Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Mechanism Switch in Surface-Enhanced Raman Scattering: The Role of Nanoparticle Dimensions.

Surface-enhanced Raman scattering (SERS) is renowned for amplifying Raman signals, with electromagnetic mechanism (EM) enhancement arising from localized surface plasmon resonances and chemical mechanism (CM) enhancement as a result of charge transfer interactions. Despite the conventional emphasis on EM as a result of plasmonic effects, recent findings highlight the significance of CM when noble metals appear as smaller entities. However, the threshold size of the noble metal clusters/particles corresponding to the switch in SERS mechanisms is not clear at present. In this work, the VSe2-xOx/Au composites with different Au sizes are employed, in which a clear view of the SERS mechanism switch is observed at the Au size range of 16-21 nm. Our findings not only provide insight into the impact of noble metal size on SERS efficiency but also offer quantitative data to assist researchers in making informed judgments when analyzing SERS mechanisms.

Immunomodulation Pathogenesis and Treatment of Bone Nonunion.

Fractures and bone nonunion commonly require surgical intervention. Serious outcomes of non-healing in the late stages of fracture place a significant financial burden on society and families. Bone nonunion occurs when a fracture stops healing, for many reasons, and leads to a variety of bad outcomes. Numerous factors, including biomechanics and immunology, are involved in the complicated mechanisms of bone nonunion. The immune-inflammatory response plays a significant part in the emergence of bone nonunion, and the occurrence, control, and remission of inflammation in the bone healing process have a significant influence on the ultimate success of bone tissue repair. In the bone microenvironment, immune cells and associated cytokines control bone repair, which is significantly influenced by macrophages, T cells, and fibroblast growth factor. To limit acute inflammation and  balance osteogenesis and osteoblastogenesis for tissue repair and regeneration, immune cells and various cytokines in the local microenvironment must be precisely regulated. As a bad complication of late-stage fractures, bone nonunion has a significant effect on patients' quality of life and socioeconomic development. Therefore, in-depth research on its pathogenesis and treatment methods has important clinical value. To provide more precise, focused therapeutic options for the treatment of bone nonunion, we discuss the regulatory roles of the key immune cells engaged in bone healing within the microenvironment during bone healing and their effect on osteogenesis.

Universal Formation of Single Atoms from Molten Salt for Facilitating Selective CO2 Reduction.

Clarifying the formation mechanism of single-atom sites guides the design of emerging single-atom catalysts (SACs) and facilitates the identification of the active sites at atomic scale. Herein, a molten-salt atomization strategy is developed for synthesizing zinc (Zn) SACs with temperature universality from 400 to 1000/1100 °C and an evolved coordination from Zn-N2Cl2 to Zn-N4. The electrochemical tests and in situ attenuated total reflectance-surface-enhanced infrared absorption spectroscopy confirm that the Zn-N4 atomic sites are active for electrochemical carbon dioxide (CO2) conversion to carbon monoxide (CO). In a strongly acidic medium (0.2 m K2SO4, pH = 1), the Zn SAC formed at 1000 °C (Zn1NC) containing Zn-N4 sites enables highly selective CO2 electroreduction to CO, with nearly 100% selectivity toward CO product in a wide current density range of 100-600 mA cm-2. During a 50 h continuous electrolysis at the industrial current density of 200 mA cm-2, Zn1NC achieves Faradaic efficiencies greater than 95% for CO product. The work presents a temperature-universal formation of single-atom sites, which provides a novel platform for unraveling the active sites in Zn SACs for CO2 electroreduction and extends the synthesis of SACs with controllable coordination sites.

Single-Cell Transcriptional Profile Construction of Rat Pituitary Glands before and after Sexual Maturation and Identification of Novel Marker Spp1 in Gonadotropes.

The mammalian pituitary gland drives highly conserved physiological processes such as somatic cell growth, pubertal transformation, fertility, and metabolism by secreting a variety of hormones. Recently, single-cell transcriptomics techniques have been used in pituitary gland research. However, more studies have focused on adult pituitary gland tissues from different species or different sexes, and no research has yet resolved cellular differences in pituitary gland tissue before and after sexual maturation. Here, we identified a total of 15 cell clusters and constructed single-cell transcriptional profiles of rats before and after sexual maturation. Furthermore, focusing on the gonadotrope cluster, 106 genes were found to be differentially expressed before and after sexual maturation. It was verified that Spp1, which is specifically expressed in gonadotrope cells, could serve as a novel marker for this cell cluster and has a promotional effect on the synthesis and secretion of follicle-stimulating hormone. The results provide a new resource for further resolving the regulatory mechanism of pituitary gland development and pituitary hormone synthesis and secretion.

Reversibly Reactive Affinity Selection-Mass Spectrometry Enables Identification of Covalent Peptide Binders.

Covalent peptide binders have found applications as activity-based probes and as irreversible therapeutic inhibitors. Currently, there is no rapid, label-free, and tunable affinity selection platform to enrich covalent reactive peptide binders from synthetic libraries. We address this challenge by developing a reversibly reactive affinity selection platform termed ReAct-ASMS enabled by tandem high-resolution mass spectrometry (MS/MS) to identify covalent peptide binders to native protein targets. It uses mixed disulfide-containing peptides to build reversible peptide-protein conjugates that can enrich for covalent variants, which can be sequenced by MS/MS after reduction. Using this platform, we identified covalent peptide binders against two oncoproteins, human papillomavirus 16 early protein 6 (HPV16 E6) and peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 protein (Pin1). The resulting peptide binders efficiently and selectively cross-link Cys58 of E6 at 37 °C and Cys113 of Pin1 at room temperature, respectively. ReAct-ASMS enables the identification of highly selective covalent peptide binders for diverse molecular targets, introducing an applicable platform to assist preclinical therapeutic development pipelines.

Comparison of Different Fusion Radiomics for Predicting Benign and Malignant Sacral Tumors: A Pilot Study.

Differentiating between benign and malignant sacral tumors is crucial for determining appropriate treatment options. This study aims to develop two benchmark fusion models and a deep learning radiomic nomogram (DLRN) capable of distinguishing between benign and malignant sacral tumors using multiple imaging modalities. We reviewed axial T2-weighted imaging (T2WI) and non-contrast computed tomography (NCCT) of 134 patients pathologically confirmed as sacral tumors. The two benchmark fusion models were developed using fusion deep learning (DL) features and fusion classical machine learning (CML) features from multiple imaging modalities, employing logistic regression, K-nearest neighbor classification, and extremely randomized trees. The two benchmark models exhibiting the most robust predictive performance were merged with clinical data to formulate the DLRN. Performance assessment involved computing the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, negative predictive value (NPV), and positive predictive value (PPV). The DL benchmark fusion model demonstrated superior performance compared to the CML fusion model. The DLRN, identified as the optimal model, exhibited the highest predictive performance, achieving an accuracy of 0.889 and an AUC of 0.961 in the test sets. Calibration curves were utilized to evaluate the predictive capability of the models, and decision curve analysis (DCA) was conducted to assess the clinical net benefit of the DLR model. The DLRN could serve as a practical predictive tool, capable of distinguishing between benign and malignant sacral tumors, offering valuable information for risk counseling, and aiding in clinical treatment decisions.

Lymphatic plastic bronchitis and primary chylothorax: A study based on computed tomography lymphangiography.

BACKGROUND: This study presents an evaluation of the computed tomography lymphangiography (CTL) features of lymphatic plastic bronchitis (PB) and primary chylothorax to improve the diagnostic accuracy for these two diseases. AIM: To improve the diagnosis of lymphatic PB or primary chylothorax, a retrospective analysis of the clinical features and CTL characteristics of 71 patients diagnosed with lymphatic PB or primary chylothorax was performed. METHODS: The clinical and CTL data of 71 patients (20 with lymphatic PB, 41 with primary chylothorax, and 10 with lymphatic PB with primary chylothorax) were collected retrospectively. CTL was performed in all patients. The clinical manifestations, CTL findings, and conventional chest CT findings of the three groups of patients were compared. The chi-square test or Fisher's exact test was used to compare the differences among the three groups. A difference was considered to be statistically significant when P < 0.05. RESULTS: (1) The percentages of abnormal contrast medium deposits on CTL in the three groups were as follows: Thoracic duct outlet in 14 (70.0%), 33 (80.5%) and 8 (80.0%) patients; peritracheal region in 18 (90.0%), 15 (36.6%) and 8 (80.0%) patients; pleura in 6 (30.0%), 33 (80.5%) and 9 (90.0%) patients; pericardium in 6 (30.0%), 6 (14.6%) and 4 (40.0%) patients; and hilum in 16 (80.0%), 11 (26.8%) and 7 (70.0%) patients; and (2) the abnormalities on conventional chest CT in the three groups were as follows: Ground-glass opacity in 19 (95.0%), 18 (43.9%) and 8 (80.0%) patients; atelectasis in 4 (20.0%), 26 (63.4%) and 7 (70.0%) patients; interlobular septal thickening in 12 (60.0%), 11 (26.8%) and 3 (30.0%) patients; bronchovascular bundle thickening in 14 (70.0%), 6 (14.6%) and 4 (40.0%) patients; localized mediastinal changes in 14 (70.0%), 14 (34.1%), and 7 (70.0%) patients; diffuse mediastinal changes in 6 (30.0%), 5 (12.2%), and 3 (30.0%) patients; cystic lesions in the axilla in 2 (10.0%), 6 (14.6%), and 2 (20.0%) patients; and cystic lesions in the chest wall in 0 (0%), 2 (4.9%), and 2 (4.9%) patients. CONCLUSION: CTL is well suited to clarify the characteristics of lymphatic PB and primary chylothorax. This method is an excellent tool for diagnosing these two diseases.

GnRH-driven FTO-mediated RNA m6A modification promotes gonadotropin synthesis and secretion.

BACKGROUND: Gonadotropin precisely controls mammalian reproductive activities. Systematic analysis of the mechanisms by which epigenetic modifications regulate the synthesis and secretion of gonadotropin can be useful for more precise regulation of the animal reproductive process. Previous studies have identified many differential m6A modifications in the GnRH-treated adenohypophysis. However, the molecular mechanism by which m6A modification regulates gonadotropin synthesis and secretion remains unclear. RESULTS: Herein, it was found that GnRH can promote gonadotropin synthesis and secretion by promoting the expression of FTO. Highly expressed FTO binds to Foxp2 mRNA in the nucleus, exerting a demethylation function and reducing m6A modification. After Foxp2 mRNA exits the nucleus, the lack of m6A modification prevents YTHDF3 from binding to it, resulting in increased stability and upregulation of Foxp2 mRNA expression, which activates the cAMP/PKA signaling pathway to promote gonadotropin synthesis and secretion. CONCLUSIONS: Overall, the study reveals the molecular mechanism of GnRH regulating the gonadotropin synthesis and secretion through FTO-mediated m6A modification. The results of this study allow systematic interpretation of the regulatory mechanism of gonadotropin synthesis and secretion in the pituitary at the epigenetic level and provide a theoretical basis for the application of reproductive hormones in the regulation of animal artificial reproduction.

Upregulated lncRNA PRNT promotes progression and oxaliplatin resistance of colorectal cancer cells by regulating HIPK2 transcription.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer and a significant cause of cancer-related mortality globally. Resistance to chemotherapy, especially during CRC treatment, leads to reduced effectiveness of drugs and poor patient outcomes. Long noncoding RNAs (lncRNAs) have been implicated in various pathophysiological processes of tumor cells, including chemotherapy resistance, yet the roles of many lncRNAs in CRC remain unclear. AIM: To identify and analyze the lncRNAs involved in oxaliplatin resistance in CRC and to understand the underlying molecular mechanisms influencing this resistance. METHODS: Gene Expression Omnibus datasets GSE42387 and GSE30011 were reanalyzed to identify lncRNAs and mRNAs associated with oxaliplatin resistance. Various bioinformatics tools were employed to elucidate molecular mechanisms. The expression levels of lncRNAs and mRNAs were assessed via quantitative reverse transcription-polymerase chain reaction. Functional assays, including MTT, wound healing, and Transwell, were conducted to investigate the functional implications of lncRNA alterations. Interactions between lncRNAs and transcription factors were examined using RIP and luciferase reporter assays, while Western blotting was used to confirm downstream pathways. Additionally, a xenograft mouse model was utilized to study the in vivo effects of lncRNAs on chemotherapy resistance. RESULTS: LncRNA prion protein testis specific (PRNT) was found to be upregulated in oxaliplatin-resistant CRC cell lines and negatively correlated with homeodomain interacting protein kinase 2 (HIPK2) expression. PRNT was demonstrated to sponge transcription factor zinc finger protein 184 (ZNF184), which in turn could regulate HIPK2 expression. Altered expression of PRNT influenced CRC cell sensitivity to oxaliplatin, with overexpression leading to decreased sensitivity and decreased expression reducing resistance. Both RIP and luciferase reporter assays indicated that ZNF184 and HIPK2 are targets of PRNT. The PRNT/ZNF184/HIPK2 axis was implicated in promoting CRC progression and oxaliplatin resistance both in vitro and in vivo. CONCLUSION: The study concludes that PRNT is upregulated in oxaliplatin-resistant CRC cells and modulates the expression of HIPK2 by sponging ZNF184. This regulatory mechanism enhances CRC progression and resistance to oxaliplatin, positioning PRNT as a promising therapeutic target for CRC patients undergoing oxaliplatin-based chemotherapy.

Neighbouring Synergy in High-Density Single Ir Atoms on CoGaOOH for Efficient Alkaline Electrocatalytic Oxygen Evolution.

The catalytic performance of single-atom catalysts was strictly limited by isolated single-atom sites. Fabricating high-density single atoms to realize the synergetic interaction in neighbouring single atoms could optimize the adsorption behaviors of reaction intermediates, which exhibited great potential to break performance limitations and deepen mechanistic understanding of electrocatalysis. However, the catalytic behavior governed by neighbouring single atoms is particularly elusive and has yet to be understood. Herein, we revealed that the synergetic interaction in neighbouring single atoms contributes to superior performance for oxygen evolution relative to isolated Ir single atoms. Neighbouring single atoms was achieved by fabricating high-density single atoms to narrow the distance between single atoms. Electrochemical measurements demonstrated that the Nei-Ir1/CoGaOOH with neighbouring Ir single atoms exhibited a low overpotential of 170 mV at a current density of 10 mA cm-2, and long-durable stability over 2000 h for oxygen evolution. Mechanistic studies revealed that neighbouring single atoms synergetic stabilized the *OOH intermediates via extra hydrogen bonding interactions, thus significantly reducing the reaction energy barriers, as compared to isolated Ir single atoms. The discovery of the synergetic interaction in neighbouring single atoms could offer guidance for the development of efficient electrocatalysts, thus accelerating the world's transition to sustainable energy.

The value of the dermal rim sign on nonenhanced magnetic resonance imaging for predicting dermal backflow in patients with primary lower extremity lymphedema.

PURPOSE: The dermal rim sign (DRS) on nonenhanced magnetic resonance imaging has been shown to predict dermal backflow (DBF) in patients with secondary upper limb lymphedema. However, whether the DRS has the same effects on primary lower extremity lymphedema (PLEL) has not been clearly reported. Therefore, this study aimed to explore whether the DRS can be used to diagnose DBF on lymphoscintigraphy in patients with PLEL. METHODS: A total of 94 patients who were diagnosed with PLEL were recruited for this retrospective study from January 2022 to December 2023. All the patients were divided into two groups according to the lymphoscintigraphy findings: no DBF and DBF. The magnetic resonance imaging data of the two groups were recorded and statistically compared for the following indicators: range of lymphedema involvement (left, right, whole lower limbs, only thigh, only calf and ankle), signs of lymphedema (notable thickening of skin, parallel line sign, grid sign, honeycomb sign, band sign, lymph lake sign, crescent sign, DRS), and lymphedema measurement (skin thickness, band width). The DRS is characterized by notable thickening of the skin plus the grid sign and/or honeycomb sign, plus the band sign. RESULTS: The following statistically significant differences in the following indicators were found between the two groups (P < .05): notable skin thickening, parallel line sign, grid sign, honeycomb sign, band sign, DRS, skin thickness, and band width. The sensitivity, specificity, and accuracy for predicting for DBF with the DRS was 82%, 64%, and 77%, respectively. CONCLUSIONS: This study confirmed good consistency between the DRS and DBF from the perspective of imaging. This tool is suitable for children, adolescents, and patients with contraindications to lymphoscintigraphy. The DRS has important value in assessing the severity of PLEL. The DRS is suggested for the clinical use of combined surgical treatment of PLEL.

Development and characterization of discontinuous atmospheric pressure interface - Dual pressure chamber miniature mass spectrometer.

Miniaturized mass spectrometers have become increasingly prevalent for real-time detection and analysis, owing to their compact size and portability. The pursuit of performance enhancement in these instruments is a pivotal objective within the domain of mass spectrometry miniaturization. This study introduces a novel miniature mass spectrometer featuring a discontinuous atmospheric pressure interface and a dual pressure chamber. Compared to conventional single-chamber, discontinuous sampling interface mass spectrometers, the newly developed instrument demonstrates a more than tenfold improvement in detection efficiency. This significant enhancement is achieved without the need for complex control of switch coupling time series, thereby streamlining the circuit design and improving the instrument's fault tolerance. Furthermore, by capitalizing on the benefits of discontinuous sampling, the instrument reduces the operational pressure relative to traditional continuous sampling in differential pressure vacuum chambers. It accommodates larger inlet capillary (0.38 mm) and skimmer (0.5 mm) diameters, leading to a ninefold increase in response strength for risperidone and lowering the detection limit to 0.5 ppb. The instrument's capacity for rapid drug detection, along with enhanced resolution and detection limits, underscores its potential utility. Additionally, it facilitates the use of smaller mechanical pumps, significantly diminishing both the instrument's volume and power consumption. This presents a promising avenue for further miniaturization of mass spectrometers.

Substrate recruitment via eIF2γ enhances catalytic efficiency of a holophosphatase that terminates the integrated stress response.

Dephosphorylation of pSer51 of the α subunit of translation initiation factor 2 (eIF2αP) terminates signaling in the integrated stress response (ISR). A trimeric mammalian holophosphatase comprised of a protein phosphatase 1 (PP1) catalytic subunit, the conserved C-terminally located ~70 amino acid core of a substrate-specific regulatory subunit (PPP1R15A/GADD34 or PPP1R15B/CReP) and G-actin (an essential cofactor) efficiently dephosphorylate eIF2αP in vitro. Unlike their viral or invertebrate counterparts, with whom they share the conserved 70 residue core, the mammalian PPP1R15s are large proteins of more than 600 residues. Genetic and cellular observations point to a functional role for regions outside the conserved core of mammalian PPP1R15A in dephosphorylating its natural substrate, the eIF2 trimer. We have combined deep learning technology, all-atom molecular dynamics simulations, X-ray crystallography, and biochemistry to uncover binding of the γ subunit of eIF2 to a short helical peptide repeated four times in the functionally important N terminus of human PPP1R15A that extends past its conserved core. Binding entails insertion of Phe and Trp residues that project from one face of an α-helix formed by the conserved repeats of PPP1R15A into a hydrophobic groove exposed on the surface of eIF2γ in the eIF2 trimer. Replacing these conserved Phe and Trp residues with Ala compromises PPP1R15A function in cells and in vitro. These findings suggest mechanisms by which contacts between a distant subunit of eIF2 and elements of PPP1R15A distant to the holophosphatase active site contribute to dephosphorylation of eIF2αP by the core PPP1R15 holophosphatase and to efficient termination of the ISR in mammals.

Three Polyoxometalate-Based Ag-Organic Compounds as Heterogeneous Catalysts for the Synthesis of Benzimidazoles.

Three new POM-based compounds, with formulae [Na0.63Ag3(Htba)2.37(tba)0.63(H2O)2(PMo12O40)]·4H2O (Ag3PMo), [Ag4(Htba)4(H2O)2(PMo12O40)](NO3)·H2O (Ag4PMo), and [Ag3(Htba)2(tba)(PW12O40)0.5](NO3)0.5·13H2O (Ag3PW), were prepared with a 3-(4H-1,2,4-triazol-4-yl)benzoic acid (Htba) ligand, Keggin-type anions ([PMo12O40]3-/[PW12O40]3-), and a silver ion (Ag+). The structural features of these compounds are particularly different from the multinuclear subunits, which are [Ag3(tba)3] clusters in Ag3PMo, [Ag4(tba)3] chains in Ag4PMo, and [Ag3(tba)3]2 clusters in Ag3PW, connected by multidonor atom tba ligands and Ag+ ions. Meanwhile, in these compounds, polyanions act as polydentate ligands to link adjacent Ag-tba metal-organic units and expand their spatial dimensions. These compounds, as heterogeneous catalysts, exhibit high stability and excellent catalytic activity to construct benzimidazoles. Ag3PMo could efficiently catalyze the condensation of benzene-1,2-diamines and benzaldehydes and produce benzimidazoles in good yields. In addition, Ag3PMo could be reused up to 7 times and was suitable for gram-scale reactions.

Metabolome and microbiome analyses of the anti-fatigue mechanism of Acanthopanax senticosus leaves.

Acanthopanax senticosus leaves, widely used as a vegetable and tea, are reported to be beneficial in treating neurological disorders. At present, their anti-fatigue effect remains to be established. In this study, we analyzed the composition of the extracts from A. senticosus leaves and confirmed their antioxidant and anti-inflammatory properties at the cellular level. In mice subjected to exhaustive running on a treadmill, supplementation with A. senticosus leaf extracts enhanced exercise performance and alleviated fatigue via the reversal of exercise-induced 5-HT elevation, metabolic waste accumulation, organ damage, and glucose metabolism-related gene expression. The collective findings from microbiome and metabolomic analyses indicate that A. senticosus leaf extracts increase α-diversity, regulate microbial composition, and reverse exercise-mediated disruption of carbohydrate, creatine, amino acid, and trimethylamine metabolism. This study provides preliminary evidence for the utility of A. senticosus leaves as a promising anti-fatigue food and offers insights into the underlying mechanism.

Structure of the p53 degradation complex from HPV16.

Human papillomavirus (HPV) is a significant contributor to the global cancer burden, and its carcinogenic activity is facilitated in part by the HPV early protein 6 (E6), which interacts with the E3-ligase E6AP, also known as UBE3A, to promote degradation of the tumor suppressor, p53. In this study, we present a single-particle cryoEM structure of the full-length E6AP protein in complex with HPV16 E6 (16E6) and p53, determined at a resolution of ~3.3 Å. Our structure reveals extensive protein-protein interactions between 16E6 and E6AP, explaining their picomolar binding affinity. These findings shed light on the molecular basis of the ternary complex, which has been pursued as a potential therapeutic target for HPV-driven cervical, anal, and oropharyngeal cancers over the last two decades. Understanding the structural and mechanistic underpinnings of this complex is crucial for developing effective therapies to combat HPV-induced cancers. Our findings may help to explain why previous attempts to disrupt this complex have failed to generate therapeutic modalities and suggest that current strategies should be reevaluated.

Activation of autophagy promotes the inhibitory effect of curcumin analog EF-24 against MDA-MB-231 cancer cells.

Breast cancer is the leading cause of cancer deaths in women worldwide. EF-24, an analog of curcumin, has been shown to possess promising anticancer effects. However, the underlying mechanism remains elusive. In the present study, the inhibitory effect of EF-24 against one breast cancer cell line, MDA-MB-231, and its anti-migration ability were assessed by MTT, wound healing, and Transwell assay. Furthermore, we found that EF-24 could induce initiation of autophagy as evidenced by fluorescence and electron microscope observation. EF-24 also induced mitochondrial apoptosis in MDA-MB-231 cells as detected by Hoechst 33342 staining, flow cytometry analysis, and western blot analysis. In addition, the early autophagy inhibitor 3-MA could reduce the cleavage of PARP protein and protect cells from EF-24-induced apoptosis, while the autophagy inducer (rapamycin) could enhance the anticancer effect of EF-24 in MDA-MB-231 cells, which suggest that EF-24 induces crosstalk between autophagy and apoptosis, which herein participate in the antiproliferative effect of EF-24 in breast cancer cells. Moreover, removal of EF-24-activated ROS with NAC significantly reversed migration ability of MDA-MB-231 cells, indicating that EF-24 exerted an inhibitory effect through a ROS-mediating pathway. These results will help to elucidate the antitumor mechanism of curcumin analogs and to explore future potential clinical applications.

MRI-Based Machine Learning Fusion Models to Distinguish Encephalitis and Gliomas.

This paper aims to compare the performance of the classical machine learning (CML) model and the deep learning (DL) model, and to assess the effectiveness of utilizing fusion radiomics from both CML and DL in distinguishing encephalitis from glioma in atypical cases. We analysed the axial FLAIR images of preoperative MRI in 116 patients pathologically confirmed as gliomas and clinically diagnosed with encephalitis. The 3 CML models (logistic regression (LR), support vector machine (SVM) and multi-layer perceptron (MLP)), 3 DL models (DenseNet 121, ResNet 50 and ResNet 18) and a deep learning radiomic (DLR) model were established, respectively. The area under the receiver operating curve (AUC) and sensitivity, specificity, accuracy, negative predictive value (NPV) and positive predictive value (PPV) were calculated for the training and validation sets. In addition, a deep learning radiomic nomogram (DLRN) and a web calculator were designed as a tool to aid clinical decision-making. The best DL model (ResNet50) consistently outperformed the best CML model (LR). The DLR model had the best predictive performance, with AUC, sensitivity, specificity, accuracy, NPV and PPV of 0.879, 0.929, 0.800, 0.875, 0.867 and 0.889 in the validation sets, respectively. Calibration curve of DLR model shows good agreement between prediction and observation, and the decision curve analysis (DCA) indicated that the DLR model had higher overall net benefit than the other two models (ResNet50 and LR). Meanwhile, the DLRN and web calculator can provide dynamic assessments. Machine learning (ML) models have the potential to non-invasively differentiate between encephalitis and glioma in atypical cases. Furthermore, combining DL and CML techniques could enhance the performance of the ML models.