Objective:Glioblastoma(GBM)and brain metastases(BMs)are the two most common malignant brain tumors in adults.Magnetic resonance imaging(MRI)is a commonly used method for screening and evaluating the prognosis of brain tumors,but the specificity and sensitivity of conventional MRI sequences in differential diagnosis of GBM and BMs are limited.In recent years,deep neural network has shown great potential in the realization of diagnostic classification and the establishment of clinical decision support system.This study aims to apply the radiomics features extracted by deep learning techniques to explore the feasibility of accurate preoperative classification for newly diagnosed GBM and solitary brain metastases(SBMs),and to further explore the impact of multimodality data fusion on classification tasks. Methods:Standard protocol cranial MRI sequence data from 135 newly diagnosed GBM patients and 73 patients with SBMs confirmed by histopathologic or clinical diagnosis were retrospectively analyzed.First,structural T1-weight,T1C-weight,and T2-weight were selected as 3 inputs to the entire model,regions of interest(ROIs)were manually delineated on the registered three modal MR images,and multimodality radiomics features were obtained,dimensions were reduced using a random forest(RF)-based feature selection method,and the importance of each feature was further analyzed.Secondly,we used the method of contrast disentangled to find the shared features and complementary features between different modal features.Finally,the response of each sample to GBM and SBMs was predicted by fusing 2 features from different modalities. Results:The radiomics features using machine learning and the multi-modal fusion method had a good discriminatory ability for GBM and SBMs.Furthermore,compared with single-modal data,the multimodal fusion models using machine learning algorithms such as support vector machine(SVM),Logistic regression,RF,adaptive boosting(AdaBoost),and gradient boosting decision tree(GBDT)achieved significant improvements,with area under the curve(AUC)values of 0.974,0.978,0.943,0.938,and 0.947,respectively;our comparative disentangled multi-modal MR fusion method performs well,and the results of AUC,accuracy(ACC),sensitivity(SEN)and specificity(SPE)in the test set were 0.985,0.984,0.900,and 0.990,respectively.Compared with other multi-modal fusion methods,AUC,ACC,and SEN in this study all achieved the best performance.In the ablation experiment to verify the effects of each module component in this study,AUC,ACC,and SEN increased by 1.6%,10.9%and 15.0%,respectively after 3 loss functions were used simultaneously. Conclusion:A deep learning-based contrast disentangled multi-modal MR radiomics feature fusion technique helps to improve GBM and SBMs classification accuracy.

Ferroptosis,discovered in 2012,is a newly form of non-apoptotic and non-necrotic cell death,which is characterized by an increasement in lipid peroxidation and accumulation of intracellular iron ions.Glutathione peroxidase 4(GPX4)is the fourth member of the selenoprotein GPx family and plays a crucial role in clearing lipid peroxides in cells,making it an important regulator of ferroptosis.Small molecule inhibitors targeting GPX4 can induce ferroptosis,offering a new strategy for treating drug-resistant cancers and neurodegenerative diseases.The protein structure and function of GPX4 were primarily discusseed,and the latest advances in small molecule inhibitors of GPX4 were summarized,which provided a research foundation for developing ferroptosis inducers based on GPX4 inhibition.

Objective:To investigate the risk factors of non-valvular paroxysmal atrial fibrillation (NVPAF) with cerebral ischemic stroke(CIS) and analyze NVPAF by using left atrial automatic imaging (AFILA). Logistic regression model was established for left atrial(LA) function parameters.Methods:A total of 205 patients with NVPAF were included in the study and divided into the NVPAF group without ischemic stroke (154 patients) and the CIS group (51 patients). The clinical baseline data, blood biochemical results and AFILA ultrasound data of all patients were collected. Univariate analysis was performed to compare the above data between the two groups of patients. The independent risk factors were obtained by multivariate logistic regression analysis. Logistic regression model was compared with CHA2DS2-VASc scoring system in terms of area under ROC curve, sensitivity and specificity.Results:There were significant differences in age, CHA2DS2-VASc score, taking anticoagulant drugs, history of hypertension, diabetes and coronary heart disease, LAEF, S_R, S_CT, WBC, NEUT, HCY, UREA, NDD, NT-proBNP, Fibrinogen(Fib), Cardiac troponin I(cTnI) and NLR between the two groups (all P<0.05). The results of multifactor analysis showed that: age, hypertension, S_ CT, UREA, NLR, Fib and cTnI were independent risk factors associated with CIS in patients with paroxysmal atrial fibrillation[ OR value: 1.608 ( P=0.003), 3.821 ( P=0.019), 1.259 ( P=0.001), 1.326( P=0.001), 1.352 ( P=0.011), 1.502 ( P=0.042), 7.651( P=0.001)]. After adjusting for the age, sex and history of hypertension included in CHA2DS2-VASc score, S_CT significantly led to NVPAF complicated with stroke[ OR value 1.259 (1.095-1.447), P=0.001]. The diagnostic efficacy of Logistic regression model is better than that of CHA2DS2-VASc scoring (AUC of 0.931 vs 0.717, 95% CI: 0.896-0.967 vs 0.634-0.799, sensitivity of 0.883 vs 0.755, specificity of 0.849 vs 0.713, all P<0.001). Conclusions:Age, hypertension, S_CT, UREA, NLR, fibrinogen, cTnI are independently associated risk factors for patients with combined CIS; The diagnostic efficacy of Logistic regression model is better than that of CHA2DS2-VASc scoring model.And the sensitivity and specificity are high.

Invasive fungal infections (IFIs) have been associated with high mortality, highlighting the urgent need for developing novel antifungal strategies. Herein the first light-responsive antifungal agents were designed by optical control of fungal ergosterol biosynthesis pathway with photocaged triazole lanosterol 14α-demethylase (CYP51) inhibitors. The photocaged triazoles completely shielded the CYP51 inhibition. The content of ergosterol in fungi before photoactivation and after photoactivation was 4.4% and 83.7%, respectively. Importantly, the shielded antifungal activity (MIC₈₀ ≥ 64 μg/mL) could be efficiently recovered (MIC₈₀ = 0.5-8 μg/mL) by light irradiation. The new chemical tools enable optical control of fungal growth arrest, morphological conversion and biofilm formation. The ability for high-precision antifungal treatment was validated by in vivo models. The light-activated compound A1 was comparable to fluconazole in prolonging survival in Galleria mellonella larvae with a median survival of 14 days and reducing fungal burden in the mouse skin infection model. Overall, this study paves the way for precise regulation of antifungal therapy with improved efficacy and safety.

Objective To evaluate the in vitro synergistic antifungal activity of HDAC inhibitors in combination with azole drugs against azoles-resistant Candida strains. Methods The checkerboard microdilution method was used to evaluate the antifungal activity of the HDAC inhibitors in combination with azole drugs against clinically drug-resistant strains. The fungistatic activity and toxicity of Rocilinostat was determined through time-growth curve assay and cytotoxicity assay. Results The compound Rocilinostat combined with azole drugs showed excellent synergistic antifungal activity against a variety of azoles-resistant Candida albicans and Candida glabrata. The combination of high concentration Rocilinostat with FLC exhibited fungistatic effects. Very low toxicity was detected with Rocilinostat towards normal cells. Rocilinostat showed better HDAC inhibitory activity than SAHA. Conclusion As a fungi HDAC inhibitor, Rocilinostat has excellent in vitro synergistic antifungal activity and no severe toxicity to normal human cells.

Metabolic-associated fatty liver disease (MAFLD), which is previously known as non-alcoholic fatty liver disease (NAFLD), represents a major health concern worldwide with limited therapy. Here, we provide evidence that ferroptosis, a novel form of regulated cell death characterized by iron-driven lipid peroxidation, was comprehensively activated in liver tissues from MAFLD patients. The canonical-GPX4 (cGPX4), which is the most important negative controller of ferroptosis, is downregulated at protein but not mRNA level. Interestingly, a non-canonical GPX4 transcript-variant is induced (inducible-GPX4, iGPX4) in MAFLD condition. The high fat-fructose/sucrose diet (HFFD) and methionine/choline-deficient diet (MCD)-induced MAFLD pathologies, including hepatocellular ballooning, steatohepatitis and fibrosis, were attenuated and aggravated, respectively, in cGPX4-and iGPX4-knockin mice. cGPX4 and iGPX4 isoforms also displayed opposing effects on oxidative stress and ferroptosis in hepatocytes. Knockdown of iGPX4 by siRNA alleviated lipid stress, ferroptosis and cell injury. Mechanistically, the triggered iGPX4 interacts with cGPX4 to facilitate the transformation of cGPX4 from enzymatic-active monomer to enzymatic-inactive oligomers upon lipid stress, and thus promotes ferroptosis. Co-immunoprecipitation and nano LC-MS/MS analyses confirmed the interaction between iGPX4 and cGPX4. Our results reveal a detrimental role of non-canonical GPX4 isoform in ferroptosis, and indicate selectively targeting iGPX4 may be a promising therapeutic strategy for MAFLD.

Candida auris is emerging as a major global threat to human health. C. auris infections are associated with high mortality due to intrinsic multi-drug resistance. Currently, therapeutic options for the treatment of C. auris infections are rather limited. We aim to provide a comprehensive review of current strategies, drug candidates, and lead compounds in the discovery and development of novel therapeutic agents against C. auris. The drug resistance profiles and mechanisms are briefly summarized. The structures and activities of clinical candidates, drug combinations, antifungal chemosensitizers, repositioned drugs, new targets, and new types of compounds will be illustrated in detail, and perspectives for guiding future research will be provided. We hope that this review will be helpful to prompting the drug development process to combat this fungal pathogen.

Objective: To investigate the pathogenicity of rare damaging variants from ciliary pathway to human lumbosacral neural tube defects(NTDs). Methods: The coding region sequences of 49 ciliary genes were amplified by AmpliSeq technique and sequenced by PGM sequencing platform for screening the rare damaging variants, and the parents without phenotype were used as controls to evaluate the pathogenicity of variants. Results: The rare de novo mutation of GLI3 gene(c.C580 T,p.H194 Y) was detected in one patient.The rare complex heterozygous mutations of CRB2 gene(c.G1392 C,p.R464 S;c.T3448 C,p.C1150 R) was detected in another patient. Conclusion Rare damaging variants from ciliary pathway may be associated with the occurrence of human lumbosacral NTDs.

The dose-related adverse effects of MDM2‒P53 inhibitors have caused significant concern in the development of clinical safe anticancer agents. Herein we report an unprecedented homo-PROTAC strategy for more effective disruption of MDM2‒P53 interaction. The design concept is inspired by the capacity of sub-stoichiometric catalytic PROTACs enabling to degrade an unwanted protein and the dual functions of MDM2 as an E3 ubiquitin ligase and a binding protein with tumor suppressor P53. The new homo-PROTACs are designed to induce self-degradation of MDM2. The results of the investigation have shown that PROTAC

BACKGROUND: Preoperative diagnosis and differential diagnosis of small solid pulmonary nodules are very difficult. Computed tomography (CT), as a common method for lung cancer screening, is widely used in clinical practice. The aim of this study was to analyze the clinical data of patients with malignant pulmonary nodules and intrapulmonary lymph nodes in the clinical diagnosis and treatment of <1 cm solid pulmonary nodules, so as to provide reference for the differentiation of the two. METHODS: Patients with solid pulmonary nodules who underwent surgery from June 2017 to June 2020 were analyzed retrospectively. The clinical data of 145 nodules (lung adenocarcinoma 60, lung carcinoid 2, malignant mesothelioma 1, sarcomatoid carcinoma 1, lymph node 81) were collected and finally divided into two groups: lung adenocarcinoma and intrapulmonary lymph nodes, and their clinical data were statistically analyzed. According to the results of univariate analysis (χ² test, t test), the variables with statistical differences were selected and included in Logistic regression multivariate analysis. The predictive variables were determined and the receiver operating characteristic (ROC) curve was drawn to get the area under the curve (AUC) value of the area under the curve. RESULTS: Logistic regression analysis showed that the longest diameter, Max CT value, lobulation sign and spiculation sign were important indicators for distinguishing lung adenocarcinoma from intrapulmonary lymph nodes, and the risk ratios were 106.645 (95%CI: 3.828-2,971.220, P<0.01), 0.980 (95%CI: 0.969-0.991, P<0.01), 3.550 (95%CI: 1.299-9.701, P=0.01), 3.618 (95%CI: 1.288-10.163, P=0.02). According to the results of Logistic regression analysis, the prediction model is determined, the ROC curve is drawn, and the AUC value under the curve is calculated to be 0.877 (95%CI: 0.821-0.933, P<0.01). CONCLUSIONS For <1 cm solid pulmonary nodules, among many factors, the longest diameter, Max CT value, lobulation sign and spiculation sign are more important in distinguishing malignant pulmonary nodules from intrapulmonary lymph nodes.