ObjectiveTo investigate the effect and mechanism of Yishen Tongluo prescription in protecting mice from oxidative stress injury in diabetic kidney disease （DKD） via the nuclear factor erythroid 2-related factor 2 （Nrf2）/heme oxygenase-1 （HO-1）/NAD（P）H quinone oxidoreductase 1 （NQO1） signaling pathway. MethodsSpecific pathogen-free （SPF） male C57BL/6 mice were assigned into a control group （n=10） and a modeling group （n=50）. The DKD model was established by intraperitoneal injection of streptozotocin. The mice in the modeling group were randomized into a model group， a semaglutide （40 μg·kg^-1） group， and high-， medium-， and low-dose （18.2， 9.1， 4.55 g·kg^-1， respectively） Yishen Tongluo prescription groups， with 10 mice in each group. The treatment lasted for 12 weeks. Blood glucose and 24-h urine protein levels were measured， and the kidney index （KI） was calculated. Serum levels of creatinine （SCr）， blood urea nitrogen （BUN）， alanine aminotransferase （ALT）， and aspartate aminotransferase （AST） were assessed. The pathological changes in the renal tissue were evaluated by hematoxylin-eosin， periodic acid-Schiff， periodic acid-silver methenamine， and Masson’s trichrome staining. Enzyme-linked immunosorbent assay kits were used to measure the levels of β2-microglobulin （β2-MG）， neutrophil gelatinase-associated lipocalin （NGAL）， kidney injury molecule-1 （KIM-1）， liver fatty acid-binding protein （L-FABP）， nitric oxide synthase （NOS）， glutathione （GSH）， total antioxidant capacity （T-AOC）， and 8-hydroxy-2'-deoxyguanosine （8-OHdG）. Immunohistochemical staining was performed to examine the expression of Kelch-like ECH-associated protein 1 （Keap1） and malondialdehyde （MDA）. Real-time fluorescence quantitative polymerase chain reaction (Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of factors in the Nrf2/HO-1/NQO1 signaling pathway. ResultsCompared with the control group， the DKD model group showed rises in blood glucose， 24-h urine protein， KI， SCr， BUN， and ALT levels， along with glomerular hypertrophy， renal tubular dilation， thickened basement membrane， mesangial expansion， and collagen deposition. Additionally， the model group showed elevated levels of β2-MG， NGAL， KIM-1， L-FABP， NOS， and 8-OHdG， lowered levels of GSH and T-AOC， up-regulated expression of MDA and Keap1， and down-regulated expression of Nrf2， HO-1， NQO1， and glutamate-cysteine ligase catalytic subunit （GCLC） （P<0.05）. Compared with the model group， the semaglutide group and the medium- and high-dose Yishen Tongluo prescription groups showed reductions in blood glucose， 24-h urine protein， KI， SCr， BUN， and ALT levels， along with alleviated pathological injuries in the renal tissue. In addition， the three groups showed lowered levels of β2-MG， NGAL， KIM-1， L-FABP， NOS， and 8-OHdG， elevated levels of GSH and T-AOC， down-regulated expression of MDA and Keap1， and up-regulated expression of Nrf2， HO-1， NQO1， and GCLC （P<0.05）. ConclusionYishen Tongluo prescription exerts renoprotective effects in the mouse model of DKD by modulating the Nrf2/HO-1/NQO1 signaling pathway， mitigating oxidative stress， and reducing renal tubular injuries.

Objective: To investigate the mechanism of Yishen Tongluo Formula in ameliorating renal pyroptosis in diabetic nephropathy mice by regulating the toll-like receptor 4 (TLR4)/myeloid differentiation factor 88 (MyD88)/nuclear factor-κB (NF-κB) signaling pathway. Methods: Sixty C57BL/6 male mice were randomly divided into control (10 mice) and intervention groups (50 mice) using random number table method. The diabetes nephropathy model was established by intraperitoneally injecting streptozotocin(50 mg/kg). After modeling, the intervention group was further divided into model, semaglutide (40 μg/kg), and high-, medium-, and low-dose Yishen Tongluo Formula groups (15.6, 7.8, and 3.9 g/kg, respectively) using random number table method. The high-, medium-, and low-dose Yishen Tongluo Formula groups were administered corresponding doses of medication by gavage, the semaglutide group received a subcutaneous injection of semaglutide injection, and the control group and model groups were administered distilled water by gavage for 12 consecutive weeks. Random blood glucose levels of mice in each group were monitored, and the 24-h urinary protein content was measured using biochemical method every 4 weeks; after treatment, the serum creatinine and urea nitrogen levels were measured using biochemical method. The weight of the kidneys was measured, and the renal index was calculated. Hematoxylin and eosin, periodic acid-Schiff, periodic Schiff-methenamine, and Masson staining were used to observe the pathological changes in renal tissue. An enzyme-linked immunosorbent assay was used to detect urinary β2-microglobulin (β2-MG), neutrophil gelatinase-associated lipocalin (NGAL), and kidney injury molecule-1 (KIM-1) levels. Western blotting and real-time fluorescence PCR were used to detect the relative protein and mRNA expression levels of nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3), Caspase-1, gasdermin D (GSDMD), interleukin-1β (IL-1β), and interleukin-18 (IL-18) in renal tissue. Immunohistochemistry was used to detect the proportion of protein staining area of the TLR4, MyD88, and NF-κB in renal tissue. Results: Compared with the control group, the random blood glucose, 24-h urinary protein, serum creatinine, urea nitrogen, and renal index of the model group increased, and the urine β2-MG, NGAL, and KIM-1 levels increased. The relative protein and mRNA expression levels of NLRP3, Caspase-1, GSDMD, IL-1β, and IL-18 in renal tissue increased, and the proportion of TLR4, MyD88, and NF-κB protein positive staining areas increased (P<0.05). Pathological changes such as glomerular hypertrophy were observed in the renal tissue of the model group. Compared with the model group, the Yishen Tongluo Formula high-dose group showed a decrease in random blood glucose after 12 weeks of treatment (P<0.05). The Yishen Tongluo Formula high- and medium-dose groups showed a decrease in 24-h urinary protein, creatinine, urea nitrogen, and renal index, as well as decreased β2-MG, NGAL, and KIM-1 levels. NLRP3, Caspase-1, GSDMD, IL-1 β, and IL-18 relative protein and mRNA expression levels were also reduced, and the proportion of TLR4, MyD88, and NF-κB protein positive staining areas was reduced (P<0.05). Pathological damage to renal tissue was ameliorated. Conclusion Yishen Tongluo Formula may exert protective renal effects by inhibiting renal pyroptosis and alleviating tubular interstitial injury in diabetic nephropathy mice by regulating the TLR4/MyD88/NF-κB signaling pathway.

Objective:To develop PixelSIFT-UNet, a novel semantic segmentation model that integrates deep learning with scale-invariant feature transform (SIFT) algorithm to improve the segmentation accuracy of oral mucosal lesions.Methods:This investigation utilized 838 standard clinical white light images of oral mucosal diseases acquired from January 2020 to December 2022 at the Stomatology Hospital Zhejiang University School of Medicine. Randomization was achieved through Python′s random.seed function implementation. The random sample function was subsequently applied for sampling distribution. The dataset was stratified into three subsets with a 6∶2∶2 ratio: training ( n=506), validation ( n=166), and testing ( n=166). Lesion boundaries were annotated using Labelme software, and a PixelSIFT-UNet-based deep learning model was developed with VGG-16 and ResNet-50 backbone networks. Model parameters were optimized using the validation set, and performance metrics [including Dice coefficient, mean intersection over union (mIoU), mean pixel accuracy (mPA), and Precision] were assessed on the test set. The model′s performance was benchmarked against conventional semantic segmentation frameworks (U-Net and PSPNet). Results:The developed PixelSIFT-UNet model could achieve precise segmentation of three common oral mucosal lesions: oral lichen planus, oral leukoplakia, and oral submucous fibrosis. Utilizing VGG-16 as the backbone network, the model achieved Dice coefficient, mIoU, mPA, and Precision values of 0.642, 0.699, 0.836, and 0.792, respectively. Implementation with ResNet-50 backbone network yielded metrics of 0.668, 0.733, 0.872 and 0.817, demonstrating significant improvements across all performance indicators compared to conventional U-Net model (relevant metrics: 0.662, 0.717, 0.861 and 0.809) and PSPNet model (relevant metrics: 0.671, 0.721, 0.858 and 0.813).Conclusions:The proposed PixelSIFT-UNet architecture demonstrates superior performance in oral mucosal lesion segmentation tasks, surpassing conventional semantic segmentation models and providing robust quantitative improvements in segmentation accuracy.

Objective:To construct curved microgrooves with gradient surface roughness on polycaprolactone (PCL) members by regulating alkali etching time and to investigate the synergistic effect of surface roughness and curved microgrooves on the in vitro osteogenic differentiation of mouse pre-osteoblasts (MC3T3-E1), aiming to determine the optimal PCL surface modification strategy. Methods:Soft lithography and melt-casting techniques were used to fabricate PCL membranes with regularly arranged curved microgrooves (CMP). Alkali etching was performed for 24, 48, and 72 h. Groups: smooth PCL (control), CMP (curved microgrooves only), CMP-24 h, CMP-48 h, CMP-72 h (CMP etched for 24, 48, 72 h, respectively). Surface physicochemical properties were characterized: surface morphology was observed by scanning electron microscopy (SEM), surface roughness was measured by atomic force microscopy (AFM), and surface hydrophilicity was evaluated by contact angle measurement. MC3T3-E1 cells were cultured in vitro. Cell adhesion, proliferation, and osteogenic differentiation were assessed using cell counting (CCK-8), immunofluorescence staining, alkaline phosphatase (ALP) and Alizarin red staining with quantification. The mRNA expression levels of osteogenesis-related genes [ALP, collagen type Ⅰ (COL-1), Runt-related transcription factor 2 (RUNX-2), osteocalcin (OCN), osteopontin (OPN)] were detected by real-time fluorescence quantitative PCR (RT-qPCR). Results:Curved microgrooves were successfully fabricated on PCL membranes. Alkali treatment improved surface hydrophilicity and increased roughness. The CMP-72 h group exhibited the best hydrophilicity (contact angle: 33.2°±5.5°), with significant differences compared to all other groups (all P<0.05). The CMP-72 h group showed the highest roughness [(59.966±4.729) nm], which was significantly different from all other groups (all P<0.05). CCK-8 results on day 5 showed that both curved microgrooves and roughness promoted cell proliferation: CMP-24 h (0.292±0.003) and CMP-72 h (0.383±0.004) were significantly higher than those in the smooth group (0.270±0.005) (all P<0.05). Immunofluorescence staining revealed that curved microgrooves induced significant contact guidance of cells; this effect weakened with increasing etching time. ALP and Alizarin red staining indicated the deepest osteogenic staining in the CMP-48 h group. Both ALP activity (0.013 021±0.000 032) and Alizarin red quantification (0.290±0.003) were highest in the CMP-48 h group, significantly different from all other groups (all P<0.05). RUNX-2 expression in CMP-24 h and CMP-48 h groups (1.845±0.087 and 1.837±0.027, respectively) was significantly higher than in other groups (all P<0.05), with no significant difference between these two groups ( P>0.05). CMP-48 h group exhibited the highest mRNA expression of all osteogenic genes tested, specifically ALP (2.194±0.028), COL-1 (1.983±0.024), OCN (7.644±0.156), and OPN (2.648±0.031), all significantly greater than other groups (all P<0.05). Conclusions:Both curved microgrooves and surface roughness modification enhance the in vitro osteogenic differentiation of cells on PCL membranes. Among the tested strategies, alkali etching of curved microgrooves for 48 hours (CMP-48h) provided the optimal enhancement of osteogenic capability for MC3T3-E1 cells and represented a promising surface modification strategy for future PCL membranes.

Objective:To explore the factors influencing the success rate of culturing patient-derived gastric and colorectal cancer organoids.Methods:From Feb 2022 to Oct 2023, 398 tumor tissue specimens from patients who underwent gastric cancer and colorectal cancer resection at the Department of Gastrointestinal Surgery, the Affiliated Hospital of Qingdao University, were used for organoid culture. The clinicopathological factors affecting the success rate of organoid culture were analyzed.Results:The overall success rate of organoid culture in this group was 75.1% (299/398), with the success rate of gastric cancer organoid culture being 79.8%(154/193) and that of colorectal cancer being 70.7% (145/205). Different clinicopathological T stage ( χ2=4.765, P<0.05),histological type ( χ2=11.248, P<0.05), and tumor regression grade (TRG) grade after neoadjuvant chemotherapy ( χ2=7.797, P<0.05) were related to the success rate of organoid culture . Multivariate analysis showed that the TRG grade was an independent influencing factor( P=0.040). For colorectal cancer, different pathological T stage ( χ2=5.108, P<0.05), histological type ( χ2=11.270, P<0.05), and TRG grade after neoadjuvant chemotherapy ( χ2=6.797, P<0.05) were related to the success rate of organoidculture . Different from gastric cancer, the results of multivariate analysis of colorectal cancer showed that the histological type was an independent influencing factor ( P=0.018). Conclusions:The pathologic T stage, histological type of tumors, and TRG of cancer patients all have a significant impact on the success rate of establishing tumor organoids. Among them, the TRG grade is an independent influencing factor for the culture of gastric cancer organoids, and the histological type is an independent influencing factor for colorectal cancer organoids.

Objective:To compare the effects of robotic and laparoscopic radical gastrectomy on short-term clinical outcomes and long-term prognosis in obese patients with gastric cancer.Methods:Clinical data from 231 obese gastric cancer patients undergoing laparoscopic or robotic radical gastrectomy at the Department of Gastrointestinal Surgery, Affiliated Hospital of Qingdao University between Jan 2015 and Dec 2022 was analyzed. After propensity score matching, the patients were divided into robotic surgery group ( n=79) and laparoscopic surgery group ( n=79). The short-term clinical outcomes and long-term prognosis were compared. Results:Compared with the laparoscopic group, the robotic group had a significantly greater number of dissected lymph nodes [(32±13) vs. (26±11), t=2.797, P=0.006], shorter operation time [(245±65) min vs. (272±62) min, t=-2.669, P=0.008], less intraoperative blood loss[(84±69) vs. (119±56) ml, t=-3.502, P=0.001], shorter postoperative hospital stay [(8.2±3.5) vs. (9.6±4.2) d, t=-2.363, P=0.019], and higher hospitalization cost [(102,139±18,303) vs. (77,857±18,325) yuan, t=8.333, P<0.001]. The 5-year overall survival and disease-free survival rates were comparable between the robotic and laparoscopic groups (77.2% vs. 74.7%, P=0.684; and 73.4% vs. 68.4%, P=0.491, respectively). Conclusions:Robotic radical gastrectomy is a safe and feasible alternative for obese gastric cancer patients in experienced hands. It offers advantages in short-term clinical outcomes, however, it fails to provide a significant long-term survival benefit.

Objective:To compare the short- and long-term outcomes of robotic versus laparoscopic gastrectomy in patients with locally advanced gastric cancer after neoadjuvant chemotherapy.Methods:Data from 321 patients with locally advanced gastric cancer undergoing neoadjuvant chemotherapy followed by robotic ( n=109) and laparoscopic ( n=212) radical gastrectomy at our center between May 2017 and Sep 2022 was collected. After 1∶1 propensity score matching, 106 patients from each group were included in the final analysis to compare short-term clinical outcomes and long-term prognostic indicators. Results:The robotic group had a significantly lower overall complication rate (13.2% vs. 28.3%, χ2=6.453, P=0.007) and surgery-related complication rate (8.5% vs. 17.9%, χ2=3.333, P=0.043) than the laparoscopic group. The robotic group also retrieved more total lymph nodes (35.3±4.9 vs. 31.4±6.3, t=4.863, P<0.001) and supra-pancreatic lymph nodes (13.1±3.4 vs. 10.1±2.1, t=5.258, P<0.001). Additionally, the robotic group had a shorter operative time [(218±47) min vs. (267±71) min, t=-6.001, P<0.001], less intraoperative blood loss [(47±12) ml vs. (71±17) ml, t=-5.424, P<0.001], and faster postoperative recovery. The 3-year recurrence-free survival rate was significantly higher in the robotic group compared to the laparoscopic group (75.5% vs. 62.3%, P=0.017). Conclusion:Compared with laparoscopic gastrectomy, robotic gastrectomy allows for a more lymph nodes harvest, significantly reduces intraoperative blood loss and complication rates and significantly improves recurrence-free survival.

Objective:To construct curved microgrooves with gradient surface roughness on polycaprolactone (PCL) members by regulating alkali etching time and to investigate the synergistic effect of surface roughness and curved microgrooves on the in vitro osteogenic differentiation of mouse pre-osteoblasts (MC3T3-E1), aiming to determine the optimal PCL surface modification strategy. Methods:Soft lithography and melt-casting techniques were used to fabricate PCL membranes with regularly arranged curved microgrooves (CMP). Alkali etching was performed for 24, 48, and 72 h. Groups: smooth PCL (control), CMP (curved microgrooves only), CMP-24 h, CMP-48 h, CMP-72 h (CMP etched for 24, 48, 72 h, respectively). Surface physicochemical properties were characterized: surface morphology was observed by scanning electron microscopy (SEM), surface roughness was measured by atomic force microscopy (AFM), and surface hydrophilicity was evaluated by contact angle measurement. MC3T3-E1 cells were cultured in vitro. Cell adhesion, proliferation, and osteogenic differentiation were assessed using cell counting (CCK-8), immunofluorescence staining, alkaline phosphatase (ALP) and Alizarin red staining with quantification. The mRNA expression levels of osteogenesis-related genes [ALP, collagen type Ⅰ (COL-1), Runt-related transcription factor 2 (RUNX-2), osteocalcin (OCN), osteopontin (OPN)] were detected by real-time fluorescence quantitative PCR (RT-qPCR). Results:Curved microgrooves were successfully fabricated on PCL membranes. Alkali treatment improved surface hydrophilicity and increased roughness. The CMP-72 h group exhibited the best hydrophilicity (contact angle: 33.2°±5.5°), with significant differences compared to all other groups (all P<0.05). The CMP-72 h group showed the highest roughness [(59.966±4.729) nm], which was significantly different from all other groups (all P<0.05). CCK-8 results on day 5 showed that both curved microgrooves and roughness promoted cell proliferation: CMP-24 h (0.292±0.003) and CMP-72 h (0.383±0.004) were significantly higher than those in the smooth group (0.270±0.005) (all P<0.05). Immunofluorescence staining revealed that curved microgrooves induced significant contact guidance of cells; this effect weakened with increasing etching time. ALP and Alizarin red staining indicated the deepest osteogenic staining in the CMP-48 h group. Both ALP activity (0.013 021±0.000 032) and Alizarin red quantification (0.290±0.003) were highest in the CMP-48 h group, significantly different from all other groups (all P<0.05). RUNX-2 expression in CMP-24 h and CMP-48 h groups (1.845±0.087 and 1.837±0.027, respectively) was significantly higher than in other groups (all P<0.05), with no significant difference between these two groups ( P>0.05). CMP-48 h group exhibited the highest mRNA expression of all osteogenic genes tested, specifically ALP (2.194±0.028), COL-1 (1.983±0.024), OCN (7.644±0.156), and OPN (2.648±0.031), all significantly greater than other groups (all P<0.05). Conclusions:Both curved microgrooves and surface roughness modification enhance the in vitro osteogenic differentiation of cells on PCL membranes. Among the tested strategies, alkali etching of curved microgrooves for 48 hours (CMP-48h) provided the optimal enhancement of osteogenic capability for MC3T3-E1 cells and represented a promising surface modification strategy for future PCL membranes.

Robot-assisted surgery with its advantages such as three-dimensional high-definition vision, dexterous robotic arms, and tremor filtration, is increasingly being applied to complex radical gastrectomy. However, the role of the surgical assistant remains crucial during the procedure. The assistant is responsible for tasks outside the console, including adjusting robotic arms, changing instruments, exposing the surgical field, and addressing unexpected situations. The technical proficiency of the assistant and their collaboration efficiency with the primary surgeon directly impact the smoothness of surgery and patients' outcomes. With the expansion of robot-assisted surgical indications, the establishment of a standardized training system and the optimization of team collaboration models have become urgent challenges to address. This article draws on the author's practical experience as an assistant in robot-assisted gastric cancer surgeries, conducting an in-depth analysis of the responsibilities and operational skills of surgical assistants in robot-assisted procedures. The aim is to develop a relatively comprehensive set of operational guidelines for surgical assistants in robot-assisted radical gastrectomy, providing valuable references for enhancing the overall efficiency of surgical teams and improving surgical outcomes.

Objective:To develop PixelSIFT-UNet, a novel semantic segmentation model that integrates deep learning with scale-invariant feature transform (SIFT) algorithm to improve the segmentation accuracy of oral mucosal lesions.Methods:This investigation utilized 838 standard clinical white light images of oral mucosal diseases acquired from January 2020 to December 2022 at the Stomatology Hospital Zhejiang University School of Medicine. Randomization was achieved through Python′s random.seed function implementation. The random sample function was subsequently applied for sampling distribution. The dataset was stratified into three subsets with a 6∶2∶2 ratio: training ( n=506), validation ( n=166), and testing ( n=166). Lesion boundaries were annotated using Labelme software, and a PixelSIFT-UNet-based deep learning model was developed with VGG-16 and ResNet-50 backbone networks. Model parameters were optimized using the validation set, and performance metrics [including Dice coefficient, mean intersection over union (mIoU), mean pixel accuracy (mPA), and Precision] were assessed on the test set. The model′s performance was benchmarked against conventional semantic segmentation frameworks (U-Net and PSPNet). Results:The developed PixelSIFT-UNet model could achieve precise segmentation of three common oral mucosal lesions: oral lichen planus, oral leukoplakia, and oral submucous fibrosis. Utilizing VGG-16 as the backbone network, the model achieved Dice coefficient, mIoU, mPA, and Precision values of 0.642, 0.699, 0.836, and 0.792, respectively. Implementation with ResNet-50 backbone network yielded metrics of 0.668, 0.733, 0.872 and 0.817, demonstrating significant improvements across all performance indicators compared to conventional U-Net model (relevant metrics: 0.662, 0.717, 0.861 and 0.809) and PSPNet model (relevant metrics: 0.671, 0.721, 0.858 and 0.813).Conclusions:The proposed PixelSIFT-UNet architecture demonstrates superior performance in oral mucosal lesion segmentation tasks, surpassing conventional semantic segmentation models and providing robust quantitative improvements in segmentation accuracy.