Development and validation of prognostic and diagnostic model for pancreatic ductal adenocarcinoma based on scRNA-seq and bulk-seq datasets.

The 5-year overall survival (OS) of pancreatic ductal adenocarcinoma (PDAC) is only 10%, partly owing to the lack of reliable diagnostic and prognostic biomarkers. The raw gene-cell matrix for single-cell RNA-seq (scRNA-seq) analysis was downloaded from the GSA database. We drew cell atlas for PDAC and normal pancreatic tissues. The inferCNV analysis was used to distinguish tumor cells from normal ductal cells. We identified differential expression genes (DEGs) by comparing tumor cells and normal ductal cells. The common DEGs were used to conduct prognostic and diagnostic model using univariate and multivariate Cox or logistic regression analysis. Four genes, MET, KLK10, PSMB9 and ITGB6, were utilized to create risk score formula to predict OS and to establish diagnostic model for PDAC. Finally, we drew an easy-to-use nomogram to predict 2-year and 3-year OSs. In conclusion, we developed and validated the prognostic and diagnostic model for PDAC based on scRNA-seq and bulk-seq datasets.

Control of Compensation Temperature in CoGd Films through Hydrogen and Oxygen Migration under Gate Voltage.

Electrical control of magnetic properties is crucial for low-energy memory and logic spintronic devices. We find that the magnetic properties of ferrimagnetic CoGd can be altered through ionic liquid gating. Gate voltages manipulate the opposite magnetic moments in Co and Gd sublattices and induce a giant magnetic compensation temperature change of more than 200 K in Pt/CoGd/Pt heterostructures. The electrically controlled dominant magnetic sublattice allows voltage-induced magnetization switching. Both experiments and theoretical calculations demonstrate that the significant modulations of compensation temperature are relevant to the reduced Gd moments due to the presence of hydrogen ions at positive voltages as well as the enhanced Co moments and reduced Gd moments due to the injection of oxygen ions at negative voltages. These findings expand the possibilities for all-electric and reversible magnetization control in the field of spintronics.

Demodulation of the overlapping reflection spectrum of serial FBGs based on a weighted differential evolution algorithm.

This study addresses the wavelength demodulation problem of the overlapping reflection spectrum of serial fiber Bragg gratings (FBGs) with nearly-identical wavelength. Specifically, a novel demodulation model for the overlapping reflection spectrum was presented based on spectrum similarity, and this model encodes FBGs through reflectivity. Subsequently, a weighted differential evolution algorithm was employed to calculate the FBG wavelengths. And the factors affecting the demodulation accuracy of the proposed method were simulated and analyzed. Finally, the proposed method was applied to demodulate the overlapping reflection spectra of serial FBGs. The experiment results indicate that the proposed method is suitable for completely overlapping, partially overlapping, and non-overlapping reflection spectra of serial FBGs. The wavelength demodulation accuracy demonstrated here in fully overlapping situations for two, three, and four FBGs was only 4.5, 14.9, and 24.6 pm, respectively.

Review: Acetylation mechanisms and targeted therapies in cardiac fibrosis.

Cardiac fibrosis is a common pathophysiological remodeling process that occurs in a variety of cardiovascular diseases and greatly influences heart structure and function, progressively leading to the development of heart failure. However, to date, few effective therapies for cardiac fibrosis exist. Abnormal proliferation, differentiation, and migration of cardiac fibroblasts are responsible for the excessive deposition of extracellular matrix in the myocardium. Acetylation, a widespread and reversible protein post-translational modification, plays an important role in the development of cardiac fibrosis by adding acetyl groups to lysine residues. Many acetyltransferases and deacetylases regulate the dynamic alterations of acetylation in cardiac fibrosis, regulating a range of pathogenic conditions including oxidative stress, mitochondrial dysfunction, and energy metabolism disturbance. In this review, we demonstrate the critical roles that acetylation modifications caused by different types of pathological injury play in cardiac fibrosis. Furthermore, we propose therapeutic acetylation-targeting strategies for the prevention and treatment of patients with cardiac fibrosis.

Electrical Control of Magnetism through Proton Migration in Fe3O4/Graphene Heterostructure.

Ion migration has direct and crucial bearing on the crystal lattice field, electron filling, orbital occupation and spin polarization, which in turn changes the physical properties. Electric field is an effective way to control ion migration, but it may include simultaneous movement of multiple ions and increase the complexity of the system. Therefore, controllable and selective single ion migration with an unambiguous mechanism is highly desired. Here, the magnetic moments of Fe3O4 could be reversibly controlled by ionic liquid gating on the basis of migration of pure protons. A bilayer graphene could serve as an ion sieve, allowing only protons rather than oxygen ions or hydroxyl groups to participate in the gating process, thus guaranteeing the reversibility of magnetic property changes. This work is expected to supply an ideal arena for electrically sketching the functionalities of solid state materials based on the selective ion migration.

ECTransNet: An Automatic Polyp Segmentation Network Based on Multi-scale Edge Complementary.

Colonoscopy is acknowledged as the foremost technique for detecting polyps and facilitating early screening and prevention of colorectal cancer. In clinical settings, the segmentation of polyps from colonoscopy images holds paramount importance as it furnishes critical diagnostic and surgical information. Nevertheless, the precise segmentation of colon polyp images is still a challenging task owing to the varied sizes and morphological features of colon polyps and the indistinct boundary between polyps and mucosa. In this study, we present a novel network architecture named ECTransNet to address the challenges in polyp segmentation. Specifically, we propose an edge complementary module that effectively fuses the differences between features with multiple resolutions. This enables the network to exchange features across different levels and results in a substantial improvement in the edge fineness of the polyp segmentation. Additionally, we utilize a feature aggregation decoder that leverages residual blocks to adaptively fuse high-order to low-order features. This strategy restores local edges in low-order features while preserving the spatial information of targets in high-order features, ultimately enhancing the segmentation accuracy. According to extensive experiments conducted on ECTransNet, the results demonstrate that this method outperforms most state-of-the-art approaches on five publicly available datasets. Specifically, our method achieved mDice scores of 0.901 and 0.923 on the Kvasir-SEG and CVC-ClinicDB datasets, respectively. On the Endoscene, CVC-ColonDB, and ETIS datasets, we obtained mDice scores of 0.907, 0.766, and 0.728, respectively.

Predictive Model of Early Death of Resectable Pancreatic Ductal Adenocarcinoma After Curative Resection: A SEER-Based Study.

OBJECTIVE: This study aims to determine the factors that predict early death and establish a predictive model for early death by analyzing clinical characteristics of patients with resectable pancreatic ductal adenocarcinoma (R-PDAC) who die early after radical surgery. MATERIALS AND METHODS: This was a retrospective study of patients who underwent radical surgical resection for R-PDAC in the Surveillance, Epidemiology, and End Results (SEER) database. Patients with overall survival ≤ 12 months were assigned as early death group and above 1 year as the late death group. Univariate and multivariate logistic regression was conducted to identify factors significantly associated with early death. An early death predictive model was constructed based on the identified independent risk factors. RESULTS: A total of 9695 patients were analyzed, and the total incidence of early death was 30.72%. Multivariable analysis showed that factors significantly associated with early death included age at diagnosis, race, marital status, tumor location, tumor size, tumor grade, number of positive lymph nodes, number of examined lymph nodes, positive lymph node ratio, chemotherapy, and radiotherapy. The predictive model showed good discrimination with a C-index of 0.722 (95% confidence interval: 0.711-0.733) and convincing calibration. CONCLUSIONS: We developed a predictive model that may be easily applied to patients with R-PDAC after radical resection to predict the chance of death within 1 year. For patients with high risk of early death, neoadjuvant therapy should be considered. Even after radical resection, more aggressive adjuvant chemotherapy (with or without combined radiotherapy) must be used to minimize the chance of early death.

Application of logistic differential equation models for early warning of infectious diseases in Jilin Province.

BACKGROUND: There is still a relatively serious disease burden of infectious diseases and the warning time for different infectious diseases before implementation of interventions is important. The logistic differential equation models can be used for predicting early warning of infectious diseases. The aim of this study is to compare the disease fitting effects of the logistic differential equation (LDE) model and the generalized logistic differential equation (GLDE) model for the first time using data on multiple infectious diseases in Jilin Province and to calculate the early warning signals for different types of infectious diseases using these two models in Jilin Province to solve the disease early warning schedule for Jilin Province throughout the year. METHODS: Collecting the incidence of 22 infectious diseases in Jilin Province, China. The LDE and GLDE models were used to calculate the recommended warning week (RWW), the epidemic acceleration week (EAW) and warning removed week (WRW) for acute infectious diseases with seasonality, respectively. RESULTS: Five diseases were selected for analysis based on screening principles: hemorrhagic fever with renal syndrome (HFRS), shigellosis, mumps, Hand, foot and mouth disease (HFMD), and scarlet fever. The GLDE model fitted the above diseases better (0.80 ≤ R2 ≤ 0.94, P <  0. 005) than the LDE model. The estimated warning durations (per year) of the LDE model for the above diseases were: weeks 12-23 and 40-50; weeks 20-36; weeks 15-24 and 43-52; weeks 26-34; and weeks 16-25 and 41-50. While the durations of early warning (per year) estimated by the GLDE model were: weeks 7-24 and 36-51; weeks 13-37; weeks 11-26 and 39-54; weeks 23-35; and weeks 12-26 and 40-50. CONCLUSIONS: Compared to the LDE model, the GLDE model provides a better fit to the actual disease incidence data. The RWW appeared to be earlier when estimated with the GLDE model than the LDE model. In addition, the WRW estimated with the GLDE model were more lagged and had a longer warning time.

CsPAO2 Improves Salt Tolerance of Cucumber through the Interaction with CsPSA3 by Affecting Photosynthesis and Polyamine Conversion.

Polyamine oxidases (PAOs) are key enzymes in polyamine metabolism and are related to the tolerance of plants to abiotic stresses. In this study, overexpression of cucumber (Cucumis sativus L.) PAO2 (CsPAO2) in Arabidopsis resulted in increased activity of the antioxidant enzyme and accelerated conversion from Put to Spd and Spm, while malondialdehyde content (MDA) and electrolyte leakage (EL) was decreased when compared with wild type, leading to enhanced plant growth under salt stress. Photosystem Ⅰ assembly 3 in cucumber (CsPSA3) was revealed as an interacting protein of CsPAO2 by screening yeast two-hybrid library combined with in vitro and in vivo methods. Then, CsPAO2 and CsPSA3 were silenced in cucumber via virus-mediated gene silencing (VIGS) with pV190 as the empty vector. Under salt stress, net photosynthetic rate (Pn) and transpiration rate (Tr) of CsPAO2-silencing plants were lower than pV190-silencing plants, and EL in root was higher than pV190-silencing plants, indicating that CsPAO2-silencing plants suffered more serious salt stress damage. However, photosynthetic parameters of CsPSA3-silencing plants were all higher than those of CsPAO2 and pV190-silencing plants, thereby enhancing the photosynthesis process. Moreover, CsPSA3 silencing reduced the EL in both leaves and roots when compared with CsPAO2-silencing plants, but the EL only in leaves was significantly lower than the other two gene-silencing plants, and conversion from Put to Spd and Spm in leaf was also promoted, suggesting that CsPSA3 interacts with CsPAO2 in leaves to participate in the regulation of salt tolerance through photosynthesis and polyamine conversion.

Auxin is involved in arbuscular mycorrhizal fungi-promoted tomato growth and NADP-malic enzymes expression in continuous cropping substrates.

BACKGROUND: Despite significant limitations of growth medium reuse, a large amount of organic substrate is reused in soilless cultivation of horticultural crops in China. Arbuscular mycorrhizal fungi (AMF) can promote nutrient absorption and improve plant tolerance to biotic and abiotic stresses. However, the mechanisms governing the effects of AMF on crop growth in organic continuous cropping substrates have not been elucidated. RESULTS: In this study, we showed that the inoculation of AMF in continuous cropping substrates promoted growth and root development, and increased the root and NADP-malic enzyme (NADP-ME) activity of tomato seedlings. Root transcriptome analysis demonstrated that the plant hormone signal transduction pathway was highly enriched, and 109 genes that positively correlated with the AMF-inoculated plant phenotype were obtained by gene set enrichment analysis (GSEA), which identified 9 genes related to indole acetic acid (IAA). Importantly, the levels of endogenous IAA in tomato seedlings significantly increased after AMF inoculation. Furthermore, the application of AMF significantly increased the expression levels of NADP-ME1 and NADP-ME2, as well as the activity of NADP-ME, and enhanced the root activity of tomato seedlings in comparison to that observed without inoculation of AMF. However, these effects were blocked in plants treated with 2,3,5-triiodobenzoic acid (TIBA), a polar transport inhibitor of IAA. CONCLUSIONS: These results suggest that IAA mediates the AMF-promoted tomato growth and expression of NADP-MEs in continuous cropping substrates. The study provides convincing evidence for the reuse of continuous cropping substrates by adding AMF as an amendment.

Estimating the transmissibility of hepatitis C: A modelling study in Yichang City, China.

Yichang is a city in central China in the Hubei Province. This study aimed to estimate the dynamics of the transmissibility of hepatitis C using a mathematical model and predict the transmissibility of hepatitis C in 2030. Data of hepatitis C cases from 13 counties or districts (cities) in Yichang from 2008 to 2016 were collected. A susceptible-infectious-chronic-recovered (SICR) model was developed to fit the data. The transmissibility of hepatitis C at the counties or districts was calculated based on new infections (including infected or chronically infected cases) reported monthly in the city caused by one infectious individual (MNI). The trend of the MNI was fitted and predicted using 11 models, with the coefficient of determination (R2 ) was being used to test the goodness of fit of these models. A total of 3065 cases of hepatitis C were reported in Yichang from 2008 to 2016. The median MNI of Yichang was 0.0768. According to the fitting results and analysis, the trend of transmissibility of hepatitis C in Yichang City conforms with the logarithmic (R2  = 0.918, p < 0.001):MNI = 0.265-0.108 log(t) and exponential (R2  = 0.939, p < 0.001): MNI = 0.344e(-0.278t) models. Hence, the transmission of hepatitis C virus at the county level has a downward trend. In conclusion, the transmissibility of hepatitis C in Yichang has a downward trend. With the current preventive and control measures in place, the spread of hepatitis C can be controlled.

A modified alternative fistula risk score (a-FRS) obtained from the computed tomography enhancement pattern of the pancreatic parenchyma predicts pancreatic fistula after pancreatoduodenectomy.

BACKGROUND: Alternative fistula risk score (a-FRS) is useful to predict clinically relevant postoperative pancreatic fistula (CR-POPF) after pancreatoduodenectomy (PD). METHODS: Clinical data from 239 patients undergoing PD were collected. The CT value of the pancreatic parenchyma was measured in the nonenhanced (N), arterial (A), portal venous (P), and late (L) phases. The A/N, A/P, P/L and A/L ratios were calculated and their correlation with CR-POPF were analyzed. By replacing pancreatic texture with the best CT attenuation ratio, a modified a-FRS was developed. RESULTS: Forty-seven patients developed CR-POPF. The A/P ratio (P < 0.001), P/L ratio (P = 0.002) and A/L ratio (P < 0.001) were significantly higher in the CR-POPF group. The A/L ratio performed best in predicting CR-POPF (AUC: 0.803) and the cut-off value is 1.36. A/L ratio >1.36 (P < 0.001), body mass index (P = 0.005) and duct diameter (P = 0.037) were independently associated with CR-POPF. By replacing soft texture with an A/L ratio >1.36, a modified a-FRS was developed and performed better than the a-FRS (AUC: 0.823 vs 0.748, P = 0.006) in predicting CR-POPF. CONCLUSIONS: The modified a-FRS is an objective and preoperative model for predicting the occurrence of CR-POPF after PD.

Validation and modification of the AJCC 8th TNM staging system for pancreatic ductal adenocarcinoma in a Chinese cohort: A nationwide pancreas data center analysis.

OBJECTIVE: To validate the 8th edition of the American Joint Committee on Cancer (AJCC) staging system for pancreatic ductal adenocarcinoma (PDAC) in a Chinese cohort of radically resected patients and to develop a refined staging system for PDAC. METHODS: Data were collected from the China Pancreas Data Center (CPDC) for patients with resected PDAC in 2016 and 2017, and cancer-specific survival (CSS) was evaluated using the Kaplan-Meier method and log-rank test. Univariate and multivariate analyses based on Cox regression were performed to identify prognostic factors. The recursive partitioning analysis (RPA), Kaplan-Meier method, and log-rank test were performed on the training dataset to generate a proposed modification for the 8th TNM staging system utilizing the preoperative carbohydrate antigen (CA)19-9 level. Validation was performed for both staging systems in the validation cohort. RESULTS: A total of 1,676 PDAC patients were retrieved, and the median CSS was significantly different between the 8th TNM groupings, with no significant difference in survival between stage IB and IIA. The analysis of T and N stages demonstrated a better prognostic value in the N category. Multivariate analysis showed that the preoperative serum CA19-9 level was the strongest prognostic indicator among all the independent risk factors. All patients with CA19-9 >500 U/mL had similar survival, and we proposed a new staging system by combining IB and IIA and stratifying all patients with high CA19-9 into stage III. The modified staging system had a better performance for predicting CSS than the 8th AJCC staging scheme. CONCLUSIONS: The 8th AJCC staging system for PDAC is suitable for a Chinese cohort of resected patients, and the N category has a better prognostic value than the T category. Our modified staging system has superior accuracy in predicting survival than the 8th AJCC TNM staging system.

Copper-Promoted Double Oxidative C-H Amination Cascade for the Synthesis of Imidazo[1,5-a]quinolines.

A copper-promoted cascade reaction of 2-methylazaarenes and benzylamines has been developed via sequential double oxidative C(sp(3))-H aminations. This protocol provides straightforward access to imidazo[1,5-a]quinoline derivatives without employing prefunctionalized substrates.

Advances in TRPV6 inhibitors for tumors by targeted therapies: Macromolecular proteins, synthetic small molecule compounds, and natural compounds.

TRPV6, a Ca2+-selective member of the transient receptor potential vanilloid (TRPV) family, plays a key role in extracellular calcium transport, calcium ion reuptake, and maintenance of a local low calcium environment. An increasing number of studies have shown that TRPV6 is involved in the regulation of various diseases. Notably, overexpression of TRPV6 is closely related to the occurrence of various cancers. Research confirmed that knocking down TRPV6 could effectively reduce the proliferation and invasiveness of tumors by mainly mediating the calcium signaling pathway. Hence, TRPV6 has become a promising new drug target for numerous tumor treatments. However, the development of TRPV6 inhibitors is still in the early stage, and the existing TRPV6 inhibitors have poor selectivity and off-target effects. In this review, we focus on summarizing and describing the structure characters, and mechanisms of existing TRPV6 inhibitors to provide new ideas and directions for the development of novel TRPV6 inhibitors.

Hypoxia-induced epigenetic regulation of miR-485-3p promotes stemness and chemoresistance in pancreatic ductal adenocarcinoma via SLC7A11-mediated ferroptosis.

The mechanism of hypoxia in chemoresistance of pancreatic ductal adenocarcinoma (PDAC) remains elusive. In this study, we revealed the essential role of miR-485-3p in PDAC, particularly its impact on cancer stemness and gemcitabine resistance under hypoxic conditions. We found substantial downregulation of miR-485-3p in PDAC tissues, with lower expression correlating to poor patient outcomes. Mechanistically, miR-485-3p influenced stemness characteristics, as evidenced by reduced tumor-sphere formation and increased sensitivity to gemcitabine upon overexpression. Moreover, we identified SOX9 and SLC7A11 as two targets of miR-485-3p, which play a vital role in stemness and ferroptosis. Under the hypoxic condition, DNMT3B expression was upregulated, leading to hypermethylation of the miR-485-3p promoter region. The reduced miR-485-3p expression promoted stemness and chemoresistance of PDAC. In conclusion, our findings elucidate the intricate interplay of hypoxia, epigenetic modifications, and ferroptosis in PDAC and shed light on potential avenues for targeted interventions that modulate cancer stemness and chemosensitivity, offering prospects for improved therapeutic strategies for PDAC.

TREATMENT OF COMATOSE SURVIVORS OF IN-HOSPITAL CARDIAC ARREST WITH EXTENDED ENDOVASCULAR COOLING METHOD FOR 72 H: A PROPENSITY SCORE-MATCHED ANALYSIS.

ABSTRACT: Aims: Targeted temperature management is recommended for at least 24 h in comatose survivors of in-hospital cardiac arrest (IHCA) after the return of spontaneous circulation; however, whether an extension for 72 h leads to better neurological outcomes is uncertain. Methods: We included data from the Qilu Hospital of Shandong University between July 20, 2019, and June 30, 2022. Unconscious patients who had return of spontaneous circulation lasting >20 consecutive min and received endovascular cooling (72 h) or normothermia treatment were compared in terms of survival-to-discharge and favorable neurological survival. Propensity score matching was used to formulate balanced 1:3 matched patients. Results: In total, 2,084 patients were included. Sixteen patients received extended endovascular cooling and 48 matched controls received normothermia therapy. Compared with the normothermia group, patients who received prolonged endovascular cooling had a higher survival-to-discharge rate. However, good neurological outcomes did not differ significantly. Before matching, Cox regression analysis, using mortality as the event, showed that extended endovascular cooling independently affected the survival of IHCA patients. Conclusions: Among comatose patients who had been resuscitated from IHCA, the use of endovascular cooling for 72 h might confer a benefit on survival-to-discharge.

TDCAU-Net: retinal vessel segmentation using transformer dilated convolutional attention-based U-Net method.

Retinal vessel segmentation plays a vital role in the medical field, facilitating the identification of numerous chronic conditions based on retinal vessel images. These conditions include diabetic retinopathy, hypertensive retinopathy, glaucoma, and others. Although the U-Net model has shown promising results in retinal vessel segmentation, it tends to struggle with fine branching and dense vessel segmentation. To further enhance the precision of retinal vessel segmentation, we propose a novel approach called transformer dilated convolution attention U-Net (TDCAU-Net), which builds upon the U-Net architecture with improved Transformer-based dilated convolution attention mechanisms. The proposed model retains the three-layer architecture of the U-Net network. The Transformer component enables the learning of contextual information for each pixel in the image, while the dilated convolution attention prevents information loss. The algorithm efficiently addresses several challenges to optimize blood vessel detection. The process starts with five-step preprocessing of the images, followed by chunking them into segments. Subsequently, the retinal images are fed into the modified U-Net network introduced in this paper for segmentation. The study employs eye fundus images from the DRIVE and CHASEDB1 databases for both training and testing purposes. Evaluation metrics are utilized to compare the algorithm's results with state-of-the-art methods. The experimental analysis on both databases demonstrates that the algorithm achieves high values of sensitivity, specificity, accuracy, and AUC. Specifically, for the first database, the achieved values are 0.8187, 0.9756, 0.9556, and 0.9795, respectively. For the second database, the corresponding values are 0.8243, 0.9836, 0.9738, and 0.9878, respectively. These results demonstrate that the proposed approach outperforms state-of-the-art methods, achieving higher performance on both datasets. The TDCAU-Net model presented in this study exhibits substantial capabilities in accurately segmenting fine branching and dense vessels. The segmentation performance of the network surpasses that of the U-Net algorithm and several mainstream methods.

MCSF-Net: a multi-scale channel spatial fusion network for real-time polyp segmentation.

Colorectal cancer is a globally prevalent cancer type that necessitates prompt screening. Colonoscopy is the established diagnostic technique for identifying colorectal polyps. However, missed polyp rates remain a concern. Early detection of polyps, while still precancerous, is vital for minimizing cancer-related mortality and economic impact. In the clinical setting, precise segmentation of polyps from colonoscopy images can provide valuable diagnostic and surgical information. Recent advances in computer-aided diagnostic systems, specifically those based on deep learning techniques, have shown promise in improving the detection rates of missed polyps, and thereby assisting gastroenterologists in improving polyp identification. In the present investigation, we introduce MCSF-Net, a real-time automatic segmentation framework that utilizes a multi-scale channel space fusion network. The proposed architecture leverages a multi-scale fusion module in conjunction with spatial and channel attention mechanisms to effectively amalgamate high-dimensional multi-scale features. Additionally, a feature complementation module is employed to extract boundary cues from low-dimensional features, facilitating enhanced representation of low-level features while keeping computational complexity to a minimum. Furthermore, we incorporate shape blocks to facilitate better model supervision for precise identification of boundary features of polyps. Our extensive evaluation of the proposed MCSF-Net on five publicly available benchmark datasets reveals that it outperforms several existing state-of-the-art approaches with respect to different evaluation metrics. The proposed approach runs at an impressive ∼45 FPS, demonstrating notable advantages in terms of scalability and real-time segmentation.