MTF2 facilitates the advancement of osteosarcoma through mediating EZH2/SFRP1/Wnt signaling.

BACKGROUND: Osteosarcoma is a soft tissue neoplasm with elevated recurrence risk and highly metastatic potential. Metal response element binding transcriptional factor 2 (MTF2) has been revealed to exert multiple activities in human tissues. The present research was conducted to explore the functions and related response mechanism of MTF2 in osteosarcoma which have not been introduced yet. METHODS: Bioinformatics tools identified the differential MTF2 expression in osteosarcoma tissues. MTF2 expression in osteosarcoma cells was examined with Western blot. Cell Counting Kit-8 (CCK-8) assay, 5-Ethynyl-2'-deoxyuridine (EDU) staining, wound healing as well as transwell assays measured cell proliferation, migration and invasion, respectively. Flow cytometry assay detected the cellular apoptotic level. Western blot also measured the expressions of proteins associated with epithelial mesenchymal transition (EMT), apoptosis and enhancer of zeste homolog 2 (EZH2)/secreted frizzled-related protein 1 (SFRP1)/Wnt signaling. Co-immunoprecipitation (Co-IP) assay confirmed MTF2-EZH2 interaction. RESULTS: MTF2 expression was increased in osteosarcoma tissues and cells. MTF2 interference effectively inhibited the proliferation, migration and invasion of osteosarcoma cells and promoted the cellular apoptotic rate. MTF2 directly bound to EZH2 and MTF2 silence reduced EZH2 expression, activated SFRP1 expression and blocked Wnt signaling in osteosarcoma cells. EZH2 upregulation or SFRP1 antagonist WAY-316606 partly counteracted the impacts of MTF2 down-regulation on the SFRP1/Wnt signaling and the biological phenotypes of osteosarcoma cells. CONCLUSIONS: MTF2 might down-regulate SFRP1 to activate Wnt signaling and drive the progression of osteosarcoma via interaction with EZH2 protein.

Effects of perioperative hydrogen inhalation on brain edema and prognosis in patients with glioma: a single-center, randomized controlled study.

Introduction: Brain edema is a life-threatening complication that occurs after glioma surgery. There are no noninvasive and specific treatment methods for brain edema. Hydrogen is an anti-inflammatory and antioxidant gas that has demonstrated therapeutic and preventative effects on several diseases, particularly in the nervous system. This study aimed to determine the therapeutic effects of hydrogen administration on brain edema following glioma surgery and elucidate its mechanism. Methods: A single-center, randomized controlled clinical trial of hydrogen inhalation was conducted (China Clinical Trial Registry [ChiCTR-2300074362]). Participants in hydrogen (H) group that inhaled hydrogen experienced quicker alleviation of postoperative brain edema compared with participants in control (C) group that inhaled oxygen. Results: The volume of brain edema before discharge was significantly lower in the H group (p < 0.05). Additionally, the regression rate of brain edema was higher in the H group than in the C group, which was statistically significant (p < 0.05). Furthermore, 3 days after surgery, the H group had longer total sleep duration, improved sleep efficiency, shorter sleep latency, and lower numerical rating scale (NRS) scores (p < 0.05). Discussion: In conclusion, hydrogen/oxygen inhalation effectively reduced postoperative brain edema in glioma patients. Further research is necessary to understand the underlying mechanisms of hydrogen's therapeutic effects. Hydrogen is expected to become a new target for future adjuvant therapy for brain edema.

Selenium spatial distribution and bioavailability of soil-plant systems in China: a comprehensive review.

Selenium (Se) has a dual nature, with beneficial and harmful effects on plants, essential for both humans and animals, playing a crucial role in ecosystem regulation. Insufficient Se in specific terrestrial environments raises concerns due to its potential to cause diseases, while excess Se can lead to severe toxicity. Thus, maintaining an optimal Se level is essential for living organisms. This review focuses first on Se transformation, speciation, and geochemical properties in soil, and then provides a concise overview of Se distribution in Chinese soil and crops, with a focus on the relationship between soil Se levels and parent materials. Additionally, this paper explores Se bioavailability, considering parent materials and soil physicochemical properties, using partial least squares path modeling for analysis. This paper aimed to be a valuable resource for effectively managing Se-enriched soil resources, contributing to a better understanding of Se role in ecosystems.

Dietary patterns suggest that dark chocolate intake may have an inhibitory effect on oral cancer: a Mendelian randomization study.

Background: Previous studies reported that variations in dietary intake patterns substantially impact human health, specifically tumorigenesis. However, confounding factors in previous cohort studies have obscured the relationship between dietary differences and the risk of oral cancer (OC). Materials and methods: We developed an outcome dataset from genome-wide association studies (GWAS) data on three OCs within the GAME-ON project, using GWAS-META merging. We extracted 21 dietary exposures, including 10 dietary patterns, 6 vitamins, and 5 micronutrients, from the UK Biobank database, using the inverse variance weighting method as the primary statistical method. Sensitivity analysis was conducted to detect heterogeneity and pleiotropy. Serum metabolite concentrations were adjusted using multivariate Mendelian randomization. Results: Of the 10 analyzed dietary patterns, 8 showed no significant association with the risk of developing OC. Consumption of dark chocolate (inverse variance weighted [IVW]: Odds ratio (OR) = 0.786, 95% confidence interval [CI]: 0.622-0.993, p = 0.044) and sweet pepper exhibited an inverse relationship with OC risk (IVW: OR = 0.757, 95% CI: 0.574-0.997, p = 0.048). Reverse MR analysis revealed no reverse causality. Furthermore, no significant correlation was observed between the intake of 6 vitamins and 5 micronutrients and the risk of developing OC. After using multivariable MR to adjust for serum caffeine, linoleate, theophylline, and theobromine metabolism levels, consuming dark chocolate was unrelated to a decreased risk of OC. After adjusting each serum metabolite individually, the observed p-values deviated from the original values to varying degrees, indicating that the components of dark chocolate could have different effects. Among these components, theophylline demonstrated the most significant inhibitory effect. Conclusion: This study demonstrated a causal relationship between the intake of dark chocolate and sweet peppers and a lower risk of OC. The components of dark chocolate could have different effects.

Association study of Plasmodium falciparum Acetyl-CoA Synthetase Mutations S868G and V949I with antimalarial drugs.

Plasmodium falciparum acetyl-CoA synthetase (PfACAS) protein is an important source of acetyl-CoA. We detected the mutations S868G and V949I in PfACAS by whole-genome sequencing analysis in some recrudescent parasites after antimalarial treatment with artesunate and dihydroartemisinin-piperaquine, suggesting that they may confer drug resistance. Using CRISPR/Cas9 technology, we engineered parasite lines carrying the PfACAS S868G and V949I mutations in two genetic backgrounds and evaluated their susceptibility to antimalarial drugs in vitro. The results demonstrated that PfACAS S868G and V949I mutations alone or in combination were not enough to provide resistance to antimalarial drugs.

Advancing Ionic Liquid Research with pSCNN: A Novel Approach for Accurate Normal Melting Temperature Predictions.

Ionic liquids (ILs), known for their distinct and tunable properties, offer a broad spectrum of potential applications across various fields, including chemistry, materials science, and energy storage. However, practical applications of ILs are often limited by their unfavorable physicochemical properties. Experimental screening becomes impractical due to the vast number of potential IL combinations. Therefore, the development of a robust and efficient model for predicting the IL properties is imperative. As the defining feature, it is of practice significance to establish an accurate yet efficient model to predict the normal melting point of IL (T m), which may facilitate the discovery and design of novel ILs for specific applications. In this study, we presented a pseudo-Siamese convolution neural network (pSCNN) inspired by SCNN and focused on the T m. Utilizing a data set of 3098 ILs, we systematically assess various deep learning models (ANN, pSCNN, and Transformer-CNF), along with molecular descriptors (ECFP fingerprint and Mordred properties), for their performance in predicting the T m of ILs. Remarkably, among the investigated modeling schemes, the pSCNN, coupled with filtered Mordred descriptors, demonstrates superior performance, yielding mean absolute error (MAE) and root-mean-square error (RMSE) values of 24.36 and 31.56 °C, respectively. Feature analysis further highlights the effectiveness of the pSCNN model. Moreover, the pSCNN method, with a pair of inputs, can be extended beyond ionic liquid melting point prediction.

Hydrogen mitigates brain injury by prompting NEDD4-CX43- mediated mitophagy in traumatic brain injury.

BACKGROUND: Hydrogen (H2) has emerged as a potential therapeutic intervention for traumatic brain injury (TBI). However, the precise mechanism underlying H2's neuroprotective effects in TBI remain incompletely understood. METHODS: TBI mouse model was induced using the controlled cortical impact (CCI) method, and a cell model was established by exposing astrocytes to lipopolysaccharide (LPS). Cell viability was detected by CCK-8 kits. Cell apoptosis was measured by flow cytometry. ELISA was used to detect cytokine quantification. Protein and gene expression was detected by western blot and RT-PCR analysis. Co-immunoprecipitation (CO-IP) were employed for protein-protein interactions. Morris water maze test and rotarod test were applied for TBI mice. RESULTS: H2 treatment effectively inhibited the LPS-induced cell injury and cell apoptosis in astrocytes. NEDD4 expression was increased following H2 treatment coupled with enhanced mitophagy in LPS-treated astrocytes. Overexpression of NEDD4 and down-regulation of connexin 43 (CX43) mirrored the protective effects of H2 treatment in LPS-exposed astrocytes. NEDD4 interacts CX43 to regulates the ubiquitinated degradation of CX43. While overexpression of CX43 reversed the protective effects of H2 treatment in LPS-exposed astrocytes. In addition, H2 treatment significantly alleviated brain injury in TBI mouse model. CONCLUSION: H2 promoted NEDD4-CX43 mediated mitophagy to protect brain injury induced by TBI, highlighting a novel pathway underlying the therapeutic effects of H2 in TBI.

A smart tablet-phone-based high-performance pancreatic cancer cell biosensing system for drug screening.

Exploring more efficient pancreatic cancer drug screening platforms is of significant importance for accelerating the drug development process. In this study, we developed a high-sensitivity bioluminescence system based on smartphones and smart tablets, and constructed a pancreatic cancer drug screening platform (PCDSP) by combining the pancreatic cancer cell sensing model (PCCSM) on the multiwell plates (MTP). A smart tablet was used as the light source and a smartphone as the colorimetric sensing device. The smartphone dynamically controls the color and brightness displayed on the smart tablet to achieve lower LOD and wider detection ranges. We constructed PCCSM for 24 h, 48 h, and 72 h , and performed colorimetric experiments using both PCDSP and a commercial plate reader (CPR). The results showed that the PCDSP had a lower LOD than that of CPR. Moreover, PCDSP even exhibited a lower LOD for 24 h PCCSM testing compared to CPR for 48 h PCCSM testing, effectively shortening the drug evaluation process. Additionally, the PCDSP offers higher portability and efficiency compared with CPR, making it a promising platform for efficient pancreatic cancer drug screening.

Machine Learning for Prediction of Non-Small Cell Lung Cancer Based on Inflammatory and Nutritional Indicators in Adults: A Cross-Sectional Study.

Purpose: The aim of this study was to evaluate the potential benefit of blood inflammation in the diagnosis of non-small cell lung cancer (NSCLC) and propose a machine-learning-based method to predict NSCLC in asymptomatic adults. Patients and Methods: A cross-sectional study was evaluated using medical records of 139 patients with non-small cell lung cancer and physical examination data from May 2022 to May 2023 of 198 healthy controls. The NSCLC cohort comprised 128 cases of adenocarcinoma, 3 cases of squamous cell carcinoma, and 8 cases of other NSCLC subtypes. The correlation between inflammatory and nutritional markers, such as monocytes, neutrophils, LMR, NLR, PLR, PHR and non-small cell lung cancer was examined. Features were selected using Python's feature selection library and analyzed by five algorithms. The predictive ability of the model for non-small cell lung cancer diagnosis was assessed by precision, accuracy, recall, F1 score, and area under the curve (AUC). Results: The results showed that the top 14 important factors were PDW, age, TP, RBC, HGB, LYM, LYM%, RDW, PLR, LMR, PHR, MONO, MONO%, gender. Additionally, the naive Bayes (NB) algorithm demonstrated the highest overall performance in predicting adult NSCLC among the five machine learning algorithms, achieving an accuracy of 0.87, a macro average F1 score of 0.85, a weighted average F1 score of 0.87, and an AUC of 0.84. Conclusion: In feature ranking, platelet distribution width was the most important feature, and the NB algorithm performed best in predicting adult NSCLC diagnosis.

Mass measurement under medium vacuum in optically levitated nanoparticles based on Maxwell speed distribution law.

As one of the directions of optical levitation technology, the mass measurement of micro-nano particles has always been a research hotspot in extremely weak mechanical measurements. When nanoscale particles are trapped in an optical trap, parameters such as density, diameter, and shape are unknown. Here we propose what we believe to be a new method to measure mass by fitting particle motion information to the Maxwell speed distribution law, with an accuracy better than 7% at 10 mbar. This method has the characteristics of requiring no external driving force, no precise natural frequency, no prior information such as density, and non-destructive testing within the medium vacuum range. With the increasing iterations, the uncertainty of mass measurement is reduced, and the accuracy of mass measurement of levitated particles is verified under multiple air pressures. It provides what we believe is a new method for the future non-destructive testing of nanoscale particles, and provides an apparently new way for the sensing measurement and metrology application fields of levitation dynamics systems.

Acetyl-CoA Synthetase Mutations S868G and V949I Do Not Confer Resistance to Antimalarial Drugs in vitro in Plasmodium falciparum.

Plasmodium falciparum acetyl-CoA synthetase (PfACAS) protein is an important source of acetyl-CoA. We detected the mutations S868G and V949I in PfACAS by whole-genome sequencing analysis in some recrudescent parasites after antimalarial treatment with artesunate and dihydroartemisinin-piperaquine, suggesting that they may confer drug resistance. Using CRISPR/Cas9 technology, we engineered parasite lines carrying the PfACAS S868G and V949I mutations in two genetic backgrounds and evaluated their susceptibility to antimalarial drugs in vitro. The results demonstrated that PfACAS S868G and V949I mutations alone or in combination were not enough to provide resistance to antimalarial drugs.

Recurrent bacterial meningitis caused by incomplete Type I inner ear malformation: A case report.

The incidence of incomplete partition Type I inner ear malformation is very low; therefore, bacterial meningitis caused by this malformation is also rare. Here, we report a case of such a patient. This case is a young female patient, who is 7 years old, began to have recurrent headaches, and after 5 years, also began to have chest and back pain. The doctor diagnosed meningitis, and the anti-infection treatment was effective. She was followed up annually and continued to have outbreaks repeatedly for 17 years, but the cause of repeated infection was not found. After a detailed diagnosis and treatment in our hospital, the patient was finally diagnosed with incomplete partition Type I inner ear malformation, resulting in repeated bacterial meningitis. The patient recovered well after surgical treatment, and the symptoms did not recur after 1-year follow-up.

Application of C-InGAN Model in Interpretable Feature of Bearing Fault Diagnosis.

Although traditional fault diagnosis methods are proficient in extracting signal features, their diagnostic interpretability remains challenging. Consequently, this article proposes a conditionally interpretable generative adversarial network (C-InGAN) model for the interpretable feature fault diagnosis of bearings. Initially, the vibration signal is denoised and transformed into a frequency domain signal. The model consists of the two primary networks, each employing a convolutional layer and an attention module, generator (G) and discriminator (D), respectively. Latent code was incorporated into G to constrain the generated samples, and a discriminant layer was added to D to identify the interpretable features. During training, the two networks were alternately trained, and the feature mapping relationship of the pre-normalized encoder was learned by maximizing the information from the latent code and the discriminative result. The encoding that represents specific features in the vibration signal was extracted from the random noise. Ultimately, after completing adversarial learning, G is capable of generating a simulated signal of the specified feature, and D can assess the interpretable features in the vibration signal. The effectiveness of the model is validated through three typical experimental cases. This method effectively separates the discrete and continuous feature coding in the signal.

Exploring the environmental risks and seasonal variations of potentially toxic elements (PTEs) in fine road dust in resource-based cities based on Monte Carlo simulation, geo-detector and random forest model.

The environmental pollution caused by mineral exploitation and energy consumption poses a serious threat to ecological security and human health, particularly in resource-based cities. To address this issue, a comprehensive investigation was conducted on potentially toxic elements (PTEs) in road dust from different seasons to assess the environmental risks and influencing factors faced by Datong City. Multivariate statistical analysis and absolute principal component score were employed for source identification and quantitative allocation. The geo-accumulation index and improved Nemerow index were utilized to evaluate the pollution levels of PTEs. Monte Carlo simulation was employed to assess the ecological-health risks associated with PTEs content and source orientation. Furthermore, geo-detector and random forest analysis were conducted to examine the key environmental variables and driving factors contributing to the spatiotemporal variation in PTEs content. In all PTEs, Cd, Hg, and Zn exhibited higher levels of content, with an average content/background value of 3.65 to 4.91, 2.53 to 3.34, and 2.15 to 2.89 times, respectively. Seasonal disparities were evident in PTEs contents, with average levels generally showing a pattern of spring (winter) > summer (autumn). PTEs in fine road dust (FRD) were primarily influenced by traffic, natural factors, coal-related industrial activities, and metallurgical activities, contributing 14.9-33.9 %, 41.4-47.5 %, 4.4-8.3 %, and 14.2-29.4 % to the total contents, respectively. The overall pollution and ecological risk of PTEs were categorized as moderate and high, respectively, with the winter season exhibiting the most severe conditions, primarily driven by Hg emissions from coal-related industries. Non-carcinogenic risk of PTEs for adults was within the safe limit, yet children still faced a probability of 4.1 %-16.4 % of unacceptable risks, particularly in summer. Carcinogenic risks were evident across all demographics, with children at the highest risk, mainly due to Cr and smelting industrial sources. Geo-detector and random forest model indicated that spatial disparities in prioritized control elements (Cr and Hg) were primarily influenced by particulate matter (PM10) and anthropogenic activities (industrial and socio-economic factors); variations in particulate matter (PM10 and PM2.5) and meteorological factors (wind speed and precipitation) were the primary controllers of seasonal disparities of Cr and Hg.

Reducing carbon and nitrogen loss by shortening the composting duration based on seed germination index (SCD@GI): Feasibilities and challenges.

Addressing carbon (C) and nitrogen (N) losses through composting has emerged as a critical environmental challenge recently, and how to mitigate these losses has been a hot topic across the world. As the emissions of carbonaceous and nitrogenous gases were closely correlated with the composting process, the feasibility of composting duration shortening on C and N loss needs to be explored. Therefore, the goal of this paper is to find evidence-based approaches to reduce composting duration, utilizing the seed germination index as a metric (SCD@GI), for assessing its efficiency on C and N loss reductions as well as compost quality. Our findings reveal that the terminal seed germination index (GI) frequently surpassed the necessary benchmarks, with a significant portion of trials achieving the necessary GI within 60 % of the standard duration. Notably, an SCD@GI of 80 % resulted in a reduction of CO2 and NH3 by 21.4 % and 21.9 %, respectively, surpassing the effectiveness of the majority of current mitigation strategies. Furthermore, compost quality, maturity specifically, remained substantially unaffected at a GI of 80 %, with the composting process maintaining adequate thermophilic conditions to ensure hygienic quality and maturity. This study also highlighted the need for further studies, including the establishment of uniform GI testing standards and comprehensive life cycle analyses for integrated composting and land application practices. The insights gained from this study would offer new avenues for enhancing C and N retention during composting, contributing to the advancement of high-quality compost production within the framework of sustainable agriculture.

Deceased Donors With HIV in the Era of the HOPE Act: Referrals and Procurement.

Background: The HIV Organ Policy Equity Act legalizes organ procurement from donors with HIV (HIV D+). A prior survey of Organ Procurement Organizations (OPOs) estimated >2000 HIV D+ referrals/year; however, only 30-35 HIV D+/year have had organs procured. Given this gap, we sought to understand HIV D+ referrals and procurements in practice. Methods: We prospectively collected data on all OPO-reported HIV D+ referrals, including reasons for nonprocurement. We evaluated trends and compared HIV D+ characteristics by procurement status using regression, chi-squared tests, and Wilcoxon rank-sum tests. Results: From December 23, 2015 to May 31, 2021, there were 710 HIV D+ referrals from 49 OPOs, of which 171 (24%) had organs procured. HIV D+ referrals increased from 7 to 15 per month (P < 0.001), and the procurement rate increased from 10% to 39% (P < 0.001). Compared with HIV D+ without procurement, HIV D+ with procurement were younger (median age 36 versus 50 y), more commonly White (46% versus 36%), and more often had trauma-related deaths (29% versus 8%) (all P < 0.001). Nonprocurement was attributed to medical reasons in 63% of cases, of which 36% were AIDS-defining infections and 64% were HIV-unrelated, commonly due to organ failure (36%), high neurologic function (31%), and cancer (14%). Nonprocurement was attributed to nonmedical reasons in 26% of cases, commonly due to no authorization (42%), no waitlist candidates (21%), or no transplant center interest (20%). Conclusions: In the early years of the HIV Organ Policy Equity Act, actual HIV D+ referrals were much lower than prior estimates; however, the numbers and procurement rates increased over time. Nonprocurement was attributed to both medical and nonmedical issues, and addressing these issues could increase organ availability.