Insights into anthropogenic impact on atmospheric inorganic aerosols in the largest city of the Tibetan Plateau through multidimensional isotope analysis

Particulate inorganic nitrogen aerosols (PIN) significantly influence air pollution and pose health risks worldwide. Despite extensive observations on ammonium (pNH4+) and nitrate (pNO3-) aerosols in various regions, their key sources and mechanisms in the Tibetan Plateau remain poorly understood. To bridge this gap, this study conducted a sampling campaign in Lhasa, the Tibetan Plateau's largest city, with a focus on analyzing the multiple isotopic signatures (δ15N, ∆17O). These isotopes were integrated into a Bayesian mixing model to quantify the source contributions and oxidation pathways for pNH4+ and pNO3-. Our results showed that traffic was the largest contributor to pNH4+ (31.8 %), followed by livestock (25.4 %), waste (21.8 %), and fertilizer (21.0 %), underscoring the impact of vehicular emissions on urban NH3 levels in Lhasa. For pNO3-, coal combustion emerged as the largest contributor (27.3 %), succeeded by biomass burning (26.3 %), traffic emission (25.3 %), and soil emission (21.1 %). In addition, the ∆17O-based model indicated a dominant role of NO2 + OH (52.9 %) in pNO3- production in Lhasa, which was similar to previous observations. However, it should be noted that the NO3 + volatile organic component (VOC) contributed up to 18.5 % to pNO3- production, which was four times higher than the Tibetan Plateau's background regions. Taken together, the multidimensional isotope analysis performed in this study elucidates the pronounced influence of anthropogenic activities on PIN in the atmospheric environment of Lhasa.

Photochemical fate of β-blocker pindolol in riverine and its downstream coastal waters

Pindolol (PIN) is a commonly used β-blocker drug and has been frequently detected in various natural waters. Comprehensive understanding of its environmental photochemical transformation is necessary to assess its environmental risk. In this study, the photodegradation kinetics and mechanisms of PIN in both freshwater and coastal water were investigated for the first time. The photodegradation experiments were carried out by steady-state photochemical experiment under simulated sunlight irradiation. The results showed that the photodegradation rate of PIN in the freshwater of the Pearl River estuary was significantly faster than that in its downstream coastal water. In river water, PIN can undergo both direct photolysis and indirect photolysis induced by riverine dissolved organic matter (DOM) mainly through excited triplet-state of DOM and singlet oxygen, while direct photolysis dominated its degradation in coastal water. The promotion effect was found to be much greater for Suwannee River Natural Organic Matter (SRNOM) than that of the sampled riverine DOM, due to its high steady-state concentrations of reactive species. Interestingly, coastal DOM in northern and southern China were found to have similar promotion effects on PIN photodegradation for the first time, but both less than that of riverine DOM. A total of seven degradation products of PIN resulting from hydroxylation, hydrogen abstraction and cleavage of ether bond were identified. Biological toxicity of one products were found to be higher than that of PIN. These results are of significance for knowing the persistence and ecological risk of PIN in natural waters.

Novel selective agents for the degradation of AR/AR-V7 to treat advanced prostate cancer

The androgen receptor AR antagonists, such as enzalutamide and apalutamide, are efficient therapeutics for the treatment of prostate cancer (PCa). Even though they are effective at first, resistance to both drugs occurs frequently. Resistance is mainly driven by aberrations of the AR signaling pathway including AR gene amplification and the expression of AR splice variants (e.g. AR-V7). This highlights the urgent need for alternative therapeutic strategies. Here, a total of 24 compounds were synthesized and biologically evaluated to disclose compound 20i, exhibiting potent AR antagonistic activities (IC50 = 172.85 ± 21.33 nM), promising AR/AR-V7 protein degradation potency, and dual targeting site of probably AR (ligand-binding domain, LBD and N-terminal domain, NTD). It potently inhibits cell growth with IC50 values of 4.87 ± 0.52 and 2.07 ± 0.34 μM in the LNCaP and 22RV1 cell lines, respectively, and exhibited effective tumor growth inhibition (TGI = 50.9 %) in the 22RV1 xenograft study. These data suggest that 20i has the potential for development as an AR/AR-V7 inhibitor with degradation ability to treat advanced prostate cancer.

Mutation characteristics and molecular evolution of ovarian metastasis from gastric cancer and potential biomarkers for paclitaxel treatment

Ovarian metastasis is one of the major causes of treatment failure in patients with gastric cancer (GC). However, the genomic characteristics of ovarian metastasis in GC remain poorly understood. In this study, we enroll 74 GC patients with ovarian metastasis, with 64 having matched primary and metastatic samples. Here, we show a characterization of the mutation landscape of this disease, alongside an investigation into the molecular heterogeneity and pathway mutation enrichments between synchronous and metachronous metastasis. We classify patients into distinct clonal evolution patterns based on the distribution of mutations in paired samples. Notably, the parallel evolution group exhibits the most favorable prognosis. Additionally, by analyzing the differential response to chemotherapy, we identify potential biomarkers, including SALL4, CCDC105, and CLDN18, for predicting the efficacy of paclitaxel treatment. Furthermore, we validate that CLDN18 fusion mutations improve tumor response to paclitaxel treatment in GC with ovarian metastasis in vitro and vivo.

Proton pump inhibitors enhance macropinocytosis-mediated extracellular vesicle endocytosis by inducing membrane v-ATPase assembly

Besides participating in diverse pathological and physiological processes, extracellular vesicles (EVs) are also excellent drug-delivery vehicles. However, clinical drugs modulating EV levels are still lacking. Here, we show that proton pump inhibitors (PPIs) reduce EVs by enhancing macropinocytosis-mediated EV uptake. PPIs accelerate intestinal cell endocytosis of autocrine immunosuppressive EVs through macropinocytosis, thereby aggravating inflammatory bowel disease. PPI-induced macropinocytosis facilitates the clearance of immunosuppressive EVs from tumour cells, improving antitumor immunity. PPI-induced macropinocytosis also increases doxorubicin and antisense oligonucleotides of microRNA-155 delivery efficiency by EVs, leading to enhanced therapeutic effects of drug-loaded EVs on tumours and acute liver failure. Mechanistically, PPIs reduce cytosolic pH, promote ATP6V1A (v-ATPase subunit) disassembly from the vacuolar membrane and enhance the assembly of plasma membrane v-ATPases, thereby inducing macropinocytosis. Altogether, our results reveal a mechanism for macropinocytic regulation and PPIs as potential modulators of EV levels, thus regulating their functions.

UCFNNet: Ulcerative colitis evaluation based on fine-grained lesion learner and noise suppression gating

BACKGROUND AND OBJECTIVE

Ulcerative colitis (UC) is a chronic disease characterized by recurrent symptoms and significant morbidity. The exact cause of the disease remains unknown. The selection of current treatment options for ulcerative colitis depends on the severity and location of the disease in each patient. Therefore, developing a fully automated endoscopic images for evaluating UC is crucial for guiding treatment plans and facilitating early prevention efforts.

METHODS

We propose a network called ulcerative colitis evaluation based on fine-grained lesion learner and noise suppression gating (UCFNNet). UCFNNet contains three novel modules. Firstly, a fine-grained lesion feature learner (FG-LF Learner) is proposed by integrating local features and a Softmax category prediction (SCP) module to improve the feature accuracy in small lesion areas. Subsequently, a graph convolutional feature combiner (GCFC) is developed to connect features across adjacent convolutional layers and to incorporate short connections between input and output, thereby mitigating feature loss during transmission. Thereafter, a noise suppression gating (NS gating) technique is designed by implementing a grid attention mechanism and a feature gating (FG) module to prioritize significant lesion features and suppress irrelevant and noisy regions in the input feature map.

RESULTS

We evaluate the performance of the proposed network on both privately-collected and publicly-available datasets. The evaluation of UC achieves excellent results on privately-collected dataset, with an accuracy (ACC) of 89.57 %, Matthews correlation coefficient (MCC) of 85.52 %, precision of 89.26 %, recall of 89.48 %, and F1-score of 89.78 %. The results are also impressive on publicly-available dataset, with ACC of 85.47 %, MCC of 80.42 %, precision of 85.62 %, recall of 84.00 %, and F1-score of 84.53 %, surpassing the performance of state-of-the-art techniques.

CONCLUSION

Our proposed model introduces three innovative algorithm modules, which outperform the current state-of-the-art methods and achieve high ACC and F1-score. This indicates that our method has superior performance compared to traditional machine learning and existing deep methods, which means that our method has good application prospects. Meanwhile, it has been verified that the proposed model demonstrates good interpretability. The source code is available at github.com/YinLeRenNB/UCFNNet.

Dynamical evolution of CO2 and H2O on garnet electrolyte elucidated by ambient pressure X-ray spectroscopies

Garnet-type Li6.5La3Zr1.5Ta0.5O12 (LLZO) is considered a promising solid electrolyte, but the surface degradation in air hinders its application for all-solid-state battery. Recent studies have mainly focused on the final products of the LLZO surface reactions due to lacking of powerful in situ characterization methods. Here, we use ambient pressure X-ray spectroscopies to in situ investigate the dynamical evolution of LLZO surface in different gas environments. The newly developed ambient pressure mapping of resonant Auger spectroscopy clearly distinguishes the lithium containing species, including LiOH, Li2O, Li2CO3 and lattice oxygen. The reaction of CO2 with LLZO to form Li2CO3 is found to be a thermodynamically favored self-limiting reaction. On the contrary, the reaction of H2O with LLZO lags behind that of CO2, but intensifies at high pressure. More interestingly, the results provide direct spectroscopic evidence for the existence of Li+/H+ exchange and reveal the importance of the initial layer formed on clean electrolyte surface in determining their air stability. This work demonstrates that the newly developed in situ technologies pave a new way to investigate the oxygen evolution and surface degradation mechanism in energy materials.

Comparison of different machine learning classification models for predicting deep vein thrombosis in lower extremity fractures

Deep vein thrombosis (DVT) is a common complication in patients with lower extremity fractures. Once it occurs, it will seriously affect the quality of life and postoperative recovery of patients. Therefore, early prediction and prevention of DVT can effectively improve the prognosis of patients. This study constructed different machine learning models to explore their effectiveness in predicting DVT. Five prediction models were applied to the study, including Extreme Gradient Boosting (XGBoost) model, Logistic Regression (LR) model, RandomForest (RF) model, Multilayer Perceptron (MLP) model, and Support Vector Machine (SVM) model. Afterwards, the performance of the obtained prediction models was evaluated by area under the curve (AUC), accuracy, sensitivity, specificity, F1 score, and Kappa. The prediction performances of the models based on machine learning are as follows: XGBoost model (AUC = 0.979, accuracy = 0.931), LR model (AUC = 0.821, accuracy = 0.758), RF model (AUC = 0.970, accuracy = 0.921), MLP model (AUC = 0.830, accuracy = 0.756), SVM model (AUC = 0.713, accuracy = 0.661). On our data set, the XGBoost model has the best performance. However, the model still needs external verification research before clinical application.

Genomic and immune microenvironment features influencing chemoimmunotherapy response in gastric cancer with peritoneal metastasis: a retrospective cohort study

BACKGROUND

Patients with peritoneal metastasis (PM) from gastric cancer (GC) exhibit poor prognosis. Chemoimmunotherapy offers promising clinical benefits; however, its efficacy and predictive biomarkers in a conversion therapy setting remain unclear. The authors aimed to retrospectively evaluate chemoimmunotherapy efficacy in a conversion therapy setting for GC patients with PM and establish a prediction model for assessing clinical benefits.

MATERIALS AND METHODS

A retrospective evaluation of clinical outcomes encompassed 55 GC patients with PM who underwent chemoimmunotherapy in a conversion therapy setting. Baseline PM specimens were collected for genomic and transcriptomic profiling. Clinicopathological factors, gene signatures, and tumor immune microenvironment were evaluated to identify predictive markers and develop a prediction model.

RESULTS

Chemoimmunotherapy achieved a 41.8% objective response rate and 72.4% R0 resection rate in GC patients with PM. Patients with conversion surgery showed better overall survival (OS) than those without the surgery (median OS: not reached vs 7.82 m, P<0.0001). Responders to chemoimmunotherapy showed higher ERBB2 and ERBB3 mutation frequencies, CTLA4 and HLA-DQB1 expression, and CD8+ T cell infiltration, but lower CDH1 mutation and naïve CD4+ T cell infiltration, compared to nonresponders. A prediction model was established integrating CDH1 and ERBB3 mutations, HLA-DQB1 expression, and naïve CD4+ T cell infiltration (AUC=0.918), which were further tested using an independent external cohort (AUC=0.785).

CONCLUSION

This exploratory study comprehensively evaluated clinicopathological, genomic, and immune features and developed a novel prediction model, providing a rational basis for the selection of GC patients with PM for chemoimmunotherapy-involved conversion therapy.

Catheter-guided anvil insertion for circular stapler esophagojejunal anastomosis: a novel technique in laparoscopic total gastrectomy

OBJECTIVE

This study evaluates feasibility, safety, and short-term outcomes of employing the catheter-guided stapler anvil insertion technique for esophagojejunal anastomosis using a circular stapler during laparoscopic total gastrectomy (LTG).

MATERIALS AND METHODS

From September 2021 to April 2023, the catheter-guided stapler anvil insertion technique was employed in 80 patients undergoing laparoscopic total gastrectomy (LTG) for esophagojejunal anastomosis. A modified D2 dissection, according to the en bloc technique, was performed in the patients. Subsequently, a longitudinal incision, approximately 2 cm in length, was made on the anterior wall of the esophagus, about 2 cm above the tumor. The transection line was pre-marked with blue dye along the esophagus's minor axis, and the tail of the anvil was capped with a 10-cm length of catheter (F14 d4.7 mm). The surgeon secures the head of anvil and carefully inserts it into the esophagus, ensuring that only a 5-cm segment of the catheter remains outside the esophagus. A linear cutter was employed to transect and seal the lower end of the esophagus. Subsequently, esophagojejunostomy was performed under laparoscopic guidance using a circular stapler.

RESULTS

Among patients undergoing esophagojejunal anastomosis with the new technique, postoperative complications included pneumonia or pleural effusion in 14 patients (17.5%), anastomotic stenosis in 3 patients (3.75%), abdominal infection in 2 patients (2.5%), and intestinal obstruction in 1 patient (1.25%). No instances of anastomotic leakage, anastomotic bleeding, or deaths were recorded. All patients experiencing complications improved with conservative treatment, without the need for secondary surgery.

CONCLUSION

The catheter-guided stapler anvil insertion technique is demonstrated to be a safe and effective method for esophagojejunostomy, potentially reducing the occurrence of anastomotic leakage.

Variability of somatosensory evoked potential and motor evoked potential change criteria in thoracic spinal decompression surgery based on preoperative motor status

BACKGROUND CONTEXT

Combined somatosensory- and motor-evoked potential (SSEP and MEP) changes for predicting prognosis in thoracic spinal surgery have been variably reported.

PURPOSE

We aimed to explore the validity of combined SSEP and MEP for predicting postoperative motor deficits (PMDs) in thoracic spinal decompression surgery (TSDS) and identify a relatively optimal neurophysiological predictor of PMDs in patients based on preoperative motor status.

STUDY SETTING

Retrospective study.

PATIENT SAMPLE

A total of 475 patients were analyzed.

OUTCOME MEASURES

A reduction in muscle strength by more than or equal to one manual muscle testing (MMT) grade postoperatively compared with the preoperative MMT grade was identified as PMDs. Postoperative motor deficits were detected by comparing the preoperative and postoperative physical examination findings in short- and long-term follow-up visits.

METHODS

All patients were divided into two subgroups according to preoperative motor status. The following data were collected: (1) demographic data; (2) IONM (intraoperative neuromonitoring) data; and (3) postoperative motor outcomes. Binary logistic regression analysis was performed to assess the efficacy of IONM change to predict PMDs. A receiver operating characteristic curve (ROC) was used to establish optimal IONM warning criteria.

RESULTS

Ninety-eight patients had severe preoperative motor deficits (Group S), and 377 patients did not (Group N). MEP and SSEP change was effective for predicting PMDs in the short term (p<.01) and long term (p<.01) for TSDS patients. In Group N, the cutoff values for predicting PMDs in the short term were a decrease of 65% in SSEP amplitude and 89.5% in MEP amplitude of the baseline value. Furthermore, the cutoff values for predicting PMDs in the short term were durations of change of 24.5 minutes for SSEP and 32.5 minutes for MEP. In Group S, however, the cutoff values for predicting PMDs in the short term were a decrease of 36.5% in SSEP amplitude and 59.5% in MEP amplitude of the baseline value. Moreover, the critical values for predicting short-term PMDs were durations of change of 16.5 minutes for SSEP and 17.5 minutes for MEP.

CONCLUSIONS

The optimal IONM changes for prediction vary depending on preoperative motor status. Combined SSEP and MEP are excellent for predicting PMDs in TSDS.

Chinese expert consensus on cone-beam CT-guided diagnosis, localization and treatment for pulmonary nodules

Cone-beam computed tomography (CBCT) system can provide real-time 3D images and fluoroscopy images of the region of interest during the operation. Some systems can even offer augmented fluoroscopy and puncture guidance. The use of CBCT for interventional pulmonary procedures has grown significantly in recent years, and numerous clinical studies have confirmed the technology's efficacy and safety in the diagnosis, localization, and treatment of pulmonary nodules. In order to optimize and standardize the technical specifications of CBCT and guide its application in clinical practice, the consensus statement has been organized and written in a collaborative effort by the Professional Committee on Interventional Pulmonology of China Association for Promotion of Health Science and Technology.

Erratum: Ubiquitous Non-Majorana Zero-Bias Conductance Peaks in Nanowire Devices [Phys. Rev. Lett. 123, 107703 (2019)]

This corrects the article DOI: 10.1103/PhysRevLett.123.107703.

Beyond waste: understanding urine's potential in precision medicine

Urine-derived stem cells (USCs) are a promising source of stem cells for cell therapy, renal toxicity drug testing, and renal disease biomarker discovery. Patients' own USCs can be used for precision medicine. In this review we first describe the isolation and characterization of USCs. We then discuss preclinical studies investigating the use of USCs in cell therapy, exploring the utility of USCs and USC-derived induced pluripotent stem cells (u-iPSCs) in drug toxicity testing, and investigating the use of USCs as biomarkers for renal disease diagnosis. Finally, we discuss the challenges of using USCs in these applications and provide insights into future research directions. USCs are a promising tool for advancing renal therapy, drug testing, and biomarker discovery. Further research is needed to explore their potential.

Physical and psychological correlates of somatic symptom in patients with functional constipation: a cross-sectional study

BACKGROUND

The symptoms of functional constipation (FC) were obviously affected by mental symptoms, which was consistent with somatic symptoms. However, the characteristics of FC patients with somatic symptom remains unexplored.

METHODS

Clinical characteristics including somatic symptom (SOM, PHQ-15), depression (PHQ-9), anxiety (GAD-7), quality of life (PAC-QOL), constipation (KESS), demographic variables, anatomical abnormalities and symptoms were investigated. Subsequent analyses encompassed the comparison of clinical parameters between patients with SOM + group (PHQ-15 ≥ 10) and SOM- group (PHQ-15 < 10), subgroup analysis, correlation analysis, and logistic regression. Lastly, we evaluated the somatic symptom severity (SSS) among FC patients subjected to various stressors.

RESULTS

Notable disparities were observed between SOM + and SOM- groups in variety of physiological and psychological variables, including gender, stressful events, sleep disorders, reduced interest, GAD-7, PHQ-15, PHQ-9, PAC-QOL, anterior rectocele, KESS, and internal anal sphincter achalasia (IASA) (P < 0.05). Subgroup analysis affirmed consistent findings across mental symptoms. Correlation analyses revealed significant associations between SSS and KESS, anterior rectocele, GAD-7, PHQ-9, and PAC-QOL (P < 0.05). Logistic regression identified PHQ-9 (OR = 7.02, CI: 2.06-27.7, P = 0.003), GAD-7 (OR = 7.18, CI: 2.00-30.7, P = 0.004), and KESS (OR = 16.8, CI: 3.09-113, P = 0.002) as independent predictors of SSS. Elevated SSS scores were significantly associated with couple, parental, and work-related stressors (P < 0.05).

CONCLUSION

A marked heterogeneity was observed between SOM + and SOM- patients of FC, with SOM + accompanied by more severe constipation, anxiety and depression symptoms. This finding underscores the importance of considering somatic symptoms in diagnosis and treatment of FC.

Physiological and Molecular Response of Liriodendron chinense to Varying Stand Density

Stand density affects the potentially superior productivity of forest ecosystems directly by regulating the light and nutrient availability of trees. Understanding how stand density influences the growth and development of trees is crucial for supporting forest management in the context of climate change. We focused on Liriodendron chinense in experimental plantations created in 2003, with planting densities ranging from 277 to 10,000 trees per hectare at six plots. The leaf structure and photosynthetic capacity of L. chinense changed significantly under different stand densities, which had a negative impact on their biomass (leaf mass) and nutrient (total carbohydrate content) accumulation. Transcriptional differences were observed among samples from plots with different planting densities. The expression of 1784 genes was negatively dependent on stand density, participating mainly in the biological processes of "circadian rhythm", "carbon metabolism", and "amino acid biosynthesis". Furthermore, we identified a photosynthesis-related module and constructed a gene regulatory network to discover that the transcription factors of MYB and bHLH may have important roles in the transcriptional regulation of photosynthesis biosynthesis by activating or repressing the expression of petA (Litul.15G096200), psbE (Litul.10G033900), and petD (Litul.17G061600) at different stand densities. Our study quantified the impact of stand density on tree growth at physiological and molecular levels. Our observations provide theoretical support for plantation establishment of L. chinense.

RALDH1 Inhibition Shows Immunotherapeutic Efficacy in Hepatocellular Carcinoma

Globally, hepatocellular carcinoma (HCC) is one of the most commonly diagnosed cancers and a leading cause of cancer-related death. We previously identified an immune evasion pathway whereby tumor cells produce retinoic acid (RA) to promote differentiation of intratumoral monocytes into protumor macrophages. Retinaldehyde dehydrogenase 1 (RALDH1), RALDH2, and RALDH3 are the three isozymes that catalyze RA biosynthesis. In this study, we have identified RALDH1 as the key driver of RA production in HCC and demonstrated the efficacy of RALDH1-selective inhibitors (Raldh1-INH) in suppressing RA production by HCC cells. Raldh1-INH restrained tumor growth in multiple mouse models of HCC by reducing the number and tumor-supporting functions of intratumoral macrophages as well as increasing T-cell infiltration and activation within tumors. Raldh1-INH also displayed favorable pharmacokinetic, pharmacodynamic, and toxicity profiles in mice thereby establishing them as promising new drug candidates for HCC immunotherapy.

Clinicopathological characteristics of gastric neuroendocrine neoplasms: A comprehensive analysis

OBJECTIVE

This study aimed to explore the clinicopathological characteristics and prognostic implications of gastric neuroendocrine neoplasms (g-NENs).

METHODS

A retrospective enrollment of 142 patients diagnosed with g-NENs was conducted at Zhejiang Cancer Hospital between January 1, 2007 and December 31, 2021. The study compared essential clinicopathological features and survival rates. Additionally, the prognosis of gastric neuroendocrine carcinomas/mixed neuroendocrine-non-neuroendocrine neoplasms (g-NEC/MiNEN) were contrasted with those of gastric adenocarcinoma (GAC) and signet ring cell carcinoma (SRCC).

RESULTS

The study comprised a total of 142 g-NENs cases, with a male-to-female ratio of approximately 2:1. The 5-year survival rates for g-NEC and g-MiNEN were 26.7% and 35.2%, respectively. Corresponding 5-year survival rates for G1 and G2 were observed at 100% and 80.0%, respectively. g-NEC/MiNEN showed a significantly worse prognosis compared to g-NET (p < 0.001). g-NEC/MiNEN exhibited a poor prognosis compared to GAC (p < 0.001), and within poorly differentiated GAC, g-NEC/MiNEN demonstrated a worse prognosis (p = 0.007). Additionally, patients receiving postoperative adjuvant therapy exhibited notably prolonged overall survival (OS) in the case of g-NEC/MiNEN (p = 0.010).

CONCLUSION

In short, the prognosis of g-NEC/MiNEN was worse than that of g-NET, GAC and poorly differentiated GAC, but this group benefit from postoperative adjuvant therapy.

Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia

PURPOSE

To explore the predictive value of radiomics in predicting stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients and construct a prediction model based on clinical features and DWI-MRI radiomics features.

METHODS

Univariate and multivariate logistic regression analyses were used to identify the independent clinical predictors for SAP. Pearson correlation analysis and the least absolute shrinkage and selection operator with ten-fold cross-validation were used to calculate the radiomics score for each feature and identify the predictive radiomics features for SAP. Multivariate logistic regression was used to combine the predictive radiomics features with the independent clinical predictors. The prediction performance of the SAP models was evaluated using receiver operating characteristics (ROC), calibration curves, decision curve analysis, and subgroup analyses.

RESULTS

Triglycerides, the neutrophil-to-lymphocyte ratio, dysphagia, the National Institutes of Health Stroke Scale (NIHSS) score, and internal carotid artery stenosis were identified as clinically independent risk factors for SAP. The radiomics scores in patients with SAP were generally higher than in patients without SAP (P < 0. 05). There was a linear positive correlation between radiomics scores and NIHSS scores, as well as between radiomics scores and infarct volume. Infarct volume showed moderate performance in predicting the occurrence of SAP, with an AUC of 0.635. When compared with the other models, the combined prediction model achieved the best area under the ROC (AUC) in both training (AUC = 0.859, 95% CI 0.759-0.936) and validation (AUC = 0.830, 95% CI 0.758-0.896) cohorts (P < 0.05). The calibration curves and decision curve analysis further confirmed the clinical value of the nomogram. Subgroup analysis showed that this nomogram had potential generalization ability.

CONCLUSION

The addition of the radiomics features to the clinical model improved the prediction of SAP in AIS patients, which verified its feasibility.

The Association between Assisted Reproductive Technologies and Neurodevelopmental Disorders in Offspring: An Overview of Current Evidence

The utilization of assisted reproductive technologies (ART) is on the rise, resulting in a growing population of ART-conceived offspring. The health concerns of this unique population have attracted significant attention. During ART procedures, gametes and early-stage embryos are exposed to various non-physiological conditions, such as manipulation, culture media, and cryopreservation, which may disrupt embryonic development and potentially impact the health of offspring. Notably, the potential impact of ART on neurodevelopment and its association with an increased risk of neurodevelopmental disorders (NDD) later in life remains a subject of debate. This review aims to summarize the current research advancements concerning the effects of ART on neurodevelopment, specifically focusing on the evidence of the relationship between ART, epigenetic modifications, and NDD, including autism spectrum disorder, intellectual disability, attention deficit hyperactivity disorder, and cerebral palsy. Future studies should prioritize large sample sizes, rigorous adjustment for confounding factors, and the use of interdisciplinary approaches to effectively monitor the neurodevelopmental outcomes of ART-conceived children.

A novel scaffold long-acting selective estrogen receptor antagonist and degrader with superior preclinical profile against ER+ breast cancer

Breast cancer is one of the most common malignant tumors in women worldwide, with the majority of cases showing expression of estrogen receptors (ERs). Although drugs targeting ER have significantly improved survival rates in ER-positive patients, drug resistance remains an unmet clinical need. Fulvestrant, which overcomes selective estrogen receptor modulator (SERM) and AI (aromatase inhibitor) resistance, is currently the only long-acting selective estrogen receptor degrader (SERD) approved for both first and second-line settings. However, it fails to achieve satisfactory efficacy due to its poor solubility. Therefore, we designed and synthesized a series of novel scaffold (THC) derivatives, identifying their activities as ER antagonists and degraders. G-5b, the optimal compound, exhibited binding, antagonistic, degradation or anti-proliferative activities comparable to fulvestrant in ER+ wild type and mutants breast cancer cells. Notably, G-5b showed considerably improved stability and solubility. Research into the underlying mechanism indicated that G-5b engaged the proteasome pathway to degrade ER, subsequently inhibiting the ER signaling pathway and leading to the induction of apoptosis and cell cycle arrest events. Furthermore, G-5b displayed superior in vivo pharmacokinetics and pharmacodynamics properties, coupled with a favorable safety profile in the MCF-7 tamoxifen-resistant (MCF-7/TR) tumor xenograft model. Collectively, G-5b has emerged as a highly promising lead compound, offering potent antagonistic and degradation activities, positioning it as a novel long-acting SERD worthy of further refinement and optimization.

Role of Autophagy and Pyroptosis in Intervertebral Disc Degeneration

Intervertebral disc degeneration is a chronic degenerative disease caused by the interaction of genetic and environmental factors, mainly manifested as lower back pain. At present, the diagnosis of intervertebral disc degeneration mainly relies on imaging. However, early intervertebral disc degeneration is usually insidious, and there is currently a lack of relevant clinical biomarkers that can reliably reflect early disease progression. Pyroptosis is a regulatory form of cell death triggered by the activation of inflammatory bodies and caspase, which can induce the formation of plasma membrane pores and cell swelling or lysis. Previous studies have shown that during the progression of intervertebral disc degeneration, sustained activation of inflammasomes leads to nuclear cell pyroptosis, which can occur in the early stages of intervertebral disc degeneration. Moreover, intervertebral disc nucleus pulposus cells adapt to the external environment through autophagy and maintain cellular homeostasis and studying the mechanism of autophagy in IDD and intervening in its pathological and physiological processes can provide new ideas for the clinical treatment of IDD. This review analyzes the effects of pyroptosis and autophagy on IDD by reviewing relevant literature in recent years, in order to explore the relationship between pyroptosis, autophagy and IDD.

A recurrence-predictive model based on eight genes and tumor mutational burden/microsatellite instability status in Stage II/III colorectal cancer

BACKGROUND

Although adjuvant chemotherapy (ACT) is widely used to treat patients with Stage II/III colorectal cancer (CRC), administering ACT to specific patients remains a challenge. The decision to ACT requires an accurate assessment of recurrence risk and absolute treatment benefit. However, the traditional TNM staging system does not accurately assess a patient's individual risk of recurrence.

METHODS

To identify recurrence risk-related genetic factors for Stage II/III CRC patients after radical surgery, we conducted an analysis of whole-exome sequencing of 47 patients with Stage II/III CRC who underwent radical surgery at five institutions. Patients were grouped into non-recurrence group (NR, n = 24, recurrence-free survival [RFS] > 5 years) and recurrence group (R, n = 23, RFS <2 years). The TCGA-COAD/READ cohort was employed as the validation dataset.

RESULTS

A recurrence-predictive model (G8plus score) based on eight gene (CUL9, PCDHA12, HECTD3, DCX, SMARCA2, FAM193A, AATK, and SORCS2) mutations and tumor mutation burden/microsatellite instability (TMB/MSI) status was constructed, with 97.87% accuracy in our data and 100% negative predictive value in the TCGA-COAD/READ cohort. For the TCGA-COAD/READ cohort, the G8plus-high group had better RFS (HR = 0.22, p = 0.024); the G8plus-high tumors had significantly more infiltrated immune cell types, higher tertiary lymphoid structure signature scores, and higher immunological signature scores. The G8plus score was also a predict biomarker for immunotherapeutic in advanced CRC in the PUCH cohort.

CONCLUSIONS

In conclusion, the G8plus score is a powerful biomarker for predicting the risk of recurrence in patients with stage II/III CRC. It can be used to stratify patients who benefit from ACT and immunotherapy.

Plant Protein-Derived Active Peptides: A Comprehensive Review

Active peptides are a class of physiologically active protein fragments, which can be prepared from different sources. In the past few decades, the production of peptides with various effects from different plant proteins continues to receive academic attention. With advances in extraction, purification, and characterization techniques, plant protein-derived active peptides continue to be discovered. They have been proven to have various functional activities such as antioxidant, antihypertensive, immunomodulatory, antimicrobial, anti-inflammatory, antidiabetic, antithrombotic, and so on. In this review, we searched Web of Science and China National Knowledge Infrastructure for relevant articles published in recent years. There are 184 articles included in this manuscript. The current status of plant protein-derived active peptides is systematically introduced, including their sources, preparation, purification and identification methods, physiological activities, and applications in the food industry. Special emphasis has been placed on the problems of active peptide exploration and the future trend. Based on these, it is expected to provide theoretical reference for the further exploitation of plant protein-derived active peptides, and promote the healthy and rapid development of active peptide industry.

D-SAT: dual semantic aggregation transformer with dual attention for medical image segmentation

Objective. Medical image segmentation is significantly essential to assist clinicians in facilitating a quick and accurate diagnoses. However, most of the existing methods are still challenged by the loss of semantic information, blurred boundaries and the huge semantic gap between the encoder and decoder.Approach. To tackle these issues, a dual semantic aggregation transformer with dual attention is proposed for medical image segmentation. Firstly, the dual-semantic feature aggregation module is designed to build a bridge between convolutional neural network (CNN) and Transformer, effectively aggregating CNN's local feature detail ability and Transformer's long-range modeling ability to mitigate semantic information loss. Thereafter, the strip spatial attention mechanism is put forward to alleviate the blurred boundaries during encoding by constructing pixel-level feature relations across CSWin Transformer blocks from different spatial dimensions. Finally, a feature distribution gated attention module is constructed in the skip connection between the encoder and decoder to decrease the large semantic gap by filtering out the noise in low-level semantic information when fusing low-level and high-level semantic features during decoding.Main results. Comprehensive experiments conducted on abdominal multi-organ segmentation, cardiac diagnosis, polyp segmentation and skin lesion segmentation serve to validate the generalization and effectiveness of the proposed dual semantic aggregation transformer with dual attention (D-SAT). The superiority of D-SAT over current state-of-the-art methods is substantiated by both subjective and objective evaluations, revealing its remarkable performance in terms of segmentation accuracy and quality.Significance. The proposed method subtly preserves the local feature details and global context information in medical image segmentation, providing valuable support to improve diagnostic efficiency for clinicians and early disease control for patients. Code is available athttps://github.com/Dxkm/D-SAT.

Precision nephrotoxicity testing using 3D in vitro models

Nephrotoxicity is a significant concern during the development of new drugs or when assessing the safety of chemicals in consumer products. Traditional methods for testing nephrotoxicity involve animal models or 2D in vitro cell cultures, the latter of which lack the complexity and functionality of the human kidney. 3D in vitro models are created by culturing human primary kidney cells derived from urine in a 3D microenvironment that mimics the fluid shear stresses of the kidney. Thus, 3D in vitro models provide more accurate and reliable predictions of human nephrotoxicity compared to existing 2D models. In this review, we focus on precision nephrotoxicity testing using 3D in vitro models with human autologous urine-derived kidney cells as a promising approach for evaluating drug safety.

[Investigating ocular parameters for predicting anomalous vault among phakic intraocular lens patients]

Objective: To analyze the relationships between preoperative ocular parameters and postoperative anomalous vaults, and research their predictive diagnostic value. Methods: In this retrospective case series study, 664 eyes from 332 patients underwent posterior chamber phakic intraocular lens (pIOL) implantation at Shanghai Bright Eye Hospital and Wuxi Huaxia Eye Hospital from November 2020 to November 2021. Preoperative ocular parameters, including spherical equivalent, intraocular pressure, horizontal/vertical ciliary sulcus diameters (HCS/VCS), white-to-white diameters (WTW), corneal steep/flat curvature, central corneal thickness, anterior chamber depth (ACD), lens thickness (LT), and axial length were collected. The pIOL vaults were measured 3 months after surgery. Patients were categorized into low vault group, optimal vault group, and high vault group based on whether the vault fell within the ideal range (250 to 750 μm). Using the optimal vault group as a benchmark, receiver operating characteristic (ROC) curves were drawn for each ocular parameter of the low and high vault groups to analyze diagnostic efficiency and cut-off values for abnormal vaults after pIOL operation. Each ocular parameter was used as an independent variable to establish a multivariate logistic regression model for two different vault anomalies. ROC curves were drawn and analyzed again based on the regression results. Results: Statistically significant differences were observed in WTW, HCS-WTW, ACD, and LT among the three groups. Comparisons between each pair of groups indicated that WTW in the high vault group significantly differed from the other two groups (P<0.05), HCS-WTW in the low vault group significantly differed from the other groups (P<0.05), and ACD and LT explained statistical differences among the three groups (P<0.05), while other parameters showed no differences. ROC curves illustrated that independent ocular parameters such as LT, HCS-WTW, and ACD had clinical predictive diagnostic significance for low vault abnormalities. The area under the curve (AUC), sensitivity, and specificity for these parameters were 0.829(0.952, 0.561), 0.745(0.857, 0.644), and 0.730(0.619, 0.853), respectively. The diagnostic cut-off values were 3.745, 0.020, and 2.975 mm, respectively. The clinical predictive significance of independent ocular parameters in diagnosing the high vault group was poor (AUC<0.7). The predictive Logistic model equation for low vault was Logistic(V1)=-10.067+5.328·HCS-3.620·WTW+6.263·LT, and the predictive model for high vault was Logistic(V2)=6.232+1.323·WTW-3.358·LT. The new parameters in the predictive equation significantly improved the diagnostic efficiency of low and high vault abnormalities, reaching 0.884(0.810, 0.824) and 0.736(0.810, 0.554), respectively. Conclusions: Preoperative predictive diagnostic parameters for postoperative low vault group included LT, HCS-WTW, and ACD, while the high vault group had no independent predictive diagnostic parameters. Logistic regression improved the predictive diagnostic efficiency of abnormal vaults.

Mapping and modeling human colorectal carcinoma interactions with the tumor microenvironment

The initiation and progression of cancer are intricately linked to the tumor microenvironment (TME). Understanding the function of specific cancer-TME interactions poses a major challenge due in part to the complexity of the in vivo microenvironment. Here we predict cancer-TME interactions from single cell transcriptomic maps of both human colorectal cancers (CRCs) and mouse CRC models, ask how these interactions are altered in human tumor organoid (tumoroid) cultures, and functionally recapitulate human myeloid-carcinoma interactions in vitro. Tumoroid cultures suppress gene expression programs involved in inflammation and immune cell migration, providing a reductive platform for re-establishing carcinoma-immune cell interactions in vitro. Introduction of human monocyte-derived macrophages into tumoroid cultures instructs macrophages to acquire immunosuppressive and pro-tumorigenic gene expression programs similar to those observed in vivo. This includes hallmark induction of SPP1, encoding Osteopontin, an extracellular CD44 ligand with established oncogenic effects. Taken together, these findings offer a framework for understanding CRC-TME interactions and provide a reductionist tool for modeling specific aspects of these interactions.

Simulation Investigation on the Influence Mechanism of Toluene and Heptane on the Aggregation of Asphaltene Molecules

Asphaltenes are a group of compounds that are soluble in benzene and toluene but insoluble in nonpolar small molecule n-alkanes. The asphaltene aggregation in the asphaltene-heptane-toluene system was studied using molecular dynamics (MD) simulation, and the interaction between asphaltene molecules during this process was also revealed from the evolution of the density field, radial distribution function (RDF), and intermolecular distance of asphaltenes. Three main findings were made: (1) more asphaltene precipitates (heptane) were contained, and more asphaltene dimers or trimers were formed during the MD simulation; (2) asphaltene molecules interacted with each other to form aggregates in the form of π-π or H-bond interaction. The stable distance of the π-π interaction was 3.3-3.5 Å, and the stable distance of the H-bond connection was 1.7-1.9 Å. (3) The asphaltene interaction in the heptane-rich system was dominated by π-π interaction between asphaltene molecules. However, the asphaltene interactions in the toluene-rich system were mainly the π-π interaction between asphaltene molecules and toluene and the H-bond interaction between the side chains of asphaltene molecules. The results of this study can aid in understanding how asphaltene molecules aggregate and self-associate and can also offer theoretical support for flow assurance in systems used to produce crude oil.

GPR35 acts a dual role and therapeutic target in inflammation

GPR35 is a G protein-coupled receptor with notable involvement in modulating inflammatory responses. Although the precise role of GPR35 in inflammation is not yet fully understood, studies have suggested that it may have both pro- and anti-inflammatory effects depending on the specific cellular environment. Some studies have shown that GPR35 activation can stimulate the production of pro-inflammatory cytokines and facilitate the movement of immune cells towards inflammatory tissues or infected areas. Conversely, other investigations have suggested that GPR35 may possess anti-inflammatory properties in the gastrointestinal tract, liver and certain other tissues by curbing the generation of inflammatory mediators and endorsing the differentiation of regulatory T cells. The intricate role of GPR35 in inflammation underscores the requirement for more in-depth research to thoroughly comprehend its functional mechanisms and its potential significance as a therapeutic target for inflammatory diseases. The purpose of this review is to concurrently investigate the pro-inflammatory and anti-inflammatory roles of GPR35, thus illuminating both facets of this complex issue.

[Advances in clinical significance and detection methods research of high density lipoprotein subfractions]

High density lipoprotein (HDL) is an important biochemical index of clinical cardiovascular disease. Many new studies have demonstrated abnormalities of plasma HDL subfractions in patients with this disease,and their clinical significance is greater than the overall abnormalities of HDL. Therefore,the HDL subfraction as an important factor in cardiovascular disease has attracted extensive research and attention. This article summarizes current research on HDL subfractions,their measurements and their relationships with atherosclerosis and coronary artery disease.

SOX combined with sintilimab versus SOX alone in the perioperative management of locally advanced gastric cancer: a propensity score-matched analysis

OBJECTIVES

To evaluate the efficacy of SOX combined with a programmed cell death protein-1 (PD-1) inhibitor compared with SOX alone in the perioperative management of locally advanced gastric cancer and to explore biomarkers that may predict response to anti-PD-1 therapy.

METHODS

Data of patients with clinical stage T3-4aN0-3M0 (IIb-III) gastric cancer were reviewed to create a primary database. Patients treated with perioperative SOX combined with sintilimab were included in Group A, while those treated with SOX alone were included in Group B. After one-to-one propensity score matching, pathological response and short-term survival outcomes were compared between the two groups. In addition, potential efficacy-related biomarkers were analyzed.

RESULTS

Between January 2018 and December 2022, a total of 150 patients were included in the analysis, with 75 patients in each group. The rates of pathological complete response (21.3% vs. 4.0%; P = 0.001) and major pathological response (45.3% vs. 22.7%; P = 0.003) in Group A were statistically higher than those in Group B. There was no significant difference in 1-year overall survival (92.8% vs. 92.0%; P = 0.392) and disease-free survival (88.9% vs. 88.0%; P = 0.357) between the two groups. Subgroup analysis of Group A showed that the pathological complete response (40.6% vs. 8.6%; P = 0.002) and major pathological response (65.6% vs. 28.6%; P = 0.002) rates were significantly higher in programmed death ligand-1-positive patients with a combined positive score of ≥ 5. A pathological complete response was achieved in 42.9% patients (3/7) with mismatch repair deficiency. For the two patients confirmed as Epstein-Barr virus-positive, one patient achieved a pathological complete response and the other achieved a major pathological response.

CONCLUSIONS

The adoption of SOX combined with a PD-1 inhibitor may improve the pathological response rate of patients with locally advanced gastric cancer, especially those with programmed death ligand-1 combined positive score ≥ 5, Epstein-Barr virus-positivity and mismatch repair deficiency. However, further prospective studies are still warranted to confirm the long-term survival benefit.

Characterization and properties of manganese oxide film coated clinoptilolite as filter material in fixed-bed columns for removal of Mn(II) from aqueous solution

A new filter material, manganese oxide film coated clinoptilolite (MOFCC), was characterized and introduced to explore the effect in treating high concentration of manganese (1.71-2.12 mg L-1) from aqueous solution in fixed-bed column. Adsorption behavior of Mn(II) can be approximately described with the Langmuir isotherm. During the continuous 30 days filtration experiment, the removal rate of Mn(II) has maintained to be above 95.51%, the accumulated removal amount (806.42 mg) is much higher than the theoretical adsorption capacity (89.71 mg), which indicated that the removal of manganese by MOFCC includes both adsorption and auto-catalytic oxidation process, and it does not require a start-up period. SEM, EDS, XPS, XRD, ZETA potential and BET analyses were used to observe the surface properties of MOFCC. The manganese oxide film of MOFCC exhibits in clusters, apparently on occupied surface, the main component of the manganese oxide film is (Na0.7Ca0.3)Mn7O14·2.8H2O, the specific surface area of MOFCC is 38.76 m2 g-1, and the pore size is concentrated in the range of 3-40 nm, within the mesoporous range mesopores. pHpzc (point of zero charge) value is about 2.36. The characteristics of MOFCC make it an excellent manganese removal filter material for water treatment plant. Therefore, there is a long-term practical significance to develop new system for deep removal of manganese based on MOFCC.

Prediction of recurrent ischaemic stroke using radiomics data and machine learning methods in patients with acute ischaemic stroke: protocol for a multicentre, large sample, prospective observational cohort study in China

INTRODUCTION

Stroke is a leading cause of mortality and disability worldwide. Recurrent strokes result in prolonged hospitalisation and worsened functional outcomes compared with the initial stroke. Thus, it is critical to identify patients who are at high risk of stroke recurrence. This study is positioned to develop and validate a prediction model using radiomics data and machine learning methods to identify the risk of stroke recurrence in patients with acute ischaemic stroke (AIS).

METHODS AND ANALYSIS

A total of 1957 patients with AIS will be needed. Enrolment at participating hospitals will continue until the required sample size is reached, and we will recruit as many participants as possible. Multiple indicators including basic clinical data, image data, laboratory data, CYP2C19 genotype and follow-up data will be assessed at various time points during the registry, including baseline, 24 hours, 7 days, 1 month, 3 months, 6 months, 9 months and 12 months. The primary outcome was stroke recurrence. The secondary outcomes were death events, prognosis scores and adverse events. Imaging images were processed using deep learning algorithms to construct a programme capable of automatically labelling the lesion area and extracting radiomics features. The machine learning algorithms will be applied to integrate cross-scale, multidimensional data for exploratory analysis. Then, an ischaemic stroke recurrence prediction model of the best performance for patients with AIS will be established. Calibration, receiver operating characteristic and decision curve analyses will be evaluated.

ETHICS AND DISSEMINATION

This study has received ethical approval from the Medical Ethics Committee of the Second Affiliated Hospital of Nanchang University (medical research review No.34/2021), and informed consent will be obtained voluntarily. The research findings will be disseminated through publication in journals and presented at conferences.

TRIAL REGISTRATION NUMBER

ChiCTR2200055209.

Logic gate-driven dual-index balanced visualization strategy for tumor metastasis diagnosis

Exfoliated tumor cells are integral to malignant tumors diagnosis. The process of clinical cytology of exfoliation involves several complex steps that require at least two days of preparation. Here, we develop a balanced-etching visual kit based on concentration differences of Glutathione/Glucose (GSH/Glu) to distinguish normal from exfoliated tumor cells rapidly and accurately. The balanced-etching visualization kit can be used to obtain color cards and screen exfoliated tumor cells initially (within 10 min). Furthermore, by utilizing logic gates and machine learning algorithms for RGB extraction of the color card obtained from the kit, accurate screening of exfoliated tumor cells is achieved. Finally, a series of clinical tumor samples, such as urine, pleural fluids, ascites, and gastric fluids, have been validated. With effective experimental methods, accurate disease information, and appropriate therapeutic programs, the novel diagnostic strategy is expected to promote precision medicine.

PMJAF-Net: Pyramidal multi-scale joint attention and adaptive fusion network for explainable skin lesion segmentation

Traditional convolutional neural networks have achieved remarkable success in skin lesion segmentation. However, the successive pooling operations and convolutional spans reduce the feature resolution and hinder the dense prediction for spatial information, resulting in blurred boundaries, low accuracy and poor interpretability for irregular lesion segmentation under low contrast. To solve the above issues, a pyramidal multi-scale joint attention and adaptive fusion network for explainable (PMJAF-Net) skin lesion segmentation is proposed. Firstly, an adaptive spatial attention module is designed to establish the long-term correlation between pixels, enrich the global and local contextual information, and refine the detailed features. Subsequently, an efficient pyramidal multi-scale channel attention module is proposed to capture the multi-scale information and edge features by using the pyramidal module. Meanwhile, a channel attention module is devised to establish the long-term correlation between channels and highlight the most related feature channels to capture the multi-scale key information on each channel. Thereafter, a multi-scale adaptive fusion attention module is put forward to efficiently fuse the scale features at different decoding stages. Finally, a novel hybrid loss function based on region salient features and boundary quality is presented to guide the network to learn from map-level, patch-level and pixel-level and to accurately predict the lesion regions with clear boundaries. In addition, visualizing attention weight maps are utilized to visually enhance the interpretability of our proposed model. Comprehensive experiments are conducted on four public skin lesion datasets, and the results demonstrate that the proposed network outperforms the state-of-the-art methods, with the segmentation assessment evaluation metrics Dice, JI, and ACC improved to 92.65%, 87.86% and 96.26%, respectively.

Hyperthermic intraperitoneal chemotherapy (HIPEC) plus systemic chemotherapy versus systemic chemotherapy alone in locally advanced gastric cancer after D2 radical resection: a randomized-controlled study

BACKGROUND

Currently, there is a lack of an effective strategy for the prevention of peritoneal metastasis (PM) from locally advanced gastric cancer (AGC). This randomized-controlled study aimed to evaluate the outcome of D2 radical resection with hyperthermic intraperitoneal chemotherapy (HIPEC) plus systemic chemotherapy versus systemic chemotherapy alone in locally AGC patients.

METHODS

All enrolled patients were randomly assigned to receive HIPEC plus systemic chemotherapy (HIPEC group) or systemic chemotherapy alone (non-HIPEC group) after radical gastrectomy. HIPEC was performed intraperitoneally with cisplatin (40 mg/m2) within 72 h after surgery, while systemic chemotherapy based on the SOX regimen (S-1 combined with oxaliplatin) was administered 4-6 weeks after radical surgery. Patterns of recurrence, adverse events, 3-year disease-free survival (DFS), and overall survival (OS) were analyzed.

RESULTS

A total of 134 patients were enrolled in the present study. The 3-year DFS rate was 73.8% in the HIPEC group, which was significantly higher than that in the non-HIPEC group (61.2%, P = 0.031). The 3-year OS rate was 73.9% in the HIPEC group and 77.6% in the non-HIPEC group, with no significant difference (P = 0.737). PM was the most common distant metastasis in both groups. The occurrence rate of PM in the HIPEC group was statistically lower than that in the non-HIPEC group (20.9% vs. 40.3%, P = 0.015). Grade 3 or 4 adverse events occurred in 19 (14.2%) patients, and there was no significant difference between the two groups.

CONCLUSION

Radical surgery followed by HIPEC combined with systemic chemotherapy is a safe and feasible strategy for locally AGC patients and could effectively improve DFS and reduce the occurrence of PM. However, more prospective randomized studies with a large sample size are warranted.

TRIAL REGISTRATION

This study was registered with www.medresman.org.cn as ChiCTR2200055966 on 10/12/2016.

Insights into the mechanisms of natural organic matter on the photodegradation of indomethacin under natural sunlight and simulated light irradiation

Indomethacin (INDO) is an antipyretic and analgesic pharmaceutical that has been widely detected in the aquatic environment. Photodegradation is an essential pathway for removal of INDO in sunlit surface water, however the effect of dissolved organic matter (DOM) on its photodegradation and the ecotoxicity of photodegradation products are largely unknown. In this study, the effect of DOM on the photodegradation of INDO under both natural and simulated light irradiation was studied. The results showed that indirect photolysis is the main photodegradation pathway of INDO in presence of DOM where 3DOM* plays the most important promoting role. Compared to commercial DOM (SRNOM and SRFA), DOM extracted from local-lake water (SLDOM) promoted the photodegradation to the highest extent. Although the steady-state concentrations of 3DOM* of SRNOM and SRFA were higher than SLDOM, their inhibition effect surpassed SLDOM namely higher light screening effect and phenolic antioxidant concentrations. The photodegradation pathway in pure water is different from that in DOM system where the decarboxylation of acetic acid chain and the oxidative fracture of indole ring are the main degradation pathways. Density Functional Theory (DFT) calculation further supports the proposed degradation pathways of INDO. ECOSAR calculation showed that the toxicity of INDO photodegradation products to aquatic organisms may maintain or even exceed its parent compound. Therefore, comprehensive understanding of the impact of DOM on the photodegradation of INDO is of crucial significance for evaluating its ecological risk in the natural environment.

Immortalization-upregulated protein promotes pancreatic cancer progression by regulating NPM1/FHL1-mediated cell-cycle-checkpoint protein activity

Immortalization-upregulated protein (IMUP) plays a vital role in cell proliferation and tumor progression. However, its role in pancreatic ductal adenocarcinoma (PDAC) remains unclear. Here, we select IMUP as an alternative gene based on GeneChip analysis of clinical PDAC tissues and transcriptome data from The Cancer Genome Atlas. IMUP expression is upregulated in PDAC tumor tissues. Moreover, high IMUP expression correlates with poor prognosis, while IMUP depletion inhibits PDAC cell proliferation and colony formation capacity in vitro, and decreases xenograft tumor growth in vivo. IMUP downregulation leads to cell-cycle arrest in the S phase. IMUP knockdown increases the expression of four-and-a-half LIM domain protein 1 (FHL1), which regulates the phosphorylation of cell division cycle 25A (CDC25A) by cycle checkpoint kinase 1 (CHK1) and promotes cytoplasmic distribution of CDC25A by interaction with 14-3-3ξ. Furthermore, FHL1 knockdown restores the effects induced by IMUP depletion. Liquid chromatography tandem mass spectrometry and immunoprecipitation analysis further show that IMUP interacts directly with nucleophosmin (NPM1) and enhances its stability. DNA methylation sequencing shows that FHL1 promoter methylation decreases when IMUP is downregulated. Overexpression of NPM1 can increase the methylation level of FHL1, thereby decreasing its expression. Our study provides a novel perspective on IMUP/NPM1/FHL1-mediated cell-cycle arrest by regulating CDC25A phosphorylation in PDAC. These findings may provide a new therapeutic target for PDAC.

Screening of Ginkgo Individuals with Superior Growth Structural Characteristics in Different Genetic Groups Using Terrestrial Laser Scanning (TLS) Data

With the concept of sustainable management of plantations, individual trees with excellent characteristics in plantations have received attention from breeders. To improve and maintain long-term productivity, accurate and high-throughput access to phenotypic characteristics is essential when establishing breeding strategies. Meanwhile, genetic diversity is also an important issue that must be considered, especially for plantations without seed source information. This study was carried out in a ginkgo timber plantation. We used simple sequence repeat (SSR) markers for genetic background analysis and high-density terrestrial laser scanning for growth structural characteristic extraction, aiming to provide a possibility of applying remote sensing approaches for forest breeding. First, we analyzed the genetic diversity and population structure, and grouped individual trees according to the genetic distance. Then, the growth structural characteristics (height, diameter at breast height, crown width, crown area, crown volume, height to living crown, trunk volume, biomass of all components) were extracted. Finally, individual trees in each group were comprehensively evaluated and the best-performing ones were selected. Results illustrate that terrestrial laser scanning (TLS) point cloud data can provide nondestructive estimates of the growth structural characteristics at fine scale. From the ginkgo plantation containing high genetic diversity (average polymorphism information content index was 0.719) and high variation in growth structural characteristics (coefficient of variation ranged from 21.822% to 85.477%), 11 excellent individual trees with superior growth were determined. Our study guides the scientific management of plantations and also provides a potential for applying remote sensing technologies to accelerate forest breeding.

Comparison of the Predictive Value of Inflammatory Biomarkers for the Risk of Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke

Purpose

To investigate the predictive value of various inflammatory biomarkers in patients with acute ischemic stroke (AIS) and evaluate the relationship between stroke-associated pneumonia (SAP) and the best predictive index.

Patients and Methods

We calculated the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), prognostic nutritional index (PNI), systemic inflammation response index (SIRI), systemic immune inflammation index (SII), Glasgow prognostic score (GPS), modified Glasgow prognostic score (mGPS), and prognostic index (PI). Variables were selectively included in the logistic regression analysis to explore the associations of NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI with SAP. We assessed the predictive performance of biomarkers by analyzing receiver operating characteristic (ROC) curves. We further used restricted cubic splines (RCS) to investigate the association. Next, we conducted subgroup analyses to investigate whether specific populations were more susceptible to NLR.

Results

NLR, PLR, MLR, SIRI, SII, GPS, mGPS, and PI increased significantly in SAP patients, and PNI was significantly decreased. After adjustment for potential confounders, the association of inflammatory biomarkers with SAP persisted. NLR showed the most favorable discriminative performance and was an independent risk factor predicting SAP. The RCS showed an increasing nonlinear trend of SAP risk with increasing NLR. The AUC of the combined indicator of NLR and C-reactive protein (CRP) was significantly higher than those of NLR and CRP alone (DeLong test, P<0.001). Subgroup analyses suggested good generalizability of the predictive effect.

Conclusion

NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI can predict the occurrence of SAP. Among the indices, the NLR was the best predictor of SAP occurrence. It can therefore be used for the early identification of SAP.

A pan-cancer analysis of potassium channel tetramerization domain containing 12 in human cancer

Abnormal expression of the potassium channel tetramerization domain containing 12 (KCTD12) is closely related to the occurrence and development of various tumors, but a pan-cancer analysis of KCTD12 has not yet been conducted. We explored the association between KCTD12 and more than 30 human malignancies using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. First, the mRNA and protein levels of KCTD12 were examined and their correlations with tumor stage and survival were explored. Second, we analyzed the infiltration of CD8+ and CD4+ T cells and cancer-associated fibroblasts in tumors and explored the correlation between KCTD12 expression and tumor cell stemness, genomic heterogeneity, and diagnostic specificity. Finally, we explored the molecular mechanisms associated with KCTD12 using KEGG/GO analysis. The results showed that KCTD12 mRNA and protein expression levels decreased in most tumors was significantly associated with the prognosis of tumor patients, and the phosphorylation level of KCTD12 decreased in several tumors, such as S200 and T196, pancreatic adenocarcinoma (PAAD), lung adenocarcinoma (LUAD), and breast invasive cancer (BRCA). The expression of KCTD12 was positively correlated with the degree of cancer-associated fibroblasts infiltration in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), head and neck squamous cell carcinoma (HNSC), PAAD, and stomach adenocarcinoma (STAD). The relationship between KCTD12 expression and CD8+ and CD4+ T cell infiltration was also clarified. KCTD12 showed high diagnostic sensitivity for various types of tumors and may be involved in tumor cell biology by affecting tumor cell stemness, tumor burden, and other characteristics. Finally, we analyzed the molecular functions of KCTD12 and possible KEGG/GO signaling pathways. In this study, we developed a biological marker for diagnosis, prognosis, and immune infiltration of the pan-cancers.

Identification and In Silico Analysis of ACE-Inhibitory Peptides Derived from Milk Fermented by Lacticaseibacillus paracasei

Inhibition of angiotensin I-converting enzyme (ACE) activity is an effective way to treat hypertension. In the present study, the ability to produce ACE-inhibitory peptides during fermentation of skimmed milk by the Lacticaseibacillus paracasei M3 strain was evaluated, and the inhibitory mechanism and stability were studied by bioinformatics analysis. The results showed that the ACE inhibition activity of fermented milk was 71.94 ± 1.39%. After digestion with gastric juice and pancreatic juice, the ACE inhibitory activities of the fermented milk were 78.40 ± 1.93 and 74.96 ± 1.73%, respectively. After the fermented milk was purified using ultrafiltration and gel chromatography, 11 peptides from milk proteins were identified and sequenced by Nano LC-MS/MS. Molecular docking displayed that peptide PWIQPK had a high affinity, with ACE showing a binding energy of -6.10 kcal/mol. Hydrogen bonds were formed between PWIQPK and Glu384 in the S1 active pocket of ACE and Asp358. In addition, van der Waals forces were observed. In silico proteolysis suggested that PWIQPK could resist the digestion of pepsin and trypsin, indicating that it is relatively stable in the digestive tract. All results indicate that milk fermented by L. paracasei M3 has the potential to be used as a functional food having antihypertensive effects.

Efficacy of chemotherapy combined with surgical resection for gastric cancer with synchronous ovarian metastasis: A propensity score matching analysis

BACKGROUND

Ovarian metastasis from gastric cancer (GC) is characterized by aggressive biological behavior and poor outcome. Currently, there is no standard treatment mode for such patients. Thus, we evaluated the efficacy of conversion therapy in patients with synchronous ovarian metastasis from GC in this study.

METHODS

About 219 GC patients with ovarian metastasis in 2011-2020 were enrolled. Two groups were established based on the different treatment: the conversion therapy group (chemotherapy combined with surgical resection, CS group) and the non-conversion therapy group (NCS group). Propensity score matching (PSM) was used to analyze the efficacy of different treatment modes on the prognosis of these patients.

RESULTS

Ninety-two patients were included according to PSM results, with 46 patients each in CS and NCS groups. The median overall survival (OS) in the CS group was notably better than that in the NCS group (p < 0.001). Twenty-six patients (56.52%) in the CS group achieved R0 resection, and they had a better prognosis (p = 0.003). Compared with patients who underwent simultaneous gastrectomy and ovarian metastasectomy (CSb group), those who underwent ovarian metastasectomy before systemic chemotherapy (CSa group) had a higher R0 resection rate (p = 0.016) and longer survival time (p = 0.002). A total of 38 patients (41.30%) across both groups received hyperthermic intraperitoneal chemotherapy (HIPEC), and these patients had a better survival (p = 0.043).

CONCLUSION

The conversion therapy is safe and effective for patients with synchronous ovarian metastasis from GC and can improve their prognosis. However, our results need to be confirmed by more randomized controlled clinical studies.

Comprehensive Detection of PD-L1 Protein and mRNA in Tumor Cells and Extracellular Vesicles through a Real-Time qPCR Assay

A growing number of studies have shown that tumor cells secrete extracellular vesicles (EVs) containing programmed death-ligand 1 (PD-L1) protein. These vesicles can travel to lymph nodes and remotely inactivate T cells, thereby evading immune system attack. Therefore, the simultaneous detection of PD-L1 protein expression in cells and EVs is of great significance in guiding immunotherapy. Herein, we developed a method based on qPCR for the simultaneous detection of PD-L1 protein and mRNA in EVs and their parental cells (PREC-qPCR assay). Lipid probes immobilized on magnetic beads were used to capture EVs directly from samples. For RNA assay, EVs were directly broken by heating and quantified with qPCR. As to protein assay, EVs were recognized and bound with specific probes (such as aptamers), which were used as templates in subsequent qPCR analysis. This method was used to analyze EVs of patient-derived tumor clusters (PTCs) and plasma samples from patients and healthy volunteers. The results revealed that the expression of exosomal PD-L1 in PTCs was correlated with tumor types and significantly higher in plasma-derived EVs from tumor patients than that of healthy individuals. When extended to cells and PD-L1 mRNAs, the results showed that the expression of PD-L1 protein was consistent with mRNA in cancer cell lines, while PTCs demonstrated significant heterogeneity. This comprehensive detection of PD-L1 at four levels (cell, EVs, protein, and mRNA) is believed to enhance our understanding of the relationship among PD-L1, tumors, and the immune system and to provide a promising tool for predicting the benefits of immunotherapy.

Tailoring Electronic Structure to Achieve Maximum Utilization of Transition Metal Redox for High-Entropy Na Layered Oxide Cathodes

Charge compensation from cationic and anionic redox couples accompanying Na⁺ (de)intercalation in layered oxide cathodes contributes to high specific capacity. However, the engagement level of different redox couples remains unclear and their relationship with Na⁺ content is less studied. Here we discover that it is possible to take full advantage of the high-voltage transition metal (TM) redox reaction through low-valence cation substitution to tailor the electronic structure, which involves an increased ratio of Na⁺ content to available charge transfer number of TMs. Taking Na_xCu_0.11Ni_0.11Fe_0.3Mn_0.48O₂ as the example, the Li⁺ substitution increases the ratio to facilitate the high-voltage TM redox activity, and further F-ion substitution decreases the covalency of the TM-O bond to relieve structural changes. As a consequence, the final high-entropy Na_0.95Li_0.07Cu_0.11Ni_0.11Fe_0.3Mn_0.41O_1.97F_0.03 cathode demonstrates ∼29% capacity increase contributed by the high-voltage TMs and exhibits excellent long-term cycling stability due to the improved structural reversibility. This work provides a paradigm for the design of high-energy-density electrodes by simultaneous electronic and crystal structure modulation.

High-Temperature Liquid-Liquid Phase Transition in Glass-Forming Liquid Pd43Ni20Cu27P10

Liquid-liquid phase transition (LLPT) is a transition from one liquid state to another with the same composition but distinct structural change, which provides an opportunity to explore the relationships between structural transformation and thermodynamic/kinetic anomalies. Herein the abnormal endothermic LLPT in Pd₄₃Ni₂₀Cu₂₇P₁₀ glass-forming liquid was verified and studied by flash differential scanning calorimetry (FDSC) and ab initio molecular dynamics (AIMD) simulations. The results show that the change of the atomic local structure of the atoms around the Cu-P bond leads to the change in the number of specific clusters <0 2 8 0> and <1 2 5 3>, which leads to the change in the liquid structure. Our findings reveal the structural mechanisms that induce unusual heat-trapping phenomena in liquids and advance the understanding of LLPT.

Therapeutic Benefits of Stem Cells and Exosomes for Sulfur-Mustard-Induced Tissue Damage

Sulfur mustard (SM) is a highly toxic chemical agent that causes severe tissue damage, particularly to the eyes, lungs, and skin. Despite advances in treatment, there is a need for more effective therapies for SM-induced tissue injury. Stem cell and exosome therapies are emerging as promising approaches for tissue repair and regeneration. Stem cells can differentiate into multiple cell types and promote tissue regeneration, while exosomes are small vesicles that can deliver therapeutic cargo to target cells. Several preclinical studies demonstrated the potential of stem cell, exosome, or combination therapy for various tissue injury, showing improvements in tissue repairing, inflammation, and fibrosis. However, there are also challenges associated with these therapies, such as the requirement for standardized methods for exosome isolation and characterization, the long-term safety and efficacy and reduced SM-induced tissue injury of these therapies. Stem cell or exosome therapy was used for SM-induced eye and lung injury. Despite the limited data on the use for SM-induced skin injury, this therapy is a promising area of research and may offer new treatment options in the future. In this review, we focused on optimizing these therapies, evaluating their safety and efficacy, and comparing their efficacy to other emerging therapeutic approaches potentially for SM-induced tissue injury in the eye, lung, and skin.

MCE-Net: Polyp segmentation with multiple branch series-parallel attention and channel interaction via edge distribution guidance

OBJECTIVE

Accurate polyp segmentation is vital for diagnosing colorectal cancer. However, it is still challenging for accurate polyp segmentation and several bottlenecks exist, such as incomplete boundary, localization bias and lack of micro blocks along with large fragmented boundaries in uncertain regions.

APPROACH

To address the above issues, a novel polyp segmentation network with multiple branch series-parallel attention and channel interaction via edge distribution guidance is proposed. Initially, the edge distribution guidance strategy is proposed to generate the edge distribution following Cauchy distribution to capture complementary edges with sufficient details. Subsequently, a multiple branch series-parallel attention (MBSA) module is put forward to extract features from various receptive fields to pinpoint tiny polyps by a multiple kernel dilated convolution block, while combining semantics of different dimensions to filter out noise and refining the details of micro target. Ultimately, the channel interaction model (CIM) is proposed to improve the segmentation accuracy of the polyps in uncertain area by splitting channels into groups and conducts group-wise interaction to excavate subtle clues contained in different channels.

MAIN RESULTS

Extensive experimental results demonstrate that the proposed method is superior over the state-of-the-art methods with the mean dice of 0.8972, 0.9420, 0.8312, 0.8064 and 0.9214 on five public polyp datasets.

SIGNIFICANCE

The proposed method improves the integrity of the margins and internal details for polyp segmentation, which will provide a powerful aid for doctors to achieve accurate judgments, reducing the likelihood of colorectal cancer and improving the survival chances of patients.