Analysis of the clinical efficacy and safety of anti-PD-1 immune checkpoint inhibitors in locally advanced nasopharyngeal cancer.

OBJECTIVE: To analyze the efficacy and adverse effects of anti-PD-1 immune checkpoint inhibitors aimed at nasopharyngeal carcinoma (NPC). METHODS: During the first stage of the study, using 40 patients with stage III/IVa NPC treated with anti-PD-1 immune checkpoint inhibitors in combination with chemoradiotherapy as a first-line treatment (observation group) and 70 patients with NPC treated with chemoradiotherapy alone (control group). In the second stage of the study, 88 patients with NPC treated with immune checkpoint inhibitors were grouped according to the number of lines of immunotherapy, the number of times, and the types of application. RESULTS: Observation of the short-term effects in the first stage indicated that the objective response rate (ORR) of the observation group and the control group against primary foci of NPC was 75.0% versus 40.0%; the mortality rate of the observation group was much lower than that of the control group. The overall first-line treatment evaluation of the observation vs. control groups were as follows: ORR (67.5% vs. 38.6%); median PFS (17.52 vs. 17.21 months); and median OS (18.68 vs. 18.14 months), respectively (p < 0.05). The second stage of the study had an ORR of 53.4%, and the efficacy of immunotherapy was related to staging, timing, and frequency. CONCLUSION: Anti-PD-1 immune checkpoint inhibitors combined with chemoradiotherapy as the first-line treatment for nasopharyngeal carcinoma may improve patient outcomes significantly. Timing, frequency, and the type of immunotherapy exerted an effect on the efficacy of immunotherapy. Adverse effects that occurred during treatment were tolerable and controllable.

Effective and mechanistic insights into shale gas wastewater reverse osmosis concentrate treatment using ozonation-biological activated carbon process.

Reverse osmosis (RO) plays a pivotal role in shale gas wastewater resource utilization. However, managing the reverse osmosis concentrate (ROC) characterized by high salinity and increased concentrations of organic matter is challenging. In this study, we aimed to elucidate the enhancement effects and mechanisms of pre-ozonation on organic matter removal efficacy in ROC using a biological activated carbon (BAC) system. Our findings revealed that during the stable operation phase, the ozonation (O3 and O3/granular activated carbon)-BAC system removes 43.6-72.2 % of dissolved organic carbon, achieving a 4-7 fold increase in efficiency compared with that in the BAC system alone. Through dynamic analysis of influent and effluent water quality, biofilm performance, and microbial community structure, succession, and function prediction, we elucidated the following primary enhancement mechanisms: 1) pre-ozonation significantly enhances the biodegradability of ROC by 4.5-6 times and diminishes the organic load on the BAC system; 2) pre-ozonation facilitates the selective enrichment of microbes capable of degrading organic compounds in the BAC system, thereby enhancing the biodegradation capacity and stability of the microbial community; and 3) pre-ozonation accelerates the regeneration rate of the granular activated carbon adsorption sites. Collectively, our findings provide valuable insights into treating ROC through pre-oxidation combined with biotreatment.

Predictive value of PD-L1 and TMB for short-term efficacy prognosis in non-small cell lung cancer and construction of prediction models.

Objective: To investigate the correlation between programmed death ligand 1(PD-L1), tumor mutation burden (TMB) and the short-term efficacy and clinical characteristics of anti-PD-1 immune checkpoint inhibitor combination chemotherapy in NSCLC patients. The efficacy of the prediction model was evaluated. Methods: A total of 220 NSCLC patients receiving first-line treatment with anti-PD-1 immune checkpoint inhibitor combined with chemotherapy were retrospectively collected. The primary endpoint was short-term efficacy ORR. The correlation between short-term efficacy, PD-L1, TMB, and clinical characteristics using χ2 test or t-test was evaluated. Screen the independent prognostic factors using univariate and multivariate logistic regression analyses, and construct a nomogram prediction model using the "rms" package in R software. Using receiver operating characteristic (ROC) curve analysis to evaluate the independent Prognostic factors and the prediction model. Using decision curve analysis (DCA) to verify the superiority of the prediction model. Results: The mean values of PD-L1, TMB, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, and albumin were the highest in the ORR group, PD-L1 expression and TMB correlated with epidermal growth factor receptor expression. Multivariate analyses showed that PD-L1, TMB, and neutrophil were independent prognostic factors for ORR. The area under the ROC curve (AUC) values of the ROC constructed based on these three indicators were 0.7104, 0.7139, and 0.7131, respectively. The AUC value under the ROC of the nomogram model was 0.813. The DCA of the model showed that all three indicators used together to build the prediction model of the net return were higher than those of the single indicator prediction model. Conclusion: PD-L1, TMB, and neutrophils are independent prognostic factors for short-term efficacy. The nomogram prediction model constructed using these three indicators can further improve predictive efficacy of ICIs in patients with NSCLC.

A phase I clinical trial of sonodynamic therapy combined with temozolomide in the treatment of recurrent glioblastoma.

PURPOSE: The prognosis of recurrent glioblastoma (rGBM) is poor, and there is currently no effective treatment strategy. Sonodynamic therapy (SDT) is a new method for cancer treatment that uses a combination of low-frequency ultrasound and sonosensitisers to produce antitumor effects, which have shown good therapeutic effects in preclinical studies. Therefore, we initiated an open, prospective pilot study to evaluate the safety, tolerability, and efficacy of SDT for the treatment of rGBM. METHODS: Nine patients with rGBM were enrolled who had received multiple treatments, but the nidus continued to progress without additional standard treatments. After MRI localisation, porphyrin drugs were injected, and intermittent low-frequency ultrasound therapy was performed for five days. RESULTS: None of the nine patients in this clinical trial showed any clinical, neurological, haematological, or skin-targeted adverse effects associated with SDT. After the completion of the trial, one patient maintained stable disease, and eight patients experienced disease progression. Among the eight with progressive disease, the median progression-free survival time was 84 days. Four patients died, and the median overall survival duration after recurrence was 202.5 days. CONCLUSION: The number of patients in this study was small; therefore, a long-term survival benefit was not demonstrated. However, this study suggests that SDT has potential as a treatment for rGBM and warrants further exploration. Trial information: Chinese Clinical Trial Registry ( http://www.chictr.org.cn/ ): ChiCTR2200065992. November 2, 2022, retrospectively registered.

Deep information-guided feature refinement network for colorectal gland segmentation.

PURPOSE: Reliable quantification of colorectal histopathological images is based on the precise segmentation of glands but precise segmentation of glands is challenging as glandular morphology varies widely across histological grades, such as malignant glands and non-gland tissues are too similar to be identified, and tightly connected glands are even highly possibly to be incorrectly segmented as one gland. METHODS: A deep information-guided feature refinement network is proposed to improve gland segmentation. Specifically, the backbone deepens the network structure to obtain effective features while maximizing the retained information, and a Multi-Scale Fusion module is proposed to increase the receptive field. In addition, to segment dense glands individually, a Multi-Scale Edge-Refined module is designed to strengthen the boundaries of glands. RESULTS: The comparative experiments on the eight recently proposed deep learning methods demonstrated that our proposed network has better overall performance and is more competitive on Test B. The F1 score of Test A and Test B is 0.917 and 0.876, respectively; the object-level Dice is 0.921 and 0.884; and the object-level Hausdorff is 43.428 and 87.132, respectively. CONCLUSION: The proposed colorectal gland segmentation network can effectively extract features with high representational ability and enhance edge features while retaining details to the maximum, dramatically improving the segmentation performance on malignant glands, and better segmentation results of multi-scale and closed glands can also be obtained.