Dragon boat exercise reshapes the temporal-spatial dynamics of the brain.

Although exercise training has been shown to enhance neurological function, there is a shortage of research on how exercise training affects the temporal-spatial synchronization properties of functional networks, which are crucial to the neurological system. This study recruited 23 professional and 24 amateur dragon boat racers to perform simulated paddling on ergometers while recording EEG. The spatiotemporal dynamics of the brain were analyzed using microstates and omega complexity. Temporal dynamics results showed that microstate D, which is associated with attentional networks, appeared significantly altered, with significantly higher duration, occurrence, and coverage in the professional group than in the amateur group. The transition probabilities of microstate D exhibited a similar pattern. The spatial dynamics results showed the professional group had lower brain complexity than the amateur group, with a significant decrease in omega complexity in the α (8-12 Hz) and ß (13-30 Hz) bands. Dragon boat training may strengthen the attentive network and reduce the complexity of the brain. This study provides evidence that dragon boat exercise improves the efficiency of the cerebral functional networks on a spatiotemporal scale.

Multiparameter MRI-based radiomics analysis for preoperative prediction of type II endometrial cancer.

Objectives: This study aimed to develop and validate a radiomics nomogram based on multiparameter MRI for preoperative differentiation of type II and type I endometrial carcinoma (EC). Methods: A total of 403 EC patients from two centers were retrospectively recruited (training cohort, 70 %; validation cohort, 30 %). Radiomics features were extracted from T2-weighted imaging, dynamic contrast-enhanced T1-weighted imaging at delayed phase(DCE4), and apparent diffusion coefficient (ADC) maps. Following dimensionality reduction, radiomics models were developed by logistic regression (LR), random forest (RF), bootstrap aggregating (Bagging), support vector machine (SVM), artificial neural network (ANN), and naive bayes (NB) algorithms. The diagnostic performance of each radiomics model was evaluated using the ROC curve. A nomogram was constructed by incorporating the optimal radiomics signatures with significant clinical-radiological features and immunohistochemistry (IHC) markers obtained from preoperative curettage specimens. The diagnostic performance and clinical value of the nomogram were evaluated using ROC curves, calibration curves, and decision curve analysis (DCA). Results: Among the radiomics models, the NB model, developed from 12 radiomics features derived from ADC and DCE4 sequences, exhibited strong performance in both training and validation sets, with the AUC values of 0.927 and 0.869, respectively. The nomogram, incorporating the radiomics model with significant clinical-radiological features and IHC markers, demonstrated superior performance in both the training (AUC = 0.951) and the validation sets (AUC = 0.915). Additionally, it exhibited excellent calibration and clinical utility. Conclusions: The radiomics nomogram has great potential to differentiate type II from type I EC, which may be an effective tool to guide clinical decision-making for EC patients.

Comparison between solid pseudopapillary neoplasms of the pancreas and pancreatic ductal adenocarcinoma with cystic changes using computed tomography.

BACKGROUND: Solid pseudopapillary neoplasms of the pancreas (SPN) share similar imaging findings with pancreatic ductal adenocarcinoma with cystic changes (PDAC with cystic changes), which may result in unnecessary surgery. AIM: To investigate the value of computed tomography (CT) in differentiation of SPN from PDAC with cystic changes. METHODS: This study retrospectively analyzed the clinical and imaging findings of 32 patients diagnosed with SPN and 14 patients diagnosed with PDAC exhibiting cystic changes, confirmed through pathological diagnosis. Quantitative and qualitative analysis was performed, including assessment of age, sex, tumor size, shape, margin, density, enhancement pattern, CT values of tumors, CT contrast enhancement ratios, "floating cloud sign," calcification, main pancreatic duct dilatation, pancreatic atrophy, and peripancreatic invasion or distal metastasis. Multivariate logistic regression analysis was used to identify relevant features to differentiate between SPN and PDAC with cystic changes, and receiver operating characteristic curves were obtained to evaluate the diagnostic performance of each variable and their combination. RESULTS: When compared to PDAC with cystic changes, SPN had a lower age (32 years vs 64 years, P < 0.05) and a slightly larger size (5.41 cm vs 3.90 cm, P < 0.05). SPN had a higher frequency of "floating cloud sign" and peripancreatic invasion or distal metastasis than PDAC with cystic changes (both P < 0.05). No significant difference was found with respect to sex, tumor location, shape, margin, density, main pancreatic duct dilatation, calcification, pancreatic atrophy, enhancement pattern, CT values of tumors, or CT contrast enhancement ratios between the two groups (all P > 0.05). The area under the receiver operating characteristic curve of the combination was 0.833 (95% confidence interval: 0.708-0.957) with 78.6% sensitivity, 81.3% specificity, and 80.4% accuracy in differentiation of SPN from PDAC with cystic changes. CONCLUSION: A larger tumor size, "floating cloud sign," and peripancreatic invasion or distal metastasis are useful CT imaging features that are more common in SPN and may help discriminate SPN from PDAC with cystic changes.

Predicting the 28-day prognosis of acute-on-chronic liver failure patients based on machine learning.

BACKGROUND: We aimed to establish a prognostic predictive model based on machine learning (ML) methods to predict the 28-day mortality of acute-on-chronic liver failure (ACLF) patients, and to evaluate treatment effectiveness. METHODS: ACLF patients from six tertiary hospitals were included for analysis. Features for ML models' development were selected by LASSO regression. Models' performance was evaluated by area under the curve (AUC) and accuracy. Shapley additive explanation was used to explain the ML model. RESULTS: Of the 736 included patients, 587 were assigned to a training set and 149 to an external validation set. Features selected included age, hepatic encephalopathy, total bilirubin, PTA, and creatinine. The eXtreme Gradient Boosting (XGB) model outperformed other ML models in the prognostic prediction of ACLF patients, with the highest AUC and accuracy. Delong's test demonstrated that the XGB model outperformed Child-Pugh score, MELD score, CLIF-SOFA, CLIF-C OF, and CLIF-C ACLF. Sequential assessments at baseline, day 3, day 7, and day 14 improved the predictive performance of the XGB-ML model and can help clinicians evaluate the effectiveness of medical treatment. CONCLUSIONS: We established an XGB-ML model to predict the 28-day mortality of ACLF patients as well as to evaluate the treatment effectiveness.

LORIS robustly predicts patient outcomes with immune checkpoint blockade therapy using common clinical, pathologic and genomic features.

Despite the revolutionary impact of immune checkpoint blockade (ICB) in cancer treatment, accurately predicting patient responses remains challenging. Here, we analyzed a large dataset of 2,881 ICB-treated and 841 non-ICB-treated patients across 18 solid tumor types, encompassing a wide range of clinical, pathologic and genomic features. We developed a clinical score called LORIS (logistic regression-based immunotherapy-response score) using a six-feature logistic regression model. LORIS outperforms previous signatures in predicting ICB response and identifying responsive patients even with low tumor mutational burden or programmed cell death 1 ligand 1 expression. LORIS consistently predicts patient objective response and short-term and long-term survival across most cancer types. Moreover, LORIS showcases a near-monotonic relationship with ICB response probability and patient survival, enabling precise patient stratification. As an accurate, interpretable method using a few readily measurable features, LORIS may help improve clinical decision-making in precision medicine to maximize patient benefit. LORIS is available as an online tool at https://loris.ccr.cancer.gov/ .

Microenvironment shapes small-cell lung cancer neuroendocrine states and presents therapeutic opportunities.

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intratumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the cell-extrinsic drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the TME exhibit substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAFs) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLC's adaptable nature, opening possibilities for reprogramming the TME-tumor communications that shape SCLC tumor states.

Crucial Involvement of Heme Biosynthesis in Vegetative Growth, Development, Stress Response, and Fungicide Sensitivity of Fusarium graminearum.

Heme biosynthesis is a highly conserved pathway from bacteria to higher animals. Heme, which serves as a prosthetic group for various enzymes involved in multiple biochemical processes, is essential in almost all species, making heme homeostasis vital for life. However, studies on the biological functions of heme in filamentous fungi are scarce. In this study, we investigated the role of heme in Fusarium graminearum. A mutant lacking the rate-limiting enzymes in heme synthesis, coproporphyrinogen III oxidase (Cpo) or ferrochelatase (Fc), was constructed using a homologous recombination strategy. The results showed that the absence of these enzymes was lethal to F. graminearum, but the growth defect could be rescued by the addition of hemin, so we carried out further studies with the help of hemin. The results demonstrated that heme was required for the activity of FgCyp51, and its absence increased the sensitivity to tebuconazole and led to the upregulation of FgCYP51 in F. graminearum. Additionally, heme plays an indispensable role in the life cycle of F. graminearum, which is essential for vegetative growth, conidiation, external stress response (especially oxidative stress), lipid accumulation, fatty acid ß-oxidation, autophagy, and virulence.

IGF2BP3 promotes glutamine metabolism of endometriosis by interacting with UCA1 to enhances the mRNA stability of GLS1.

BACKGROUND: Insulin like growth factor II mRNA binding protein 3 (IGF2BP3) has been implicated in numerous inflammatory and cancerous conditions. However, its precise molecular mechanisms in endometriosis (EMs) remains unclear. The aim of this study is to examine the influence of IGF2BP3 on the occurrence and progression of EMs and to elucidate its underlying molecular mechanism. METHODS: Efects of IGF2BP3 on endometriosis were confrmed in vitro and in vivo. Based on bioinformatics analysis, RNA immunoprecipitation (RIP), RNA pull-down assays and Fluorescent in situ hybridization (FISH) were used to show the association between IGF2BP3 and UCA1. Single-cell spatial transcriptomics analysis shows the expression distribution of glutaminase 1 (GLS1) mRNA in EMs. Study the effect on glutamine metabolism after ectopic endometriotic stromal cells (eESCs) were transfected with Sh-IGF2BP3 and Sh-UCA1 lentivirus. RESULTS: Immunohistochemical staining have revealed that IGF2BP3 was upregulated in ectopic endometriotic lesions (EC) compared to normal endometrial tissues (EN). The proliferation and migration ability of eESCs were greatly reduced by downregulating IGF2BP3. Additionally, IGF2BP3 has been observed to interact with urothelial carcinoma associated 1 (UCA1), leading to increased stability of GLS1 mRNA and subsequently enhancing glutamine metabolism. Results also demonstrated that IGF2BP3 directly interacts with the 3' UTR region of GLS1 mRNA, influencing its expression and stability. Furthermore, UCA1 was able to bind with c-MYC protein, stabilizing c-MYC mRNA and consequently enhancing GLS1 expression through transcriptional promotion. CONCLUSION: These discoveries underscored the critical involvement of IGF2BP3 in the elevation and stability of GLS1 mRNA in the context of glutamine metabolism by interacting with UCA1 in EMs. The implications of our study extended to the identification of possible therapeutic targets for individuals with EMs.

Long-term PM2.5 exposure associated with severity of angina pectoris and related health status in patients admitted with acute coronary syndrome: Modification effect of genetic susceptibility and disease history.

Long-term particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5) exposure has been associated with the occurrence of acute coronary syndrome (ACS). However, the impact of PM2.5 exposure and its components on the severity of angina pectoris and disease-related health status in patients hospitalized for ACS is understudied. To assess the association between long-term exposure to PM2.5 components and the angina pectoris severity in ACS patients, as well as the modification effects of genetic factors and disease history in north China. During 2017-2019, 6729 ACS patients were collected in Shandong Province and Beijing, with their angina pectoris severity evaluated using Seattle Angina Questionnaire (SAQ). The 0-3 years' average concentrations of PM2.5 and its five major components were assigned to each patient's residential address. Linear mixed-effects model, weighted quantile regression, and quantile g-computation were used to estimate the effects of both single and joint associations between PM2.5 components and SAQ scores. The interactive effect was estimated by polygenic risk scores and disease history. For each interquartile range increase in PM2.5, the overall SAQ score changed by -3.71% (95%CI: -4.54% to -2.88%), with score of angina stability more affected than angina frequency and other dimensions of angina pectoris severity. Sulfate and ammonium were major contributors to the effect of PM2.5 exposure. Significant modification effect was only observed for disease history, especially for the dimension of physical limitation. Among a series of pre-existing diseases, patients with a family history of coronary artery disease, previous percutaneous coronary intervention or coronary artery bypass grafting, and stroke were more susceptible to PM2.5 exposure than others. Greater exposure to PM2.5 is associated with more serious angina pectoris and worse disease-related health status in ACS patients. Public health and clinical priority should be given to cutting down key effective components and protecting highly vulnerable individuals.

MAFLD as part of systemic metabolic dysregulation.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases worldwide. In recent years, a new terminology and definition of metabolic dysfunction-associated fatty liver disease (MAFLD) has been proposed. Compared to the NAFLD definition, MAFLD better emphasizes the pathogenic role of metabolic dysfunction in the development and progression of this highly prevalent condition. Metabolic disorders, including overweight/obesity, type 2 diabetes mellitus (T2DM), atherogenic dyslipidemia and hypertension, are often associated with systemic organ dysfunctions, thereby suggesting that multiple organ damage can occur in MAFLD. Substantial epidemiological evidence indicates that MAFLD is not only associated with an increased risk of liver-related complications, but also increases the risk of developing several extra-hepatic diseases, including new-onset T2DM, adverse cardiovascular and renal outcomes, and some common endocrine diseases. We have summarized the current literature on the adverse effect of MAFLD on the development of multiple extrahepatic (cardiometabolic and endocrine) complications and examined the role of different metabolic pathways and organ systems in the progression of MAFLD, thus providing new insights into the role of MAFLD as a multisystem metabolic disorder. Our narrative review aimed to provide insights into potential mechanisms underlying the known associations between MAFLD and extrahepatic diseases, as part of MAFLD as a multisystem disease, in order to help focus areas for future drug development targeting not only liver disease but also the risk of extrahepatic complications.

Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma.

BACKGROUND: One of the primary reasons for the dismal survival rates in pancreatic ductal adenocarcinoma (PDAC) is that most patients are usually diagnosed at late stages. There is an urgent unmet clinical need to identify and develop diagnostic methods that could precisely detect PDAC at its earliest stages. AIM: To evaluate the potential value of radiomics analysis in the differentiation of early-stage PDAC from late-stage PDAC. METHODS: A total of 71 patients with pathologically proved PDAC based on surgical resection who underwent contrast-enhanced computed tomography (CT) within 30 d prior to surgery were included in the study. Tumor staging was performed in accordance with the 8th edition of the American Joint Committee on Cancer staging system. Radiomics features were extracted from the region of interest (ROI) for each patient using Analysis Kit software. The most important and predictive radiomics features were selected using Mann-Whitney U test, univariate logistic regression analysis, and minimum redundancy maximum relevance (MRMR) method. Random forest (RF) method was used to construct the radiomics model, and 10-times leave group out cross-validation (LGOCV) method was used to validate the robustness and reproducibility of the model. RESULTS: A total of 792 radiomics features (396 from late arterial phase and 396 from portal venous phase) were extracted from the ROI for each patient using Analysis Kit software. Nine most important and predictive features were selected using Mann-Whitney U test, univariate logistic regression analysis, and MRMR method. RF method was used to construct the radiomics model with the nine most predictive radiomics features, which showed a high discriminative ability with 97.7% accuracy, 97.6% sensitivity, 97.8% specificity, 98.4% positive predictive value, and 96.8% negative predictive value. The radiomics model was proved to be robust and reproducible using 10-times LGOCV method with an average area under the curve of 0.75 by the average performance of the 10 newly built models. CONCLUSION: The radiomics model based on CT could serve as a promising non-invasive method in differential diagnosis between early and late stage PDAC.

Genome-Wide Identification and Expression Analysis of Kiwifruit Leucine-Rich Repeat Receptor-Like Proteins Reveal Their Roles in Biotic and Abiotic Stress Responses.

Leucine-rich repeat receptor-like proteins (LRR-RLPs), a major group of receptor-like proteins in plants, have diverse functions in plant physiology, including growth, development, signal transduction, and stress responses. Despite their importance, the specific roles of kiwifruit LRR-RLPs in response to biotic and abiotic stresses remain poorly understood. In this study, we performed family identification, characterization, transcriptome data analysis, and differential gene expression analysis of kiwifruit LRR-RLPs. We identified totals of 101, 164, and 105 LRR-RLPs in Actinidia chinensis 'Hongyang', Actinidia eriantha 'Huate', and Actinidia chinensis 'Red5', respectively. Synteny analysis revealed that the expansion of kiwifruit LRR-RLPs was primarily attributed to segmental duplication events. Based on RNA-seq data from pathogen-infected kiwifruits, we identified specific LRR-RLP genes potentially involved in different stages of pathogen infection. Additionally, we observed the potential involvement of kiwifruit LRR-RLPs in abiotic stress responses, with upstream transcription factors possibly regulating their expression. Furthermore, protein interaction network analysis unveiled the participation of kiwifruit LRR-RLP in the regulatory network of abiotic stress responses. These findings highlight the crucial roles of LRR-RLPs in mediating both biotic and abiotic stress responses in kiwifruit, offering valuable insights for the breeding of stress-resistant kiwifruit varieties.

Screening and Application of DNA Aptamers for Heparin-Binding Protein.

Rapid detection of heparin-binding protein (HBP) is essential for timely intervention in sepsis cases. Current detection techniques are usually antibody-based immunological methods, which have certain problems, such as complexity and slow detection, and fall short in meeting the urgency of clinical needs. The application of an aptamer can address these concerns well. In this study, HBP-specific DNA aptamers were screened first. Among which, Apt-01, Apt-02, and Apt-13 had a high affinity for HBP, exhibiting impressive KD values of 3.42, 1.44, and 1.04 nmol/L, respectively. Then, the aptamer of HBP and its partially complementary primer probe were combined to form double-stranded DNA (dsDNA) and synthesize a circular DNA template. The template is complementary to the primer probe, but due to the presence of dsDNA, ExoIII cleaves C2-13 as an RCA primer probe, rendering the template unable to recognize the primer probe and preventing the RCA reaction from proceeding. When the target is present, it competes with the adapter for recognition and releases C2-13, exposing its 3' end. After initiating the RCA at room temperature and reacting with SYBR GreenII at 37 °C for 20 min, fluorescence changes can be observed and quantitatively analyzed at a 530 nm wavelength, achieving quantitative biological analysis. Apt-01 was used to develop a fluorescent biosensor for HBP detection, which exhibited a good linear range (0.01 nmol/L to 10 nmol/L) and detection limit (0.0056 nmol/L). This advancement holds the potential to lay a solid groundwork for pioneering sensitive and specific methods for HBP detection and to significantly enhance the diagnostic processes for sepsis.

Impact of Onset Time, Number, Type, and Sequence of Extrahepatic Organ Failure on Prognosis of Acute-on-chronic Liver Failure.

Background and Aims: The impact of the characteristics of extrahepatic organ failure (EHOF) including the onset time, number, type, and sequence on the prognosis of acute-on-chronic liver failure (ACLF) patients remains unknown. This study aimed to identify the association between the characteristics of EHOF and the prognosis of ACLF patients. Methods: ACLF subjects enrolled at six hospitals in China were included in the analysis. The risk of mortality based on the characteristics of EHOF was evaluated. Survival of study groups was compared by Kaplan-Meier analysis and log-rank tests. Results: A total of 736 patients with ACLF were included. EHOF was observed in 402 patients (54.6%), of which 295 (73.4%) developed single EHOF (SEHOF) and 107 (26.6%) developed multiple EHOF (MEHOF). The most commonly observed EHOF was coagulation failure (47.0%), followed by renal (13.0%), brain (4.9%), respiratory (4.3%), and circulatory (2.3%) failure. Survival analysis found that MEHOF or SEHOF patients with brain failure had a worse prognosis. However, no significant outcome was found in the analysis of the effect of onset time and sequence of failed organs on prognosis. Patients were further divided into three risk subgroups by the EHOF characteristics. Kaplan-Meier analysis showed that risk stratification resulted in the differentiation of patients with different risks of mortality both in the training and validation cohorts. Conclusions: The mortality of ACLF patients was determined by the number and type, but not the onset time and sequence of EHOF. Risk stratification applicable to clinical practice was established.

Current status and future trends of the global burden of MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most common chronic liver disease globally, affecting more than a third of the world's adult population. This comprehensive narrative review summarizes the global incidence and prevalence rates of MASLD and its related adverse hepatic and extrahepatic outcomes. We also discuss the substantial economic burden of MASLD on healthcare systems, thus further highlighting the urgent need for global efforts to tackle this common and burdensome liver condition. We emphasize the clinical relevance of early interventions and a holistic approach that includes public health strategies to reduce the global impact of MASLD.

Identification of Ossnrk1a-1 Regulated Genes Associated with Rice Immunity and Seed Set.

Sucrose non-fermenting-1-related protein kinase-1 (SnRK1) is a highly conserved serine-threonine kinase complex regulating plants' energy metabolisms and resistance to various types of stresses. However, the downstream genes regulated by SnRK1 in these plant physiological processes still need to be explored. In this study, we found that the knockout of OsSnRK1a resulted in no obvious defects in rice growth but notably decreased the seed setting rate. The ossnrk1a mutants were more sensitive to blast fungus (Magnaporthe oryzae) infection and showed compromised immune responses. Transcriptome analyses revealed that SnRK1a was an important intermediate in the energy metabolism and response to biotic stress. Further investigation confirmed that the transcription levels of OsNADH-GOGAT2, which positively controls rice yield, and the defense-related gene pathogenesis-related protein 1b (OsPR1b) were remarkably decreased in the ossnrk1a mutant. Moreover, we found that OsSnRK1a directly interacted with the regulatory subunits OsSnRK1ß1 and OsSnRK1ß3, which responded specifically to blast fungus infection and starvation stresses, respectively. Taken together, our findings provide an insight into the mechanism of OsSnRK1a, which forms a complex with specific ß subunits, contributing to rice seed set and resistance by regulating the transcription of related genes.

One-Shot Dual-Detection-Based Single-Molecule Super-Resolution Imaging Method for Real-Time Observation of Spatiotemporal Catalytic Activity Variations on the Plasmonic Gold Nanoparticle Surface.

Understanding the relationship between the surface properties of a single plasmonic nanoparticle and its catalytic performance is critical for developing highly efficient nanocatalysts. In this study, a one-shot dual-detection-based single-molecule super-resolution imaging method in the evanescent field was developed to observe real-time spatiotemporal catalytic activity on a single plasmonic gold nanoparticle (AuNP) surface. The scattering intensity of AuNPs and the fluorescence of resorufin molecules produced on the AuNP surface were obtained simultaneously to investigate the relationship between nanoparticles and catalytic reactions at a single-molecule level. Chemisorbed adsorbates (i.e., catalytic product and resorufin) changed the electron density of individual AuNPs throughout the catalytic cycle, resulting in the fluctuation of the scattering intensity of individual AuNPs, which was attributed to the electron transfer between reactant resazurin molecules and AuNPs. The increase in the electron density of individual AuNPs affected the catalytic reaction rate. Furthermore, sequential mapping of individual catalytic events at the subdiffraction limit resolution was completed for real-time surface dynamics and spatiotemporal activity variations on the single AuNP surface. The developed method can aid in understanding surface-property-dependent catalytic kinetics and facilitate the development of nanoparticle-based heterogeneous catalysts at subdiffraction limit resolution.

Activity of thonningianin A against Candida albicans in vitro and in vivo.

Fungal infections are increasing rapidly, and antifungal agents used in clinics are limited. Therefore, novel antifungal agents with high efficiency are urgently required. In this study, we investigated the antifungal activity of thonningianin A (THA), a natural compound that is widely found in plants. We first determined the activity of THA against Candida albicans, one of the most common fungal pathogens, and found that THA showed antifungal activity against all C. albicans tested, including several fluconazole-resistant isolates. THA also inhibits the growth of non-Candida albicans species. In addition, THA displayed antibiofilm activity and could not only inhibit biofilm formation but also destroy mature biofilms. The in vivo antifungal efficacy of THA was confirmed in a Galleria mellonella infection model. Further studies revealed that THA could enhance intracellular reactive oxygen species (ROS) production and regulate the transcription of several redox-related genes. Specifically, caspase activity and expression of CaMCA1, a caspase-encoding gene in C. albicans, were remarkably increased upon THA treatment. Consistent with this, in the presence of THA, the Camca1 null mutant displayed higher survival rates and reduced caspase activity compared to the wild-type or CaMCA1-reintroduced strains, indicating an important role of CaMCA1 in the antifungal activity of THA. Taken together, our results indicate that THA possesses excellent antifungal activity and may be a promising novel antifungal candidate. KEY POINTS: • THA exhibits activity against Candida species, including fluconazole-resistant isolates • THA inhibits biofilm formation and destroys mature biofilm • Elevated ROS production and CaMCA1-mediated caspase activity are involved in the antifungal mechanisms of THA.

A Weakly Supervised Segmentation Network Embedding Cross-Scale Attention Guidance and Noise-Sensitive Constraint for Detecting Tertiary Lymphoid Structures of Pancreatic Tumors.

The presence of tertiary lymphoid structures (TLSs) on pancreatic pathological images is an important prognostic indicator of pancreatic tumors. Therefore, TLSs detection on pancreatic pathological images plays a crucial role in diagnosis and treatment for patients with pancreatic tumors. However, fully supervised detection algorithms based on deep learning usually require a large number of manual annotations, which is time-consuming and labor-intensive. In this paper, we aim to detect the TLSs in a manner of few-shot learning by proposing a weakly supervised segmentation network. We firstly obtain the lymphocyte density maps by combining a pretrained model for nuclei segmentation and a domain adversarial network for lymphocyte nuclei recognition. Then, we establish a cross-scale attention guidance mechanism by jointly learning the coarse-scale features from the original histopathology images and fine-scale features from our designed lymphocyte density attention. A noise-sensitive constraint is introduced by an embedding signed distance function loss in the training procedure to reduce tiny prediction errors. Experimental results on two collected datasets demonstrate that our proposed method significantly outperforms the state-of-the-art segmentation-based algorithms in terms of TLSs detection accuracy. Additionally, we apply our method to study the congruent relationship between the density of TLSs and peripancreatic vascular invasion and obtain some clinically statistical results.

New insights into the downregulation of cytochrome P450 2E1 via nuclear factor κB-dependent pathways in immune-mediated liver injury.

The extent of immune-mediated hepatic damage (such as in viral hepatitis) is characterised by the downregulation of cytochrome P450s (CYPs), a class of drug-metabolising enzymes. However, whether this downregulation aids liver cells in maintaining their homeostasis or whether the damage is aggravated remains largely unexplored. Herein, we evaluated the effects of phosphorylation mediated by the protein kinase C (PKC)/cAMP-response element binding protein (CREB) and nitration mediated by inducible nitric oxide synthase (iNOS) on the downregulation of CYP2E1 during immune-mediated liver injury. Additionally, we investigated the regulatory mechanism mediated by the nuclear factor κB (NF-κB). The rat model of immune-mediated liver injury was replicated by administering a single i.v. injection of Bacillus Calmette-Guerin (BCG, 125 mg/kg) vaccine and three i.p. injections of ammonium pyrrolidine dithiocarbamate (25, 50, 100 mg/kg/d, days 11, 12, and 13); blood was then collected on day 14. Subsequently, the livers were extracted to identify the different pharmacokinetic and biochemical indicators involved in the process. Our study reports new findings on the dependence between PKC-mediated CREB phosphorylation in the anti-inflammatory pathway and nitration emergency induced by iNOS in pro-inflammatory pathways in the NF-κB pathway. The interaction of these two pathways leads to the downregulation and recovery of CYP2E1, thus alleviating inflammation and nitration stress. Our results confirm that BCG-mediated downregulation of CYP2E1 is linked to iNOS-induced nitration and PKC/NF-κB-mediated CREB phosphorylation, and that NF-κB is an important molecular target in this process. These findings suggest that the downregulation of CYP2E1 may be an autonomous process characteristic of liver cells, helping them adapt to environmental changes, alleviate further hypoxia in inflamed tissues, and minimise exposure to toxic and harmful metabolites.