N6-methyladenosine-mediated upregulation of LNCAROD confers radioresistance in esophageal squamous cell carcinoma through stabilizing PARP1.

BACKGROUND: Radiotherapy is a primary therapeutic modality for esophageal squamous cell carcinoma (ESCC), but its effectiveness is still restricted due to the resistance of cancer cells to radiation. Long non-coding RNAs (lncRNAs) and N6-methyladenosine (m6A) have been shown to play significant roles in tumour radioresistance. However, the precise manifestation and role of m6A-modified lncRNAs in ESCC radioresistance remain unclear. METHODS: Bioinformatics analysis was conducted to identify m6A-modified lncRNAs implicated in the radioresistance of ESCC. A series of functional experiments were performed to investigate the function of LNCAROD in ESCC. Methylated RNA immunoprecipitation, chromatin isolation by RNA purification-mass spectrometry, RNA immunoprecipitation, and co-immunoprecipitation experiments were performed to explore the mechanism of m6A-mediated upregulation of LNCAROD expression and the downstream mechanism enhancing the radioresistance of ESCC. The efficacy of LNCAROD in vivo was assessed using murine xenograft models. RESULTS: Herein, we identified LNCAROD as a novel METTL3-mediated lncRNA that enhanced radioresistance in ESCC cells and was post-transcriptionally stabilised by YTHDC1. Moreover, we confirmed that LNCAROD prevented ubiquitin-proteasome degradation of PARP1 protein by facilitating PARP1-NPM1 interaction, thereby contributing to homologous recombination-mediated DNA double-strand breaks repair and enhancing the radiation resistance of ESCC cells. Silencing LNCAROD in a nude mouse model of ESCC in vivo resulted in slower tumour growth and increased radiosensitivity. CONCLUSION: Our findings enhance the understanding of m6A-modified lncRNA-driven machinery in ESCC radioresistance and underscore the significance of LNCAROD in this context, thereby contributing to the development of a potential therapeutic target for ESCC patients.

Unveiling the potential role of virus-encoded polyphosphate kinases in enhancing phosphorus removal in activated sludge systems.

While microbial phosphate removal in activated sludge (AS) systems has been extensively studied, the role of viruses in this process remains largely unexplored. In this study, we identified 149 viral auxiliary metabolic genes associated with phosphorus cycling from 2,510 viral contigs (VCs) derived from AS systems. Notably, polyphosphate kinase 1 (ppk1) and polyphosphate kinase 2 (ppk2) genes, which are primarily responsible for phosphate removal, were found in five unclassified VCs. These genes exhibited conserved protein structures and active catalytic sites, indicating a pivotal role of viruses in enhancing phosphorus removal. Phylogenetic analysis demonstrated a close relationship between viral ppk genes and their bacterial counterparts, suggesting the occurrence of horizontal gene transfer. Furthermore, experimental assays validated that viral ppk genes enhanced host phosphate removal capabilities. VCs carrying ppk genes were observed across diverse ecological and geographical contexts, suggesting their potential to bolster host functions in varied environmental and nutrient settings, spanning natural and engineered systems. These findings uncover a previously underappreciated mechanism by which viruses enhance phosphate removal in wastewater treatment plants. Overall, our study highlights the potential for leveraging virus-encoded genes to improve the efficiency of biological phosphorus removal processes, offering new insights into the microbial ecology of AS systems and the role of viruses in biogeochemical cycling.

Seed Priming with Dynamically Transformed Selenium Nanoparticles to Enhance Salt Tolerance in Rice.

Seed priming with nanomaterials is an emerging approach for improving plant stress tolerance. Here, we demonstrated a mechanism for enhancing salt tolerance in rice under salt stress via priming with nonstimulatory nanoparticles such as selenium nanoparticles (SeNPs), distinct from stimulatory nanomaterials. Due to the dynamic transformation ability of SeNPs, SeNP priming could enhance rice salt tolerance by mediating the glutathione cycle to eliminate excess reactive oxygen species (ROS). During priming, SeNPs penetrated rice seeds and transitioned into a soluble form (99.9%) within the embryo endosperm. Subsequently, the soluble selenium (Se) was transported to rice roots and metabolized into various Se-related derivatives, including selenomethionine (SeMet), Na2SeO3 (Se IV), selenocysteine (SeCys2), and methylselenocysteine (MeSeCys). These derivatives significantly enhanced the root activities of key enzymes such as glutathione peroxidase (GSH-PX), glutathione reductase (GR), catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) by 24.97%, 47.98%, 16.23%, 16.81%, and 14.82%, respectively, thus reinforcing the glutathione cycle and ROS scavenging pathways. Moreover, these alterations induced transcriptional changes in rice seedlings, with genes involved in signal transduction, transcription factors (TFs), ROS scavenging, and protein folding being upregulated, activating signal perception and self-repair mechanisms. These findings offer valuable insights for the agricultural application of nanomaterials.

Quantum classical hybrid convolutional neural networks for breast cancer diagnosis.

The World Health Organization states that early diagnosis is essential to increasing the cure rate for breast cancer, which poses a danger to women's health worldwide. However, the efficacy and cost limitations of conventional diagnostic techniques increase the possibility of misdiagnosis. In this work, we present a quantum hybrid classical convolutional neural network (QCCNN) based breast cancer diagnosis approach with the goal of utilizing quantum computing's high-dimensional data processing power and parallelism to increase diagnosis efficiency and accuracy. When working with large-scale and complicated datasets, classical convolutional neural network (CNN) and other machine learning techniques generally demand a large amount of computational resources and time. Their restricted capacity for generalization makes it challenging to maintain consistent performance across multiple data sets. To address these issues, this paper adds a quantum convolutional layer to the classical convolutional neural network to take advantage of quantum computing to improve learning efficiency and processing speed. Simulation experiments on three breast cancer datasets, GBSG, SEER and WDBC, validate the robustness and generalization of QCCNN and significantly outperform CNN and logistic regression models in classification accuracy. This study not only provides a novel method for breast cancer diagnosis but also achieves a breakthrough in breast cancer diagnosis and promotes the development of medical diagnostic technology.

Early inhibition of BRD4 facilitates iPSC reprogramming via accelerating rDNA dynamic expression.

BACKGROUND: iPSC reprogramming technology exhibits significant promise in the realms of clinical therapeutics, disease modeling, pharmaceutical drug discovery, and various other applications. However, the extensive utilization of this technology has encountered impediments in the form of inefficiency, prolonged procedures, and ambiguous biological processes. Consequently, in order to improve this technology, it is of great significance to delve into the underlying mechanisms involved in iPSC reprogramming. The BET protein BRD4 plays a crucial role in the late stage of reprogramming; however, its precise function in the early stage remains unclear. RESULTS: Our study aims to investigate BRD4's role in the early stages of iPSC reprogramming. Our investigation reveals that early inhibition of BRD4 substantially enhances iPSC reprogramming, whereas its implementation during the middle-late stage impedes the process. During the reprogramming, ribosome DNA expression initially increases before decreasing and then gradually recovers. Early inhibition of BRD4 improved the decline and restoration of rDNA expression in the early and middle-late stages, respectively. Additionally, we uncovered the mechanism of BRD4's regulation of rDNA transcription throughout reprogramming. Specifically, BRD4 interacts with UBF and co-localizes to both the rDNA promoter and enhancer regions. Ultimately, BRD4 facilitates rDNA transcription by promoting the enrichment of histone H3 lysine 27 acetylation in the surrounding chromatin. Moreover, we also discovered that early inhibition of BRD4 facilitates cells' transition out of the somatic cell state and activate pluripotent genes. CONCLUSIONS: In conclusion, our results demonstrate that early inhibition of BRD4 promotes sequential dynamic expression of rDNA, which improves iPSC reprogramming efficiency.

PDHX acetylation facilitates tumor progression by disrupting PDC assembly and activating lactylation mediated gene expression.

Deactivation of the mitochondrial pyruvate dehydrogenase complex (PDC) is important for the metabolic switching of cancer cell from oxidative phosphorylation to aerobic glycolysis. Studies examining PDC activity regulation have mainly focused on the phosphorylation of pyruvate dehydrogenase (PDH, E1), leaving other post-translational modifications (PTMs) largely unexplored. Here, we demonstrate that the acetylation of Lys 488 of pyruvate dehydrogenase complex component X (PDHX) commonly occurs in hepatocellular carcinoma (HCC), disrupting PDC assembly and contributing to lactate-driven epigenetic control of gene expression. PDHX, an E3-binding protein (E3BP) in the PDC, is acetylated by the p300 at Lys 488, impeding the interaction between PDHX and dihydrolipoyl transacetylase (DLAT, E2), thereby disrupting PDC assembly to inhibit its activation. PDC disruption results in the conversion of most glucose to lactate, contributing to the aerobic glycolysis and H3K56 lactylation-mediated gene expression, facilitating tumor progression. These findings highlight a previously unrecognized role of PDHX acetylation in regulating PDC assembly and activity, linking PDHX Lys 488 acetylation and histone lactylation during HCC progression and providing a potential biomarker and therapeutic target for further development.

Multiple Primary Cavernous Hemangiomas of the Skull.

Multiple primary cavernous hemangiomas of the skull are exceedingly rare, with surgery often being the treatment of choice. The complexity of radiologic diagnosis means that the identification of these hemangiomas still largely depends on pathologic analysis. This article outlines the diagnostic and therapeutic journey of a 52-year-old female patient afflicted with multiple primary cavernous hemangiomas of the skull. Although the occurrence of multiple cavernous hemangiomas in this patient may seem fortuitous, the authors aim to contribute to understanding the pathogenesis of such conditions through this case report.

Indigenized Characterization Factors for Health Damage Due to Ambient PM2.5 in Life Cycle Impact Assessment in China.

Life cycle assessment (LCA) is a broadly used method for quantifying environmental impacts, and life cycle impact assessment (LCIA) is an important step as well as a major source of uncertainties in LCA. Characterization factors (CFs) are pivotal elements in LCIA models. In China, the health loss due to ambient PM2.5 is an important aspect of LCIA results, which, however, is generally assessed by adopting CFs developed by global models and there remains a need to integrate localized considerations and the latest information for more precise applications in China. In this study, we developed indigenized CFs for LCIA of health damage due to ambient PM2.5 in China by coupling the atmospheric chemical transport model GEOS-Chem, exposure-response model GEMM containing Chinese cohort studies, and the latest local data. Results show that CFs of four major PM2.5 precursors all exhibit significant interregional variation and monthly differences in China. Our results were generally an order of magnitude higher and show disparate spatial distribution compared to CFs currently in use, suggesting that the health damage due to ambient PM2.5 was underestimated in LCIA in China, and indigenized CFs need to be adopted for more accurate results in LCIA and LCA studies.

Mid-Pleistocene climate transition triggered by Antarctic Ice Sheet growth.

Despite extensive investigation, the nature and causes of the Mid-Pleistocene Transition remain enigmatic. In this work, we assess its linkage to asynchronous development of bipolar ice sheets by synthesizing Pleistocene mid- to high-latitude proxy records linked to hemispheric ice sheet evolution. Our results indicate substantial growth of the Antarctic Ice Sheets (AISs) at 2.0 to 1.25 million years ago, preceding the rapid expansion of Northern Hemisphere Ice Sheets after ~1.25 million years ago. Proxy-model comparisons suggest that AIS and associated Southern Ocean sea ice expansion can induce northern high-latitude cooling and enhanced moisture transport to the Northern Hemisphere, thus triggering the Mid-Pleistocene Transition. The dynamic processes involved are crucial for assessing modern global warming that is already inducing asynchronous bipolar melting of ice sheets.

Polysulfone membranes decorated with Fe-Mn binary oxide nanoparticles and polydopamine for enhanced arsenate/arsenite adsorptive removal.

Arsenic contamination of water is a global environmental concern, and membrane technology combined with nanotechnology contributes to more efficient removal of arsenic. In this study, Fe-Mn oxide (FM), Polydopamine (PDA), and PDA-modified FM (PFM) were incorporated into polysulfone (PSF) to prepare adsorption membranes (PFMP) for arsenic removal. The prepared nanoparticles and membranes were characterized using TEM, SEM, FTIR, TGA, contact angle, and pure water flux. The introduction of particles enhanced the hydrophilicity of the membranes and significantly enhanced the pure water flux of the membranes. Adsorption experiments indicated that the PFMP membrane exhibited the best arsenic removal performance, with maximum adsorption capacities for As(III) and As(V) were 11.57 mg/g and 12.39 mg/g, respectively. The Langmuir model fitted the adsorption isotherms well, and the kinetics followed the pseudo-second-order model. The filtration experiment revealed that the PFMP membrane was capable of reducing As(III) solution (915 L/m2) and As(V) solution (1075 L/m2) from a concentration of 100 µg/L to the safe limit of As (＜10 µg/L). The As-loaded membrane was regenerated using NaOH solution (pH = 11), and the filtration experiment was repeated. FTIR and XPS demonstrated that the mechanism of the reaction between the membrane and arsenic was ligand exchange, where the arsenic ions were bonded to the oxygen ions to form Mn-O-As and Fe-O-As.

Overcoming Challenges in Oligonucleotide Therapeutics Analysis: A Novel Nonion Pair Approach.

Oligonucleotide therapeutics (OT) have emerged as promising drug modality for various intractable diseases. Recently, liquid chromatography-mass spectrometry (LC-MS) has been commonly employed for characterizing and quantifying OT in biological samples. Traditionally, the ion pairing-reverse phase (IP-RP) LC-MS method has been utilized in OT bioanalyses; however, this approach is associated with several limitations, including the memory effect and ion suppression effect of IP reagents. Therefore, this study aimed to develop a new RP-LC-MS method that eliminates the need for IP reagents. Our investigation revealed that ammonium bicarbonate was essential for the successful implementation of this nonIP-RP-LC-MS-based bioanalysis of OT. Moreover, the developed method demonstrated high versatility, accommodating the analysis of various natural or chemically modified oligonucleotides. The sensitivity of the method was further assessed using reconstituted plasma samples (the lower limit of quantification in this experiment was 0.5-1 ng/mL). In summary, the developed nonIP-RP-LC-MS method offers an easy, reliable, and cost-effective approach to the bioanalysis of OT.

Methods for constructing and evaluating consensus genomic interval sets.

The amount of genomic region data continues to increase. Integrating across diverse genomic region sets requires consensus regions, which enable comparing regions across experiments, but also by necessity lose precision in region definitions. We require methods to assess this loss of precision and build optimal consensus region sets. Here, we introduce the concept of flexible intervals and propose three novel methods for building consensus region sets, or universes: a coverage cutoff method, a likelihood method, and a Hidden Markov Model. We then propose three novel measures for evaluating how well a proposed universe fits a collection of region sets: a base-level overlap score, a region boundary distance score, and a likelihood score. We apply our methods and evaluation approaches to several collections of region sets and show how these methods can be used to evaluate fit of universes and build optimal universes. We describe scenarios where the common approach of merging regions to create consensus leads to undesirable outcomes and provide principled alternatives that provide interoperability of interval data while minimizing loss of resolution.

Uptake of zinc from the soil to the wheat grain: Nonlinear process prediction based on artificial neural network and geochemical data.

Trace elements in plants primarily derive from soils, subsequently influencing human health through the food chain. Therefore, it is essential to understand the relationship of trace elements between plants and soils. Since trace elements from soils absorbed by plants is a nonlinear process, traditional multiple linear regression (MLR) models failed to provide accurate predictions. Zinc (Zn) was chosen as the objective element in this case. Using soil geochemical data, artificial neural networks (ANN) were utilized to develop predictive models that accurately estimated Zn content within wheat grains. A total of 4036 topsoil samples and 73 paired rhizosphere soil-wheat samples were collected for the simulation study. Through Pearson correlation analysis, the total content of elements (TCEs) of Fe, Mn, Zn, and P, as well as the available content of elements (ACEs) of B, Mo, N, and Fe, were significantly correlated with the Zn bioaccumulation factor (BAF). Upon comparison, ANN models outperformed MLR models in terms of prediction accuracy. Notably, the predictive performance using ACEs as input factors was better than that using TCEs. To improve the accuracy, a two-step model was established through multiple testing. Firstly, ACEs in the soil were predicted using TCEs and properties of the rhizosphere soil as input factors. Secondly, the Zn BAF in grains was predicted using ACE as input factors. Consequently, the content of Zn in wheat grains corresponding to 4036 topsoil samples was predicted. Results showed that 85.69 % of the land was suitable for cultivating Zn-rich wheat. This finding offers a more accurate method to predict the uptake of trace elements from soils to grains, which helps to warn about abnormal levels in grains and prevent potential health risks.

Experimental and Theoretical Studies on Long Alkyl Chain-Bearing Dibenzotriazole Ionic Liquids as Eco-friendly Corrosion Inhibitors in Aqueous Hydrochloride Acid.

Three long alkyl chain-bearing dibenzotriazole ionic liquids (BTA-R-BTA, R = 8, 12, and 16) were synthesized with high yield (>98%) through a simple and eco-friendly process. Their anticorrosion performance for Q235 carbon steel in 6 M hydrochloride acid was comprehensively evaluated by weight loss tests, electrochemical methods (potentiodynamic polarization and electrochemical impedance spectroscopy), and surface analysis techniques. As the length of the alkyl chain increased, the maximum corrosion inhibition efficiency enhanced from 55.02% (for BTA-8-BTA at 1.2 mM) to 97.10% (for BTA-12-BTA at 0.3 mM) and 98.84% (for BTA-16-BTA at 0.3 mM). Density functional theory calculation indicated that the alkyl chain length had little influence on the inhibitors' electronic structures, while molecular dynamics simulations revealed that the thickness, surface coverage, and compactness of adsorption films formed at the metal-electrolyte interface increased with the elongated alkyl chain. Corrosion inhibition efficiency is strongly correlated with the structures of the adsorption film.

Lactate modulates zygotic genome activation through H3K18 lactylation rather than H3K27 acetylation.

In spite of its essential role in culture media, the precise influence of lactate on early mouse embryonic development remains elusive. Previous studies have implicated lactate accumulation in medium affecting histone acetylation. Recent research has underscored lactate-derived histone lactylation as a novel epigenetic modification in diverse cellular processes and diseases. Our investigation demonstrated that the absence of sodium lactate in the medium resulted in a pronounced 2-cell arrest at the late G2 phase in embryos. RNA-seq analysis revealed that the absence of sodium lactate significantly impaired the maternal-to-zygotic transition (MZT), particularly in zygotic gene activation (ZGA). Investigations were conducted employing Cut&Tag assays targeting the well-studied histone acetylation and lactylation sites, H3K18la and H3K27ac, respectively. The findings revealed a noticeable reduction in H3K18la modification under lactate deficiency, and this alteration showed a significant correlation with changes in gene expression. In contrast, H3K27ac exhibited minimal correlation. These results suggest that lactate may preferentially influence early embryonic development through H3K18la rather than H3K27ac modifications.

Viewing 3D spatial biology with highly-multiplexed Raman imaging: from spectroscopy to biotechnology.

Understansding complex biological systems requires the simultaneous characterization of a large number of interacting components in their native 3D environment with high spatial resolution. Highly-multiplexed Raman imaging is an emerging general strategy for detecting biomarkers with scalable multiplexity and ultra-sensitivity based on a series of stimulated Raman scattering (SRS) techniques. Here we review recent advances in highly-multiplexed Raman imaging and how they contribute to the technological revolution in 3D spatial biology, focusing on the developmental pathway from spectroscopy study to biotechnology invention. We envision highly-multiplexed Raman imaging is taking off, which will greatly facilitate our understanding in biological and medical research fields.

Comparison of radiofrequency ablation and surgery for thyroid papillary microcarcinoma: efficacy, safety and life quality.

Objective: To compare the efficacy, safety and patients' quality of life of radiofrequency ablation (RFA) and surgery in the treatment of papillary thyroid microcarcinoma (PTMC). Methods: MEDLINE, EMBASE, Cochrane, CNKI and other databases were searched for studies on radiofrequency ablation versus traditional surgery for PTMC up to October 2022. RevMan5.4 software was used for Meta-analysis. Results: 10 articles were selected from 392 articles, including 873 cases of radiofrequency ablation and 781 cases of open surgery. After meta-analysis, the incidence of postoperative complications in the radiofrequency ablation group was lower than that in the surgery group, and the difference was statistically significant [OR=0.24, 95%CI (0.14,0.41), P<0.001]. There were no significant differences in lymph node metastasis rate, local recurrence rate, and new tumor rate between the two groups [OR=1.6, 95%CI (0.21, 12.41), P>0.05; OR=0.85, 95%CI (0.05, 13.8), P>0.05; OR=0.12, 95%CI (0.01, 0.98), P>0.05]. The treatment time and hospital stay in the radiofrequency ablation group were shorter than those in the open surgery group [MD=-49.99, 95%CI (-62.02, -37.97), P<0.001; MD=-5.21, 95%CI(-7.19,-3.23),P<0.001], and the cost was significantly lower than that of the traditional surgery group [SMD=-14.97, 95%CI (-19.14, -10.81), P<0.001]. The quality of life of patients in the radiofrequency ablation group was higher than that in the surgery group [MD=-1.61, 95%CI (-2.06, -1.17), P<0.001]. Conclusion: Compared with traditional open surgery, radiofrequency ablation for papillary thyroid microcarcinoma has the advantages of less trauma, fewer complications, faster recovery and higher quality of life. The indications need to be strictly controlled in the treatment. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier (CRD42022374987).

Macrophage-derived extracellular vesicles regulate skeletal stem/progenitor Cell lineage fate and bone deterioration in obesity.

Obesity-induced chronic inflammation exacerbates multiple types of tissue/organ deterioration and stem cell dysfunction; however, the effects on skeletal tissue and the underlying mechanisms are still unclear. Here, we show that obesity triggers changes in the microRNA profile of macrophage-secreted extracellular vesicles, leading to a switch in skeletal stem/progenitor cell (SSPC) differentiation between osteoblasts and adipocytes and bone deterioration. Bone marrow macrophage (BMM)-secreted extracellular vesicles (BMM-EVs) from obese mice induced bone deterioration (decreased bone volume, bone microstructural deterioration, and increased adipocyte numbers) when administered to lean mice. Conversely, BMM-EVs from lean mice rejuvenated bone deterioration in obese recipients. We further screened the differentially expressed microRNAs in obese BMM-EVs and found that among the candidates, miR-140 (with the function of promoting adipogenesis) and miR-378a (with the function of enhancing osteogenesis) coordinately determine SSPC fate of osteogenic and adipogenic differentiation by targeting the Pparα-Abca1 axis. BMM miR-140 conditional knockout mice showed resistance to obesity-induced bone deterioration, while miR-140 overexpression in SSPCs led to low bone mass and marrow adiposity in lean mice. BMM miR-378a conditional depletion in mice led to obesity-like bone deterioration. More importantly, we used an SSPC-specific targeting aptamer to precisely deliver miR-378a-3p-overloaded BMM-EVs to SSPCs via an aptamer-engineered extracellular vesicle delivery system, and this approach rescued bone deterioration in obese mice. Thus, our study reveals the critical role of BMMs in mediating obesity-induced bone deterioration by transporting selective extracellular-vesicle microRNAs into SSPCs and controlling SSPC fate.

Feature Extraction Methods for Underwater Acoustic Target Recognition of Divers.

The extraction of typical features of underwater target signals and excellent recognition algorithms are the keys to achieving underwater acoustic target recognition of divers. This paper proposes a feature extraction method for diver signals: frequency-domain multi-sub-band energy (FMSE), aiming to achieve accurate recognition of diver underwater acoustic targets by passive sonar. The impact of the presence or absence of targets, different numbers of targets, different signal-to-noise ratios, and different detection distances on this method was studied based on experimental data under different conditions, such as water pools and lakes. It was found that the FMSE method has the best robustness and performance compared with two other signal feature extraction methods: mel frequency cepstral coefficient filtering and gammatone frequency cepstral coefficient filtering. Combined with the commonly used recognition algorithm of support vector machines, the FMSE method can achieve a comprehensive recognition accuracy of over 94% for frogman underwater acoustic targets. This indicates that the FMSE method is suitable for underwater acoustic recognition of diver targets.