-binding protein-2 gene, and reduced iron concentration. CONCLUSIONS: Our research suggests that HBO therapy has the potential to be an effective treatment for SCI in the subacute phase by mitigating ferroptosis.

CircRNA-CIRH1A Promotes the Development of Osteosarcoma by Regulating PI3K/AKT and JAK2/STAT3 Signaling Pathways.

Osteogenic sarcoma (OS), one of the mesenchymal tumors with a high degree of malignancy, mainly occurs in the metaphysis of the long bones and around the knee joints in children and adolescents. The poor diagnosis in patients with OS can be attributed to the lack of early clinical symptoms, although the growth of tumor mass gradually results in severe pain and systemic symptoms. The mechanisms underlying the pathogenesis of OS are not fully understood. Thus, identifying early diagnostic biomarkers and novel targets involved in the progression of OS is of critical significance in the management of OS. CircRNA is a class of non-coding RNAs characterized by the close-loop structure and increased stability, which are implicated in the regulation of cell proliferation, differentiation, migration, and apoptosis. Moreover, circRNAs also play significant roles in aging and chronic disorders, such as cancer and cardiovascular diseases. Accordingly, we reported the upregulation of circRNA-CIRH1A in OS tissues and cell lines. Silencing circRNA-CIRH1A in OS cell lines (U2OS, HOS, Saos-2, and MG-63) could inhibit the cell proliferation, invasion, migration, and apoptosis, which was also validated in xenograft tumorigenesis mouse model. We further demonstrated that circRNA-CIRH1A sponged miR-1276, which subsequently disrupted the effect of miR-1276 on PI3K/AKT and JAK2/STAT3 signaling pathways. Together, our study revealed the oncogenic role of circRNA-CIRH1A in OS, and identified miR-1276/ PI3K-AKT and JAK2-STAT3 signaling axis as the key downstream mediators of circRNA-CIRH1A.

Predictors and optimal management of tumor necrosis factor antagonist nonresponse in inflammatory bowel disease: A literature review.

Tumor necrosis factor-α (TNF-α) antagonists, the first biologics approved for treating patients with inflammatory bowel disease (IBD), are effective for the induction and maintenance of remission and significantly improving prognosis. However, up to one-third of treated patients show primary nonresponse (PNR) to anti-TNF-α therapies, and 23%-50% of IBD patients experience loss of response (LOR) to these biologics during subsequent treatment. There is still no recognized predictor for evaluating the efficacy of anti-TNF drugs. This review summarizes the existing predictors of PNR and LOR to anti-TNF in IBD patients. Most predictors remain controversial, and only previous surgical history, disease manifestations, drug concentrations, antidrug antibodies, serum albumin, some biologic markers, and some genetic markers may be potentially predictive. In addition, we also discuss the next steps of treatment for patients with PNR or LOR to TNF antagonists. Therapeutic drug monitoring plays an important role in treatment selection. Dose escalation, combination therapy, switching to a different anti-TNF drug, or switching to a biologic with a different mechanism of action can be selected based on the concentration of the drug and/or antidrug antibodies.

Predictors of favorable outcome and mortality after endovascular thrombectomy in young Chinese patients with large vascular occlusions.

Background: Endovascular thrombectomy (EVT) has evolved into the standard treatment for patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO). However, little information is available on the management of EVT in young patients with AIS-LVO in China. The purpose of this study was to assess the favorable outcomes and mortality rates after 90 days of EVT in young Chinese patients with AIS-LVO and their predictors. Methods: This retrospective study included young Chinese patients aged 18-50 years with AIS-LVO. The primary efficacy endpoint was the modified Rankin scale (mRS) score at day 90, and the primary safety endpoint was mortality within 90 days. Using univariate and multivariate logistic regression analyses, the associations between clinical, imaging, and procedure variables and favorable (mRS 0-2) outcomes or mortality at 90 days were analyzed. Results: A total of 113 patients were included in the study with a mean age of 43.1 ± 6.3 years. Symptomatic intracranial hemorrhage (sICH) occurred in 8 (7.1%) patients. Favorable functional outcomes (mRS 0-2) were recovered in 42.5% of patients at 3 months. After 90 days, the mortality rate was 32.3%. Multivariate analysis revealed that the increase in admission NIHSS score was associated with a lower probability of functional independence (aOR 1.08, 95% CI 1.02-1.15, p = 0.01 and aOR 1.01, 95% CI 1-1.01, p = 0.008, respectively) and a higher probability of death at 90 days (aOR 1.1, 95% CI 1.03-1.18, p = 0.007 and aOR 1.00, 95% CI 1-1.01, p = 0.021, respectively). Conclusion: This study demonstrate that EVT provides higher rates of arterial recanalization, rather than better favorable outcomes and lower risk of death at 3 months in young Chinese patients with AIS-LVO. Increased NIHSS scores on admission may be associated with poor patient prognosis.