Stigma receptors control intraspecies and interspecies barriers in Brassicaceae.

Flowering plants have evolved numerous intraspecific and interspecific prezygotic reproductive barriers to prevent production of unfavourable offspring1. Within a species, self-incompatibility (SI) is a widely utilized mechanism that rejects self-pollen2,3 to avoid inbreeding depression. Interspecific barriers restrain breeding between species and often follow the SI × self-compatible (SC) rule, that is, interspecific pollen is unilaterally incompatible (UI) on SI pistils but unilaterally compatible (UC) on SC pistils1,4-6. The molecular mechanisms underlying SI, UI, SC and UC and their interconnections in the Brassicaceae remain unclear. Here we demonstrate that the SI pollen determinant S-locus cysteine-rich protein/S-locus protein 11 (SCR/SP11)2,3 or a signal from UI pollen binds to the SI female determinant S-locus receptor kinase (SRK)2,3, recruits FERONIA (FER)7-9 and activates FER-mediated reactive oxygen species production in SI stigmas10,11 to reject incompatible pollen. For compatible responses, diverged pollen coat protein B-class12-14 from SC and UC pollen differentially trigger nitric oxide, nitrosate FER to suppress reactive oxygen species in SC stigmas to facilitate pollen growth in an intraspecies-preferential manner, maintaining species integrity. Our results show that SRK and FER integrate mechanisms underlying intraspecific and interspecific barriers and offer paths to achieve distant breeding in Brassicaceae crops.

Visceral and ectopic fat are more predictively associated with primary liver cancer than overall obesity from genetic sights: A Mendelian randomization study.

Several observational studies have reported an association between obesity and primary liver cancer (PLC), while the causality behind this association and the comparison of the risk effects of different obesity indicators on PLC remain unclear. In this study, we performed two-sample Mendelian randomization (MR) analyses to assess the associations of genetically determined liver fat, visceral adipose tissue (VAT), and body mass index (BMI) with the risk of PLC. The summary statistics of exposures were obtained from two genome-wide association studies (GWASs) based on the UK Biobank (UKB) imaging cohort and the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. GWAS summary statistics for PLC were obtained from FinnGen consortium R7 release data, including 304 PLC cases and 218 488 controls. Inverse-variance weighted (IVW) was used as the primary analysis, and a series of sensitivity analyses were performed to further verify the robustness of these findings. IVW analysis highlighted a significant association of genetically determined liver fat (OR per SD increase: 7.14; 95% CI: 5.10-9.99; P = 2.35E-30) and VAT (OR per SD increase: 5.70; 95% CI: 1.32-24.72; P = .020) with PLC but not of BMI with PLC. The findings were further confirmed by a series of MR methods. No evidence of horizontal pleiotropy between these associations existed. Our study suggested that genetically determined liver fat and VAT rather than BMI were associated with an increased risk of PLC, which suggested that visceral fat distribution is more predictive of the clinical risk of PLC than common in vitro measures.

Prognostic value of the Naples prognostic score in patients with intrahepatic cholangiocarcinoma after hepatectomy.

BACKGROUND: The Naples Prognostic Score (NPS), integrating inflammatory and nutritional biomarkers, has been reported to be associated with the prognosis of various malignancies, but there is no report on intrahepatic cholangiocarcinoma (ICC). This study aimed to explore the prognostic value of NPS in patients with ICC. METHODS: Patients with ICC after hepatectomy were collected, and divided into three groups. The prognosis factors were determined by Cox regression analysis. Predictive efficacy was evaluated by the time-dependent receiver operating characteristic (ROC) curves. RESULTS: A total of 174 patients were included (Group 1: 33 (19.0%) patients; Group 2: 83 (47.7%) patients; and Group 3: 58 (33.3%) patients). The baseline characteristics showed the higher the NPS, the higher the proportion of patients with cirrhosis and Child-Pugh B, and more advanced tumors. The Kaplan-Meier curves reflect higher NPS were associated with poor survival. Multivariable analysis showed NPS was an independent risk factor of overall survival (NPS group 2 vs. 1: HR = 1.671, 95% CI: 1.022-3.027, p = 0.009; NPS group 3 vs. 1: HR = 2.208, 95% CI: 1.259-4.780, p = 0.007) and recurrence-free survival (NPS group 2 vs. 1: HR = 1.506, 95% CI: 1.184-3.498, p = 0.010; NPS group 3 vs. 1: HR = 2.141, 95% CI: 2.519-4.087, P = 0.001). The time ROC indicated NPS was superior to other models in predicting prognosis. CONCLUSIONS: NPS is a simple and effective tool for predicting the long-term survival of patients with ICC after hepatectomy. Patients with high NPS require close follow-up, and improving NPS may prolong the survival time.

Prioritizing Organic Pollutants for Shale Gas Exploitation: Life Cycle Environmental Risk Assessments in China and the US.

Environmental impacts associated with shale gas exploitation have been historically underestimated due to neglecting to account for the production or the release of end-of-pipe organic pollutants. Here, we assessed the environmental impacts of shale gas production in China and the United States using life cycle assessment. Through data mining, we compiled literature information on organic pollutants in flowback and produced water (FPW), followed by assessments using USEtox to evaluate end-of-pipe risks. Results were incorporated to reveal the life cycle risks associated with shale gas exploitation in both countries. China exhibited higher environmental impacts than the US during the production phase. Substantially different types of organic compounds were observed in the FPW between two countries. Human carcinogenic and ecological toxicity attributed to organics in FPW was 3 orders of magnitude higher than that during the production phase in the US. Conversely, in China, end-of-pipe organics accounted for approximately 52%, 1%, and 47% of the overall human carcinogenic, noncarcinogenic, and ecological impacts, respectively. This may be partially limited by the quantitative data available. While uncertainties exist associated with data availability, our study highlights the significance of integrating impacts from shale gas production to end-of-pipe pollution for comprehensive environmental risk assessments.

Deep Learning Bridged Bioactivity, Structure, and GC-HRMS-Readable Evidence to Decipher Nontarget Toxicants in Sediments.

Identifying causative toxicants in mixtures is critical, but this task is challenging when mixtures contain multiple chemical classes. Effect-based methods are used to complement chemical analyses to identify toxicants, yet conventional bioassays typically rely on an apical and/or single endpoint, providing limited diagnostic potential to guide chemical prioritization. We proposed an event-driven taxonomy framework for mixture risk assessment that relied on high-throughput screening bioassays and toxicant identification integrated by deep learning. In this work, the framework was evaluated using chemical mixtures in sediments eliciting aryl-hydrocarbon receptor activation and oxidative stress response. Mixture prediction using target analysis explained <10% of observed sediment bioactivity. To identify additional contaminants, two deep learning models were developed to predict fingerprints of a pool of bioactive substances (event driver fingerprint, EDFP) and convert these candidates to MS-readable information (event driver ion, EDION) for nontarget analysis. Two libraries with 121 and 118 fingerprints were established, and 247 bioactive compounds were identified at confidence level 2 or 3 in sediment extract using GC-qToF-MS. Among them, 12 toxicants were analytically confirmed using reference standards. Collectively, we present a "bioactivity-signature-toxicant" strategy to deconvolute mixtures and to connect patchy data sets and guide nontarget analysis for diverse chemicals that elicit the same bioactivity.

CYP1B1-AS1 Delays the Malignant Progression of Colorectal Cancer by Binding with NOP58.

BACKGROUND: Colorectal cancer (CRC) is a prevalent type of gastrointestinal cancer, and its poor prognosis is mainly attributed to the occurrence of invasion and metastasis. CYP1B1-AS1, as non-coding RNA, plays an important role in tumorigenesis and progression. However, the mechanism by which CYP1B1-AS1 acts in CRC is not yet understood. AIMS: The objective of this study was to investigate how CYP1B1-AS1 contributes to the development of CRC, and provide a base for CRC diagnosis and treatment. METHODS: RT-qPCR was used to detect the expression level of CYP1B1-AS1 in CRC and adjacent tissues. CCK-8, Edu, scratch healing, and transwell experiments were used to detect the changes of proliferation, migration, and invasion ability of CRC cells after overexpression or knockdown of CYP1B1-AS1 respectively. The RNA binding protein NOP58 combined with CYP1B1-AS1 was verified by RIP and RNA Pull-down experiments. Functional recovery experiments validated the interaction between CYP1B1-AS1 and NOP58 in CRC cells. The changes of EMT-related proteins were detected by Western blot, and the half-life of transcription factor SNAIL mRNA were detected by RT-qPCR after overexpression or knockdown of NOP58. RESULTS: CYP1B1-AS1 was found to be significantly downregulated in CRC compared to adjacent noncancerous tissues. Experiments conducted in vitro and in vivo confirmed that upregulation of CYP1B1-AS1 significantly inhibited the proliferation, migration, and invasion of CRC cells. In addition, CYP1B1-AS1 can directly bind to NOP58 and negatively regulate NOP58. The effect of overexpression CYP1B1-AS1 was reversed by NOP58 overexpression. NOP58 regulates the EMT process of CRC cells by affecting the stability of EMT-related transcription factor SNAIL mRNA, and then affects the progress of CRC. CONCLUSION: This research proves that CYP1B1-AS1 can inhibit the occurrence of EMT in CRC by binding with NOP58, thus delaying the progress of CRC. This finding indicates that CYP1B1-AS1 may be a novel biomarker to improve the diagnosis and treatment of CRC.

Spatial profiles of the bacterial microbiota throughout the gastrointestinal tract of dairy goats.

The gastrointestinal tract (GIT) is stationed by a dynamic and complex microbial community with functions in digestion, metabolism, immunomodulation, and reproduction. However, there is relatively little research on the composition and function of microorganisms in different GIT segments in dairy goats. Herein, 80 chyme samples were taken from ten GIT sites of eight Xinong Saanen dairy goats and then analyzed and identified the microbial composition via 16S rRNA V1-V9 amplicon sequencing. A total of 6669 different operational taxonomic units (OTUs) were clustered, and 187 OTUs were shared by ten GIT segments. We observed 264 species belonging to 23 different phyla scattered across ten GITs, with Firmicutes (52.42%) and Bacteroidetes (22.88%) predominating. The results revealed obvious location differences in the composition, diversity, and function of the GIT microbiota. In LEfSe analysis, unidentified_Lachnospiraceae and unidentified_Succinniclassicum were significantly enriched in the four chambers of stomach, with functions in carbohydrate fermentation to compose short-chain fatty acids. Aeriscardovia, Candidatus_Saccharimonas, and Romboutsia were significantly higher in the foregut, playing an important role in synthesizing enzymes, amino acids, and vitamins and immunomodulation. Akkermansia, Bacteroides, and Alistipes were significantly abundant in the hindgut to degrade polysaccharides and oligosaccharides, etc. From rumen to rectum, α-diversity decreased first and then increased, while ß-diversity showed the opposite trend. Metabolism was the major function of the GIT microbiome predicted by PICRUSt2, but with variation in target substrates along the regions. In summary, GIT segments play a decisive role in the composition and functions of microorganisms. KEY POINTS: • The jejunum and ileum were harsh for microorganisms to colonize due to the presence of bile acids, enzymes, faster chyme circulation, etc., exhibiting the lowest α-diversity and the highest ß-diversity. • Variability in microbial profiles between the three foregut segments was greater than four chambers of stomach and hindgut, with a higher abundance of Firmicutes dominating than others. • Dairy goats dominated a higher abundance of Kiritimatiellaeota than cows, which was reported to be associated with fatty acid synthesis.

Precise planning based on 3D-printed dry-laboratory models can reduce perioperative complications of laparoscopic surgery for complex hepatobiliary diseases: a preoperative cohort study.

BACKGROUND & AIMS: Complications after laparoscopic liver resection (LLR) are important factors affecting the prognosis of patients, especially for complex hepatobiliary diseases. The present study aimed to evaluate the value of a three-dimensional (3D) printed dry-laboratory model in the precise planning of LLR for complex hepatobiliary diseases. METHODS: Patients with complex hepatobiliary diseases who underwent LLR were preoperatively enrolled, and divided into two groups according to whether using a 3D-printed dry-laboratory model (3D vs. control group). Clinical variables were assessed and complications were graded by the Clavien-Dindo classification. The Comprehensive Complication Index (CCI) scores were calculated and compared for each patient. Multivariable analysis was performed to determine the risk factors of postoperative complications. RESULTS: Sixty-two patients with complex hepatobiliary diseases underwent the precise planning of LLR. Among them, thirty-one patients acquired the guidance of a 3D-printed dry-laboratory model, and others were only guided by traditional enhanced CT or MRI. The results showed no significant differences between the two groups in baseline characters. However, compared to the control group, the 3D group had a lower incidence of intraoperative blood loss, as well as postoperative 30-day and major complications, especially bile leakage (all P < 0.05). The median score on the CCI was 20.9 (range 8.7-51.8) in the control group and 8.7 (range 8.7-43.4) in the 3D group (mean difference, -12.2, P = 0.004). Multivariable analysis showed the 3D model was an independent protective factor in decreasing postoperative complications. Subgroup analysis also showed that a 3D model could decrease postoperative complications, especially for bile leakage in patients with intrahepatic cholelithiasis. CONCLUSION: The 3D-printed models can help reduce postoperative complications. The 3D-printed models should be recommended for patients with complex hepatobiliary diseases undergoing precise planning LLR.

3D Reverse-Time Migration Imaging for Multiple Cross-Hole Research and Multiple Sensor Settings of Cross-Hole Seismic Exploration.

The two-dimensional (2D) cross-hole seismic computed tomography (CT) imaging acquisition method has the potential to characterize the target zone optimally compared to surface seismic surveys. It has wide applications in oil and gas exploration, engineering geology, etc. Limited to 2D hole velocity profiling, this method cannot acquire three-dimensional (3D) information on lateral geological structures outside the profile. Additionally, the sensor data received by cross-hole seismic exploration constitute responses from geological bodies in 3D space and are potentially affected by objects outside the well profiles, distorting the imaging results and geological interpretation. This paper proposes a 3D cross-hole acoustic wave reverse-time migration imaging method to capture 3D cross-hole geological structures using sensor settings in multi-cross-hole seismic research. Based on the analysis of resulting 3D cross-hole images under varying sensor settings, optimizing the observation system can aid in the cost-efficient obtainment of the 3D underground structure distribution. To verify this method's effectiveness on 3D cross-hole structure imaging, numerical simulations were conducted on four typical geological models regarding layers, local high-velocity zones, large dip angles, and faults. The results verify the model's superiority in providing more reliable and accurate 3D geological information for cross-hole seismic exploration, presenting a theoretical basis for processing and interpreting cross-hole data.

Enantioselective formal total synthesis of dihydrospirotryprostatin B.

Spirotryprostatins are representative members of medicinally interesting bioactive molecules of the spirooxindole natural products. In this communication, we present a novel enantioselective total synthesis of the spirooxindole alkaloid dihydrospirotryprostatin B. The synthesis takes advantage of copper-catalyzed tandem reaction of o-iodoanilide chiral sulfinamide derivatives with alkynone to rapidly construct the key quaternary carbon stereocenter of the natural product dihydrospirotryprostatin B.

Multicenter propensity score-matched analysis to compare perioperative morbidity after laparoscopic or robotic complex hepatectomy for solitary hepatocellular carcinoma.

BACKGROUND: Postoperative complications are vital factors affecting the prognosis of patients with hepatocellular carcinoma (HCC), especially for complex hepatectomy. The present study aimed to compare perioperative complications between laparoscopic and robotic complex hepatectomy (LCH vs. RCH). METHODS: Patients with solitary HCC after complex hepatectomy were collected from a multicenter database. Propensity score-matched (PSM) analysis was adopted to control confounding bias. Multivariable analysis was performed to determine the prognostic factors. RESULTS: 436 patients were included. After PSM, 43 patients were included in both the LCH and RCH groups. The results showed that compared to LCH, RCH had lower rates of blood loss and transfusion, and lower postoperative 30-day and major morbidity, and post-hepatectomy liver failure (PHLF) (all P < 0.05). Additionally, the length of hospital stay was shorter in the RCH group (P = 0.026). Multivariable analysis showed RCH is an independent protective factor for reducing the 30-day morbidity, major morbidity and PHLF. CONCLUSION: RCH has advantages over LCH in the minimally invasive treatment of complex HCC, as it can reduce the incidence of postoperative morbidity. Therefore, RCH should be considered for patients with HCC who require complex hepatectomy.

Semi-Supervised Deep Learning-Based Multi-component Spectral Calibration Modeling for UV-vis and Near-Infrared Spectroscopy without Information Loss.

Spectral analysis is an important method for characterizing and identifying chemical species. However, quantitative spectral analysis of multiple chemical properties in the real world has always been a challenging problem due to the strong correlation, massive noise, and serious information overlapping of the spectral features. Here, we present a new semi-supervised spectral calibration method based on information lossless decoupling of spectral features named NICEM. To realize the separation and extraction of key latent features, the method uses the flow-based model non-linear independent component estimation (NICE) to learn the sample distribution. The spectral data information is transformed into independent latent variables obeying Gaussian distribution by the reversible structure of deep network without information loss, so as to find the essential properties and realize the feature nonlinear decomposition. Moreover, the association between the input latent feature variables and attributes is evaluated by the maximum mutual information coefficient to eliminate the adverse effects of irrelevant information in the latent variable space and mine key information. Since the latent variables are independent in each dimension, the NICEM method is easier to establish an accurate semi-supervised multi-component calibration model even for high overlapping and complex spectral data. The applicability of the proposed spectral modeling method is demonstrated by using three ultraviolet-visible and near-infrared spectral data sets with 15 physical and chemical properties including diesel fuels, corn, and multi-metal ions solution. Results show that the proposed NICEM method has the highest determination coefficient (R2) and significantly improves extrapolation compared with the seven state-of-the-art methods. The proposed method is intuitive because it obviates complex feature engineering and prior knowledge and is a promising spectral calibration tool for quantitative analysis in other spectroscopy applications.

Efficacy of adjuvant TACE on the prognosis of patients with HCC after hepatectomy: a multicenter propensity score matching from China.

BACKGROUND: The survival benefit of adjuvant transarterial chemoembolization (TACE) in patients with hepatectomy for hepatocellular carcinoma (HCC) after hepatectomy remains controversial. We aimed to investigate the survival efficacy of adjuvant TACE after hepatectomy for HCC. METHODS: 1491 patients with HCC who underwent hepatectomy between January 2018 and September 2021 at four medical centers in China were retrospectively analyzed, including 782 patients who received adjuvant TACE and 709 patients who did not receive adjuvant TACE. Propensity score matching (PSM) (1:1) was performed to minimize selection bias, which balanced the clinical characteristics of the two groups. RESULTS: A total of 1254 patients were enrolled after PSM, including 627 patients who received adjuvant TACE and 627 patients who did not receive adjuvant TACE. Patients who received adjuvant TACE had higher disease-free survival (DFS, 1- ,2-, and 3-year: 78%-68%-62% vs. 69%-57%-50%, p < 0.001) and overall survival (OS, 1- ,2-, and 3-year: 96%-88%-80% vs. 90%-77%-66%, p < 0.001) than those who did not receive adjuvant TACE (Median DFS was 39 months). Among the different levels of risk factors affecting prognosis [AFP, Lymphocyte-to-monocyte ratio, Maximum tumor diameter, Number of tumors, Child-Pugh classification, Liver cirrhosis, Vascular invasion (imaging), Microvascular invasion, Satellite nodules, Differentiation, Chinese liver cancer stage II-IIIa], the majority of patients who received adjuvant TACE had higher DFS or OS than those who did not receive adjuvant TACE. More patients who received adjuvant TACE accepted subsequent antitumor therapy such as liver transplantation, re-hepatectomy and local ablation after tumor recurrence, while more patients who did not receive adjuvant TACE accepted subsequent antitumor therapy with TACE after tumor recurrence (All p < 0.05). CONCLUSIONS: Adjuvant TACE may be a potential way to monitor early tumor recurrence and improve postoperative survival in patients with HCC.

Two-Compartmental Toxicokinetic Model Predicts Interspecies Sensitivity Variation of Imidacloprid to Aquatic Invertebrates.

Interspecies sensitivity to the same chemical can be several orders of magnitude different. Quantifying toxicologically internal levels and toxicokinetic (TK) parameters is critical in elucidating the interspecies sensitivity. Herein, a two-compartmental TK model was constructed to characterize the uptake, distribution, and elimination kinetics toward interspecies sensitivity to an insecticide, imidacloprid. Imidacloprid exhibited the highest lethality to the insect Chironomus dilutus, followed by Lumbriculus variegatus, Hyalella azteca, and Daphnia magna. Interspecies sensitivity of imidacloprid to these invertebrates varied by ∼1000 folds based on water concentrations (LC50). Remarkably, the sensitivity variation decreased to ∼50 folds based on the internal residues (LR50), highlighting the critical role of TK in interspecies sensitivity. A one-compartmental TK model failed to simulate the bioaccumulation of imidacloprid in these invertebrates except for D. magna. Instead, a two-compartmental model successfully simulated the slow elimination of imidacloprid in the remaining three species by internally distinguishing the highly dynamic (C1) and toxicologically available (C2) fractions. We further showed that the species sensitivity of the invertebrates to imidacloprid was significantly related to C2, demonstrating that C2 was toxicologically available and responsible for the toxicity of imidacloprid. This mechanistic-based model bridged the internal distribution of organic contaminants in small invertebrates and the associated toxic potency.

Homeobox B9 Promotes Colon Cancer Progression by Targeting SRSF3.

BACKGROUND: Homeobox B9 (HOXB9) is one of the HOX family of transcription factors that are essential for cancer development and embryonic growth. However, the clinical importance and biological involvement of HOXB9 in colon cancer (CC) are not adequately understood. AIMS: To investigate whether HOXB9 participates in the proliferation, invasion, and migration of CC. METHODS: This study investigated the function and clinical significance of HOXB9 mRNA and protein expression in CC. Furthermore, overexpression and knockdown experiments of HOXB9 were developed to explore their effects on CC cell transwell and proliferation. Moreover, a molecular mechanism of HOXB9 regulate serine/arginine-rich splicing factor 3 (SRSF3) was explored. RESULTS: HOXB9 expression was higher in CC cells and tissues at both the mRNA and protein levels. Poor survival in CC patients was significantly connected with high HOXB9 expression, which was also strongly associated with the TNM stage and lymph node metastases. Furthermore, in vitro CC cell proliferation, transwell were markedly aided by HOXB9 overexpression. Contrarily, HOXB9 knockdown had the reverse result and inhibited the formation of xenograft tumors in naked mice. Gene set enrichment analysis (GSEA) revealed a correlation between high HOXB9 expression and spliceosomes. JASPAR and GEPIA2.0, in addition to CHIP and dual-luciferase reporting assays, confirmed that HOXB9 targets the promoter of SRSF3 to enhance its expression. We also found that SRSF3 knockdown eliminated HOXB9 from cell proliferation and transwell. CONCLUSION: We characterized the function and mechanism of HOXB9 in regulating colon cancer growth, suggesting a novel molecular approach for colon cancer-targeted therapy.

Ubiquitin-Like Protein FAT10 Promote Colorectal Cancer Progression by Affecting the Ubiquitination of Capn4.

BACKGROUND: Emerging evidence showed that FAT10 is a vital regulator of tumor occurrence and development. The molecular mechanisms underlying the specific role of FAT10 in colorectal cancer (CRC) are not yet known. AIMS: To investigate whether FAT10 participates in the proliferation, invasion and metastasis of CRC. METHODS: This study investigated the function and clinical significance of FAT10 protein expression in CRC. Furthermore, over-expression and knockdown experiments of FAT10 were developed to explore their effects on CRC cell migration and proliferation. Moreover, a molecular mechanism of FAT10 regulate calpain small subunit 1(Capn4) was explored. RESULTS: In this research, the FAT10 expression level was elevated in CRC tissues compared to corresponding normal tissues. In addition, the elevated FAT10 expression level is significantly linked to advanced clinical stage and poor CRC prognosis. Furthermore, a very high expression of FAT10 was observed in CRC cells, and FAT10 overexpression significantly enhanced the in vivo proliferation, invasion, and metastasis of the cells, whereas knockdown of FAT10 inhibited all these cellular factors in both in vivo and in vitro environments. Moreover, the outcomes of this study suggested that FAT10 enhances colorectal cancer progression through enhancement of Capn4 expression, leading to the progression of various human tumors, as reported by previous research. The mechanism via which FAT10 promotes CRC cells proliferation, invasion, and metastasis involves modification of the ubiquitination and degradation processes of Capn4. CONCLUSION: FAT10 is a vital regulator of the tumorigenesis and advancement of CRC, thus serving as a promising pharmaceutical target for treating CRC patients.

The dopamine receptor antagonist trifluoperazine prevents phenotype conversion and improves survival in mouse models of glioblastoma.

Glioblastoma (GBM) is the deadliest adult brain cancer, and all patients ultimately succumb to the disease. Radiation therapy (RT) provides survival benefit of 6 mo over surgery alone, but these results have not improved in decades. We report that radiation induces a glioma-initiating cell phenotype, and we have identified trifluoperazine (TFP) as a compound that interferes with this phenotype conversion. TFP causes loss of radiation-induced Nanog mRNA expression, and activation of GSK3 with consecutive posttranslational reduction in p-Akt, Sox2, and ß-catenin protein levels. TFP did not alter the intrinsic radiation sensitivity of glioma-initiating cells (GICs). Continuous treatment with TFP and a single dose of radiation reduced the number of GICs in vivo and prolonged survival in syngeneic and patient-derived orthotopic xenograft (PDOX) mouse models of GBM. Our findings suggest that the combination of a dopamine receptor antagonist with radiation enhances the efficacy of RT in GBM by preventing radiation-induced phenotype conversion of radiosensitive non-GICs into treatment-resistant, induced GICs (iGICs).

Risk factors analysis of surgical site infections in postoperative colorectal cancer: a nine-year retrospective study.

BACKGROUND: Colorectal cancer (CRC) patients undergoing surgery are at a high risk of developing surgical site infections (SSIs), which contribute to increased morbidity, prolonged hospitalization, and escalated healthcare costs. Understanding the incidence, risk factors, and impact of SSIs is crucial for effective preventive strategies and improved patient outcomes. METHODS: This retrospective study analyzed data from 431 CRC patients who underwent surgery at Huangshan Shoukang Hospital between 2014 and 2022. The clinical characteristics and demographic information were collected. The incidence and impact of SSIs were evaluated, and independent risk factors associated with SSIs were identified using multivariable logistic regresison. A nomogram plot was constructed to predict the likelihood of SSIs occurrence. RESULTS: The overall incidence rate of SSIs was 7.65% (33/431). Patients with SSIs had significantly longer hospital stays and higher healthcare costs. Risk factors for SSIs included elevated Body Mass Index (BMI) levels (odds ratio, 1.12; 95% CI, 1.02-1.23; P = 0.017), the presence of diabetes (odds ratio, 3.88; 95% CI, 1.42 - 9.48; P = 0.01), as well as specific surgical factors such as open surgical procedures (odds ratio, 2.39; 95% CI [1.09; 5.02]; P = 0.031), longer surgical duration (odds ratio, 1.36; 95% CI [1.01; 1.84]; P = 0.046), and the presence of a colostomy/ileostomy (odds ratio, 3.17; 95% CI [1.53; 6.62]; P = 0.002). Utilizing multivariable regression analysis, which encompassed factors such as open surgical procedures, the presence of diabetes and colostomy/ileostom, the nomogram plot functions as a visual aid in estimating the individual risk of SSIs for patients. CONCLUSIONS: Risk factors for SSIs included higher BMI levels, the presence of diabetes, open surgical procedures, longer surgical duration, and the presence of colostomy/ileostomy. The nomogram plot serves as a valuable tool for risk assessment and clinical decision-making.

A Model Transfer Method among Spectrometers Based on Improved Deep Autoencoder for Concentration Determination of Heavy Metal Ions by UV-Vis Spectra.

Ultraviolet Visible (UV-Vis) spectroscopy detection technology has been widely used in quantitative analysis for its advantages of rapid and non-destructive determination. However, the difference of optical hardware severely restricts the development of spectral technology. Model transfer is one of the effective methods to establish models on different instruments. Due to the high dimension and nonlinearity of spectral data, the existing methods cannot effectively extract the hidden differences in spectra of different spectrometers. Thus, based on the necessity of spectral calibration model transfer between the traditional large spectrometer and the micro-spectrometer, a novel model transfer method based on improved deep autoencoder is proposed to realize spectral reconstruction between different spectrometers. Firstly, two autoencoders are used to train the spectral data of the master and slave instrument, respectively. Then, the hidden variable constraint is added to enhance the feature representation of the autoencoder, which makes the two hidden variables equal. Combined with a Bayesian optimization algorithm for the objective function, the transfer accuracy coefficient is proposed to characterize the model transfer performance. The experimental results show that after model transfer, the spectrum of the slave spectrometer is basically coincident with the master spectrometer and the wavelength shift is eliminated. Compared with the two commonly used direct standardization (DS) and piecewise direct standardization (PDS) algorithms, the average transfer accuracy coefficient of the proposed method is improved by 45.11% and 22.38%, respectively, when there are nonlinear differences between different spectrometers.