Methods: Fifty patients who underwent UBE-TLIF and 50 patients who underwent W-TLIF, each with >2 years of follow-up, were retrospectively analyzed. Outcomes included operative parameters, time to postoperative mobilization, paravertebral muscle atrophy and fat infiltration rates, clinical scores (Visual Analog Scale [VAS], Oswestry Disability Index [ODI], Japanese Orthopaedic Association [JOA]), modified Macnab criteria, fusion rates, and complications. Results: Compared with W-TLIF, the UBE-TLIF group had significantly less intraoperative blood loss, shorter operative times, and lower postoperative drainage volumes (p <0.05). The UBE-TLIF group showed faster postoperative recovery and shorter hospital stays. At 6 months, 1 year, and 2 years, W-TLIF patients had higher multifidus and erector spinae atrophy, and greater paravertebral muscle fat infiltration (p <0.05). The UBE-TLIF group also had lower VAS and ODI scores at 1 year and 2 years (p <0.05) and fewer surgical complications (6% vs. 10%). Fusion rates (94% vs. 92%) and modified Macnab outcomes (88% vs. 86%) were comparable (p >0.05). Conclusions UBE-TLIF is associated with reduced intraoperative trauma, quicker recovery, and fewer complications. In the long-term, it better preserves paravertebral muscle integrity and provides superior pain and functional outcomes.

The objective of this study is to map the global scientific competitive landscape in the field of artificial intelligence (AI) medical devices using scientific data. A bibliometric analysis was conducted using the Web of Science Core Collection to examine global research trends in AI-based medical devices. As of the end of 2023, a total of 55 147 relevant publications were identified worldwide, with 76.6% published between 2018 and 2024. Research in this field has primarily focused on AI-assisted medical image and physiological signal analysis. At the national level, China (17 991 publications) and the United States (14 032 publications) lead in output. China has shown a rapid increase in publication volume, with its 2023 output exceeding twice that of the U.S.; however, the U.S. maintains a higher average citation per paper (China: 16.29; U.S.: 35.99). At the institutional level, seven Chinese institutions and three U.S. institutions rank among the global top ten in terms of publication volume. At the researcher level, prominent contributors include Acharya U Rajendra, Rueckert Daniel and Tian Jie, who have extensively explored AI-assisted medical imaging. Some researchers have specialized in specific imaging applications, such as Yang Xiaofeng (AI-assisted precision radiotherapy for tumors) and Shen Dinggang (brain imaging analysis). Others, including Gao Xiaorong and Ming Dong, focus on AI-assisted physiological signal analysis. The results confirm the rapid global development of AI in the medical device field, with "AI + imaging" emerging as the most mature direction. China and the U.S. maintain absolute leadership in this area-China slightly leads in publication volume, while the U.S., having started earlier, demonstrates higher research quality. Both countries host a large number of active research teams in this domain.
Artificial Intelligence ; Bibliometrics ; Humans ; China ; Equipment and Supplies ; United States ; Biomedical Research

Recently,diffusion models have emerged as a promising paradigm for molecular design and optimization.However,most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geom-etries,with limited research on molecular sequence diffusion models.The International Union of Pure and Applied Chemistry(IUPAC)names are more akin to chemical natural language than the simplified molecular input line entry system(SMILES)for organic compounds.In this work,we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language(SMILES)and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language.We propose DiffIUPAC,a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings.Evaluation results demonstrate that our model out-performs existing methods and successfully captures the semantic rules of both chemical languages.Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints.Additionally,to illustrate the model's applicability in drug design,we conducted case studies in functional group editing,analogue design and linker design.

Objective:Objective The potential of a three- dimensional bioprinted cell-laden gelatin methactyloyl (GelMA)+ hyaluronic acid (HA) composite bioink in tissue engineering was assessed by evaluating cell viability, scaffold morphology, and cell compatibility.Methods:Rabbit chondrocytes were isolated and cultured. Composite hydrogels were prepared using GelMA and HA, and their applicability in tissue engineering was assessed by evaluating physicochemical properties, cytocompatibility, and printability. The swelling and mechanical properties of 100g/L GelMA inks as the control group, and 100g/L GelMA+ 20g/L HA inks as the experimental group were assessed following photocrosslinking of the cylindrical model. The printing resolution of the GelMA/HA mesh scaffold loaded with chondrocytes was evaluated based on appearance and expansion ratio. Cell viability was determined using cell live/dead test after 14 days, while cytocompatibility was observed through in vitro microscopy and multiple immunofluorescence staining after 7 days. GraphPad Prism 8.0 was utilized for data visualization and statistical analysis. Independent-samples t-test was employed to compare differences among groups. A P-value less than 0.05 was considered statistically significant. Results:The swelling ratio of GelMA group was 10.57±0.40, which exceeded that of the GelMA+ HA group (7.63±0.61, P<0.05). The compressive elastic modulus of GelMA+ HA group measured (77.53±4.30) kPa, significantly surpassing that of the GelMA group [(25.60±5.70) kPa, P<0.05]. The extension ratio of GelMA was 2.59±0.33, while the experimental group recorded 2.66±0.12, with no statistically significant difference between them ( P>0.05). There were no notable disparities in cell viability between the two groups; both exhibited viabilities greater than 85%. On the initial day of culture, both groups exhibited intact structures, regular pores, and a substantial number of spherical cells. After 14 days of culture, the GelMA scaffold structure appeared blurred with nearly vanished pores, while large live cells were visible. The GelMA+ HA scaffold structure was slightly more relaxed with relatively intact pores and a significant presence of live cells. Furthermore, multiple immunofluorescence staining after 7 days of culture revealed no notable disparity in cell count and collagen components between the two groups; however, cell morphology in the GelMA+ HA group displayed significant elongation and clustering. Conclusion:The GelMA+ HA hydrogel exhibits enhanced mechanical properties and reduced swelling ratio, rendering it suitable for the fabrication of complex structures. Additionally, it demonstrates excellent cell compatibility.

Recently, diffusion models have emerged as a promising paradigm for molecular design and optimization. However, most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geometries, with limited research on molecular sequence diffusion models. The International Union of Pure and Applied Chemistry (IUPAC) names are more akin to chemical natural language than the Simplified Molecular Input Line Entry System (SMILES) for organic compounds. In this work, we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language (SMILES) and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language. We propose DiffIUPAC, a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings. Evaluation results demonstrate that our model outperforms existing methods and successfully captures the semantic rules of both chemical languages. Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints. Additionally, to illustrate the model's applicability in drug design, we conducted case studies in functional group editing, analogue design and linker design.

AIM To evaluate the quality of Rubi Fructus.METHODS UPLC-Q-TOF-MS/MS was adopted in the component identification,after which the HPLC fingerprints were established,cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition.and the contents of chlorogenic acid,ferulic acid,ellagic acid,isoquercitrin,kaempferol-3-O-rutinoside,astragalin,tiliroside quercetin,kaempferol were determined.RESULTS Total 34 constituents were identified.There were 19 common peaks in the fingerprints for 31 batches of medicinal materials with the similarities of more than 0.8.Wild varieties and cultivated varieties,and medicinal materials from different producing areas could be distinguished;4 principal components demonstrated the accumulative variance contribution rate of 84.142％;8 differential components were screened,2 of which were ellagic acid and astragalin.Ellagic acid and astragalin displayed higher contents in the wild varieties than those in the cultivated varieties(P＜0.05,P＜0.01).CONCLUSION UPLC-Q-TOF-MS/MS,HPLC fingerprints combined with content determination can be used for the quality control of Rubi Fructus.

Objective:To explore the development process of family resilience in children with congenital pseudarthrosis of the tibia (CPT) and to understand the long-term challenges and coping strategies that CPT imposes on the families of affected children.Methods:This study combined purposive sampling and theoretical sampling. It selected 15 caregivers of CPT children from Hunan Children's Hospital for semi-structured interviews. Grounded theory was used to analyze the interview results.Results:The development of family resilience in CPT children's families occurred in three stages: pre-formation stage, formation stage, and maintenance stage. In facing negative emotions and family challenges, caregivers first needed to rebuild their inner beliefs. They then adjusted the family organizational model, adopted open and inclusive communication, and actively sought external support to foster the development of family resilience. Ultimately, caregivers were able to self-regulate their emotions, accumulate caregiving experience, and begin to shift their life perspective.Conclusions:The development of family resilience in CPT children's families is a dynamic, multi-stage process with interactions of multiple factors. Healthcare providers should offer professional health guidance according to the different stages of family development. Moreover, the government and schools should increase their attention and support, working together with families and healthcare providers to enhance family resilience for children with CPT.

Objective:Objective The potential of a three- dimensional bioprinted cell-laden gelatin methactyloyl (GelMA)+ hyaluronic acid (HA) composite bioink in tissue engineering was assessed by evaluating cell viability, scaffold morphology, and cell compatibility.Methods:Rabbit chondrocytes were isolated and cultured. Composite hydrogels were prepared using GelMA and HA, and their applicability in tissue engineering was assessed by evaluating physicochemical properties, cytocompatibility, and printability. The swelling and mechanical properties of 100g/L GelMA inks as the control group, and 100g/L GelMA+ 20g/L HA inks as the experimental group were assessed following photocrosslinking of the cylindrical model. The printing resolution of the GelMA/HA mesh scaffold loaded with chondrocytes was evaluated based on appearance and expansion ratio. Cell viability was determined using cell live/dead test after 14 days, while cytocompatibility was observed through in vitro microscopy and multiple immunofluorescence staining after 7 days. GraphPad Prism 8.0 was utilized for data visualization and statistical analysis. Independent-samples t-test was employed to compare differences among groups. A P-value less than 0.05 was considered statistically significant. Results:The swelling ratio of GelMA group was 10.57±0.40, which exceeded that of the GelMA+ HA group (7.63±0.61, P<0.05). The compressive elastic modulus of GelMA+ HA group measured (77.53±4.30) kPa, significantly surpassing that of the GelMA group [(25.60±5.70) kPa, P<0.05]. The extension ratio of GelMA was 2.59±0.33, while the experimental group recorded 2.66±0.12, with no statistically significant difference between them ( P>0.05). There were no notable disparities in cell viability between the two groups; both exhibited viabilities greater than 85%. On the initial day of culture, both groups exhibited intact structures, regular pores, and a substantial number of spherical cells. After 14 days of culture, the GelMA scaffold structure appeared blurred with nearly vanished pores, while large live cells were visible. The GelMA+ HA scaffold structure was slightly more relaxed with relatively intact pores and a significant presence of live cells. Furthermore, multiple immunofluorescence staining after 7 days of culture revealed no notable disparity in cell count and collagen components between the two groups; however, cell morphology in the GelMA+ HA group displayed significant elongation and clustering. Conclusion:The GelMA+ HA hydrogel exhibits enhanced mechanical properties and reduced swelling ratio, rendering it suitable for the fabrication of complex structures. Additionally, it demonstrates excellent cell compatibility.

Objective To analyze the changes of neutrophil-to-albumin ratio(NPAR),monocyte-to-lymphocyte ratio(MLR),neutrophil-to-lymphocyte ratio(NLR)and interleukin-17A(IL-17A)in patients with severe autoimmune encephalitis(AE)and the predictive value of their combined detection for prognosis.Methods A total of 105 patients with severe AE admitted from May 2021 to April 2025 were selected as the severe group.During the same period,35 patients with mild-to-moderate AE and 35 healthy controls were enrolled in a 3:1:1 ratio as the mild-to-moderate group and control group respectively.The levels of NPAR,MLR,NLR and IL-17A were compared among the three groups.Patients with severe AE were observed for one month.According to the prognosis of patients,they were divided into poor prognosis subgroup[modified Rankin scale(mRS)score≥3,n=31]and good prognosis subgroup(mRS score<3,n=74).The levels of NPAR,MLR,NLR and IL-17A in the two groups were compared,to analyze the correlation between NPAR,MLR,NLR and IL-17A levels and mRS score in patients with severe AE,and to evaluate the predictive value of combined detection of the four indicators for prognosis in these patients.Results The levels of NPAR,MLR,NLR and serum IL-17A in mild-to-moderate group and severe group were higher than those in control group,which were higher in the severe group than in the mild-to-moderate group(P<0.05).The course of disease in the poor prognosis group was longer than that in the good prognosis group,and the proportion of patients with γ-aminobutyric acid B receptor antibody and the levels of NPAR,MLR,NLR and serum IL-17A were higher than those in the good prognosis group(P<0.05).Higher levels of NPAR,MLR,NLR and serum IL-17A were all risk factors for poor prognosis of patients with severe AE(OR=2.445,4.319,2.502,1.791,P<0.05).The levels of NPAR,MLR,NLR and serum IL-17A were positively correlated with the mRS score of patients with severe AE(r=0.546,0.519,0.554,0.561,P<0.001).The area under the receiver operating characteristic(ROC)curve(AUC)of NPAR,MLR,NLR and IL-17A detected in combination in predicting the prognosis of patients with severe AE was higher than that of the four indicators detected alone(P<0.05).Conclusion The changes in NPAR,MLR,NLR and IL-17A levels in patients with AE were closely related to the severity and prognosis of the disease.In the meantime,higher levels of NPAR,MLR,NLR and serum IL-17A were risk factors for poor prognosis,and the combined detection of the four indicators could effectively improve the predictive value for prognosis in patients with severe AE.

Objective To analyze the changes of neutrophil-to-albumin ratio(NPAR),monocyte-to-lymphocyte ratio(MLR),neutrophil-to-lymphocyte ratio(NLR)and interleukin-17A(IL-17A)in patients with severe autoimmune encephalitis(AE)and the predictive value of their combined detection for prognosis.Methods A total of 105 patients with severe AE admitted from May 2021 to April 2025 were selected as the severe group.During the same period,35 patients with mild-to-moderate AE and 35 healthy controls were enrolled in a 3:1:1 ratio as the mild-to-moderate group and control group respectively.The levels of NPAR,MLR,NLR and IL-17A were compared among the three groups.Patients with severe AE were observed for one month.According to the prognosis of patients,they were divided into poor prognosis subgroup[modified Rankin scale(mRS)score≥3,n=31]and good prognosis subgroup(mRS score<3,n=74).The levels of NPAR,MLR,NLR and IL-17A in the two groups were compared,to analyze the correlation between NPAR,MLR,NLR and IL-17A levels and mRS score in patients with severe AE,and to evaluate the predictive value of combined detection of the four indicators for prognosis in these patients.Results The levels of NPAR,MLR,NLR and serum IL-17A in mild-to-moderate group and severe group were higher than those in control group,which were higher in the severe group than in the mild-to-moderate group(P<0.05).The course of disease in the poor prognosis group was longer than that in the good prognosis group,and the proportion of patients with γ-aminobutyric acid B receptor antibody and the levels of NPAR,MLR,NLR and serum IL-17A were higher than those in the good prognosis group(P<0.05).Higher levels of NPAR,MLR,NLR and serum IL-17A were all risk factors for poor prognosis of patients with severe AE(OR=2.445,4.319,2.502,1.791,P<0.05).The levels of NPAR,MLR,NLR and serum IL-17A were positively correlated with the mRS score of patients with severe AE(r=0.546,0.519,0.554,0.561,P<0.001).The area under the receiver operating characteristic(ROC)curve(AUC)of NPAR,MLR,NLR and IL-17A detected in combination in predicting the prognosis of patients with severe AE was higher than that of the four indicators detected alone(P<0.05).Conclusion The changes in NPAR,MLR,NLR and IL-17A levels in patients with AE were closely related to the severity and prognosis of the disease.In the meantime,higher levels of NPAR,MLR,NLR and serum IL-17A were risk factors for poor prognosis,and the combined detection of the four indicators could effectively improve the predictive value for prognosis in patients with severe AE.