Punicalagin Restricts Growth, Promotes Apoptosis, and Reduces Invasion in Human Gastric Cancer Cells.

This research investigated the anticancer properties of punicalagin, a prominent bioactive polyphenol extracted from Punica granatum L, in human gastric cancer cell lines. Normal and gastric cancer cells were exposed to different doses of punicalagin for various durations. Punicalagin exhibited cytotoxic effects on gastric cancer cells in a dose- and time-dependent fashion, while sparing normal gastric epithelial cells. It is noteworthy that among the 3 gastric cancer cells, HGC-27 cells were more resistant to punicalagin than 23,132/87 and AGS cells. Furthermore, punicalagin triggered apoptosis in gastric cancer cells, evidenced by a rise in both early and late apoptotic cell percentages. Western blot analysis further revealed that punicalagin elevated the levels of activated caspase-3. Conversely, punicalagin curtailed cell invasion and reduced the expression of MMP-2, MMP-9, Snail, and Slug. From a mechanistic standpoint, Western blotting indicated that punicalagin might inhibit the Erk and NF-κB pathways, leading to apoptosis induction and the inhibition of cell invasion in gastric cancer cells. These results indicate that punicalagin promotes apoptosis and inhibits cell invasion in gastric cancer cells by activating caspase-3 and suppressing MMP-2, MMP-9, Snail, and Slug through the inhibition of the Erk and NF-κB pathways.

Integrated Single-cell and Transcriptome Sequencing Analyses Identified PREX1 as an Immune-related Prognostic Biomarker for Liver Hepatocellular Carcinoma.

Background: PtdIns (3,4,5) P3-dependent Rac exchanger 1 (PREX1), also known as PREX1, a member of the Rac guanine nucleotide exchange factors (Rac-GEF) family. Studies have suggested that PREX1 plays a role in mediating oncogenic pathway activation and controlling various biological mechanisms in different types of cancer, including liver hepatocellular carcinoma (LIHC). However, the function of PREX1 in the pathogenesis of LIHC and its potential role on immunological regulation is not clearly elucidated. Methods: The expression level and the clinical role of PREX1 in LIHC was analyzed based on database from the Cancer Genome Atlas (TCGA), TNM plotter and University of Alabama Cancer Database (UALCAN). We investigated the relationship between PREX1 and immunity in LIHC by TISIDB, CIBERSORT and single cell analysis. Immunotherapy responses were assessed by the immunophenoscores (IPS). Moreover, biological functional assays were performed to further investigate the roles of PREX1 in liver cancer cell lines. Results: Higher expression of PREX1 in LIHC tissues than in normal liver tissues was found based on public datasets. Further analysis revealed that PREX1 was associated with worse clinical characteristics and dismal prognosis. Pathway enrichment analysis indicated that PREX1 participated in immune-related pathways. Through CIBERSORT and single cell analysis, we found a remarkable correlation between the expression of PREX1 and various immune cells, especially macrophages. In addition, high PREX1 expression was found to be associated with a stronger response to immunotherapy. Furthermore, in vitro assays indicated that depletion of PREX1 can suppress invasion and proliferation of LIHC cells. Conclusion: Elevated expression of PREX1 indicates poor prognosis, influences immune modulation and predicts sensitivity of immunosuppression therapy in LIHC. Our results suggested that PREX1 may be a prognostic biomarker and therapeutic target, offering new treatment options for LIHC.

Projected performance of Si- and 2D-material-based SRAM circuits ranging from 16 nm to 1 nm technology nodes.

Researchers have been developing 2D materials (2DM) for electronics, which are widely considered a possible replacement for silicon in future technology. Two-dimensional transition metal dichalcogenides are the most promising among the different materials due to their electronic performance and relatively advanced development. Although field-effect transistors (FETs) based on 2D transition metal dichalcogenides have been found to outperform Si in ultrascaled devices, the comparison of 2DM-based and Si-based technologies at the circuit level is still missing. Here we compare 2DM- and Si FET-based static random-access memory (SRAM) circuits across various technology nodes from 16 nm to 1 nm and reveal that the 2DM-based SRAM exhibits superior performance in terms of stability, operating speed and energy efficiency when compared with Si SRAM. This study utilized technology computer-aided design to conduct device and circuit simulations, employing calibrated MoS2 nFETs and WSe2 pFETs. It incorporated layout design rules across various technology nodes to comprehensively analyse their SRAM functionality. The results show that, compared with three-dimensional structure Si transistors at 1 nm node, the planar 2DMFETs exhibited lower capacitance, leading to reduced cell read access time (-16%), reduced time to write (-72%) and lowered dynamic power (-60%). The study highlights the provisional benefits of using planar 2DM transistors to mitigate the performance degradation caused by reduced metal pitch and increased wire resistance in advanced nodes, potentially opening up exciting possibilities for high-performance and low-power circuit applications.

Excited-State Charge Transfer Coupling from Quasiparticle Energy Density Functional Theory.

The recently developed Quasiparticle Energy (QE) scheme, based on a DFT calculation with one more (or less) electron, offers a good description of excitation energies, even with charge transfer characters. In this work, QE is further extended to calculate electron transfer (ET) couplings involving two excited states. We tested it with a donor-acceptor complex, consisting of a furan and a 1,1-dicyanoethylene (DCNE), in which two low lying charge transfer and local excitation states are involved. With generalized Mülliken-Hush and fragment charge-difference schemes, couplings from the QE approach generally agree well with those obtained from TDDFT, except that QE couplings exhibit better exponential distance dependence. Couplings from half-energy gaps with an external field are also calculated and reported. Our results show that the QE scheme is robust in calculating ET couplings with greatly reduced computational time.

Identification of prognostic biomarkers for cholangiocarcinoma by combined analysis of molecular characteristics of clinical MVI subtypes and molecular subtypes.

Cholangiocarcinoma (CCA) is widely noted for its high degree of malignancy, rapid progression, and limited therapeutic options. This study was carried out on transcriptome data of 417 CCA samples from different anatomical locations. The effects of lipid metabolism related genes and immune related genes as CCA classifiers were compared. Key genes were derived from MVI subtypes and better molecular subtypes. Pathways such as epithelial mesenchymal transition (EMT) and cell cycle were significantly activated in MVI-positive group. CCA patients were classified into three (four) subtypes based on lipid metabolism (immune) related genes, with better prognosis observed in lipid metabolism-C1, immune-C2, and immune-C4. IPTW analysis found that the prognosis of lipid metabolism-C1 was significantly better than that of lipid metabolism-C2 + C3 before and after correction. KRT16 was finally selected as the key gene. And knockdown of KRT16 inhibited proliferation, migration and invasion of CCA cells.

Climate sensitivity and relative humidity changes in global storm-resolving model simulations of climate change.

The climate simulation frontier of a global storm-resolving model (GSRM; or k-scale model because of its kilometer-scale horizontal resolution) is deployed for climate change simulations. The climate sensitivity, effective radiative forcing, and relative humidity changes are assessed in multiyear atmospheric GSRM simulations with perturbed sea-surface temperatures and/or carbon dioxide concentrations. Our comparisons to conventional climate model results can build confidence in the existing climate models or highlight important areas for additional research. This GSRM's climate sensitivity is within the range of conventional climate models, although on the lower end as the result of neutral, rather than amplifying, shortwave feedbacks. Its radiative forcing from carbon dioxide is higher than conventional climate models, and this arises from a bias in climatological clouds and an explicitly simulated high-cloud adjustment. Last, the pattern and magnitude of relative humidity changes, simulated with greater fidelity via explicitly resolving convection, are notably similar to conventional climate models.

Enzyme-activatable charge transfer in gold nanoclusters.

Surface-protecting ligands, as a major component of metal nanoclusters (MNCs), can dominate molecular characteristics, performance behaviors, and biological properties of MNCs, which brings diversity and flexibility to the nanoclusters and largely promotes their applications in optics, electricity, magnetism, catalysis, biology, and other fields. We report herein the design of a new kind of water-soluble luminescent gold nanoclusters (AuNCs) for enzyme-activatable charge transfer (CT) based on the ligand engineering of AuNCs with 6-mercaptopurine ribonucleoside (MPR). This elaborately designed cluster, Au5(MPR)2, can form a stable intramolecular CT state after light excitation, and exhibits long-lived color-tunable phosphorescence. After the cleavage by purine nucleoside phosphorylase (PNP), the CT triplet state can be easily directed to a low-lying energy level, leading to a bathochromic shift of the emission band accompanied by weaker and shorter-lived luminescence. Remarkably, these ligand-engineered AuNCs show high affinity towards PNP as well as decent performance for analyzing and visualizing enzyme activity and related drugs. The work of this paper provides a good example for diversifying physicochemical properties and application scenarios of MNCs by rational ligand engineering, which will facilitate future interest and new strategies to precisely engineer solution-based nanocluster materials.

Impact of traumatic brain injury on risk for schizophrenia and bipolar disorder.

The impact of traumatic brain injury (TBI) on subsequent risk of schizophrenia (SCZ) or bipolar disorder (BD) remains contested. Possible genetic and environmental confounding effects have also been understudied. Therefore, we aim to investigate the impact of TBI on the risk of SCZ and BD and whether the effect varies by injury severity, age at injury, and sex. We identified 4,184 SCZ and 18,681 BD cases born between 1973 and 1998 in the Swedish National Registers. Case-control samples matched (1:5) on birth year, sex, and birthplace were created along with a family design study, with cases matched to non-case full siblings. TBI was associated with higher risk of SCZ and BD (IRR=1.33 for SCZ, IRR=1.78 for BD). The association remained significant in the sibling comparison study. Moderate or severe TBI was associated with higher risk for both SCZ and BD compared to mild TBI. Older age at injury was associated with higher risk of SCZ and BD, and the effect of TBI was stronger in women than men. Findings indicate that TBI is a risk factor for both SCZ and BD with differential impact by age, severity and sex and that this association cannot be explained by familial confounding alone.

Prognostic factors for patients with pathologic T1-T2N+ esophageal squamous cell carcinoma: A retrospective study with external validation.

BACKGROUND: Lymph node metastasis is significantly associated with a worse prognosis in patients with localized early-stage esophageal squamous cell carcinoma. This study aimed to explore the prognostic factors and develop a nomogram for predicting survival in patients with pathologic T1-2N+ esophageal squamous cell carcinoma. METHODS: Between 2014 and 2022, patients with pT1-2N+ esophageal squamous cell carcinoma who underwent esophagectomy with lymphadenectomy at 2 institutes were reviewed and assigned to training and external validation cohorts. Independent prognostic factors were identified via univariate and multivariate Cox regression analyses. The nomogram model was developed and evaluated by the area under the receiver operating characteristic curve and calibration curve. RESULTS: In total, 268 patients with a median age of 65 years (range, 40-82) were included and assigned to training (n = 190) and external validation (n = 78) cohorts. The Cox proportional hazards model demonstrated that body mass index (P = .031), surgical approach (P < .001), T stage (P = .015), and Clavien-Dindo classification (P < .001) were independent prognostic factors in the training cohort. The nomogram showed good discrimination, with an area under the receiver operating characteristic curve for 1-year, 3-year, and 5-year of 0.810, 0.789, and 0.809 in the training cohort and 0.782, 0.679, and 0.698 in the validation cohort. The calibration curve showed that the predicted survival probability was in good agreement with the actual survival probability. CONCLUSION: Lower body mass index, left surgical approach, T2 stage, and Clavien-Dindo classification grade III to V were related to worse prognosis in patients with pT1-T2N+ esophageal squamous cell carcinoma. The developed nomogram may predict individual survival accurately.

Characteristics of painful temporomandibular disorders and their influence on jaw functional limitation and oral health-related quality of life.

BACKGROUND: There is limited knowledge about the impact of painful temporomandibular disorders (TMDs) and pain characteristics on jaw functional limitation and oral health-related quality of life (OHRQoL) in TMD patients. OBJECTIVES: The influence of painful TMDs and pain characteristics on jaw functional limitation and OHRQoL was investigated. Inter-relationships between limitation in jaw function and various OHRQoL domains, along with facial pain attributes predicting impaired jaw function and diminished OHRQoL were also examined. METHODS: TMD patients were recruited from a university-based hospital. A comprehensive questionnaire comprising demographic variables, the DC/TMD Symptom Questionnaire, Graded Chronic Pain Scale, Jaw Functional Limitation Scale-8 (JFLS-8) and Oral Health Impact Profile-TMD (OHIP-TMD) was administered. Participants underwent a protocolized physical examination, and TMD diagnoses were determined utilising the DC/TMD algorithms. Participants were subsequently stratified into intra-articular/pain-related/combined TMD groups, as well as no TMD pain, acute/chronic pain and low/high-intensity pain groups. Data were assessed using non-parametric and hierarchical linear regression analyses (α = .05). RESULTS: The final sample consisted of 280 participants (mean age 31.2 (SD 11.8) years; 79.3% women). Significant differences in pain characteristics, JFLS-8, and global OHIP scores were observed across the various TMD subtypes, pain chronicity and pain intensity categories. Pain intensity and pain-related interference exhibited moderate correlations with JFLS-8 and global OHIP scores (rs = 0.53-0.60). Moderate associations were also noted between JFLS-8 and global OHIP, as well as most OHIP domains (rs = 0.42-0.64). Both jaw functional limitation and OHRQoL were predicted by sex, pain intensity and pain-related interference. CONCLUSIONS: Sex, pain intensity and pain-related interference are key determinants for both impaired jaw function and diminished OHRQoL, with pain-related interference exerting a more pronounced effect.

Standards-Free Absolute Quantitation of Oxidizable Glycopeptides by Coulometric Mass Spectrometry.

Currently, glycopeptide quantitation is mainly based on relative quantitation due to absolute quantitation requiring isotope-labeled or standard glycopeptides which may not be commercially available or are very costly and time consuming to synthesize. To address this grand challenge, coulometric mass spectrometry (CMS), based on the combination of electrochemistry (EC) and mass spectrometry (MS), was utilized to quantify electrochemically active glycopeptides without the need of using standard materials. In this study, we studied tyrosine-containing glycopeptides, NYIVGQPSS(ß-GlcNAc)TGNL-OH and NYSVPSS(ß-GlcNAc)TGNL-OH, and successfully quantified them directly with CMS with a discrepancy of less than 5% between the CMS measured amount and the theoretical amount. Taking one step further, we applied this approach to quantify glycopeptides generated from the digestion of NIST mAb, a monoclonal antibody reference material. Through HILIC column separation, five N297 glycopeptides resulting from NIST mAb tryptic digestion were successfully separated and quantified by CMS for an absolute amount without the use of any standard materials. This study indicates the potential utility of CMS for quantitative proteomics research.

Rehabilitation Program for Postlaryngectomy Patients Following Ileocolon Flap Transfer for Voice Reconstruction: An Essential Part of Success.

BACKGROUND: Speech restoration is important for communication and social activities after pharyngolaryngectomy in head and neck cancer or corrosive injury. Several techniques of voice restoration have been developed to improve life quality. The aim of this paper was to focus on the microsurgical transfer of ileocolon flap and outcome of further voice rehabilitation. PATIENTS AND METHODS: From 2010 to 2022, 69 patients had ileocolon flap at our hospital with postoperative speech training and regular follow-up for over 1 year. The patients received deglutition training first, followed by voice rehabilitation. Voice outcomes were evaluated at an interval of 3 months and finally at 12 months of voice training rehabilitation. Among other examinations, the speech function was evaluated using a 4-point Likert scale and senior surgeon (H-c.C.) scoring system. RESULTS: The results showed that speech function reached 13.1% of excellent voice, 65.1% of good voice, 13.1% of fair result, and 8.7% of poor result by Likert scales. Meanwhile, the senior surgeon (H-c.C.) score showed 17.4% of excellent, 63.8% of moderate, and 18.8% of poor results. About voice laboratory results, maximal phonation time was 11.0 seconds, and the average number counted in one breath was 15. Loudness and frequency showed 56.0 dB and 105.0 Hz, respectively. CONCLUSION: The study showed that after voice reconstruction with ileocolon flap followed by the voice rehabilitation program, the patients would have a better understanding of the altered anatomical structures and practice in a more efficient way. Adequate recommendation by the therapists to plastic surgeons for revision surgeries optimized voice function of the patients.

Structural and mechanistic investigations on CC bond forming α-oxoamine synthase allowing L-glutamate as substrate.

Carbon­carbon (C-C) bonds serve as the fundamental structural backbone of organic molecules. As a critical CC bond forming enzyme, α-oxoamine synthase is responsible for the synthesis of α-amino ketones by performing the condensation reaction between amino acids and acyl-CoAs. We previously identified an α-oxoamine synthase (AOS), named as Alb29, involved in albogrisin biosynthesis in Streptomyces albogriseolus MGR072. This enzyme belongs to the α-oxoamine synthase family, a subfamily under the pyridoxal 5'-phosphate (PLP) dependent enzyme superfamily. In this study, we report the crystal structures of Alb29 bound to PLP and L-Glu, which provide the atomic-level structural insights into the substrate recognition by Alb29. We discover that Alb29 can catalyze the amino transformation from L-Gln to L-Glu, besides the condensation of L-Glu with ß-methylcrotonyl coenzyme A. Subsequent structural analysis has revealed that one flexible loop in Alb29 plays an important role in both amino transformation and condensation. Based on the crystal structure of the S87G mutant in the loop region, we capture two distinct conformations of the flexible loop in the active site, compared with the wild-type Alb29. Our study offers valuable insights into the catalytic mechanism underlying substrate recognition of Alb29.

[Identification of Protein-Coding Gene Markers in Breast Invasive Carcinoma Based on Machine Learning].

Objective To screen out the biomarkers linked to prognosis of breast invasive carcinoma based on the analysis of transcriptome data by random forest (RF),extreme gradient boosting (XGBoost),light gradient boosting machine (LightGBM),and categorical boosting (CatBoost). Methods We obtained the expression data of breast invasive carcinoma from The Cancer Genome Atlas and employed DESeq2,t-test,and Cox univariate analysis to identify the differentially expressed protein-coding genes associated with survival prognosis in human breast invasive carcinoma samples.Furthermore,RF,XGBoost,LightGBM,and CatBoost models were established to mine the protein-coding gene markers related to the prognosis of breast invasive cancer and the model performance was compared.The expression data of breast cancer from the Gene Expression Omnibus was used for validation. Results A total of 151 differentially expressed protein-coding genes related to survival prognosis were screened out.The machine learning model established with C3orf80,UGP2,and SPC25 demonstrated the best performance. Conclusions Three protein-coding genes (UGP2,C3orf80,and SPC25) were screened out to identify breast invasive carcinoma.This study provides a new direction for the treatment and diagnosis of breast invasive carcinoma.

Doxycycline cotherapy with albendazole relieves neural function damage in C57BL/6 and BALB/c mice infected with Angiostrongylus cantonensis.

BACKGROUND: We investigated the effects of combination therapy albendazole and doxycycline in Angiostrongylus cantonensis-infected mice during early and late treatment. MATERIALS AND METHODS: C57BL/6 and BALB/c mice were divided into five groups: (i) uninfected, (ii) infected with A. cantonensis, (iii) infected + 10 mg/kg albendazole, (iv) infected + 25mg/kg doxycycline, and (v) infected + 10 mg/kg albendazole + 25 mg/kg doxycycline. We administered drugs in both early treatments started at 7-day post infections (dpi) and late treatments (14 dpi) to A. cantonensis-infected C57BL/6 and BALB/c mice. To assess the impact of these treatments, we employed the Morris water maze test to evaluate spatial learning and memory abilities, and the rotarod test to measure motor coordination and balance in C57BL/6 mice. Additionally, we monitored the expression of the cytokine IL-33 and GFAP in the brain of these mice using western blot analysis. RESULTS: In this study, A. cantonensis infection was observed to cause extensive cerebral angiostrongyliasis in C57BL/6 mice. This condition significantly affected their spatial learning and memory abilities, as assessed by the Morris water maze test, as well as their motor coordination, which was evaluated using the rotarod test. Early treatment with albendazole led to favorable recovery outcomes. Both C57BL/6 and BALB/c mice express IL-33 and GFAP after co-therapy. The differences of levels and patterns of IL-33 and GFAP expression in mice may be influenced by the balance between pro-inflammatory and anti-inflammatory signals within the immune system. CONCLUSIONS: Combination therapy with anthelmintics and antibiotics in the early stage of A. cantonensis infection, in C57BL/6 and BALB/c mice resulted in the death of parasites in the brain and reduced the subsequent neural function damage and slowed brain damage and neurobehavior impairment. This study suggests a more effective and novel treatment, and drug delivery method for brain lesions that can decrease the neurological damage of angiostrongyliasis patients.

Multidimensional Refinement Graph Convolutional Network With Robust Decouple Loss for Fine-Grained Skeleton-Based Action Recognition.

Graph convolutional networks (GCNs) have been widely used in skeleton-based action recognition. However, existing approaches are limited in fine-grained action recognition due to the similarity of interclass data. Moreover, the noisy data from pose extraction increase the challenge of fine-grained recognition. In this work, we propose a flexible attention block called channel-variable spatial-temporal attention (CVSTA) to enhance the discriminative power of spatial-temporal joints and obtain a more compact intraclass feature distribution. Based on CVSTA, we construct a multidimensional refinement GCN (MDR-GCN) that can improve the discrimination among channel-, joint-, and frame-level features for fine-grained actions. Furthermore, we propose a robust decouple loss (RDL) that significantly boosts the effect of the CVSTA and reduces the impact of noise. The proposed method combining MDR-GCN with RDL outperforms the known state-of-the-art skeleton-based approaches on fine-grained datasets, FineGym99 and FSD-10, and also on the coarse NTU-RGB + D 120 dataset and NTU-RGB + D X-view version. Our code is publicly available at https://github.com/dingyn-Reno/MDR-GCN.

Potential applications of artificial intelligence in image analysis in cornea diseases: a review.

Artificial intelligence (AI) is an emerging field which could make an intelligent healthcare model a reality and has been garnering traction in the field of medicine, with promising results. There have been recent developments in machine learning and/or deep learning algorithms for applications in ophthalmology-primarily for diabetic retinopathy, and age-related macular degeneration. However, AI research in the field of cornea diseases is relatively new. Algorithms have been described to assist clinicians in diagnosis or detection of cornea conditions such as keratoconus, infectious keratitis and dry eye disease. AI may also be used for segmentation and analysis of cornea imaging or tomography as an adjunctive tool. Despite the potential advantages that these new technologies offer, there are challenges that need to be addressed before they can be integrated into clinical practice. In this review, we aim to summarize current literature and provide an update regarding recent advances in AI technologies pertaining to corneal diseases, and its potential future application, in particular pertaining to image analysis.

Thermodynamic Origin-Based In Situ Electrochemical Construction of Reversible p-n Heterojunctions for Optimal Stability in Potassium Ion Storage.

Heterojunctions in electrode materials offer diverse improvements during the cycling process of energy storage devices, such as volume change buffering, accelerated ion/electron transfer, and better electrode structure integrity, however, obtaining optimal heterostructures with nanoscale domains remains challenging within constrained materials. A novel in situ electrochemical method is introduced to develop a reversible CuSe/PSe p-n heterojunction (CPS-h) from Cu3PSe4 as starting material, targeting maximum stability in potassium ion storage. The CPS-h formation is thermodynamically favorable, characterized by its superior reversibility, minimized diffusion barriers, and enhanced conversion post K+ interaction. Within CPS-h, the synergy of the intrinsic electric field and P-Se bonds enhance electrode stability, effectively countering the Se shuttling phenomenon. The specific orientation between CuSe and PSe leads to a 35° lattice mismatch generates large space at the interface, promoting efficient K ion migration. The Mott-Schottky analysis validates the consistent reversibility of CPS-h, underlining its electrochemical reliability. Notably, CPS-h demonstrates a negligible 0.005% capacity reduction over 10,000 half-cell cycles and remains stable through 2,000 and 4,000 cycles in full cells and hybrid capacitors, respectively. This study emphasizes the pivotal role of electrochemical dynamics in formulating highly stable p-n heterojunctions, representing a significant advancement in potassium-ion battery (PIB) electrode engineering.