Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

In analytical techniques such as ion mobility spectrometry(IMS)and mass spectrometry(MS),the ionization efficiency of target analytes is primarily constrained by the type of ionization source and factors such as the species and number density of the reactant ions.Systematic investigation into the reactivity differences of various reactant ions under varying conditions can not only significantly enhance the detection sensitivity of target compound product ions but also provide a theoretical foundation for establishing efficient detection methods based on ion-molecule reaction mechanisms.In this study,the pressure of a pressure-tunable photoionization tandem ion mobility spectrometry(PI-tandem-IMS)was reduced from ambient pressure(100 kPa)to low pressure(20 kPa)to systematically examine the reactivity differences between two negative reactant ions,CO3-and CO4-,and methyl salicylate(MeSA)under varying pressures.When the pressure decreased,the increased relative signal intensity of CO4-significantly influenced the detection sensitivity of the characteristic product ion[MeSA·O2]-.Based on differences in ion mobility(k0),the delay time for the opening of TPG2 was adjusted to selectively inject CO-3 and CO-4 in the drift region 2.Independent characterization of the reactivity of these reactant ions with MeSA in the reaction region confirmed that CO4-exhibited superior reactivity toward MeSA.The theoretical model revealed an Arrhenius plot for the ion-molecule reaction between CO4-and MeSA,showing a positive correlation between the reaction rate coefficient(k)and temperature,the activation energy Ea was 62.45 kJ/mol.Furthermore,controlling parameters such as pressure or temperature significantly influenced the progression of this ion-molecule reaction,demonstrating the technical advantages of PI-tandem-IMS in mechanistic studies and regulation of ion-molecule reactions.

The resolving power and sensitivity are critical for on-site detection of hazardous chemicals using stand-alone ion mobility spectrometry(IMS).However,improving the sensitivity and resolving power of IMS has long been a prominent research hot spot.In the commonly used IMS based on the Bradbury-Nielsen gate(BNG),the gating voltage difference(GVD)applied between the two sets of grid wires affects the electric field distribution in the ionization region and the drift region.This,in turn,influences the spatial distribution and temporal width of the injected ion swarm,and has an impact on the ion mobility discrimination,sensitivity,and resolving power of the instrument.This study showed that increasing the GVD could induce an ion converging effect,boosting the ion number density in front of the BNG by nearly 300％.To simultaneously utilize temporal compression and ion converging effects,a novel BNG controlling mode was proposed by adding a chopping state to the conventional controlling mode.This chopping state reduced the mobility discrimination effects between ions with mobility differences up to about 0.90 cm2/(V·s)to 1/22 of their original value.When analyzing hazardous chemical mixtures using the novel BNG controlling mode,compared with conventional mode,the signal intensity of low-mobility methyl salicylate ions(MS·O2)-increased by 18-fold while the resolving power maintained around 100,and the detection limit for MS was improved from 3.75 &mu;g/L to 97 ng/L.This novel BNG controlling mode only added a potential wave to the low voltage wires,with no requirement of changing the structure of the drift tube,and was easy to apply to existing commercial instruments.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Ion mobility spectroscopy(IMS)has many advantages such as fast detection speed,high sensitivity,and portability,and thus plays an important role in on-site detection of chemical agents,explosives,drugs,environmental pollutants,and other pollutants.As a key component of IMS,the ion number density and temporal width of the injected ion packets directly determine the IMS detection sensitivity and resolution.In yhis study,the dual-parallel-grid structure of Tyndall-Powell gate(TPG),which could effectively isolate the electric fields within the ionization region,gate region,and drift region,was utilized to develop a dual effect TPG gating method for simultaneously enhancing the mobility discrimination reduction and ion packet temporal width compression,thereby improving the IMS performance.A TPG-IMS platform was thus built up and the effects of parameters such as gate opening pulsed width,gate penetration voltage,and ion injection voltage on the sensitivity and resolving power of IMS were systematically investigated using the dual-effect TPG gating method.The results demonstrated that,when detecting diethyl phosphate(DEP)and diethyl methylphosphate(DEMP)mixture using the dual effect TPG gating method,the peak currents of(DEP)2H+and(DEP·DEMP)H+ions with low K0 values were increased by 18 and 45 times respectively,while maintaining a high resolution of about 90.The limits of detection for DEP and DEMP were decreased from 4 ppb(10-9)to 235 ppt(10-12)and from 5 ppb to 156 ppt,respectively.This gating method only regulated the potential of the TPG grid adjacent to the drift region,without changing the structure of the ion mobility tube,making it convenient to apply on existing commercial instruments.

Colorectal cancer is one of the most common malignant tumors of the digestive system.Oxali-platin(OXA)-based combination chemotherapy is the most commonly used strategy for treating patients with advanced-stage disease in clinical practice.However,the development of resistance greatly limits the effectiveness of chemotherapy and is a major cause of treatment failure.Due to the unknown mecha-nisms of resistance,there is an urgent need for a high-throughput,highly specific sequencing method to explore the causes of oxaliplatin resistance.Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9 (CRISPR/Cas9) is a rapidly advancing high-throughput technology that can be employed for screening resistance genes.However,its role in identifying genes involved in oxaliplatin resistance in colorectal cancer remains unclear.We constructed an sgRNA library containing 5256 small-guide RNAs (sgRNAs) targeting 910 human epigenetic-related genes,using lentivirus packaging.By de-termining the viral infection conditions through protein immunoblotting and flow cytometry,we maintained the multiplicity of infection (MOI) below 30％ to ensure that each cell is infected with only one sgRNA,thereby knocking out one gene.Colorectal cancer cells HCT116 and SW620 were infected with lentivirus carrying library,and single clones were obtained and expanded through a positive selection strategy.By the positive selection strategy,we identified 21 genes that regulate the sensitivity of colorectal cancer cells to oxaliplatin.By knocking out of candidate genes,we observed that deletion of TDRKH,ALKBH3,UNKL,TTF2,TNKS,AURKA,RBM12,ELAVL2,DKC1,LSM5,NOL8 and PRPF3 significantly in-creased the half-maximal inhibitory concentration (IC50) of oxaliplatin in colorectal cancer cells (P<0.05) .Among them,high expression of the ALKBH3,AURKA,and RBM12 genes was significantly cor-related with clinical prognosis (overall survival:P=0.043,P<0.0001,P=0.045;recurrence-free sur-vival:P=0.004,P=0.0019,P=0.0064) .Our study demonstrates that the CRISPR/Cas9 library is a high-throughput method for screening tumor sensitivity genes,providing target references for further ex-ploring the mechanism of colorectal cancer sensitivity to oxaliplatin.

Colorectal cancer is one of the most common malignant tumors of the digestive system.Oxali-platin(OXA)-based combination chemotherapy is the most commonly used strategy for treating patients with advanced-stage disease in clinical practice.However,the development of resistance greatly limits the effectiveness of chemotherapy and is a major cause of treatment failure.Due to the unknown mecha-nisms of resistance,there is an urgent need for a high-throughput,highly specific sequencing method to explore the causes of oxaliplatin resistance.Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9 (CRISPR/Cas9) is a rapidly advancing high-throughput technology that can be employed for screening resistance genes.However,its role in identifying genes involved in oxaliplatin resistance in colorectal cancer remains unclear.We constructed an sgRNA library containing 5256 small-guide RNAs (sgRNAs) targeting 910 human epigenetic-related genes,using lentivirus packaging.By de-termining the viral infection conditions through protein immunoblotting and flow cytometry,we maintained the multiplicity of infection (MOI) below 30％ to ensure that each cell is infected with only one sgRNA,thereby knocking out one gene.Colorectal cancer cells HCT116 and SW620 were infected with lentivirus carrying library,and single clones were obtained and expanded through a positive selection strategy.By the positive selection strategy,we identified 21 genes that regulate the sensitivity of colorectal cancer cells to oxaliplatin.By knocking out of candidate genes,we observed that deletion of TDRKH,ALKBH3,UNKL,TTF2,TNKS,AURKA,RBM12,ELAVL2,DKC1,LSM5,NOL8 and PRPF3 significantly in-creased the half-maximal inhibitory concentration (IC50) of oxaliplatin in colorectal cancer cells (P<0.05) .Among them,high expression of the ALKBH3,AURKA,and RBM12 genes was significantly cor-related with clinical prognosis (overall survival:P=0.043,P<0.0001,P=0.045;recurrence-free sur-vival:P=0.004,P=0.0019,P=0.0064) .Our study demonstrates that the CRISPR/Cas9 library is a high-throughput method for screening tumor sensitivity genes,providing target references for further ex-ploring the mechanism of colorectal cancer sensitivity to oxaliplatin.

【Objective】 Corin, a transmembrane serine protease that can cleave atrial natriuretic peptide precursor (pro-ANP) into atrial natriuretic peptide with smaller bioactive molecules, participates in the pathophysiological process of hypertension and cardiac hypertrophy. The purpose of this study was to explore the relationship of Corin gene variation with blood pressure responses to sodium and potassium dietary interventions. 【Methods】 In 2004, we recruited 514 participants from 124 families in 7 villages of Baoji, Shaanxi Province, China. All the subjects received a 3-day normal diet, a 7-day low-salt diet, a 7-day high-salt diet, and finally a 7-day high-salt and potassium supplementation. Fifteen single nucleotide polymorphisms (SNPs) of Corin gene were selected for final analysis. 【Results】 SNPs rs12509275 were significantly associated with diastolic blood pressure (DBP) response to low-salt diet, while rs3749584 was associated with pulse pressure (PP) response to low-salt diet.SNP rs3749584 and rs10517195 were significantly associated with PP response to high-salt diet. In addition,rs17654278 were significantly associated with systolic blood pressure (SBP) response to high-salt and potassium supplementation, rs2271037 was significantly correlated with DBP responses to high-salt and potassium supplementation, and rs4695253, rs12509275, rs2351783, rs36090894 were significantly associated with PP response to high-salt and potassium supplementation. 【Conclusion】 Corin gene polymorphisms were associated with blood pressure response to sodium and potassium, suggesting that Corin gene may be involved in pathophysiological process of salt sensitivity and potassium sensitivity.

Objective To evaluate the accuracy of different convolutional neural networks (CNN),representative deep learning models,in the differential diagnosis of ameloblastoma and odontogenic keratocyst,and subsequently compare the diagnosis results between models and oral radiologists. Methods A total of 1000 digital panoramic radiographs were retrospectively collected from the patients with ameloblastoma (500 radiographs) or odontogenic keratocyst (500 radiographs) in the Department of Oral and Maxillofacial Radiology,Peking University School of Stomatology.Eight CNN including ResNet (18,50,101),VGG (16,19),and EfficientNet (b1,b3,b5) were selected to distinguish ameloblastoma from odontogenic keratocyst.Transfer learning was employed to train 800 panoramic radiographs in the training set through 5-fold cross validation,and 200 panoramic radiographs in the test set were used for differential diagnosis.Chi square test was performed for comparing the performance among different CNN.Furthermore,7 oral radiologists (including 2 seniors and 5 juniors) made a diagnosis on the 200 panoramic radiographs in the test set,and the diagnosis results were compared between CNN and oral radiologists. Results The eight neural network models showed the diagnostic accuracy ranging from 82.50% to 87.50%,of which EfficientNet b1 had the highest accuracy of 87.50%.There was no significant difference in the diagnostic accuracy among the CNN models (P=0.998,P=0.905).The average diagnostic accuracy of oral radiologists was (70.30±5.48)%,and there was no statistical difference in the accuracy between senior and junior oral radiologists (P=0.883).The diagnostic accuracy of CNN models was higher than that of oral radiologists (P<0.001). Conclusion Deep learning CNN can realize accurate differential diagnosis between ameloblastoma and odontogenic keratocyst with panoramic radiographs,with higher diagnostic accuracy than oral radiologists.
Humans ; Ameloblastoma/diagnostic imaging* ; Deep Learning ; Diagnosis, Differential ; Radiography, Panoramic ; Retrospective Studies ; Odontogenic Cysts/diagnostic imaging* ; Odontogenic Tumors