CLSPN actives Wnt/ß-catenin signaling to facilitate glycolysis and cell proliferation in oral squamous cell carcinoma.

OBJECTIVE: Oral squamous cell carcinoma (OSCC) is a common malignancy with a poor prognosis. This study aimed to determine the influence and underlying mechanisms of CLSPN on OSCC. METHODS: CLSPN expression was tested using quantitative real-time polymerase chain reaction, immunohistochemistry, and western blotting. Flow cytometry, cell counting kit, and colony formation assays were performed to determine OSCC cell apoptosis, viability, and proliferation, respectively. In OSCC cells, the extracellular acidification rate (ECAR), oxygen consumption rate (OCR), glucose uptake, and lactate production were determined using the corresponding kits. Changes in the protein levels of HK2, PKM2, LDHA, Wnt3a, and ß-catenin were assessed using western blotting. RESULTS: CLSPN expression was increased in OSCC tissues. Overexpression of CLSPN in HSC-2 cells promoted cell proliferation, increased the levels of ECAR, glucose uptake, and lactate production, and increased the protein levels of HK2, PKM2, LDHA, Wnt3a, and ß-catenin, but inhibited OCR levels and apoptosis. The knockdown of CLSPN in CAL27 cells resulted in the opposite results. Moreover, the effects of CLSPN overexpression on glycolysis and OSCC cell proliferation were reversed by Wnt3a knockdown. In vivo, knockdown of CLSPN restrained tumor growth, glycolysis, and the activation of Wnt/ß-catenin signaling. CONCLUSION: CLSPN promoted glycolysis and OSCC cell proliferation, and reduced apoptosis, which was achieved by the activation of Wnt/ß-catenin signaling pathway.

Emerging roles of nerve-bone axis in modulating skeletal system.

Over the past decades, emerging evidence in the literature has demonstrated that the innervation of bone is a crucial modulator for skeletal physiology and pathophysiology. The nerve-bone axis sparked extensive preclinical and clinical investigations aimed at elucidating the contribution of nerve-bone crosstalks to skeleton metabolism, homeostasis, and injury repair through the perspective of skeletal neurobiology. To date, peripheral nerves have been widely reported to mediate bone growth and development and fracture healing via the secretion of neurotransmitters, neuropeptides, axon guidance factors, and neurotrophins. Relevant studies have further identified several critical neural pathways that stimulate profound alterations in bone cell biology, revealing a complex interplay between the skeleton and nerve systems. In addition, inspired by nerve-bone crosstalk, novel drug delivery systems and bioactive materials have been developed to emulate and facilitate the process of natural bone repair through neuromodulation, eventually boosting osteogenesis for ideal skeletal tissue regeneration. Overall, this work aims to review the novel research findings that contribute to deepening the current understanding of the nerve-bone axis, bringing forth some schemas that can be translated into the clinical scenario to highlight the critical roles of neuromodulation in the skeletal system.

Application of carbon nanoparticles combined with intraoperative neuromonitoring in papillary thyroid microcarcinoma surgery.

PURPOSES: To improve the lymph node dissection as well as protect parathyroid gland and recurrent laryngeal nerve, the carbon nanoparticles and intraoperative neuromonitoring were applied in papillary thyroid microcarcinoma surgery. METHODS: Carbon nanoparticles and intraoperative neuromonitoring were used in the experimental group, whereas the control group were not. Routine pathological examination was performed. RESULTS: The lymph nodes dissected was significantly higher in the experimental group, but the metastatic lymph nodes were not. The number of mistakenly dissected parathyroid gland and postoperative hypoparathyroidism were 3 and 13 in the experimental group respectively, significantly less than 10 and 25 in the control group. The incidences of overall, transient and persistent recurrent laryngeal nerve palsy in the experimental group were 5.5%, 5.5% and 0% respectively, whereas in the control group were 8.6%, 6.9% and 1.7%. CONCLUSIONS: Carbon nanoparticles can improve lymph node dissection in papillary thyroid microcarcinoma surgery, and the combination of carbon nanoparticles with intraoperative neuromonitoring can reduce surgical complications and improve patient quality of life.

Bidirectional machine learning-assisted sensitivity-based stochastic searching approach for groundwater DNAPL source characterization.

In this study, we designed a machine learning-based parallel global searching method using the Bayesian inversion framework for efficient identification of dense non-aqueous phase liquid (DNAPL) source characteristics and contaminant transport parameters in groundwater. Swarm intelligence organized hybrid-kernel extreme learning machine (SIO-HKELM) was proposed to approximate the forward and inverse input-output correlation with a high accuracy using the DNAPL transport numerical simulation model. An adaptive inverse-HKELM was established for preliminary estimation of the source characteristics and contaminant transport parameters to correct prior information and generate high-quality initial starting points of parallel searching. A local accurate forward-HKELM surrogate of the numerical model was embedded in the searching system for avoiding repetitive CPU-demanding likelihood evaluations. A sensitivity-based Metropolis criterion (MC), incorporating the dynamic particle swarm optimization (SD-PSO) algorithm, was developed for improving the search ergodicity and realizing precise inversion of all the unknown variables with drastic variations in sensitivity to the likelihood function. Results showed that the generalization capability and robustness of SIO-HKELM were superior to those of the traditional machine learning methods, including KELM and support vector regression (SVR), and it sufficiently approximated the forward and inverse input-output mapping of the numerical model with testing determination coefficients of 0.9944 and 0.6440, respectively. With high-quality prior information and initial starting points generated by the adaptive inverse-HKELM feed approach, the uncertainty in the inversion outputs was reduced, and the searching process rapidly converged to reasonable posterior distributions in around 60 iterations. Compared with the widely used multichain Markov chain Monte Carlo (MCMC) approach, the parallel searching lines generated by SD-PSO-MC adequately covered the searching space, and the "equifinality" effect was more effectively restrained by reducing the relative errors of all the point estimations to less than 8%. Therefore, the real source information reflected by the statistical characteristics of the SD-PSO-MC inversion outputs was more precise than that obtained using the multichain MCMC approach.

Trehalose and its dihydrate: terahertz insights from solid to solution states.

Carbohydrates are pivotal biomolecules in biochemistry; this study employs terahertz time-domain spectroscopy (THz-TDS) to investigate the spectral characteristics of trehalose and its hydrate across the 0.1 to 2.2 THz frequency range. Notable differences in spectra between the two compounds were observed. Density Functional Theory (DFT) simulations of the crystal structure were conducted to elucidate this phenomenon. The consistency between experimental results and simulations substantiates the reliability of the experimental findings. Additionally, the spectral characteristics of these carbohydrates in solution were examined using microfluidic chip technology. This approach facilitates a comprehensive comparison of their behaviors in both solid and solution states.

Vibrational spectroscopic detection and analysis of salicylic acid and aspirin binary cocrystal.

Salicylic acid is a raw material for preparing aspirin and holds an important position in medical history. Studying the crystallization of these two drugs is of great significance in improving their dissolution rate, bioavailability, and physical stability. Although various techniques have been used for structural characterization, there is still a lack of information on the collective vibrational behavior of aspirin and salicylic acid eutectic compounds. Firstly, two starting materials (salicylic acid and aspirin) were ground in a 1:1 M ratio to prepare eutectic compounds. The eutectic composition was studied using vibrational spectroscopy techniques, such as X-ray powder diffusion (XRPD), terahertz time-domain spectroscopy (THz-TDS), and Raman spectroscopy. Additionally, the structure of the aspirin and salicylic acid eutectic was simulated and optimized using density functional theory. It was found that the eutectic type II was the most consistent with the experiment, and the corresponding vibration modes of each peak were provided. These results offer a unique method for characterizing the structural composition of eutectic crystals, which can be utilized to enhance the physical and chemical properties, as well as the pharmacological activity, of specific drugs at the molecular level.

Is residential greenness associated with dyslipidemia and lipid levels in Chinese rural-dwelling adults? The Henan rural cohort study.

Scarce epidemiologic research examined the associations between residential greenness and dyslipidemia or lipid levels in low/middle-income countries. Baseline statistics (2015-2017) of 39,259 rural-dwelling adults were obtained from a Chinese longitudinal study. The blood lipid level was measured utilizing an enzymatic assay method. According to the 2016 Chinese guidelines on dyslipidemia (revision), patients with dyslipidemia were defined. Participants' exposure to residential greenness was characterized by the satellite-based normalized difference vegetation index (NDVI). Mixed effects logistic regression and mixed effects linear regression were performed to assess the associations of residential greenness with dyslipidemia and lipid levels. The median (interquartile range, IQR) of 3-year average NDVI1000-m was 0.521 (0.089) units. Each IQR increase in NDVI1000-m was significantly linked with increased odds of hyperbetalipoproteinemia (OR = 1.33, 95%CI 1.21-1.46). The same increment in NDVI1000-m was associated with lower total cholesterol (TC) levels and increased low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) levels. For instance, the %changes in HDL-C levels was 0.71% (95%CI 0.17%-1.26%). The above relationships were partially mediated by reducing air pollution and lowering body mass index (BMI). Interaction effect analysis observed the greenness-lipid association was stronger in males than females (i.e., NDVI1000-m-TC association). Long-term exposure to residential greenness was associated with odds of dyslipidemia and lipid levels in Chinese rural-dwelling adults, particularly among males. Considering the cross-sectional study design, more longitudinal studies are needed to identify the causal associations.

Fatty acid ß-oxidation promotes breast cancer stemness and metastasis via the miRNA-328-3p-CPT1A pathway.

MicroRNAs (miRNA) have been shown to be associated with tumor diagnosis, prognosis, and therapeutic response. MiR-328-3p plays a significant role in breast cancer growth; however, its actual function and how it modulates specific biological functions is poorly understood. Here, miR-328-3p was significantly downregulated in breast cancer, especially in patients with metastasis. Mitochondrial carnitine palmitoyl transferase 1a (CPT1A) is a downstream target gene in the miR-328-3p-regulated pathway. Furthermore, the miR-328-3p/CPT1A/fatty acid ß-oxidation/stemness axis was shown responsible for breast cancer metastasis. Collectively, this study revealed that miR-328-3p is a potential therapeutic target for the treatment of breast cancer patients with metastasis, and also a model for the miRNA-fatty acid ß-oxidation-stemness axis, which may assist inunderstanding the cancer stem cell signaling functions of miRNA.

Association between Sleep Timing and Weight Status among 14- to 19-Year-Old Adolescents in Wuhan, China.

This study examined the cross-sectional and longitudinal association of sleep timing with weight status in 14- to 19-year-old adolescents in Wuhan, China. A prospective school-based study was conducted in Wuhan, China between 28 May and 29 September 2019. Data on sociodemographic information, academic performance, diet, mental health status, physical activity, sleep characteristics, body weight, and height were collected. A linear regression model and binary logistic regression model were performed. A total of 1194 adolescents were included in the analysis. Adolescents who woke up before 05:45 had higher body mass index (BMI) Z-score (odds ratio (OR) with 95% confidence interval (CI) = 1.28 (1.05, 1.57), p = 0.02) and higher odds of overweight/obesity (odds ratio (OR) with 95% confidence interval (CI) = 1.74 (1.10, 2.76), p = 0.02) at baseline after fully adjustment for covariates, compared with those who woke up after 05:45. Longitudinal data showed a nonsignificant association between waking up time and change in BMI Z-score (p = 0.18). No association of bedtime with weight status was observed in this sample after full adjustment (p > 0.1). Earlier waking up time might contribute to overweight and obesity in adolescents; however, more data are needed to test and elucidate this relationship.

JAZF1 Suppresses Papillary Thyroid Carcinoma Cell Proliferation and Facilitates Apoptosis via Regulating TAK1/NF-κB Pathways.

PURPOSE: Juxtaposed with another zinc finger gene 1 (JAZF1) is involved in gluconeogenesis, insulin sensitivity, cell differentiation, lipid metabolism and inflammation, but its role in carcinoma remains inexplicit. PATIENTS AND METHODS: We explored the JAZF1 expression in human papillary thyroid cancer (PTC) tissues, adjacent normal thyroid tissues and nodular goitre tissues, as well as Ki67 expression in PTC tissues, using immunohistochemistry staining. Western blotting and RT-qPCR were performed to explore the JAZF1 expression levels in Nthy-ori 3-1, BCPAP and TPC-1 cells. BCPAP cells overexpressing JAZF1 were constructed using an Adv-JAZF1-GFP recombinant adenovirus vector. Next, the cell proliferation assay, colony formation assay, cell cycle analysis, apoptosis and immunofluorescence were performed. The mRNA expression level of nuclear factor-κB p65 (NF-κB p65) was examined using RT-qPCR. The expression of Bcl-2, Bax, transforming growth factor beta-activated kinase 1 (TAK1), NF-κB p65 and NF-κB p-p65 were examined using Western blotting. RESULTS: The expression of JAZF1 in human PTC tissues was downregulated compared with adjacent thyroid tissues or nodular goitre. Additionally, JAZF1 expression was associated with the location and lymph node metastasis of PTC. The expression level of JAZF1 had a negative correlation with Ki67 labelling index (LI). Compared to Nthy-ori 3-1 cells and TPC-1 cells, BCPAP cells expressed the lowest JAZF1. JAZF1 overexpressed significantly inhibited proliferation, caused G0/G1 cell cycle arrest and promoted apoptosis in BCPAP cells. Furthermore, JAZF1 overexpressed in BCPAP cells clearly upregulated the expression level of Bax protein, whereas decreased the expression of Bcl-2, TAK1, NF-κB but did not affect the mRNA or protein expression level of NF-κB p65. CONCLUSION: JAZF1 inhibits proliferation and induces apoptosis in BCPAP cells by suppressing the activation of TAK1/NF-κB signalling pathways, suggesting that JAZF1 may serve as a reliable molecular marker in PTC.

A comparative research of different ensemble surrogate models based on set pair analysis for the DNAPL-contaminated aquifer remediation strategy optimization.

Surrogate-based simulation-optimization technique is an effective approach for optimizing the surfactant enhanced aquifer remediation (SEAR) strategy for clearing DNAPLs. The performance of the surrogate model, which is used to replace the simulation model for the aim of reducing computation burden, is the key of corresponding researches. However, previous researches are generally based on a stand-alone surrogate model, and rarely make efforts to improve the approximation accuracy of the surrogate model to the simulation model sufficiently by combining various methods. In this regard, we present set pair analysis (SPA) as a new method to build ensemble surrogate (ES) model, and conducted a comparative research to select a better ES modeling pattern for the SEAR strategy optimization problems. Surrogate models were developed using radial basis function artificial neural network (RBFANN), support vector regression (SVR), and Kriging. One ES model is assembling RBFANN model, SVR model, and Kriging model using set pair weights according their performance, and the other is assembling several Kriging (the best surrogate modeling method of three) models built with different training sample datasets. Finally, an optimization model, in which the ES model was embedded, was established to obtain the optimal remediation strategy. The results showed the residuals of the outputs between the best ES model and simulation model for 100 testing samples were lower than 1.5%. Using an ES model instead of the simulation model was critical for considerably reducing the computation time of simulation-optimization process and maintaining high computation accuracy simultaneously.

Heavy metal pollution in soil associated with a large-scale cyanidation gold mining region in southeast of Jilin, China.

Different gold mining and smelting processes can lead to distinctive heavy metal contamination patterns and results. This work examined heavy metal pollution from a large-scale cyanidation gold mining operation, which is distinguished from artisanal and small-scale amalgamation gold mining, in Jilin Province, China. A total of 20 samples including one background sample were collected from the surface of the mining area and the tailings pond in June 2013. These samples were analyzed for heavy metal concentrations and degree of pollution as well as sources of Cr, Cu, Zn, Pb, Ni, Cd, As, and Hg. The mean concentrations of Pb, Hg, and Cu (819.67, 0.12, and 46.92 mg kg-1, respectively) in soil samples from the gold mine area exceeded local background values. The mean Hg content was less than the first-class standard of the Environmental Quality for Soils, which suggested that the cyanidation method is helpful for reducing Hg pollution. The geochemical accumulation index and enrichment factor results indicated clear signs that enrichment was present for Pb, Cu, and Hg, with the presence of serious Pb pollution and moderate presence to none of Hg and Cu pollution. Multivariate statistical analysis showed that there were three metal sources: (1) Pb, Cd, Cu, and As came from anthropogenic sources; (2) Cr and Zn were naturally occurring; whereas (3) Hg and Ni had a mix of anthropogenic and natural sources. Moreover, the tailings dam plays an important role in intercepting the tailings. Furthermore, the potential ecological risk assessment results showed that the study area poses a potentially strong risk to the ecological health. Furthermore, Pb and Hg (due to high concentration and high toxicity, respectively) are major pollutants on the risk index, and both Pb and Hg pollution should be of great concern at the Haigou gold mines in Jilin, China.

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method.

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.