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Garsorasib (D-1553; InventisBio, Shangai, China), a potent KRASG12Cinhibitor, has shown promising antitumour activity in patients with KRASG12C-mutated (ie, Gly12Cys) non-small-cell lung cancer (NSCLC) in a phase 1 study. We report results from a phase 2 study conducted to evaluate the efficacy and safety of garsorasib in patients with locally advanced or metastatic KRASG12C-mutated NSCLC.

Directed Energy Deposition (DED) is crucial in the ongoing industrial revolution, providing a unique ability to fabricate high-quality components with complex shapes. However, the determination of key process parameters, such as scan sequence, laser power, and scanning speed, often relies on offline trial-and-error or heuristic methods. These methods are not only suboptimal but also lack generalizability. A major challenge is the non-uniform temperature distribution during manufacturing, which affects the uniformity of the mechanical properties. To overcome these challenges, we have developed a framework based on Deep Reinforcement Learning (DRL). This framework dynamically adjusts process parameters to achieve an optimal control policy. Additionally, we introduce a cost-effective temperature simulation model of the deposition process. This model is particularly useful for researchers testing the proximal policy optimization algorithm. The experimental results demonstrate that DRL policies substantially improve temperature uniformity in Inconel 718, enhancing hardness variability with improvements of 31.8 % and 27.1 % in horizontal and vertical building directions, respectively. This research marks an important step toward achieving a highly intelligent and automated optimization of process parameters. It also proves to be robust and computationally efficient for future online implementation.

Antenna tuning plays an essential role in ensuring high quality wireless communications. Targeting for higher Quality of Service (QoS), many existing network antenna tuning schemes are based on expert knowledge, rule-based policies or conventional optimization theory. However, maximizing the traffic-related QoS does not guarantee that all customers experience good services. In addition, existing schemes are often limited to some handcrafted rules or heuristics and lack of adaptability especially in a time-varying environment. Quality of Experience (QoE), a user-centric metric, can better measure users’ satisfaction for services in wireless networks. This article proposes the cooperative tuning of antennas based on QoE, a paradigm shift from network-centric QoS to user-centric QoE domain. In a normal cellular network, besides the need of improving the overall QoE, it requires handling faults from different cells. As Multi-agent Reinforcement Learning (MARL) has the capability of self-learning the dynamics of environment, we propose an antenna configuration algorithm based on multi-goal MARL. In our framework, agents from different cells not only need to cooperate with each other to achieve the global goal of increasing the overall QoE of the wireless network but also complete some personal goals by combating the faults encountered in their own cells. To accelerate the training efficiency, we introduce a novel two-stage curriculum learning. To reduce the collection time of each QoE sample, we develop an accurate and timely QoE/QoS mapping model with the cascading of a Random Forest Classifier (RFC) and a Deep Neural Network (DNN) (abbreviated as RFC-DNN), which can help us obtain QoE by collecting QoS measurements and perform QoE-based antenna configurations with smaller time granularity. Our proposed RFC-DNN model can reduce the time by 70% when predicting the QoE of a single sample. A huge amount of time will be saved in MARL when tens of thousands of transitions/samples need to be collected. The performance results show that our proposed antenna tuning schemes can not only address specific faults in each cell, but also significantly improve the global average QoE with a faster and more stable convergence speed.

Graphical Abstract:

There is increasing interest in replacing alteplase with tenecteplase as the preferred thrombolytic treatment for patients with acute ischaemic stroke. We aimed to establish the non-inferiority of tenecteplase to alteplase for these patients.

Quality of experience (QoE) is a vital metric that indicates how well the wireless network provides transmission services to users, while quality of service (QoS) help better configure the network parameters for higher performance. The evaluation time of QoE is usually several orders of magnitude larger than that of QoS, because QoE is the perception of users over a period of time, but QoS can be collected every millisecond. Therefore, the implementation of QoE/QoS mapping model can help us obtain QoE by collecting the QoS measurements, and perform QoE-based network configurations with smaller time granularity. Many studies are made to obtain the QoS to QoE mapping, including the use of machine learning (ML) methods. However, traditional ML-based regression methods for QoE/QoS mapping face the challenge of high regression error and catastrophic forgetting in dealing with continuously arriving data. In this paper, we propose a novel QoE model based on continual deep learning in wireless network. This model is formed with two deep neural networks (DNNs) concatenated. The first DNN classifies data into different subsets, which are then fed into the second DNN for regression. The second DNN dynamically form the corresponding subnets, each with nodes and connections adaptively selected in each new time period with new arriving data. We solve the catastrophic forgetting problem with the use of node splitting and hidden state augmentation. Our proposed learning framework greatly reduces the regression error to as low as 0.9314%. The experimental results demonstrate that our proposed model reduces the root mean square error (RMSE) by $21 \sim 86$21∼86 times compared with several existing approaches, specially, the testing error of our proposed model is more than 80 times lower than that of traditional DNN. Compared with other DNN-based cascade models, our proposed method provides good performance in both training time and RMSE.

Several pulsar timing array (PTA) collaborations have recently reported the evidence for a stochastic gravitational-wave background (SGWB), which can unveil the formation of primordial seeds of inhomogeneities in the early universe. With the SGWB parameters inferred from PTAs data, we can make a prediction of the seeds for early galaxy formation from the domain walls in the axion-like particles (ALPs) field distribution. This also naturally provides a solution to the observation of high redshifts by the James Webb Space Telescope. The predicted photon coupling of the ALP is within the reach of future experimental searches.

Pulmonary sarcomatoid carcinoma (PSC) contains carcinomatous component (CaC) and sarcomatous component (SaC). Herein, we explored the genomic origin and intratumor heterogeneity (ITH) of PSC. We collected 31 resected PSC tumors and obtained CaC and SaC by laser capture microdissection for next-generation sequencing. The majority of PSCs (97%) had component-shared alterations. Driver mutations in EGFR, KRAS, MET, PIK3CA, and EML4-ALKfusion were mostly component-shared. Twenty-seven (87%) PSCs had component-private alterations. Compared with pure lung adenocarcinoma (LUAD), adenocarcinoma component of PSC showed lower EGFRincidence. Compared with other typical sarcomas, numerous genes of SaC exhibited significant differences. CaC and SaC had equivalent and proportional tumor mutation burden (TMB), as well as PD-L1 level. Compared with LUAD, SaC had significant higher TMB and more patients with high PD-L1 expression (tumor proportion score =50%). PSC with lower proportion of component-shared alterations (trunk-ratio) had a prolonged disease-free survival (DFS), regardless of the influence of clinical factors. We conclude that most PSCs originate from a monoclone accompanied by genomic ITH which is a potential independent prognostic factor, and more proportion of PSCs may be beneficial from immune checkpoint inhibitors.

Acute myeloid leukemia (AML) is the most common subtype of hematological malignancy in humans, and its incidence increases with age. The treatment of AML still faces challenges. Therefore, there is an urgent need to develop more effective targeted therapies. The receptor tyrosine kinase C-KIT confers critical proliferative signals to AML. Cancerous inhibitor of protein phosphatase 2A (CIP2A) is an endogenous inhibitor of protein phosphatase 2A (PP2A), which promotes the growth and transformation of various solid tumors. These actions make CIP2A a promising target for tumor treatment. Here, we reported the effects and underlying mechanisms of a natural compound, cucurbitacin B (CuB), on AML. We reported that CuB suppressed growth and induced apoptosis in AML cells. The inhibition of growth and activation of apoptosis were mediated through CuB-induced downregulation of the CIP2A/PP2A/C-KIT signal pathway. Furthermore, CuB inactivated the JAK2 and STAT3 molecules downstream of C-KIT via the downregulation of CIP2A. These results advance our understanding of CuB-induced growth inhibition and apoptosis and support further investigation of CuB as a CIP2A inhibitor for AML therapies.

Variants with known or possible pathogenicity located in genes that are unrelated to primary disease conditions are defined as secondary findings. Secondary findings are not the primary targets of whole exome and genome sequencing (WES/WGS) assay but can be of great practical value in early disease prevention and intervention. The driving force for this study was to investigate the impact of racial difference and disease background on secondary findings. Here, we analyzed secondary findings frequencies in 421 whole exome-sequenced Chinese children who are phenotypically normal or bear congenital heart diseases/juvenile obesity. In total, 421 WES datasets were processed for potential deleterious variant screening. A reference gene list was defined according to the American College of Medical Genetics and Genomics (ACMG) recommendations for reporting secondary findings v2.0 (ACMG SF v2.0). The variant classification was performed according to the evidence-based guidelines recommended by the joint consensus of the ACMG and the Association for Molecular Pathology (AMP). Among the 421 WES datasets, we identified 11 known/expected pathogenic variants in 12 individuals, accounting for 2.85% of our samples, which is much higher than the reported frequency in a Caucasian population. In conclusion, secondary findings are not so rare in Chinese children, which means that we should pay more attention to the clinical interpretation of sequencing results.

The aberrant expression of cancerous inhibitor of protein phosphatase 2A (CIP2A) indicates poor prognosis and promotes EMT and metastasis. EMT, a crucial cellular process that occurs during cancer progression and metastasis, has been reported to promote drug resistance in several previous studies. Consequently, ongoing research has been focused on exploring therapeutic options for preventing EMT to delay or reverse drug resistance. Polyphyllin I (PPI) is a natural component extracted from Paris polyphyllathat displays anti-cancer properties. In the present study, we investigated whether PPI can be used in the cisplatin (DDP)-resistant human gastric cancer cell line SGC7901/DDP. The results demonstrated that PPI treatment significantly inhibited cell proliferation, invasion and EMT. TGF-β1 is known to promote EMT-induced metastasis in numerous tumor types. PPI inhibited the invasion of TGFβ1-induced SGC7901/DDP cells in vitro. PPI also increased the mRNA and protein expression levels of E-cadherin but decreased the expression levels of vimentin. Further examination of the mechanism revealed that the CIP2A/PP2A/Akt pathway is partially involved in this regulation of EMT-related biomarkers and invasion. Furthermore, xenograft tests also confirmed the antitumor effects of PPI in vivo. We propose that PPI could be developed as a candidate drug for treating cancer invasion and migration.

Realization problems, including the minimum realization of Boolean control networks (BCNs), are investigated by the vertex partition method. A general definition of the realization for BCNs that does not involve any subspaces is proposed. For the new and existing realization definitions, by a common concolorous perfect vertex partition (CCP-VP) of vertex-colored state transition graphs, an equivalence relation and a quotient mapping are defined, which induce a quotient system, i.e., the realization of original BCNs. In addition, if the CCP-VP is an equal partition, a realization induced by a γ-friendly controlled invariant regular subspace is constructed. Finally, an algorithm is designed to construct the minimum realization of BCNs for different realization definitions, and three examples are given to illustrate the obtained results.

PURPOSE:The incidence of anaplastic lymphoma kinase (ALK) rearrangement in pulmonary sarcomatoid carcinoma (PSC) is controversial. In this study, we aimed to reveal the reliable frequency and the clinical-pathologic characteristics of pulmonary sarcomatoid carcinoma (PSC) with ALK rearrangement in Chinese population, and to provide insight into the translatability of anti-ALK treatment in this treatment-refractory disease. METHODS:Immunohistochemistry (IHC) using a Ventana anti-ALK (D5F3) rabbit monoclonal antibody was performed in 141 PSC specimens collected from multiple medical centers. IHC-positive cases were then confirmed using ALK fluorescent in situ hybridization (FISH). The incidence rates and clinical-pathologic characteristics of ALK-rearranged PSC were then analyzed. Response to ALK inhibitor crizotinib in a patient with ALK-rearranged PSC was evaluated according to the response evaluation criteria for solid tumors (RECIST) version 1.1. RESULTS:Five of 141 (3.5%) of PSCs showed ALK rearrangement-positive by IHC and then were confirmed by FISH. Two were carcinosarcomas and the other three were pulmonary pleomorphic carcinoma (PPC). Strong positive ALK rearrangement was observed in both the epithelioid and sarcomatoid components. The median age of ALK-positive patients was younger than that of ALK-negative patients. PSCs in never-smokers were more likely to harbor ALK rearrangement than those in former or current smokers (P<.05). A 40-year-old woman diagnosed with ALK-rearranged PPC experienced a partial response (−32%) to the ALK inhibitor crizotinib. CONCLUSIONS:The incidence rates of ALK rearrangement in PSC in the Chinese population are similar to those of other subtypes of NSCLC. PSCs in younger never-smokers are more often to harbor ALK rearrangement. ALK inhibitors may serve as an effective treatment for ALK-rearranged PSC.

Anticipating the lifespan of a lithium-ion battery is a challenging task due to the unstable external working conditions and complex internal response. To enhance the accuracy of the remaining usable life prediction of lithium-ion batteries, this study proposes a feature extraction method that relies on the peak value of the incremental capacity (IC) curve for a data-driven prediction approach. This method can significantly reduce the amount of data required for training the model. Furthermore, the grey correlation method (GCM) is employed to select features that have a high correlation with the target value, thereby further reducing the amount of data required for training the model. It is explored how well characteristics may be extracted from various peak intervals. The time series prediction-capable long short-term memory (LSTM) network is used to create the data-driven model. Finally, the experimental findings demonstrate that the proposed data-driven model's prediction error is smaller than 1.18 %. The proposed data-driven in this work is found to have a superior prediction impact on the same data set in different deep learning methods when compared to other data-driven approaches.

Electrical discharge machining (EDM) is a nontraditional processing technology that can be used to process materials with a high melting point, high strength, high hardness and low brittleness. Kerosene, as a common dielectric, produces aerosol and toxic gas at high temperatures, which seriously affects the health of operators and air quality. In this study, edible vegetable oils such as sunflower oil, rapeseed oil and peanut oil were used as dielectric to improve the sustainability of EDM. The Taguchi method was used to design experiments, and the effects of vegetable oils with different viscosities on machinability during EDM were discussed from the perspective of mechanism. The machinability was evaluated with the material removal rate (MRR), energy efficiency per unit volume (EEV) and surface roughness (Ra). In addition, the debris diameters of different vegetable oils after processing were studied by using a super depth-of-field optical microscope. The results showed that the MRR of rapeseed oil was 28.9% higher than that of sunflower oil and 25% higher than that of peanut oil. In terms of the MRR, Ra and EEV, rapeseed oil also had obvious advantages because of its high viscosity. In addition, because of the high viscosity of rapeseed oil, the distribution proportion of large fragments was obviously larger than that of the other two oils. The proportion of debris larger than 35 μm in rapeseed oil was 8.21% and that of sunflower oil was only 2.79%. Therefore, vegetable oils can be used instead of a kerosene dielectric to improve the sustainability of EDM and to realize green manufacturing.

In this report, a novel, label-free fluorescence aptasensor for cocaine was developed based on a G-quadruplex and ruthenium(ii) complex molecular light switch. A Ru[(bpy)2(bqdppz)]2+ligand with high selectivity towards G-quadruplex was synthesized and introduced to serve as a prominent molecular light switch viaspecifically recognizing a cocaine aptamer G-quadruplex. The one-step detection strategy was simply achieved by target-binding-triggered structural dissociation of G-quadruplex accompanied by the sufficient release of Ru-ligand and significant decrease of fluorescent signal. A linear response was obtained over the range of 12–1300 nM, with a low detection limit of 5 nM. The proposed aptasensing method possesses the advantages of speed, easy preparation, being label-free, high sensitivity and low cost.

A simple and new fluorescent and colorimetric probe bearing 7-nitrobenz-2-oxa-1,3-diazole and 4-maleimidophenol fragments for biothiols was designed and synthesized. The probe itself showed almost no background fluorescence (ΦF< 1 × 10−4) and displayed fluorescence turn-on response with selectivity for thiols over other relevant biological species in aqueous solutions. In addition, the probe exhibited 110 nm red-shifted absorption spectra accompanied by color changes which could be obviously distinguished by the naked eye. Furthermore, the probe showed high sensitivity towards thiols with a detection limit of 1.2 × 10−7M (S/N = 3) and the mechanism regarding the optical responses of the probe to thiols was explained by density function theory (DFT) calculations. Finally, the probe has been successfully used to image thiols in HeLa cells.

Nano LiFePO4/C particles with high capacity and high rate were fabricated by one-step solid-state reaction using nano Fe2O3, LiH2PO4and sucrose as raw materials. The effect of synthesis temperature on the morphology and the electrochemical performance was investigated. LiFePO4/C materials were characterized by differential scanning calorimetry (DSC) and thermogravimetry (TG), X-ray diffraction (XRD), X-ray photoelectron spectrometry (XPS), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and the elemental analyzer. The results show that nano Fe2O3can reduce and make uniform the LiFePO4grain size (<100nm) effectively as well as accelerate the solid-state reaction kinetics which is a convenient way for industrialization. The precursor sintered at 740°C for 5h exhibits the highest electrochemical capacity (166.9mAh/g at 0.1C) and the best rate performance.

Flavor-specific scalar bosons exist in various Standard Model extensions and couple to a single generation of fermions via a global flavor symmetry breaking mechanism. Given this strategy, we propose a MeV flavor-specific scalar model in dimension-5 operator series, which explains the muon g— 2 anomaly and proton radius puzzle by coupling with the muon and down-quark at the same time. The framework is consistent with the null result of high-intensity searches. Specifically, the supernova constraints for muon couplings become weakened by including the contribution of down-quark interaction. The parameter space for explaining muon g— 2 discrepancy is available when 10% energy deposition is required in the energy explosion process in the supernova, but this is ruled out by the 1% energy deposition requirement. We also investigate the searches for mediator and dark matter and the resulting constraints on viable parameter space such as nuclear physics constraints, direct detection for light boosted dark matter, and possible CMB constraints. When compared with conventional dark matter production, light dark matter production has two additional modifications: bound state formation and early kinetic equilibrium decoupling. We are now looking into the implications of these effects on the relic density of light dark matter.

AbstractIn this paper, it is proved that all irreducible Harish-Chandra modules over the ? Heisenberg?Virasoro algebra are of the intermediate series (all weight spaces are at most one-dimensional).

Abstract: GRB 080913, with a spectroscopically determined redshift of z=6.7, was the record holder for being the most remote stellar object before the discovery of the recent gamma-ray burst GRB 090423, whose redshift is about 8.2. The gradually accumulated high redshift GRB sample has shed light on the origin and physical properties of GRBs during the cosmic re-ionization epoch. Here, we present a detailed numerical fit to the multi-wavelength data of the optical afterglow of GRB 080913 and then constrain its circumburst environment and the other model parameters. We conclude that the late optical/X-ray plateau at about one day since the burst is due to the Poynting-flux dominated injection from the central engine which is very likely a massive spinning black hole with super strong magnetic fields.