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Abstract Background The initial randomized, double‐blinded, actively controlled, phase III ANEAS study (NCT03849768) demonstrated that aumolertinib showed superior efficacy relative to gefitinib as first‐line therapy in epidermal growth factor receptor (EGFR)‐mutated advanced non‐small cell lung cancer (NSCLC). Metastatic disease in the central nervous system (CNS) remains a challenge in the management of NSCLC. This study aimed to compare the efficacy of aumolertinib versus gefitinib among patients with baseline CNS metastases in the ANEAS study. Methods Eligible patients were enrolled and randomly assigned in a 1:1 ratio to orally receive either aumolertinib or gefitinib in a double‐blinded fashion. Patients with asymptomatic, stable CNS metastases were included. Follow‐up imaging of the same modality as the initial CNS imaging was performed every 6 weeks for 15 months, then every 12 weeks. CNS response was assessed by a neuroradiological blinded, independent central review (neuroradiological‐BICR). The primary endpoint for this subgroup analysis was CNS progression‐free survival (PFS). Results Of the 429 patients enrolled and randomized in the ANEAS study, 106 patients were found to have CNS metastases (CNS Full Analysis Set, cFAS) at baseline by neuroradiological‐BICR, and 60 of them had CNS target lesions (CNS Evaluable for Response, cEFR). Treatment with aumolertinib significantly prolonged median CNS PFS compared with gefitinib in both cFAS (29.0 vs. 8.3 months; hazard ratio [HR] = 0.31; 95% confidence interval [CI], 0.17‐0.56; P < 0.001) and cEFR (29.0 vs. 8.3 months; HR = 0.26; 95% CI, 0.11‐0.57; P < 0.001). The confirmed CNS overall response rate in cEFR was 85.7% and 75.0% in patients treated with aumolertinib and gefitinib, respectively. Competing risk analysis showed that the estimated probability of CNS progression without prior non‐CNS progression or death was consistently lower with aumolertinib than with gefitinib in patients with and without CNS metastases at baseline. No new safety findings were observed. Conclusions These results indicate a potential advantage of aumolertinib over gefitinib in terms of CNS PFS and the risk of CNS progression in patients with EGFR‐mutated advanced NSCLC with baseline CNS metastases. Trial registration ClinicalTrials.gov number, NCT03849768

Abstract Background Iron deficiency (ID) is the most prevalent nutritional deficiency disease in preterm infants, significantly affecting their growth and development. For preterm infants to flourish physically and neurologically, timely iron supplementation is essential. The main goals of this study were to determine whether the present iron supplementation regimen results in iron overload in late preterm infants and whether it can meet the growth requirements of early preterm infants for catch-up. Methods We conducted a prospective follow-up study on preterm infants at the Department of Child Health, West China Second University Hospital, Sichuan University, from January 1, 2020, to August 31, 2020. In this study, 177 preterm infants were divided into two groups based on gestational age—early preterm infants (gestational age

Abstract Background There is inconclusive evidence to suggest that the expression of programmed cell death ligand 1 (PD-L1) is a putative predictor of response to EGFR-TKI therapy in advanced EGFR-mutant non-small cell lung cancer (NSCLC). We evaluated the heterogeneity in PD-L1 expression in the primary lung site and metastatic lymph nodes to analyze the association between PD-L1 expression and response for patients treated with EGFR-TKI. Methods This study reviewed 184 advanced NSCLC patients with EGFR mutations who received first-generation EGFR-TKI as first-line treatment from 2020 to 2021 at Shanghai Chest Hospital. The patients were divided into the primary lung site group (n = 100) and the metastatic lymph nodes group (n = 84) according to the biopsy site. The patients in each group were divided into TPS

The increasing demand for indoor positioning information has led to a growing emphasis on indoor localization. Non-Line-of-Sight (NLOS) conditions diminish the accuracy of Ultra-Wide Band (UWB) system positioning, while over time, Inertial Navigation Systems (INS) suffer from accumulating positioning errors. To address these issues, this paper proposes a method that combines UWB and INS sensors. Compared to individual system positioning methods, this approach effectively enhances localization precision, leveraging the complementary strengths of both systems. The paper utilizes Extended Kalman Filtering (EKF) to fuse residual positioning information, and the obtained residual position results are processed using the Multiple Fading Factor Square Root Kalman Filter technique (MSTSCKF). Moreover, during temporal asynchrony, it updates INS positioning and yaw angle information using EKF output for subsequent INS positioning until the next data correction. To further mitigate NLOS effects, a k-means preprocessing method is applied to UWB data. Root Mean Square Error (RMSE) is used as an evaluation metric. Simulation and experimental results demonstrate that the proposed method effectively accounts for NLOS error influences, thereby enhancing navigation and positioning accuracy.

Introduction: Previous results from the phase 3 ALESIA study (NCT02838420) revealed that alectinib (a central nervous system [CNS]-active, ALK inhibitor) had clinical benefits in treatment-naïve Asian patients with advanced ALK-positive NSCLC, consistent with the global ALEX study. We present updated data after more than or equal to 5 years of follow-up from the “last patient in” date. Methods: Adult patients with treatment-naïve, advanced ALK-positive NSCLC from mainland China, South Korea, and Thailand were randomized 2:1 to receive twice-daily 600 mg alectinib (n = 125) or 250 mg crizotinib (n = 62). The primary endpoint was investigator-assessed progression-free survival. Secondary or exploratory endpoints included overall survival, objective response rate, time to CNS progression, and safety. Results: At the data cutoff (May 16, 2022), the median survival follow-up was 61 and 51 months in the alectinib and crizotinib arms, respectively. Median progression-free survival was 41.6 months with alectinib versus 11.1 months with crizotinib (stratified hazard ratio = 0.33, 95% confidence interval: 0.23–0.49). Overall survival data remain immature; 5-year overall survival rates were 66.4% (alectinib arm) versus 56.1% (crizotinib arm). Objective response rate was 91.2% versus 77.4% with alectinib and crizotinib, respectively. CNS progression was delayed with alectinib versus crizotinib (cause-specific hazard ratio = 0.16, 95% confidence interval: 0.08–0.32). Median treatment duration was longer with alectinib versus crizotinib (42.3 versus 12.6 mo). No new safety signals were observed. Conclusions: With four additional years of follow-up, these updated results confirm the clinical benefit and manageable safety of alectinib in Asian patients with advanced ALK-positive NSCLC, and confirm alectinib as a standard-of-care treatment for patients with advanced ALK-positive NSCLC.

Abstract Immunotherapy represented by anti-PD-(L)1 and anti-CTLA-4 inhibitors has revolutionized cancer treatment, but challenges related to resistance and toxicity still remain. Due to the advancement of immuno-oncology, an increasing number of novel immunoregulatory targets and mechanisms are being revealed, with relevant therapies promising to improve clinical immunotherapy in the foreseeable future. Therefore, comprehending the larger picture is important. In this review, we analyze and summarize the current landscape of preclinical and translational mechanistic research, drug development, and clinical trials that brought about next-generation pharmacological immunoregulatory anti-cancer agents and drug candidates beyond classical immune checkpoint inhibitors. Along with further clarification of cancer immunobiology and advances in antibody engineering, agents targeting additional inhibitory immune checkpoints, including LAG-3, TIM-3, TIGIT, CD47, and B7 family members are becoming an important part of cancer immunotherapy research and discovery, as are structurally and functionally optimized novel anti-PD-(L)1 and anti-CTLA-4 agents and agonists of co-stimulatory molecules of T cells. Exemplified by bispecific T cell engagers, newly emerging bi-specific and multi-specific antibodies targeting immunoregulatory molecules can provide considerable clinical benefits. Next-generation agents also include immune epigenetic drugs and cytokine-based therapeutics. Cell therapies, cancer vaccines, and oncolytic viruses are not covered in this review. This comprehensive review might aid in further development and the fastest possible clinical adoption of effective immuno-oncology modalities for the benefit of patients.

Combining inertial navigation system (INS) and ultra-wideband (UWB) technologies can effectively compensate for their respective shortcomings, thus significantly enhancing the accuracy of indoor positioning systems. However, in the process of fusing these two technologies, signal fading under non-line-of-sight (NLOS) conditions, multipath effects, and errors accumulated by the INS over a long period of time are still key issues that need to be addressed. To cope with these challenges, a new fusion localization algorithm is proposed in this study. The algorithm employs a combination of fuzzy C-mean (FCM) and K-Medoids algorithms for UWB for position computation on the one hand, and an Implicit Unscented Particle Filter (IUPF)-enhanced INS for navigation information processing on the other. In addition, based on the INS error equation, this algorithm realizes the effective fusion of UWB and INS positioning information through the Minimum Error Entropy Extended Kalman Filter (MEE-EKF) technique. This integrated approach significantly improves the accuracy and stability when dealing with the localization problem in complex indoor environments. After simulation experiments under different noise conditions and real environment experiments, the algorithm proposed in this study shows significant advantages in terms of localization performance over the traditional UWB/INS localization methods in recent years. In real experiments, the algorithm achieves an average of 36.15% improvement in positioning accuracy.

Abstract The SEL1L-HRD1 protein complex represents the most conserved branch of endoplasmic reticulum (ER)-associated degradation (ERAD). Despite recent advances in both mouse models and humans, in vivo evidence for the importance of SEL1L in the ERAD complex formation and its (patho-)physiological relevance in mammals remains limited. Here we report that SEL1L variant p.Ser658Pro (SEL1L S658P ) is a pathogenic hypomorphic mutation, causing partial embryonic lethality, developmental delay, and early-onset cerebellar ataxia in homozygous mice carrying the bi-allelic variant. Biochemical analyses reveal that SEL1L S658P variant not only reduces the protein stability of SEL1L, but attenuates the SEL1L-HRD1 interaction, likely via electrostatic repulsion between SEL1L F668 and HRD1 Y30 residues. Proteomic screens of SEL1L and HRD1 interactomes reveal that SEL1L-HRD1 interaction is a prerequisite for the formation of a functional HRD1 ERAD complex, as SEL1L is required for the recruitment of E2 enzyme UBE2J1 as well as DERLIN to HRD1. These data not only establish the disease relevance of SEL1L-HRD1 ERAD, but also provide additional insight into the formation of a functional HRD1 ERAD complex.

Abstract Endoplasmic reticulum-associated degradation (ERAD) plays indispensable roles in many physiological processes; however, the nature of endogenous substrates remains largely elusive. Here we report a proteomics strategy based on the intrinsic property of the SEL1L-HRD1 ERAD complex to identify endogenous ERAD substrates both in vitro and in vivo. Following stringent filtering using a machine learning algorithm, over 100 high-confidence potential substrates are identified in human HEK293T and mouse brown adipose tissue, among which ~88% are cell type-specific. One of the top shared hits is the catalytic subunit of the glycosylphosphatidylinositol (GPI)-transamidase complex, PIGK. Indeed, SEL1L-HRD1 ERAD attenuates the biogenesis of GPI-anchored proteins by specifically targeting PIGK for proteasomal degradation. Lastly, several PIGK disease variants in inherited GPI deficiency disorders are also SEL1L-HRD1 ERAD substrates. This study provides a platform and resources for future effort to identify proteome-wide endogenous substrates in vivo, and implicates SEL1L-HRD1 ERAD in many cellular processes including the biogenesis of GPI-anchored proteins.

LiDAR and cameras, often regarded as the “eyes” of intelligent driving vehicles, are vulnerable to adverse weather conditions like haze, rain, and snow, compromising driving safety. In order to solve this problem and enhance the environmental sensing capability under severe weather conditions, this paper proposes a multimodal back-end fusion object detection method, Sec-CLOCs, which is specifically optimized for vehicle detection under heavy snow. This method achieves object detection by integrating an improved YOLOv8s 2D detector with a SECOND 3D detector. First, the quality of image data is enhanced through the Two-stage Knowledge Learning and Multi-contrastive Regularization (TKLMR) image processing algorithm. Additionally, the DyHead detection head and Wise-IOU loss function are introduced to optimize YOLOv8s and improve 2D detection performance.The LIDROR algorithm preprocesses point cloud data for the SECOND detector, yielding 3D object detection results. The CLOCs back-end fusion algorithm is then employed to merge the 2D and 3D detection outcomes, thereby enhancing overall object detection capabilities. The experimental results show that the Sec-CLOCs algorithm achieves a vehicle detection accuracy of 82.34% in moderate mode (30–100 m) and 81.76% in hard mode (more than 100 m) under heavy snowfall, which demonstrates the algorithm’s high detection performance and robustness.

As the most common degenerative joint disease, osteoarthritis (OA) contributes significantly to pain and disability during aging. Several genes of interest involved in articular cartilage damage in OA have been identified. However, the direct causes of OA are poorly understood. Evaluating the public human RNA-seq dataset showed that CBFB (subunit of a heterodimeric Cbfβ/Runx1, Runx2, or Runx3 complex) expression is decreased in the cartilage of patients with OA. Here, we found that the chondrocyte-specific deletion of Cbfb in tamoxifen-induced Cbfbf/f;Col2a1-CreERT mice caused a spontaneous OA phenotype, worn articular cartilage, increased inflammation, and osteophytes. RNA-sequencing analysis showed that Cbfβ deficiency in articular cartilage resulted in reduced cartilage regeneration, increased canonical Wnt signaling and inflammatory response, and decreased Hippo/Yap signaling and Tgfβ signaling. Immunostaining and western blot validated these RNA-seq analysis results. ACLT surgery-induced OA decreased Cbfβ and Yap expression and increased active β-catenin expression in articular cartilage, while local AAV-mediated Cbfb overexpression promoted Yap expression and diminished active β-catenin expression in OA lesions. Remarkably, AAV-mediated Cbfb overexpression in knee joints of mice with OA showed the significant protective effect of Cbfβ on articular cartilage in the ACLT OA mouse model. Overall, this study, using loss-of-function and gain-of-function approaches, uncovered that low expression of Cbfβ may be the cause of OA. Moreover, Local admission of Cbfb may rescue and protect OA through decreasing Wnt/β-catenin signaling, and increasing Hippo/Yap signaling and Tgfβ/Smad2/3 signaling in OA articular cartilage, indicating that local Cbfb overexpression could be an effective strategy for treatment of OA.

Abstract Background The immune system may influence prognosis, and lymphopenia is a frequent side effect of concurrent chemoradiotherapy (CCRT). Radical irradiation for locally advanced esophageal cancer (LA‐EC) exposes significant vascular and heart volumes. In this study, we hypothesized that lymphopenia is linked to cardiac and pericardial doses and affects patient prognosis. Methods and Materials We identified 190 LA‐EC patients who received radical CCRT. Multivariate analysis (MVA) was performed to correlate clinical factors and dosimetric parameters with overall survival (OS). We collected lymphocyte‐related variables and ratios before and during CCRT. MVA was performed to correlate hematologic toxicity with OS. The relationship between dosimetric parameters and G4 lymphopenia was determined using logistic stepwise regression. Finally, a nomogram of G4 lymphopenia was developed and validated externally. Results Median follow‐up time for all patients was 27.5 months. On MVA for OS, higher pericardial V30 (PV30) was linked to worse survival (HR: 1.013, 95% CI: 1.001–1.026, p = 0.039). The median OS stratified by PV30 > 55.3% and PV30 ≤ 55.3% was 24.0 months and 54.0 months, respectively (p = 0.004). G4 lymphopenia was shown to be linked with worse OS in the MVA of hematological toxicity with OS (HR: 2.042, 95% CI: 1.335–3.126, p = 0.001). Thirty of the 100 patients in the training set had G4 lymphopenia. Logistic stepwise regression was used to identify variables associated with G4 lymphopenia, and the final model consisted of stage‐IVA (p = 0.017), platelet‐to‐lymphocyte ratio during CCRT (p = 0.008), Heart V50 (p = 0.046), and PV30 (p = 0.048). Finally, a nomogram predicting G4 lymphocytopenia were constructed and externally validated. The ROC curve showed an AUC for internal validation of 0.775 and external validation of 0.843. Conclusion Higher doses of pericardial radiation might affect LA‐EC patients' prognosis by inducing G4 lymphopenia during CCRT. Further prospective studies are warranted to confirm these findings, especially in the era of immune‐checkpoint inhibitor treatment.

This paper analyzes enterprise investment capability based on quantitative analysis under data mining technology and selects cash flow as the key indicator of enterprise investment to make a predictive analysis of enterprise cash flow. The system of enterprise investment capacity indicators is constructed, and the relationship between cash flow and each quantitative is analyzed by the regression model. The case analysis of the enterprise financing structure and the risk of bank financial indicators were conducted separately, and the results showed that the financing structure of enterprise A was dominated by long-term borrowing, which accounted for more than 60% every year, followed by bonds payable, which accounted for between 10% and 30% every year. The return on assets of Bank A is between 15% and 20%, much higher than the other two banks.

Abstract Endoplasmic reticulum (ER)-associated degradation (ERAD) and ER-phagy are two principal degradative mechanisms for ER proteins and aggregates, respectively; however, the crosstalk between these two pathways under physiological settings remains unexplored. Using adipocytes as a model system, here we report that SEL1L-HRD1 protein complex of ERAD degrades misfolded ER proteins and limits ER-phagy and that, only when SEL1L-HRD1 ERAD is impaired, the ER becomes fragmented and cleared by ER-phagy. When both are compromised, ER fragments containing misfolded proteins spatially coalesce into a distinct architecture termed Coalescence of ER Fragments (CERFs), consisted of lipoprotein lipase (LPL, a key lipolytic enzyme and an endogenous SEL1L-HRD1 substrate) and certain ER chaperones. CERFs enlarge and become increasingly insoluble with age. Finally, we reconstitute the CERFs through LPL and BiP phase separation in vitro, a process influenced by both redox environment and C-terminal tryptophan loop of LPL. Hence, our findings demonstrate a sequence of events centered around SEL1L-HRD1 ERAD to dispose of misfolded proteins in the ER of adipocytes, highlighting the profound cellular adaptability to misfolded proteins in the ER in vivo.

Abstract Background The efficacy and toxicity profiles for extensive‐stage small cell lung cancer (ES‐SCLC) are unclear. We aimed to address this gap through a Bayesian network meta‐analysis. Methods We performed network analysis from randomized controlled trials comparing these treatments: PD‐(L)1 inhibitor, CTLA‐4 inhibitor, CXCR inhibitor, PARP inhibitor, CDK inhibitor, chemotherapy, and their combinations. Pooled estimations of progression‐free survival, overall survival, objective response rate, and toxicity (systematic and specific) were conducted within the Bayesian framework. Results Twenty‐five trials involving 9 strategies were included. In terms of progression‐free survival and overall survival, PD‐(L)1 inhibitor combined with cisplatin/carboplatin (P) and etoposide (E) shown the acknowledged superiority than other treatments. The addition of CTLA‐4 inhibitor (ipilimumab) to EP had the highest response rate among these regimens, and the combination of chemotherapy (irinotecan) and cisplatin/carboplatin had the greatest probability of performing considerable systematic security. The secondary endpoint was specific adverse events, including vomiting, fatigue, thrombocytopenia, constipation, and decreased appetite; hence we depicted the specific toxicity profile of each regimen. In addition, we identified the differences between PD‐1 inhibitors and PD‐L1 inhibitors in prolonging overall survival time for the central nervous system (CNS)/liver metastases patients. Conclusions EP combined with PD‐(L)1 inhibitor followed by CTLA‐4 inhibitors or anti‐angiogenesis was the considerable treatment with considerable efficacy and safety for ES‐SCLC. Each treatment has a unique specific toxicity profile, which needs more attention.

Background: Iron deficiency (ID) and ID anemia are widespread in low-income countries, particularly among preterm infants. Hepcidin is a key regulator of iron metabolism, which offers the possibility of new solutions to diagnose ID in premature infants. Objective: To explore the relationship between iron metabolism and hepcidin in premature infants. Materials and methods: The study involved 81 preterm infants between 28+1 and 36+6 who underwent iron status indicators and hepcidin testing at 6 months of corrected gestational age. The preterm infants were divided into two groups based on iron status indicators: ID and no ID. Results: Serum hepcidin was lower for premature infants with ID compared to those without ID (log10hepcidin, 1.18 ± 0.44 vs 1.49 ± 0.37, p = 0.002). A single-variate linear regression model was used to explore the correlation between hepcidin and other indicators of iron metabolism. A strongly positive relationship was observed between hepcidin levels and ferritin levels (p < 0.001) in the correlation analysis. Conclusions: Hepcidin can be used as an efficient indicator of iron storage and a promising indicator for the early diagnosis of ID in premature infants.

Abstract In response to the fast and intensive traffic changes and the presence of redundant links in the network topology in data centre networks, multipath routing has become the dominant approach. Existing multipath routing algorithms are still inadequate in terms of adapting to dynamic changes in the network state quickly and the cooperation of path selection and sub-flow assignment. Therefore, this paper proposes a sub-flow adaptive multipath routing algorithm for data centre networks (SAMP). The deep deterministic policy gradient (DDPG) algorithm is introduced. DDPG combines deep learning (DL) and reinforcement learning (RL) to implement different network state changes quickly, especially in the process of topology, to achieve dynamic migration of the optimised decisions that have been learned. An adaptive multipath routing model for subflows is established to accomplish collaborative scheduling of path selection and subflow assignment based on the real-time state of the network. The experimental results show that the algorithm can be well adapted to the data centre network, and when compared with several traditional methods, it reduces the latency by an average of 31.3%, improves the task transmission success rate by an average of 14.9%, and increases the throughput by 37.1%.

The growth of skeletal muscle relies on a delicate equilibrium between protein synthesis and degradation; however, how proteostasis is managed in the endoplasmic reticulum (ER) is largely unknown. Here, we report that the SEL1L-HRD1 ER-associated degradation (ERAD) complex, the primary molecular machinery that degrades misfolded proteins in the ER, is vital to maintain postnatal muscle growth and systemic energy balance. Myocyte-specific SEL1L deletion blunts the hypertrophic phase of muscle growth, resulting in a net zero gain of muscle mass during this developmental period and a 30% reduction in overall body growth. In addition, myocyte-specific SEL1L deletion triggered a systemic reprogramming of metabolism characterized by improved glucose sensitivity, enhanced beigeing of adipocytes, and resistance to diet-induced obesity. These effects were partially mediated by the upregulation of the myokine FGF21. These findings highlight the pivotal role of SEL1L-HRD1 ERAD activity in skeletal myocytes for postnatal muscle growth, and its physiological integration in maintaining whole-body energy balance.

Abstract Quitting smoking could potentially minimize the risk of a high neutrophil-to-lymphocyte ratio (NLR) among tobacco use-related (TUR) cancer survivors. A total of 1263 TUR cancer survivors aged 20 to 85 years old were investigated using data from the National Health and Nutritional Examination Survey 1999–2018. The primary outcome was the NLR, which was defined as having two levels: high-risk (≥ 3) and low-risk (

In the field of HVAC (heating, ventilation and air conditioning) control, the model-based optimal control method has been extensively studied and verified by scholars, but this method highly depends on the accuracy of the model, the collection of a large amount of historical data, and the deployment of sensors.In response to the above problems,combined with EnergyPlus, actual system parameters and historical data, the HVAC optimized control model was constructed, and an improved double pools-based DQN (DPs-DQN) algorithm was proposed.Finally, it was applied to the load distribution of different types of chillers, the combined optimal control of cooling tower fan frequency and cooling water pump frequency in HVAC system.Based on the constructed problem model, aiming at the problem of sample imbalance in the decision-making optimization process, the algorithm established two independent experience pools on the basis of DQN to store load distribution and non load distribution samples respectively.During the training process, followed a certain ratio to sample from the experience pool to speed up the algorithm convergence.The proposed method was compared with the model-based control method and the baseline method.The experimental results show that compared with the baseline method, the model-based HVAC controller can save 11.5% (optimal energy-saving efficiency), while the DPs-DQN can save energy by 7.5% in the first year.At the same time, as the system runs, the controller can obtain results close to the optimal energy saving efficiency in the eighth year.In addition, compared with the model-based HVAC controller, the controller does not depend on the system model, and requires less prior knowledge and sensors in the online control process, which is more valuable in actual engineering applications.

In GaN:Mg, the MgGa acceptor is compensated extensively by the formation of nitrogen vacancies (VN) and Mg interstitials (Mgi). However, we show that such compensation can be overcome by forming two kinds of Mg-rich complexes: one that contains VN and the other that contains only MgGa and Mgi. Such complexing not only neutralizes VN and Mgi but also forms better complex acceptors that have lower formation energies and smaller hole localization energies than isolated MgGa. Our results help explain the different doping behaviors in samples grown by different methods.

Abstract Endometrial cancer (EC) is the most common female reproductive tract cancer and its incidence has been continuously increasing in recent years. The underlying mechanisms of EC tumorigenesis remain unclear, and efficient target therapies are lacking, for both of which feasible endometrial cancer animal models are essential but currently limited. Here, an organoid and genome editing‐based strategy to generate primary, orthotopic, and driver‐defined ECs in mice is reported. These models faithfully recapitulate the molecular and pathohistological characteristics of human diseases. The authors names these models and similar models for other cancers as organoid‐initiated precision cancer models (OPCMs). Importantly, this approach can conveniently introduce any driver mutation or a combination of driver mutations. Using these models,it is shown that the mutations in Pik3ca and Pik3r1 cooperate with Pten loss to promote endometrial adenocarcinoma in mice. In contrast, the Kras G12D mutati led to endometrial squamous cell carcinoma. Then, tumor organoids are derived from these mouse EC models and performed high‐throughput drug screening and validation. The results reveal distinct vulnerabilities of ECs with different mutations. Taken together, this study develops a multiplexing approach to model EC in mice and demonstrates its value for understanding the pathology of and exploring the potential treatments for this malignancy.

IntroductionThree members of Capripoxvirus (CaPV) genus, including lumpy skin disease virus (LSDV), goatpox virus (GTPV), and sheeppox virus (SPPV), are mentioned as notifiable forms by World Organization for Animal Health. These viruses have negatively impacted ruminant farming industry worldwide, causing great economic losses. Although SPPV and GTPV cause more severe clinical disease in only one animal species, they can transfer between sheep and goats. Both homologous and heterologous immunization strategies are used to protect animals against CaPVs. However, development of accurate and rapid methods to distinguish these three viruses is helpful for the early detection, disease surveillance, and control of CaPV infection. Therefore, we developed a novel triplex real-time PCR (qPCR) for the differentiation of LSDV, GTPV, and SPPV.MethodsUniversal primers were designed to detect pan-CaPV sequences. Species-specific minor groove binder (MGB)-based probes were designed, which were labeled with FAM for LSDV, HEX for GTPV, and ROX for SPPV. The sensitivity, specificity, reproducibility, and ability of detecting mixed infections were evaluated for the triplex qPCR. Further, 226 clinical samples of the infection and negative controls were subjected to the triplex qPCR, and the results were verified using PCR-restriction fragment length polymorphism (PCR-RFLP) and sequencing methods for PRO30 gene.ResultsThe triplex qPCR could successfully distinguish LSDV, GTPV, and SPPV in one reaction, and the assay sensitivity was 5.41, 27.70, and 17.28 copies/μL, respectively. No cross-reactivity was observed with other viruses causing common ruminant diseases, including des petits ruminants virus, foot-and-mouth disease virus, bluetongue virus, ovine contagious pustular dermatitis virus, infectious bovine rhinotracheitis virus, and bovine viral diarrhea-mucosal disease virus. Inter-and intra-assay variabilities were < 2.5%. The results indicated that the triplex qPCR was highly specific, sensitive, and reproducible. Simulation experiments revealed that this assay could successfully distinguish two or three viruses in case of mixed infections without any cross-reaction. For clinical samples, the results were completely consistent with the results of PCR-RFLP and sequencing. This demonstrated that the assay was reliable for clinical application.DiscussionThe triplex qPCR is a robust, rapid, and simple tool for identifying various types of CaPV as it can successfully distinguish LSDV, GTPV, and SPPV in one reaction. Furthermore, the assay can facilitate more accurate disease diagnosis and surveillance for better control of CaPV infection.

Anaplastic lymphoma kinase (ALK) fusions represent the second most common oncogenic driver mutation in non-small cell lung cancer (NSCLC). As the new class of 3rd generation of ALK tyrosine kinase inhibitor (TKI), lorlatinib has shown robust potency and brain-penetrant clinical activity against a wide spectrum of multiple resistance mutations within the ALK domain detected during crizotinib and 2nd generation ALK TKI treatment. Lorlatinib is generally well-tolerated with unique adverse drug reaction/adverse event, including hyperlipidemia and central nervous system effects, which are mostly mild to moderate severity and manageable through dosage modifications and/or standard medical intervention. For advanced NSCLC with ALK positivity, patients should be evaluated for baseline characteristics and pre-existing medication, informed of the potential toxicities, and periodically monitored to balance benefits and risks. Moreover, a multidisciplinary group of experts is essential to establish a comprehensive diagnostic and therapeutic strategy.

Three principal ER quality-control mechanisms, namely, the unfolded protein response, ER-associated degradation (ERAD), and ER-phagy are each important for the maintenance of ER homeostasis, yet how they are integrated to regulate ER homeostasis and organellar architecture in vivo is largely unclear. Here we report intricate crosstalk among the 3 pathways, centered around the SEL1L-HRD1 protein complex of ERAD, in the regulation of organellar organization in β cells. SEL1L-HRD1 ERAD deficiency in β cells triggers activation of autophagy, at least in part, via IRE1α (an endogenous ERAD substrate). In the absence of functional SEL1L-HRD1 ERAD, proinsulin is retained in the ER as high molecular weight conformers, which are subsequently cleared via ER-phagy. A combined loss of both SEL1L and autophagy in β cells leads to diabetes in mice shortly after weaning, with premature death by approximately 11 weeks of age, associated with marked ER retention of proinsulin and β cell loss. Using focused ion beam scanning electron microscopy powered by deep-learning automated image segmentation and 3D reconstruction, our data demonstrate a profound organellar restructuring with a massive expansion of ER volume and network in β cells lacking both SEL1L and autophagy. These data reveal at an unprecedented detail the intimate crosstalk among the 3 ER quality-control mechanisms in the dynamic regulation of organellar architecture and β cell function.

Immunotherapy plus chemotherapy has been approved for the first-line treatment of extensive-stage small cell lung cancer (ES-SCLC, stage IV). Recently, the 2023 version of the National Comprehensive Cancer Network Guidelines recommended immunotherapy plus chemotherapy as the neoadjuvant regimen in patients with resectable non-small cell lung cancer (NSCLC). However, it is still unclear whether the combination regimen of immunotherapy plus chemotherapy is also beneficial for SCLC in the neoadjuvant context. Here, we report the case of a patient with stage IIIB SCLC who showed long-term survival and good tolerance to the neoadjuvant chemoimmunotherapy consisting of tislelizumab (an anti–PD-1 monoclonal antibody) plus etoposide-carboplatin. The patient achieved pathological complete response after receiving two cycles of neoadjuvant tislelizumab and chemotherapy followed by surgery. Two courses of post-operative tislelizumab and etoposide-carboplatin treatment were performed. The patient has survived for more than 23 months with no recurrence or metastases after neoadjuvant therapy. Multiplexed immunofluorescence and immunohistochemistry staining showed that the post-treatment specimens had remarkable immune cells infiltration, including CD3+ T cells, CD4+ T cells, and CD8+ T cells, which contrasted with very low levels of these cells in the pre-treatment samples. This study is, to the best of our knowledge, the first attempt to present the neoadjuvant chemoimmunotherapy of tislelizumab in combination with etoposide-carboplatin in SCLC. Our study suggested that neoadjuvant tislelizumab plus chemotherapy may facilitate radical resection and benefit patients with locally advanced (stage IIB-IIIC) SCLC.

A critical issue in intelligent building control is detecting energy consumption anomalies based on intelligent device status data. The building field is plagued by energy consumption anomalies caused by a number of factors, many of which are associated with one another in apparent temporal relationships. For the detection of abnormalities, most traditional detection methods rely solely on a single variable of energy consumption data and its time series changes. Therefore, they are unable to examine the correlation between the multiple characteristic factors that affect energy consumption anomalies and their relationship in time. The outcomes of anomaly detection are one-sided. To address the above problems, this paper proposes an anomaly detection method based on multivariate time series. Firstly, in order to extract the correlation between different feature variables affecting energy consumption, this paper introduces a graph convolutional network to build an anomaly detection framework. Secondly, as different feature variables have different influences on each other, the framework is enhanced by a graph attention mechanism so that time series features with higher influence on energy consumption are given more attention weights, resulting in better anomaly detection of building energy consumption. Finally, the effectiveness of this paper's method and existing methods for detecting energy consumption anomalies in smart buildings are compared using standard data sets. The experimental results show that the model has better detection accuracy.

AimTo investigate the predictive value of C-reactive protein (CRP) to serum albumin (ALB) ratio in the severity and prognosis of acute pancreatitis (AP), and compare the predictive value of the CRP/ALB ratio with the Ranson score, modified computed tomography severity index (MCTSI) score, and Bedside Index of Severity in Acute Pancreatitis (BISAP) score.MethodsThis cohort study retrospectively analyzed clinical data of AP patients from August 2018 to August 2020 in our hospital. Logistic regression analysis was utilized to determine the effects of CRP/ALB ratio, Ranson, MCTSI, and BISAP score on severe AP (SAP), pancreatic necrosis, organ failure, and death. The predictive values of CRP/ALB ratio, Ranson, MCTSI, and BISAP score were examined with the area under the curve (AUC) of the receiver operator characteristic (ROC) curve analysis. DeLong test was used to compare the AUCs between CRP/ALB ratio, Ranson, MCTSI, and BISAP score.ResultsTotally, 284 patients were included in this study, of which 35 AP patients (12.32%) developed SAP, 29 (10.21%) organ failure, 30 (10.56%) pancreatic necrosis and 11 (3.87%) died. The result revealed that CRP/ALB ratio on day 2 was associated with SAP [odds ratio (OR): 1.74, 95% confidence interval (CI): 1.32 to 2.29], death (OR: 1.73, 95%CI: 1.24 to 2.41), pancreatic necrosis (OR: 1.28, 95%CI: 1.08 to 1.50), and organ failure (OR: 1.43, 95%CI: 1.18 to 1.73) in AP patients. Similarly, CRP/ALB on day 3 was related to a higher risk of SAP (OR: 1.50, 95%CI: 1.24 to 1.81), death (OR: 1.8, 95%CI: 1.34 to 2.65), pancreatic necrosis (OR: 1.22, 95%CI: 1.04 to 1.42), and organ failure (OR: 1.21, 95%CI: 1.04 to 1.41). The predictive value of CRP/ALB ratio for pancreatic necrosis was lower than that of MCTSI, for organ failure was lower than that of Ranson and BISAP, and for death was higher than that of MCTSI.ConclusionThe CRP/ALB ratio may be a novel but promising, easily measurable, reproducible, non-invasive prognostic score that can be used to predict SAP, death, pancreatic necrosis, and organ failure in AP patients, which can be a supplement of Ranson, MCTSI, and BISAP scores.

ObjectivesWe aimed to identify the weight gain patterns of small-for-gestational age (SGA) infants in early life and to explore the predictive value for later overweight/obesity in childhood.MethodsWe obtained data from a prospective cohort including term SGA infants born between January 2006 and November 2015 who received regular health care from birth to 5 years in West China Second University Hospital, Chengdu, China. A latent class growth analysis (LCGA) was applied to group children with similar growth trajectory patterns. Multiple logistic regression was performed to examine the association between weight gain patterns and later overweight/obesity.ResultsA total of 296 term SGA infants were finally included. Five weight gain trajectories were identified, including excessive rapid catch-up growth (ERCG) (class 1, 10.9%), rapid catch-up growth (RCG) (class 2, 17.9%), appropriate catch-up growth (ACG) (class 3, 53.0%), slow catch-up growth (SCG) (class 4, 13.4%) and almost no catch growth (NCG) (class 5, 4.8%). SGA infants in class 1 and class 2 had a higher BMI according to age- and sex-specific Z scores from 2–5 years of age. In addition, 25% of SGA infants in class 1 and 13.2% of SGA infants in class 2 were found to be overweight/obese at 2-5 years of age. After adjusting for confounders, we found that extremely rapid weight gain (class 1) in the first 2 years of life increased the risk of overweight/obesity by 2.1 times at 2 to 5 years of age (aOR=2.1, 95% CI: 1.3~4.8; P

Dexmedetomidine (Dex) is a highly selective α2 adrenergic agonist used in clinical anesthesia. Studies have shown that Dex can act on the collecting duct and reduce the body’s water reabsorption, thereby increasing water discharge. However, the specific mechanism of Dex on water homeostasis remains unclear. The hypothalamus is the regulatory center of water and salt balance and secretes related neurochemical hormones, such as arginine vasopressin (AVP), to regulate the discharge of water and salt. The paraventricular nucleus (PVN) and supraoptic nucleus (SON) in the hypothalamus are also considered to be the key targets of the thirst loop. They are responsible for the secretion of AVP. The suprachiasmatic nucleus (SCN) is also one of the brain regions where AVP neurons are densely distributed in the hypothalamus. This study used C57BL/6J mice for behavior, immunofluorescence, and blood analysis experiments. Our results showed that Dex could not only depress the expression of AVP in the PVN but also reduce serum AVP concentration. The animal water intake was decreased without impairing the difference in food consumption and the urine excretion was enhanced after the intraperitoneal injection of Dex, while AVP supplementation restored the water intake and inhibited the urine excretion of mice in the Dex group. In addition, the renin-angiotensin-aldosterone system is vital to maintaining serum sodium concentration and extracellular volume. We found that serum sodium, serum chloride, serum aldosterone (ALD) concentration, and plasma osmolality were decreased in the Dex group, which inhibited water reabsorption, and the plasma osmolarity of mice in the Dex group supplemented with AVP was significantly higher than that in Dex group. We also found that Dex significantly increased the concentration of blood urea nitrogen and decreased the concentration of creatinine within the normal range of clinical indicators, indicating that there was no substantive lesion in the renal parenchyma. These results showed that Dex could modulate the balance of water-electrolyte metabolism by depressing the expression of AVP in PVN without impairing renal function.

ObjectiveCamrelizumab is a newly developed program-death receptor one inhibitor; the real-world evidence about its application in hepatocellular carcinoma (HCC) treatment is lacking. Therefore, this prospective, multi-center, real-world study evaluated the efficacy and safety of camrelizumab plus transarterial chemoembolization (TACE) in treating intermediate-to-advanced HCC patients.MethodsThis study consecutively enrolled 101 intermediate to advanced HCC patients. All patients received camrelizumab-based treatment within 30 days of the perioperative period of the TACE operation. The primary outcome was progression-free survival (PFS), and the secondary effects were overall survival (OS), objective response rate (ORR), disease control rate (DCR), and AEs.ResultsSpecifically, the median PFS was 9.7 (95% confidence interval: 7.4–12.0) months, with a 1-year PFS rate of 30.6%. Meanwhile, the median OS was not reached (NR) yet, with a 1-year OS rate of 61.9%. Besides, the CR, PR, SD, and PD rates were 12.8%, 44.9%, 29.5%, and 12.8%, respectively. The ORR and DCR were 57.7% and 87.2%, respectively. More cycles of camrelizumab were independently correlated with prolonged PFS (hazard ratio (HR): 0.415, P = 0.002), whereas longer intervals between camrelizumab administration and TACE were independently associated with unfavorable PFS (HR: 1.873, P = 0.032). The incidence of total AEs was 90.1%; most AEs were grade 1 (20.8%), grade 2 (28.7%) and grade 3 (37.6%), while only 3 (3.0%) patients had grade 4 AEs.ConclusionThe camrelizumab plus TACE regimen is effective and safe, indicating its potential to serve as a promising treatment choice for intermediate to advanced HCC patients.

ObjectiveNearly half of patients who undergo mechanical thrombectomy (MT) do not experience a favorable outcome. The association between blood pressure fluctuation and clinical outcomes after successful MT is controversial. We evaluated the influence of blood pressure variability (BPV) on the clinical outcomes of stroke patients with large vessel occlusion (LVO) who underwent successful recanalization after MT.MethodsPatients with anterior circulation LVO stroke who underwent successful emergency MT (modified Thrombolysis in Cerebral Infarction, mTICI ≥ 2b) at the Shanghai Tenth People's Hospital of Tongji University from 2017 to 2021 were enrolled. Multivariate logistic models were used to investigate the association between BPV (mean arterial pressure [MAP] assessed using the standard deviation [SD]) and clinical outcomes. The primary outcome was 90-day modified Rankin Scale scores (mRS), and the secondary outcomes were 30-day mortality and symptomatic intracranial hemorrhage (sICH).ResultsA total of 458 patients (56.8% men), with a mean age of 72 ± 1 years, were enrolled. Among them, 207 (45.2%) patients had unfavorable functional outcomes (mRS score 3–6) at 90 days, 61 (13.3%) patients died within 30 days, and 20 (4.4%) patients had sICH. In a fully adjusted model, BPV was associated with a higher risk of a 90-day mRS score of 3–6 (P = 0.04), 30-day mortality (P < 0.01), and sICH (P < 0.01). A significant interaction between MAP SD and rescue futile recanalization treatment was observed (P < 0.01).ConclusionsAmong patients with LVO stroke who underwent successful recanalization, higher BPV was associated with worse functional outcomes, especially in those who underwent rescue treatment.

Introduction: RET is well known as an important driver gene in NSCLC. Moreover, RET is a rare acquired resistance mechanism to EGFR-mutant NSCLC. Only 36 NSCLC cases of coexistence of EGFR and RET were reported previously worldwide. So far, there have been no reports on the following: (1) whether combination of EGFR tyrosine kinase inhibitor (TKI) and RET TKI works for meningeal metastasis; (2) the concentrations of EGFR TKI and RET TKI in the cerebrospinal fluid (CSF) and plasma; and (3) whether RET fusions and EGFR mutation happened in the same clone or not. Methods: We reported a patient with an EGFR-mutant NSCLC with acquired RET fusions and meningeal metastasis treated with pralsetinib and osimertinib; the specimen was analyzed by next-generation sequencing (Illumina NovaSeq 6000 platform). Symptom improvement and magnetic resonance imaging scan were used for effect evaluation. Furthermore, we determined the concentrations of pralsetinib and osimertinib in CSF and plasma by means of liquid chromatography tandem mass spectrometry. We also detected RET fusion and EGFR L858R mutation by methods of fluorescence in situ hybridization and immunohistochemistry with continuous sections to analyze whether RET fusions coexist with EGFR mutation in the same clone or not. Results: The allele frequency of the RET fusion was detected to be 12.88%. This patient achieved a partial response, indicating pralsetinib combined with osimertinib may be clinically beneficial for meningeal metastasis in patients harboring acquired coexistent RET fusions. The concentrations of pralsetinib in the CSF and plasma were 704.76 nM and 91.31 μM, whereas those of osimertinib in the CSF and plasma were 23.70 nM and 2148.94 nM, respectively. RET fusion was found in the same clone of EGFR L858R mutation. Conclusions: Our finding of this case indicated that RET fusion and EGFR mutation occur in the same population of cell clones, rather than in different cell clones. Combined pralsetinib may be an effective way to overcome the resistance, even for meningeal metastasis, owing to high CSF distribution of pralsetinib.

Abstract Spinal cord injury (SCI) is a devastating traumatic condition accompanied with excessive inflammatory response and apoptosis of microglia. Long noncoding RNAs (lncRNAs) have been confirmed to be key regulators of cell inflammatory response. Nevertheless, the role of lncRNA KCNQ1OT1 in microglia apoptosis or inflammatory response after SCI remains to be explored. Our study focused on exploring the role and mechanism of KCNQ1OT1 in microglia after SCI. RT-qPCR showed that SCI induced the increase of KCNQ1OT1 level in mice spinal cord. Inhibition of KCNQ1OT1 suppressed the inflammatory response and apoptosis of microglia. In addition, KCNQ1OT1 was proved to bind with miR-589-5p, and NPTN was directly targeted by miR-589-5p. Furthermore, KCNQ1OT1 was negatively correlated with miR-589-5p and positively associated with NPTN. Rescue assays indicated that NPTN overexpression reversed the anti-inflammatory and anti-apoptosis effects of KCNQ1OT1 silencing. In summary, these data revealed that KCNQ1OT1 promoted inflammatory response and apoptosis of microglia by regulating the miR-589-5p/NPTN axis after SCI, which may offer a novel promising therapeutic target for SCI.

Non-small cell lung cancer (NSCLC) is the most common pathological type of lung cancer. The systemic antitumor therapy of advanced NSCLC has undergone renovations of chemotherapy, targeted therapy and immunotherapy, which results in greatly improved survival for patients with advanced NSCLC. Immune checkpoint inhibitors (ICIs), especially targeting programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1), has changed the treatment paradigm of NSCLC. ICIs have become the standard treatment for advanced NSCLC without epidermal growth factor receptor(EGFR) mutation or anaplastic lymphomakinase(ALK) translocation in the first- or second-line setting, and for locally advanced NSCLC following concurrent radiotherapy and chemotherapy. ICIs are also promising in adjuvant/neoadjuvant therapy. More and more ICIs have been approved domestically for the treatment of NSCLC. Led by the NSCLC expert committee of Chinese Society of Clinical Oncology (CSCO), this consensus was developed and updated based on thoroughly reviewing domestic and foreign literatures, clinical trial data, systematic reviews, experts’ discussion and the consensus(2019 version). This consensus will aid domestic clinicians in the treatment of NSCLC with ICIs.

Plants recognize the presence or invasion of microbes through cell surface-localized pattern recognition receptors (PRRs) and intracellular nucleotide-binding domain leucine-rich repeat receptors (NLRs). Although PRRs and NLRs are activated by ligands located in different subcellular compartments through distinct mechanisms, signals initiated from PRRs and NLRs converge into several common signaling pathways with different dynamics. Increasing evidence suggests that PRR- and NLR-mediated signaling extensively crosstalk and such interaction can greatly influence immune response outcomes. Sophisticated experimental setups enabled dissection of the signaling events downstream of PRRs and NLRs with fine temporal and spatial resolution; however, the molecular links underlying the observed interactions in PRR and NLR signaling remain to be elucidated. In this review, we summarize the latest knowledge about activation and signaling mediated by PRRs and NLRs, deconvolute the intimate association between PRR- and NLR-mediated signaling, and propose hypotheses to guide further research on key topics.

Cancer stem cells, a relatively small group of self-renewing cancer cells, were first isolated from acute myeloid leukemia. These cells can play a crucial role in tumor metastasis, relapse, and therapy resistance. The cancer stem cell theory may be applied to lung cancer and explain the inefficiency of traditional treatments and eventual recurrence. However, because of the unclear accuracy and illusive biological function of cancer stem cells, some researchers remain cautious about this theory. Despite the ongoing controversy, cancer stem cells are still being investigated, and their biomarkers are being discovered for application in cancer diagnosis, targeted therapy, and prognosis prediction. Potential lung cancer stem cell markers mainly include surface biomarkers such as CD44, CD133, epithelial cell adhesion molecule, and ATP-binding cassette subfamily G member 2, along with intracellular biomarkers such as aldehyde dehydrogenase, sex-determining region Y-box 2, NANOG, and octamer-binding transcription factor 4. These markers have different structures and functions but are closely associated with the stem potential and uncontrollable proliferation of tumor cells. The aberrant activation of major signaling pathways, such as Notch, Hedgehog, and Wnt, may be associated with the expression and regulation of certain lung cancer stem cell markers, thus leading to lung cancer stem cell maintenance, chemotherapy resistance, and cancer promotion. Treatments targeting lung cancer stem cell markers, including antibody drugs, nanoparticle drugs, chimeric antigen receptor T-cell therapy, and other natural or synthetic specific inhibitors, may provide new hope for patients who are resistant to conventional lung cancer therapies. This review provides comprehensive and updated data on lung cancer stem cell markers with regard to their structures, functions, signaling pathways, and promising therapeutic target approaches, aiming to elucidate potential new therapies for lung cancer.

Calculating and predicting drug-target interactions (DTIs) is a crucial step in the field of novel drug discovery. Nowadays, many models have improved the prediction performance of DTIs by fusing heterogeneous information, such as drug chemical structure and target protein sequence and so on. However, in the process of fusion, how to allocate the weight of heterogeneous information reasonably is a huge challenge. In this paper, we propose a model based on Q-learning algorithm and Neighborhood Regularized Logistic Matrix Factorization (QLNRLMF) to predict DTIs. First, we obtain three different drug-drug similarity matrices and three different target-target similarity matrices by using different similarity calculation methods based on heterogeneous data, including drug chemical structure, target protein sequence and drug-target interactions. Then, we initialize a set of weights for the drug-drug similarity matrices and target-target similarity matrices respectively, and optimize them through Q-learning algorithm. When the optimal weights are obtained, a new drug-drug similarity matrix and a new drug-drug similarity matrix are obtained by linear combination. Finally, the drug target interaction matrix, the new drug-drug similarity matrices and the target-target similarity matrices are used as inputs to the Neighborhood Regularized Logistic Matrix Factorization (NRLMF) model for DTIs. Compared with the existing six methods of NetLapRLS, BLM-NII, WNN-GIP, KBMF2K, CMF, and NRLMF, our proposed method has achieved better effect in the four benchmark datasets, including enzymes(E), nuclear receptors (NR), ion channels (IC) and G protein coupled receptors (GPCR).

Lung cancer is the leading cause of cancer death worldwide as well as in China. For many years, conventional oncologic treatments such as surgery, chemotherapy, and radiotherapy (RT) have dominated the field of non-small cell lung cancer (NSCLC). The recent introduction of immunotherapy in clinical practice, led to a paradigm shift in lung cancer as in many other solid tumors. Recent pre-clinical and clinical data have shown RT may also modify antitumor immune responses through induction of immunogenic cell death and reprogramming of the tumor microenvironment. This has led many to reexamine RT as a partner therapy to immuno-oncology treatments and investigate their potential synergy in an exponentially growing number of clinical trials. Clinical trials combining radiotherapy and immunotherapy are attracting major attention, experts were invited to discuss frontier and controversial academic topics: (1) Recent developments of clinical synergy between radiation and immune checkpoint inhibitors (ICIs) in the treatment of NSCLC; (2) Will immunotherapy and radiotherapy increase the toxicity risk for cancer patients; (3) How to cope the mixed responses/disassociated responses phenomenon in checkpoint inhibition therapy to NSCLC with local ablative therapy; (4) Combining radiotherapy and immunotherapy in the treatment of NSCLC brain metastases.

Background and Objective Mortality of lung cancer can be decreased by early screening effectively. However, consistent and proficient standards & methods have not been established in China. This study was based on pulmonary nodules/lung cancer comprehensive management platform established by West China Hospital, Sichuan University. Early screening of pulmonary nodules was integrated into standard healthcare of lung cancer system, aiming to improve survivals of lung cancer patients. Methods Three cohorts were established: healthy populations, pulmonary nodules cohort and lung cancer patients cohort, and related clinical data will be collected and analyzed. Preliminary plan includes verifying effect of pulmonary nodules screening module. Results Pulmonary nodules screening was performed in 2,836 employers (>40 years old) of West China Hospital. Lung cancers were diagnosed in 66 participants, all receiving surgery to remove the lesions. 65 of them were with early stage diseases, 1 with lung cancer and brain metastasis. Conclusion Proficient screening, follow-up and healthcare can be achieved via pulmonary nodules/lung cancer comprehensive management mode, which will be extended all over west China region in future.

Background This retrospective study compared the efficacy and side effect profile between postoperative adjuvant radiotherapy and chemoradiotherapy in stage II or stage III thoracic esophageal squamous cell carcinoma (TESCC) patients who underwent curative (R0) esophagectomy. Methods A total of 272 TESCC patients who underwent radical esophagectomy from 2007 to 2016 were included in this retrospective analysis. All cases were pathologically confirmed with stage II or III disease and 148 patients received postoperative chemoradiotherapy (CRT), while the remaining 124 patients received postoperative radiotherapy (RT) alone. Results In CRT and RT groups, the three‐year overall survival rates were 51.3 versus 31.5% (P

Non-small cell lung cancer (NSCLC) is the most common pathological type of lung cancer, most NSCLC patients are at advanced stage at the time of diagnosis. For patients without sensitive driven-oncogene mutations, chemotherapy is still the main treatment at present, the overall prognosis is poor. Improving outcomes and obtaining long-term survival are the most urgent needs of patients with advanced NSCLC. In recent years, immunotherapy has developed rapidly. Immune checkpoint inhibitors (ICIs), especially targeting programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1), have made a breakthrough in the treatment of NSCLC, beneficial to patients’ survival and changed the treatment pattern for NSCLC. It shows more and more important role in the treatment of NSCLC. Led by NSCLC expert committee of Chinese society of clinical oncology (CSCO), relevant experts in this field were organized. On the basis of referring to domestic and foreign literature, systematically evaluating the results of Chinese and foreign clinical trials, and combining the experiences of the experts, the experts group reached an agreement to develop this consensus. It will guide domestic counterparts for better application of ICIs to treat NSCLC.

BackgroundPeyronie's disease (PD) is a chronic wound healing disorder, mainly involving tunica albuginea. Collagenase Clostridium Histolyticum (CCH) has shown its effectiveness in treating PD, but its efficacy and safety remain controversial, which propelled us to conduct the first evidence-based research on this topic.MethodsWe searched the Web of Science, PubMed, Embase, and ClinicalTrials.gov for related randomized controlled trials (RCTs). A systematic review and meta-analysis were performed to compare the penile curvature deformity (PCD), Peyronie's Disease Questionnaire peyronie's disease symptom bother (PDSB), penile pain score, total treatment-related adverse events (TAEs), and specific adverse events, including penile pain, penile edema, injection site pain, and contusion. Cochrane Collaboration's tool and Review Manager 5.3.0 version were applied, respectively, to evaluate the study quality and heterogeneity.ResultsFour articles (five RCTs) with 1,227 patients were finally included in the meta-analysis. The results revealed that CCH had excellent efficacy in relieving PCD (weighted mean difference [WMD]: −318.77, p < 0.001) and PDSB (WMD: −1.20, p < 0.001) compared to the placebo group, but there was no difference in the penile pain score (WMD: −0.64, P = 0.39) between the two groups. Furthermore, the incidence of TAEs in the CCH group was higher [odds ratio (OR): 12.86, p < 0.001].ConclusionsThe current evidence suggests that CCH has a significant effect on treating PD. Considering that all these adverse events are acceptable and curable, CCH could slow the disease progression in the acute phase or act as a substitute for patients unable or unwilling to undergo surgery. However, the conclusion could not be certainly drawn until RCTs with a larger scale proved it.

Although lycopene intake and risk of prostate cancer have been explored for decades, recent studies show that Non-Hispanic Black Prostate Cancer (PCa) patients benefit less than Non-Hispanic White patients from a lycopene intake intervention program. This study examined whether a lycopene intake-related racial disparity exists in reducing the risk of PCa in healthy adults. Data on healthy, cancer-free Non-Hispanic Black (NHB) men (n = 159) and Non-Hispanic White (NHW) men (n = 478) from the 2003 to 2010 NHANES dataset were analyzed. Total lycopene intake from daily diet, age, living status, race/ethnicity, education level, poverty income ratio, body mass index, and smoking status were studied as independent variables. The combination of total Prostate-Specific Antigen (PSA) level and the ratio of free PSA was set as criteria for evaluating the risk of PCa. Multivariable logistic regression was used in race-stratified analyses to compute odds ratios (OR) and 95% confidence intervals (95% CI) comparing high PCa risk with low PCa risk. We found, in the whole population, race/ethnicity was the only factor that influenced lycopene intake from the daily diet. NHB men consumed less lycopene than NHW men (3,716 vs. 6,487 (mcg), p = 0.01). Sufficient lycopene intake could reduce the risk of PCa (OR: 0.40, 95% CI: 0.18–0.85, p = 0.02). Men aged between 66 and 70 had high PCa risk (OR: 3.32, 95% CI: 1.12–9.85, p = 0.03). Obesity served as a protective factor against the high risk of PCa (OR: 0.25, 95% CI: 0.12–0.54, p = 0.001). NHW men aged between 66 and 70 had a high risk of PCa (OR: 4.01, 95% CI: 1.02–15.73, p = 0.05). Obese NHW men also had lower risk of PCa (OR: 0.18, 95% CI: 0.07–0.47 p = 0.001). NHB men had a high risk of PCa compared to NHW men (OR: 2.27, 95% CI: 1.35–3.81 p = 0.004). NHB men who were living without partners experienced an even higher risk of PCa (OR: 3.35, 95% CI: 1.01–11.19 p = 0.07). Sufficient lycopene intake from daily food could serve as a protector against PCa. Such an association was only observed in NHW men. Further studies are needed to explore the dose-response relationship between lycopene intake and the association of PCa risk in NHB men.

Cu impurities are reported to have significant effects on the electrical and optical properties of bulk ZnO. In this work, we study the defect properties of Cu in ZnO using hybrid quantum mechanical/molecular mechanical (QM/MM)–embedded cluster calculations based on a multi-region approach that allows us to model defects at the true dilute limit, with polarization effects described in an accurate and consistent manner. We compute the electronic structure, energetics, and geometries of Cu impurities, including substitutional and interstitial configurations, and analyze their effects on the electronic structure. Under ambient conditions, CuZn is the dominant defect in the d9 state and remains electronically passive. We find that, however, as we approach typical vacuum conditions, the interstitial Cu defect becomes significant and can act as an electron trap.

Nowadays, millions of patients suffer from physical disabilities, including lower-limb disabilities. Researchers have adopted a variety of physical therapies based on the lower-limb exoskeleton, in which it is difficult to adjust equipment parameters in a timely fashion. Therefore, intelligent control methods, for example, deep reinforcement learning (DRL), have been used to control the medical equipment used in human gait adjustment. In this study, based on the key-value attention mechanism, we reconstructed the agent’s observations by capturing the self-dependent feature information for decision-making in regard to each state sampled from the replay buffer. Moreover, based on Softmax Deep Double Deterministic policy gradients (SD3), a novel DRL-based framework, key-value attention-based SD3 (AT_SD3), has been proposed for gait adjustment. We demonstrated the effectiveness of our proposed framework in gait adjustment by comparing different gait trajectories, including the desired trajectory and the adjusted trajectory. The results showed that the simulated trajectories were closer to the desired trajectory, both in their shapes and values. Furthermore, by comparing the results of our experiments with those of other state-of-the-art methods, the results proved that our proposed framework exhibited better performance.

BackgroundData on the use of immune checkpoint inhibitors (ICIs) in advanced non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutation are limited. The current study aimed to assess the efficacy of ICIs in EGFR-mutant advanced NSCLC and explore the relevant influential factors.Materials and MethodsRelevant clinical data of EGFR-mutant NSCLC patients who had received ICIs were collected from multiple hospitals. The primary endpoint was progression-free survival (PFS), and the secondary endpoints were overall survival (OS), objective response rate (ORR), and relevant influential factors.ResultsA total of 122 advanced EGFR-mutant NSCLC patients were included in the final analysis. The total cohort had an objective response rate (ORR) of 32.0%, a median progression-free survival (mPFS) of 5.0 months, and a median overall survival (mOS) of 14.4 months. Among 96 patients with common EGFR mutations (19Del, 52 patients; L858R, 44 patients), those who were administered front-line ICI exhibited better survival benefits than those who received later-line ICI after disease progression on tyrosine kinase inhibitors (TKIs) treatment (mPFS: 7.2 months vs. 3.4 months, respectively, P < 0.0001; mOS: 15.1 months vs. 8.4 months, respectively, P

Currently, reinforcement learning (RL) has shown great potential in energy saving in HVAC systems. However, in most cases, RL takes a relatively long period to explore the environment before obtaining an excellent control policy, which may lead to an increase in cost. To reduce the unnecessary waste caused by RL methods in exploration, we extended the deep forest-based deep Q-network (DF-DQN) from the prediction problem to the control problem, optimizing the running frequency of the cooling water pump and cooling tower in the cooling water system. In DF-DQN, it uses the historical data or expert experience as a priori knowledge to train a deep forest (DF) classifier, and then combines the output of DQN to attain the control frequency, where DF can map the original action space of DQN to a smaller one, so DF-DQN converges faster and has a better energy-saving effect than DQN in the early stage. In order to verify the performance of DF-DQN, we constructed a cooling water system model based on historical data. The experimental results show that DF-DQN can realize energy savings from the first year, while DQN realized savings from the third year. DF-DQN’s energy-saving effect is much better than DQN in the early stage, and it also has a good performance in the latter stage. In 20 years, DF-DQN can improve the energy-saving effect by 11.035% on average every year, DQN can improve by 7.972%, and the model-based control method can improve by 13.755%. Compared with traditional RL methods, DF-DQN can avoid unnecessary waste caused by exploration in the early stage and has a good performance in general, which indicates that DF-DQN is more suitable for engineering practice.