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Transcriptomic analysis from lung adenocarcinoma identified an 11-gene signature that could classify metabolic reprogramming phenotypes in patients.

Background: Lung cancer is a complex disease composed of neuroendocrine (NE) and non-NE tumors. Accurate diagnosis of lung cancer is essential in guiding therapeutic management. Several transcriptional signatures have been reported to distinguish between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) belonging to non-NE tumors. This study aims to identify a transcriptional panel that could distinguish the histological subtypes of NE tumors to complement the morphology-based classification of an individual.Methods: A public dataset with NE subtypes, including 21 small-cell lung cancer (SCLC), 56 large-cell NE carcinomas (LCNECs), and 24 carcinoids (CARCIs), and non-NE subtypes, including 85 ADC and 61 SCC, was used as a training set. In the training set, consensus clustering was first used to filter out the samples whose expression patterns disagreed with their histological subtypes. Then, a rank-based method was proposed to develop a panel of transcriptional signatures for determining the NE subtype for an individual, based on the within-sample relative gene expression orderings of gene pairs. Twenty-three public datasets with a total of 3,454 samples, which were derived from fresh-frozen, formalin-fixed paraffin-embedded, biopsies, and single cells, were used for validation. Clinical feasibility was tested in 10 SCLC biopsy specimens collected from cancer hospitals via bronchoscopy.Results: The NEsubtype-panel was composed of three signatures that could distinguish NE from non-NE, CARCI from non-CARCI, and SCLC from LCNEC step by step and ultimately determine the histological subtype for each NE sample. The three signatures achieved high average concordance rates with 97.31%, 98.11%, and 90.63%, respectively, in the 23 public validation datasets. It is worth noting that the 10 clinic-derived SCLC samples diagnosed via immunohistochemical staining were also accurately predicted by the NEsubtype-panel. Furthermore, the subtype-specific gene expression patterns and survival analyses provided evidence for the rationality of the reclassification by the NEsubtype-panel.Conclusion: The rank-based NEsubtype-panel could accurately distinguish lung NE from non-NE tumors and determine NE subtypes even in clinically challenging samples (such as biopsy). The panel together with our previously reported signature (KRT5-AGR2) for SCC and ADC would be an auxiliary test for the histological diagnosis of lung cancer.

This paper presents a model predictive thrust force control (MPTFC) method for a multiple-modular permanent magnet synchronous linear motor (PMSLM). It focuses on the thrust assignment and thrust ripple of the motor drive system with a multiple-branch inverter. A discrete time model of the PMSLM is established, and the driving system structure and operation principle of the motor are studied. A multi-mode cost function is designed according to the requirements of the different load conditions, and the optimal voltage vector action time is determined. The operation mode is analyzed to determine the distribution factor, so as to reduce the thrust pulsation during operation and improve the performance of the drive system. The results indicate that the proposed MPTFC method is effective in different operating modes, and the drive system has high efficiency and safer performance compared to a conventional drive system.

BackgroundTo identify a computed tomography (CT) derived radiomic signature for the options of concurrent chemo-radiotherapy (CCR) in patients with non-small cell lung cancer (NSCLC).MethodsA total of 226 patients with NSCLC receiving CCR were enrolled from public dataset, and allocated to discovery and validation sets based on patient identification number. Using CT images of 153 patients in the discovery dataset, we pre-selected a list of radiomic features significantly associated with 5-year survival rate and adopted the least absolute shrinkage and selection operator regression to establish a predictive radiomic signature for CCR treatment. We performed transcriptomic analyzes of the signature, and evaluated its association with molecular lesions and immune landscapes in a dataset with matched CT images and transcriptome data. Furthermore, we identified CCR resistant genes positively correlated with resistant scores of radiomic signature and screened essential resistant genes for NSCLC using genome-scale CRIPSR data. Finally, we combined DrugBank and Genomics of Drug Sensitivity in Cancer databases to excavate candidate therapeutic agents for patients with CCR resistance, and validated them using the Connectivity Map dataset.ResultsThe radiomic signature consisting of nine features was established, and then validated in the dataset of 73 patients receiving CCR log-rank P = 0.0005, which could distinguish patients into resistance and sensitivity groups, respectively, with significantly different 5-year survival rate. Furthermore, the novel proposed radiomic nomogram significantly improved the predictive performance (concordance indexes) of clinicopathological factors. Transcriptomic analyzes linked our signature with important tumor biological processes (e.g. glycolysis/glucoseogenesis, ribosome). Then, we identified 36 essential resistant genes, and constructed a gene-agent network including 10 essential resistant genes and 35 candidate therapeutic agents, and excavated AT-7519 as the therapeutic agent for patients with CCR resistance. The therapeutic efficacy of AT-7519 was validated that significantly more resistant genes were down-regulated induced by AT-7519, and the degree gradually increased with the enhanced doses.ConclusionsThis study illustrated that radiomic signature could non-invasively predict therapeutic efficacy of patients with NSCLC receiving CCR, and indicated that patients with CCR resistance might benefit from AT-7519 or CCR treatment combined with AT-7519.

Objective. To explore the correlation of complex impacted mandibular teeth and pericoronitis, as well as the effect of minimally invasive tooth extraction on patients’ long-term outcomes of masticatory ability. Methods. A total of 101 patients with complex impacted teeth who were treated in our hospital from March 2019 to June 2021 were selected and divided into the control group (n = 55) and the observation group (n = 46) according to the different treatment methods. The patients in the control group were given conventional extraction treatment, and the patients in the observation group were given minimally invasive extraction treatment. The clinicopathological features of patients complicated by pericoronitis were observed and the relationship between complex impacted mandibular teeth and pericoronitis was discussed. Additionally, we made statistics on operative time (OT), intraoperative blood loss (IBL), dental socket integrity score, and adverse reactions (ARs) and compared the clinical efficacy between the observation group and control group. The Visual Analogue Scale (VAS) and Oral Health Impact Profile scale (OHIP-14) were utilized for pain assessment and oral health status evaluation, respectively. Bite force (BF) and masticatory efficiency were also measured. Results. OG showed less OT and IBL than CG, with a higher dental socket integrity score (P0.05). After treatment, the VAS score of OG decreased, while the mouth-opening degree and OHIP-14 score increased (P0.05). Conclusion. Complex mandibular impacted teeth can easily induce pericoronitis, so clinicians should pay attention to the influencing factors of pericoronitis. Minimally invasive surgery for complex impacted mandibular teeth can effectively improve treatment outcomes, accelerate patient rehabilitation, and provide more effective protection for patients’ oral health and masticatory ability, which is worth promoting in clinical use.

The measurement of water cut in crude oil is an essential procedure in petroleum production and it is desirable to obtain these data through an automatic and real-time method. Microwave sensors can be used for the task, and they are safe, robust and can cover the whole water cut range. However, they are relatively susceptible to the water conductivity and temperature, and the algorithms for addressing these problems are still rare in the literature. In this paper, a microwave transmission sensor that can measure the water cut under varying salinity conditions is proposed, and the algorithm for solving the water cut and salinity simultaneously with the measured amplitude and phase is described in detail. Experiments under different water cut and salinity conditions are conducted, and the results are used to verify the model and algorithm. Finally, a simplified and fast method for uncertainty analysis is proposed and applied to the iteration algorithm under test conditions. It can be concluded that accuracy higher than 95% in the water cut measurements can be expected under the 0~100% water cut range, and an error of about 10% in the water conductivity is achievable under water-continuous flow conditions. The uncertainty analysis shows that the calculated water cut and salinity results are negatively correlated, and the water salinity uncertainty tends to be larger than the water cut uncertainty. When the water salinity is high, the water cut uncertainty tends to be high whereas the water salinity uncertainty tends to be low.

In this article, the electro-osmotic flow of Oldroyd-B fluid in a circular micro-channel with slip boundary condition is considered. The corresponding fractional system is represented by using a newly defined time-fractional Caputo-Fabrizio derivative without singular kernel. Closed form solutions for the velocity field are acquired by means of Laplace and finite Hankel transforms. Additionally, Stehfest’s algorithm is used for inverse Laplace transform. The solutions for fractional Maxwell, ordinary Maxwell and ordinary Newtonian fluids are obtained as limiting cases of the obtained solution. Finally, the influence of fractional and some important physical parameters on the fluid flow are spotlighted graphically.

A novel discrete-valued model-predictive control (DVMPC) algorithm termed DVMPC2 for the position control of pneumatic actuators using inexpensive on/off valves is presented. DVMPC2 includes a more flexible cost function, an improved prediction strategy, and other improvements. The actuator is a double-acting cylinder with two on/off solenoid poppet valves connected to each chamber. To reduce the switching frequency and prolong the valve life, DVMPC2 directly switches the valves when necessary, instead of using relatively high-frequency pulse-width modulation. Experimental comparisons are made with the state-of-the-art sliding-mode control (SMC) algorithm and the previous DVMPC algorithm. The comparisons are based on the five performance metrics: integral of time-weighted absolute error (ITAE), root mean square error (RMSE), overshoot (OS), steady-state error (SSE), and valve switches per second (SPS). The robustness is evaluated by increasing and decreasing the total mass of the moving components while keeping the controller parameters constant. The experimental results show that the proposed algorithm is superior to the previous DVMPC and outperformed SMC by a wide margin. Specifically, DVMPC2 reduced ITAE by 80%, RMSE by 52%, OS by 43%, and SPS by 20% relative to SMC. There was no clear winner in terms of SSE.

The electro-osmotic peristaltic flow of a viscoelastic fluid through a cylindrical micro-channel is studied in this paper. The fractional Jeffreys constitutive model, including the relaxation time and retardation time, is utilized to describe the viscoelasticity of the fluid. Under the assumptions of long wavelength, low Reynolds number, and Debye-Hückel linearization, the analytical solutions of pressure gradient, stream function and axial velocity are explored in terms of Mittag-Leffler function by Laplace transform method. The corresponding solutions of fractional Maxwell fluid and generalized second grade fluid are also obtained as special cases. The numerical analysis of the results are depicted graphically, and the effects of electro-osmotic parameter, external electric field, fractional parameters and viscoelastic parameters on the peristaltic flow are discussed.

Abstract Alkaline water electrolysis is a promising low-cost strategy for clean and sustainable hydrogen production but is largely limited by the sluggish anodic oxygen evolution reaction and the challenges in maintaining adequate separation between H2 and O2. Here, we reveal an anodic-cathodic sequential oxygen evolution process via electrochemical oxidation and subsequent reduction of Ni hydroxides, enabling much lower overpotentials than conventional anodic oxygen evolution. By using (isotope-labeled) differential electrochemical mass spectrometry and in situ Raman spectroscopy combined with density functional theory calculations, we evidence that the sequential oxygen evolution originates from the electrochemical oxidation of Ni hydroxides to NiOO– active species while undergoing a different, reductive step of NiOO– for the final release of O2 due to weakened Ni–O covalency. Based on this sequential process, we propose and demonstrate a hybrid water electrolysis and energy storage device, which enables time-decoupled hydrogen and oxygen evolution and electrochemical energy storage in the Ni hydroxides.

BackgroundLung adenocarcinoma (LUAD) is a heterogeneous tumor characterized by diverse genetic and molecular alterations. Developing a multi-omics-based classification system for LUAD is urgently needed to advance biological understanding.MethodsData on clinical and pathological characteristics, genetic alterations, DNA methylation patterns, and the expression of mRNA, lncRNA, and microRNA, along with somatic mutations in LUAD patients, were gathered from the TCGA and GEO datasets. A computational workflow was utilized to merge multi-omics data from LUAD patients through 10 clustering techniques, which were paired with 10 machine learning methods to pinpoint detailed molecular subgroups and refine a prognostic risk model. The disparities in somatic mutations, copy number alterations, and immune cell infiltration between high- and low-risk groups were assessed. The effectiveness of immunotherapy in patients was evaluated through the TIDE and SubMap algorithms, supplemented by data from various immunotherapy groups. Furthermore, the Cancer Therapeutics Response Portal (CTRP) and the PRISM Repurposing dataset (PRISM) were employed to investigate new drug treatment approaches for LUAD. In the end, the role of SLC2A1 in tumor dynamics was examined using RT-PCR, immunohistochemistry, CCK-8, wound healing, and transwell tests.ResultsBy employing multi-omics clustering, we discovered two unique cancer subtypes (CSs) linked to prognosis, with CS2 demonstrating a better outcome. A strong model made up of 17 genes was created using a random survival forest (RSF) method, which turned out to be an independent predictor of overall survival and showed reliable and impressive performance. The low-risk group not only had a better prognosis but also was more likely to display the “cold tumor” phenotype. On the other hand, individuals in the high-risk group showed a worse outlook and were more likely to respond positively to immunotherapy and six particular chemotherapy medications. Laboratory cell tests demonstrated that SLC2A1 is abundantly present in LUAD tissues and cells, greatly enhancing the proliferation and movement of LUAD cells.ConclusionsThorough examination of multi-omics data offers vital understanding and improves the molecular categorization of LUAD. Utilizing a powerful machine learning system, we highlight the immense potential of the riskscore in providing individualized risk evaluations and customized treatment suggestions for LUAD patients.

Abstract Hypoxic-ischemic brain damage (HIBD) can result in significant global rates of neonatal death or permanent neurological disability. N6-methyladenosine (m6A) modification of RNA influences fundamental aspects of RNA metabolism, and m6A dysregulation is implicated in various neurological diseases. However, the biological roles and clinical significance of m6A in HIBD remain unclear. We currently evaluated the effect of HIBD on cerebral m6A methylation in RNAs in neonatal rats. The m6A dot blot assay showed a global augmentation in RNA m6A methylation post-HI. Herein, we also report on demethylase FTO, which is markedly downregulated in the hippocampus and is the main factor involved with aberrant m6A modification following HI. By conducting a comprehensive analysis of RNA-seq data and m6A microarray results, we found that transcripts with m6A modifications were more highly expressed overall than transcripts without m6A modifications. The overexpression of FTO resulted in the promotion of Akt/mTOR pathway hyperactivation, while simultaneously inhibiting autophagic function. This is carried out by the demethylation activity of FTO, which selectively demethylates transcripts of phosphatase and tensin homolog (PTEN), thus promoting its degradation and reduced protein expression after HI. Moreover, the synaptic and neurocognitive disorders induced by HI were effectively reversed through the overexpression of FTO in the hippocampus. Cumulatively, these findings demonstrate the functional importance of FTO-dependent hippocampal m6A methylome in cognitive function and provides novel mechanistic insights into the therapeutic potentials of FTO in neonatal HIBD.

Abstract Saturated N-heterocyclic pyrrolidines are common in natural products, medicinal compounds and agrochemicals. However, reconstruction of their skeletal structures creating new chemical space is a challenging task, and limited methods exist for this purpose. In this study, we report a skeletal modification strategy for conversion of polar cyclic pyrrolidines into nonpolar linear dienes through a N-atom removal and deconstruction process. This involves N-sulfonylazidonation followed by rearrangement of the resulting sulfamoyl azide intermediates. This can be an energetically unfavorable process, which involves the formation of active C–C π bonds, the consumption of inert C–N and C–C σ bonds and the destruction of stable five-membered rings, but we have used it here to produce versatile conjugated and nonconjugated dienes with links of varying lengths. We also studied the application of this method in late-stage skeletal modification of bioactive compounds, formal traceless C(sp2)–H functionalization and formal N-atom deletion.