The development of 5G remote robot-assisted gastrointestinal surgery is an important breakthrough in remote surgery in the field of four-level surgery. This paper will review the development history of 5G remote robot assisted gastrointestinal surgery, and share the Gansu province people′s hospital in 5G remote robot assisted gastrointestinal surgery about preoperative preparation, network and equipment connection,“3+2” Trocar layout, safety emergency treatment mechanism of exploratory experience, for 5G remote robot assisted gastrointestinal surgery, and the status and prospect of 5G remote robot assisted gastrointestinal surgery.

Objective:To compare the efficacies of endovascular therapy (EVT) and standard medical therapy in acute ischemic stroke (AIS) patients aged ≥85 years, and analyze the independent influencing factors for poor prognosis of AIS patients after EVT.Methods:Sixty-nine AIS patients aged ≥85 years admitted to Department of Neurology, Xi'an Third Hospital from January 2018 to April 2024, including 40 accepted EVT and 28 accepted standard medicinal therapy, were enrolled. Modified Rankin scale (mRS) was used to evaluate the prognosis of the patients 90 days after onset. General data, prognosis and complications between the EVT group and standard medical therapy group were compared. General data, treatment processes and complications between patients with good prognosis and poor prognosis in the EVT group were compared. Multivariate Logistic regression was used to analyze the independent influencing factors for poor prognosis in AIS patients after EVT.Results:Compared with the standard medical therapy, the EVT group had significantly lower NIHSS score at discharge, greater improvement in NIHSS score (NIHSS score at admission-NIHSS score at discharge), lower mRS score 90 days after onset, higher good prognosis rate, lower mortality rate within 90 days of onset, and longer hospital stay ( P<0.05). In the EVT group, 11 patients (27.5%) had good prognosis and 29 patients (72.5%) had poor prognosis 90 days after onset. Compared with the good prognosis group, the poor prognosis group had significantly higher blood glucose level and lower Alberta Stroke Program Early CT Score (ASPECT) on admission ( P<0.05). Multivariate Logistic regression analysis showed that blood glucose on admission ( OR=2.363, 95% CI: 1.134-4.928, P=0.022) and ASPECT score on admission ( OR=0.273, 95% CI: 0.088-0.854, P=0.026) were independent influencing factors for poor prognosis in AIS patients after EVT. Conclusion:AIS patients aged ≥85 years received EVT have better prognosis compared with those accepted standard medical therapy; these patients with high glucose level and low ASPECT score on admission have poor prognosis.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

Objective:To compare the efficacies of endovascular therapy (EVT) and standard medical therapy in acute ischemic stroke (AIS) patients aged ≥85 years, and analyze the independent influencing factors for poor prognosis of AIS patients after EVT.Methods:Sixty-nine AIS patients aged ≥85 years admitted to Department of Neurology, Xi'an Third Hospital from January 2018 to April 2024, including 40 accepted EVT and 28 accepted standard medicinal therapy, were enrolled. Modified Rankin scale (mRS) was used to evaluate the prognosis of the patients 90 days after onset. General data, prognosis and complications between the EVT group and standard medical therapy group were compared. General data, treatment processes and complications between patients with good prognosis and poor prognosis in the EVT group were compared. Multivariate Logistic regression was used to analyze the independent influencing factors for poor prognosis in AIS patients after EVT.Results:Compared with the standard medical therapy, the EVT group had significantly lower NIHSS score at discharge, greater improvement in NIHSS score (NIHSS score at admission-NIHSS score at discharge), lower mRS score 90 days after onset, higher good prognosis rate, lower mortality rate within 90 days of onset, and longer hospital stay ( P<0.05). In the EVT group, 11 patients (27.5%) had good prognosis and 29 patients (72.5%) had poor prognosis 90 days after onset. Compared with the good prognosis group, the poor prognosis group had significantly higher blood glucose level and lower Alberta Stroke Program Early CT Score (ASPECT) on admission ( P<0.05). Multivariate Logistic regression analysis showed that blood glucose on admission ( OR=2.363, 95% CI: 1.134-4.928, P=0.022) and ASPECT score on admission ( OR=0.273, 95% CI: 0.088-0.854, P=0.026) were independent influencing factors for poor prognosis in AIS patients after EVT. Conclusion:AIS patients aged ≥85 years received EVT have better prognosis compared with those accepted standard medical therapy; these patients with high glucose level and low ASPECT score on admission have poor prognosis.

The development of 5G remote robot-assisted gastrointestinal surgery is an important breakthrough in remote surgery in the field of four-level surgery. This paper will review the development history of 5G remote robot assisted gastrointestinal surgery, and share the Gansu province people′s hospital in 5G remote robot assisted gastrointestinal surgery about preoperative preparation, network and equipment connection,“3+2” Trocar layout, safety emergency treatment mechanism of exploratory experience, for 5G remote robot assisted gastrointestinal surgery, and the status and prospect of 5G remote robot assisted gastrointestinal surgery.

Exponential growth of the mass spectrometry (MS) data is exhibited when the mass spectrometry-based proteomics has been developing rapidly. It is a great challenge to develop some quick, accurate and repeatable methods to identify peptides and proteins. Nowadays, the spectral library searching has become a mature strategy for tandem mass spectra based proteins identification in proteomics, which searches the experiment spectra against a collection of confidently identified MS/MS spectra that have been observed previously, and fully utilizes the abundance in the spectrum, peaks from non-canonical fragment ions, and other features. This review provides an overview of the implement of spectral library search strategy, and two key steps, spectral library construction and spectral library searching comprehensively, and discusses the progress and challenge of the library search strategy.

Objective To investigate the clinical features, diagnosis and treatment of heterotopic pancreas in gastrointestinal tract. Methods A total of 60 cases of heterotopic pancreas in gastrointestinal tract diagnosed through endoscopic ultrasonography and pathological examination were treated in our hospital in the recent 10 years. Their data were retrospectively analyzed. Results Among all the 60 patients, the lesions were located in duodenal bulb cavity in 3 cases, in duodenal descendent in 2 cases, in gastric angle in 3 cases,in the junction of gastric antrum and corpus ventriculi in 2 cases and in gastric antrum in 50 cases. All of the 60 patients were definitely diagnosed through endoscopy, endoscopic ultrasonography and pathological examination. 28 patients were treated by endoscopic high-frequency electronic resection, 2 patients were treated by endoscopic mucosal resection (EMR), 30 patients were treated by surgical operation; no operative complication was found, and satisfactory clinical effects had been observed in these patients. Conclusions Endoscopic ultrasonography has great value in the diagnosis and endoscopic therapy of heterotopic pancreas in gastrointestinal tract. It can provide the guide for the choice of treatment. Minimally invasive endoscopic treatment is safe and effective for heterotopic pancreas and has great clinical value.