[Objective] To validate and optimize the platelet transfusion refractoriness (PTR) prediction model for patients with hematological disorders established by our center. [Methods] The data of patients with hematological diseases who received platelet transfusions from December 2021 to December 2022 were used as the training set, and data from January 2023 to December 2023 as the validation set. The validation set data was used to validate the predictive model constructed on the training set. Relevant risk factors for PTR were collected through literature review and preliminary studies。 The patients were divided into effective and ineffective groups according to the corrected count increment (CCI) of platelet counts. Predictive factors were screened using univariate and multivariate logistic regression. The calibration of the model were assessed via calibration curves, while discrimination, accuracy, sensitivity, and specificity were evaluated using receiver operating characteristic (ROC) curves Clinical utility was further analyzed with decision curve analysis (DCA). [Results] The Hosmer-Lemeshow (H-L) goodness-of-fit test for the validation set yielded S: P=0.000, indicating that the original model needs optimization. Baseline comparisons and logistic regression identified the number of red blood cell units (RBCU) and platelet units (PLT-U) transfused as key predictors for the optimized model. The H-L goodness-of-fit test S: P values for the training and validation sets were 0.930 and 0.056, respectively; the ROC areas were 0.793 5 and 0.809 4, specificities 90.95% and 84.21%, sensitivities 59.26% and 70.04%, and accuracies 78.14% and 74.10%, respectively. DCA demonstrated clinical net benefit within a prediction probability threshold range of 0.2-0.8. [Conclusion] Transfusion volumes of RBC-U and PLT-U were inversely associated with PTR in hematological patients. The resulting PTR prediction model exhibits moderate predictive efficacy and clinical benefit.

ObjectiveBased on the concept of quality by design（QbD）， the processing process of calcined Pyritum was optimized， and its X-ray diffraction（XRD） fingerprint was established. MethodsThe safety， effectiveness and quality controllability of calcined Pyritum were taken as the quality profile（QTPP）， the color， hardness， metallic luster， phase composition， the contents of heavy metals and hazardous elements were taken as the critical quality attributes（CQAs）， and the calcination temperature， calcination time， paving thickness and particle size were determined as the critical process parameters（CPPs）. Differential thermal analysis， X-ray diffraction（XRD） and inductively coupled plasma mass spectrometry（ICP-MS） were used to analyze the correlation between the calcination temperature and CQAs of calcined Pyritum. Then， based on the criteria importance through intercriteria correlation（CRITIC）-entropy weight method， the optimal processing process of calcined Pyritum was optimized by orthogonal test. Powder XRD was used to analyze the phase of calcined Pyritum samples processed according to the best process， and the mean and median maps of calcined Pyritum were established by the superposition of geometric topological figures， and similarity evaluation and cluster analysis were carried out. ResultsThe results of single factor experiments showed that the physical phase of Pyritum changed from FeS₂ to Fe₇S₈ during the process of temperature increase， the color gradually deepened from dark yellow， and the contents of heavy metals and harmful elements decreased. The optimized processing process of calcined Pyritum was as follows：calcination temperature at 750 ℃， calcination time of 2.5 h， paving thickness of 3 cm， particle size of 0.8-1.2 cm， vinegar quenching 1 time［Pyritum-vinegar（10∶3）］. After calcination， the internal structure of Pyritum was honeycomb-shaped， which was conducive to the dissolution of active ingredients. XRD fingerprints of 13 batches of calcined Pyritum characterized by 10 common peaks were established. The similarities of the relative peak intensities of the XRD fingerprints of the analyzed samples were>0.96， and it could effectively distinguish the raw products and unqualified products. ConclusionTemperature is the main factor affecting the quality of calcined Pyritum. After processing， the dissolution of the effective components in Pyritum increases， and the contents of heavy metals and harmful substances decrease， reflecting the function of processing to increase efficiency and reduce toxicity. The optimized processing process is stable and feasible， and the established XRD fingerprint can be used as one of the quality control standards of calcined Pyritum.

ObjectiveBased on the concept of quality by design（QbD）， the processing process of calcined Pyritum was optimized， and its X-ray diffraction（XRD） fingerprint was established. MethodsThe safety， effectiveness and quality controllability of calcined Pyritum were taken as the quality profile（QTPP）， the color， hardness， metallic luster， phase composition， the contents of heavy metals and hazardous elements were taken as the critical quality attributes（CQAs）， and the calcination temperature， calcination time， paving thickness and particle size were determined as the critical process parameters（CPPs）. Differential thermal analysis， X-ray diffraction（XRD） and inductively coupled plasma mass spectrometry（ICP-MS） were used to analyze the correlation between the calcination temperature and CQAs of calcined Pyritum. Then， based on the criteria importance through intercriteria correlation（CRITIC）-entropy weight method， the optimal processing process of calcined Pyritum was optimized by orthogonal test. Powder XRD was used to analyze the phase of calcined Pyritum samples processed according to the best process， and the mean and median maps of calcined Pyritum were established by the superposition of geometric topological figures， and similarity evaluation and cluster analysis were carried out. ResultsThe results of single factor experiments showed that the physical phase of Pyritum changed from FeS₂ to Fe₇S₈ during the process of temperature increase， the color gradually deepened from dark yellow， and the contents of heavy metals and harmful elements decreased. The optimized processing process of calcined Pyritum was as follows：calcination temperature at 750 ℃， calcination time of 2.5 h， paving thickness of 3 cm， particle size of 0.8-1.2 cm， vinegar quenching 1 time［Pyritum-vinegar（10∶3）］. After calcination， the internal structure of Pyritum was honeycomb-shaped， which was conducive to the dissolution of active ingredients. XRD fingerprints of 13 batches of calcined Pyritum characterized by 10 common peaks were established. The similarities of the relative peak intensities of the XRD fingerprints of the analyzed samples were>0.96， and it could effectively distinguish the raw products and unqualified products. ConclusionTemperature is the main factor affecting the quality of calcined Pyritum. After processing， the dissolution of the effective components in Pyritum increases， and the contents of heavy metals and harmful substances decrease， reflecting the function of processing to increase efficiency and reduce toxicity. The optimized processing process is stable and feasible， and the established XRD fingerprint can be used as one of the quality control standards of calcined Pyritum.

Objective To explore the risk factors for platelet transfusion refractoriness(PTR)in patients with hemato-logical disorders,construct a prediction model and validate the model efficacy.Methods Patients with hematological disor-ders who received platelet transfusion therapy in the Chengdu Second People's Hospital from December 2021 to December 2022 were retrospectively included to judge the effectiveness of platelet transfusion and screened for risk factors by univariate and multivariate logistic regression.A prediction model for PTR was constructed using receiver operating characteristic(ROC)curve,calibration curve and decision curve(DCA)to assess the differentiation,calibration and clinical value of the model,respectively.Results A total of 334 hematological patients were included,including 168 males and 176 females,with a PTR incidence of 40.4%.Univariate and multivariate logistic regression analysis showed that platelet transfusion vol-ume,erythrocyte transfusion volume,and neutrophil ratio were risk factors for PTR(P<0.05).A prediction model for PTR in hematological patients was established based on these risk factors.The area under the model's curve was 0.8377(95%CI:0.723-0.772),the sensitivity was 58.52%,and the specificity was 89.95%.The calibration curve showed that the S∶P was 0.964,the maximum absolute difference Emax was 0.032,and the average absolute difference Eavg was 0.009.The DCA a-nalysis showed that the model had clinical application value when the risk threshold ranged from 0.2 to 0.9.Conclusion The PTR prediction model based on platelet transfusion volume,erythrocyte transfusion volume and neutrophil ratio can pro-vide a basis for effective platelet transfusion in hematological patients.

Traditional spine surgery frequently encounters difficulties with inadequate surgical visualization and high risk.Robot-assisted spine surgery is quickly evolving,particularly in screw placement,providing three-dimensional imaging and precise positioning to optimize the surgical process. Robot-assisted systems can increase surgical precision,reduce operating time and radiation exposure,and improve patient prognosis. They also have strong image recognition and analysis capabilities,reducing intraoperative instability and fatigue and allowing remote manipulation.While robot-assisted spine surgery has demonstrated noteworthy advantages in regards to screw placement accuracy and reduced radiation exposure,its effects on operative time remain subject to debate,with cost being a significant hindrance to widespread implementation.Long-term clinical validation and studies of outcomes are necessary for the extensive use of robotic-assisted spine surgery.Future priorities include the enhancement of surgical navigation and imaging,integration of artificial intelligence,improvement of telesurgical capabilities,expansion of robotic functionality,and the development of policy guidance and clinical guidelines to accompany the growth of technology.Robot-assisted spine surgery enhances accuracy and safety,and is anticipated to assume an increasingly crucial role in spine surgery as technology advances and becomes more widely available.

Traditional spine surgery frequently encounters difficulties with inadequate surgical visualization and high risk.Robot-assisted spine surgery is quickly evolving,particularly in screw placement,providing three-dimensional imaging and precise positioning to optimize the surgical process. Robot-assisted systems can increase surgical precision,reduce operating time and radiation exposure,and improve patient prognosis. They also have strong image recognition and analysis capabilities,reducing intraoperative instability and fatigue and allowing remote manipulation.While robot-assisted spine surgery has demonstrated noteworthy advantages in regards to screw placement accuracy and reduced radiation exposure,its effects on operative time remain subject to debate,with cost being a significant hindrance to widespread implementation.Long-term clinical validation and studies of outcomes are necessary for the extensive use of robotic-assisted spine surgery.Future priorities include the enhancement of surgical navigation and imaging,integration of artificial intelligence,improvement of telesurgical capabilities,expansion of robotic functionality,and the development of policy guidance and clinical guidelines to accompany the growth of technology.Robot-assisted spine surgery enhances accuracy and safety,and is anticipated to assume an increasingly crucial role in spine surgery as technology advances and becomes more widely available.

Objective The present study aimed to explore the effects of CC-chemokine receptor 5 antagonism on tumor growth and immune microenvironment.Methods Cell Counting Kit-8 was used to detect in vitro anti-proliferation activity of maraviroc,a selective CC-chemokine receptor 5 inhibitor,on Lewis cells,a mouse lung adenocarcinoma cell strain.Flow cytometry and real-time quantitative PCR were respectively used to detect cell apop-tosis and Caspase 8 gene expression.In a congenic mouse lung cancer model,the mice were intraperitoneally admin-istered with maraviroc or vehicle.Tumor sizes were measured and tumor infiltrating CD4+,CD8+ and Foxp3+ cells were determined by immunofluorescent staining.Results Our results showed that maraviroc could inhibit the growth of Lewis cancer cells not only in vitro but also in vivo.This in-vitro inhibition was presumably attributable to apoptosis induction by the enhancement of Caspase 8 gene expression after maraviroc blockade.Additionally,more CD4+ and CD8+ cells but less Foxp3+ cells were detected in tumor mass from the mice administered with maraviroc.Conclusions Taken together,it can be speculated that CCR5 blockade may inhibit the growth of Lewis cells by inducing cell apoptosis and impairing the immunosuppressive tumor microenvironment.It is worthy of further investi-gation as a candidate for cancer therapy.

Objective:To assess the effectiveness and viability of 5G-enabled robot-assisted thoracolumbar internal fixation surgery, scrutinizing its benefits and potential limitations in a clinical setting.Methods:This retrospective case series study analyzed 61 patients who underwent robot-assisted remote thoracolumbar internal fixation surgery between April and December 2021. The orthopaedic robotic telesurgery system, centered at Beijing Jishuitan Hospital and utilizing 5G technology for network transmission, was used to assist in screw placement. The surgeries, distributed across ten hospitals and executed over an average distance of 1 617 km (maximum exceeding 3 000 km), were appraised by examining the accuracy of screw placement, intraoperative communication efficacy, complication rates, among other metrics, and benchmarked against traditional local procedures.Results:Telesurgery was completed successfully in all patients, averaging 92±32 minutes per operation. Out of 354 screws placed, 89.8% were positioned perfectly and 97.5% were deemed clinically acceptable. The 61 patients, followed-up for an average of 18.9±1.9 months, exhibited significant postoperative improvement in pain. The preoperative visual analogue scale (VAS) pain score was 5.74±1.30 and improved to 2.30±0.90 at discharge, a statistically significant difference ( t=11.002, P<0.001). 6 patients with thoracolumbar degenerative spine disease showed significant relief of claudication and pain symptoms postoperatively. 55 patients with thoracolumbar spine fractures had a preoperative height ratio of 62.78%±12.60% at the anterior margin of the injured vertebrae, which recovered to 85.36%±8.35% postoperatively, a statistically significant difference ( t=16.977, P<0.001). All fractures were healed at final follow-up. No perioperative complications, such as vascular or nerve injuries or infections, occurred. Additionally, there were no complications related to the use of the robot. The 5G network ensured stable transmission of robotic control signals, images, and audio signals during the procedure, with no signal delays or communication failures observed. The perfect rate (90.2% vs. 93.8%, χ 2=0.169, P=0.681) and clinical acceptability rate (99.0% vs. 100.0%, P=1.000) of remote versus local robotic-assisted screw placement in participating hospital 1 (Shantou Xin Sheng Orthopaedic Hospital) were similar. The perfect rate (87.0% vs. 85.4%, χ 2=0.075, P=0.784) and clinical acceptability rate (100.0% vs. 96.6%, χ 2=0.580, P=0.446) of remote versus local robotic-assisted screw placement in participating hospital 2 (Guizhou Provincial People's Hospital) were similar. Conclusion:5G technology enhances the remote application of robotic thoracolumbar surgery without compromising patient safety or outcome quality. It underscores the potential for broader adoption of surgical robotics, aiding in the standardization of medical practices across China, boosting healthcare efficiency, and aligning with the Healthy China strategy.

Objective:To investigate the efficacy and safety of Enterprise stenting in the treatment of symptomatic middle cerebral artery atherosclerotic stenosis.Methods:Patients with symptomatic middle cerebral artery atherosclerotic stenosis underwent Enterprise stenting in the Department of Neurology, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School from January 2020 to December 2022 were retrospectively included. The degree of residual stenosis, periprocedural complications, in-stent restenosis and stroke recurrence during follow-up were evaluated.Results:A total of 75 patients were enrolled, including 55 males (73.3%), aged 58±9.7 years. The last preprocedural symptom was stroke in 65 cases (86.7%) and transient ischemic attack in 10 cases (13.3%). Sixty-seven patients (89.3%) had the M1 segment stenosis of the middle cerebral artery, and 8 (10.7%) had the M2 segment stenosis. The degree of stenosis was 88.4%±8.90%. The median time from the last onset to stenting was 18 days (interquartile range, 13-24 days). The procedural success rate was 100%, and the residual stenosis degree was 17.3%±6.1%. Four patients (5.3%) experienced periprocedural complications, including three ischemic strokes and one symptomatic intracranial hemorrhage. Sixty-one patients (81.3%) completed 3- to 12-month follow-up, of which 7 patients (11.5%) had in-stent restenosis and 2 (3.3%) had recurrent ischemic stroke.Conclusion:Enterprise stenting may be safe and effective in the treatment of symptomatic middle cerebral artery stenosis.

Objective To construct N6-methyladenosine related long non-coding RNA(LncRNA)pairing model for renal cell carcinoma based on bioinformatics analysis of the cancer ganome atlas(TCGA)database and to explore its prognosis value.Methods Transcriptome data of RNA-sep for renal cell carcinoma and its related clinical information were downloaded from the TCGA database.Perl software was used to organize and separate LncRNA and messenger RNA(mRNA)from the transcriptome data.A total of 564 tissues from renal cell carcinoma cases and 72 normal tissues were obtained,and thus 540 renal cancer patients were eventually included.Random data table method was used to divide 540 patients with renal cancer into a training group(n=275)and a validation group(n=265)by caret.M6A related LncRNA pairing models were established based on the single factor and multivariate COX regression analysis.The risk assessment equation was obtained using the LASSO regression algorithm.The risk scores were calculated based on this equation,and the optimal critical point of the median risk value was applied to divide all patients into high-risk and low-risk groups.Kaplan-Meier survival analysis was used to make a survival curve for the differences between high and low risk groups in the overall sample.The gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analyses were conducted using the Cluster Profiler software package.The relationship between N6-methyladenosine related LncRNA pairing model and immune cell infiltration was analyzed by R software.Results Kaplan-Meier survival analysis showed the total survival time of patients in the low-risk group was significantly higher than that of patients in the high-risk group of the training group(P<0.05).Compared with high risk group,the overall survival time of patients(G1～2,G3～4,Ⅰ～Ⅱ,or Ⅲ～Ⅳ,age≤65 years,or patients>65 years old)in low risk group was higher(P<0.05).Differential gene enrichment analysis was obtained for high and low risk groups,which mainly enriched with many differential genes such as muscle contraction,rhabdomytic cell differentiation,myofibril,receptor activation activity,and vascular smooth muscle contraction.The highest driver genes in high risk group and low risk group exhibited mutation frequency and mutation information,and their risk score was positively correlated with the degree of T cell and plasma cell infiltration(r=0.638,P=0.001).Conclusion Bioinformatics-based analysis of the N6-methyladenosine related LncRNA pairing models can be helpful to predict the prognosis of patients with renal cancer.It provides new ideas for the prognosis evaluation and optimal treatment strategy of renal cancer,and contributes to further analyzing the molecular mechanism of the occurrence and development of gastric cancer in the future.