PLEK2 promotes migration and invasion in pancreatic ductal adenocarcinoma by MMP1 through IL-17 pathway.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor prognosis primarily due to metastasis. Accumulating evidence suggests that PLEK2 acts as an oncogene in various tumors. This study aimed to investigate the effects of PLEK2 on PDAC. Expression analysis of PLEK2 was conducted using qRT-PCR, Western blot, and immunohistochemistry in PDAC. Wound healing and transwell assays were performed to evaluate the impact of PLEK2 on cell migration and invasion. A xenograft tumor model was employed to assess the in vivo proliferation of PLEK2. Additionally, the downstream pathway of PLEK2 was analyzed through RNA-seq and confirmed by Western blot analysis. The results demonstrated the upregulation of PLEK2 expression in tumor specimens. High PLEK2 expression was significantly associated with poor overall survival and advanced TNM stages. Correlation analyses revealed positive correlations between PLEK2 and TGF-ß, EGFR, and MMP1. Wound healing and transwell assays demonstrated that PLEK2 promoted PDAC cell migration and invasion, potentially through the activation of the epithelial-to-mesenchymal transition process. The in vivo experiment further confirmed that PLEK2 knockdown suppressed tumor growth. RNA-seq analysis revealed PLEK2's regulation of MMP1 and activation of p-ERK and p-STAT3, which were verified by Western blot analysis. Overall, the present study suggests that PLEK2 may play a tumor-promoting role in PDAC. These findings provide valuable insights into the molecular mechanisms of pancreatic cancer and highlight the potential of PLEK2 as a therapeutic target.

Dual and triple gene combinations of KRT5, KRT17, and S100A2 identify basal-like subtype of pancreatic ductal adenocarcinoma and correlate with survival outcome.

There is a significant difference in prognosis and response to chemotherapy between basal and classical subtypes of pancreatic ductal adenocarcinoma (PDAC). Further biomarkers are required to identify subtypes of PDAC. We selected candidate biomarkers via review articles. Correlations between these candidate markers and the PDAC molecular subtype gene sets were analyzed using bioinformatics, confirming the biomarkers for identifying classical and basal subtypes. Subsequently, 298 PDAC patients were included, and their tumor tissues were immunohistochemically stratified using these biomarkers. Survival data underwent analysis, including Cox proportional hazards modeling. Our results indicate that the pairwise and triple combinations of KRT5/KRT17/S100A2 exhibit a higher correlation coefficient with the basal-like subtype gene set, whereas the corresponding combinations of GATA6/HNF4A/TFF1 show a higher correlation with the classical subtype gene set. Whether analyzing unmatched or propensity-matched data, the overall survival time was significantly shorter for the basal subtype compared with the classical subtype (p < .001), with basal subtype patients also facing a higher risk of mortality (HR = 4.017, 95% CI 2.675-6.032, p < .001). In conclusion, the combined expression of KRT5, KRT17, and S100A2, in both pairwise and triple combinations, independently predicts shorter overall survival in PDAC patients and likely identifies the basal subtype. Similarly, the combined expression of GATA6, HNF4A, and TFF1, in the same manner, may indicate the classical subtype. In our study, the combined application of established biomarkers offers valuable insights for the prognostic evaluation of PDAC patients.

Impact of an AI-Based laparoscopic cholecystectomy coaching program on the surgical performance: a randomized controlled trial.

BACKGROUND: Laparoscopic cholecystectomy (LC) is the gold standard for treating symptomatic gallstones but carries inherent risks like bile duct injury (BDI). While critical view of safety (CVS) is advocated to mitigate BDI, its real-world adoption is limited. Additionally, significant variations in surgeon performance impede procedural standardization, highlighting the need for a feasible, innovative, and effective training approach. The aim of this study is to develop an Artificial Intelligence (AI)-assisted coaching program for LC to enhance surgical education and improve surgeon's performance. MATERIALS AND METHODS: We conducted a multi-center, randomized controlled trial from May 2022 to August 2023 to assess the impact of an AI-based coaching program, SmartCoach, on novice performing LC. Surgeons and patients meeting specific inclusion criteria were randomly assigned to either a coaching group with AI-enhanced feedback or a self-learning group. The primary outcome was assessed using the Laparoscopic Cholecystectomy Rating Form (LCRF), with secondary outcomes including surgical safety, efficiency, and adverse events. Statistical analyses were performed using SPSS, with significance set at P-value less than 0.05. RESULTS: Between May 2022 and August 2023, 22 surgeons were initially enrolled from 10 hospitals, with 18 completing the study. No demographic differences were noted between coaching and self-learning groups. In terms of surgical performance (LCRF scores), the coaching group showed significant improvement over time (31 to 40, P=0.008), outperforming the self-learning group by study end (40 vs 38, P=0.032). Significant improvements in CVS achievement were also noted in the coaching group (11% to 78%, P=0.021). Overall, the coaching program was well-received, outpacing traditional educational methods in both understanding and execution of CVS and participants in the intervention group expressed strongly satisfaction with the program. CONCLUSIONS: The AI-assisted surgical coaching program effectively improved surgical performance and safety for novice surgeons in LC procedures. The model holds significant promise for advancing surgical education.

CDK4/6 inhibition sensitizes MEK inhibition by inhibiting cell cycle and proliferation in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is not sensitive to most chemotherapy drugs, leading to poor chemotherapy efficacy. Recently, Trametinib and Palbociclib have promising prospects in the treatment of pancreatic cancer. This article aims to explore the effects of Trametinib on pancreatic cancer and address the underlying mechanism of resistance as well as its reversal strategies. The GDSC (Genomics of Drug Sensitivity in Cancer) and CTD2 (Cancer Target Discovery and Development) were utilized to screen the potential drug candidate in PDAC cell lines. The dose-increase method combined with the high-dose shock method was applied to induce the Trametinib-resistant PANC-1 and MIA PaCa-2 cell lines. The CCK8 proliferation assay, colony formation assay, flow cytometry, and western blot were conducted to verify the inhibitory effect of Trametinib and Palbociclib. RNA-seq was performed in resistant PDAC cell lines to find the differential expression genes related to drug resistance and predict pathways leading to the reversal of Trametinib resistance. The GDSC and CTD2 database screening revealed that Trametinib demonstrates a significant inhibitory effect on PDAC. We found that Trametinib has a lower IC50 than Gemcitabine in PDAC cell lines. Both Trametinib and Gemcitabine can decrease the proliferation capacity of pancreatic cells, induce cell cycle arrest, and increase apoptosis. Simultaneously, the phosphorylation of the AKT and ERK pathways were inhibited by the treatment of Trametinib. In addition, the RNA-seq of Trametinib-induced resistance PDAC cell lines reveals that the cyclin-dependent kinase (CDK)-RB-E2F regulatory axis and G2/M DNA damage checkpoint might lead the drug resistance. Besides, the combination of Trametinib with Palbociclib could inhibit the proliferation and cell cycle of both resistant cells lines and also restore the sensitivity of drug-resistant cells to Trametinib. Last but not least, the interferon-α and interferon-γ expression were upregulated in resistance cell lines, which might lead to the reversal of drug resistance. The study shows Trametinib has a critical inhibitory effect on PDAC. Besides, the combination of Trametinib with Palbociclib can inhibit the proliferation of PDAC-resistant cells.

Real-time fluorescence-guided adhesiolysis with indocyanine green in intra-abdominal surgery (with video).

Intra-abdominal adhesions have consistently posed a challenge for surgeons during procedures. This study aims to investigate the feasibility of utilizing indocyanine green (ICG) in conjunction with near-infrared imaging for the detection of intra-abdominal adhesions. In vitro, we analyzed factors affecting ICG fluorescence. We divided SD rats into groups to study ICG excretion in different digestive tract regions. Additionally, we reviewed surgical videos from previous cholecystectomy cases, categorizing them by ICG injection timing and assessing fluorescence imaging in various digestive tract regions. Finally, we preoperatively injected ICG into two cholecystectomized patients with abdominal adhesions, guiding intraoperative adhesiolysis with near-infrared fluorescence imaging. In vitro, we observed a significant influence of protein and ICG concentrations on ICG fluorescence intensity. Our rat experiments unveiled a strong and highly significant correlation (Kendall's tau-b = 1, P < 0.001) between the timing of ICG injection and the farthest point of intestinal fluorescence. A retrospective case analysis further validated this finding (Kendall's tau-b = 0.967, P < 0.001). Under the guidance of fluorescence navigation, two cholecystectomized patients with intra-abdominal adhesions successfully underwent adhesiolysis, and no postoperative complications occurred. The intraoperative combination of ICG with near-infrared fluorescence imaging effectively enhances the visibility of the liver, bile ducts, and various segments of the gastrointestinal tract while providing real-time navigation. This real-time fluorescence guidance has the potential to aid surgeons in the dissection of intra-abdominal adhesions.

SurgSmart: an artificial intelligent system for quality control in laparoscopic cholecystectomy: an observational study.

BACKGROUND: The rate of bile duct injury in laparoscopic cholecystectomy (LC) continues to be high due to low critical view of safety (CVS) achievement and the absence of an effective quality control system. The development of an intelligent system enables the automatic quality control of LC surgery and, eventually, the mitigation of bile duct injury. This study aims to develop an intelligent surgical quality control system for LC and using the system to evaluate LC videos and investigate factors associated with CVS achievement. MATERIALS AND METHODS: SurgSmart, an intelligent system capable of recognizing surgical phases, disease severity, critical division action, and CVS automatically, was developed using training datasets. SurgSmart was also applied in another multicenter dataset to validate its application and investigate factors associated with CVS achievement. RESULTS: SurgSmart performed well in all models, with the critical division action model achieving the highest overall accuracy (98.49%), followed by the disease severity model (95.45%) and surgical phases model (88.61%). CVSI, CVSII, and CVSIII had an accuracy of 80.64, 97.62, and 78.87%, respectively. CVS was achieved in 4.33% in the system application dataset. In addition, the analysis indicated that surgeons at a higher hospital level had a higher CVS achievement rate. However, there was still considerable variation in CVS achievement among surgeons in the same hospital. CONCLUSIONS: SurgSmart, the surgical quality control system, performed admirably in our study. In addition, the system's initial application demonstrated its broad potential for use in surgical quality control.

"Plane first" approach for laparoscopic radical antegrade modular pancreatosplenectomy.

BACKGROUND: Laparoscopic radical antegrade modular pancreatosplenectomy (L-RAMPS) has not been widely performed due to its technical challenging. We introduce a novel approach, named "Plane first" approach, for L-RAMPS in this study. METHODS: From January 2015 to August 2021, we performed 51 cases of L-RAMPS. Patients were divided into two groups basing on the surgical approach: conventional approach (group 1) and "Plane first" approach (group 2). Data were retrospectively collected in terms of demographic characteristics, intra-operative variables, post-operative variables, and follow-up outcomes. RESULTS: The age, sex, BMI, and tumor size were comparable between two groups. Two patients in the group 1 required converting to open surgery. The patients in the group 2 required fewer operative time (210.5 ± 65.5 min vs. 252.4 ± 24.7 min, p < 0.01). They also suffered from less blood loss (136.0 ± 100.0 ml vs. 158.8 ± 137.0 ml, p = 0.15). The overall complications for patients in two groups were comparable. In terms of oncological outcomes, posterior margin was positive in two patients (10.5%) in the group 1. One patient (3.1%) in the group 2 had positive pancreatic neck margin. The number of lymph nodes harvested and overall survival between the two groups were comparable. CONCLUSION: "Plane first" approach RAMPS for patients with pancreatic adenocarcinoma in the left pancreas is safe and feasible, even in patients with PV/SMV involvement.

Surgesture: a novel instrument based on surgical actions for objective skill assessment.

BACKGROUND: Due to varied surgical skills and the lack of an efficient rating system, we developed Surgesture based on elementary functional surgical gestures performed by surgeons, which could serve as objective metrics to evaluate surgical performance in laparoscopic cholecystectomy (LC). METHODS: We defined 14 LC basic Surgestures. Four surgeons annotated Surgestures among LC videos performed by experts and novices. The counts, durations, average action time, and dissection/exposure ratio (D/E ratio) of LC Surgestures were compared. The phase of mobilizing hepatocystic triangle (MHT) was extracted for skill assessment by three professors using a modified Global Operative Assessment of Laparoscopic Skills (mGOALS). RESULTS: The novice operation time was significantly longer than the expert operation time (58.12 ± 19.23 min vs. 26.66 ± 8.00 min, P < 0.001), particularly during MHT phase. Novices had significantly more Surgestures than experts in both hands (P < 0.05). The left hand and inefficient Surgesture of novices were dramatically more than those of experts (P < 0.05). The experts demonstrated a significantly higher D/E ratio of duration than novices (0.79 ± 0.37 vs. 2.84 ± 1.98, P < 0.001). The counts and time pattern map of LC Surgestures during MHT demonstrated that novices tended to complete LC with more types of Surgestures and spent more time exposing the surgical scene. The performance metrics of LC Surgesture had significant but weak associations with each aspect of mGOALS. CONCLUSION: The newly constructed Surgestures could serve as accessible and quantifiable metrics for demonstrating the operative pattern and distinguishing surgeons with various skills. The association between Surgestures and Global Rating Scale laid the foundation for establishing a bridge to automated objective surgical skill evaluation.

Artificial intelligence-based automated laparoscopic cholecystectomy surgical phase recognition and analysis.

BACKGROUND: Artificial intelligence and computer vision have revolutionized laparoscopic surgical video analysis. However, there is no multi-center study focused on deep learning-based laparoscopic cholecystectomy phases recognizing. This work aims to apply artificial intelligence in recognizing and analyzing phases in laparoscopic cholecystectomy videos from multiple centers. METHODS: This observational cohort-study included 163 laparoscopic cholecystectomy videos collected from four medical centers. Videos were labeled by surgeons and a deep-learning model was developed based on 90 videos. Thereafter, the performance of the model was tested in additional ten videos by comparing it with the annotated ground truth of the surgeon. Deep-learning models were trained to identify laparoscopic cholecystectomy phases. The performance of models was measured using precision, recall, F1 score, and overall accuracy. With a high overall accuracy of the model, additional 63 videos as an analysis set were analyzed by the model to identify different phases. RESULTS: Mean concordance correlation coefficient for annotations of the surgeons across all operative phases was 92.38%. Also, the overall phase recognition accuracy of laparoscopic cholecystectomy by the model was 91.05%. In the analysis set, there was an average surgery time of 2195 ± 896 s, with a huge individual variance of different surgical phases. Notably, laparoscopic cholecystectomy in acute cholecystitis cases had prolonged overall durations, and the surgeon would spend more time in mobilizing the hepatocystic triangle phase. CONCLUSION: A deep-learning model based on multiple centers data can identify phases of laparoscopic cholecystectomy with a high degree of accuracy. With continued refinements, artificial intelligence could be utilized in huge data surgery analysis to achieve clinically relevant future applications.

Visible-light photocatalytic degradation of bisphenol A using cobalt-to-oxygen doped graphitic carbon nitride with nitrogen vacancies via metal-to-ligand charge transfer.

As an environmentally friendly and promising semiconductor, graphitic carbon nitride (g-C3N4) was widely used in photocatalytic treatment of aqueous organic pollutants. In this study, cobalt-to-oxygen doped graphitic carbon nitride with feeble nitrogen vacancies (Co-OCNVN) as metal-to-ligand charge transfer was synthesized via a facile thermal polymerization method with low cost and non-toxic precursors. The oxygen doped graphitic carbon nitride with feeble nitrogen vacancies (OCNVN) ligand was successfully formed and cobalt was presented in OCNVN in an ionic form (in the form of Co2+-Nx). The cobalt atoms were chemically coordinated to the OCNVN matrix rather than forming cobalt oxide on the surface of OCNVN. The embedded cobalt atoms maintained the absorption margin of ligand OCNVN (up to 700 nm) and served as the separation centers to promote the interfacial electron transfer as well. Due to the synergistic effects of the embedded cobalt atoms and oxygen doping, the Co-OCNVN showed an outstanding activity for the visible-light photocatalytic oxidation of endocrine disruptor bisphenol A (BPA).