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The NiCoCrFeAlW eutectic high-entropy alloy exhibits a balanced combination of ductility and strength. This study examines the microstructure evolution and mechanical properties of the Ni30Co30Cr10Fe10Al18W2 alloy at varying growth velocities (10, 20, 50, 100, and 200 μm/s), which in its as-cast state, features a microstructure that includes both coarse dendrites and lamellar eutectic. The structure of the coarse dendrites is characterized by an ordered body-centered cubic (B2) phase, while the lamellar eutectic, features a combination of face-centered cubic (FCC) and ordered B2 phases. The microstructure, characterized by lamellar and dendritic structures that are parallel to the growth direction after directional solidification, undergoes a morphological transition at the solid-liquid interface from a planar to a dendritic form as growth velocity increases. The tensile fracture strength initially increases with the growth velocity, reaching a peak of 1286 MPa at a velocity of 50 μm/s, and then subsequently decreases as the growth velocity continues to increase. Directional solidification results in an increase in sample elongation with increasing growth velocity, achieving an elongation of 22.5% at 200 μm/s. An examination of the deformation mechanism reveals that the lamellar structure, composed of the more ductile FCC phase and the harder B2 phase, effectively harmonizes the plasticity and strength of the alloy. Therefore, directional solidification significantly adjusts the eutectic microstructure's orientation, thereby enhancing the mechanical properties along the direction of solidification.

Abstract Background Concurrent chemoradiotherapy (CCRT) is a crucial treatment for non-small cell lung carcinoma (NSCLC). However, the use of deep learning (DL) models for predicting the response to CCRT in NSCLC remains unexplored. Therefore, we constructed a DL model for estimating the response to CCRT in NSCLC and explored the associated biological signaling pathways. Methods Overall, 229 patients with NSCLC were recruited from six hospitals. Based on contrast-enhanced computed tomography (CT) images, a three-dimensional ResNet50 algorithm was used to develop a model and validate the performance in predicting response and prognosis. An associated analysis was conducted on CT image visualization, RNA sequencing, and single-cell sequencing. Results The DL model exhibited favorable predictive performance, with an area under the curve of 0.86 (95% confidence interval [CI] 0.79–0·92) in the training cohort and 0.84 (95% CI 0.75–0.94) in the validation cohort. The DL model (low score vs. high score) was an independent predictive factor; it was significantly associated with progression-free survival and overall survival in both the training (hazard ratio [HR] = 0.54 [0.36−0.80], P = 0.002; 0.44 [0.28−0.68], P

Abstract As an emerging multi‐energy consumption subject, data centres (DCs) are bound to become crucial energy users for integrated energy systems (IES). Therefore, how to fully tap the potential of the collaborative operation between DCs and IES to improve total energy efficiency and economic performance is becoming a pressing need. In this article, the authors research an optimization coordinated by the energy scheduling and information service provision within the scenario of an integrated energy system with a data centre (IES‐DC). The mathematical model of IES‐DC is first established to reveal the energy conversion process of the electricity‐heat‐gas IES and the DC's energy consumption affected by the scale of active IT equipment. For dynamical providing multi‐energy and computing service by coordinating scheduling energy and information equipment, the formulations of IES‐DC scheduling, which is described as a Markov decision process (MDP), are presented, and it is solved by introducing the twin‐delayed deep deterministic policy gradient (TD3), which is a model‐free deep reinforcement learning (DRL) algorithm. Finally, the numerical studies show that compared with benchmarks, the proposed method based on the TD3 algorithm can effectively control the operation of energy conversion equipment and the number of active servers in IES‐DC.

Abstract Efficient semantic segmentation of large-scale point cloud scenes is a fundamental and essential task for perception or understanding the surrounding 3d environments. However, due to the vast amount of point cloud data, it is always a challenging to train deep neural networks efficiently and also difficult to establish a unified model to represent different shapes effectively due to their variety and occlusions of scene objects. Taking scene super-patch as data representation and guided by its contextual information, we propose a novel multiscale super-patch transformer network (MSSPTNet) for point cloud segmentation, which consists of a multiscale super-patch local aggregation (MSSPLA) module and a super-patch transformer (SPT) module. Given large-scale point cloud data as input, a dynamic region-growing algorithm is first adopted to extract scene super-patches from the sampling points with consistent geometric features. Then, the MSSPLA module aggregates local features and their contextual information of adjacent super-patches at different scales. Owing to the self-attention mechanism, the SPT module exploits the similarity among scene super-patches in high-level feature space. By combining these two modules, our MSSPTNet can effectively learn both local and global features from the input point clouds. Finally, the interpolating upsampling and multi-layer perceptrons are exploited to generate semantic labels for the original point cloud data. Experimental results on the public S3DIS dataset demonstrate its efficiency of the proposed network for segmenting large-scale point cloud scenes, especially for those indoor scenes with a large number of repetitive structures, i.e., the network training of our MSSPTNet is much faster than other segmentation networks by a factor of tens to hundreds.

Nairobi Sheep Disease (NSD) is a typical tick-borne syndrome characterized by severe hemorrhagic gastroenteritis, spontaneous abortion, and a high case fatality rate in small ruminants. The pathogenic agent, Nairobi sheep disease virus (NSDV), has also been associated with human infections, indicating its possible zoonotic potential. Prior to this study, NSDV has been detected from ticks collected in Jilin, Hubei, and Liaoning provinces in China. In the present study, a total of 343 ticks (Haemaphysalis longicornis) were collected in Shandong province, China in 2020, and pooled into 16 libraries. Analysis of the meta-transcriptomic sequencing data identified NSDV strains SDWL07, SDWL08, and SDWL16 from three pools. The SDWL07 and SDWL16 strains were detected from unfed ticks, while SDWL08 was detected from cattle-feeding ticks. Phylogenetic analyses showed higher sequence identities between the three strains and other Chinese NSDV strains than those from India and Kenya. Phylogenetic analyses also revealed that they clustered together and fell within the China lineage, suggesting no potential genetic reassortment among them. In summary, this is the first report of the identification of NSDV in Shandong province, highlighting the continually expanding endemic regions of this pathogen. Surveillance of NSDV should be intensified in China, especially in areas where H. longicornis is endemic.

ObjectiveTo analyze the clinical prognostic factors and treatments for angioimmunoblastic T-cell lymphoma (AITL) and develop a novel prognostic model specifically for AITL.MethodWe retrospectively analyzed 231 patients with AITL from the First Affiliated Hospital of Zhengzhou University. Patients were enrolled between January 2014 and July 2023. The primary end points were overall survival (OS) and progression-free survival (PFS).ResultThe patients’ median age was 63 years, with 88.3% at an advanced stage (III/IV). The majority of patients (47.6%) received anthracycline-containing regimens, and there was no significant difference in survival compared with those treated with epigenetic-targeting and gemcitabine- containing regimens. The median PFS and OS were 6 and 17 months, respectively. In multivariate analysis, age >60 years, Eastern Cooperative Oncology Group performance status ≥2, elevated LDH, and splenomegaly were associated with inferior OS. Based on these four factors, a novel prognostic model (AITL model) was constructed that stratified patients into low‐, intermediate‐, and high‐risk groups, with 2-year OS estimates of 63.6%, 42.1%, and 18.6%, respectively.ConclusionCurrently, there is no consensus on the optimal initial therapy for AITL, and the efficacy of anthracycline-containing regimens remains suboptimal. The novel model developed herein demonstrates predictive significance for both OS and PFS, and exhibits better stratification and discrimination capabilities.

Exercise-induced anaphylaxis (EIA) is a rare and potentially life-threatening disorder. In difficult to control and refractory cases of EIA, biologics such as omalizumab and dupilumab have shown promise, with documented successful outcomes. Here, we present a case of EIA with lipid transfer protein (LTP) sensitization successfully treated with omalizumab with long-term follow-up. A 12-year-old girl presented to our allergy department because of recurrent episodes of EIA, with no specific food ingestion before exercise. Allergen testing revealed sensitization to weed pollens, particularly mugwort (76.1 kUA/L) and Alternaria alternata (10.8 kUA/L). Allergen component testing indicated sensitization to LTP components from mugwort Art v 3 (49.9 kUA/L), wheat Tri a 14 (2.03 kUA/L), and peach Pru p 3 (11.5 kUA/L), with a negative result for omega-5 gliadin. Despite initial prophylactic treatment with budesonide–formoterol (80/4.5 μg) and cetirizine (10 mg) before exercise, the patient still experienced EIA; she was then recommended for dupilumab therapy (an initial dose of 600 mg, followed by 300 mg every 2 weeks for six doses). However, even while undergoing dupilumab therapy, she suffered two anaphylactic episodes after running 800–1,000 m. With the patient's consent, a trial of omalizumab was initiated (injections of 300 mg every 4 weeks). After 2 months of omalizumab therapy, the patient showed significant improvement. She had been engaging in physical exercise three times a week and experienced a mild episode of urticaria. There were no further episodes of anaphylaxis or emergency room visits. By the fourth month of omalizumab treatment, she was able to consume food normally even just before exercising and had returned to her full activity level without any restrictions. This case presents the first successful off-label use of omalizumab in the prevention of EIA in the Chinese population. It is concluded that omalizumab may be helpful in resolving EIA symptoms, as evidenced by this case of successful long-term use.

Abstract Purpose This study aimed to identify ultrasound and clinicopathological characteristics related to recurrence in HER2‐positive (HER2+) breast cancer, and to develop nomograms for predicting recurrence. Methods In this dual‐center study, we retrospectively enrolled 570 patients with HER2+ breast cancer. The ultrasound and clinicopathological characteristics of hormone receptor (HR)−/HER2+ patients and HR+/HER2+ patients were analyzed separately according to HR status. Eighty percent of the original samples from HR−/HER2+ and HR+/HER2+ patients were extracted by bootstrap sampling as the training cohorts, while the remaining 20% were used as the external validation cohorts. Informative characteristics were screened through univariate and multivariable Cox regression in the training cohorts and used to develop nomograms for predicting recurrence. The predictive accuracy was calculated using Harrell's C‐index and calibration curves. Results Three informative characteristics (axillary nodal status, calcification, and Adler degree) were identified in HR−/HER2+ patients, and another three (histological grade, axillary nodal status, and echogenic halo) in HR+/HER2+ patients. Based on these, two separate nomograms were constructed to assess recurrence risk. In the training cohorts, the C‐index was 0.740 (95% CI: 0.667–0.811) for HR−/HER2+ nomogram, and 0.749 (95% CI: 0.679–0.820) for HR+/HER2+ nomogram. In the validation cohorts, the C‐index was 0.708 (95% CI: 0.540–0.877) for HR−/HER2+ group, and 0.705 (95% CI: 0.557–0.853) for HR+/HER2+ group. The calibration curves also indicated the excellent accuracy of the nomograms. Conclusions Ultrasound performance of HER2+ breast cancers with different HR status was significantly different. Nomograms integrating ultrasound and clinicopathological characteristics exhibited favorable performance and have the potential to serve as a reliable method for predicting recurrence in heterogeneous breast cancer.

IntroductionLow ground temperature is a major factor limiting overwintering in cucumber cultivation facilities in northern alpine regions. Lower temperatures in the root zone directly affect the physiological function of the root system, which in turn affects the normal physiological activity of plants. However, the importance of the ground temperature in facilities has not attracted sufficient attention. MethodsTherefore, this study tested the cucumber variety Jinyou 35 under three root zone temperatures (room temperature, 20–22°C; suboptimal temperature, 13– 15°C; and low temperature, 8–10°C) to investigated possible cold resistance mechanisms in the root of cucumber seedlings through hormone, metabolomics, and transcriptomics analyses.Results and discussionThe results showed that cucumber roots were subjected to chilling stress at different temperatures. Hormone analysis indicated that auxin content was highest in the roots. Jasmonic acid and strigolactone participated in the low-temperature stress response. Auxin and jasmonate are key hormones that regulate the response of cucumber roots to low temperatures. Phenolic acid was the most abundant metabolite in cucumber roots under chilling stress. Additionally, triterpenes may play an important role in chilling resistance. Differentially expressed genes and metabolites were significantly enriched in benzoxazinoid biosynthesis in the room temperature vs. suboptimal temperature groups and the room temperature vs. low temperature groups. Most differentially expressed transcription factor genes in AP2/ERF were strongly induced in cucumber roots by both suboptimal and low-temperature stress conditions. These results provide guidance for the cultivation of cucumber in facilities.

Despite the associations of dietary patterns and air pollution with human reproductive health have been demonstrated, the interaction of maternal preconception diet and PM2.5 and its components exposure on in vitro fertilization (IVF) treatment outcomes has not been investigated. A total of 2688 couples from an ongoing prospective cohort were included. Principle component analysis with varimax rotation was performed to determine dietary patterns. One-year and 85-day average PM2.5 and its components exposure levels before oocyte retrieval were estimated. Generalized linear regression models were conducted to assess the association of dietary patterns and PM2.5 and its components exposure with IVF outcomes. Interactive effects of dietary patterns on the association between PM2.5 and its components and IVF outcomes were evaluated by stratified analyses based on different dietary patterns. A positive association between the “Fruits-Vegetables-Dairy” pattern and normal fertilization (p-trend = 0.009), Day 3 available embryos (p-trend = 0.048), and top-quality embryos (p-trend = 0.041) was detected. Conversely, women with higher adherence to the “Puffed food-Bakery-Candy” pattern were less likely to achieve Day 3 available embryos (p-trend = 0.042) and top-quality embryos (p-trend = 0.030), clinical pregnancy (p-trend = 0.049), and live birth (p-trend = 0.020). Additionally, increased intake of animal organs and seafood improved the odds of live birth (p-trend = 0.048). Exposure to PM2.5, SO42-, organic matter (OM), and black carbon (BC) had adverse effects on embryo development and pregnancy outcomes. Furthermore, our findings indicated that the effects of PM2.5 components exposure on normal fertilization and embryo quality were modified by the “Grains-Tubers-Legumes”. Moreover, moderate intake of animal organs and seafood appeared to attenuate the effect of NO3- and NH4+ on the risk of early abortion. Our findings provide human evidence of the interaction between dietary patterns and PM2.5 exposure on IVF outcomes during preconception, implicating the potential for dietary interventions in infertile women to improve reproductive outcomes under conditions of unavoidable ambient air-pollutant exposure.

Invasive Emerald Ash Borer (EAB) damage pose significant challenges for sustainable forest management, necessitating accurate mapping of damaged ash trees. Traditional change detection methods, using time-series imagery, are essential for monitoring forest disturbances but complicated by abnormal fluctuations in original time-series features. Tree phenology also complicates this process by masking the reflectance characteristics indicative of EAB infestation. To address these challenges, we propose an improved change detection method integrating patterns from host tree phenology and EAB life history. This improved method includes: (1) select the indices with time stability to enhance detection reliability by partial least squares method (PLS); (2) correction on negative change values before and positive change values after the phenological peak based on known patterns of tree phenology and EAB life history. Result confirms that this method effectively reflects the seasonal growth and decline dynamics of ash trees, revealing the impacts of phenology and EAB infestation. EAB-damaged trees exhibited slower growth in May and premature decline in July compared with healthy tree, with the damage severity influencing the rate of leaf decline. This proposed method achieved an overall accuracy of 53.4%-76.7% across different months for ash trees with health, light and severe damage. This study highlights the capabilities of integrating pest life history and phenology in change detection method and provide a new method to monitor individual tree health across large areas by high-resolution satellite imagery.

Abstract Cancer immunotherapy has rapidly transformed cancer treatment, yet resistance remains a significant hurdle, limiting its efficacy in many patients. Circular RNAs (circRNAs), a novel class of non-coding RNAs, have emerged as pivotal regulators of gene expression and cellular processes. Increasing evidence indicates their involvement in modulating resistance to cancer immunotherapy. Notably, certain circRNAs function as miRNA sponges or interact with proteins, influencing the expression of immune-related genes, including crucial immune checkpoint molecules. This, in turn, shapes the tumor microenvironment and significantly impacts the response to immunotherapy. In this comprehensive review, we explore the evolving role of circRNAs in orchestrating resistance to cancer immunotherapy, with a specific focus on their mechanisms in influencing immune checkpoint gene expression. Additionally, we underscore the potential of circRNAs as promising therapeutic targets to augment the effectiveness of cancer immunotherapy. Understanding the role of circRNAs in cancer immunotherapy resistance could contribute to the development of new therapeutic strategies to overcome resistance and improve patient outcomes.

Repetitive implant-related infections (IRIs) are devastating complications in orthopedic surgery, threatening implant survival and even the life of the host. Biofilms conceal bacterial-associated antigens (BAAs) and result in a ''cold tumor''-like immune silent microenvironment, allowing the persistence of IRIs. To address this challenge, an iron-based covalent organic framed nanoadjuvant doped with curcumin and platinum (CFCP) was designed in the present study to achieve efficient treatment of IRIs by inducing a systemic immune response. Specifically, enhanced sonodynamic therapy (SDT) from CFCP combined with iron ion metabolic interference increased the release of bacterial-associated double-stranded DNA (dsDNA). Immunogenic dsDNA promoted dendritic cell (DC) maturation through activation of the stimulator of interferon gene (STING) and amplified the immune stimulation of neutrophils via interferon-β (IFN-β). At the same time, enhanced BAA presentation aroused humoral immunity in B and T cells, creating long-term resistance to repetitive infections. Encouragingly, CFCP served as neoadjuvant immunotherapy for sustained antibacterial protection on implants and was expected to guide clinical IRI treatment and relapse prevention.

Abstract Cancer therapeutic resistance remains a significant challenge in the pursuit of effective treatment strategies. Circular RNAs (circRNAs), a class of non-coding RNAs, have recently emerged as key regulators of various biological processes, including cancer progression and drug resistance. This review highlights the emerging role of circRNAs-mediated autophagy in cancer therapeutic resistance, a cellular process that plays a dual role in cancer by promoting both cell survival and death. Increasing evidence suggests that circRNAs can modulate autophagy pathways, thereby influencing the response of cancer cells to therapeutic agents. In this context, the intricate interplay between circRNAs, autophagy, and therapeutic resistance is explored. Various mechanisms are discussed through which circRNAs can impact autophagy, including direct interactions with autophagy-related genes, modulation of signaling pathways, and cross-talk with other non-coding RNAs. Furthermore, the review delves into specific examples of how circRNA-mediated autophagy regulation can contribute to resistance against chemotherapy and radiotherapy. Understanding these intricate molecular interactions provides valuable insights into potential strategies for overcoming therapeutic resistance in cancer. Exploiting circRNAs as therapeutic targets or utilizing them as diagnostic and predictive biomarkers opens new avenues for developing personalized treatment approaches. In summary, this review underscores the importance of circRNA-mediated autophagy in cancer therapeutic resistance and proposes future directions for research in this exciting and rapidly evolving field.

Lithium-ion capacitors (LICs) combining the advantages of lithium-ion batteries and supercapacitors are considered a promising next-generation energy storage device. However, the sluggish kinetics of battery-type anode cannot match the capacitor-type cathode, restricting the development of LICs. Herein, hierarchical carbon framework (HCF) anode material composed of 0D carbon nanocage bridged with 2D graphene network are developed via a template-confined synthesis process. The HCF with nanocage structure reduces the Li+ transport path and benefits the rapid Li+ migration, while 2D graphene network can promote the electron interconnecting of carbon nanocages. In addition, the doped N atoms in HCF facilitate to the adsorption of ions and enhance the pseudo contribution, thus accelerate the kinetics of the anode. The HCF anode delivers high specific capacity, remarkable rate capability. The LIC pouch-cell based on HCF anode and active HCF (a-HCF) cathode can provide a high energy density of 162 Wh kg−1 and a superior power density of 15.8 kW kg−1, as well as a long cycling life exceeding 15,000 cycles. This study demonstrates that the well-defined design of hierarchical carbon framework by incorporating 0D carbon nanocages and 2D graphene network is an effective strategy to promote LIC anode kinetics and hence boost the LIC electrochemical performance.

BackgroundSystemic immune-inflammation index (SII) is associated with increased risk in a wide range of illnesses. However, few studies have explored the associations between SII and the risk of malnutrition. Therefore, this study aimed to investigate the association between SII and malnutrition in a nationwide, multicenter, cross-sectional study involving Chinese hospitalized patients.DesignFrom August 2020 to August 2021, a total of 40,379 hospitalized patients met the inclusion and exclusion criteria. Detailed demographic data, diagnoses, as well as physical and laboratory examination results were recorded. The diagnosis of malnutrition was used with two distinct methods: the Malnutrition Screening Tool 2002 (NRS 2002) + Global Leaders Initiative on Malnutrition (GLIM) criteria and the controlling nutritional status (CONUT) score. The risk factors for malnutrition were analyzed using binary logistic regression and multiple logistic regression to obtain odds ratios (OR) and 95% confidence intervals (CI). Restricted cubic spline (RCS), linear spline, and receiver operating characteristic (ROC) analysis were also used.ResultsThe prevalence of malnutrition diagnosed by the two methods was 13.4% and 14.9%, respectively. In the NRS 2002 + GLIM diagnostic model, lnSII showed statistical significance between the malnutrition and non-malnutrition group (6.28 ± 0.78 vs. 6.63 ± 0.97, p

Lymphoma is a highly heterogeneous lymphohematopoietic tumor. As our understanding of the biological and pathological characteristics of lymphoma improves, we are identifying an increasing number of lymphoma subtypes. Genotyping has enhanced our ability to diagnose, treat, and monitor the prognosis of lymphoma. Despite significant improvements in treatment effectiveness, traditional methods for assessing disease response and monitoring prognosis are imperfect, and there is no significant improvement in overall remission rates for lymphoma patients. Minimal Residual Disease (MRD) is often indicative of refractory disease or early relapse. For lymphoma patients, personalized MRD monitoring techniques offer an efficient means to estimate disease remission levels, predict early relapse risk, and assess the effectiveness of new drug regimens. In this review, we delve into the MRD procedures in lymphoma, including sample selection and requirements, detection methods and their limitations and advantages, result interpretation. Besides, we also introduce the clinical applications of MRD detection in lymphoma.

To ensure the safe operation and dispatching control of a low-voltage distributed photovoltaic (PV) power distribution network (PDN), the load forecasting problem of the PDN is studied in this study. Based on deep learning technology, this paper proposes a robot-assisted load forecasting method for low-voltage distributed photovoltaic power distribution networks using enhanced long short-term memory (LSTM). This method employs the frequency domain decomposition (FDD) to obtain boundary points and incorporates a dense layer following the LSTM layer to better extract data features. The LSTM is used to predict low-frequency and high-frequency components separately, enabling the model to precisely capture the voltage variation patterns across different frequency components, thereby achieving high-precision voltage prediction. By verifying the historical operation data set of a low-voltage distributed PV-PDN in Guangdong Province, experimental results demonstrate that the proposed “FDD+LSTM” model outperforms both recurrent neural network and support vector machine models in terms of prediction accuracy on both time scales of 1 h and 4 h. Precisely forecast the voltage in different seasons and time scales, which has a certain value in promoting the development of the PDN and related technology industry chain.

The incidence of breast cancer is increasing annually, making it a major health threat for women. Chemoprevention using natural, dietary, or synthetic products has emerged as a promising approach to address this growing burden. Atractylenolide-III (AT-III), a sesquiterpenoid present in various medicinal herbs, has demonstrated potential therapeutic effects against several diseases, including tumors, nonalcoholic fatty liver disease, and cerebral ischemic injury. However, its impact on breast cancer chemoprevention remains unexplored. In this study, we used an N-methyl-N-nitrosourea (NMU)-induced rat breast cancer model and 17β-estradiol (E2)-treated MCF-10A cells to evaluate the chemopreventive potential of AT-III on mammary tumorigenesis. AT-III inhibited mammary tumor progression, evidenced by reduced tumor volume and multiplicity, prolonged tumor latency, and the reversal of NMU-induced weight loss. Furthermore, AT-III suppressed NMU-induced inflammation and oxidative stress through the Nrf2/ARE pathway in breast cancer tissues. In vitro, AT-III effectively suppressed E2-induced anchorage-independent growth and cell migration in MCF-10A cells. Nrf2 knockdown attenuated the protective effects of AT-III, highlighting the pivotal role of Nrf2 in AT-III-mediated suppression of tumorigenesis. The mechanism involves the induction of Nrf2 expression by AT-III through the autophagic degradation of Kelch-like ECH-associated protein 1 (Keap1). Overall, the results of this study indicate that AT-III is a promising candidate for breast cancer chemoprevention and provide valuable insights into its molecular interactions and signaling pathways.

The limited expansion ability and functional inactivation of T cells within the solid tumor microenvironment are major problems faced during in the application of using tumor-infiltrating lymphocytes (TILs) in vivo. We sought to determine whether TILs carrying a PD-1-CD28-enhanced receptor and CD19 CAR could overcome this limitation and mediate tumor regression. First, anti-tumor effects of PD-1-CD28-enhanced receptor or CD19 CAR modified NY-ESO-1-TCR-T cells to mimic the TILs function (hereafter “PD-1-CD28-TCR-T” or “CD19 CAR-TCR-T” cells, respectively) were tested using the NY-ESO-1 over-expressed tumor cell line in vitro and in a tumor-bearing model. Furthermore, the safety and anti-tumor ability of S-TILs (TILs modified through transduction with a plasmid encoding the PD-1-CD28-T2A-CD19 CAR) were evaluated in vivo. PD-1-CD28-TCR-T cells showed a formidable anti-tumor ability that was not subject to PD-1/PD-L1 signaling in vivo. CD19 CAR-TCR-T cells stimulated with CD19+ B cells exhibited powerful expansion and anti-tumor abilities both in vitro and in vivo. Three patients with refractory solid tumors received S-TILs infusion. No treatment-related mortality was observed, and none of the patients experienced serious side effects. One patient with melanoma achieved a partial response, and two patients with colon or kidney cancer achieved long-term stable disease following S-TILs therapy. To the best of our knowledge, this is the first study describing the safety and efficacy of the adoptive transfer of autologous S-TILs to control disease in patients with advanced cancers, suggesting that S-TILs may be a promising alternative therapy for cancer.

Immune checkpoint blockade (ICB) therapy potently revives T cell's response to cancer. However, patients suffered with tumors that had inadequate infiltrated immune cells only receive limited therapeutic benefits from ICB therapy. Synthetic biology promotes the alternative strategy of harnessing tumor-targeting bacteria to synthesize therapeutics to modulate immunity in situ. Herein, we engineered attenuated Salmonella typhimurium VNP20009 with gene circuits to synthetize granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin 7 (IL-7) within tumors, which recruited dendritic cells (DCs) and enhanced T cell priming to elicit anti-tumor response. The bacteria-produced GM-CSF stimulated the maturation of bone marrow-derived dendritic cells (BMDCs), while IL-7 promoted the proliferation of spleen isolated T cells and inhibited cytotoxicity T cell apoptosis in vitro. Virtually, engineered VNP20009 prefer to colonize in tumors, and inhibited tumor growth by enhancing DCs and T cell infiltration. Moreover, the tumor-toxic GZMB+ CD8+ T cell and IFN-γ+ CD8+ T cell populations conspicuously increased with the treatment of engineered bacteria. The combination of GM–CSF–IL-7-VNP20009 with PD-1 antibody synergistically stunted the tumor progress and metastasis.

Abstract Point cloud completion, the issue of estimating the complete geometry of objects from partially-scanned point cloud data, becomes a fundamental task in many 3d vision and robotics applications. To address the limitations on inadequate prediction of shape details for traditional methods, a novel coarse-to-fine point completion network (DCSE-PCN) is introduced in this work using the modules of local details compensation and shape structure enhancement for effective geometric learning. The coarse completion stage of our network consists of two branches—a shape structure recovery branch and a local details compensation branch, which can recover the overall shape of the underlying model and the shape details of incomplete point cloud through feature learning and hierarchical feature fusion. The fine completion stage of our network employs the structure enhancement module to reinforce the correlated shape structures of the coarse repaired shape (such as regular arrangement or symmetry), thus obtaining the completed geometric shape with finer-grained details. Extensive experimental results on ShapeNet dataset and ModelNet dataset validate the effectiveness of our completion network, which can recover the shape details of the underlying point cloud whilst maintaining its overall shape. Compared to the existing methods, our coarse-to-fine completion network has shown its competitive performance on both chamfer distance (CD) and earth mover distance (EMD) errors. Such as, the repairing results on the ShapeNet dataset of our completion network are reduced by an average of $$35.62\%$$ 35.62 % , $$33.31\%$$ 33.31 % , $$29.62\%$$ 29.62 % , and $$23.62\%$$ 23.62 % in terms of CD error, comparing with PCN, FoldingNet, Atlas, and CRN methods, respectively; and also reduced by an average of $$15.63\%$$ 15.63 % , $$1.29\%$$ 1.29 % , $$64.52\%$$ 64.52 % , and $$62.87\%$$ 62.87 % in terms of EMD error, respectively. Meanwhile, the completion results on the ModelNet dataset of our network have an average reduction of $$28.41\%$$ 28.41 % , $$26.57\%$$ 26.57 % , $$20.65\%$$ 20.65 % , and $$18.55\%$$ 18.55 % in terms of CD error, comparing to PCN, FoldingNet, Atlas, and CRN methods, respectively; and also an average reduction of $$21.91\%$$ 21.91 % , $$19.59\%$$ 19.59 % , $$43.51\%$$ 43.51 % , and $$21.49\%$$ 21.49 % in terms of EMD error, respectively. Our proposed point completion network is also robust to different degrees of data incompleteness and model noise.

Abstract Intrauterine adhesion (IUA) is characterized by endometrial fibrosis. S100A8/A9 plays an important role in inflammation and fibroblast activation. However, the role of S100A8/A9 in IUA remains unclear. In this study, we collect normal and IUA endometrium to verify the expression of S100A8/A9. Human endometrial stromal cells (hEnSCs) are isolated to evaluate fibrosis progression after S100A8/A9 treatment. A porcine IUA model is established by electrocautery injury to confirm the therapeutic effect of menstrual blood-derived stromal cells (MenSCs) on IUA. Our study reveals increased S100A8/A9 expression in IUA endometrium. S100A8/A9 significantly enhances hEnSCs proliferation and upregulates fibrosis-related and inflammation-associated markers. Furthermore, S100A8/A9 induces hEnSCs fibrosis through the RAGE-JAK2-STAT3 pathway. Transplantation of MenSCs in a porcine IUA model notably enhances angiogenesis, mitigates endometrial fibrosis and downregulates S100A8/A9 expression. In summary, S100A8/A9 induces hEnSCs fibrosis via the RAGE-JAK2-STAT3 pathway, and MenSCs exhibit marked effects on endometrial restoration in the porcine IUA model.

Abstract Background Identifying precise biomarkers of immunotherapy response for non-small cell lung carcinoma (NSCLC) before treatment is challenging. This study aimed to construct and investigate the potential performance of a sub-regional radiomics model (SRRM) as a novel tumor biomarker in predicting the response of patients with NSCLC treated with immune checkpoint inhibitors, and test whether its predictive performance is superior to that of conventional radiomics, tumor mutational burden (TMB) score and programmed death ligand-1 (PD-L1) expression. Methods We categorized 264 patients from retrospective databases of two centers into training (n = 159) and validation (n = 105) cohorts. Radiomic features were extracted from three sub-regions of the tumor region of interest using the K-means method. We extracted 1,896 features from each sub-region, resulting in 5688 features per sample. The least absolute shrinkage and selection operator regression method was used to select sub-regional radiomic features. The SRRM was constructed and validated using the support vector machine algorithm. We used next-generation sequencing to classify patients from the two cohorts into high TMB (≥ 10 muts/Mb) and low TMB (

Motion planning algorithms for unmanned tracked vehicles (UTV) which travel on off-road terrain often suffer from low accuracy and poor robustness when confronted with track sliding factor. SSTP-RRT (Slope-Steering Trajectory Parameter-space Rapidly-exploring Random Tree) motion planning algorithm is proposed for the slope-steering motion planning of UTV while considering the track sliding factor. A modified tracked vehicle slope-steering mechanical model is established to describe the process of UTV steering on the slope. The proposed UTV slope-steering model considers combined horizontal and vertical track sliding as well as steering centrifugal force. The PSO-LM (Particle Swarm Optimization - Levenberg Marquardt) algorithm is proposed to solve how to choose the initial values for the solution of the nonlinear system of equations of the model. The vehicle velocity, steering radii, and heading angle are taken as the independent variables, and the output rotational velocities of the inner and outer sprockets are taken as the dependent variables. The data are generated in a pre-computed way, and the output can be acquired by the point cloud surface fitting method based on moving least squares. By this method, UTV can travel according to the planned trajectory on the slope precisely and duly.

Abstract Accurately forecasting regional distributed photovoltaic (DPV) power is crucial in mitigating the negative impact of high DPV penetration on the reliability and resilience of the distribution network. However, most of the current photovoltaic power forecasting methods suffer from two key problems: (1) ignoring the asymmetric influence relationship among DPV sites; (2) lack of consideration of dynamic spatiotemporal correlation among DPV sites. As a result, these methods are unable to fully adapt to the characteristics of DPV, making it challenging to directly apply the existing forecasting methods to improve the accuracy of DPV power forecasting. To conquer this limitation, a dynamic directed Graph Convolution Neural Network (DDGCN) is applied to regional DPV ultra‐short‐term power forecasting. Unlike the conventional Graph Convolution Neural Network (GCN) based forecasting methods, the proposed method improves GCN to process the directed graph. On this basis, to capture the dynamic and directed adjacency relationship among graph nodes, a temporal attention mechanism is proposed and combined with the directed GCN model. In this way, the dynamic and asymmetric/directed relationships among DPV sites can be taken into account. It is worth noting that the DPVs’ adjacency relationship can be constructed without any prior knowledge by end‐to‐end model training. The simulation experiment proves that the prediction accuracy can be further improved by taking into account the dynamic directed relationship among the sites via a real DPV power dataset.

Purpose: Male overweight and obesity could affect sperm quality and reproductive health. However, the impact of body mass index (BMI) on assisted reproductive technology (ART) outcomes in oligospermia and/or asthenospermia patients is yet lacking. This study aims to assess the impact of paternal BMI on ART and neonatal outcomes among oligozoospermia and/or asthenospermia patients undergoing in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI). Materials and Methods: In this study, 2,075 couples undergoing their first fresh embryo transfer between January 2015 and June 2022 were recruited. Following the World Health Organization’s (WHO’s) categories, couples were stratified into three cohorts based on paternal BMI: normal weight (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2), and obese (≥30.0 kg/m2). Modified Poisson regression models were used to assess the associations of paternal BMI with fertilization, in vitro embryonic development, and pregnancy outcomes. Logistic regression models were performed to investigate the associations of paternal BMI with pregnancy loss and neonatal outcomes. Furthermore, stratified analyses were performed based on fertilization methods, male infertility cause, and maternal BMI. Results: Higher paternal BMI is associated with a lower likelihood of achieving normal fertilized (p-trend=0.002), Day 3 transferable (p-trend=0.007), and high-quality embryos (p-trend=0.046) in IVF cycles, rather than in ICSI cycles. Paternal BMI of oligospermia or asthenospermia was negatively correlated with day 3 transferable (p-trend=0.013 and 0.030) and highquality embryos (p-trend=0.024 and 0.027). Moreover, for neonatal outcomes, paternal BMI was positively associated with macrosomia (p-trend=0.019), large for gestational age (LGA) (p-trend=0.031), and very LGA (p-trend=0.045). Conclusions: Our data suggested that higher paternal BMI was associated with fetal overgrowth, reduced fertilization, and embryonic development potential. Among males with oligospermia and/or asthenospermia, the impact of overweight and obesity on the choice of fertilization method and the long-term effects on their offspring need to be further investigated.

Abstract Background Brentuximab vedotin (BV) was approved as a therapy for patients with CD30‐positive lymphoma in China in 2020 based on the results of multiple clinical trails. Few Chinese real‐world data of its use are yet available. Herein, we present the application situation of BV in patients with lymphoma among different hospitals in Henan province in China under real‐world conditions. Methods This was a multicenter and retrospective study in 104 patients with lymphoma who received BV for the first time between August 2020 and September 2022 across eight centers in Henan province. Data on the clinical use, effectiveness and adverse events (AEs) of BV were extracted from patient medical records. Short‐term effectiveness was assessed based on objective response rate (ORR), complete response (CR), partial response (PR), stable disease (SD) and progressive disease (PD). Progression‐free survival (PFS) and overall survival (OS) were calculated using Kaplan–Meier method. Safety was also evaluated in our study. Results 104 lymphoma patients were enrolled in our study, who had completed a median of two cycles (range,1–8) of BV‐based treatment. A total of 72.1% of patients were relapsed/refractory (R/R) lymphoma, and only 27.9% were previously untreated lymphoma who received BV in frontline treatment settings. Among them who received effectiveness evaluation, the ORR achieved 64.5% (CR 25.8%, PR 38.7%). After a median follow‐up of 11 months, the 6‐month PFS rate and OS rate achieved 77.2% and 90.1% respectively, and the 12‐month PFS rate and OS rate achieved 77.2% and 79.9% respectively. In general, BV‐based treatment was well‐tolerated, with 38.5% incidence of grade ≥3 AEs. The most commonly reported AEs were hematologic disorders, especially neutropenia, with the incidence reaching 50.0%. Conclusions BV‐based regimens could be a promising therapeutic option with remarkable effectiveness and moderate toxicity in treating Chinese lymphoma patients with CD30 expression.

Abstract Background The clinicopathologic characteristics and prognosis of nasal and nonnasal extranodal natural killer T‐cell lymphoma (ENKTL) are considered to be different. However, the underlying features responsible for these differences are not well clarified especially in the era of asparaginase therapy. Methods In total, 1007 newly diagnosed ENKTL patients from 11 medical centers were included in this study. Clinicopathologic characteristics and survival data were collected. The chi‐squared test and Kruskal–Wallis test were utilized for the comparison of different groups. Univariable and multivariable Cox proportional hazards models were used to screen prognostic factors. Results Overall, 869 (86.3%) patients were nasal forms. Compared to patients with nasal ENKTL, nonnasal patients were at more advanced stages and had poor performance status, bone marrow involvement, elevated serum lactate dehydrogenase (LDH), and CD56‐negative status (p

Abstract Objective The aim of the present study was to investigate the therapeutic effect of ammidin on hypoxia/reoxygenation (H/R) injury in primary neonatal rat cardiomyocytes by observing the role of ferroptosis in the process of H/R injury, and to verify its target and regulatory signaling pathways. Methods The network pharmacology analysis was used to predict the biological processes, core targets and related signaling pathways of Angelica dahurica in the treatment of ferroptosis. Cell viability was assessed using live cell imaging and cell counting kit-8. Lactate dehydrogenase (LDH), reactive oxygen species (ROS) production, and malondialdehyde (MDA), superoxide dismutase (SOD) and mitochondrial membrane potential (MMP) content were determined to assess the level of ferroptosis. Western blotting was performed to measure protein expression. Results Network pharmacology predicted that Acyl-CoA synthetase long chain family member 4 (ACSL4) was highly associated with myocardial H/R injury in the intersection of Angelica dahurica and ferroptosis. The top three active components of Angelica dahurica were found to be mandenol, alloisoimperatorin and ammidin, among which ammidin was found to have the strongest binding to the target proteins of the ACSL4/AMPK/mTOR pathway. H/R reduced the viability of cardiomyocytes, while the inhibition of ferroptosis by ferrostatin-1 alleviated the H/R-induced inhibition of cardiomyocyte viability. This was evidenced by the increased cell viability, SOD release, MMP level and glutathione peroxidase 4 (GPX4) protein expression, as well as the decreased LDH and MDA release and ROS production and ACSL4 protein expression (P

Abstract Underwater images suffer from color distortion, low clarity and halos problems due to light absorption, particle scattering and non‐uniform illumination. To address these degradation issues, a multi‐cues underwater image restoration algorithm combined with light field technology is proposed. First, based on Epipolar Plane Image, the light field cue transmittance containing depth information is calculated. Then, according to the turbidity of the underwater image, the light field cue transmittance and the polarization cue transmittance are fused to obtain the multi‐cues transmittance, which can effectively reduce the effect of particle scattering and color bias. Finally, the background light is estimated through the all‐focus operation, which can effectively overcome the distortion of an underwater single image and simultaneously reduce the halo phenomenon. Experimental results show that the method achieves the best results evaluated by UCIQE, UIQM, PSNR, and SSIM, and the restored color under the method is closer to the actual image than other underwater restoration methods.

Sustainable forest management faces challenges from various biotic and abiotic stresses. The Asian longhorned beetle (ALB) and drought stress both induce water shortages in poplar trees, but require different management strategies. In northwestern China, ALB and drought stress caused massive mortality in poplar shelterbelts, which seriously affected the ecological functions of poplars. Developing a large-scale detection method for discriminating them is crucial for applying targeted management. This study integrated UAV-hyperspectral and LiDAR data to distinguish between ALB and drought stress in poplars of China’s Three-North Shelterbelt. These data were analyzed using a Partial Least Squares-Support Vector Machine (PLS-SVM). The results showed that the LiDAR metric (elev_sqrt_mean_sq) was key in detecting drought, while the hyperspectral band (R970) was key in ALB detection, underscoring the necessity of integrating both sensors. Detection of ALB in poplars improved when the poplars were well watered. The classification accuracy was 94.85% for distinguishing well-watered from water-deficient trees, and 80.81% for detecting ALB damage. Overall classification accuracy was 78.79% when classifying four stress types: healthy, only ALB affected, only drought affected, and combined stress of ALB and drought. The results demonstrate the effectiveness of UAV-hyperspectral and LiDAR data in distinguishing ALB and drought stress in poplar forests, which contribute to apply targeted treatments based on the specific stress in poplars in northwest China.

Currently, there are various types of microscales and the conventional line detection system usually has only one detection method, which is difficult to adapt to the diverse calibration needs of microscales. This article investigates the high-precision measurement method of a microscale based on optoelectronics and the image integration method to solve the diversified calibration needs of microscales. The automatic measurement and processing system integrates two methods: the photoelectric signal measurement method and the photoelectric image measurement method. This article studies the smooth motion method based on ordinary linear guides, investigates the method of reducing the cosine error of a small-range interference length measurement, proposes an image-based line positioning method, and studies the edge and center recognition algorithms of the line. According to the experimental data, the system’s measurement accuracy was analyzed using the photoelectric signal measurement method to measure the 1 mm microscale, the maximum difference from the reference value was 0.105 μm, the standard uncertainty was 0.068 μm, and the absolute value of normalized error was less than 1. The accuracy of the image measurement method to measure the 1 mm microscale was consistent with that of the photoelectric signal method. The results show good consistency in the measurement results between the two methods of the integrated measurement system. The photoelectric signal method has the technical characteristics of high measurement efficiency and high accuracy, while the pixel-based measurement of the image method has two-dimensional measurement characteristics, which can realize measurements that cannot be realized by the photoelectric signal method; therefore, the measurement system of optoelectronics and image integration is characterized by high precision and a wide range of measurement adaptations.

Liaoning Province, a crucial agricultural region in Northeast China, has endured frequent drought disasters in recent years, significantly affecting both agricultural production and the ecological environment. Conducting drought research is of paramount importance for formulating scientific drought monitoring and prevention strategies, ensuring agricultural production and ecological safety. This study developed a Comprehensive Joint Drought Index (CJDI) using the empirical Copula function to systematically analyze drought events in Liaoning Province from 1981 to 2020. Through the application of MK trend tests, Morlet wavelet analysis, and run theory, the spatiotemporal variation patterns and recurrence characteristics of drought in Liaoning Province were thoroughly investigated. The results show that, compared to the three classic drought indices, Standardized Precipitation Index (SPI), Evaporative Demand Drought Index (EDDI), and Standardized Precipitation Evapotranspiration Index (SPEI), CJDI has the highest accuracy in monitoring actual drought events. From 1981 to 2020, drought intensity in all regions of Liaoning Province (east, west, south, and north) exhibited an upward trend, with the western region experiencing the most significant increase, as evidenced by an MK test Z-value of −4.53. Drought events in Liaoning Province show clear seasonality, with the most significant periodic fluctuations in spring (main cycles of 5–20 years, longer cycles of 40–57 years), while the frequency and variability of drought events in autumn and winter are lower. Mild droughts frequently occur in Liaoning Province, with joint and co-occurrence recurrence periods ranging from 1.0 to 1.8 years. Moderate droughts have shorter joint recurrence periods in the eastern region (1.2–1.4 years) and longer in the western and southern regions (1.4–2.2 years), with the longest co-occurrence recurrence period in the southern region (3.0–4.0 years). Severe and extreme droughts are less frequent in Liaoning Province. This study provides a scientific foundation for drought monitoring and prevention in Liaoning Province and serves as a valuable reference for developing agricultural production strategies to adapt to climate change.

Isolated coronoid process fractures are uncommon, and iatrogenic isolated fractures are extremely rare. This case describes a displaced fracture of an isolated coronoid process thought to be due to excessive force applied by a dentist that had been overlooked and left untreated for about a month. The patient was a woman in her late 50’s and she had undergone a molar extraction. Her dentist had confused her symptoms of trismus, pain, and facial oedema with the complex tooth extraction procedure. Following a cone-beam computed tomography (CBCT) scan we showed that the mandibular coronoid process on her right side had suffered a longitudinal fracture, and the fractured fragment had rotated upwards and inwards. Following successful surgical elimination of the fragmented coronoid process, the patient received targeted physiotherapy sessions that yielded excellent results. At the five-month follow-up, the ability of the patient to open her mouth had improved enormously, and her facial appearance almost recovered to its original state.

With the fast development of large-scale Photovoltaic (PV) plants, the automatic PV fault identification and positioning have become an important task for the PV intelligent systems, aiming to guarantee the safety, reliability, and productivity of large-scale PV plants. In this paper, we propose a residual learning-based robotic (UAV) image analysis model for low-voltage distributed PV fault identification and positioning. In our target scenario, the unmanned aerial vehicles (UAVs) are deployed to acquire moving images of low-voltage distributed PV power plants. To get desired robustness and accuracy of PV image detection, we integrate residual learning with attention mechanism into the UAV image analysis model based on you only look once v4 (YOLOv4) network. Then, we design the sophisticated multi-scale spatial pyramid fusion and use it to optimize the YOLOv4 network for the nuanced task of fault localization within PV arrays, where the Complete-IOU loss is incorporated in the predictive modeling phase, significantly enhancing the accuracy and efficiency of fault detection. A series of experimental comparisons in terms of the accuracy of fault positioning are conducted, and the experimental results verify the feasibility and effectiveness of the proposed model in dealing with the safety and reliability maintenance of low-voltage distributed PV systems.

BackgroundNodal T-follicular helper cell lymphomas (nTFHLs) represent a new family of peripheral T-cell lymphomas (PTCLs), and comparative studies of their constituents are rare.MethodsThis study retrospectively enrolled 10 patients with nTFHL-F and 30 patients with nTFHL-NOS diagnosed between December 2017 and October 2023 at six large comprehensive tertiary hospitals; 188 patients with nTFHL-AI were diagnosed during the same period at the First Affiliated Hospital of Zhengzhou University for comparison.ResultsCompared with nTFHL-AI, nTFHL-NOS patients exhibited better clinical manifestations, lower TFH expression levels, and a lower Ki-67 index. However, no differences in clinicopathological features were observed between nTFHL-F and nTFHL-AI patients as well as nTFHL-NOS patients. According to the survival analysis, the median OS for patients with nTFHL-NOS, nTFHL-AI, and nTFHL-F were 14.2 months, 10 months, and 5 months, respectively, whereas the median TTP were 14 months, 5 months, and 3 months, respectively. Statistical analysis revealed differences in TTP among the three subtypes(P=0.0173). Among the population of patients receiving CHOP-like induction therapy, there were significant differences in the OS and TTP among the nTFHL-NOS, nTFHL-AI, and nTFHL-F patients (P=0.0134, P=0.0205). Both the GDPT and C-PET regimens significantly improved the ORR, OS, and PFS in nTFHL patients.ConclusionThere are significant differences in the clinical manifestations, pathology, and survival outcomes among the three subtypes of nTFHLs. However, further research with a larger sample size, and involving clinical pathology and molecular genetics is needed to determine the distinctive biological characteristics of these tumors.

Hypoxanthine phosphoribosyl transferase 1 (HPRT1), once considered a housekeeping gene, has been identified as playing an important role in several tumors. Its role in pan-cancer, however, has not been systematically studied. This study evaluates the relationship between HPRT1 and clinical parameters, survival prognosis, and tumor immunity based on multi omics data from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Drug sensitivity analysis screened 16 effective drugs against HPRT1, exploring the interactions with chemicals and genes. The significance of HPRT1 in tumor immunotherapy has also been investigated. Immunohistochemistry confirmed significant differences in the expression of HPRT1 between five tumor types (colon adenocarcinoma [COAD], head-neck squamous cell carcinoma [HNSC], lung adenocarcinoma [LUAD], thyroid carcinoma [THCA], and uterine corpus endometrial carcinoma [UCEC]) and adjacent normal tissues (P < 0.05). HPRT1 competitive endogenous RNA network was constructed in HNSC. Through cytological experiments, it was verified that HPRT1 plays a carcinogenic role in HNSC and is associated with tumor cell proliferation, migration, invasion, and apoptosis. In addition, there was a significant positive correlation between HPRT1 and programmed cell death-1 (PD-1) expression in HNSC (P < 0.05). These findings suggest that HPRT1 may be a potential biomarker for predicting and treating cancer.

Abstract Background The Parkinson’s disease (PD) gene family expression is strongly linked to tumor development and progression; PINK1 and PARK2 are essential members of the PD gene family. However, the relationship between PINK1 and PARK2 and esophageal squamous cell carcinoma (ESCC) remains unknown. This research aims to clarify the prognostic value of PINK1 and PARK2 in ESCC. Methods PINK1 and PARK2 protein levels in 232 ESCC specimens, and 125 matched adjacent normal tissues were detected by immunohistochemistry. The relationship between PINK1 and PARK2 protein expression and clinicopathological features were analyzed. Kaplan–Meier survival analysis was performed to estimate the prognostic value of the PINK1 and PARK2 proteins in patients. Cox univariate and multivariate analyses were used to assess the risk factors affecting the OS for patients with ESCC. Results PINK1 and PARK2 had low expression in ESCC. Patients with low PINK1 had worse differentiation and advanced T and TNM stages. Lower PARK2 expression was linked to lymph node metastases and an advanced TNM stage. Furthermore, reduced PINK1 and PARK2 levels were associated with a poor prognosis for ESCC. Cox univariate and multivariate analyses revealed that PINK1, PARK2, and tumor size were closely associated with the prognosis of patients with ESCC, and PARK2 was an independent risk factor for patients with ESCC. Finally, the PINK1 and PARK2 proteins were closely related and shared the same signal pathway. Conclusions PINK1 and PARK2 could work as tumor suppressors in ESCC and are likely to become new treatment targets for ESCC.

Abstract Purpose The prognostic factors for diffuse large B‐cell lymphoma (DLBCL) have been fully explored, but prognostic information for bulky mass DLBCL patients is limited. This study aimed to analyze the prognostic value of MYC protein expression and other biological parameters in bulky mass DLBCL patients. Methods We defined a bulky mass as a maximum tumor diameter ≥7.5 cm and studied 227 patients with de novo bulky mass DLBCL. Results In all patients with bulky mass DLBCL, the 1‐year and 3‐year OS rates were 72.7% and 57.1%, respectively, and the 1‐year and 3‐year PFS rates were 52.0% and 42.5%, respectively. The MYC overexpression group (n = 140) showed significantly worse overall survival (OS; p = 0.019) and progression‐free survival (PFS; p = 0.001) than the non‐MYC overexpression group (n = 87). Subgroup analyses demonstrated that the MYC overexpression group was associated with inferior OS and PFS in the subgroups with the International Prognostic Index score of 3–5 (OS: p = 0.011; PFS: p

Abstract Severe combined immunodeficiency (SCID) encompasses a range of inherited disorders that lead to a profound deterioration of the immune system. Among the pivotal genes associated with SCID, RAG1 and IL2RG play crucial roles. IL2RG is essential for the development, differentiation, and functioning of T, B, and NK cells, while RAG1 critically contributes to adaptive immunity by facilitating V(D)J recombination during the maturation of lymphocytes. Animal models carrying mutations in these genes exhibit notable deficiencies in their immune systems. Non-human primates (NHPs) are exceptionally well-suited models for biomedical research due to their genetic and physiological similarities to humans. Cytosine base editors (CBEs) serve as powerful tools for precisely and effectively modifying single-base mutations in the genome. Their successful implementation has been demonstrated in human cells, mice, and crop species. This study outlines the creation of an immunodeficient monkey model by deactivating both the IL2RG and RAG1 genes using the CBE4max system. The base-edited monkeys exhibited a severely compromised immune system characterized by lymphopenia, atrophy of lymphoid organs, and a deficiency of mature T cells. Furthermore, these base-edited monkeys were capable of hosting and supporting the growth of human breast cancer cells, leading to tumor formation. In summary, we have successfully developed an immunodeficient monkey model with the ability to foster tumor growth using the CBE4max system. These immunodeficiency monkeys show tremendous potential as valuable tools for advancing biomedical and translational research.

Waste cooking oil’s (WCO’s) potential as a rejuvenator of aged asphalt has received attention in recent years, with the acid value of WCO affecting its rejuvenation effect. This study explored the rejuvenation effect of WCO with a high acid value on aged asphalt by using molecular dynamics simulation. First, the representative molecules of WCO with a high acid value and asphalt were determined. The rejuvenation effect of WCO on aged asphalt was analyzed by adding different contents of WCO to an aged asphalt model. The effect of WCO on the thermodynamic properties of the aged asphalt was analyzed. The results show that WCO can restore the thermodynamic properties of aged asphalt binder to a certain extent. Regarding the microstructure of rejuvenated asphalt, WCO molecules dispersed around asphaltenes weakened the latter’s aggregation and improved the colloidal structure of the aged asphalt. In terms of interface adhesion properties, WCO can improve the adhesion properties between asphalt binder and SiO2, but it has limited influence on water sensitivity. The results allowed us to comprehensively evaluate the rejuvenation effect of WCO with a high acid value on aged asphalt and to explore its rejuvenation mechanism.

ObjectiveIn order to set or improve the lightning protection measures of ships, it is necessary to evaluate the strike risk of critical equipment and the protection effect of the lightning rod.MethodsIn this paper, a lightning leader fractal model is constructed and applied to a simulation study on the lightning attachment process of a ship. The configuration method of the simulation boundary of the model and the quantitative evaluation method of lightning strike risk are improved, and a quantitative study on the influence of different factors on the lightning strike risk of the ship is performed.ResultsThe simulation results show that the protection probability of the lightning rod in the middle of the ship is more than 75% under the basic configuration. The bow, stern and antenna far away from the lightning rod have a relatively large risk of circling strike. The lightning strike probability of the shipboard antenna is lower if the lightning initiation position is closer to the lightning rod, the lightning current is greater or the lightning rod is higher.Conclusions The lightning leader fractal model constructed in this paper can be used to investigate the weak links of direct lightning protection on the surface of ships, which can provide useful references for the direct lightning protection design of ships.

Abstract Background Intrauterine adhesion (IUA) is a recurrent and refractory reproductive dysfunction disorder for which menstrual blood-derived stromal cells (MenSCs) might be a promising intervention. We reported that administration of MenSCs-derived exosomes (MenSCs-EXO) could achieve similar therapeutic effects to MenSCs transplantation, including alleviating endometrial fibrosis and improving fertility in IUA rats. The mass spectrometry sequencing result suggested that UBR4, a member of the proteasome family, was abundantly enriched in MenSCs-EXO. This study aimed to investigate the key role of UBR4 in MenSCs-EXO for the treatment of IUA and the specific molecular mechanism. Results UBR4 was lowly expressed in the endometrial stromal cells (EndoSCs) of IUA patients. MenSCs-EXO treatment could restore the morphology of IUA endometrium, reduce the extent of fibrosis, and promote endometrial and vascular proliferation. Knockdown of UBR4 in MenSCs did not affect the characteristics of exosomes but attenuated the therapeutic effect of exosomes. UBR4 in MenSCs-EXO could alleviate endometrial fibrosis by boosting YAP ubiquitination degradation and promoting YAP nuclear-cytoplasmic translocation. Moreover, P65 could bind to the UBR4 promoter region to transcriptionally promote the expression level of UBR4 in MenSCs. Conclusion Our study clarified that MenSCs-EXO ameliorated endometrial fibrosis in IUA primarily by affecting YAP activity mediated through UBR4, while inflammatory signaling P65 may affect UBR4 expression in MenSCs to enhance MenSCs-EXO therapeutic effects. This revealed a novel mechanism for the treatment of IUA with MenSCs-EXO, proposing a potential option for the clinical treatment of endometrial injury.

In the construction and maintenance of particle accelerators, all the accelerator elements should be installed in the same coordinate system, only in this way could the devices in the actual world be consistent with the design drawings. However, with the occurrence of the movements of the reinforced concrete cover plates at short notice or building deformations in the long term, the control points upon the engineering structure will be displaced, and the fitness between the subnetwork and the global control network may be irresponsible. Therefore, it is necessary to evaluate the deformations of the 3D alignment control network. Different from the extant investigations, in this paper, to characterize the deformations of the control network, all of the congruent models between the points measured in different epochs have been identified, and the congruence model with the most control points is considered as the primary or fundamental model, the remaining models are recognized as the additional ones. Furthermore, the discrepancies between the primary S-transformation parameters and the additional S-transformation parameters can reflect the relative movements of the additional congruence models. Both the iterative GCT method and the iterative combinatorial theory are proposed to detect multiple congruence models in the control network. Considering the actual work of the alignment, it is essential to identify the competitive models in the monitoring network, which can provide us a hint that, even the fitness between the subnetwork and the global control network is good, there are still deformations which may be ignored. The numerical experiments show that the suggested approaches can describe the deformation of the 3D alignment control network roundly.

Abstract Dilated cardiomyopathy (DCM) is the leading cause of heart transplantation. By microRNA (miRNA) array, a Kaposi’s sarcoma-associated herpes virus (KSHV)-encoded miRNA, kshv-miR-K12-1-5p, was detected in patients with DCM. The KSHV DNA load and kshv-miR-K12-1-5p level in plasma from 696 patients with DCM were measured and these patients were followed-up. Increased KSHV seropositivity and quantitative titers were found in the patients with DCM compared with the non-DCM group (22.0% versus 9.1%, p

Five-membered pyrroline nitroxides with high-potential is fascinating as catholyte for aqueous organic redox flow batteries (AORFBs), however, it suffers from a primary deficiency of insufficient stability due to ring-opening side reaction. Herein we report a spatial structure regulation strategy by host-guest chemistry, encapsulating 3-carbamoyl-2,2,5,5-tetramethylpyrroline-1-oxyl (CPL) into hydrosoluble cyclodextrins (CDs) with an inclusion structure of N–O· head towards cavity bottom, to boost the solubility and cyclability of pyrroline nitroxides significantly. The armor-clad CPL (CPL⊂HP-β-CD) catholyte in 0.05–0.5 ​M presents a battery capacity fade rate as low as 0.002 ​%/cycle (0.233 ​%/day) compared to the sole CPL in 0.05 ​M (0.039 ​%/cycle or 5.23 ​%/day) over 500 cycles in assembled AORFBs. The optimized reclining spatial structure with N–O· head towards CD cavity bottom effectively inhibits the attack of Lewis base species on the hydrogen abstraction site in pyrroline ring, and thus avoids the ring-opening side reaction of pyrroline nitroxides.