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.

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.

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.

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.