Post-marketing safety concerns with elagolix: a disproportionality analysis of the FDA adverse event reporting system.

OBJECTIVE: Elagolix is approved for the treatment of moderate-to-severe pain associated with endometriosis. However, the long-term safety of elagolix in a large sample of real-world patients is unknown. METHODS: The U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) reports were collected and analyzed from January 2019 to June 2023. Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multi-item gamma Poisson shrinker (MGPS) algorithms, were employed in data mining to quantify the signals of elagolix-related adverse events (AEs). RESULTS: After removing the non-drug-related AE signals, we detected several AE signals such as hot flushes, bone pain, suicidal ideation, depression, and increased liver enzymes, which were known during the clinical trial phase. In addition to this, we detected several unexpected important AEs that were not mentioned in the drug insert, including cystitis interstitial, parosmia, and epiploic appendagitis. The median onset time of elagolix-associated AEs was 28.5 days. CONCLUSION: Our study provides a comprehensive picture of the safety of elagolix in the post-marketing setting, while also identifying potential new AE signals. These findings emphasize the importance of continued monitoring of the potential risks of elagolix.

Mechanisms involved in the regulation of mitochondrial quality control by PGAM5 in heart failure.

Heart failure refers to a group of clinical syndromes in which various heart diseases lead to the inability of cardiac output to meet the metabolic needs of the body's tissues. Cardiac metabolism requires enormous amounts of energy; thus, impaired myocardial energy metabolism is considered a key factor in the occurrence and development of heart failure. Mitochondria serve as the primary energy source for cardiomyocytes, and their regular functionality underpins healthy cardiac function. The mitochondrial quality control system is a crucial mechanism for regulating the functionality of cardiomyocytes, and any abnormality in this system can potentially impact the morphology and structure of mitochondria, as well as the energy metabolism of cardiomyocytes. PGAM5, a multifunctional protein, plays a key role in the regulation of mitochondrial quality control through multiple pathways. Therefore, abnormal PGAM5 function is closely related to mitochondrial damage. This article reviews the mechanism of PGAM5's involvement in the regulation of the mitochondrial quality control system in the occurrence and development of heart failure, thereby providing a theoretical basis for future in-depth research.

Silibinin attenuates TGF-ß2-induced fibrogenic changes in human trabecular meshwork cells by targeting JAK2/STAT3 and PI3K/AKT signaling pathways.

Transforming growth factor-ß2 (TGF-ß2) induced fibrogenic changes in human trabecular meshwork (HTM) cells have been implicated in trabecular meshwork (TM) damage and intraocular pressure (IOP) elevation in primary open-angle glaucoma (POAG) patients. Silibinin (SIL) exhibited anti-fibrotic properties in various organs and tissues. This study aimed to assess the effects of SIL on the TGF-ß2-treated HTM cells and to elucidate the underlying mechanisms. Our study found that SIL effectively inhibited HTM cell proliferation, attenuated TGF-ß2-induced cell migration, and mitigated TGF-ß2-induced reorganization of both actin and vimentin filaments. Moreover, SIL suppressed the expressions of fibronectin (FN), collagen type I alpha 1 chain (COL1A1), and alpha-smooth muscle actin (α-SMA) in the TGF-ß2-treated HTM cells. RNA sequencing indicated that SIL interfered with the phosphoinositide 3-kinase (PI3K)/protein kinase B (PKB, also known as AKT) signaling pathway, extracellular matrix (ECM)-receptor interaction, and focal adhesion in the TGF-ß2-treated HTM cells. Western blotting demonstrated SIL inhibited the activation of Janus kinase 2 (JAK2)/signal transducers and activators of transcription 3 (STAT3) and the downstream PI3K/AKT signaling pathways induced by TGF-ß2, potentially contributing to its inhibitory effects on ECM protein production in the TGF-ß2-treated HTM cells. Our study demonstrated the ability of SIL to inhibit TGF-ß2-induced fibrogenic changes in HTM cells. SIL could be a potential IOP-lowering agent by reducing the fibrotic changes in the TM tissue of POAG patients, which warrants further investigation through additional animal and clinical studies.

Hot-Injection Synthesis of Cesium Lead Halide Perovskite Nanowires with Tunable Optical Properties.

Metal halide perovskite semiconductors have emerged as promising materials for various optoelectronic applications due to their unique crystal structure and outstanding properties. Among different forms, perovskite nanowires (NWs) offer distinct advantages, including a high aspect ratio, superior crystallinity, excellent light absorption, and carrier transport properties, as well as unique anisotropic luminescence properties. Understanding the formation mechanism and structure-property relationship of perovskite NWs is crucial for exploring their potential in optoelectronic devices. In this study, we successfully synthesized all-inorganic halide perovskite NWs with high aspect ratios and an orthorhombic crystal phase using the hot-injection method with controlled reaction conditions and surface ligands. These NWs exhibit excellent optical and electrical properties. Moreover, precise control over the halogen composition through a simple anion exchange process enables the tuning of the bandgap, leading to fluorescence emission, covering a wide range of colors across the visible spectrum. Consequently, these perovskite NWs hold great potential for efficient energy conversion and catalytic applications in photoelectrocatalysis.

Impact of Carrier Gas Flow Rate on the Synthesis of Monolayer WSe2 via Hydrogen-Assisted Chemical Vapor Deposition.

Transition metal dichalcogenides (TMDs), particularly monolayer TMDs with direct bandgap properties, are key to advancing optoelectronic device technology. WSe2 stands out due to its adjustable carrier transport, making it a prime candidate for optoelectronic applications. This study explores monolayer WSe2 synthesis via H2-assisted CVD, focusing on how carrier gas flow rate affects WSe2 quality. A comprehensive characterization of monolayer WSe2 was conducted using OM (optical microscope), Raman spectroscopy, PL spectroscopy, AFM, SEM, XPS, HRTEM, and XRD. It was found that H2 incorporation and flow rate critically influence WSe2's growth and structural integrity, with low flow rates favoring precursor concentration for product formation and high rates causing disintegration of existing structures. This research accentuates the significance of fine-tuning the carrier gas flow rate for optimizing monolayer WSe2 synthesis, offering insights for fabricating monolayer TMDs like WS2, MoSe2, and MoS2, and facilitating their broader integration into optoelectronic devices.

Superdiffusive Rotation of Interfacial Water on Noble Metal Surface.

Interfacial water on a metal surface acts as an active layer through the reorientation of water, thereby facilitating the energy transfer and chemical reaction across the metal surface in various physicochemical and industrial processes. However, how this active interfacial water collectively behaves on flat noble metal substrates remains largely unknown due to the experimental limitation in capturing librational vibrational motion of interfacial water and prohibitive computational costs at the first-principles level. Herein, by implementing a machine-learning approach to train neural network potentials, we enable performing advanced molecular dynamics simulations with ab initio accuracy at a nanosecond scale to map the distinct rotational motion of water molecules on a metal surface at room temperature. The vibrational density of states of the interfacial water with two-layer profiles reveals that the rotation and vibration of water within the strong adsorption layer on the metal surface behave as if the water molecules in the bulk ice, wherein the O-H stretching frequency is well consistent with the experimental results. Unexpectedly, the water molecules within the adjacent weak adsorption layer exhibit superdiffusive rotation, contrary to the conventional diffusive rotation of bulk water, while the vibrational motion maintains the characteristic of bulk water. The mechanism underlying this abnormal superdiffusive rotation is attributed to the translation-rotation decoupling of water, in which the translation is restrained by the strong hydrogen bonding within the bilayer interfacial water, whereas the rotation is accelerated freely by the asymmetric water environment. This superdiffusive rotation dynamics may elucidate the experimentally observed large fluctuation of the potential of zero charge on Pt and thereby the conventional Helmholtz layer model revised by including the contribution of interfacial water orientation. The surprising superdiffusive rotation of vicinal water next to noble metals will shed new light on the physicochemical processes and the activity of water molecules near metal electrodes or catalysts.

Prevalence and Associations of Co-occurrence of NFE2L2 Mutations and Chromosome 3q26 Amplification in Lung Cancer.

Background NFE2L2 (nuclear factor erythroid-2-related factor-2) encodes a basic leucine zipper (bZIP) transcription factor and exhibits variations in various tumor types, including lung cancer. In this study, we comprehensively investigated the impact of simultaneous mutations on the survival of NFE2L2 -mutant lung cancer patients within specific subgroups. Methods A cohort of 1,103 lung cancer patients was analyzed using hybridization capture-based next-generation sequencing. Results The NFE2L2 gene had alterations in 3.0% (33/1,103) of lung cancer samples, including 1.5% (15/992) in adenocarcinoma and 16.2% (18/111) in squamous cell carcinoma. Thirty-four variations were found, mainly in exons 2 (27/34). New variations in exon 2 (p.D21H, p.V36_E45del, p.F37_E45del, p.R42P, p.E67Q, and p.L76_E78delinsQ) were identified. Some patients had copy number amplifications. Co-occurrence with TP53 (84.8%), CDKN2A (33.3%), KMT2B (33.3%), LRP1B (33.3%), and PIK3CA (27.3%) mutations was common. Variations of NFE2L2 displayed the tightest co-occurrence with IRF2 , TERC , ATR , ZMAT3 , and SOX2 ( p < 0.001). In The Cancer Genome Atlas Pulmonary Squamous Carcinoma project, patients with NFE2L2 variations and 3q26 amplification had longer median survival (63.59 vs. 32.04 months, p = 0.0459) and better overall survival. Conclusions NFE2L2 mutations display notable heterogeneity in lung cancer. The coexistence of NFE2L2 mutations and 3q26 amplification warrants in-depth exploration of their potential clinical implications and treatment approaches for affected patients.

Prediction and optimization method for welding quality of components in ship construction.

Welding process, as one of the crucial industrial technologies in ship construction, accounts for approximately 70% of the workload and costs account for approximately 40% of the total cost. The existing welding quality prediction methods have hypothetical premises and subjective factors, which cannot meet the dynamic control requirements of intelligent welding for processing quality. Aiming at the low efficiency of quality prediction problems poor timeliness and unpredictability of quality control in ship assembly-welding process, a data and model driven welding quality prediction method is proposed. Firstly, the influence factors of welding quality are analyzed and the correlation mechanism between process parameters and quality is determined. According to the analysis results, a stable and reliable data collection architecture is established. The elements of welding process monitoring are also determined based on the feature dimensionality reduction method. To improve the accuracy of welding quality prediction, the prediction model is constructed by fusing the adaptive simulated annealing, the particle swarm optimization, and the back propagation neural network algorithms. Finally, the effectiveness of the prediction method is verified through 74 sets of plate welding experiments, the prediction accuracy reaches over 90%.

Synthesis of Size-Adjustable CsPbBr3 Perovskite Quantum Dots for Potential Photoelectric Catalysis Applications.

As a direct band gap semiconductor, perovskite has the advantages of high carrier mobility, long charge diffusion distance, high defect tolerance and low-cost solution preparation technology. Compared with traditional metal halide perovskites, which regulate energy band and luminescence by changing halogen, perovskite quantum dots (QDs) have a surface effect and quantum confinement effect. Based on the LaMer nucleation growth theory, we have synthesized CsPbBr3 QDs with high dimensional homogeneity by creating an environment rich in Br- ions based on the general thermal injection method. Moreover, the size of the quantum dots can be adjusted by simply changing the reaction temperature and the concentration of Br- ions in the system, and the blue emission of strongly confined pure CsPbBr3 perovskite is realized. Finally, optical and electrochemical tests suggested that the synthesized quantum dots have the potential to be used in the field of photocatalysis.

Knowledge, attitude, and practice of atrial fibrillation in high altitude areas.

Background: To investigate the knowledge, attitude, and practice (KAP) of atrial fibrillation (AF) among the general population in high-altitude areas. Methodology: A web-based cross-sectional study was conducted among the general population in high-altitude areas. Results: A total of 786 valid questionnaires were enrolled, with a mean age of 34.75 ± 14.16 years. The mean score of knowledge, attitude and practice were 8.22 ± 6.50 (possible range: 0-10), 28.90 ± 5.63 (possible range: 8-40), 34.34 ± 6.44 (possible range: 9-45), respectively. The multivariate analysis showed that knowledge scores (OR = 1.108, 95% CI = 1.075-1.142, p < 0.001), attitude scores (OR = 1.118, 95% CI = 1.081-1.156, p < 0.001), and never smoking (OR = 2.438, 95% CI = 1.426-4.167, p = 0.001) were independently associated with proactive practice. The structural equation modeling (SEM) showed direct effect of knowledge on practice (p = 0.014), and attitude on practice (p = 0.004), while no effect of knowledge on attitude (p = 0.190). Conclusion: The general population in high-altitude regions had adequate knowledge, positive attitude, and proactive practice towards AF. The SEM was suitable for explaining general population' KAP regarding AF, revealing that knowledge directly and positively affected attitude and practice.

Disulfidptosis and ferroptosis related genes predict prognosis and personalize treatment for hepatocellular carcinoma.

Background: Understanding the interplay between disulfidptosis, ferroptosis, and hepatocellular carcinoma (HCC) could provide valuable insights into the pathogenesis of HCC and potentially identify novel therapeutic targets for the treatment of this deadly disease. This study aimed to identify a prognostic signature for HCC by examining the differential expression of genes related to disulfidptosis and ferroptosis (DRG-FRG), and to assess its clinical applicability. Methods: By integrating 23 disulfidptosis and 259 ferroptosis related genes with HCC messenger RNA (mRNA) expression data from The Cancer Genome Atlas (TCGA), differentially expressed DRG-FRG genes were identified. From these, 11 DRG-FRG genes were selected to construct a risk signature model using least absolute shrinkage and selection operator regression analyses. The prognostic performance of this model was evaluated by Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) analysis. Subsequently, a nomogram was built by combining the signature with clinical variables. To further delve into the underlying mechanisms, we performed bioinformatics analysis using a variety of databases. Results: A prognostic signature based on 11 DRG-FRG genes effectively categorized HCC patients into high- and low-risk groups, showing a significant survival difference. Even after considering clinical variables, this signature remained an independent prognostic factor. Furthermore, the signature played a role in various critical biological processes and pathways that drive HCC progression. Potential therapeutic benefits could be derived from small molecule drugs targeting NQO1 and SLC7A11. Interestingly, the high-risk group exhibited resistance to several chemotherapeutic drugs, yet showed sensitivity to others when contrasted with the low-risk group. Lastly, the DRG-FRG genes signature had a strong correlation with the tumor immune microenvironment, marked by an elevated expression of immune checkpoint molecules in the high-risk group. Conclusions: The signature based on 11 DRG-FRG genes stands out as a promising prognostic biomarker for HCC. Beyond its predictive value, it sheds light on the intricate crosstalk between DRG-FRG genes and HCC. Importantly, these findings could pave the way for enhanced prognostic prediction, informed treatment decisions, and the advancement of immunotherapy for HCC patients.

Quercetin inhibits necroptosis in cardiomyocytes after ischemia-reperfusion via DNA-PKcs-SIRT5-orchestrated mitochondrial quality control.

We investigated the mechanism by which quercetin preserves mitochondrial quality control (MQC) in cardiomyocytes subjected to ischemia-reperfusion stress. An enzyme-linked immunosorbent assay was employed in the in vivo experiments to assess myocardial injury markers, measure the transcript levels of SIRT5/DNAPK-cs/MLKL during various time intervals of ischemia-reperfusion, and observe structural changes in cardiomyocytes using transmission electron microscopy. In in vitro investigations, adenovirus transfection was employed to establish a gene-modified model of DNA-PKcs, and primary cardiomyocytes were obtained from a mouse model with modified SIRT5 gene. Reverse transcription polymerase chain reaction, laser confocal microscopy, immunofluorescence localization, JC-1 fluorescence assay, Seahorse energy analysis, and various other assays were applied to corroborate the regulatory influence of quercetin on the MQC network in cardiomyocytes after ischemia-reperfusion. In vitro experiments demonstrated that ischemia-reperfusion injury caused changes in the structure of the myocardium. It was seen that quercetin had a beneficial effect on the myocardial tissue, providing protection. As the ischemia-reperfusion process continued, the levels of DNA-PKcs/SIRT5/MLKL transcripts were also found to change. In vitro investigations revealed that quercetin mitigated cardiomyocyte injury caused by mitochondrial oxidative stress through DNA-PKcs, and regulated mitophagy and mitochondrial kinetics to sustain optimal mitochondrial energy metabolism levels. Quercetin, through SIRT5 desuccinylation, modulated the stability of DNA-PKcs, and together they regulated the "mitophagy-unfolded protein response." This preserved the integrity of mitochondrial membrane and genome, mitochondrial dynamics, and mitochondrial energy metabolism. Quercetin may operate synergistically to oversee the regulation of mitophagy and the unfolded protein response through DNA-PKcs-SIRT5 interaction.

[Analysis of a child featuring global developmental delay and autism due to variant of TBR1 gene and a literature review].

OBJECTIVE: To explore the clinical characteristics and genetic basis for a child with global developmental delay and autism. METHODS: A child who had presented at West China Second University Hospital of Sichuan University on April 13, 2021 was selected as the study subject. Clinical manifestations, laboratory examination and result of genetic testing were analyzed. RESULTS: The main symptoms of the child had included cognitive, language and motor delay, autism and epilepsy. Electroencephalogram revealed multiple focal discharges in both waking and sleeping stages, with the remarkable one seen at the sleeping stage. Cranial MRI showed pachygyria and local cortical thickening, Whole exome sequencing (WES) revealed that the child has harbored a heterozygous c.1589_1595dup (p.Gly533Leufs*143) frameshifting variant in the TBR1 gene (OMIM 604616). Based on the guidelines from the American College of Medical Genetics and Genomics, the variant was predicted to be likely pathogenic (PS2+PVS1_Supporting+PM2_Supporting). After treated with levetiracetam and rehabilitation training, the child did not have seizure in the past 5 months, and his motor development has also significantly improved. CONCLUSION: The c.1589_1595dup variant of the TBR1 gene probably underlay the disease in this patient.

One-pot reaction for the preparation of diatom hemostatic particles with effective hemostasis and economic benefits.

Effective hemostatic materials have been in demand for rapid pre-hospital hemostasis in emergency situations, which can significantly reduce accidental deaths. The development of emergency hemostatic materials with rapid hemostasis, biosafety, and economical preparation is a great challenge. In this study, Ca(OH)2-complexed diatom powder hemostatic particles (Ca(OH)2-Php) were prepared based on a one-pot reaction by directly mixing various raw materials and by rotary granulation. High-temperature calcination was able to carbonate and consume the organic matter in the hemostatic particles. The crosslinked hydrogen bonds in those particles were converted to silica-oxygen bonds, the particles became more stable, and the porous structure of diatom biosilica (DBs) was exposed. Ca(OH)2-Php has high porosity, can quickly adsorb the water in blood (water absorption: 75.85 ± 6.93%), and exhibits rapid hemostasis capacity (clotting time was shortened by 43% compared with that of the control group), good biocompatibility (hemolysis rate <7%, no cytotoxicity), and simplicity of handling (conveniently debride, no residues, no tissue inflammation). This study provides a new idea for the preparation of emergency hemostatic materials, and Ca(OH)2-Php prepared by one-pot reaction has various high-quality characteristics including rapid hemostasis, wide applicability, economical preparation, and potential for large-scale production.

Methyl rosmarinate is an allosteric inhibitor of SARS-CoV-2 3 CL protease as a potential candidate against SARS-cov-2 infection.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been ongoing for more than three years and urgently needs to be addressed. Traditional Chinese medicine (TCM) prescriptions have played an important role in the clinical treatment of patients with COVID-19 in China. However, it is difficult to uncover the potential molecular mechanisms of the active ingredients in these TCM prescriptions. In this paper, we developed a new approach by integrating the experimental assay, virtual screening, and the experimental verification, exploring the rapid discovery of active ingredients from TCM prescriptions. To achieve this goal, 4 TCM prescriptions in clinical use for different indications were selected to find the antiviral active ingredients in TCMs. The 3-chymotrypsin-like protease (3CLpro), an important target for fighting COVID-19, was utilized to determine the inhibitory activity of the TCM prescriptions and single herb. It was found that 10 single herbs had better inhibitory activity than other herbs by using a fluorescence resonance energy transfer (FRET) - based enzymatic assay of SARS-CoV-2 3CLpro. The ingredients contained in 10 herbs were thus virtually screened and the predicted active ingredients were experimentally validated. Thus, such a research strategy firstly removed many single herbs with no inhibitory activity against SARS-CoV-2 3CLpro at the very beginning by FRET-based assay, making our subsequent virtual screening more effective. Finally, 4 active components were found to have stronger inhibitory effects on SARS-CoV-2 3CLpro, and their inhibitory mechanism was subsequently investigated. Among of them, methyl rosmarinate as an allosteric inhibitor of SARS-CoV-2 3CLpro was confirmed and its ability to inhibit viral replication was demonstrated by the SARS-CoV-2 replicon system. To validate the binding mode via docking, the mutation experiment, circular dichroism (CD), enzymatic inhibition and surface plasmon resonance (SPR) assay were performed, demonstrating that methyl rosmarinate bound to the allosteric site of SARS-CoV-2 3CLpro. In conclusion, this paper provides the new ideas for the rapid discovery of active ingredients in TCM prescriptions based on a specific target, and methyl rosmarinate has the potential to be developed as an antiviral therapeutic candidate against SARS-CoV-2 infection.

An Efficient Approach to the Accurate Prediction of Mutational Effects in Antigen Binding to the MHC1.

The major histocompatibility complex (MHC) can recognize and bind to external peptides to generate effective immune responses by presenting the peptides to T cells. Therefore, understanding the binding modes of peptide-MHC complexes (pMHC) and predicting the binding affinity of pMHCs play a crucial role in the rational design of peptide vaccines. In this study, we employed molecular dynamics (MD) simulations and free energy calculations with an Alanine Scanning with Generalized Born and Interaction Entropy (ASGBIE) method to investigate the protein-peptide interaction between HLA-A*02:01 and the G9209 peptide derived from the melanoma antigen gp100. The energy contribution of individual residue was calculated using alanine scanning, and hotspots on both the MHC and the peptides were identified. Our study shows that the pMHC binding is dominated by the van der Waals interactions. Furthermore, we optimized the ASGBIE method, achieving a Pearson correlation coefficient of 0.91 between predicted and experimental binding affinity for mutated antigens. This represents a significant improvement over the conventional MM/GBSA method, which yields a Pearson correlation coefficient of 0.22. The computational protocol developed in this study can be applied to the computational screening of antigens for the MHC1 as well as other protein-peptide binding systems.

Designing transparent piezoelectric metasurfaces for adaptive optics.

Simultaneously generating various motion modes with high strains in piezoelectric devices is highly desired for high-technology fields to achieve multi-functionalities. However, traditional approach for designing multi-degrees-of-freedom systems is to bond together several multilayer piezoelectric stacks, which generally leads to cumbersome and complicated structures. Here, we proposed a transparent piezo metasurface to achieve various types of strains in a wide frequency range. As an example, we designed a ten-unit piezo metasurface, which can produce high strains (ε3 = 0.76%), and generate linear motions along X-, Y- and Z-axis, rotary motions around X-, Y- and Z-axis as well as coupled modes. An adaptive lens based on the proposed piezo metasurface was demonstrated. It can realize a wide range of focal length (35.82 cm ~ ∞) and effective image stabilization with relatively large displacements (5.05 µm along Y-axis) and tilt angles (44.02' around Y-axis). This research may benefit the miniaturization and integration of multi-degrees-of-freedom systems.

Platelet-derived microparticles adoptively transfer integrin ß3 to promote antitumor effect of tumor-infiltrating T cells.

Approximately two-thirds of hepatocellular carcinoma (HCC) is considered a "cold tumor" characterized by few tumor-infiltrating T cells and an abundance of immunosuppressive cells. Cilengitide, an integrin αvß3 inhibitor, has failed in clinical trials as a potential anticancer drug. This failure implies that integrin αvß3 may play an important role in immune cells. However, the expression and potential role of integrin αvß3 in T cells of HCC patients remain unknown. Here, we established two HCC models and found that cilengitide had a dual effect on the HCC microenvironment by exerting both antitumor effect and immunosuppressive effect on T cells. This may partly explain the failure of cilengitide in clinical trials. In clinical specimens, HCC-infiltrating T cells exhibited deficient expression and activation of integrin ß3, which was associated with poor T-cell infiltration into tumors. Additionally, integrin ß3 functioned as a positive immunomodulatory molecule to facilitate T-cell infiltration and T helper 1-type immune response in vitro. Furthermore, T cells and platelet-derived microparticles (PMPs) co-culture assay revealed that PMPs adoptively transferred integrin ß3 to T cells and positively regulated T cell immune response. This process was mediated by clathrin-dependent endocytosis and macropinocytosis. Our data demonstrate that integrin ß3 deficiency on HCC-infiltrating T cells may be involved in shaping the immunosuppressive tumor microenvironment. PMPs transfer integrin ß3 to T cells and positively regulate T cell immune response, which may provide a new insight into immune therapy of HCC.

Determination of Trace Organic Contaminant Concentration via Machine Classification of Surface-Enhanced Raman Spectra.

Surface-enhanced Raman spectroscopy (SERS) has been well explored as a highly effective characterization technique that is capable of chemical pollutant detection and identification at very low concentrations. Machine learning has been previously used to identify compounds based on SERS spectral data. However, utilization of SERS to quantify concentrations, with or without machine learning, has been difficult due to the spectral intensity being sensitive to confounding factors such as the substrate parameters, orientation of the analyte, and sample preparation technique. Here, we demonstrate an approach for predicting the concentration of sample pollutants from SERS spectra using machine learning. Frequency domain transform methods, including the Fourier and Walsh-Hadamard transforms, are applied to spectral data sets of three analytes (rhodamine 6G, chlorpyrifos, and triclosan), which are then used to train machine learning algorithms. Using standard machine learning models, the concentration of the sample pollutants is predicted with >80% cross-validation accuracy from raw SERS data. A cross-validation accuracy of 85% was achieved using deep learning for a moderately sized data set (∼100 spectra), and 70-80% was achieved for small data sets (∼50 spectra). Performance can be maintained within this range even when combining various sample preparation techniques and environmental media interference. Additionally, as a spectral pretreatment, the Fourier and Hadamard transforms are shown to consistently improve prediction accuracy across multiple data sets. Finally, standard models were shown to accurately identify characteristic peaks of compounds via analysis of their importance scores, further verifying their predictive value.