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BackgroundChina has entered the era of digital health care after years of reforms in the health care system. The use of digital technologies in healthcare services is rapidly increasing, indicating the onset of a new period. The reform of health insurance has also entered a new phase. ObjectiveThis study aims to investigate the evolution of health care insurance within the context of telemedicine and Internet Plus Healthcare (IPHC) during the digital health care era by using scientometric methods to analyze publication patterns, influential keywords, and research hot spots. It seeks to understand how health care insurance has adapted to the growing integration of IPHC and telemedicine in health care services and the implications for policy and practice. MethodsA total of 411 high-quality studies were curated from the China National Knowledge Infrastructure (CNKI) database in the Chinese language, scientometric analysis was conducted, and VOSviewer software was used to conduct a visualized analysis of keywords and hot spots in the literature. ResultsThe number of articles in this field has increased notably from 2000 to 2022 and has increased annually based on a curve of y=0.332exp (0.4002x) with R2=0.6788. In total, 62 institutions and 811 authors have published research articles in the Chinese language in this field. This study included 290 keywords and formulated a total of 5 hot-topic clusters of “telemedicine,” “IPHC,” “internet hospital,” “health insurance payments,” and “health insurance system.” ConclusionsStudies on the application of digital technologies in health care insurance has evolved from foundational studies to a broader scope. The emergence of internet hospitals has showcased the potential for integrating IPHC services into insurance payment systems. However, this development also highlights the necessity for enhanced interregional coordination mechanisms. The reform of health insurance payment is contingent upon ongoing advancements in digital technology and increased investment in electronic medical records and primary health care services. Future efforts should focus on integrating technology with administrative systems, advancing mobile health care solutions, and ensuring interoperability among various payment systems to improve efficiency and standardize health care services.

Abstract Human resource management (HRM) in healthcare is an important component in relation to the quality and efficiency of healthcare delivery. However, a comprehensive overview is lacking to assess and track the current status and trends of HRM research in healthcare. This study aims to describe the current situation and global trends in HRM research in healthcare as well as to indicate the frontiers and future directions of research. The research methodology is based on bibliometric mapping using scientific visualization software (VOSviewer). The data were collected from the Web of Science(WoS) core citation database. After applying the search criteria, we retrieved 833 publications, which have steadily increased over the last 30 years. In addition, 93 countries and regions have published relevant research. The United States and Australia have made significant contributions in this area. Current research articles focus on topics clustered into performance, hospital/COVID-19, job satisfaction, human resource management, occupational/mental health, and quality of care. The most frequently co-occurring keywords are human resource management, job satisfaction, nurses, hospitals, health services, quality of care, COVID-19, and nursing. There is limited research on compensation management and employee relations management, so the current HRM research field still has not been able to present a complete and systematic roadmap. We propose that our colleagues should consider focusing on these research gaps in the future.

Abstract Background Myocardial ischemia-reperfusion (I/R) injury is accompanied by an imbalance in the cardiac autonomic nervous system, characterized by over-activated sympathetic tone and reduced vagal nerve activity. In our preceding study, we pioneered the development of the magnetic vagus nerve stimulation (mVNS) system. This system showcased precise vagus nerve stimulation, demonstrating remarkable effectiveness and safety in treating myocardial infarction. However, it remains uncertain whether mVNS can mitigate myocardial I/R injury and its specific underlying mechanisms. In this study, we utilized a rat model of myocardial I/R injury to delve into the therapeutic potential of mVNS against this type of injury. Results Our findings revealed that mVNS treatment led to a reduction in myocardial infarct size, a decrease in ventricular fibrillation (VF) incidence and a curbing of inflammatory cytokine release. Mechanistically, mVNS demonstrated beneficial effects on myocardial I/R injury by inhibiting NLRP3-mediated pyroptosis through the M2AChR/OGDHL/ROS axis. Conclusions Collectively, these outcomes highlight the promising potential of mVNS as a treatment strategy for myocardial I/R injury.

Abstract Background Patients with non‐small‐cell lung cancer (NSCLC) and uncommon EGFR alterations typically have worse treatment outcomes than patients with classically EGFR‐mutated NSCLC. This study aimed to investigate the efficacy and safety of PD‐1 blockade with sintilimab plus anti‐angiogenic treatment with anlotinib in patients with NSCLC harboring uncommon EGFR mutations. Methods Patients with metastatic NSCLC harboring uncommon EGFR mutations after two previous treatments, including a platinum‐based chemotherapy regimen and a targeted treatment (or chemotherapy only for patients harboring EGFR ex20ins), received sintilimab combined with anlotinib. The primary endpoint was objective response rate (ORR). Results At data cutoff (September 27, 2022), median follow‐up was 22.3 months (range, 1.2–37.6). Among 21 enrolled patients, 12 had EGFR ex20ins and nine had other uncommon EGFR mutations such as L861Q, G719A, and G709X. Overall, eight patients (38.1%) achieved an objective response, and 18 (85.7%) achieved disease control. Median (95% CI) progression‐free survival (PFS) was 7.0 (5.4–8.6) months, and median overall survival (OS) was 20.0 (15.6–24.4) months. The 12‐month PFS rate (95% CI) was 22.2% (7.4–42.0), and the 12‐month OS rate was 66.7% (42.5–82.5). Patients harboring EGFR ex20ins had similar ORR and PFS to those with other mutations. Six patients (28.6%) experienced grade 3 treatment‐related adverse events (TRAEs); hand‐foot syndrome was the most common grade 3 TRAE (2 patients; 9.5%). No grade ≥4 TRAEs were observed. Conclusions The combination of sintilimab and anlotinib demonstrated durable efficacy and was generally well tolerated in patients with NSCLC and uncommon EGFR mutations who had received prior standard‐of‐care treatments. (ClinicalTrials.gov identifier: NCT04790409).

Bone age is one of the most important evaluation indexes for the growth and development of children and adolescents. The bone age assessment method based on deep learning generally uses the whole left wrist X-ray film or some regions of interest in the left wrist X-ray film. Based on the entire X-ray film, the intelligent evaluation process is simple, but the accuracy is low. Although intelligent evaluation based on regions of interest has high accuracy, it requires prior knowledge and the process is complex. To solve the above problems, this paper proposes a multi-region combined method for bone age assessment. A small number of regions of interest in wrist bone X-ray films are extracted, and then the whole X-ray film and these regions of interest were used to evaluate the bone age. The experiment uses the improved Inception-ResNet-V2 convolutional neural network. The results show that compared with other bone age assessment studies on the open data set published by the North American radiological Association, this method can obtain higher accuracy of bone age assessment, with an average absolute error of 7.11 months. This method improves the efficiency and accuracy of bone age assessment while simplifying the assessment process.

BackgroundQL1604 is a humanized immunoglobulin G4 monoclonal antibody against programmed cell death protein 1. This first-in-human, open-label phase I study aimed to investigate the safety and tolerability and to identify the recommended doses of QL1604 for future studies. Pharmacokinetics/pharmacodynamics (PK/PD) and preliminary antitumor activity were also assessed.MethodsPatients with advanced or metastatic solid tumors who failed or had no standard therapies available were recruited. In the dose-escalation phase, patients were treated with QL1604 at 0.3 mg/kg, 1 mg/kg, 3 mg/kg, and 10 mg/kg intravenously once every 2 weeks (Q2W) in an accelerated titration with a traditional 3 + 3 design, followed by a dose-expansion phase at 3 mg/kg Q2W, 3 mg/kg once every 3 weeks (Q3W), 10 mg/kg Q2W and a fixed dose of 200 mg Q3W. Dose-limiting toxicities (DLTs) were assessed during the first 28 days after the first dose of study drug. Adverse events (AEs) were graded per National Cancer Institute Common Terminology Criteria for Adverse Events version 5.0, and antitumor activity of QL1604 was evaluated by investigators on the basis of Response Evaluation Criteria in Solid Tumors version 1.1.ResultsA total of 35 patients with advanced or metastatic solid tumors were enrolled. DLTs were reported in one patient at the dose level of 3 mg/kg Q2W (grade 3 immune-mediated myositis and myasthenia gravis), and maximum tolerated dose was not reached. The most frequent treatment-related AEs (≥10%) were fatigue (37.1%), anemia (22.9%), increased blood thyroid-stimulating hormone (17.1%), increased aspartate aminotransferase (AST) (17.1%), increased alanine aminotransferase (ALT) (14.3%), decreased white blood cell (WBC) count (11.4%), rash (14.3%), and pruritus (14.3%). AEs leading to discontinuation of QL1604 occurred in three of the 35 patients (8.6%). Partial responses (PRs) occurred in seven patients, resulting in an objective response rate of 20.0% (7/35). Single dose of QL1604 exhibited a dose-dependent increase in the exposure ranging from 0.3 mg/kg to 10 mg/kg. Mean receptor occupancy (RO) for QL1604 at the dose of 3 mg/kg (Q2W and Q3W) and 200 mg (Q3W) was greater than 80% during cycle 1 after one infusion.ConclusionQL1604 monotherapy exhibited favorable safety, PK, and signal of antitumor activity in patients with advanced or metastatic solid tumors, and the results supported further clinical studies of QL1604. On the basis of the safety, PK, and RO data, the recommended dosage for further clinical trials is 3 mg/kg or a fixed dose of 200 mg given every 3 weeks.Clinical Trial Registrationhttps://classic.clinicaltrials.gov/ct2/show/NCT05649761?term=QL1604&draw=2&rank=1, identifier NCT05649761.

Some achievements have been made in a province of China for old cavern reconstruction of salt-cavern gas storage, but some of the reconstructed caverns are not suitable to be used as underground gas storages for peak sheaving of pipeline network due to small working gas capacity and high cost of cushion gas. However, underground salt caverns are still very important strategic resources. Specifically, these salt caverns, if constructed as a compressed air energy storage power station, can be used to store power resources in the valley power stage. Based on successful foreign cases and the given situation of these underground salt caverns, specific parameters for reconstruction of the energy storage power station were calculated, and the economic analysis was carried out for the energy storage power station reconstructed with old salt caverns. The results show that X1 old cavern can store 3.07×106 kW·h of energy and generate 17.49×104 kW·h power in a single injection production cycle according to the actual situation. The reconstruction of salt cavern gas storage would have a good development prospect under the background of "carbon peaking and carbon neutrality" if it could explore to establish a suitable business mode while improving the technology.

Abstract Background Determining the tissue of origin (TOO) is essential for managing cancer of unknown primary (CUP). In this study, we evaluated the concordance between genome profiling and DNA methylation analysis in determining TOO for lung-specific CUP and assessed their performance by comparing the clinical responses and survival outcomes of patients predicted with multiple primary or with metastatic cancer. Methods We started by retrospectively screening for CUP patients who presented with both intra- and extrathoracic tumors. Tumor samples from included patients were analyzed with targeted sequencing with a 520-gene panel and targeted bisulfite sequencing. TOO inferences were made in parallel via an algorithm using genome profiles and time interval between tumors and via machine learning-based classification of DNA methylation profiles. Results Four hundred patients were screened retrospectively. Excluding patients definitively diagnosed with conventional diagnostic work-up or without available samples, 16 CUP patients were included. Both molecular approaches alone enabled inference of clonality for all analyzed patients. Genome profile enabled TOO inference for 43.8% (7/16) patients, and the percentage rose to 68.8% (11/16) after considering inter-tumor time lag. On the other hand, DNA methylation analysis was conclusive for TOO prediction for 100% (14/14) patients with available samples. The two approaches gave 100% (9/9) concordant inferences regarding clonality and TOO identity. Moreover, patients predicted with metastatic disease showed significantly shorter overall survival than those with multiple primary tumors. Conclusions Genome and DNA methylation profiling have shown promise as individual analysis for TOO identification. This study demonstrated the feasibility of incorporating the two methods and proposes an integrative scheme to facilitate diagnosing and treating lung-specific CUPs.

Abstract Background Brain metastasis is a common and lethal complication of non-small cell lung cancer (NSCLC). It is mostly diagnosed only after symptoms develop, at which point very few treatment options are available. Therefore, patients who have an increased risk of developing brain metastasis need to be identified early. Our study aimed to identify genomic and epigenomic biomarkers for predicting brain metastasis risk in NSCLC patients. Methods Paired primary lung tumor tissues and either brain metastatic tissues or cerebrospinal fluid (CSF) samples were collected from 29 patients with treatment-naïve advanced NSCLC with central nervous system (CNS) metastases. A control group comprising 31 patients with advanced NSCLC who died without ever developing CNS metastasis was also included. Somatic mutations and DNA methylation levels were examined through capture-based targeted sequencing with a 520-gene panel and targeted bisulfite sequencing with an 80,672 CpG panel. Results Compared to primary lung lesions, brain metastatic tissues harbored numerous unique copy number variations. The tumor mutational burden was comparable between brain metastatic tissue (P = 0.168)/CSF (P = 0.445) and their paired primary lung tumor samples. Kelch-like ECH-associated protein (KEAP1) mutations were detected in primary lung tumor and brain metastatic tissue samples of patients with brain metastasis. KEAP1 mutation rate was significantly higher in patients with brain metastasis than those without (P = 0.031). DNA methylation analysis revealed 15 differentially methylated blocks between primary lung tumors of patients with and without CNS metastasis. A brain metastasis risk prediction model based on these 15 differentially methylated blocks had an area under the curve of 0.94, with 87.1% sensitivity and 82.8% specificity. Conclusions Our analyses revealed 15 differentially methylated blocks in primary lung tumor tissues, which can differentiate patients with and without CNS metastasis. These differentially methylated blocks may serve as predictive biomarkers for the risk of developing CNS metastasis in NSCLC. Additional larger studies are needed to validate the predictive value of these markers.

Abstract Background There is only limited knowledge of the treatment responses and clinical outcomes of immune checkpoint inhibitors (ICIs) in driver gene‐negative non‐small cell lung cancer (NSCLC) patients with brain metastases (BM). This study aims to assess the efficacy of immunotherapy in these patients in a real world setting. Methods NSCLC‐BM patients without driver gene mutations who received ICIs were retrospectively identified between July 2017 and December 2019. The primary observation endpoint was intracranial objective response rate (iORR), and secondary objectives were objective response rate (ORR), intracranial and systemic progression‐free survival (iPFS, PFS), and overall survival (OS). Results We reviewed 1578 patients with lung cancer and BM. According to the exclusion criteria, 41 patients were finally enrolled. Among these 41 patients, iORR was 36.6% (95% confidence interval [CI] = 21.2%–52.0%), whereas iPFS was 6.8 (95% CI = 3.32–10.35) months. Additionally, ORR, PFS, and OS were 24.4% (95% CI = 10.7%–38.1%), 6.2 (95% CI = 4.57–7.83) months and 13.7 (95% CI = 11.20–16.26) months, respectively. ICIs combined with concurrent radiotherapy group exhibited preferred iORR (p = 0.030) compared with no radiotherapy group, and ICIs plus chemotherapy showed improved OS (p = 0.024) compared to ICI monotherapy. Moreover, the lines of ICI treatment ≥2 (p = 0.005) and derived neutrophil‐to‐lymphocyte ratio (dNLR) ≥3 (p = 0.010) were independently negative factors for OS. Conclusion In NSCLC‐BMs patients lacking driver genes, ICIs exhibited an effective drug regime. A combination of ICIs with concurrent radiotherapy showed a better intracranial response, whereas ICIs plus chemotherapy were associated with superior OS.

Unmanned Aerial Vehicle (UAV) path planning research refers to the UAV automatically planning an optimal path to the destination under the corresponding environment, while avoiding collision with obstacles in this process. In order to solve the problem of 3D path planning of UAV in a dynamic environment, a heuristic dynamic reward function is designed to guide the UAV. We propose the Environment Exploration Twin Delayed Deep Deterministic Policy Gradient (EE-TD3) algorithm, which combines the symmetrical 3D environment exploration coding mechanism on the basis of TD3 algorithm. The EE-TD3 algorithm model can effectively avoid collisions, improve the training efficiency, and achieve faster convergence speed. Finally, the performance of the EE-TD3 algorithm and other deep reinforcement learning algorithms was tested in the simulation environment. The results show that the EE-TD3 algorithm is better than other algorithms in solving the 3D path planning problem of UAV.

Predicting the drug response of patients with cancer is crucial for implementing targeted therapy. Here, Su et al. make patient-derived cell lines and perform targeted sequencing and RNA-seq to identify CDKN2A/2B loss as a predictor of response to CDK4/6 inhibitors in esophageal squamous cell carcinoma.

Visibility affects all forms of traffic: roads, sailing, and aviation. Visibility prediction is meaningful in guiding production and life. Different from weather prediction, which relies solely on atmosphere factors, the factors that affect meteorological visibility are more complicated, such as the air pollution caused by factory exhaust emission. However, the current prediction of visibility is mostly based on the numerical prediction method similar to the weather prediction. We proposed a method using multimodal fusion to build a weather visibility prediction system in this paper. An advanced numerical prediction model and a method for emission detection were used to build a multimodal fusion visibility prediction system. We used the most advanced regression algorithm, XGBoost, and LightGBM, to train the fusion model for numerical prediction. Through the estimation of factory emission by the traditional detector in the satellite image, we propose to add the result of estimation based on Landsat-8 satellite images to assist the prediction. By testing our numerical model in atmosphere data of various meteorological observation stations in Beijing-Tianjin-Hebei region from 2002 to 2018, our numerical prediction model turns out to be more accurate than other existing methods, and after fusing with emission detection method, the accuracy of our visibility prediction system has been further improved.

Abstract Background Brain metastasis is an extremely serious sequela with a dismal prognosis in non-small cell lung cancer (NSCLC). The present study aimed to identify novel biomarkers and potential therapeutic targets for brain metastases of NSCLC. Methods We performed high-throughput Luminex assays to profile the transcriptional levels of 36 genes in 70 operable NSCLC patients, among whom 37 developed brain metastases as the first relapse within 3 years after surgery. The Cox proportional hazards regression model was used to evaluate the association between genes and brain metastases. Wound healing assay and transwell assay was carried out to estimate the function of target gene in vitro. And left ventricular injection on nude mice was used to evaluate the effect of target gene in vivo. Results Growth-associated protein 43 (GAP43) was found to be related to brain metastasis. Multivariate Cox regression analysis showed that NSCLC patients with elevated GAP43 had a 3.29-fold increase in the risk for brain metastasis compared with those with low levels (95% confidence interval: 1.55–7.00; P = 0.002). Kaplan–Meier survival curves revealed that GAP43 was also associated with overall survival. Analysis of a cohort of 1926 NSCLC patients showed similar results: patients with high levels of GAP43 had worse progression-free and overall survival rates. Furthermore, in vitro experiments showed that GAP43 facilitated cell migration. Animal studies demonstrated that GAP43-silenced NSCLC cells were less likely to metastasize to the brain and bone than control cells. Immunofluorescence and F-actin/G-actin in vivo assays indicated that GAP43 knockdown triggered depolymerization of the F-actin cytoskeleton. Rho GTPase activation assays showed that Rac1 was deactivated after GAP43 was silenced. Conclusions Our findings suggest that GAP43 is an independent predictor of NSCLC brain metastasis and that it may facilitate metastasis by regulating the Rac1/F-actin pathway.

Abstract Background Next generation sequencing (NGS) is being increasingly applied for assisting cancer molecular diagnosis. However, it is still needed to validate NGS accuracy on detection of DNA alternations based on a large number of clinical samples, especially for DNA rearrangements and copy number variations (CNVs). This study is to set up basic parameters of targeted NGS for clinical diagnosis and to understand advantage of targeted NGS in comparison with the conventional methods of molecular diagnosis. Methods Genomic DNA from 1000 Genomes Project and DNA from cancer cell lines have been used to establish the basic parameters for targeted NGS. The following confirmation was conducted by clinical samples. The multiple variants tested by amplification-refractory mutation system (ARMS), fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) were evaluated by targeted NGS to determine the sensitivity. Furthermore, the multiple variants detected by targeted NGS were confirmed by current conventional methods to elucidate the specificity. Results At sequencing depth of 500×, the maximal sensitivities on detecting single nucletic variances (SNVs) and small insertions/deletions (Indels) can reach 99% and 98.7% respectively, and in 20% of cancer cells, CNV detection can reach to the maximal level. The following confirmation of the sensitivity and specificity was conducted by a large cohort of clinical samples. For SNV and indel detection in clinical samples, targeted NGS can identify all hotspot mutations with 100% sensitivity and specificity. On ALK fusion detection, about 86% IHC-identified cases could be identified by targeted NGS and all ALK fusion detected by targeted NGS were confirmed by IHC. For HER2-amplification, 14 HER2-amplification cases identified by target NGS were all confirmed by FISH and about 93.3% of Her-2 IHC (3+) cases were identified by targeted NGS. Finally, the targeted NGS platform developed here has accurately detected EGFR hotspot mutations in 215 NSCLC patients. Conclusions DNA from cancer cell lines is better than standard DNA as a reference to establish basic parameters for targeted NGS. Comparison of the conventional methods using a large cohort of patient samples confirmed the high preformance of targeted NGS on detecting DNA alterations.

Tight oil in the redeposited carbonates was mainly distributed in the Lower Submember of Member 3 of Shahejie Formation in Shulu sag of Jizhong depression, North China. Through high-resolution 3D seismic data, well logging data and drilling data, the Lower Submember of Member 3 of Shahejie Formation was divided into 5 third-order sequences and 15 parasequence sets. The redeposited marl and rudstone were major reserving horizons of tight oil, and ten reserving space types were developed and could be classified into two main categories, i.e., pores and fractures. Two types of tight oil reservoirs were established, i.e., the marl hydrocarbon reservoir of the source-reservoir integration and the rudstone hydrocarbon reservoirs of the source-reservoir paragenesis. The assemblage relationship among the high-quality source rocks, system tracts with the source-reservoir configuration was the major control factor for tight oil accumulation in the redeposited carbonates. The lacustrine transgressive system tracts and highstand systems tracts in SQ1 to SQ5 were the favorable horizons for development of the marl hydrocarbon reservoir, the lowstand system tracts in SQ1 to SQ3 were the favorable horizons for development of the rudstone hydrocarbon reservoir. Keywords: Member 3 of Shahejie Formation, Tight oil, Re-deposited carbonate, Marl, Rudstone, Third-order sequence, Hydrocarbon reservoir

In this study, a unified constitutive model has been developed for both yield strength and work hardening behaviour prediction of aluminium alloys with different types of precipitates during and after artificial ageing. The different type and dimensions of general precipitate shapes (sphere, plate, rod) have been classified and modelled by a primary dimension and aspect ratio, with which a general set of equations has been utilised to model the precipitates evolutions during ageing of various aluminium alloys. In addition, the effects of main microstructures on not only yield strength but also work-hardening behaviour of artificially aged aluminium alloys have been considered and modelled, based on which, a whole set of unified constitutive model considering both micro- and macro-properties for long-term artificial ageing of aluminium alloys has been proposed. Artificial ageing of two representative aluminium alloys (an Al-Mg-Si alloy AA6063 and an Al-Cu-Li alloy AA2198) has been adopted to show the capability and effectiveness of the developed model. The results show that the model can successfully predict the microstructures, yield strength and work hardening behaviour of various aluminium alloys with different precipitate types after long-term artificial ageing process, e.g., from 0 h to 500 h. It is believed that the model can be used for ageing of other aluminium alloys with dominant sphere, plate or rod-shaped precipitates.

In mine ventilation networks, the reasonable airflow distribution is very important for the production safety and economy. Three basic problems of the natural, full-controlled and semi-controlled splitting were reviewed in the paper. Aiming at the high difficulty semi-controlled splitting problem, the general nonlinear multi-objectives optimization mathematical model with constraints was established based on the theory of mine ventilation networks. A new algorithm, which combined the improved differential evaluation and the critical path method (CPM) based on the multivariable separate solution strategy, was put forward to search for the global optimal solution more efficiently. In each step of evolution, the feasible solutions of air quantity distribution are firstly produced by the improved differential evolution algorithm, and then the optimal solutions of regulator pressure drop are obtained by the CPM. Through finite steps iterations, the optimal solution can be given. In this new algorithm, the population of feasible solutions were sorted and grouped for enhancing the global search ability and the individuals in general group were randomly initialized for keeping diversity. Meanwhile, the individual neighborhood in the fine group which may be closely to the optimal solutions were searched locally and slightly for achieving a balance between global searching and local searching, thus improving the convergence rate. The computer program was developed based on this method. Finally, the two ventilation networks with single-fan and multi-fans were solved. The results show that this algorithm has advantages of high effectiveness, fast convergence, good robustness and flexibility. This computer program could be used to solve large-scale generalized ventilation networks optimization problem in the future. Keywords: Mine ventilation network, Differential evolution algorithm, Critical path method, Population group and neighborhood search, Multivariable separate solution

Bone age is one of the most important evaluation indexes for the growth and development of children and adolescents. The bone age assessment method based on deep learning generally uses the whole left wrist X-ray film or some regions of interest in the left wrist X-ray film. Based on the entire X-ray film, the intelligent evaluation process is simple, but the accuracy is low. Although intelligent evaluation based on regions of interest has high accuracy, it requires prior knowledge and the process is complex. To solve the above problems, this paper proposes a multi-region combined method for bone age assessment.Asmall number of regions of interest in wrist bone X-ray films are extracted, and then the whole X-ray film and these regions of interest were used to evaluate the bone age. The experiment uses the improved Inception-ResNet-V2 convolutional neural network. The results show that compared with other bone age assessment studies on the open data set published by the North American radiological Association, this method can obtain higher accuracy of bone age assessment, with an average absolute error of 7.11 months. This method improves the efficiency and accuracy of bone age assessment while simplifying the assessment process. [ABSTRACT FROM AUTHOR]

Background: QL1604 is a humanized immunoglobulin G4 monoclonal antibody against programmed cell death protein 1. This first-in-human, open-label phase I study aimed to investigate the safety and tolerability and to identify the recommended doses of QL1604 for future studies. Pharmacokinetics/pharmacodynamics (PK/PD) and preliminary antitumor activity were also assessed. Methods: Patients with advanced or metastatic solid tumors who failed or had no standard therapies available were recruited. In the dose-escalation phase, patients were treated with QL1604 at 0.3 mg/kg, 1 mg/kg, 3 mg/kg, and 10 mg/kg intravenously once every 2 weeks (Q2W) in an accelerated titration with a traditional 3 + 3 design, followed by a dose-expansion phase at 3 mg/kg Q2W, 3 mg/kg once every 3 weeks (Q3W), 10 mg/kg Q2W and a fixed dose of 200 mg Q3W. Dose-limiting toxicities (DLTs) were assessed during the first 28 days after the first dose of study drug. Adverse events (AEs) were graded per National Cancer Institute Common Terminology Criteria for Adverse Events version 5.0, and antitumor activity of QL1604 was evaluated by investigators on the basis of Response Evaluation Criteria in Solid Tumors version 1.1. Results: A total of 35 patients with advanced or metastatic solid tumors were enrolled. DLTs were reported in one patient at the dose level of 3 mg/kg Q2W (grade 3 immune-mediated myositis and myasthenia gravis), and maximum tolerated dose was not reached. The most frequent treatment-related AEs (≥10%) were fatigue (37.1%), anemia (22.9%), increased blood thyroid-stimulating hormone (17.1%), increased aspartate aminotransferase (AST) (17.1%), increased alanine aminotransferase (ALT) (14.3%), decreased white blood cell (WBC) count (11.4%), rash (14.3%), and pruritus (14.3%). AEs leading to discontinuation of QL1604 occurred in three of the 35 patients (8.6%). Partial responses (PRs) occurred in seven patients, resulting in an objective response rate of 20.0% (7/35). Single dose of QL1604 exhibited a dose-dependent increase in the exposure ranging from 0.3 mg/kg to 10 mg/kg. Mean receptor occupancy (RO) for QL1604 at the dose of 3 mg/kg (Q2W and Q3W) and 200 mg (Q3W) was greater than 80% during cycle 1 after one infusion. Conclusion: QL1604 monotherapy exhibited favorable safety, PK, and signal of antitumor activity in patients with advanced or metastatic solid tumors, and the results supported further clinical studies of QL1604. On the basis of the safety, PK, and RO data, the recommended dosage for further clinical trials is 3 mg/kg or a fixed dose of 200 mg given every 3 weeks. [ABSTRACT FROM AUTHOR]