Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.

BACKGROUND: We aimed to construct and validate a deep learning (DL) radiomics nomogram using baseline and restage enhanced computed tomography (CT) images and clinical characteristics to predict the response of metastatic lymph nodes to neoadjuvant chemotherapy (NACT) in locally advanced gastric cancer (LAGC). METHODS: We prospectively enrolled 112 patients with LAGC who received NACT from January 2021 to August 2022. After applying the inclusion and exclusion criteria, 98 patients were randomized 7:3 to the training cohort (n = 68) and validation cohort (n = 30). We established and compared three radiomics signatures based on three phases of CT images before and after NACT, namely radiomics-baseline, radiomics-delta, and radiomics-restage. Then, we developed a clinical model, DL model, and a nomogram to predict the response of LAGC after NACT. We evaluated the predictive accuracy and clinical validity of each model using the receiver operating characteristic curve and decision curve analysis, respectively. RESULTS: The radiomics-delta signature was the best predictor among the three radiomics signatures. So, we developed and validated a DL delta radiomics nomogram (DLDRN). In the validation cohort, the DLDRN produced an area under the receiver operating curve of 0.94 (95% confidence interval, 0.82-0.96) and demonstrated adequate differentiation of good response to NACT. Furthermore, the DLDRN significantly outperformed the clinical model and DL model (p < 0.001). The clinical utility of the DLDRN was confirmed through decision curve analysis. CONCLUSIONS: In patients with LAGC, the DLDRN effectively predicted a therapeutic response in metastatic lymph nodes, which could provide valuable information for individualized treatment.

Long term survival outcomes of surgery combined with hyperthermic intraperitoneal chemotherapy for perforated low-grade appendiceal mucinous neoplasms: A multicenter retrospective study.

BACKGROUND: Low-grade appendiceal mucinous neoplasms (LAMN) are very rare, accounting for approximately 0.2%-0.5% of gastrointestinal tumors. We conducted a multicenter retrospective study to explore the impact of different surgical procedures combined with HIPEC on the short-term outcomes and long-term survival of patients. METHODS: We retrospectively analyzed the clinicopathological data of 91 LAMN perforation patients from 9 teaching hospitals over a 10-year period, and divided them into HIPEC group and non-HIPEC group based on whether or not underwent HIPEC. RESULTS: Of the 91 patients with LAMN, 52 were in the HIPEC group and 39 in the non-HIPEC group. The Kaplan-Meier method predicted that 52 patients in the HIPEC group had 5- and 10-year overall survival rates of 82.7% and 76.9%, respectively, compared with predicted survival rates of 51.3% and 46.2% for the 39 patients in the non-HIPEC group, with a statistically significant difference between the two groups (χ2 = 10.622, p = 0.001; χ2 = 10.995, p = 0.001). Compared to the 5-year and 10-year relapse-free survival rates of 75.0% and 65.4% in the HIPEC group, respectively, the 5-year and 10-year relapse-free survival rates of 48.7% and 46.2% in the non-HIPEC group were significant different between the two outcomes (χ2 = 8.063, p = 0.005; χ2 = 6.775, p = 0.009). The incidence of postoperative electrolyte disturbances and hypoalbuminemia was significantly higher in the HIPEC group than in the non-HIPEC group (p = 0.023; p = 0.044). CONCLUSIONS: This study shows that surgery combined with HIPEC can significantly improve 5-year and 10-year overall survival rates and relapse-free survival rates of LAMN perforation patients, without affecting their short-term clinical outcomes.

Comparison of short- and long-term outcomes between laparoscopic and open gastrectomy for locally advanced gastric cancer following neoadjuvant chemotherapy: a propensity score matching analysis.

BACKGROUND: This study was performed to evaluate the safety and efficacy of laparoscopic gastrectomy (LG) in patients with locally advanced gastric cancer (LAGC) who received neoadjuvant chemotherapy (NACT). METHODS: We retrospectively analyzed patients who underwent gastrectomy for LAGC (cT2-4aN+M0) after NACT from January 2015 to December 2019. The patients were divided into a LG group and an open gastrectomy (OG) group. The short- and long-term outcomes in both groups were examined following propensity score matching. RESULTS: We retrospectively reviewed 288 patients with LAGC who underwent gastrectomy following NACT. Of these 288 patients, 218 were enrolled; after 1:1 propensity score matching, each group comprised 81 patients. The LG group had significantly lower estimated blood loss than the OG group [80 (50-110) vs. 280 (210-320) mL, P < 0.001) but a longer operation time [205 (186.5-222.5) vs. 182 (170-190) min, P < 0.001], a lower postoperative complication rate (24.7% vs. 42.0%, P = 0.002), and a shorter postoperative hospitalization period [8 (7-10) vs. 10 (8-11.5) days, P = 0.001]. Subgroup analysis revealed that patients who underwent laparoscopic distal gastrectomy had a lower rate of postoperative complications than patients in the OG group (18.8% vs. 38.6%, P = 0.034); however, such a pattern was not seen in patients who underwent total gastrectomy (32.3% vs. 45.9%, P = 0.251). The 3-year matched cohort analysis showed no significant difference in overall survival or recurrence-free survival (log-rank P = 0.816 and P = 0.726, respectively) (71.3% and 65.0% in OG vs. 69.1% and 61.7% in LG, respectively). CONCLUSION: In the short term, LG following NACT is safer and more effective than OG. However, the long-term results are comparable.

A Rapid, Fluorescence Switch-On Biosensor for Early Diagnosis of Sorghum Mosaic Virus.

For the first time, a nanobiosensor was established for Sorghum mosaic virus (SrMV) detection. The biosensor consists of cadmium telluride quantum dots (CdTe QDs) conjugated to the specific antibody (Ab) against SrMV coat protein (CP) and carbon quantum dots (C QDs) labeled with SrMV coat protein. The formation of the fluorophore-quencher immunocomplex CdTe QDs-Ab+C QDs-CP led to a distinct decrease in the fluorescence intensity of CdTe QDs. Conversely, the emission intensity of CdTe QDs recovered upon the introduction of unlabeled CP. The developed biosensor showed a limit of detection of 44 nM in a linear range of 0.10-0.54 µM and exhibited the strongest fluorescence intensity (about 47,000 a.u.) at 552 nm. This strategy was applied to detect purified CP in plant sap successfully with a recovery rate between 93-103%. Moreover, the feasibility of the proposed method was further verified by the detection of field samples, and the results were consistent with an enzyme-linked immunosorbent assay (ELISA). Contrarily to ELISA, the proposed biosensor did not require excessive washing and incubation steps, thus the detection could be rapidly accomplished in a few minutes. The high sensitivity and short assay time of this designed biosensor demonstrated its potential application in situ and rapid detection. In addition, the fluorescence quenching of CdTe QDs was attributed to dynamic quenching according to the Stern-Volmer equation.