OBJECTIVE: To summarize the research progress of suture augmentation (SA) in anterior cruciate ligament (ACL) reconstruction. METHODS: A comprehensive review of recent literature about SA in ACL reconstruction at home and abroad was conducted. The efficacy of SA in ACL reconstruction was evaluated by examining the definition, biomechanics, and histological studies of SA, along with its clinical application status in ACL reconstruction. RESULTS: SA demonstrates significant advantages in enhancing the biomechanical stability of ACL grafts, reducing the risk of re-rupture, and accelerating postoperative recovery. Specifically, SA improves graft stiffness, ultimate failure strength, and cyclic stability, thereby diminishing the risk of early postoperative failure and joint instability. Histologically, it fosters remodeling and tendon-bone integration through early load-sharing mechanisms; however, stress shielding may interfere with natural remodeling processes, warranting further attention. Clinically, SA reduces graft failure rates and the need for revision surgeries, markedly improving knee joint stability and functional recovery in young patients. Nevertheless, its impact on graft maturation and potential complications remains controversial. CONCLUSION Despite the many advantages of SA in ACL reconstruction, future endeavors should focus on optimizing tensioning techniques, developing bioactive materials, and conducting large-scale randomized controlled trials to further elucidate its clinical value and scope of applicability, providing a more reliable solution for ACL reconstruction.
Humans ; Anterior Cruciate Ligament Reconstruction/methods* ; Biomechanical Phenomena ; Anterior Cruciate Ligament/surgery* ; Anterior Cruciate Ligament Injuries/surgery* ; Suture Techniques ; Sutures ; Tendons/transplantation* ; Joint Instability/prevention & control* ; Knee Joint/surgery*

Intervertebral disc degeneration (IDD) is largely attributed to impaired endogenous repair. Nucleus pulposus-derived stem cells (NPSCs) senescence leads to endogenous repair failure. Small extracellular vesicles/exosomes derived from mesenchymal stem cells (mExo) have shown great therapeutic potential in IDD, while whether mExo could alleviate NPSCs senescence and its mechanisms remained unknown. We established a compression-induced NPSCs senescence model and rat IDD models to evaluate the therapeutic efficiency of mExo and investigate the mechanisms. We found that mExo significantly alleviated NPSCs senescence and promoted disc regeneration while knocking down thioredoxin (TXN) impaired the protective effects of mExo. TXN was bound to various endosomal sorting complex required for transport (ESCRT) proteins. Autocrine motility factor receptor (AMFR) mediated TXN K63 ubiquitination to promote the binding of TXN on ESCRT proteins and sorting of TXN into mExo. Knocking down exosomal TXN inhibited the transcriptional activity of nuclear factor erythroid 2-related factor 2 (NRF2) and activator protein 1 (AP-1). NRF2 and AP-1 inhibition reduced endogenous TXN production that was promoted by exosomal TXN. Inhibition of NRF2 in vivo diminished the anti-senescence and regenerative effects of mExo. Conclusively, AMFR-mediated TXN ubiquitination promoted the sorting of TXN into mExo, allowing exosomal TXN to promote endogenous TXN production in NPSCs via TXN/NRF2/AP-1 feed-forward circuit to alleviate NPSCs senescence and disc degeneration.

Methods:This study was a cross-sectional study. A prospective cohort study enrolled 42 patients with clinically suspected acute cerebrovascular disease and those undergoing follow-up examinations after intracranial vascular stenting at the First Affiliated Hospital of Zhengzhou University from June 2024 to May 2025. All patients underwent UHR PCD-CT examinations of the head and neck. Reconstructions were performed based on raw data, yielding conventional standard resolution (SR group) reconstructions and UHR images reconstructed using four distinct convolution kernels (Hv40, Hv48, Hv56, Hv64) in separate groups (Hv40 UHR group, Hv48 UHR group, Hv56 UHR group, Hv64 UHR group). Regions of interest were selected in the anterior cerebral artery, middle cerebral artery, posterior cerebral artery, posterior communicating artery, and anterior communicating artery. CT values and standard deviation (SD) values were measured for each artery, and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Additionally, the sharpness of the vessel edges and the full-width-half-maximum (FWHM) of each artery were measured. One-way analysis of variance or the nonparametric Kruskal-Wallis test was used to compare the subjective and objective image quality metrics across the five groups. Pairwise comparisons were performed using the LSD test or Dunn method.Results:Statistically significant differences were observed in the overall comparison of vascular imaging SD, SNR, CNR, vascular edge sharpness, and FWHM among the SR group, Hv40 UHR group, Hv48 UHR group, Hv56 UHR group, and Hv64 UHR group ( P<0.05). No statistically significant differences in CT values were found ( P>0.05). Pairwise comparisons revealed statistically significant differences between all groups ( P<0.05), except that no significant differences were observed in image SD, SNR, CNR, vascular edge sharpness, or FWHM between the Hv56 UHR and Hv64 UHR groups ( P>0.05). Conclusions:UHR PCD-CT provides better image quality for neurovascular imaging. For the display of small intracranial vessels, the Hv64 provides sharper vessel walls and better subjective image quality compared to the less sharp convolutional cores.Objective:To explore the value of ultra-high resolution (UHR) photon-counting detector CT (PCD-CT) to improve the quality of neurovascular images.

Objective:To evaluate the efficacy and safety of venetoclax in combination with multidrug chemotherapy in patients with newly diagnosed acute leukemia of ambiguous lineage (ALAL) .Methods:A retrospective analysis of clinical data was performed on patients with newly diagnosed ALAL who were hospitalized at Jiangsu Provincial People's Hospital from June 2021 to July 2024. Of the 13 patients who received initial induction therapy with venetoclax combined with multidrug chemotherapy, 8 received VAA+P regimen, and 5 received V+IA regimen. Patients with FLT3 mutation were treated with FLT3 inhibitor, and Ph + patients received an additional tyrosine kinase inhibitor. Overall survival (OS), disease-free survival (DFS), and adverse events were analyzed. Results:According to the World Health Organization 5th edition of the classification of hematolymphoid tumors, the immunophenotypes were T/myeloid mixed-phenotype acute leukemia (MPAL) ( n=4), B/myeloid MPAL ( n=7), and ALAL- not otherwise specified ( n=2). Of the seven patients with B/myeloid MPAL, four were Ph + and belonged to the group with specific gene abnormalities of ALAL. Three patients had FLT3 mutation (one with FLT3-TKD mutation and two with FLT3-ITD mutation). Prior to the second course of consolidation therapy, the efficacy of venetoclax induction therapy was evaluated, and a complete response rate of 100% was achieved in 13 patients. In the subsequent consolidation therapy phase, one patient discontinued treatment and was lost to follow-up; nine patients underwent allogeneic hematopoietic stem cell transplantation, four of whom died due to posttransplant complications and five achieved DFS. Of the three patients (≥70 years old) who received consolidation therapy as before, two achieved DFS and one died due to central nervous system leukemia. The median OS time was not reached in 13 patients; the 75th percentile survival time was 12.0 months, with a 12-month cumulative survival rate of 64.5%. The median DFS time was not reached in all patients; the 75th percentile DFS time was 8.2 months, with a 12-month cumulative DFS rate of 67.1%. All patients experienced grade 3 or 4 hematologic toxicity, including neutropenia and thrombocytopenia, during and after induction therapy. All patients recovered hematopoietic function after the initial induction therapy, with no fatal hemorrhage, tumor lysis syndrome, neurological adverse events, or grade 3 or higher organ toxicity, excluding preexisting conditions. Conclusion:Venetoclax in combination with multidrug chemotherapy was effective and associated with tolerable adverse reactions in patients with newly diagnosed ALAL.

Objective: To investigate if high glucose (HG) exacerbates Porphyromonas gingivalis (P.g) lipopolysaccharide (LPS)-induced inflammatory response in human gingival fibroblasts (HGFs) and to explore the underlying mechanisms. To provide a basis for the mechanism of diabetes aggravating periodontitis. Methods: HGFs were divided into four groups: the control group (basal medium), the LPS group (treated with 5 μg/mL P.g-LPS for 24 h), the HG group (treated with 25 mmol/L glucose for 24 h), and the HG+LPS group (treated with 25 mmol/L glucose + 5 μg/mL P.g-LPS for 24 h). After culturing for 24 h in the respective media, the cells were harvested for experiments. Intracellular reactive oxygen species (ROS) and mitochondrial reactive oxygen species (mtROS) were detected using 2 ', 7' - dichlorodihydrofluorescein diacetate (DCFH-DA) and MitoSOX Red staining, respectively. Fluorescence intensity was analyzed by confocal fluorescence microscopy and directly measured in cell suspension. Immunofluorescence was used to detect changes in mitochondrial DNA (mtDNA) content of HGFs. Real-time fluorescence quantitative PCR was used to detect the content of mtDNA in cytoplasm and cell supernatant. Protein expression of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway was assessed by western blot, while mRNA expression levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) were detected by PCR. Results: Compared to the control group, both the LPS group and the HG group exhibited a significant increase in ROS and mtROS, with a more pronounced elevation in the HG+LPS group, demonstrating a synergistic effect (ROS: F = 396.5, P < 0.001; mtROS: F = 29.38, P < 0.001, CI < 1). The cytoplasmic mtDNA content was significantly elevated in the LPS group, with a more marked increase in the HG+LPS group (F = 27.85, P < 0.001). The supernatant mtDNA levels were significantly higher in both the LPS and HG groups, with a more pronounced elevation in the HG+LPS group (F = 15.26, P < 0.001). The phosphorylated proteins p-STING, p-TBK1, and p-P65 in the cGAS-STING pathway showed varying degrees of activation in the LPS and HG groups, reaching the highest levels in the HG+LPS group (p-STING: F = 52.67, P < 0.001; p-TBK1: F = 15.67, P = 0.001; p-P65: F = 9.83, P = 0.005), while p-IRF3 showed no significant differences among the groups (P = 0.072). Pro-inflammatory cytokine TNF-α was significantly higher in the HG+LPS group compared to the control group (F = 15.05, P < 0.001), and IL-1β increased in both the LPS and HG groups, with a more pronounced rise in the HG+LPS group (F = 30.98, P < 0.001). IL-6 showed no significant differences among the groups (P = 0.847). Conclusion High glucose and LPS act synergistically to enhance oxidative stress, accompanied by increased mtDNA release, which activates the cGAS-STING pathway, thereby amplifying the inflammatory response in HGFs.

Accurate prediction of drug responses in cancer cell lines (CCLs) and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine. Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response (CDR) prediction, challenges remain regarding the generalization of new drugs that are unseen in the training set. Herein, we propose a multimodal fusion deep learning (DL) model called drug-target and single-cell language based CDR (DTLCDR) to predict preclinical and clinical CDRs. The model integrates chemical descriptors, molecular graph representations, predicted protein target profiles of drugs, and cell line expression profiles with general knowledge from single cells. Among these features, a well-trained drug-target interaction (DTI) prediction model is used to generate target profiles of drugs, and a pretrained single-cell language model is integrated to provide general genomic knowledge. Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods. Further ablation studies verified the effectiveness of each component of our model, highlighting the significant contribution of target information to generalizability. Subsequently, the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments, demonstrating its potential for real-world applications. Moreover, DTLCDR was transferred to the clinical datasets, demonstrating satisfactory performance in the clinical data, regardless of whether the drugs were included in the cell line dataset. Overall, our results suggest that the DTLCDR is a promising tool for personalized drug discovery.

ObjectiveTo analyze the changing trend of the disease burden of acute viral hepatitis （AVH） globally and in China from 1990 to 2021， and to provide a basis for optimizing prevention and control strategies. MethodsRelated data were extracted from the Global Burden of Disease 2021 database， including incidence rate， mortality rate， and disability-adjusted life years （DALY） for AVH globally and in China from 1990 to 2021， and the patients were divided into groups according to region， age， sex， and type of hepatitis. The Joinpoint regression model was used to calculate average annual percentage change （AAPC） and its 95% confidence interval （CI）. ResultsFrom 1990 to 2021， there was a tendency of reduction in the age-standardized incidence rate， mortality rate， and DALY rate of AVH globally， with an average annual reduction of 1.02% （95%CI： -1.10% to -0.94%， P<0.001）， 3.97% （95%CI： -4.12% to -3.82%， P<0.001）， and 3.64% （95%CI： -3.84% to -3.44%， P<0.001）， respectively； in China， there was also a tendency of reduction in these indicators， with an average annual reduction of 1.63% （95%CI： -1.70% to -1.57%， P<0.001）， 9.24% （95%CI： -9.51% to -8.97%， P<0.001）， and 7.93% （95%CI： -8.15% to -7.71%， P<0.001）， respectively. In addition， China’s share of the global disease burden of AVH continued to decrease； the proportion of new cases decreased from 24% in 1990 to 15% in 2021， the proportion of deaths decreased from 19% to 4%， and the proportion of DALY decreased from 16% to 4%. From 1990 to 2021 globally， the peaks in the incidence rate， mortality， and DALY of AVH were observed in children under 5 years of age； in China， although the peak incidence rate of the disease was still observed in children under 5 years of age， there was a tendency of increase in the incidence rate of AVH among young adults aged 25 — 29 years in recent years， with the most significant increase in the cases of acute hepatitis B （accounting for 59% of the cases in this age group）， while the disease burden of mortality and DALY mainly affected the middle-aged and elderly populations. The disease burden of AVH in the male population was higher than that in the female population. As for the distribution of disease types， acute hepatitis A was the predominant type of AVH， accounting for 64% globally and 48% in China， whereas acute hepatitis B was the leading cause of mortality and DALY， accounting for 50% of deaths globally， 80% of deaths in China， 47% of DALY globally， and 69% of DALY in China. ConclusionThere is a tendency of reduction in the disease burden of AVH globally and in China from 1990 to 2021， but there is a tendency of increase in the incidence rate of AVH among young adults in China， especially acute hepatitis B. It is necessary to implement targeted prevention and control strategies.

Colorectal cancer is one of the most prevalent malignant tumors in the digestive system globally,with both its incidence and mortality showing an upward trend.In recent years,immunother-apy has become a research focus in the prognosis of CRC.Different states of tumor-infiltrating lym-phocytes(TILs)in patients have distinct impacts on tumor progression.The diversity of TILs and their interactions among cells reflect the complex relationship between tumors and the immune system.Patients with mismatch repair-deficient and microsatellite instability-high(dMMR/MSI-H)molecular phenotypes exhibit higher levels of TILs.Moreover,immune checkpoint inhibitors(ICIs),which are relevant targeted drugs for immune checkpoint blockade,also demonstrate a higher response rate in colorectal cancer patients with dMMR/MSI-H molecular phenotypes.This article reviewed the basic characteristics and prognostic value of TILs,as well as the relationship between dMMR/MSI-H and the immunological characteristics of colorectal cancer patients.

Accurate prediction of drug responses in cancer cell lines(CCLs)and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine.Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response(CDR)prediction,chal-lenges remain regarding the generalization of new drugs that are unseen in the training set.Herein,we propose a multimodal fusion deep learning(DL)model called drug-target and single-cell language based CDR(DTLCDR)to predict preclinical and clinical CDRs.The model integrates chemical descriptors,mo-lecular graph representations,predicted protein target profiles of drugs,and cell line expression profiles with general knowledge from single cells.Among these features,a well-trained drug-target interaction(DTI)prediction model is used to generate target profiles of drugs,and a pretrained single-cell language model is integrated to provide general genomic knowledge.Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods.Further ablation studies verified the effectiveness of each component of our model,highlighting the significant contribution of target information to generalizability.Subsequently,the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments,demonstrating its potential for real-world applications.Moreover,DTLCDR was transferred to the clinical datasets,demonstrating satisfactory performance in the clinical data,regardless of whether the drugs were included in the cell line dataset.Overall,our results suggest that the DTLCDR is a promising tool for personalized drug discovery.