IL-6 Released from Hepatic Stellate Cells Promotes Glycolysis and Migration of HCC Through the JAK1/vWF/TGFB1 Axis.

Purpose: The crosstalk between hepatocellular carcinoma (HCC) cells and hepatic stellate cells (HSCs) is one of the important mechanisms of liver cancer metastasis. The relationship between liver cancer metastasis and glycolysis has been extensively studied recently. However, the role of von Willebrand factor (vWF) mediated glycolysis mechanism in liver cancer metastasis is currently unknown. Methods: Western blot was used to verify the expression of vWF in HCC cells. PAS staining, glycogen and L-lactate content assays were used to reflect cellular glycolysis levels. The ability of cell migration was explored by Wound-healing and Transwell assays. Besides, the effect of vWF on the progression of HCC in vivo was also studied using subcutaneous xenograft model. Results: vWF derived from HCC cells promoted tumor migration by mediating glycolysis. Besides, vWF participated in the crosstalk between HCC cells and HSCs. HCC cells activated HSCs through vWF-mediated TGFB1 expression and secretion, and activated HSCs upregulated vWF expression in HCC cells through IL-6 secretion feedback. Further, in vitro and in vivo experiments also confirmed the importance of the JAK1/vWF/TGFB1 axis in regulating HSCs-derived IL-6 mediated HCC migration and growth. Conclusion: In summary, this article demonstrated that IL-6 released from hepatic stellate cells enhanced glycolysis and migration ability of liver cancer cells by activating JAK1/vWF/TGFB1 axis which may also be a potential target for inhibiting liver cancer metastasis.

Crosstalk between Circadian Rhythm Dysregulation and Tumorigenesis, Tumor Metabolism and Tumor Immune Response.

Circadian rhythm is a self-regulating 24-hour system that synchronizes with the day and night cycle in organisms. The regulation of this system is controlled by clock genes, which function to harmoniously express molecular levels that facilitate the orderly coordination of various cellular processes, such as sleep, metabolism, endocrine function, cell proliferation and immunity. The root cause of tumorigenesis is that the body loses its normal regulation of cell growth at the genetic level. Long-term disruptions in circadian rhythms caused by factors such as shift work, jet lag, and unstable sleep patterns can impact cellular health, leading to various health problems, including cancer. Circadian rhythm controls most cellular functions related to cancer progression, which has a significant impact on the ability of immune cells to detect cancer cells and promote their clearance and has crucial implication for future tumor immunotherapy. This article aims to review the crosstalk between dysregulation of circadian rhythm and tumorigenesis, tumor metabolism, and immune response. Additionally, we discuss the role of circadian rhythm disruption in tumor therapy, highlighting its potential to optimize treatment timing and improve therapeutic outcomes.

Real-time passive cavitation mapping and B-mode fusion imaging via hybrid adaptive beamformer with modified diagnostic ultrasound platform.

The implementation of real-time, convenient and high-resolution passive cavitation imaging (PCM) is crucial for ensuring the safety and effectiveness of ultrasound applications related to cavitation effects. However, the current B-mode ultrasound imaging system cannot achieve these functions. By developing a hybrid adaptive beamforming algorithm, the current work presented a real-time PCM and B-mode fusion imaging technique, using a modified diagnostic ultrasound platform enabling time-division multiplexing external triggering function. The proposed hybrid adaptive beamformer combined the advantages of delay-multiply-and-sum (DMAS) and minimum variance (MV) methods to effectively suppress the side lobe and tail-like artifacts, improving the resolution of PCM images. A high-pass filter was applied to selectively detect cavitation-specific signals while removing the interference from the tissue scatters. The system enabled synchronous visualization of tissue structure and cavitation activity under ultrasound exposure. Both numerical and experimental studies demonstrated that, compared with DAS, MV-DAS and DMAS methods, the proposed MV-DMAS algorithm performed better in both axial and lateral resolutions. This work represented a significant advancement in achieving high-quality real-time B-mode and PCM fusion imaging utilizing commercial medical ultrasound system, providing a powerful tool for synchronous monitoring and manipulating cavitation activity, which would enhance the safety and efficacy of cavitation-based applications.

Machine-learning-based corrections of CMIP6 historical surface ozone in China during 1950-2014.

Due to a lack of long-term observations in China, reports on historical ozone concentration are severely limited. In this study, by combining observation, reanalysis and model simulation data, XGBoost machine learning algorithm is used to correct the surface ozone concentration from CMIP6 climate model, and the long-term and large-scale surface ozone concentration of China during 1950-2014 is obtained. The long-term evolutions and trends of ozone and meteorological effects on interannual ozone variations are further analyzed. The results reveal that CMIP6 historical simulations have a large underestimation in ozone concentrations and their trends. The XGB-derived ozone are closer to observations, with R2 value of 0.66 and 0.74 for daily and monthly retrievals, respectively. Both the concentrations and exceedances of ozone in most parts of China have shown increasing trends from 1950 to 2014. The daily mean ozone concentration without climate change effects is estimated to be 117 ppb in the year 1950 averaged over China. It indicates that the increase in anthropogenic emissions of China has a significant contribution to ozone enhancement between 1950 and 2014. The higher ozone growth rates of XGB retrievals than those from the model indicate a regional surface ozone penalty due to the warming climate. The relatively significant increment in ozone are estimated in the Central and Western China. Seasonally, the ozone enhancement is largest in spring, indicating a shift in seasonal variation of ozone. Given the uncertainty in simulating historical ozone by climate model, we show that machine learning approaches can provide improved assessment of evolution in surface ozone, along with valuable information to guide future model development and formulate future ozone pollution prevention and control policies.

Lactate-induced activation of tumor-associated fibroblasts and IL-8-mediated macrophage recruitment promote lung cancer progression.

Alterations in the tumor microenvironment are closely associated with the metabolic phenotype of tumor cells. Cancer-associated fibroblasts (CAFs) play a pivotal role in tumor growth and metastasis. Existing studies have suggested that lactate produced by tumor cells can activate CAFs, yet the precise underlying mechanisms remain largely unexplored. In this study, we initially identified that lactate derived from lung cancer cells can promote nuclear translocation of NUSAP1, subsequently leading to the recruitment of the transcriptional complex JUNB-FRA1-FRA2 near the DESMIN promoter and facilitating DESMIN transcriptional activation, thereby promoting CAFs' activation. Moreover, DESMIN-positive CAFs, in turn, secrete IL-8, which recruits TAMs or promotes M2 polarization of macrophages, further contributing to the alterations in the tumor microenvironment and facilitating lung cancer progression. Furthermore, we observed that the use of IL-8 receptor antagonists, SB225002, or Navarixin, significantly reduced TAM infiltration and enhanced the therapeutic efficacy of anti-PD-1 or anti-PD-L1 treatment. This finding indicates that inhibiting IL-8R activity can attenuate the impact of CAFs on the tumor microenvironment, thus restraining the progression of lung cancer.

A lung disease diagnosis algorithm based on 2D spectral features of ultrasound RF signals.

Lung diseases are commonly diagnosed based on clinical pathological indications criteria and radiological imaging tools (e.g., X-rays and CT). During a pandemic like COVID-19, the use of ultrasound imaging devices has broadened for emergency examinations by taking their unique advantages such as portability, real-time detection, easy operation and no radiation. This provides a rapid, safe, and cost-effective imaging modality for screening lung diseases. However, the current pulmonary ultrasound diagnosis mainly relies on the subjective assessments of sonographers, which has high requirements for the operator's professional ability and clinical experience. In this study, we proposed an objective and quantifiable algorithm for the diagnosis of lung diseases that utilizes two-dimensional (2D) spectral features of ultrasound radiofrequency (RF) signals. The ultrasound data samples consisted of a set of RF signal frames, which were collected by professional sonographers. In each case, a region of interest of uniform size was delineated along the pleural line. The standard deviation curve of the 2D spatial spectrum was calculated and smoothed. A linear fit was applied to the high-frequency segment of the processed data curve, and the slope of the fitted line was defined as the frequency spectrum standard deviation slope (FSSDS). Based on the current data, the method exhibited a superior diagnostic sensitivity of 98% and an accuracy of 91% for the identification of lung diseases. The area under the curve obtained by the current method exceeded the results obtained that interpreted by professional sonographers, which indicated that the current method could provide strong support for the clinical ultrasound diagnosis of lung diseases.

A multi-dimensional approach to unravel the intricacies of lactylation related signature for prognostic and therapeutic insight in colorectal cancer.

BACKGROUND: Lactylation, a novel contributor to post-translational protein modifications, exhibits dysregulation across various tumors. Nevertheless, its intricate involvement in colorectal carcinoma, particularly for non-histone lactylation and its intersection with metabolism and immune evasion, remains enigmatic. METHODS: Employing immunohistochemistry on tissue microarray with clinical information and immunofluorescence on colorectal cell lines, we investigated the presence of global lactylation and its association with development and progression in colorectal cancer as well as its functional location. Leveraging the AUCell algorithm alongside correlation analysis in single-cell RNA sequencing data, as well as cox-regression and lasso-regression analysis in TCGA dataset and confirmed in GEO dataset, we identified a 23-gene signature predicting colorectal cancer prognosis. Subsequently, we analyzed the associations between the lactylation related gene risk and clinical characteristics, mutation landscapes, biological functions, immune cell infiltration, immunotherapy responses, and drug sensitivity. Core genes were further explored for deep biological insights through bioinformatics and in vitro experiments. RESULTS: Our study innovatively reveals a significant elevation of global lactylation in colorectal cancer, particularly in malignant tumors, confirming it as an independent prognostic factor for CRC. Through a comprehensive analysis integrating tumor tissue arrays, TCGA dataset, GEO dataset, combining in silico investigations and in vitro experiments, we identified a 23-gene Lactylation-Related Gene risk model capable of predicting the prognosis of colorectal cancer patients. Noteworthy variations were observed in clinical characteristics, biological functions, immune cell infiltration, immune checkpoint expression, immunotherapy responses and drug sensitivity among distinct risk groups. CONCLUSIONS: The Lactylation-Related Gene risk model exhibits significant potential for improving the management of colorectal cancer patients and enhancing therapeutic outcomes, particularly at the intersection of metabolism and immune evasion. This finding underscores the clinical relevance of global lactylation in CRC and lays the groundwork for mechanism investigation and targeted therapeutic strategies given the high lactate concentration in CRC.

Unraveling the atmospheric oxidation mechanism and kinetics of naphthalene: Insights from theoretical exploration.

Naphthalene, the most abundant polycyclic aromatic hydrocarbon in the atmosphere, significantly influences OH consumption and secondary organic aerosol (SOA) formation. Naphthoquinone (NQ) is a significant contributor to ring-retaining SOA from naphthalene degradation, impacting the redox properties and toxicity of ambient particles. However, inconsistencies persist regarding concentrations of its isomers, 1,2-NQ and 1,4-NQ. In present work, our theoretical investigation into naphthalene's reaction with OH and subsequent oxygenation unveils their role in SOA formation. The reaction kinetics of initial OH and subsequent O2 oxidation was extensively studied using high-level quantum chemical methods (DLPNO-CCSD(T)/aug-ccpVQZ//M052x-D3/6-311++G(d,p)) combined with RRKM/master equation simulations. The reactions mainly proceed through electrophilic addition and abstraction from the aromatic ring. The total rate coefficient of naphthalene + OH at 300 K and 1 atm from our calculation (7.2 × 10-12 cm3 molecule-1 s-1) agrees well with previous measurements (∼1 × 10-11 cm3 molecule-1 s-1). The computed branching ratios facilitate accurate product yield determination. The largest yield of 1-hydroxynaphthalen-1-yl radical (add1) producing the major precursor of RO2 is computed to be 93.8 % in the ambient environment. Our calculated total rate coefficient (5.2 × 10-16 cm3 molecule-1 s-1) for add1 + O2 closely matches that of limited experimental data (8.0 × 10-16 cm3 molecule-1 s-1). Peroxy radicals (RO2) generated from add1 + O2 include 4-cis/trans-(1-hydroxynaphthalen-1-yl)-peroxy radical (add1-4OOadd-cis/trans, 66.0 %/17.5 %), 2-cis/trans-(1-hydroxynaphthalen-1-yl)-peroxy radical (add1-2OOadd-cis/trans, 10.3 %/6.3 %). Regarding the debated predominance of 1,4-NQ (corresponding to the parent RO2, i.e., add1-4OOadd-cis/trans) and 1,2-NQ (corresponding to the parent RO2, i.e., add1-2OOadd-cis/trans) in the atmosphere, our findings substantiate the dominance of 1,4-NQ. This study also indicates potential weakening of 1,4-NQ's dominance due to competition from decomposition reactions of add1-4OOadd-cis/trans and add1-2OOadd-cis/trans. Precise reaction kinetics data are essential for characterizing SOA transformation derived from naphthalene and assessing their climatic impacts within modeling frameworks.

Overexpression of the Chrysanthemum lavandulifolium ROS1 gene promotes flowering in Arabidopsis thaliana by reducing the methylation level of CONSTANS.

DNA demethylation is involved in the regulation of flowering in plants, yet the underlying molecular mechanisms remain largely unexplored. The RELEASE OF SILENCING 1 (ROS1) gene, encoding a DNA demethyltransferase, plays key roles in many developmental processes. In this study, the ROS1 gene was isolated from Chrysanthemum lavandulifolium, where it was strongly expressed in the leaves, buds and flowers. Overexpression of the ClROS1 gene caused an early flowering phenotype in Arabidopsis thaliana. RNA-seq analysis of the transgenic plants revealed that differentially expressed genes (DEGs) were significantly enriched in the circadian rhythm pathway and that the positive regulator of flowering, CONSTANS (CO), was up-regulated. Additionally, whole-genome bisulphite sequencing (WGBS), PCR following methylation-dependent digestion with the enzyme McrBC, and bisulfite sequencing PCR (BSP) confirmed that the methylation level of the AtCO promoter was reduced, specifically in CG context. Overall, our results demonstrated that ClROS1 accelerates flowering by reducing the methylation level of the AtCO promoter. These findings clarify the epigenetic mechanism by which ClROS1-mediated DNA demethylation regulates flowering.

Mechanistic exploration of polytetrafluoroethylene thermal plasma gasification through multiscale simulation coupled with experimental validation.

The ever-growing quantities of persistent Polytetrafluoroethylene (PTFE) wastes, along with consequential ecological and human health concerns, stimulate the need for alternative PTFE disposal method. The central research challenge lies in elucidating the decomposition mechanism of PTFE during high-temperature waste treatment. Here, we propose the PTFE microscopic thermal decomposition pathways by integrating plasma gasification experiments with multi-scale simulations strategies. Molecular dynamic simulations reveal a pyrolysis-oxidation & chain-shortening-deep defluorination (POCD) degradation pathway in an oxygen atmosphere, and an F abstraction-hydrolysis-deep defluorination (FHD) pathway in a steam atmosphere. Density functional theory computations demonstrate the vital roles of 1O2 and ·H radicals in the scission of PTFE carbon skeleton, validating the proposed pathways. Experimental results confirm the simulation results and show that up to 80.12% of gaseous fluorine can be recovered through plasma gasification within 5 min, under the optimized operating conditions determined through response surface methodology.

High-Pressure Limit and Pressure-Dependent Rate Rules for ß-Scission Reaction Class of Hydroperoxyl Alkyl Hydroperoxyl Radicals (•P(OOH)2) in Normal-Alkyl Cyclohexanes Combustion.

Chemical kinetic studies of the ß-scission reaction class of hydroperoxyl alkyl hydroperoxyl radicals (•P(OOH)2) from normal-alkyl cyclohexanes are carried out systematically through high-level ab initio calculations. Geometry optimizations and frequency calculations for all species involved in the reactions are performed at the B3LYP/CBSB7 level of theory. Electronic single-point energy calculations are calculated at the CBS-QB3 level of theory. Rate constants for the reactions of ß-scission, in the temperature range of 500-1500 K and the pressure range of 0.01-100 atm, are calculated using transition state theory (TST) and Rice-Ramsberger-Kassel-Marcus/Master-Equation (RRKM/ME) theory taking asymmetric Eckart tunneling corrections and the one-dimensional hindered rotor approximation into consideration. The rate rules are obtained by averaging the rate constants of the representative reactions of this class. These rate rules can greatly assist in constructing more accurate low-temperature combustion mechanisms for normal-alkyl cyclohexanes.

Mechanistic insights into the enhanced texture of potato noodles by incorporation of small granule starches.

Potato noodles are a popular food due to their unique texture and taste, but native potato starch often fails to meet consumer demands for precise textural outcomes. The effect of blending small granule (waxy amaranth, non-waxy oat and quinoa) starch with potato starch on the properties of noodles was investigated to enhance quality of noodles. Morphological results demonstrated that small granule starch filled gaps between potato starch granules, some of which gelatinized incompletely. Meanwhile, XRD and FTIR analysis indicated that more ordered structures and hydrogen bonding among starch granules increased with addition of small granule starch. The addition of oat or quinoa starch increased gel elasticity, decreased viscosity of the pastes, and increased the tensile strength of noodles, while addition of 30 % and 45 % waxy amaranth starch did not increase G' value of gel or tensile strength of noodles. These results indicated that amylose molecules played an important role during retrogradation, and may intertwine and interact with each other to enhance the network structure of starch gel in potato starch blended with oat or quinoa starch. This study provides a natural way to modify potato starch for desirable textural properties of noodle product.

Improved assessment sensitivity of time-varying cavitation events based on wavelet analysis.

Ultrasonic cavitation, characterized by the oscillation or abrupt collapse of cavitation nuclei in response to ultrasound stimulation, plays a significant role in various applications within both industrial and biomedical sectors. In particular, inertial cavitation (IC) has garnered considerable attention due to the resulting mechanical, chemical, and thermal effects. Passive cavitation detection (PCD) has emerged as a valuable technique for monitoring this procedure. While the fast Fourier transform (FFT) is a widely used algorithm to analyze IC-induced broadband noise detected by PCD system, it may not adequately capture the time-varying instability of cavitation due to potential nuclei collapse during ultrasound irradiation. In contrast, the continuous wavelet transform offers a more flexible approach, enabling more sensitive analysis of signals with varying frequencies over time. In this study, nanodiamond (ND) and its derivative, nitro-doped nanodiamond (N-AND), known to possess cavitation potential from previous research, were chosen as the source of cavitation nuclei. The cavitation signals detected by PCD were subjected to both FFT and wavelet analyses, with their results comprehensively compared. This research showcased the feasibility of employing wavelet analysis for effective inertial cavitation evaluation. It provided the advantage of monitoring the temporal evolution of cavitation events in real-time, enhancing sensitivity to weak and unstable cavitation signals, especially those in higher order components (3rd and 4th order). Additionally, it yielded a higher level of precision in determining IC thresholds and doses. Furthermore, the inclusion of time information through wavelet analysis offered insights into the limitations of low-cycle ultrasound in inducing IC. This study introduces a novel perspective for more sensitive and precise cavitation assessment, leveraging time and frequency data from wavelet analysis, and holds promise for effective utilization of cavitation effects while minimizing losses and damages resulting from unintended cavitation events.

Electroencephalography microstates as novel functional biomarkers for insomnia disorder.

Background: Insomnia disorder (ID) is one of the most common mental disorders. Research on ID focuses on exploring its mechanism of disease, novel treatments and treatment outcome prediction. An emerging technique in this field is the use of electroencephalography (EEG) microstates, which offer a new method of EEG feature extraction that incorporates information from both temporal and spatial dimensions. Aims: To explore the electrophysiological mechanisms of repetitive transcranial magnetic stimulation (rTMS) for ID treatment and use baseline microstate metrics for the prediction of its efficacy. Methods: This study included 60 patients with ID and 40 age-matched and gender-matched good sleep controls (GSC). Their resting-state EEG microstates were analysed, and the Pittsburgh Sleep Quality Index (PSQI) and polysomnography (PSG) were collected to assess sleep quality. The 60 patients with ID were equally divided into active and sham groups to receive rTMS for 20 days to test whether rTMS had a moderating effect on abnormal microstates in patients with ID. Furthermore, in an independent group of 90 patients with ID who received rTMS treatment, patients were divided into optimal and suboptimal groups based on their median PSQI reduction rate. Baseline EEG microstates were used to build a machine-learning predictive model for the effects of rTMS treatment. Results: The class D microstate was less frequent and contribute in patients with ID, and these abnormalities were associated with sleep onset latency as measured by PSG. Additionally, the abnormalities were partially reversed to the levels observed in the GSC group following rTMS treatment. The baseline microstate characteristics could predict the therapeutic effect of ID after 20 days of rTMS, with an accuracy of 80.13%. Conclusions: Our study highlights the value of EEG microstates as functional biomarkers of ID and provides a new perspective for studying the neurophysiological mechanisms of ID. In addition, we predicted the therapeutic effect of rTMS on ID based on the baseline microstates of patients with ID. This finding carries great practical significance for the selection of therapeutic options for patients with ID.

Controlling Morphology and Excitonic Disorder in Monolayer WSe2 Grown by Salt-Assisted CVD Methods.

Chemical synthesis is a compelling alternative to top-down fabrication for controlling the size, shape, and composition of two-dimensional (2D) crystals. Precision tuning of the 2D crystal structure has broad implications for the discovery of new phenomena and the reliable implementation of these materials in optoelectronic, photovoltaic, and quantum devices. However, precise and predictable manipulation of the edge structure in 2D crystals through gas-phase synthesis is still a formidable challenge. Here, we demonstrate a salt-assisted low-pressure chemical vapor deposition method that enables tuning W metal flux during growth of 2D WSe2 monolayers and, thereby, direct control of their edge structure and optical properties. The degree of structural disorder in 2D WSe2 is a direct function of the W metal flux, which is controlled by adjusting the mass ratio of WO3 to NaCl. This edge disorder then couples to excitonic disorder, which manifests as broadened and spatially varying emission profiles. Our work links synthetic parameters with analyses of material morphology and optical properties to provide a unified understanding of intrinsic limits and opportunities in synthetic 2D materials.

Fibrocyte: A missing piece in the pathogenesis of fibrous epulis.

OBJECTIVES: To explore the role of fibrocytes in the recurrence and calcification of fibrous epulides. METHODS: Different subtypes of fibrous epulides and normal gingival tissue specimens were first collected for histological and immunofluorescence analyses to see if fibrocytes were present and whether they differentiated into myofibroblasts and osteoblasts upon stimulated by transforming growth factor-ß1 (TGF-ß1). Electron microscopy and elemental analysis were used to characterize the extracellular microenvironment in different subtypes of fibrous epulides. Human peripheral blood mononuclear cells (PBMCs) were subsequently isolated from in vitro models to mimic the microenvironment in fibrous epulides to identify whether TGF-ß1 as well as the calcium and phosphorus ion concentration in the extracellular matrix (ECM) of a fibrous epulis trigger fibrocyte differentiation. RESULTS: Fibrous epulides contain fibrocytes that accumulate in the local inflammatory environment and have the ability to differentiate into myofibroblasts or osteoblasts. TGF-ß1 promotes fibrocytes differentiation into myofibroblasts in a concentration-dependent manner, while TGF-ß1 stimulates the fibrocytes to differentiate into osteoblasts when combined with a high calcium and phosphorus environment. CONCLUSIONS: Our study revealed fibrocytes play an important role in the fibrogenesis and osteogenesis in fibrous epulis, and might serve as a therapeutic target for the inhibition of recurrence of fibrous epulides.

Not in black or white, encryption of grayscale images by donor-acceptor Stenhouse adducts.

Invisible inks have been applied for the secrecy of texts, symbols and binary images. Based on the photochromism of donor-acceptor Stenhouse adducts (DASAs) in the solid-state promoted by ester-containing molecules, we report the encryption of grayscale information by controlling the kinetics of photoisomerization.