Identification of collagen subtypes of gastric cancer for distinguishing patient prognosis and therapeutic response.

Background: Gastric cancer is a highly heterogeneous disease, presenting a major obstacle to personalized treatment. Effective markers of the immune checkpoint blockade response are needed for precise patient classification. We, therefore, divided patients with gastric cancer according to collagen gene expression to indicate their prognosis and treatment response. Methods: We collected data for 1250 patients with gastric cancer from four cohorts. For the TCGA-STAD cohort, we used consensus clustering to stratify patients based on expression levels of 44 collagen genes and compared the prognosis and clinical characteristics between collagen subtypes. We then identified distinct transcriptomic and genetic alteration signatures for the subtypes. We analyzed the associations of collagen subtypes with the responses to chemotherapy, immunotherapy, and targeted therapy. We also established a platform-independent collagen-subtype predictor. We verified the findings in three validation cohorts (GSE84433, GSE62254, and GSE15459) and compared the collagen subtyping method with other molecular subtyping methods. Results: We identified two subtypes of gastric adenocarcinoma: a high-expression collagen subtype (CS-H) and a low-expression collagen subtype (CS-L). Collagen subtype was an independent prognostic factor, with better overall survival in the CS-L subgroup. The inflammatory response, angiogenesis, and phosphoinositide 3-kinase (PI3K)/Akt pathways were transcriptionally active in the CS-H subtype, while DNA repair activity was significantly greater in the CS-L subtype. PIK3CA was frequently amplified in the CS-H subtype, while PIK3C2A, PIK3C2G, and PIK3R1 were frequently deleted in the CS-L subtype. CS-H subtype tumors were more sensitive to fluorouracil, while CS-L subtype tumors were more sensitive to immune checkpoint blockade. CS-L subtype was predicted to be more sensitive to HER2-targeted drugs, and CS-H subtype was predicted to be more sensitive to vascular endothelial growth factor and PI3K pathway-targeting drugs. Collagen subtyping also has the potential to be combined with existing molecular subtyping methods for better patient classification. Conclusions: We classified gastric cancers into two subtypes based on collagen gene expression and validated these subtypes in three validation cohorts. The collagen subgroups differed in terms of prognosis, clinical characteristics, transcriptome, and genetic alterations. The subtypes were closely related to patient responses to chemotherapy, immunotherapy, and targeted therapy.

Rapid and Amplification-free Nucleic Acid Detection with DNA Substrate-Mediated Autocatalysis of CRISPR/Cas12a.

To enable rapid and accurate point-of-care DNA detection, we have developed a single-step, amplification-free nucleic acid detection platform, a DNA substrate-mediated autocatalysis of CRISPR/Cas12a (DSAC). DSAC makes use of the trans-cleavage activity of Cas12a and target template-activated DNA substrate for dual signal amplifications. DSAC employs two distinct DNA substrate types: one that enhances signal amplification and the other that negatively modulates fluorescent signals. The positive inducer utilizes nicked- or loop-based DNA substrates to activate CRISPR/Cas12a, initiating trans-cleavage activity in a positive feedback loop, ultimately amplifying the fluorescent signals. The negative modulator, which involves competitor-based DNA substrates, competes with the probes for trans-cleaving, resulting in a signal decline in the presence of target DNA. These DNA substrate-based DSAC systems were adapted to fluorescence-based and paper-based lateral flow strip detection platforms. Our DSAC system accurately detected African swine fever virus (ASFV) in swine's blood samples at femtomolar sensitivity within 20 min. In contrast to the existing amplification-free CRISPR/Dx platforms, DSAC offers a cost-effective and straightforward detection method, requiring only the addition of a rationally designed DNA oligonucleotide. Notably, a common ASFV sequence-encoded DNA substrate can be directly applied to detect human nucleic acids through a dual crRNA targeting system. Consequently, our single-step DSAC system presents an alternative point-of-care diagnostic tool for the sensitive, accurate, and timely diagnosis of viral infections with potential applicability to human disease detection.

Weakly Supervised Classification for Nasopharyngeal Carcinoma with Transformer in Whole Slide Images.

Pathological examination of nasopharyngeal carcinoma (NPC) is an indispensable factor for diagnosis, guiding clinical treatment and judging prognosis. Traditional and fully supervised NPC diagnosis algorithms require manual delineation of regions of interest on the gigapixel of whole slide images (WSIs), which however is laborious and often biased. In this paper, we propose a weakly supervised framework based on Tokens-to-Token Vision Transformer (WS-T2T-ViT) for accurate NPC classification with only a slide-level label. The label of tile images is inherited from their slide-level label. Specifically, WS-T2T-ViT is composed of the multi-resolution pyramid, T2T-ViT and multi-scale attention module. The multi-resolution pyramid is designed for imitating the coarse-to-fine process of manual pathological analysis to learn features from different magnification levels. The T2T module captures the local and global features to overcome the lack of global information. The multi-scale attention module improves classification performance by weighting the contributions of different granularity levels. Extensive experiments are performed on the 802-patient NPC and CAMELYON16 dataset. WS-T2T-ViT achieves an area under the receiver operating characteristic curve (AUC) of 0.989 for NPC classification on the NPC dataset. The experiment results of CAMELYON16 dataset demonstrate the robustness and generalizability of WS-T2T-ViT in WSI-level classification.

Application of a virtual ruler in predicting postoperative rebleeding from esophageal varices in patients with liver cirrhosis.

BACKGROUND: Esophageal variceal diameter (EVD) is one of the most important predictors of variceal bleeding, as well as an important predictor of the effectiveness of endoscopic esophageal varices (EV) treatments. EVD is currently determined using visual inspection by endoscopic operators, meaning that results can vary widely between operators. This approach also means that cases unsuitable for endoscopic variceal ligation (EVL) can be complicated by postoperative hemorrhage. Thus, the purpose of this study was to explore the value of a virtual ruler (VR) in predicting rebleeding after the endoscopic treatment of EV in patients with cirrhosis. METHODS: We enrolled 588 patients with cirrhosis and EV (with and without gastric varices), who were treated with EVL or endoscopic injection sclerotherapy across 3 hospitals. We categorized participants into 2 groups, a nonbleeding group and a rebleeding group, according to whether they bled again after surgery. We compared basic demographic and clinical data, laboratory tests, EVD, and treatment modalities between the 2 groups. Potential risk factors for rebleeding after EV operations were analyzed using univariate and multivariable regression analyses. Correlations between esophageal variceal rebleeding and EVD were also analyzed, as was the consistency between visual EVD estimates and EVD measured using a VR. RESULTS: Child-Pugh class, albumin (ALB) levels, prothrombin time (PT), EVD (visual value), EVD (VR value), red sign, and the number of laps used for EVL showed statistically significant differences between the rebleeding and nonbleeding groups. Univariate regression analysis showed that Child-Pugh classification, ALB levels, PT, EVD (VR value), and red sign were strongly associated with rebleeding after endoscopic treatment of EV, whereas multivariable regression analysis showed that Child-Pugh classification, ALB levels, and EVD (VR value) were predictive factors for rebleeding after endoscopic treatment of EV. Differences between visual EVD estimates and VR EVD measurements were large. (Kappa value: 0.391, P < .001). However, the 2 methods showed high agreement for EVD >1 cm (87/95) CONCLUSION: EVD (VR value) can more accurately predict rebleeding rates. It can also provide a basis for selecting appropriate endoscopic treatment modalities for EV and effectively circumvent postoperative EV rebleeding.

Markers of brain injury in patients with aneurysmal subarachnoid hemorrhage.

AIM: To investigate the correlation of serum changes and markers of brain injury (BI) in cerebrospinal fluid (CSF) with postoperative cognitive dysfunction (POCD) in patients with cerebral aneurysmal subarachnoid haemorrhage (aSAH). METHODS: 120 patients diagnosed with aSAH were included. 3 months after surgery, these patients were divided into a normal cognition group and a cognitive dysfunction (CD) group relying on the Montreal Cognitive Assessment (MoCA) Scale. RESULTS: The correlations were analysed between the serological changes and the levels of BI markers, such as neurofilament-light (NF-L) protein, Ubisquitin C-terminal hydrolase L1(UCH-L1), Glial Fibrillary Acidic Protein (GFAP), and neuron specific enolase (NSE) in patients after surgery. Hunt-Hess grading standard was employed to determine the severity of aSAH in patients. The mean values of NF-L, UCH-L1, GFAP, and NSE were (8.2 ± 4.3) pg/mL, (0.7 ± 0.3) ng/mL, (2.2 ± 0.4) ng/mL, and (48.5 ± 10.9) ng/mL in patients with severe aSAH, which were remarkably higher than those in patients with mild aSAH [(3.5 ± 0.7) pg/mL, (0.5 ± 0.2) ng/mL, (1.3 ± 0.7) ng/mL, (30.7 ± 8.2) ng/mL]. The sensitivity, specificity, and accuracy of the combined prediction of four detections for POCD were 90.80%, 84.20%, and 82.80%, respectively, which were greatly higher than those of four independent predictions (p < 0.05). The combined prediction effect of the four items, with the area under the curve (AUC) of 0.938 and the 95% confidence interval (CI) of 0.851-0.926. CONCLUSIONS: BI markers NF-L, UCH-L1, GFAP, and NSE could be utilized as predictors of POCD in patients with aSAH, deserving a reference value.

Can on-site leachate treatment facilities effectively address the issue of perfluoroalkyl acids (PFAAs) in leachate?

In recent decades, the presence of perfluoroalkyl acids (PFAAs) in municipal solid waste leachate has emerged as a growing concern. Research has focused on PFAA release and occurrence characteristics in landfill and waste-to-energy leachate, highlighting their significant impact when released into wastewater treatment plants. Given the extremely high loading rate faced by current on-site leachate treatment plants (LTPs), the objective of this study is to assess whether the current "anaerobic/aerobic (A/O) + membrane bioreactor (MBR) + nanofiltration (NF) + reverse osmosis (RO)" configuration is effective in PFAAs removal. Concentrations of raw and treated leachate in 10 on-site LTPs with same treatment configuration and varying landfill ages were measured, and a comprehensive mass flow analysis of each treatment process was conducted. The results indicate that A/O treatment has limited capacity for PFAA removal, while NF and RO processes reached 77.44 % and 94.30 % removal rates of ∑PFAAs concentration, respectively. Short-chain PFAAs (> 80 % detected frequency) primarily influenced the distribution and variations of PFAAs in leachate and tend to disperse in the water phase. Correlation analysis revealed the current on-site LTPs exhibit a more efficient removal capacity for long-chain PFAAs.

Comparison between high-flow nasal cannula and conventional oxygen therapy in COVID-19 patients: a systematic review and meta-analysis.

BACKGROUND: High-flow nasal cannula (HFNC) and conventional oxygen therapy (COT) are important respiratory support strategies for acute hypoxemic respiratory failure (AHRF) in coronavirus disease 2019 (COVID-19) patients. However, the results are conflicting for the risk of intubation with HFNC as compared to COT. OBJECTIVES: We systematically synthesized the outcomes of HFNC relative to COT in COVID-19 patients with AHRF and evaluated these outcomes in relevant subpopulations. DESIGN: This study was designed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. DATA SOURCES AND METHODS: We searched PubMed, EMBASE, Web of Science, Scopus, ClinicalTrials.gov, medRxiv, BioRxiv, and the Cochrane Central Register of Controlled Trials for randomized controlled trials and observational studies that compared the efficacy of HFNC with COT in patients with COVID-19-related AHRF. Primary outcomes were intubation rate and mortality rate. Secondary outcomes were the ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2), respiratory rate, hospital length of stay, intensive care unit (ICU) length of stay, and days free from invasive mechanical ventilation. RESULTS: In total, 20 studies with 5732 patients were included. We found a decreased risk of requiring intubation in HFNC compared to COT [odds ratio (OR) = 0.61, 95% confidence interval (CI): 0.46-0.82, p = 0.0009, I2 = 75%]. Similarly, we found HFNC was associated with lower risk of intubation rate compared to COT in the subgroup of patients with baseline PaO2/FiO2 < 200 mmHg (OR = 0.69, 95% CI: 0.55-0.86, p = 0.0007, I2 = 45%), and who were in ICU settings at enrollment (OR = 0.57, 95% CI: 0.38-0.85, p = 0.005, I2 = 80%). HFNC was associated with an improvement of PaO2/FiO2 and respiratory rate compared to COT. The use of HFNC compared to COT did not reduce the mortality rate, days free from invasive mechanical ventilation, hospital length of stay, or ICU length of stay. CONCLUSION: Compared to COT, HFNC may decrease the need for tracheal intubation in patients with COVID-19-related AHRF, particularly among patients with baseline PaO2/FiO2 < 200 mmHg and those in ICU settings. TRIAL REGISTRATION: This systematic review and meta-analysis protocol was prospectively registered with PROSPERO (no. CRD42022339072).

Superhydrophobic Nanoparticles: An Efficiently Selective Adsorbent for Surfactant-Like Contaminants from Complex Wastewater Matrices.

Surfactant-like contaminants (SLCs) with distinctive amphiphilic structures have become a global concern in wastewater due to their toxicity and persistency. Despite extensive efforts, achieving efficient and selective SLCs removal remains challenging because of their wide range of molecular weights and complex functional group compositions. Superhydrophobic nanoparticles can potentially tackle this challenge by targeting the long oleophilic chains of SLCs. However, conventional contact angle measurements hinder hydrophobicity characterization and corresponding selectivity research because of the powder morphology of nanoparticles. Herein, the authors offered information regarding the distribution of water molecular probes in surfaces and proposed a quantitative characterization approach based on low-field nuclear magnetic resonance. Through synthesizing superhydrophobic and hydrophilic polydopamine nanospheres with similar morphologies, the selective adsorption potential of superhydrophobic nanoparticles for SLCs is systematically demonstrated. As revealed by the interaction mechanisms, the superhydrophobic surface of nanospheres increased its affinity and selectivity for SLCs adsorption by enhancing hydrophobic interactions. Superhydrophobic modification achieved ten times the adsorption capacity of sodium dodecyl benzene sulfonate, an exemplified surfactant, compared with pristine nanoparticles. By regulated self-polymerization, the superhydrophobic nanospheres are coated onto the surface of a 3D sponge and enable efficient selective SLCs adsorption from highly polluted leachate matrices with long-term stability and reusability.

Arthroscopic Excision of Posterior Cruciate Ligament Cysts Using a Double Posteromedial Approach.

Cruciate ligament cysts of the knee are a rare condition. Posterior cruciate ligament cysts of the knee are less common than anterior cruciate ligament cysts. In patients with asymptomatic isolated cruciate ligament cysts of the knee, conservative treatment is recommended. Symptomatic cruciate ligament cysts of the knee are mostly manifested as knee hyperflexion pain, straightening pain, knee discomfort after standing for a long time or walking for a long time, etc., which seriously affects the quality of life, surgical treatment can be performed. The surgical treatments can be divided into ultrasound-guided cyst puncture and fluid extraction procedure and arthroscopic cystectomy. Cysts are mostly lobulated with a multi-layer cyst wall, cyst fluid extraction does not remove the cyst wall completely but simply extracts cyst fluid, leading to a high recurrence rate. Arthroscopic surgery can completely remove the cyst wall with little trauma, a low recurrence rate, and fast postoperative recovery, so arthroscopic resection is the most common and preferred method of treatment. Since posterior cruciate ligament cysts mostly occur posterior to the ligament, we remove the cyst wall by adding a double posteromedial approach to the knee joint, and the cyst wall is removed under direct vision, which is simple to operate, the cyst wall is completely cleared, the trauma is small, the postoperative recovery is fast, and there is no recurrence. Here, 8 posterior cruciate ligament cysts were removed with complete postoperative symptom relief, no surgical complications, and no recurrence at 1-year follow-up.

Machine learning: Next promising trend for microplastics study.

Microplastics (MPs), as an emerging pollutant, pose a significant threat to humans and ecosystems. However, traditional MPs characterization methods are limited by sample requirements and characterization time. Machine Learning (ML) has emerged as a vital technology for analyzing MPs pollution due to its accuracy, broad application, and powerful feature extraction. Nevertheless, environmental scientists require threshold knowledge before using ML, restricting the ML application in MPs research. Furthermore, imbalanced development of ML in MPs research is a pressing concern. In order to achieve a wide ML application in MPs research, in this review, we comprehensively discussed the size and sources of MPs datasets in relevant literature to help environmental scientists deepen their understanding of the construction of MPs datasets. Commonly used ML algorithms are analyzed from the perspective of interpretability and the need for computer facilities. Additionally, methods for improving and evaluating ML model performance, such as dataset pre-processing, model optimization, and model assessment metrics, are discussed. According to datasets and characterization techniques, MPs identification using ML was divided into three categories in this work: spectral identification, image identification, and spectral imaging identification. Finally, other applications of ML in MPs studies, including toxicity analysis, pollutants adsorption, and microbial colonization, are comprehensively discussed, which reveals the great application potential of ML. Based on the discussion above, this review suggests an algorithm selection strategy to assist researchers in selecting the most suitable ML algorithm in different situations, improving efficiency and decreasing the costs of trial and error. We believe that this work sheds light on the application of ML in MPs study.

Collagen-related gene expression level predicts the prognosis and immune therapy response.

BACKGROUND: Gastric cancer patients responded differently to the same treatment strategy and had various prognoses for the lack of biomarkers to guide the therapy choice. METHODS: RNA data of a local gastric cancer cohort with 103 patients were processed and used to explore potential treatment guiding factors. Cluster analysis was performed by non-negative matrix factorization. The expression level of collagen-related genes was evaluated by ssGSEA named collagen score (CS). Data from TCGA, ACRG, and an immune therapy cohort were utilized to explore prognosis and efficacy. Prognostic predictive power of CS was assessed using the nomogram. RESULTS: In our study, local RNA data were processed by cluster analysis, and it was found that cluster 2 contained a worse tumor infiltration status. The GSEA result showed that collagen-related pathways were differentially activated in two clusters. In TCGA and ACRG cohorts, the CS can be used as an independent prognostic factor (TCGA OS: p = 0.018, HR = 3.5; ACRG OS: p = 0.014, HR = 4.88). An immunotherapy cohort showed that the patients with higher CS had a significantly worse ORR (p = 0.0025). The high CS group contained several cell death pathways down-regulated and contained the worse tumor microenvironment. The nomogram demonstrated the survival prediction capability of collagen score. CONCLUSION: CS was verified as an independent prognostic factor and potentially reflected the therapeutic effect of immunotherapy. The CS could provide a new way to evaluate the clinical prognosis and response information helping develop the collagen-targeted treatment.

A Magnetic-Multiplier-Enabled Hybrid Generator with Frequency Division Operation and High Energy Utilization Efficiency.

The hybrid electromagnetic-triboelectric generator (HETG) is a prevalent device for mechanical energy harvesting. However, the energy utilization efficiency of the electromagnetic generator (EMG) is inferior to that of the triboelectric nanogenerator (TENG) at low driving frequencies, which limits the overall efficacy of the HETG. To tackle this issue, a layered hybrid generator consisting of a rotating disk TENG, a magnetic multiplier, and a coil panel is proposed. The magnetic multiplier not only forms the EMG part with its high-speed rotor and the coil panel but also facilitates the EMG to operate at a higher frequency than the TENG through frequency division operation. The systematic parameter optimization of the hybrid generator reveals that the energy utilization efficiency of EMG can be elevated to that of rotating disk TENG. Incorporating a power management circuit, the HETG assumes the responsibility for monitoring the water quality and fishing conditions by collecting low-frequency mechanical energy. The magnetic- multiplier-enabled hybrid generator demonstrated in this work offers a universal frequency division approach to improve the overall outputs of any hybrid generator that collects rotational energy, expanding its practical applications in diverse multifunctional self-powered systems.

Selection of Automated Platelet Counting Methods Based on Mean Platelet Volume (MPV).

BACKGROUND: Impedance-based detection and optic detection with fluorescence are common platelet counting methods used by modern hematology analyzers. There are few studies to compare the accuracy of platelet counts using these methods in case of increased MPV. METHODS: Sixty patients with immune-related thrombocytopenia (IRTP) and 60 healthy controls were included. Platelet counts were obtained by BC-6900 analyzer using impedance detection (PLT-I) and optic detection with fluorescence (PLT-O). Flow cytometry was used as the reference (FCM-ref). RESULTS: The platelet counts in patients using PLT-I were significantly lower than those using PLT-O or FCM-ref by an average of 13.3%. The platelet counts by PLT-O compared to FCM-ref were not statistically significant. MPV inversely affected the platelet counts. When MPV was < 13 fL, platelet counts by all three methods were not statistically different. When MPV was ≥ 13 fL, platelet counts by PLT-I were significantly lower (-15.8%) than those by PLT-O or FCM-ref. Furthermore, when MPV was ≥ 15 fL, platelet counts using PLT-I were further decreased (-23.6%) compared to the counts obtained by PLT-O or FCM-ref. CONCLUSIONS: The platelet counts by PLT-O in patients with IRTP is as accurate as by FCM-ref. When MPV is < 13 fL, platelet counts by all three methods are comparable. However, when MPV is ≥ 13 fL, platelet counts by PLT-I can erroneously decrease by as many as 23.6%. Therefore, in case of IRTP, or any cases when MPV ≥ 13 fL, platelet counts obtained by PLT-I method should be carefully checked by other methods, such as PLT-O to ensure a more accurate platelet count.

The Adsorption Behaviors and Mechanisms of Humic Substances by Thermally Oxidized Graphitic Carbon Nitride.

Thermal oxidation is efficient for enhancing the photocatalysis performance of graphitic carbon nitride (g-C3N4), while its effect on adsorption performance has not been fully studied, which is crucial to the application of g-C3N4 as adsorbents and photocatalysts. In this study, thermal oxidation was used to prepare sheet-like g-C3N4 (TCN), and its application for adsorption of humic acids (HA) and fulvic acids (FA) was evaluated. The results showed that thermal oxidation clearly affected the properties of TCN. After thermal oxidation, the adsorption performance of TCN was enhanced significantly, and the adsorption amount of HA increased from 63.23 (the bulk g-C3N4) to 145.35 mg/g [TCN prepared at 600 °C (TCN-600)]. Based on fitting results using the Sips model, the maximum adsorption amounts of TCN-600 for HA and FA were 327.88 and 213.58 mg/g, respectively. The adsorption for HA and FA was markedly affected by pH, alkaline, and alkaline earth metals due to electrostatic interactions. The major adsorption mechanisms included electrostatic interactions, π-π interactions, hydrogen bonding, along with a special pH-dependent conformation (for HA). These findings implied that TCN prepared from environmental-friendly thermal oxidation showed promising prospects for humic substances (HSs) adsorption in natural water and wastewater.

Using less annotation workload to establish a pathological auxiliary diagnosis system for gastric cancer.

Pathological diagnosis of gastric cancer requires pathologists to have extensive clinical experience. To help pathologists improve diagnostic accuracy and efficiency, we collected 1,514 cases of stomach H&E-stained specimens with complete diagnostic information to establish a pathological auxiliary diagnosis system based on deep learning. At the slide level, our system achieves a specificity of 0.8878 while maintaining a high sensitivity close to 1.0 on 269 biopsy specimens (147 malignancies) and 163 surgical specimens (80 malignancies). The classified accuracy of our system is 0.9034 at the slide level for 352 biopsy specimens (201 malignancies) from 50 medical centers. With the help of our system, the pathologists' average false-negative rate and average false-positive rate on 100 biopsy specimens (50 malignancies) are reduced to 1/5 and 1/2 of the original rates, respectively. At the same time, the average uncertainty rate and the average diagnosis time are reduced by approximately 22% and 20%, respectively.

Design, synthesis and biological evaluation of pyrrolopyrimidine derivatives as novel and selective positive modulator of the small conductance Ca2+-activated K+ channels.

The type 2 small conductance Ca2+-activated K+ channels (SK2) have been considered as one of the most promising therapeutic targets for spinocerebellar ataxias type 2 (SCA2) by playing a critical role in the control of normal purkinje cells (PCs) pacemaking. Herein, a novel series of pyrrolopyrimidine derivatives were designed and synthesized from the lead compound NS13001 as subtype-selective modulators of SK channels. Among them, the halogen-substituted compound 12b (EC50 = 0.34 ± 0.044 µM) was identified with a ∼5.4-fold higher potency on potentiating SK2-a channels at submicromolar concentrations as compared to NS13001 (EC50 = 1.83 ± 0.50 µM). Furthermore, compound 12b exhibited selectivity on SK2-a/SK3 subtype by displaying 93.33 ± 3.26% efficacies on SK2-a channels, and 84.54% ± 7.49% on SK3 channels. In addition, compound 12b demonstrated the potential to cross the blood-brain barrier (BBB) with suitable pharmacokinetic properties and low cytotoxicity. Molecular docking study also unveiled the binding interactions of compound 12b with SK2-CaM protein complex. Overall, the novel pyrrolopyrimidines provide an insightful guidance for future structural optimization of SK channel agonists.

Targeting WDxR motif reprograms immune microenvironment and inhibits hepatocellular carcinoma progression.

The WD-repeat (WDR) family affects carcinogenesis, but its role in the immune microenvironment is poorly characterized. Although functional loss or gain of WDR6 does not markedly change in vitro proliferative and invasive capacity of HCC cells, its deficiency in hepa1-6 cells drastically inhibits the growth and lung metastasis of orthotopically implanted tumors in immune-competent C57BL/6J mice. Mechanistically, WDR6 targets tumor suppressor UVRAG to the CUL4A-DDB1-ROC1 E3 ubiquitin ligase complex through a unique WDxR motif and promotes its degradation. This upregulates chromatin accessibility at the TNFα locus by blocking autophagic degradation of p65, elevates intratumoral myeloid-derived suppressor cell (MDSC) number, and reduces CD8+ T cell infiltration, thereby promoting HCC progression. These immunosuppressive effects are reversed by TNFα blockade. TNFα recruits NF-κB to activate the transcription of WDR6, establishing a WDR6-TNFα loop. Clinically, the WDR6/UVRAG/NF-κB pathway is hyperactivated in HCC, predicting a poor prognosis. Importantly, a WDxR-like peptide disrupts the WDR6/UVRAG complex and enhances the efficiency of anti-PD-L1 against HCC with WDR6 dysregulation.

SWI/SNF Complex Genomic Alterations as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors in Multiple Cancers.

Whether there is an association between SWI/SNF genomic alterations in tumors and response to immune checkpoint inhibitors (ICI) remains unclear because prior studies have focused on either an individual gene or a predefined set of genes. Herein, using mutational and clinical data from 832 ICI-treated patients who underwent whole-exome sequencing, including sequencing of all 31 genes of the SWI/SNF complex, we found that SWI/SNF complex alterations were associated with significantly improved overall survival (OS) in melanoma, clear-cell renal cell carcinoma, and gastrointestinal cancer, as well as improved progression-free survival (PFS) in non-small cell lung cancer. Including tumor mutational burden as a variable, the multivariate Cox regression analysis showed SWI/SNF genomic alterations had prognostic value in melanoma [HR, 0.63 (95% confidence interval, CI, 0.47-0.85), P = 0.003], clear-cell renal cell carcinoma [HR, 0.62 (95% CI, 0.46-0.85), P = 0.003], and gastrointestinal cancer [HR, 0.42 (95% CI, 0.18-1.01), P = 0.053]. Furthermore, we used the random forest method for variable screening, identifying 14 genes as a SWI/SNF signature for potential clinical application. Significant correlations were observed between SWI/SNF signature alterations and improved OS and PFS in all cohorts. This suggests that SWI/SNF gene alterations are associated with better clinical outcomes in ICI-treated patients and may serve as a predictive marker for ICI therapy in multiple cancers.

Identification of key surfactant in municipal solid waste leachate foaming and its influence mechanism.

Serious foaming problems and the excessive consumption of defoamer have undoubtedly become one of the most critical problems that hinder municipal solid waste (MSW) leachate treatment efficiency and industry development. Since there is limited research penetrating the foaming mechanism and identification of the key surfactants, current defoaming and surfactant removal techniques lack pertinence and orientation. In this study, a foaming characterization device was developed and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC/MS/MS) was optimized to accurately identify the key surfactants affecting leachate foaming and offer a glimpse into their interaction mechanisms. This study collected leachate samples from 9 typical landfills and waste-to-energy facilities of various waste compositions, climatic conditions, ages, and geographical locations. The foaming problem of leachate was mainly centered on raw leachate and nanofiltration membrane concentrate (NFC). Fresh leachate performed with relatively low foaming capacity and foam stability, associated with low surfactant concentration. The pH value of the system was positively correlated with the concentration of anionic surfactants, indicating significant impacts on surfactant release in MSW. Since the distribution characteristics of linear alkylbenzene sulfonate (LAS) in leachate were consistent with the variety of foaming performances, LAS proved to be an indispensable surfactant in the leachate involved in this study, and its content proportion escalated to 92.87% in aged leachate.

Predicting colorectal cancer microsatellite instability with a self-attention-enabled convolutional neural network.

This study develops a method combining a convolutional neural network model, INSIGHT, with a self-attention model, WiseMSI, to predict microsatellite instability (MSI) based on the tiles in colorectal cancer patients from a multicenter Chinese cohort. After INSIGHT differentiates tumor tiles from normal tissue tiles in a whole slide image, features of tumor tiles are extracted with a ResNet model pre-trained on ImageNet. Attention-based pooling is adopted to aggregate tile-level features into slide-level representation. INSIGHT has an area under the curve (AUC) of 0.985 for tumor patch classification. The Spearman correlation coefficient of tumor cell fraction given by expert pathologist and INSIGHT is 0.7909. WiseMSI achieves a specificity of 94.7% (95% confidence interval [CI] 93.7%-95.7%), a sensitivity of 84.7% (95% CI 82.6%-86.9%), and an AUC of 0.954 (95% CI 0.948-0.960). Comparative analysis shows that this method has better performance than the other five classic deep learning methods.