Osteoarthritis (OA), a highly prevalent degenerative joint disease worldwide, is defined by articular cartilage degradation, abnormal bone remodeling, and persistent chronic inflammation. It severely compromises patients’ quality of life, and currently, there is no radical cure. Abnormal mechanical stress is widely regarded as a core driver of OA pathogenesis, and the exploration of mechanical signal perception and transduction mechanisms has become crucial for deciphering OA’s pathophysiological processes. Piezo1, a key mechanosensitive cation channel belonging to the Piezo protein family, has recently gained significant attention due to its pivotal role in mediating cellular responses to mechanical stimuli in joint tissues. This review systematically examines Piezo1’s expression patterns, regulatory mechanisms, and pathological functions in OA, with a particular focus on its dual roles in modulating chondrocyte homeostasis and bone metabolism disorders, while also delving into the underlying molecular signaling pathways and potential therapeutic implications. Piezo1, consisting of approximately 2 500 amino acids and forming a unique trimeric propeller-like structure, is widely expressed in chondrocytes, osteocytes, mesenchymal stem cells, and synovial cells. It exhibits permeability to cations such as Ca²⁺, K⁺, and Na⁺, and directly responds to membrane tension changes induced by mechanical stimuli like fluid shear stress and mechanical overload. In OA patients and animal models, Piezo1 expression is significantly upregulated, especially in cartilage regions subjected to abnormal mechanical stress (e.g., human temporomandibular joint cartilage). This overexpression is closely associated with aggravated cartilage degeneration, increased chondrocyte apoptosis, accelerated cellular senescence, and intensified inflammatory responses. Mechanical overload and pro-inflammatory cytokines (e.g., IL-1β) are key inducers of Piezo1 upregulation: IL-1β activates the PI3K/AKT/mTOR signaling pathway to enhance Piezo1 expression, forming a pathogenic positive feedback loop that inhibits chondrocyte autophagy, promotes apoptosis, and further accelerates joint degeneration. Mechanistically, Piezo1 mediates OA progression through multiple interconnected pathways. When activated by mechanical stress, Piezo1 triggers excessive Ca²⁺ influx, leading to endoplasmic reticulum stress (ERS) and mitochondrial dysfunction, which directly induce chondrocyte apoptosis. This process involves the activation of downstream signaling cascades such as cGAS-STING and YAP-MMP13/ADAMTS5. YAP, a transcriptional regulator, upregulates the expression of matrix metalloproteinase 13 (MMP13) and aggrecanase (ADAMTS5), thereby accelerating cartilage matrix degradation. Additionally, Piezo1-driven Ca²⁺ overload promotes the accumulation of reactive oxygen species (ROS) and upregulates senescence markers (p16 and p21), accelerating chondrocyte senescence via the p38MAPK and NF-κB pathways. Senescent chondrocytes secrete senescence-associated secretory phenotype (SASP) factors (e.g., IL-6, IL-1β), further amplifying joint inflammation. In terms of bone metabolism, Piezo1 maintains joint homeostasis by promoting the differentiation of fibrocartilage stem cells into chondrocytes and balancing bone formation and resorption through regulating the FoxC1/YAP axis and RANKL/OPG ratio. Therapeutically, targeting Piezo1 shows promising potential. Preclinical studies have demonstrated that Piezo1 inhibitors (e.g., GsMTx4) can reduce joint damage and alleviate pain in OA mice. Simultaneously, siRNA-mediated co-silencing of Piezo1 and TRPV4 (another mechanosensitive channel) decreases intracellular Ca²⁺ concentration, inhibits chondrocyte apoptosis, and promotes cartilage repair. Conditional knockout of Piezo1 using Gdf5-Cre transgenic mice alleviates cartilage degeneration in post-traumatic OA models by downregulating MMP13 and ADAMTS5 expression. Despite existing challenges, such as off-target effects of inhibitors, inefficient local drug delivery, and interindividual genetic variability, strategies like developing selective Piezo1 antagonists, optimizing targeted nanocarriers, and combining Piezo1-targeted therapy with physical therapy provide viable avenues for clinical translation. The authors propose that Piezo1 serves as a critical therapeutic target for OA, and future research should focus on deciphering its context-dependent regulatory networks, developing tissue-specific intervention strategies, and validating their efficacy and safety in clinical trials to address the unmet medical needs of OA patients.

Objective: To investigate and analyze the influencing factors and intervention strategy preferences of preoperative dental anxiety in patients undergoing oral implant surgery, and to provide a basis for the clinical formulation and implementation of targeted interventions. Methods: This study was approved by the Hospital Medical Ethics Committee, and written informed consent was obtained from all participants. Using convenience sampling, a cross-sectional survey was conducted from January to October 2025 among 210 patients in the Department of Implantology of a tertiary dental hospital. All participants had been clinically diagnosed and were scheduled to undergo oral implant surgery on the day of the survey. The survey was conducted using a General Information Questionnaire, the Modified Dental Anxiety Scale (MDAS), and an Anxiety Cause Questionnaire. The General Information Questionnaire collected data on patients’ gender, age, presence of systemic diseases, dental treatment history, number of implants, whether bone augmentation was required. The MDAS was used to assess patients’ dental anxiety levels via MDAS scores, with a score ≥ 12 defined as dental anxiety. The Anxiety Cause Questionnaire covered the following items: fear of pain, concern that the instruments might cause permanent damage to their teeth, concern about the dentist’s technique and inability to achieve ideal results, fear of local anesthesia, concern about cross-infection, financial pressure, exposure to an unfamiliar environment and strangers, and previous unpleasant dental experiences. The MDAS scores of the items in the Anxiety Cause Questionnaire and General Information Questionnaire were analyzed using the Mann-Whitney U test or Kruskal-Wallis H test for univariate analysis, and factors with statistical significance in the univariate analysis were further analyzed using binary logistic regression for multivariate analysis. An Intervention Strategy Preference Questionnaire was used to survey patients’ preferences for the following interventions: understanding the surgical procedure, verbal reassurance from medical staff, distraction methods such as listening to music or using stress balls, staying in a physically and mentally relaxing environment, and others. Results: The average preoperative MDAS score of patients undergoing oral implant surgery was 10.91 ± 3.40, and the incidence of dental anxiety (MDAS ≥ 12) was 34.8% (73/210). Univariate analysis showed that female patients, patients aged < 45 years, had significantly higher MDAS scores (P < 0.05). Patients who selected “fear of pain” (79.0%), “fear of local anesthesia” (21.0%), and “exposure to an unfamiliar environment and strangers” (4.8%) as causes of their anxiety had higher MDAS scores than those who did not select these items (P < 0.05). Multivariate logistic regression analysis showed that patient's age (OR = 0.420), fear of pain (OR = 4.234), and exposure to an unfamiliar environment and strangers (OR = 8.220) were independent influencing factors of preoperative dental anxiety in patients undergoing oral implant surgery (P < 0.05). The Intervention Strategy Preference Questionnaire showed that “verbal reassurance from medical staff” (45.2%), “distraction” (43.3%), and “understanding the surgical procedure” (39.5%) were the most preferred intervention strategies among patients. Conclusions Preoperative dental anxiety is common among some patients undergoing oral implant surgery, particularly young and middle-aged patients, those treated by less experienced physicians, and those experiencing anxiety due to a fear of pain or exposure to an unfamiliar environment and strangers. Clinical attention should focus on these patient populations, and systematic preoperative education and psychological counseling should be provided accordingly.

Flap transplantation is a critical surgical strategy for the reconstruction of tissue defects caused by trauma, tumor resection, and congenital malformations, and its survival rate directly determines surgical efficacy and patient prognosis. Following transplantation, flaps inevitably undergo ischemia-reperfusion (I/R) injury, during which oxidative stress, inflammatory responses, and metabolic disturbances are intricately intertwined, ultimately leading to cellular injury and tissue necrosis. Recent studies have demonstrated that multiple forms of programmed cell death—including apoptosis, pyroptosis, ferroptosis, necroptosis, and PANoptosis—play central roles in flap I/R injury. The extensive crosstalk and molecular interactions among these pathways form a highly complex cell death network. Specifically, apoptosis is mediated by the imbalance of Bcl-2 family proteins and the activation of cysteine-dependent aspartate-specific protease (caspase) cascades; pyroptosis is driven by the NLRP3-caspase-1-GSDMD axis, resulting in membrane pore formation and the release of pro-inflammatory cytokines; ferroptosis is characterized by iron-dependent lipid peroxidation and dysfunction of glutathione peroxidase 4 (GPX4); necroptosis is triggered by the receptor-interacting serine/threonine-protein kinase 1 (RIPK1)-RIPK3-MLKL signaling complex, leading to membrane rupture; and PANoptosis represents an integrated form of inflammatory cell death that coordinates multiple death pathways. Importantly, these forms of programmed cell death are not independent but are interconnected through extensive signaling crosstalk. Key regulatory molecules, including caspase-8, reactive oxygen species (ROS), nuclear factor-κB (NF-κB), and nuclear factor erythroid 2-related factor 2 (Nrf2), collectively modulate the dynamic balance among these pathways. Therefore, the multidimensional interplay and spatiotemporal dynamics of programmed cell death constitute a fundamental pathological basis of flap I/R injury. This review systematically summarizes the latest advances in the mechanisms and interactions of various programmed cell death pathways in flap I/R injury, aiming to elucidate the underlying regulatory network. These insights may provide novel theoretical foundations for optimizing flap protection strategies, improving flap survival, and promoting tissue repair.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Purpose: This research observed the efficacy and safety of soft tissue expansion combined with recombinant human epidermal growth factor (rhEGF) in repairing second-degree scald scars. Methods: This study conducted a prospective, single-blind, randomized controlled trial. Eighty-four patients with deep second-degree scald scars were evenly divided into the control and observation groups. The control group was treated with soft tissue expansion, and the observation group was additionally treated with rhEGF. The skin expansion and wound healing times were compared. The changes in wound exudate and inflammation around the wound were observed after first-stage surgery. The hydroxyproline (OHP) and collagen I/III ratios were compared during the second stage of surgery.The complications and repair effects during treatment were evaluated. Results: The observation group exhibited lower expansion time, immediate retraction rate, and wound healing time, higher skin expansion rate, higher wound exudate score and inflammation score, higher OHP, lower collagen I/III, lower complication rate, and higher total effective rate than the control group (all P < 0.05). Conclusion Skin soft tissue expansion combined with rhEGF is more effective in repairing second-degree scald scars, which can effectively increase skin expansion area and reduce wound infection and complications.

Objective:To explore the effects of age and gender on the sagittal spinal-pelvic parameters during the natural aging process of healthy adults.Methods:A total of 647 Chinese healthy adults who underwent health check-ups at the Second Affiliated Hospital of Zhejiang University School of Medicine and Songyang County People's Hospital, from January 2017 to September 2024 were collected. There were 277 males and 370 females, aged 18-93 years. Anteroposterior and lateral X-ray films of the whole spine were taken to evaluate the spinal-pelvic sagittal morphology. The following parameters were measured: thoracic kyphosis (TK), lumbar lordosis(LL), sacral slope (SS), pelvic incidence (PI), pelvic tilt (PT), global tilt (GT), T 1-pelvic angle (TPA), sagittal vertical axis (SVA), thoracic Cobb angle (T-Cobb), lower end vertebra of thoracic Cobb angle (T-LEV), apex vertebra of thoracic Cobb angle (T-Apex), lumbar Cobb angle (L-Cobb). Compare the differences in spine-pelvis parameters among patients of different genders and age groups (in this study, the subjects were subdivided into the 18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80-93 years groups according to the age range). Results:The results showed that GT, SVA, TPA, and PT increased with age ( P<0.05). For males aged 18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80-93 years, PT values were 8.58°±6.47°, 9.60°±5.63°, 12.65°±7.13°, 11.00°±6.99°, 13.01°±8.63°, 15.77°±8.02°, and 18.47°±10.03° respectively; for females in the same age groups, the PT values were 8.44°±6.83°, 9.00°±6.44°, 11.84°±7.35°, 12.07°±7.51°, 15.44°±9.39°, 19.26°±8.28°, and 18.17°±9.43° respectively. For males in these age groups, the global tilt (GT) values were 6.37°±7.20°, 8.77°±6.51°, 10.38°±9.07°, 8.80°±7.49°, 10.80°±8.62°, 16.07°±10.42°, and 21.99°±12.65° respectively; for females, the GT values were 4.46°±8.09°, 5.96°±7.83°, 8.17°±6.88°, 9.41°±8.03°, 9.96°±1.39°, 17.89°±9.39°, and 19.55°±12.34° respectively. The sagittal vertical axis (SVA) values for males in the age groups were -7.94±25.57 mm, -2.98±25.69 mm, -4.63±20.90 mm, -6.43±32.81 mm, 7.85±43.39 mm, 36.49±53.89 mm, and 55.57±51.10 mm respectively; for females, they were -24.12±31.35 mm, -17.49±25.12 mm, -17.88±22.72 mm, -8.25±30.91 mm, 8.80±27.45 mm, 28.67±38.22 mm, and 23.23±35.19 mm respectively. For males, the thoracic pelvic angle (TPA) values across the age groups were 4.46°±5.94°, 6.05°±5.38°, 9.58°±9.35°, 7.52°±7.64°, 11.23°±9.59°, 16.32°±12.38°, and 18.49°±11.70° respectively; for females, the TPA values were 2.72°±6.88°, 3.68°±6.26°, 7.30°±6.11°, 7.44°±6.75°, 12.64°±9.79°, 19.08°±10.39°, and 16.79°±13.19° respectively. T-Cobb, T-LEV, and T-Apex increased slowly with age ( P<0.05). The pelvic incidence (PI) remained relatively constant in males ( P>0.05), while it increased slowly with age in females ( P<0.05). Conclusions:Sagittal anteversion of the spinal-pelvis increases with age. Gender differences are reflected in specific changes in the fluctuation amplitude of certain parameters (such as PI), and the fluctuations of indicators like T-Cobb, T-LEV, and T-Apex are closely related to the natural aging process of the spine.

Objective:To compare the safety and efficacy of 3D-printed porous bioceramic artificial bone and artificial bone substitutes in the treatment of limb bone defects.Methods:A total of 220 patients with post-traumatic limb bone defects admitted to Xijing Hospital Affiliated to Air Force Medical University of the Chinese People's Liberation Army (34 cases), the Third Hospital of Hebei Medical University (60 cases), Xi'an Honghui Hospital (28 cases), the Third Hospital of Southern Medical University (18 cases), Changsha Third Hospital (28 cases), Foshan Traditional Chinese Medicine Hospital (16 cases), Foshan Fuxing Chancheng Hospital (12 cases), and Henan Provincial Orthopaedic Hospital (24 cases) from May 2022 to October 2023 were included as research subjects. According to the manufacturing method of the bone graft material, the subjects were randomly divided into the 3D printed porous bioceramic artificial bone group (3D printing group) and the artificial bone substitute group (non-3D printing group) at a ratio of 1:1 by the envelope method. Adverse events that might be related to the surgery were selected through correlation evaluation and classified as abnormal laboratory indicators, systemic or other site symptoms and abnormalities, and local symptoms and abnormalities of the affected limb. The safety of the two groups was compared. The bone graft fusion rate, bone defect repair and healing rate, and short form 12 (SF-12) score of the two groups were calculated to evaluate the postoperative recovery.Results:Thirty-two cases were excluded (4 cases refused to use their data after reconsideration, 7 cases were not used after preoperative assessment, and 21 cases exceeded the standard for body mass index and laboratory indicators upon re-examination). A total of 188 cases were randomly divided into the 3D printing group and the non-3D printing group according to the random method, with 94 cases in each group. Among them, 11 cases in the 3D printing group and 9 cases in the non-3D printing group dropped out due to loss to follow-up. Finally, 168 cases completed the follow-up, including 83 cases in the 3D printing group and 85 cases in the non-3D printing group. In the 3D printing group, there were 53 males and 30 females, with an average age of 47.9±12.7 years; in the non-3D printing group, there were 53 males and 32 females, with an average age of 48.6±12.9 years. A total of 51 cases in the two groups experienced adverse events related to the surgery, including 13 cases of abnormal laboratory indicators (5 cases in the 3D printing group and 8 cases in the non-3D printing group), 15 cases of systemic or other site symptoms and abnormalities (9 cases in the 3D printing group and 6 cases in the non-3D printing group), and 23 cases of local symptoms and abnormalities of the affected limb (13 cases in the 3D printing group and 10 cases in the non-3D printing group). There was no statistically significant difference in the incidence of adverse events between the two groups ( P>0.05). The bone graft fusion rates of the 3D printing group and the non-3D printing group at 6 months after surgery were 99%(82/83) and 99%(84/85), respectively, and the bone defect repair and healing rates were 89%(74/83) and 89%(76/85), respectively. At the time of 12 months after surgery, the bone graft fusion rates were 99%(82/83) and 99%(84/85), respectively, and the bone defect repair and healing rates were 94%(78/83) and 92%(78/85), respectively. There was no statistically significant difference in the bone graft fusion rate and bone defect repair and healing rate between the two groups ( P>0.05). The SF-12 scores during the screening period were 27.82±2.96 points and 27.22±4.23 points in the 3D printing group and the non-3D printing group, respectively, and at 3 months after surgery were 28.08±3.13 points and 27.64±3.16 points, at 6 months after surgery were 29.42±3.10 points and 28.55±3.45 points, and at 12 months after surgery were 29.78±2.80 points and 29.58±2.94 points, respectively. There was no statistically significant difference between the groups ( P>0.05). Both groups of surgeries were successfully completed without any serious surgical or bone graft-related complications. Conclusion:The safety and efficacy of 3D-printed porous bioceramic artificial bone in the treatment of limb bone defects are not significantly different from those of currently clinically applied artificial bone substitutes.

Objective To comparatively evaluate the diagnostic value of metagenomic next-generation sequencing(mNGS)versus conventional microbial culture in spinal infections.Methods A cross-section design was conducted on 82 consecutive patients with suspected spinal infections treated between February 2022 and January 2024 at Jiangbei Branch of First Affiliated Hospital of Army Medical University(Third Military Medical University).Microbiological culture,histopathological examination,and mNGS results from infected specimens were analyzed.Clinical diagnosis,primarily based on clinical manifestations,laboratory tests and radiologic features combined with medical history,was defined as the gold standard,and then the diagnostic performance,including sensitivity and specificity,were compared between mNGS and microbial culture.Results Among the 82 patients,definitive microbiological evidence was identified in 70 cases,and mNGS demonstrated a significantly higher detection rate than microbial culture(64 vs 36 cases,78.05％vs 43.9％,P<0.05).mNGS also obtained obviously higher sensitivity,accuracy,and negative predictive value(NPV),and notably lower positive predictive value(PPV)when compared to conventional microbial culture(all P<0.05).When stratified by infection type,mNGS obtained significantly higher sensitivity and accuracy compared to microbial culture in tuberculous spinal infections(P<0.05).For non-tuberculous spinal infections,mNGS also showed superior sensitivity to microbial culture(P<0.05).Conclusion In patients with spinal infections,mNGS demonstrates a significantly higher pathogen detection rate than conventional microbial culture.This technique can provide early and broad-spectrum pathogenic microbiological evidence for spinal infection.