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This research explores the intricate-coupling relationship between typhoons and the ionosphere by the high-frequency surface wave radar's (HFSWR) over-the-horizon capabilities. This letter describes the gravity wave features in travelling ionospheric disturbances (TIDs) and ionospheric drift information. Further discussion is raised on the chaotic properties of gravity wave features using the Lyapunov exponents and chaotic attractors, particularly as they are influenced by typhoon. To predict these gravity wave features more accurately, a new model is developed by synergizing phase space reconstruction theory and statistical learning theory, a chaotic prediction model for gravity wave features constructed on a third-order Volterra filter. The experimental findings confirm that the gravity waves features detected via HFSWR present the hyperchaotic behaviour. More importantly, the innovative gravity wave prediction model based on chaotic attractor can capture the dynamics of the original chaotic system. Notably, the model's prediction accuracy has been improved by 98.6% after the introduction of phase space reconstruction modelling. [ABSTRACT FROM AUTHOR]

We show that the distribution class ℒ(γ) \ 풪풮 is not closed under infinitely divisible distribution roots for γ > 0, that is, we provide some infinitely divisible distributions belonging to the class, whereas the corresponding Lévy distributions do not. In fact, one part of these Lévy distributions belonging to the class 풪ℒ\ℒ(γ) have different properties, and the other parts even do not belong to the class 풪ℒ. Therefore, combining with the existing related results, we give a completely negative conclusion for the subject and Embrechts–Goldie conjecture. Then we discuss some interesting issues related to the results of this paper. [ABSTRACT FROM AUTHOR]

Background: The alkaloid camptothecin analog SN38 is a potent antineoplastic agent, but cannot be used directly for clinical application due to its poor water solubility. Currently, the prodrug approach on SN38 has resulted in 3 FDA-approved cancer therapeutics, irinotecan, ONIVYDE, and Trodelvy. However, only 2–8% of irinotecan can be transformed enzymatically in vivo into the active metabolite SN38, which severely limits the drug's efficacy. While numerous drug delivery systems have been attempted to achieve effective SN38 delivery, none have produced drug products with antitumor efficacy better than irinotecan in clinical trials. Therefore, novel approaches are urgently needed for effectively delivering SN38 to cancer cells with better efficacy and lower toxicity. Methods: Based on the unique properties of human serum albumin (HSA), we have developed a novel single protein encapsulation (SPE) technology to formulate cancer therapeutics for improving their pharmacokinetics (PK) and antitumor efficacy and reducing their side effects. Previous application of SPE technology to doxorubicin (DOX) formulation has led to a promising drug candidate SPEDOX-6 (FDA IND #, 152154), which will undergo a human phase I clinical trial. Using the same SPE platform on SN38, we have now produced two SPESN38 complexes, SPESN38-5 and SPESN38-8. We conducted their pharmacological evaluations with respect to maximum tolerated dose, PK, and in vivo efficacy against colorectal cancer (CRC) and soft tissue sarcoma (STS) in mouse models. Results: The lyophilized SPESN38 complexes can dissolve in aqueous media to form clear and stable solutions. Maximum tolerated dose (MTD) of SPESN38-5 is 250 mg/kg by oral route (PO) and 55 mg/kg by intravenous route (IV) in CD-1 mice. SPESN38-8 has the MTD of 45 mg/kg by IV in the same mouse model. PK of SPESN38-5 by PO at 250 mg/kg gave mouse plasma AUC0-∞ of 0.05 and 4.5 nmol × h/mL for SN38 and SN38 glucuronidate (SN38G), respectively, with a surprisingly high molar ratio of SN38G:SN38 = 90:1. However, PK of SPESN38-5 by IV at 55 mg/kg yielded much higher mouse plasma AUC0-∞ of 19 and 28 nmol × h/mL for SN38 and SN38G, producing a much lower molar ratio of SN38G:SN38 = 1.5:1. Antitumor efficacy of SPESN38-5 and irinotecan (control) was evaluated against HCT-116 CRC xenograft tumors. The data indicates that SPESN38-5 by IV at 55 mg/kg is more effective in suppressing HCT-116 tumor growth with lower systemic toxicity compared to irinotecan at 50 mg/kg. Additionally, SPESN38-8 and DOX (control) by IV were evaluated in the SK-LMS-1 STS mouse model. The results show that SPESN38-8 at 33 mg/kg is highly effective for inhibiting SK-LMS-1 tumor growth with low toxicity, in contrast to DOX's insensitivity to SK-LMS-1 with high toxicity. Conclusion: SPESN38 complexes provide a water soluble SN38 formulation. SPESN38-5 and SPESN38-8 demonstrate better PK values, lower toxicity, and superior antitumor efficacy in mouse models, compared with irinotecan and DOX. [ABSTRACT FROM AUTHOR]

The ionosphere is an integral element of the Earth and reflects the variations of the Earth's space weather and solar activity. Since extreme weather can cause ionospheric disturbances, changes in the ionosphere can indirectly enable early warning of extreme weather. The major intention of predicting the peak height of the ionospheric F2 layer (hmF2) in this paper is to acquire ionospheric variations over a period of time in a local area to facilitate future extreme weather warning research. In this paper, a dual element LSTM-CNN (long short term memory-convolutional neural network) prediction model is proposed to predict the hmF2. The performance of the proposed model is assessed by comparing it with other popular models such as SARIMA (seasonal differential autoregressive moving average), LSTM (long short term memory), BP (back propagation neural network) and IRI2016 (international reference ionospheric model) models. The outcome demonstrates that the prediction effect with the proposed model is remarkably excellent in comparison with the remaining four models. Furthermore, the proposed model has better sensitivity to rapid changes in parameters. The outcomes indicate that the forecasting model of this study has high prediction capabilities. [ABSTRACT FROM AUTHOR]

In this paper, a computational method is proposed for solving a class of fractional optimal control problems subject to canonical constraints of equality and inequality. Fractional derivatives are described in the Atangana–Baleanu-Caputo sense, and their fractional orders can be different. To solve this problem, we present a discretization scheme based on the trapezoidal rule and a novel numerical integration technique. Then, the gradient formulas of the cost and constraint functions with respect to the decision variables are derived. Furthermore, a gradient-based optimization algorithm for solving the discretized optimal control problem is developed. Finally, the applicability and effectiveness of the proposed algorithm are verified through three non-trivial example problems. [ABSTRACT FROM AUTHOR]

Aiming to utilize CO2 and solid waste form coal chemical industry synchronously, we proposed a novel process which integrated CO2 mineral carbonation and utilization of gasification slags based on chemical looping. With NH4Cl as the loop chemical, which generated HCl and NH3 through pyrolysis, the aluminum, calcium, and so forth were extracted by HCl from the coal slag, and CO2 was mineralized by calcium and NH3. NH4Cl was recovered after mineralization, and chemical looping was closed. A pilot setup with a capacity of 1‐kg CO2/h was conducted to demonstrate the feasibility of the chemical looping process. An airlift reactor was employed for mineral carbonation reaction, and conditions for extraction and mineral carbonation were optimized. The process presented the CO2 conversion of more than 90% with a calcium overall utilization ratio of 74.8%. The CO2 sequestration potential of the gasification slag is 121‐g CO2/kg slag, which is higher than that of steel slag and red mud. Calcium carbonate with the particle size of 1–10 μm can be obtained during the mineral carbonation. Simultaneously, the process extracted and enriched 62.3% of aluminum in the slag and enabled the deep utilization of the slag. [ABSTRACT FROM AUTHOR]

Thoracic aortic dissection (TAD) is a severe and extremely dangerous cardiovascular disease. Proliferation, migration and phenotypic switching of vascular smooth muscle cells (SMCs) are major pathogenetic mechanisms involved in the development of TAD. The present study was designed to investigate the expression and potential function of serine peptidase inhibitor Kunitz type 2 (SPINT2) in TAD. The gene expression profile data for ascending aorta from patients with TAD were downloaded from the GEO database with the accession number GSE52093. Bioinformatics analysis using GEO2R indicated that the differentially expressed SPINT2 was prominently decreased in TAD. The expression levels of SPINT2 mRNA and protein in aortic dissection specimens and normal aorta tissues were measured using reverse transcription-quantitative PCR and western blotting. SPINT2 expression was downregulated in clinical samples from aortic dissection specimens of patients with TAD compared with the corresponding expression noted in tissues derived from patients without TAD. In vitro, platelet-derived growth factor BB (PDGF-BB) was applied to induce the isolated primary mouse aortic SMC phenotypic modulation (a significant upregulation in the expression levels of synthetic markers), and the SMCs were infected with the adenoviral vector, Ad-SPINT2, to construct SPINT2-overexpressed cell lines. SMC viability was detected by an MTT assay and SMC proliferation was detected via the presence of Ki-67-positive cells (immunofluorescence staining). To explore the effects of SPINT2 on SMC migration, a wound healing assay was conducted. ELISA and western blotting assays were used to measure the content and expression levels of MMP-2 and MMP-9. The expression levels of vimentin, collagen I, α-SMA and SM22α were measured using western blotting. The PDGF-BB-induced proliferation and migration of SMCs were recovered by SPINT2 overexpression. The increase in the expression levels of SPINT2 reduced the expression levels of active matrix metalloproteinases (MMPs), MMP-2 and MMP-9. Overexpression of SPINT2 suppressed SMC switching from a contractile to a synthetic type, as evidenced by decreased vimentin and collagen I expression levels along with increased α-smooth muscle actin and smooth muscle protein 22-α expression levels. Furthermore, activation of ERK was inhibited in SPINT2-overexpressing SMCs. A specific ERK agonist, 12-O-tetradecanoylphorbol-13-acetate, reversed the SPINT2-mediated inhibition of SMC migration and the phenotypic switching. Collectively, the data indicated that SPINT2 was implicated in the proliferation, migration and phenotypic switching of aortic SMCs, suggesting that it may be involved in TAD progression. [ABSTRACT FROM AUTHOR]

The combination of the time-scaling transformation and control parameterization has proven to be an effective approach in addressing optimal control problems involving switching systems with predefined subsystem sequences. However, this approach has certain limitations. First, the number of control switchings is required to be no less than the number of subsystem switchings. Second, the switching of the subsystem must be accompanied by the switching of the control. Third, this scheme introduces many hyperparameters, leading to combinatorial explosion. To address these drawbacks, we introduce a novel computational approach such that the control switching can be independent of subsystem switching. The superiority of this novel approach can be clearly observed from the solutions obtained using the proposed method for solving two illustrative examples. [ABSTRACT FROM AUTHOR]

Ship detection has been an area of focus for high-frequency surface wave radar (HFSWR). The detection and identification of ship formation have proven significant in early warning, while studies on the formation identification are limited due to the complex background and low resolution of HFSWR. In this paper, we first establish a spatial distribution model of ship formation in HFSWR. Then, we propose a cascade identification algorithm of ship formation in the clutter edge. The proposed algorithm includes a preprocessing stage and a two-stage formation identification stage. The Faster R-CNN is introduced in the preprocessing stage to locate the clutter regions. In the first stage, we propose an extremum detector based on connected regions to extract suspicious regions. The suspicious regions contain ship formations, single-ship targets, and false targets. In the second stage, we design a network connected by a convolutional neural network (CNN) and an extreme learning machine (ELM) to identify two densely distributed ship formations from inhomogeneous clutter and single-ship targets. The experimental results based on the factual HFSWR background demonstrate that the proposed cascade identification algorithm is superior to the extremum detector combined with the classical CNN algorithm for ship formation identification. Meanwhile, the proposed algorithm performs well in weak formation and deformed formation identification. [ABSTRACT FROM AUTHOR]

In this paper, we consider an optimal control problem whose dynamic system consists of control-dependent time-delayed arguments in the control and discrete time-delayed arguments in the state. Recently, control parameterization methods using hybrid time-scale transformation techniques have been developed to optimize both the control parameters and their switching times when the dynamic system consists of discrete time-delayed arguments only. This transformation maps the variable switching times in the original time horizon to fixed switching times in the new time horizon. Thus, the purpose of this paper is to extend the above technique to solve problems with both control-dependent time-delayed arguments and discrete time-delayed arguments. Using the above technique, we convert both the delayed state vector and the delayed control vector into non-delayed vectors in the new time horizon; hence both the control parameters and their switching times can be optimized. The gradients of the objective functions and the constraint functions with respect to the switching times and the controls are obtained. Two numerical examples, one of which is a practical problem involving the optimal transmission of messages in an internet, are solved to demonstrate the efficiency of our method. [ABSTRACT FROM AUTHOR]

Investigating the dynamic evolution process of the ocean and ionosphere in sudden sea conditions poses a challenging problem. To address this objective, this study utilizes actual data from high-frequency surface wave radar (HFSWR) to analyze, validate, summarize, and characterize the echo properties of the ocean and ionosphere during the severe Typhoon Muifa. By employing the short-time Fourier transform (STFT) method, the HFSWR ocean and ionosphere echoes stimulated by typhoon-induced gravity waves are observed, and the joint gravity wave features of the ocean and ionosphere echoes at different time scales are extracted. Additionally, the phase-space reconstruction method is employed to characterize the dynamical evolution of the joint gravity wave features in higher-dimensional space. Furthermore, the chaotic dynamics behavior of the joint gravity wave features is analyzed using the largest Lyapunov exponents. By combining the gravity wave features with chaotic dynamics, this study introduces a method to characterize the joint gravity wave features. The extraction of joint gravity wave features in HFSWR echoes stimulated by typhoons, along with the construction of a chaotic characterization scheme for the gravity wave features, provides an innovative approach and a solid technical foundation for studying the ocean and ionosphere using HFSWR under sudden sea conditions. [ABSTRACT FROM AUTHOR]

The control parameterization method used together with time-scaling transformation is an effective approach to transform optimal control problems into optimal parameter selection problems. The approximate problems can then be solved by gradient-based optimization methods. However, the conventional time-scaling transformation requires that all the control component functions switch simultaneously, which can be undesirable in practice. In this paper, we introduce a novel technique where the switching times for each of the control component functions can be adaptively selected. To demonstrate the effectiveness and flexibility of the proposed approach, two example problems with control input and terminal state constraints are solved using the method proposed. Numerical results show that the new method achieves much better objective values with some increase in computation time compared to the conventional time-scaling transformation technique. [ABSTRACT FROM AUTHOR]

• A human-jigger parasite system with control policies is established. • A time-optimal control problem with limited resources is proposed. • A numerical method combining the control parametrization scheme with the interior point algorithm is constructed. • A trade-off between the optimal eradication time and the effective funding is provided. Tungiasis, as an epidermal parasitic skin disease, leads to long-term injury and life threats to humans in resource-limited countries. In this paper, we aim to minimize the epidemic duration of tungiasis disease with limited resources. A human-jigger parasite system with four control policies for humans and jiggers is established. We propose a time-optimal control problem, in which the eradication time and limited resources are involved. By applying the Pontryagin's minimum principle, we prove that, only bang-bang controls are admitted for all the control policies. Furthermore, a numerical scheme combining the control parametrization scheme with the interior point algorithm is constructed. Finally, numerical simulations are carried out using actual data of humans and jiggers in Brazil. From all the results, we conclude that, there is a trade-off between the optimal eradication time and the effective funding; once the effective funding is properly used, the disease can be controlled effectively; strengthening personal protections, improving treatments for humans and making adulticiding efforts contribute to keeping humans away from the disease. [ABSTRACT FROM AUTHOR]

In this paper, a numerical method is developed for solving a class of delay fractional optimal control problems involving nonlinear time-delay systems and subject to state inequality constraints. The fractional derivatives in this class of problems are described in the sense of Caputo, and they can be of different orders. First, we propose a numerical integration scheme for the fractional time-delay system and prove that the convergence rate of the numerical solution to the exact one is of second order based on Taylor expansion and linear interpolation. This gives rise to a discrete-time optimal control problem. Then, we derive the gradient formulas of the cost and constraint functions with respect to the decision variables and present a gradient computation procedure. On this basis, a gradient-based optimization algorithm is developed to solve the resulting discrete-time optimal control problem. Finally, several example problems are solved to demonstrate the effectiveness of the developed solution approach. [ABSTRACT FROM AUTHOR]

This paper proposes a method for the intelligent detection of high-frequency surface wave radar (HFSWR) targets. This method cascades the adaptive constant false alarm (CFAR) detector variability index (VI) with the convolutional neural network (CNN) to form a cascade detector (VI)CFAR-CNN. First, the (VI)CFAR algorithm is used for the first-level detection of the range–Doppler (RD) spectrum; based on this result, the two-dimensional window slice data are extracted using the window with the position of the target on the RD spectrum as the center, and input into the CNN model to carry out further target and clutter identification. When the detection rate of the detector reaches a certain level and cannot be further improved due to the convergence of the CNN model, this paper uses a dual-detection maps fusion method to compensate for the loss of detection performance. First, the optimized parameters are used to perform the weighted fusion of the dual-detection maps, and then, the connected components in the fused detection map are further processed to achieve an independent (VI)CFAR to compensate for the (VI)CFAR-CNN detection results. Due to the difficulty in obtaining HFSWR data that include comprehensive and accurate target truth values, this paper adopts a method of embedding targets into the measured background to construct the RD spectrum dataset for HFSWR. At the same time, the proposed method is compared with various other methods to demonstrate its superiority. Additionally, a small amount of automatic identification system (AIS) and radar correlation data are used to verify the effectiveness and feasibility of this method on completely measured HFSWR data. [ABSTRACT FROM AUTHOR]

Accurate evaluation of the impact range of hydraulic fracturing (HF) in coal seams is the key to optimizing HF design schemes. In this study, multistage HF processes in Well No. 1 of the Xinji No. 2 coal mine were monitored and analyzed using ground microseismic (MS) monitoring technology. An improved particle swarm optimization algorithm and waveform similarity superposition method were used to locate HF-induced MS events with different signal-to-noise ratios. The results showed that the seismic source location points were distributed horizontally within a 120 m range on both sides of the fracturing well, and vertically distributed from − 615 to − 675 m. The MS events envelope method was used to calculate the stimulated reservoir volume (SRV) of nine fracturing sections, totaling approximately 1,977,000 m3, with the largest SRV in Sections Nos. 2 and 6. Through continuous fracture network (CFN) modeling, the overall fracture extension of the HF was revealed to be rectangular and evenly distributed on both sides of the fracturing well. The main direction of the fracture extended outward along the vertical direction, in line with the direction of the injection hole. By calculating the CFN branch index (BI) and CFN length, the results showed that the fracture networks of Sections Nos. 1, 4, and 6 were more complex, and the CFN lengths of Sections Nos. 1, 2, 6, and 9 were longer. Combining the fracture network size, MS event parameters, and SRV, we determined that Sections Nos. 2 and 6 have longer fracture networks, larger HF ranges, and the best HF effect. This study is important for the evaluation of the effective range of HF in coal seams and for the design and parameter optimization of HF schemes. Highlights: Microseismic events with different signal-to-noise ratios were accurately located. The stimulated reservoir volume and the number of microseismic events in the fractured area are positively correlated. The fracture extension pattern of hydraulic fracturing was obtained by continuous fracture network modeling. [ABSTRACT FROM AUTHOR]

The problem of accurate source localization has been an area of focus in high-frequency surface wave radar (HFSWR) applications. However, antenna pattern distortion (APD) decreases the direction-of-arrival (DOA) estimation performance of the multiple signal classification (MUSIC) algorithm. Up to now, limited studies have been conducted on the calibration of antenna pattern distortion for phased arrays in HFSWR. In this paper, we first analyze the effect of APD on the performance of the MUSIC algorithm through estimation of accuracy and angular resolution. We demonstrate that using the actual pattern (or say APD) can improve DOA estimation performance. Based on this proposition, we propose a novel iterative calibration method that employs the first-order sea clutter data and can jointly estimate DOA and APD in an iterative way. To obtain available calibration points, we introduce the extraction methods of the first-order sea clutter spectrum and single-DOA spectrum points. Meanwhile, in each iteration, the Beamspace MUSIC algorithm and artificial hummingbird algorithm (AHA) are utilized to estimate the DOA and APD, respectively. Numerical results reveal a good coincidence between the actual pattern and the estimated APD. We also apply this method to process the experimental data of HFSWR. We obtain the APD vector of the real phased array and improve the direction-finding performance of several real ship targets using this vector. Both numerical and experimental results prove the correctness of our proposed calibration method. [ABSTRACT FROM AUTHOR]

The gravity wave produced by typhoons has been an essential subject of study that concerns numerous researchers. The damage to human beings and infrastructure in coastal regions caused by typhoon disasters annually is very severe, and analyzing gravity wave variation is a reliable approach to research typhoons. High-frequency surface wave radar (HFSWR) as an over-the-horizon radar can achieve real-time monitoring of an extensive sea area and space. This paper derived the gravity wave perturbation spectrum by handling high-frequency surface wave radar data during typhoons. The gravity wave spectrum data were examined by applying the chaos examination approaches of the Lyapunov exponent and phase-space reconstruction to the gravity wave spectrum data after processing and extraction. The reconstructed phase space had a specific shape in a certain direction, with the maximum Lyapunov exponent greater than zero. The gravity wave spectrum data are suggested to have chaotic properties through two chaos examination approaches. This paper demonstrated that the gravity waves observed by a radar have chaotic properties through the measurement data of HFSWR. While the chaotic properties suggest that observed gravity wave data are predictable in the short term, they are unpredictable in the long term. Predicting gravity wave data is important for understanding the chaotic properties of the atmosphere and for future gravity wave prediction. [ABSTRACT FROM AUTHOR]

Inactivation of the p53 pathway is linked to a variety of human cancers. As a critical component of the p53 pathway, ubiquitin‐specific protease 7 (USP7) acts as a deubiquitinase for both p53 and its ubiquitin E3 ligase mouse double minute 2 homolog. Here, myeloid leukemia factor 2 (MLF2) is reported as a new negative regulator of p53. MLF2 interacts with both p53 and USP7. Via these interactions, MLF2 inhibits the binding of USP7 to p53 and antagonizes USP7‐mediated deubiquitination of p53, thereby leading to p53 destabilization. Functionally, MLF2 plays an oncogenic role in colorectal cancer, at least partially, via the negative regulation of p53. Clinically, MLF2 is elevated in colorectal cancer and its high expression is associated with poor prognosis in patients with colorectal cancer. In wild‐type‐p53‐containing colorectal cancer, MLF2 and p53 expressions are inversely correlated. These findings establish MLF2 as an important suppressor of p53 function. The study also reveals a critical role for the MLF2–p53 axis in promoting colorectal carcinogenesis. [ABSTRACT FROM AUTHOR]

Background: Macrophage infiltration in the tumor microenvironment participates in the regulation of tumor progression. Previous studies have found that Notch signaling pathway is involved in regulating the progression of colorectal cancer (CRC), however, the specific mechanism is still unclear. Methods: The correlation between Notch signaling pathway and macrophage infiltration was investigated in TCGA database and verified in clinical samples of patients with CRC using immunohistochemistry. Gene Set Enrichment Analysis was used to find out genes related to Notch3 expression. Colony formation assay, and flow cytometry were utilized to test tumor growth and immune cell infiltration in vitro and in vivo. Results: Using bioinformatics analysis and clinical sample validation, we found that Notch3 was highly expressed in colon tumor tissues compared to adjacent normal tissues, and it participated in regulating the recruitment of macrophages to the tumor microenvironment. Furthermore, we found that the Notch3 expression was positively correlated with the expression of macrophage recruitment-related cytokines in colon tumor tissues. Finally, we demonstrated that depletion of Notch3 had no significant effect on the growth of colon tumor cells in vitro, while, attenuated the growth of colon cancer tumors in vivo. Simultaneous, immunosuppressive cells, macrophages and myeloid-derived suppressor cell (MDSC) infiltration were dramatically reduced in the tumor microenvironment. Conclusion: Our study illustrated that Notch3 could facilitate the progression of CRC by increasing the infiltration of macrophages and MDSCs to promote the immunosuppressive tumor microenvironment. Targeting Notch3 specifically is a potentially effective treatment for CRC. [ABSTRACT FROM AUTHOR]

Gastric cancer (GC) is a worldwide public health concern. We aimed to investigate the association between preoperative prognostic scoring system based on the combination of age, American Society of Anesthesiologists physical status (ASA-PS), and prognostic nutritional index (PNI) and long-term survival outcomes in patients with (GC). Data from 513 patients were analyzed using Cox proportional hazards regression models to evaluate the association between this prognostic score system and risks of all-cause mortality. This simple prognostic score system (0–3 points) was an independent predictor of long-term survival outcomes in patients with GC after radical gastrectomy based on multivariate analyses. Prognostic 1-point score, 2-point score, and 3-point score significantly increased 50% (95% CI, 14%–98%; P = 0.004), 75% (95% CI, 22%–151%; P = 0.003), and 116% (95% CI, 26%–271%; P = 0.005) hazards of 5-year all-cause mortality, respectively, compared to prognostic 0-point score. Five-year overall survival rates were significantly decreased as prognostic scores increased, (0 point, 57.3%; 1-point, 41.3%; 2-ponint, 36.6%; 3-point, 25.9%; P < 0.01; area under the curve [AUC] = 0.62). A prognostic scoring method based on combination of age, ASA-PS, and PNI may serve as an independent risk stratification metric for long-term survival in patients with GC. [ABSTRACT FROM AUTHOR]

Background. Immunotherapy is an important treatment modality for gastric cancer, therefore, it is crucial to understand the regulators of the tumor microenvironment in gastric cancer. Numerous studies have shown that noncoding RNAs have a critical status in the tumor progression, and the influence of competing endogenous RNA (ceRNA) networks on gastric adenocarcinoma has been widely discussed over the years, but the connection between ceRNA networks and the immune microenvironment of cancer is unclear. This study was aimed at exploring how ceRNA networks influence the prognosis of patients with gastric cancer by modulating the tumor microenvironment. Methods. The Gene Expression Omnibus was analyzed to obtain differential expression matrixes of the noncoding RNAs (circular RNAs (circRNAs), microRNAs (miRNAs)), and mRNAs. The Circular RNA Interactome web tool and TargetScan were applied to determine the miRNA binding sites of the circRNAs and miRNA target genes. The Cancer Genome Atlas provided prognostic genes for gastric cancer, and Cytoscape created the ceRNA networks. Real-time quantitative reverse transcription polymerase chain reaction and western blot assay were adopted to find out how the ceRNA network regulates the expression of the hub gene. Additionally, the TISIDB and TIMER databases were used to assess the link between the hub gene and immunotherapy, with TISIDB providing the immune genes that are coexpressed with the hub gene. Furthermore, the immune-gene signature was constructed by using Cox regression analysis. Moreover, the nomogram, which could predict the prognostic role of gastric cancer patients was created on the basis of the immune-gene signature. Results. In gastric cancer, the circ-0007707/miR-429/PDGFD pathway had a differential expression. The results demonstrated that the pathway could regulate the progression and immune microenvironment of gastric cancer by modulating the immune-gene signature, which included two immune genes (TAB1 and CXCR4). Moreover, the low-risk group patients had better survival. Conclusion. The circ-0007707/miR-429/PDGFD pathway may play a regulatory role in the progression and prognosis of gastric cancer by interfering with the tumor microenvironment, and the PDGFD-related immune-gene signature could be considered a moderator of prognostic factor for gastric cancer and to guide immunotherapy programs. [ABSTRACT FROM AUTHOR]

For some γ > 0, we show that the distribution class (ℒ(γ) ∩풪S)\S(γ) is not closed under infinitely divisible distribution roots, that is, we provide examples showing that some infinitely divisible distributions belong to this class but their corresponding Lévy distributions do not. To this end, we explore the structural properties of some distribution classes, give a positive conclusion to the Embrechts–Goldie conjecture, and study some properties of a transformation from a heavy-tailed distribution to a light-tailed one. [ABSTRACT FROM AUTHOR]

To elucidate whether cranial electrotherapy stimulation (CES) improves depression-like behavior of post-stroke depression (PSD) via regulation of glutathione peroxidase 4 (GPX4)-mediated brain-derived neurotrophic factor (BDNF) expression. Middle cerebral artery occlusion (MCAO) and chronic unpredictable mild stress (CUMS) were used to develop a rat PSD model. CES was applied, and RAS-selective lethal 3 (RSL3) was injected into the hippocampus to inhibit GPX4 in PSD rats. The depression behavior was detected by sucrose preference and forced swimming tests. The structure and morphology of the hippocampus were observed and analyzed by histopathological hematoxylin-eosin (HE) staining. The mRNA and protein expressions of GPX4 and BDNF in the hippocampus were detected by qRT-PCR, western blot and immunohistochemical analysis.The degeneration and necrosis of hippocampal neurons, the depression-like behavior were severer and the expression of BDNF in the hippocampus were decreased in PSD rats than those in MCAO and control groups. CES promoted the hippocampal neuron repair, alleviated the depression-like behavior and increased the expression of BDNF in PSD rats. The inhibition of GPX4 by RSL3 exacerbated the depression-like behavior and decreased the expression of BDNF in PSD rats. In addition, we found that RSL3 disrupted the positive effects of CES on the PSD rats. Conclusion: CES improves depression-like behavior of PSD rats through upregulation of GPX4-mediated BDNF expression in the hippocampus. [ABSTRACT FROM AUTHOR]

• GCM and G-GCM are proposed for solving group square-root Lasso (GSRL) efficiently. Both of them scale well with large problem scale. • The strict descend property and global convergence are proved. • The proposed algorithms can also be used for fast implementation of statistically sound group-sparse regression methods including SPICE/GSPICE and LIKES/BLIKES. A variant for solving Lasso and group Lasso is also provided. Group square-root Lasso (GSRL) is a promising tool for group-sparse regression since the hyperparameter is independent of noise level. Recent works also reveal its connections to some statistically sound and hyperparameter-free methods, e.g., group-sparse iterative covariance-based estimation (GSPICE). However, the non-smoothness of the data-fitting term leads to the difficulty in solving the optimization problem of GSRL, and available solvers usually suffer either slow convergence or restrictions on the dictionary. In this paper, we propose a class of efficient solvers for GSRL in a block coordinate descent manner, including group-wise cyclic minimization (GCM) for group-wise orthonormal dictionary and generalized GCM (G-GCM) for general dictionary. Both strict descent property and global convergence are proved. To cope with signal processing applications, the complex-valued multiple measurement vectors (MMV) case is considered. The proposed algorithm can also be used for the fast implementation of methods with theoretical equivalence to GSRL, e.g., GSPICE. Significant superiority in computational efficiency is verified by simulation results. [ABSTRACT FROM AUTHOR]