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Decrease in the cost of acquiring 3D point cloud data coupled with the rapid advancements in GPU computing power have resulted in an increased demand for 3D point cloud semantic segmentation in numerous 3D visual applications, including but not limited to autonomous driving, industrial control, and MR/XR, which further advances the development of deep learning methods in 3D point cloud semantic segmentation. Recently, many novel deep learning network architectures, such as RandLA-Net and Point Transformer, have been proposed and have achieved notable improvements in semantic segmentation accuracy while decreasing the computational load. However, previous research on 3D point cloud semantic segmentation methods has focused primarily on relatively early works, whose approaches have been gradually abandoned over the years and cannot accurately reflect the current research status. Moreover, the existing methods have been categorized based on their input data types, making it difficult to compare the segmentation performance of different techniques and not providing a comprehensive view of the relationship between methods using different network architectures. Therefore, this paper reviews the mainstream 3D semantic segmentation methods developed in the last three years using different deep learning network architectures and is organized into three levels. First, the two principal 3D point cloud data acquisition methods, including their customary datasets and metrics to evaluate model performance, are introduced. Second, a systematic review of 3D semantic segmentation methods based on different network architectures is organized, followed by a statistical analysis of the evaluation of performance between different models on two 3D segmentation datasets—S3DIS and ScanNet. The analysis of model performance on these two commonly used datasets includes model structure relevance, strengths, and limitations. Finally, an insightful discussion of the remaining methodological and application challenges and potential research directions is provided. This paper offers an extensive overview of the recent three-year research progress in 3D point cloud semantic segmentation and summarizes various network architecture pipelines, elucidates their fundamental operations, compares the model performance across multiple architectures, discusses their notable strengths and limitations, most importantly, concludes the current challenges and promising research directions for future investigations. Furthermore, this paper enables researchers to effortlessly identify the relevant research and research hotspots among different 3D point cloud semantic segmentation methods based on the analyses presented and aims to update the reviews on 3D point cloud semantic segmentation methods with a better viewpoint and highlight key properties and contributions of proposed methods, providing promising research directions for the main challenges.

Abstract The social economy is growing rapidly, and the power grid load demand is increasing. To maintain the stability of the power grid, it is crucial to achieve accurate and rapid power system stability assessment. In the actual operation of the power network, data loss is an unavoidable situation. However, most of the data‐driven models currently used assume that the input data is complete, which has obvious limitations in real‐world applications. This paper suggests an IVS‐GAN model to assess power system stability using incomplete phasor measurement unit measurement data with random loss. The proposed method combines the super‐resolution perception technology based on generative adversarial network (GAN) with a time‐series signal classification model. The generator adopts a 1D U‐Net network and uses convolutional layers to complete and recover missing data. The discriminator adopts a new gated recurrent unit–attention architecture proposed here to better extract voltage temporal variation features on key buses. The result of this paper is that the stability evaluation method outperforms other algorithms in high voltage data loss rates on the New England 10‐machine 39‐bus system.

Cross-modal retrieval for rice leaf diseases is crucial for prevention, providing agricultural experts with data-driven decision support to address disease threats and safeguard rice production. To overcome the limitations of current crop leaf disease retrieval frameworks, we focused on four common rice leaf diseases and established the first cross-modal rice leaf disease retrieval dataset (CRLDRD). We introduced cross-modal retrieval to the domain of rice leaf disease retrieval and introduced FHTW-Net, a framework for rice leaf disease image–text retrieval. To address the challenge of matching diverse image categories with complex text descriptions during the retrieval process, we initially employed ViT and BERT to extract fine-grained image and text feature sequences enriched with contextual information. Subsequently, two-way mixed self-attention (TMS) was introduced to enhance both image and text feature sequences, with the aim of uncovering important semantic information in both modalities. Then, we developed false-negative elimination–hard negative mining (FNE-HNM) strategy to facilitate in-depth exploration of semantic connections between different modalities. This strategy aids in selecting challenging negative samples for elimination to constrain the model within the triplet loss function. Finally, we introduced warm-up bat algorithm (WBA) for learning rate optimization, which improves the model’s convergence speed and accuracy. Experimental results demonstrated that FHTW-Net outperforms state-of-the-art models. In image-to-text retrieval, it achieved R@1, R@5, and R@10 accuracies of 83.5%, 92%, and 94%, respectively, while in text-to-image retrieval, it achieved accuracies of 82.5%, 98%, and 98.5%, respectively. FHTW-Net offers advanced technical support and algorithmic guidance for cross-modal retrieval of rice leaf diseases.

The behavior of pigs is intricately tied to their health status, highlighting the critical importance of accurately recognizing pig behavior, particularly abnormal behavior, for effective health monitoring and management. This study addresses the challenge of accommodating frequent non-rigid deformations in pig behavior using deformable convolutional networks (DCN) to extract more comprehensive features by incorporating offsets during training. To overcome the inherent limitations of traditional DCN offset weight calculations, the study introduces the multi-path coordinate attention (MPCA) mechanism to enhance the optimization of the DCN offset weight calculation within the designed DCN-MPCA module, further integrated into the cross-scale cross-feature (C2f) module of the backbone network. This optimized C2f-DM module significantly enhances feature extraction capabilities. Additionally, a gather-and-distribute (GD) mechanism is employed in the neck to improve non-adjacent layer feature fusion in the YOLOv8 network. Consequently, the novel DM-GD-YOLO model proposed in this study is evaluated on a self-built dataset comprising 11,999 images obtained from an online monitoring platform focusing on pigs aged between 70 and 150 days. The results show that DM-GD-YOLO can simultaneously recognize four common behaviors and three abnormal behaviors, achieving a precision of 88.2%, recall of 92.2%, and mean average precision (mAP) of 95.3% with 6.0MB Parameters and 10.0G FLOPs. Overall, the model outperforms popular models such as Faster R-CNN, EfficientDet, YOLOv7, and YOLOv8 in monitoring pens with about 30 pigs, providing technical support for the intelligent management and welfare-focused breeding of pigs while advancing the transformation and modernization of the pig industry.

Tomato leaf disease control in the field of smart agriculture urgently requires attention and reinforcement. This paper proposes a method called LAFANet for image-text retrieval, which integrates image and text information for joint analysis of multimodal data, helping agricultural practitioners to provide more comprehensive and in-depth diagnostic evidence to ensure the quality and yield of tomatoes. First, we focus on six common tomato leaf disease images and text descriptions, creating a Tomato Leaf Disease Image-Text Retrieval Dataset (TLDITRD), introducing image-text retrieval into the field of tomato leaf disease retrieval. Then, utilizing ViT and BERT models, we extract detailed image features and sequences of textual features, incorporating contextual information from image-text pairs. To address errors in image-text retrieval caused by complex backgrounds, we propose Learnable Fusion Attention (LFA) to amplify the fusion of textual and image features, thereby extracting substantial semantic insights from both modalities. To delve further into the semantic connections across various modalities, we propose a False Negative Elimination-Adversarial Negative Selection (FNE-ANS) approach. This method aims to identify adversarial negative instances that specifically target false negatives within the triplet function, thereby imposing constraints on the model. To bolster the model’s capacity for generalization and precision, we propose Adversarial Regularization (AR). This approach involves incorporating adversarial perturbations during model training, thereby fortifying its resilience and adaptability to slight variations in input data. Experimental results show that, compared with existing ultramodern models, LAFANet outperformed existing models on TLDITRD dataset, with top1, top5, and top10 reaching 83.3% and 90.0%, and top1, top5, and top10 reaching 80.3%, 93.7%, and 96.3%. LAFANet offers fresh technical backing and algorithmic insights for the retrieval of tomato leaf disease through image-text correlation.

BackgroundElderly stroke survivors are encouraged to receive appropriate health information to prevent recurrences. After discharge, older patients seek health information in everyday contexts, examining aspects that facilitate or impair healthy behavior.ObjectivesTo explore the experiences of older stroke patients when searching for health information, focusing on search methods, identification of health information, and difficulties faced during the search process.MethodsUsing the qualitative descriptive methodology, semi-structured interviews were conducted with fifteen participants.ResultsParticipants associated the health information they sought with concerns about future life prospects triggered by perceived intrusive changes in their living conditions. Based on the participants’ descriptions, four themes were refined: participants’ motivation to engage in health information acquisition behavior, basic patterns of health information search, source preferences for health information, and difficulties and obstacles in health information search, and two search motivation subthemes, two search pattern subthemes, four search pathway subthemes, and four search difficulty subthemes were further refined.ConclusionOlder stroke patients face significant challenges in searching for health information online. Healthcare professionals should assess survivors’ health information-seeking skills, develop training programs, provide multichannel online access to health resources, and promote secondary prevention for patients by improving survivors’ health behaviors and self-efficacy.

Escherichia coli (E. coli) mutant strains have been reported to extend the life span of Caenorhabditis elegans (C. elegans). However, the specific mechanisms through which the genes and pathways affect aging are not yet clear. In this study, we fed Drosophila melanogaster (fruit fly) various E. coli single-gene knockout strains to screen mutant strains with an extended lifespan. The results showed that D. melanogaster fed with E. coli purE had the longest mean lifespan, which was verified by C. elegans. We conducted RNA-sequencing and analysis of C. elegans fed with E. coli purE (a single-gene knockout mutant) to further explore the underlying molecular mechanism. We used differential gene expression (DGE) analysis, enrichment analysis, and gene set enrichment analysis (GSEA) to screen vital genes and modules with significant changes in overall expression. Our results suggest that E. coli mutant strains may affect the host lifespan by regulating the protein synthesis rate (cfz-2) and ATP level (catp-4). To conclude, our study could provide new insights into the genetic influences of the microbiota on the life span of a host and a basis for developing anti-aging probiotics and drugs.

[This corrects the article DOI: 10.1371/journal.pone.0241047.].

Qinling-Daba Mountains (QDM), which are located in central China, are considered as a significant climatic boundary delimiting north and south. However, the influence of complex topographic and climatic features makes it challenging to identify the exact location of the boundary, and different scholars delimit the boundary with significant differences. In addition, there is a gradual transition between climate zones, and no real dividing line exists. To explore the climate regionalization of the QDM, we focused on the identification of the transition zone rather than the exact location of the boundary between subtropical and temperate zones. Thus, we proposed a new workflow for climate regionalization based on the Geodetector-SVM model (a combination of Geodetector and support vector machines). First, we selected the spatial distribution data of six vegetation types (including typical subtropical and temperate vegetation) to represent the spatial distribution of climatic zones. Environmental factors (such as topography, temperature, precipitation, and soil) were used as explanatory variables for the spatial distribution of vegetation. Second, using the Geodetector-SVM model, the distribution characteristics and suitable environment of typical vegetation in different climatic zones are comprehensively explored. By analyzing the multiple boundaries between subtropical and temperate vegetation, the location of the transition zone of the QDM was identified. The results revealed the following: (1) The new workflow for climate regionalization based on the Geodetector-SVM model is powerful for the identification of the transition zone. The q-statistics are generally greater than 0.35, indicating that the transition zone between subtropical and temperate zones can highly reflect the character of the QDM; (2) From west to east, the transition zone mainly passes through the cities of Heishui County, Kang County, Liuba County, and Yichuan County and is approximately 30 km wide.

ObjectivesThis study aimed to explore the burden of disease and disparities in age-related macular degeneration (AMD) at the global, regional, and national levels from 1990 to 2019 using data from the Global Burden of Disease (GBD) 2019 study, with a particular focus on associations with age, period, and cohort.MethodsWe derived disability-adjusted life years (DALYs) and age-standardized rates of AMD from the GBD 2019. We used an age-period-cohort (APC) model to estimate the overall annual percentage changes in DALYs (net drifts), the annual percentage changes in different age groups (local drifts), the longitudinal age profiles (longitudinal age-specific rates), and the relative risks of period and cohort (period and cohort effects) between 1990 and 2019. Further analysis was conducted by country, region, gender and sociodemographic index (SDI).ResultsGlobally, the number of DALYs increased from 296771.9321 (95% uncertainty interval [UI], 205462.8041–418699.8184) in 1990 to 564055.0967 (95% UI, 392930.6967–789194.6407) in 2019 (59.7% were female), while the age-standardized DALYs rates decreased from 8.29 per 100,000 (95% UI, 5.8–11.58/100,000) to 7.05 per 100,000 (95% UI, 4.92–9.84/100,000). With increasing age, the burden of AMD increased, and the DALYs rates in female was greater than that in male in all age groups. The burden of disease varied across SDI regions and countries. The top three countries in terms of the number of DALYs were China, India and Italy, accounting for 45% of the global total.ConclusionThe burden of AMD varied according to SDI, country, and sex from 1990 to 2019. Due to global population growth and aging, AMD will continue to be a major public health problem in the future, and relevant health policies need to be continuously improved and optimized.

Purpose: Cerebral ischemia-reperfusion (CIR) injury is a devastating consequence of stroke characterized by oxidative stress-induced neuronal damage. Electroacupuncture (EA) has emerged as a potential therapeutic intervention for ischemic stroke, but its underlying mechanisms remain incompletely understood. This study aimed to elucidate whether EA exerts anti-oxidative stress effects against CIR injury by modulating the GSK-3β/Nrf2 pathway. Methods: CIR mouse models were established using the suture-occluded method and underwent EA pretreatment. Cognitive and neurologic function, cerebral infarct volume, and neuronal damage were assessed in mice. Oxidative stress levels and the expression of components of the GSK-3β/Nrf2 pathway in the cerebral cortex were measured. The regulatory effect of GSK-3β on Nrf2 and its role in electroacupuncture to alleviate oxygen-glucose deprivation/reoxygenation (OGD/R)-induced neuronal injury were investigated by modulating GSK-3β expression in HT22 hippocampal neuronal cells and electroacupuncture serum intervention. Ultimately, Nrf2 knockout mice, GSK-3β knockout mice, and wild-type mice treated with TBHQ (an Nrf2 activator) were utilized for further validation. Results: EA pretreatment improved cognitive impairment and neuronal damage induced by CIR injury. Mechanistically, EA inhibited oxidative stress in the cerebral cortex, manifested by reduced levels of reactive oxygen species and malondialdehyde, along with increased superoxide dismutase activity. Furthermore, EA upregulated the expression of Nrf2 and its downstream antioxidant enzymes HO-1 and NQO1, while Keap1 expression remained unaffected. In vitro, GSK-3β overexpression inhibited the protective effects of EA serum on OGD/R-induced neuronal damage. In vivo, knockout of either Nrf2 or Gsk-3β genes abolished the neuroprotective effects of EA, and TBHQ exerted effects similar to EA, confirming the significant role of GSK-3β/Nrf2 in mediating EA antioxidative effects. Conclusion: EA exerts antioxidative stress effects against CIR injury by activating the GSK-3β/Nrf2 signaling pathway, independent of Keap1 regulation.

BackgroundIn recent years, novel therapies targeting specific molecular pathways and immunotherapies have exhibited promising outcomes for treating human epidermal growth factor receptor 2 (HER2)-positive breast cancer. Our work aimed to assess the effectiveness and safety of these emerging treatment regimens for this disease.Material and methodsWe systematically searched databases including PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials their inception to August 2023 to identify relevant randomized controlled trials (RCTs). The quality of eligible RCTs was evaluated with the Cochrane risk-of-bias tool, version 2 (RoB2). Investigated outcomes encompassed progression-free survival (PFS), overall survival (OS), disease-free survival (DFS), pathologic complete remission (pCR), and adverse events (AEs). They were expressed as hazard ratio (HR) with 95% conference intervals (CI) or risk ratio (RR) with 95% CI.ResultsOur analysis identified a total of 28 RCTs suitable for inclusion in the NMA. Regarding the PFS, all these treatment regimens exhibited comparable effectiveness. In terms of OS, Capecitabine+Trastuzumab, Lapatinib+Trastuzumab and Pyrotinib+Capecitabine exhibited better effect compared to other treatments. Regarding pCR and AEs, all these treatment regimens exhibited comparable effectiveness, especially Lapatinib+Trastuzumab and Pyrotinib+Capecitabine.ConclusionOur study highlights the prominent role of targeted therapies and immunotherapies in treating HER2-positive breast cancer. The efficacy of trastuzumab-containing regimens was superior to other treatment options, while maintaining a comparable safety profile. Based on these findings, trastuzumab-containing regimens emerge as a preferable and recommended choice in clinical practice for managing HER2-positive breast cancer.Systematic Review RegistrationPROSPERO, identifier CRD42023414348.

Affected by climate warming and anthropogenic disturbances, the thermo-mechanical stability of warm and ice-rich frozen ground along the Qinghai–Tibet Railway (QTR) is continuously decreasing, and melting subsidence damage to existing warm frozen soil (WFS) embankments is constantly occurring, thus seriously affecting the stability and safety of the existing WFS embankments. In this study, in order to solve the problems associated with the melting settlement of existing WFS embankments, a novel reinforcement technology for ground improvement, called an inclined soil–cement continuous mixing wall (ISCW), is proposed to reinforce embankments in warm and ice-rich permafrost regions. A numerical simulation of a finite element model was conducted to study the freeze–thaw process and evaluate the stabilization effects of the ISCW on an existing WFS embankment of the QTR. The numerical investigations revealed that the ISCW can efficiently reduce the melt settlement in the existing WFS embankment, as well as increase the bearing capacity of the existing WFS embankment, making it favorable for improving the bearing ability of composite foundations. The present investigation breaks through the traditional ideas of “active cooling” and “passive protection” and provides valuable guidelines for the choice of engineering supporting techniques to stabilize existing WFS embankments along the QTR.

Abstract Metastasis is responsible for the majority of deaths among breast cancer patients. Although parallel polyclonal seeding has been shown to contribute to organ-specific metastasis, in the past decade, horizontal cross-metastatic seeding (metastasis-to-metastasis spreading) has also been demonstrated as a pattern of distant metastasis to multiple sites. Bone, as the most frequent first destination of breast cancer metastasis, has been demonstrated to facilitate the secondary dissemination of breast cancer cells. In this review, we summarize the clinical and experimental evidence that bone is a transfer station for the secondary dissemination of breast cancer. We also discuss the regulatory mechanisms of the bone microenvironment in secondary seeding of breast cancer, focusing on stemness regulation, quiescence-proliferation equilibrium regulation, epigenetic reprogramming and immune escape of cancer cells. Furthermore, we highlight future research perspectives and strategies for preventing secondary dissemination from bone.

In permafrost regions with warm frozen soil, the pile foundation is commonly used, but most currently available models for the WFS foundation pile–soil system are either highly empirical or overcomplicated, without a simplified theoretical manner in engineering. This study derives a novel and simplified calculated model of the WFS pile–soil system. The model is formulated in terms of the shear deformation theory and load transfer method based on the rigorous deformation mechanism of the WFS foundation soil around the pile. Considering the different depth soil features and the equilibrium state of the pile–soil system, dividing warm frozen soil foundation into three regions (TPPR, ER, and BPPR) to calculate the Dp and Ds can simply obtain the total displacement of pile under different loads. The results demonstrate that the present theoretical model can well predict the WFS foundation load–displacement response of the pile. The present model provides a simple, practical, and effective approach for the estimation of the load–displacement behavior of piles installed in the WFS foundation.

The extraction of bayberry tannins has potential to maximize the utilization of a forest waste. This study employed a four-level central composite design through response surface methodology to optimize the extraction of tannin from bayberry barks through ultrasound-assisted extraction (UAE). The effects of solute to solvent ratio (STSR), solvent concentration (SC), extraction time (ET), and sonication temperature (ST) on the total extraction yield of total condensed tannin (TCT yield) and total phenolic content (TPC) were investigated. The extracts were characterized with matrix-assisted laser desorption-time of flight mass spectrometer (MALDI-TOF MS), nuclear magnetic resonance (NMR), and gel permeation chromatography (GPC). The optimized condition was reached when the STSR and ST were set at 1:57.16 g/mL and 71.3%, when the ET and the ST was 39.1 min and 48.75 °C. In these conditions, the TCT yield and TPC reached their maximum values of 17.55% and 365.01 mg GAE/g, respectively. Furthermore, the polyflavonoids of bayberry tannin ranged from dimers to heptamers, which were only composed of proanthocyanidins (PC) containing galloy groups. [ABSTRACT FROM AUTHOR]

Purpose: Results from the LAUNCH trial suggest transarterial chemoembolization (TACE) in combination with lenvatinib is significantly more effective than lenvatinib as a first-line treatment option for advanced hepatocellular carcinoma (HCC). However, the cost of TACE is substantial. This study compares the cost-effectiveness of TACE in combination with lenvatinib (TACE-LEN) with that of lenvatinib alone as the first-line treatment for advanced HCC from the perspective of the Chinese healthcare system.Methods: Markov models of different health states were constructed to simulate first-line treatment, disease progression, and survival in patients with advanced HCC. Clinical efficacy was obtained from the LAUNCH trial. The cost of drugs was sourced from national tender prices, and the treatment cost of weight-decreased was obtained from the Fujian Provincial Bureau of Prices. Other costs and utility values were based on the published literature. Total costs, life years (LYs), quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) comprised the model output. One-way and probabilistic sensitivity analyses were performed to validate model robustness and subgroup analyses were also conducted.Results: Analysis of the model showed that compared to lenvatinib, TACE-LEN improved effectiveness by 1.60 QALYs at a total cost increase of $48,874.69, with an ICER value of $30,482.13/QALY. A one-way sensitivity analysis found that the progression-free survival utility value per year had the greatest impact on the model. A probabilistic sensitivity analysis showed that TACE-LEN had a 97.9% probability of being cost-effective as the first-line treatment option for advanced HCC compared to lenvatinib when the willingness-to-pay (WTP) value was $38,201/QALY (three times the Chinese GDP per capita in 2022). Subgroup analysis showed that all subgroups of patients preferred TACE-LEN. However, when the WTP threshold was below $30,300/QALY, TACE-LEN is no longer cost-effective.Conclusion: Our study found TACE-LEN to be a cost-effective treatment option for patients with advanced HCC compared to lenvatinib from a Chinese healthcare system perspective, but not so in low-income provinces in China.

BackgroundA recent phase III clinical trial (NCT03981796) evaluated the efficacy and safety of dostarlimab combined with carboplatin-paclitaxel (DOS-CP) compared to placebo combined with carboplatin-paclitaxel (PLB-CP) as a first-line treatment for advanced endometrial cancer (EC). The NCT03981796 trial demonstrated that DOS-CP significantly improved progression-free survival and overall survival of patients with advanced EC while maintaining an acceptable safety profile. However, DOS-CP is expensive and its cost-effectiveness has not been evaluated. This study aims to evaluate the cost-effectiveness of DOS-CP compared to PLB-CP as a first-line treatment for advanced EC from the perspective of the Chinese healthcare system.MethodsA Markov model with three health states was developed to evaluate the cost-effectiveness of DOS-CP as a first-line treatment for advanced EC. Clinical efficacy data were derived from the NCT03981796 trial, and drug costs were determined based on national tender prices. Other costs and utility values were obtained from published literature. The outcomes assessed included total costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs). The robustness of the model was assessed through one-way sensitivity analysis and probabilistic sensitivity analysis.ResultsIn comparison to PLB-CP, the ICER of DOS-CP was $98,276.61/QALY for the overall population, $53,063.61/QALY for the dMMR subgroup, and $124,088.56/QALY for the pMMR subgroup. All of these ICER values were higher than the willingness-to-pay threshold of $38,201 per QALY. The most important variable that affected the results of the model was the discount rate, the cost of dostarlimab, and the utility value for progressive disease.ConclusionFrom the perspective of the Chinese healthcare system, DOS-CP is unlikely to be a cost-effective first-line treatment option for advanced EC.

Background: The SPOTLIGHT trial demonstrated that zolbetuximab plus mFOLFOX6 (ZOL-FO) as a first-line regimen compared with placebo plus mFOLFOX6 (PLB-FO) conferred clinical benefits to patients with CLDN18.2-positive, HER2-negative advanced gastric or gastroesophageal junction (G/GEJ) adenocarcinoma. However, due to the high cost of zolbetuximab, whether ZOL-FO is cost-effective compared with PLB-FO is unclear. This study aimed to evaluate the cost-effectiveness of ZOL-FO as a first-line treatment option for CLDN18.2-positive, HER2-negative advanced G/GEJ adenocarcinoma from the perspective of the Chinese healthcare system.Methods: Markov models with three different health states were developed to assess the cost-effectiveness of ZOL-FO as a first-line treatment option for CLDN18.2-positive, HER2-negative advanced G/GEJ adenocarcinoma. Clinical efficacy data were obtained from the SPOTLIGHT trial; the drug’s cost was calculated at national bid prices, and other costs and utility values were obtained from the published literature. Outcomes included total costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs). The model’s robustness was verified using one-way sensitivity and probabilistic sensitivity analyses.Results: The ZOL-FO group gained 1.64 QALYs at $87,746.35, while the PLB-FO group gained 1.23 QALYs at $11,947.81. The ICER for ZOL-FO versus PLB-FO was $185,353.28 per QALY gained. The parameters exerting an important impact on the model results were the price of zolbetuximab, body surface area, and progression-free survival utility. At a willingness-to-pay threshold of $38,201/QALY, ZOL-FO had a 0% probability of cost-effectiveness compared with PLB-FO.Conclusion: From the perspective of the Chinese healthcare system, ZOL-FO is unlikely to be cost-effective as the first-line treatment option for CLDN18.2-positive, HER2-negative advanced G/GEJ adenocarcinoma.

Background: The EMPOWER-LUNG 3 clinical trial has shown that cemiplimab plus chemotherapy (CCT) significantly extended overall survival (OS) and progression-free survival (PFS) for patients with advanced non-small cell cancer (NSCLC) compared to placebo plus chemotherapy (PCT). However, the cost-effectiveness of this new treatment option remains unknown. Thus, we evaluated the cost-effectiveness of CCT versus (vs.) PCT as the first-line treatment for patients with advanced NSCLC from the perspective of the Chinese healthcare system.Methods: We constructed a Markov model to evaluate the cost-effectiveness of CCT as the first-line treatment for patients with advanced NSCLC. The transition probabilities were extracted from the survival data of the EMPOWER-LUNG 3 trial. The drugs’ costs were referred from national tender prices, while other model input parameters were derived from the EMPOWER-LUNG 3 trial and published literature. The outcome parameters mainly included quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs). One-way sensitivity analysis and probabilistic sensitivity analysis were performed to evaluate the robustness of the model outcomes.Results: Compared to PCT, in the CCT regimen, an additional $79,667 was spent in terms of the total cost and with an additional 0.31 QALYs, resulting in an ICER value of $253,148/QALY. Sensitivity analysis indicated that the hazard ratio (HR) of OS, the cost of cemiplimab (100 mg), and the HR of PFS, all significantly impacted the model’s results. The probability of CCT (vs. PCT) being cost-effective was 0% at a willingness-to-pay threshold of $38,201/QALYs in China. The scenario analysis showed that when the price of cemiplimab was reduced to less than $184.09/100 mg, the CCT regimen could be considered cost-effective as the first-line treatment for patients with advanced NSCLC compared to the PCT.Conclusion: In China, the CCT was not cost-effective as the first-line treatment for patients with advanced NSCLC.

Background: Cervical cancer is a common leading cause of cancer related to women death worldwide. Cylindromatosis (CYLD) is known as an important tumor suppressor in various human cancers, and a deubiquitination enzyme (DUB) as well. Previously, we identified Skp2 as an E3 ligase of Aurora B ubiquitination, but the DUB of Aurora B still remains unknown. Methods: Aurora B ubiquitination site is identified through in vivo ubiquitination assay. Activity of Aurora B and CENPA was detected by immunoblotting (IB) and immunofluorescence (IF) assay. Protein-to-protein interaction was investigated by immunoprecipitation (IP). Cell chromosome dynamics was monitored by live-cell time-lapse Imaging. Cancer cell proliferation, colony formation, apoptosis, and cell invasion and migration assays were also performed. Protein level was checked by immunohistochemical (IHC) staining in clinical cervical cancer samples. Results: We identified Lysine 115 (K115) as the main Aurora B ubiquitination site for Skp2. We could also detect an interaction of Aurora B with the DUB CYLD. We found that CYLD promoted deubiquitination of Aurora B, and regulated Aurora B activity and function as well. Compared with control, we found it took more time for the cells to finish cell mitosis with CYLD over-expression. Furthermore, we found that CYLD deficiency promoted cervical cancer cell proliferation, colony formation, cell migration and invasion, and inhibited apoptosis instead, whereas it is just opposite with CYLD over-expression. In clinical cervical cancer samples, we showed a negative correlation of CYLD expression with Aurora B activation and histological cancer cell invasion. Furthermore, there was less CYLD abundance and higher Aurora B activity in advanced cancer samples compared with early stage. Conclusions: Our findings uncover CYLD as a novel potential DUB of Aurora B, which inhibits Aurora B activation and its subsequent function in cell mitosis, and also provide more evidence for its tumor suppressor function in cervical cancer.

BackgroundSintilimab plus chemotherapy (SIDCHM) is more effective than placebo plus chemotherapy (PLCHM) for advanced or metastatic esophageal squamous cell carcinoma (ESCC). However, considering the high cost of sintilimab, this study evaluated the cost-effectiveness of SIDCHM in comparison with PLCHM for advanced or metastatic ESCC from the Chinese healthcare system perspective.MethodsPolymorphic Markov models were constructed to simulate the course and cost of SIDCHM. Treatment drug costs were calculated at national list prices and clinical data, other costs, and utility values were extracted from the reference literature. Primary outcomes included quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs). The robustness of the model was verified by one-way sensitivity analysis and probabilistic sensitivity analysis (PSA).ResultsSIDCHM obtained 1.03 QALYs at $24,044.49, whereas the effectiveness and cost of PLCHM were 0.67 QALYs and $14,166.24, respectively. The ICER for SIDCHM versus PLCHM was $23,458.08/QALY. The utility of the PFS state was the parameter that had the greatest effect on the ICER. The PSA showed that SIDCHM had an 86% probability of being cost-effective at the willingness-to-pay threshold of 3* Chinese gross domestic product per capita ($37,653/QALY).ConclusionFrom the Chinese healthcare system perspective, SIDCHM is considered a cost-effective treatment option compared with PLCHM as first-line therapy for advanced or metastatic ESCC.

Background: The findings of the CAPSTONE-1 trial showed that adebrelimab in combination with chemotherapy (etoposide-carboplatin) (ADCHM) is clinically beneficial as a first-line treatment for patients with extensive-stage small cell lung cancer (ES-SCLC), compared with placebo plus chemotherapy (PLCHM, etoposide-carboplatin). However, owing to the higher cost of adebrelimab, it is unclear whether ADCHM is cost-effective compared with PLCHM. This study aimed to evaluate the cost-effectiveness of ADCHM as a first-line treatment for patients with ES-SCLC from the perspective of the Chinese healthcare system.Methods: A Markov model with three health states was developed to assess the cost-effectiveness of ADCHM as a first-line treatment option with ES-SCLC. Clinical data were obtained from the CAPSTONE-1 trial. Costs of the drug were calculated at national tender prices, and other costs and utility values were obtained from published literature. The outcomes included life years (LYs), quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs). One-way sensitivity analysis and probabilistic sensitivity analysis were used to validate the robustness of the model.Results: The ADCHM group achieved 1.21 QALYs (2.47 LYs) for $25,312, whereas the PLCHM group achieved 0.81 QALYs (1.59 LYs) for $14,846. The ICER for ADCHM versus PLCHM was $25914 per QALY gained. The variables with the greatest impact on the model results were the utility value of progressive disease, the utility value of progression-free survival, and the price of adebrelimab (100 mg). At a willingness-to-pay threshold of $37,653/QALY, ADCHM had an 89.1% probability of being cost-effective compared with PLCHM.Conclusion: ADCHM may be a cost-effective first-line treatment strategy for ES-SCLC from the perspective of the Chinese healthcare system.

Composites with excellent thermomechanical and thermochemical properties are urgently needed in the aerospace field, especially for structural applications under high-temperature conditions. Carbon fiber-reinforced Si-based composites are considered the most promising potential high-temperature materials due to their excellent oxidation resistance and ablative behaviors, good structural designability, and excellent mechanical properties. The reinforcement of the relevant composites mainly involves carbon fiber, which possesses good mechanical and temperature resistance abilities. In this paper, the ablation behaviors and mechanisms of related composites are reviewed. For carbon fiber-reinforced pure Si-based composites (C/SiM composites), the anti-ablation mechanism is mainly attributed to the continuous glassy SiO2, which inhibits the damage of the substrate. For C/SiM composite doping with refractory metal compounds, the oxides of Si and refractory metal together protect the main substrate from ablation and oxidation. Moreover, in addition to thermochemical damage, thermophysical and thermomechanical behavior severely destroy the surface coating of the substrate.

The sustainable development goals (SDGs) reflect the pursuit of achieving spatial justice. Both SDG 1.4 and SDG 11.1 reflect a concern for urban services. Life service resources, which are the new concept proposed by the Chinese government, also call for sustainable development path. However, few studies have focused on the realization of spatial justice in life service resources. This paper proposes a two-level, four-step analysis framework composed of quantity, structure, pattern, and coupling coordination to perceive the spatial justice of life service resources. Based on remote sensing technology and geographic information science, this paper acquires and analyses multi-source data including population density, building outlines, point of interests, subway lines, etc. Furthermore, the case study in downtown Beijing found the following: (1) The total life service resources are extensive and varying in type; (2) regional differences are evident and low-level equilibrium and high-level priority development coexist; (3) life service resources are concentrated in contiguous and multi-centre clusters with a greater north–south than east–west difference; (4) the overall level of life service resources is low, specifically for “high in the centre and low in the periphery” and “high in the east and low in the west”. Future management should consider narrowing the development gap and formulating industry development plans to improve spatial justice. Finally, the comparison between Beijing and London and more cities in the future needs to consider the urban development stage, population density, and other aspects.

The human innate immune response, particularly the type-I interferon (IFN) response, is highly robust and effective first line of defense against virus invasion. IFN molecules are produced and secreted from infected cells upon virus infection and recognition. They then act as signaling/communication molecules to activate an antiviral response in neighboring cells so that those cells become refractory to infection. Previous experimental studies have identified the detailed molecular mechanisms for the IFN signaling and response. However, the principles underlying how host cells use IFN to communicate with each other to collectively and robustly halt an infection is not understood. Here we take a multiplex network modeling approach to provide a theoretical framework to identify key factors that determine the effectiveness of the IFN response against virus infection of a host. In this approach, we consider the virus spread among host cells and the interferon signaling to protect host cells as a competition process on a two-layer multiplex network. We focused on two types of network topology, i.e., the Erdős-Rényi (ER) network and the Geometric Random (GR) network, which represent the scenarios when infection of cells is mostly well mixed (e.g., in the blood) and when infection is spatially segregated (e.g., in tissues), respectively. We show that in general, the IFN response works effectively to stop viral infection when virus infection spreads spatially (a most likely scenario for initial virus infection of a host at the peripheral tissue). Importantly, we show that the effectiveness of the IFN response is robust against large variations in the distance of IFN diffusion as long as IFNs diffuse faster than viruses and they can effectively induce antiviral responses in susceptible host cells. This suggests that the effectiveness of the IFN response is insensitive to the specific arrangement of host cells in peripheral tissues. Thus, our work provides a quantitative explanation of why the IFN response can serve an effective and robust response in different tissue types to a wide range of viral infections of a host.