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Land use types, land development and utilization intensity within watersheds have changed based on intensifying human activities and climate change, thereby inducing spatiotemporal variations in non-point source pollution (NPS), significantly impacting soil and water quality. This study performed a case study on an ecological environment functional zone at the northern foot of Qinling Mountains, an area strongly affected by human activities and land use changes. It employed an improved potential non-point pollution index (PNPI) model to analyze potential non-point source pollution (PNPS) and associated risk evolution characteristics in watershed over the past 30 years. The results indicate that from 1990 to 2020, the dominant land use categories were forest and arable land, making up 95 % of the entire watershed area. Notably, urban residential land presented the most significant expansion rates and nearly doubled in area between 1990 and 2020, whereas shrubland, grassland, and unused land showed a decreasing trend. With the application of the quantile classification method, PNPS risk values were divided into five categories: very low, low, moderate, high, and very high. A polarized trend in risk was observed, with increases in areas influenced by human activities and rapid expansion of very high-risk regions. Concurrently, the pollution risk in the upstream water source area decreased. In recent years, accelerated urbanization has been the main driver causing expansion of high PNPS risk regions. This study explores the spatial and temporal evolution of PNPS risk in the Heihe Basin by using an improved PNPI model. The improved model is more accurate in calculations and provides a better understanding of the distribution of PNPS, which is an important reference for watershed management and water resource governance.

Melt electrospinning writing (MEW) combines the fundamental principles of electrospinning, a fiber forming technology, and 3D printing. The process, however, is highly complex and the quality of the fabricated structures strongly depends on the interplay of key printing parameter settings including processing temperature, applied voltage, collection speed, and applied pressure. These parameters act in unison, comprising the principal forces on the electrified jet: pushing the viscous polymer out of the nozzle and mechanically and electrostatically dragging it for deposition towards the collector. This article will reveal the correlation between the printing process parameters and the fiber morphology for curved printing fibers below the critical translation speed (CTS), and prepare controllable curved scaffolds by adjusting the electric field strength, which have fully interconnected pores and allow cells to migrate and proliferate. Furthermore, the study verified the advantages of these scaffolds through mechanical and in vitro culture experiments. The results showed that compared with the linearly printed scaffolds, the curved printed scaffolds exhibited better mechanical properties and enhanced cell attachment and proliferation.

In July 2022, regions with elevations exceeding 5 000 m on the inner Tibetan Plateau (TP) witnessed a record-breaking heatwave. But how the atmospheric circulation and soil moisture play roles in the occurrence and maintenance of the heatwave in such high elevation climate sensitive region remains unknown. Here, by using the flow analogue method, we find that negative soil moisture anomalies explain more than half of the extreme high temperature during the heatwave, while atmospheric circulation explains less than half. The high soil moisture-temperature coupling metric and the increased correlation between latent heat flux and soil moisture during heatwave revealed strong land-atmosphere feedback in the Qiangtang Plateau which has amplified the heatwave. Analyses of numerical experiments confirm that the presence of interaction between soil moisture and the atmosphere has increased the intensity of hot extreme event under the same atmospheric circulation conditions. Under the warming background, land-atmosphere coupling leads to a faster increase in extreme high temperatures compared to the global mean warming rate, and it is twice as fast as the increase in extreme high temperatures without coupling. We highlight the increased probability of extreme high temperature over the TP in the future due to soil moisture feedback and the results are hoped to inform policymakers in making decisions for climate adaptation activities.

Identification of potential cerebrovascular disorder in the patient with traumatic subarachnoid hemorrhage (tSAH) is a key element to decrease the complication occurrence and mortality rate. In this study, we aim to compare the diagnostic values between dual-source computed tomography angiography (DSCTA) and traditional tomography angiography (CTA) in identification of potential cerebrovascular disorder among tSAH patients. A total of 113 tSAH patients with the hemorrhage involving more than 2 cisterns were recruited. Among that, 42 patients received DSCTA scans, and another 71 patients received traditional CTA scans. Subsequently, all patients received digital subtraction angiography (DSA) tests to confirm the presence of the cerebrovascular disorder. In DSCTA scan group, 21.4 % (9/42) patients were reported to have cerebrovascular disorders: seven patients had intracranial aneurysms; a patient had pseudoaneurysm with carotid artery cavernous sinus fistula; and a patient had Moyamoya disease. DSA tests had the same results with that with DSCTA scans. In the cohort receiving CTA scans, 19.7 % (14/71) patients were reported to had intracranial aneurysms. However, the positive results of DSA tests for this cohort were 22.5 % (16/71). Two inconsistent results between the CTA scan and DSA test were found, including an arteriovenous malformation and an arteriovenous fistula. In summary, DSCTA and CTA had similar positive rates but differ in diagnostic accuracy for identification of cerebrovascular disorders in tSAH patients.

Abstract Relative permeability (RP) curves which provide fundamental insights into porous media flow behavior serve as critical parameters in reservoir engineering and numerical simulation studies. However, obtaining accurate RP curves remains a challenge due to expensive experimental costs, core contamination, measurement errors, and other factors. To address this issue, an innovative approach using deep learning strategy is proposed for the prediction of rock sample RP curves directly from mercury injection capillary pressure (MICP) measurements which include the mercury injection curve, mercury withdrawal curve, and pore size distribution. To capture the distinct characteristics of different rock samples' MICP curves effectively, the Gramian Angular Field (GAF) based graph transformation method is introduced for mapping the curves into richly informative image forms. Subsequently, these 2D images are combined into three-channel red, green, blue (RGB) images and fed into a Convolutional Long Short-Term Memory (ConvLSTM) model within our established self-supervised learning framework. Simultaneously the dependencies and evolutionary sequences among image samples are captured through the limited MICP-RP samples and self-supervised learning framework. After that, a highly generalized RP curve calculation proxy framework based on deep learning called RPCDL is constructed by the autonomously generated nearly infinite training samples. The remarkable performance of the proposed method is verified with the experimental data from rock samples in the X oilfield. When applied to 37 small-sample data spaces for the prediction of 10 test samples, the average relative error is 3.6%, which demonstrates the effectiveness of our approach in mapping MICP experimental results to corresponding RP curves. Moreover, the comparison study against traditional CNN and LSTM illustrated the great performance of the RPCDL method in the prediction of both S o and S w lines in oil–water RP curves. To this end, this method offers an intelligent and robust means for efficiently estimating RP curves in various reservoir engineering scenarios without costly experiments.

Objective: Glioblastomas are highly vascularized malignant tumors. We determined the efficacy and safety of the anti-angiogenic multi-kinase inhibitor, anlotinib, for a newly diagnosed glioblastoma. Methods: This multicenter, single-arm trial (NCT04119674) enrolled 33 treatment-naïve patients with histologically proven glioblastomas between March 2019 and November 2020. Patients underwent treatment with the standard STUPP regimen [fractionated focal irradiation in daily fractions of 1.8-2 Gy given 5 d/w × 6 w (total = 54-60 Gy)] or radiotherapy plus continuous daily temozolomide (TMZ) (75 mg/m2 of body surface area/d, 7 d/w from the first to the last day of radiotherapy), followed by 6 cycles of adjuvant TMZ (150–200 mg/m2 × 5 d during each 28-d cycle) plus anlotinib (8 mg/d on d 1–14 of each 3-w cycle for 2 cycles during concomitant chemoradiotherapy, 8 maximal cycles as adjuvant therapy, followed by maintenance at 8 mg/d. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall survival (OS) and adverse events (AEs). Results: Thirty-three patients received the planned treatment. The median PFS was 10.9 months (95% CI, 9.9–18.7 months) and the 12-month PFS rate was 48.5%. The median OS was 17.4 months (95% CI, 14.5–21.1 months) and the 12-month OS rate was 81.8%. The most common AEs included hypertriglyceridemia [58% (n = 19)], hypoalbuminemia [46% (n = 15)], and hypercholesterolemia [46% (n = 15)] during concurrent chemoradiotherapy and leukopenia [73% (n = 24)], hypertriglyceridemia [67% (n = 22)], and neutropenia [52% (n = 17)] during adjuvant therapy. Five patients discontinued treatment due to AEs. HEG1 (HR, 5.6; 95% CI, 1.3–23.7; P = 0.021) and RP1L1 alterations (HR, 11.1; 95% CI, 2.2–57.2; P = 0.004) were associated with a significantly shorter PFS. Conclusions: Anlotinib plus the STUPP regimen has promising anti-tumor activity against glioblastoma and manageable toxicity. HEG1 and RP1L1 alterations might be novel predictive biomarkers of the response to anlotinib.

Abstract With the rapid development of modern medical technology and the dramatic increase in the amount of medical data, traditional centralized medical information management is facing many challenges. In recent years blockchain, which is a peer-to-peer distributed database, has been increasingly accepted and adopted by different industries and use cases. Key areas of healthcare blockchain applications include electronic medical record (EMR) management, medical device supply chain management, remote condition monitoring, insurance claims and personal health data (PHD) management, among others. Even so, there are a number of challenges in applying blockchain concepts to healthcare and its data, including interoperability, data security privacy, scalability, TPS and so on. While these challenges may hinder the development of blockchain in healthcare scenarios, they can be improved with existing technologies In this paper, we propose a blockchain-based healthcare operations management framework that is combined with the Interplanetary File System (IPFS) for managing EMRs, protects data privacy through a distributed approach while ensuring that this medical ledger is tamper-proof. Doctors act as full nodes, patients can participate in network maintenance either as light nodes or as full nodes, and the hospital acts as the endpoint database of data, i.e., the IPFS node, which saves the arithmetic power of nodes and allows the data stored in the hospitals and departments to be shared with the other organizations that have uploaded the data. Therefore, the integration of blockchain and zero-knowledge proof proposed in this paper helps to protect data privacy and is efficient, better scalable, and more throughput.

Abstract Background Proteolysis-targeting chimeras (PROTACs) are being developed for therapeutic use. However, they have poor pharmacokinetic profiles and their tissue distribution kinetics are not known. Methods A typical von Hippel-Lindau tumor suppressor (VHL)—PROTAC 14C-A947 (BRM degrader)—was synthesized and its tissue distribution kinetics was studied by quantitative whole-body autoradiography (QWBA) and tissue excision in rats following IV dosing. Bile duct-cannulated (BDC) rats allowed the elucidation of in vivo clearance pathways. Distribution kinetics was evaluated in the tissues and tumors of mice to support PK-PD correlation. In vitro studies enabled the evaluation of cell uptake mechanisms and cell retention properties. Results Here, we show that A947 quickly distributes into rat tissues after IV dosing, where it accumulates and is retained in tissues such as the lung and liver although it undergoes fast clearance from circulation. Similar uptake/retention kinetics enable tumor growth inhibition over 2–3 weeks in a lung cancer model. A947 quickly excretes in the bile of rats. Solute carrier (SLC) transporters are involved in hepatocyte uptake of PROTACs. Sustained BRM protein degradation is seen after extensive washout that supports prolonged cell retention of A947 in NCI-H1944 cells. A947 tissue exposure and pharmacodynamics are inversely correlated in tumors. Conclusions Plasma sampling for VHL-PROTAC does not represent the tissue concentrations necessary for efficacy. Understanding of tissue uptake and retention could enable less frequent IV administration to be used for therapeutic dosing.

Abstract By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma.

Hot torsion tests for AZ80 magnesium alloy were carried out in the temperature range of 380 °C-260 °C, with a constant decreasing temperature rate of 10 °C/s in order to weaken the basal texture and refine the grains. The results indicated that the average grain sizes were refined forming gradient structure with increasing specimen radial position from center (12.2–5.4 μm), and that the initial basal texture intensity of the extruded magnesium alloy was weakened from 46.2 to 8.3. Furthermore, the extension twins (ETs) could be disintegrated from the twins forming separated twins with smaller sizes. Interestingly, ETs with the same twin variant intersecting with each other could be coalesced forming grains with similar orientation, while ETs with different twin variants were separated by twins boundaries contributing to grain refinement. Moreover, in addition to the conventional continuous dynamic recrystallized (CDRX) grains with 30˚ orientation rotated around C-axis of the parent grains, CDRXed grains with 30˚ rotation around a-axis and random rotation axis were also discerned. Besides, the CDRX evolution induced twins were also elaborated, exhibiting the complex competition between CDRX and twining. Hot torsion deformation with constant decreasing temperatures rate is an effective way of grain refinement and texture modification.

Abstract We previously showed that MYC promoted Burkitt lymphoma (BL) growth by inhibiting the tumor suppressor miR-150, resulting in release of miR-150 targets MYB and ZDHHC11. The ZDHHC11 gene encodes three different transcripts including a mRNA (pcZDHHC11), a linear long non-coding RNA (lncZDHHC11) and a circular RNA (circZDHHC11). All transcripts contain the same region with 18 miR-150 binding sites. Here we studied the relevance of circZDHHC11, including this miR-150 binding site region, for growth of BL cells. CircZDHHC11 was mainly present in the cytoplasmic fraction in BL cells and its localization was not altered upon miR-150 overexpression. Knockdown of circZDHHC11 caused a strong inhibition of BL growth without affecting the expression levels of MYC, MYB, miR-150 and other genes. Overexpression of circZDHHC11 neither affected cell growth, nor rescued the phenotype induced by miR-150 overexpression. Genomic deletion of the miR-150 binding site region did not affect growth, nor did it change the effect of circZDHHC11 knockdown. This indicated that the miR-150 binding site region is dispensable for the growth promoting role of circZDHHC11. To conclude, our results show that circZDHHC11 is a crucial factor supporting BL cell growth independent of its ability to sponge miR-150.

Abstract Exercise is usually regarded to have short-term beneficial effects on immune health. Here we show that early-life regular exercise exerts long-term beneficial effects on inflammatory immunity. Swimming training for 3 months in male mice starting from 1-month-old curbs cytokine response and mitigates sepsis when exposed to lipopolysaccharide challenge, even after an 11-month interval of detraining. Metabolomics analysis of serum and liver identifies pipecolic acid, a non-encoded amino acid, as a pivotal metabolite responding to early-life regular exercise. Importantly, pipecolic acid reduces inflammatory cytokines in bone marrow-derived macrophages and alleviates sepsis via inhibiting mTOR complex 1 signaling. Moreover, early-life exercise increases histone 3 lysine 4 trimethylation at the promoter of Crym in the liver, an enzyme responsible for catalyzing pipecolic acid production. Liver-specific knockdown of Crym in adult mice abolishes this early exercise-induced protective effects. Our findings demonstrate that early-life regular exercise enhances anti-inflammatory immunity during middle-aged phase in male mice via epigenetic immunometabolic modulation, in which hepatic pipecolic acid production has a pivotal function.

Abstract In this paper, we focus on the general free scalar–tensor gravity with three free coupling functions, which in the near-field region looks like general relativity (GR) plus a fifth force of Yukawa-type induced by the scalar field. We show that the fifth force is always attractive in the theory. We investigate the effects of the attractive fifth force and calculate in detail the fifth force-induced orbital precession rate $$\delta \omega /\omega $$ δ ω / ω and the parameterized post-Newtonian parameters $$\gamma $$ γ and $$\beta $$ β , all of which depend on the fifth force parameters and the interaction distance. It turns out that, due to the attractive fifth force, $$\delta \omega /\omega $$ δ ω / ω is always greater than zero, $$\gamma $$ γ is always less than one, $$\beta $$ β is greater than one at large distances, and additionally this class of theories is ruled out as an alternative theory to dark matter. We place stringent constraints on the fifth force parameters by combining the lunar laser ranging (LLR), Cassini, and Mercury precession experiments, and derive the upper bounds on the strength ratio of the fifth force to gravitational force at different scales from the LLR observation. We find that the Mercury constraint is not competitive with the LLR and Cassini constraints and the LLR observation imposes much more stringent bounds on the strength ratio on large scales than on small scales. Our results show that this theory is sufficiently close to GR for a small enough fifth force strength and can reduce to GR with a minimally coupled scalar field in the absence of fifth force.

With the continuous expansion of satellite constellation, this paper analyzed the characteristics of mega constellation, and summarized the capability requirements of routing algorithms for mega constellation from two aspects of networking transmission and service requirements, included reducing signaling overhead, load balancing, fault recovery, and guaranteeing QoS.In addition, it introduced the routing methods, algorithms, and their performances that were applicable to mega constellation.It looked forward to the future related technology directions for mega constellation, included software defined network, area division management, artificial intelligence, and computing power routing, with the aim of providing reference for the construction of 6G satellite Internet.

Abstract Background Despite the importance of medication adherence in treatment effectiveness, little is known about the association between medication non-adherence and self-inflicted violence behaviors. We aimed to assess whether medication non-adherence increased the risk of self-inflicted violence behaviors among schizophrenics in communities (hypothesis 1) and whether the dose–response relationship existed (hypothesis 2). Methods This 12-year cohort study in western China recruited 292,667 community-dwelling schizophrenics. The proportion of regular medication (PRM) was calculated by dividing the time of “regular adherence” by the total time of antipsychotic treatment during follow-up period as an indicator of medication adherence. For hypothesis 1, medication adherence was designated as a binary variable with a threshold of 0.8 (PRM); for hypothesis 2, medication adherence was specified as five-category and continuous variables, respectively. Inverse probability weighting and mixed effects Cox proportional hazards models were conducted for confounders control and survival analyses. Results One hundred eighty-five thousand eight hundred participants were eligible for the final analyses, with a mean age of 47.49 years (SD 14.55 years), of whom 53.6% were female. For hypothesis 1, the medication non-adherence group (PRM

Abstract Background Chimeric antigen receptor natural killer (CAR-NK) cells represent a promising advancement in CAR cell therapy, addressing limitations observed in CAR-T cell therapy. However, our prior study revealed challenges in CAR-NK cells targeting CD19 antigens, as they failed to eliminate CD19+ Raji cells in NSG tumor-bearing mice, noting down-regulation or loss of CD19 antigen expression in some Raji cells. In response, this study aims to enhance CD19 CAR-NK cell efficacy and mitigate the risk of tumor recurrence due to target antigen escape by developing CD19 and CD20 (CD19/CD20) dual-targeted CAR-NK cells. Methods Initially, mRNA encoding anti-CD19 CARs (FMC63 scFv-CD8α-4-1BB-CD3ζ) and anti-CD20 CARs (LEU16 scFv-CD8α-4-1BB-CD3ζ) was constructed via in vitro transcription. Subsequently, CD19/CD20 dual-targeted CAR-NK cells were generated through simultaneous electrotransfection of CD19/CD20 CAR mRNA into umbilical cord blood-derived NK cells (UCB-NK). Results Following co-electroporation, the percentage of dual-CAR expression on NK cells was 86.4% ± 1.83%, as determined by flow cytometry. CAR expression was detectable at 8 h post-electric transfer, peaked at 24 h, and remained detectable at 96 h. CD19/CD20 dual-targeted CAR-NK cells exhibited increased specific cytotoxicity against acute lymphoblastic leukemia (ALL) cell lines (BALL-1: CD19+CD20+, REH: CD19+CD20−, Jurkat: CD19−CD20−) compared to UCB-NK, CD19 CAR-NK, and CD20 CAR-NK cells. Moreover, CD19/CD20 dual-targeted CAR-NK cells released elevated levels of perforin, IFN-γ, and IL-15. Multiple activation markers such as CD69 and cytotoxic substances were highly expressed. Conclusions The creation of CD19/CD20 dual-targeted CAR-NK cells addressed the risk of tumor escape due to antigen heterogeneity in ALL, offering efficient and safe 'off-the-shelf' cell products. These cells demonstrate efficacy in targeting CD20 and/or CD19 antigens in ALL, laying an experimental foundation for their application in ALL treatment.

Abstract In response to the issues of traditional backpropagation (BP) neural networks in state of charge (SOC) estimation, including easy convergence to local optima, slow convergence speed, and low accuracy, this paper proposes a novel adaptive crossover mutation strategy and dynamic sparrow search algorithm to optimize BP networks' initial values and thresholds (ACMSSA‐BP). The proposed method is based on the sparrow search algorithm, where the number of producers and scroungers is adjusted through an adaptive factor. This improvement effectively transitions the search process from extensive full exploration to localized fine‐tuning search. In the position update phase of the producers, crossover mutation and dynamic search strategies are introduced to increase the diversity of good populations, prevent the algorithm from converging to local optima, and maintain its local search capability in the later stage. Using real transportation data from coal mining flame‐proof tracked vehicles, we applied correlation theory to extract model feature parameters and constructed a training data set to estimate the SOC. The results of both static and dynamic validation experiments have indicated that the ACMSSA‐BP method has delivered impressive performance in predicting SOC, as reflected in the mean absolute error, root mean squared error, and mean absolute percentage error values of less than 1.5%, 1.5%, and 1.6%, respectively. Compared with BP, SSA‐BP, CMSSA‐BP, PSO‐BP, and NARX_NN methods, the ACMSSA‐BP approach demonstrates enhanced accuracy in estimation, significant robustness, and impressive generalization capabilities.

Abstract Pericardial synovial sarcomas (PSS) have a low incidence rate and are highly invasive with a dismal prognosis. Standard treatment includes surgery, radiotherapy and chemotherapy but with limited response. Here, we report the case of a 15‐year‐old nonsmoking youngster diagnosed with PSS who developed disease relapsed from surgery after 1 month. Next‐generation sequencing (NGS) using baseline tissue was performed, and BRCA2 c.968dupT was detected. Then pazopanib (a multitargeted inhibitor) plus nivolumab (an immune checkpoint inhibitor) was administered, with a partial response and progression‐free survival of 14 months. BRCA2 c.968dupT has not previously been reported in PSS and its response to targeted combination immunotherapy are not well characterized. Here, we report the efficacy of pazopanib combined with nivolumab in a PSS patient harboring BRCA2 c.968dupT and also provide the clinical evidence of the utility of NGS in exploring actionable mutations for solid tumor. Combination therapy based on immunotherapy may be a potential treatment choice for PSS harboring BRCA2 mutation.

Jointed soft-hard composite rock mass is very common in engineering. The existence of joint and the uncoordinated deformation of soft-hard layer make the failure behavior more complicated. In this study, soft-hard composite rock with three parallel joints (two coplanar joints and one out-of-plane parallel joint) were fabricated to carry out uniaxial compression experiment. With the aid of digital imagine correlation (DIC) and acoustic emission (AE) technology, the influence of joint angle, ligament angle and the location of out-of-plane joint on crack propagation behavior of specimen is analyzed. The results show that when the hard layer contains more joints, the rock mass presents more obvious brittleness. The variation of peak strength with ligament angle also depends on the rock layer where the out-of-plane crack is located. Three failure modes and ten crack coalescence modes are summarized, which are affected by joint angle and ligament angle. The transition of crack coalescence between adjacent rock layer is mainly influenced by the space of wing cracks at joint tips. The coalescence of rock bridge in the layer with double joints is affected by ligament angle and the relative strength of layer. When the out-of-plane joint is in the hard layer, the coalescence possibility is greatly reduced.

The Kirkpatrick–Baez (KB) microscope is an effective instrument for x-ray imaging of hot spot. However, the non-uniform distribution of response efficiency in the field of view is a drawback of the KB microscope. A more accurate hot spot image requires the correction of the measured image by combining the hot spot position and the response efficiency distribution. Here, we describe a method to locate the position of the hot spot in the field of view during hot spot imaging with a KB microscope. The position of the hot spot in the field of view can be obtained by measuring the grazing incidence angle change during hot spot imaging. In the experiment of hot spot self-emission imaging with a four-channel KB microscope, the location of the hot spot with an accuracy of 15 μm was realized, and the intensity corrected hot spot image was obtained. This will solve the problem of the non-uniform distribution of the response efficiency of the KB microscope and enable quantitative measurement of hot spot radiation intensity.

ABSTRACT Background Despite considerable progress in cancer immunotherapy, it is not available for many patients. Resistance to immune checkpoint blockers arises from the intricate interactions between cancer and its microenvironment. Metabolic reprogramming in tumor and immune cells in the tumor microenvironment (TME) influences anti‐tumor immune responses by remodeling the immune microenvironment. Metabolic reprogramming has emerged as an important hallmark of tumorigenesis. However, few studies have focused on the TME and metabolic reprogramming. Therefore, we aimed to explore the current research status and popular topics in TME‐related metabolic reprogramming over a 20 years using a bibliometric approach. Methods Studies focusing on metabolic reprogramming and TME were searched using the Web of Science Core Collection database. Bibliometric and visual analyses of the articles and reviews were performed using Bibliometrix, VOSviewer, and CiteSpace. Results In total, 4726 articles published between 2003 and 2022 were selected. The number of publications and citations has increased annually. Cooperation network analysis indicated that the United States holds the foremost position in metabolic reprogramming and TME research with the highest volume of publications and citations, thus exerting the greatest influence. Among these institutions, Fudan University displayed the highest level of productivity. Frontiers in Immunology showed the highest degree of productivity in this field. Ho Ping‐Chih made the most article contributions, and Pearce Edward J. was the most co‐cited author. Four clusters were obtained after a cluster analysis of the authors' keywords: TME, metabolic reprogramming, immunometabolism, and immunity. Immunometabolism, glycolysis, immune cells, and tumor‐associated macrophages are relatively recent keywords that have attracted increasing attention. Conclusions A comprehensive landscape of advancements in metabolic reprogramming and the TME was evaluated, which provided crucial information for scholars to further advance this promising field. Further research should explore new topics related to immunometabolism in the TME using a transdisciplinary approach.

Idiopathic pulmonary fibrosis (IPF) is a progressive pulmonary disease that leads to interstitial inflammation, lung damage, and eventually life-threatening complications. Among various pathologic factors, Smad4 is a pivotal molecule involved in the progression and exacerbation of IPF. It mediates nuclear transfer of Smad2/Smad3 complexes and initiates the transcription of fibrosis-promoting genes. Thus, the inhibition of Smad4 expression in pulmonary fibroblasts by small interfering RNAs (siRNAs) might be a promising therapeutic strategy for IPF. Herein, we engineered exosome membranes (EM) by cationic lipid (i.e., DOTAP) to load siRNAs against Smad4 (DOTAP/siSmad4@EM), and investigated their specific delivery to pulmonary fibroblasts for treating IPF in a mouse model via pulmonary administration. As reference nanoscaffolds, undecorated DOTAP/siSmad4 complexes (lipoplexes, consisting of cationic lipid DOTAP and siRNAs) and siSmad4-loaded lipid nanoparticles (DOTAP/siSmad4@lipo, consisting of lipoplexes fused with DPPCChol liposomes) were also prepared. The results showed that DOTAP/siSmad4@EM exhibited a higher cellular uptake and gene silencing efficacies in mouse pulmonary fibroblasts (viz., MLg2908) as compared to the two reference nanoscaffolds. Furthermore, the outcomes of the in vivo experiments illustrated that DOTAP/siSmad4@EM could significantly down-regulate the Smad4 expression with augmented anti-fibrosis efficiency. Additionally, the DOTAP/siSmad4@EM conferred excellent biocompatibility with low cytokine levels in bronchoalveolar lavage fluid and proinflammatory responses in the pulmonary area. Taken together, the outcomes of our investigation imply that specific inhibition of Smad4 expression in pulmonary fibroblasts by pulmonary administrated DOTAP/siSmad4@EM is a promising therapeutic strategy for IPF, which could safely and effectively deliver siRNA drugs to the targeted site of action.

Backgroundβ-glucan has been reported to be a potential natural immune modulator for tumor growth inhibition. We aimed to evaluate the efficacy and safety of β-glucan plus immunotherapy and chemotherapy in the first-line treatment of advanced gastric adenocarcinoma.MethodsThis is a phase IB, prospective, single-arm, investigator-initiated trail. Advanced gastric adenocarcinoma patients received β-glucan, camrelizumab, oxaliplatin, oral S-1 every 3 weeks. The curative effect was evaluated every 2 cycles. The primary endpoints were objective response rate (ORR) and safety, with secondary endpoints were median progression-free survival (mPFS) and median overall survival (mOS). The exploratory endpoint explored biomarkers of response to treatment efficacy.ResultsA total of 30 patients had been enrolled, including 20 (66.7%) males and all patients with an ECOG PS score of ≥1. The ORR was 60%, the mPFS was 10.4 months (95% confidence interval [CI], 9.52-11.27), the mOS was 14.0 months (95% CI, 11.09-16.91). A total of 19 patients (63.3%) had TRAEs, with 9 patients (30%) with grade ≥ 3. The most common TRAEs were nausea (53.3%). After 2 cycles of treatment, the levels of IL-2, IFN-γ and CD4+ T cells significantly increased (P < 0.05). Furthermore, biomarker analysis indicated that patient with better response and longer OS exhibited lower GZMA expression at baseline serum.ConclusionsThis preliminary study demonstrates that β-glucan plus camrelizumab and SOX chemotherapy offers favorable efficacy and a manageable safety profile in patients with advanced gastric adenocarcinoma, and further studies are needed to verify its efficacy and safety.Clinical Trial RegistrationChinese Clinical Trials Registry, identifier ChiCTR2100044088

IntroductionDandelion is widely used in clinical practice due to its beneficial effects. Polyphenolic compounds are considered the main anti-inflammatory active ingredient of dandelion, but the gene expression patterns of polyphenolic compounds in different dandelion tissues are still unclear.MethodsIn this study, we combined a nontargeted metabolome, PacBio Iso-seq transcriptome, and Illumina RNA-seq transcriptome to investigate the relationship between polyphenols and gene expression in roots, flowers, and leaves of flowering dandelion plants.ResultsEighty-eight flavonoids and twenty-five phenolic acids were identified, and 64 candidate genes involved in flavonoid biosynthesis and 63 candidate genes involved in chicoric acid biosynthesis were identified. Most flavonoid and chicoric acid-related genes demonstrated the highest content in flowers. RNA-seq analysis revealed that genes involved in polyphenol biosynthesis pathways, such as CHS, CHI, F3H, F3’H, FLS, HQT, and CAS, which are crucial for the accumulation of flavonoids and chicoric acid, were upregulated in flowers.DiscussionThe combination of transcriptomic and metabolomic data can help us better understand the biosynthetic pathways of polyphenols in dandelion. These results provide abundant genetic resources for further studying the regulatory mechanism of dandelion polyphenol biosynthesis.

IntroductionDeveloping antibiotic adjuvants is an effective strategy to combat antimicrobial resistance (AMR). The envelope of Gram-negative bacteria (GNB) is a barrier to prevent the entry of antibiotics, making it an attractive target for novel antibiotic and adjuvant development.Methods and ResultsIn this study, we identified Caspofungin acetate (CAS) as an antibiotic adjuvant against GNB in the repurposing screen of 3,158 FDA-approved drugs. Checkerboard assays suggested that CAS could enhance the antimicrobial activity of rifampin or colistin against various GNB strains in vitro, Moreover, Galleria mellonella larvae infection model also indicated that CAS significantly potentiated the efficacy of rifampin against multidrug-resistant Escherichia coli 72 strain in vivo. Most importantly, resistance development assay showed that CAS was less susceptible to accelerating the resistance development of drug-sensitive strain E. coli MG1655. Functional studies and RNA-seq analysis confirmed that the mechanisms by which CAS enhanced the antimicrobial activities of antibiotics were involved in permeabilizing the bacterial cell envelope, disrupting proton motive force and inhibiting bacterial biofilm formation. Additionally, it has been found that PgaC is the CAS target and enzymatic assay has confirmed the inhibition activity.DiscussionOur results illustrate the feasibility of CAS as an antibiotic adjuvant against GNB, which is an alternative strategy of anti-infection.

ObjectiveThe mental health issues of individuals with coronavirus disease 2019 (COVID-19) are currently widespread. Traditional Chinese exercise (Daoyin) plays an important role in relieving patients’ psychological problems. This study aims to assess the efficacy of Daoyin in mitigating mental health issues among individuals diagnosed with COVID-19.MethodsPubMed, the Cochrane library, Embase, CNKI, Wanfang, VIP database, and SinoMed were searched from their inception to October 2023. Two researchers independently selected the eligible studies. The analysis and presentation of the findings were conducted using Review Manager 5.2 software. The data were analyzed using mean difference (MD), inverse variance, and 95% confidence intervals (CIs).ResultsA total of 12 studies (N = 1291) were included in this study. The results showed that Daoyin can significantly reduce the scores of the Self-Rating Anxiety Scale (SAS: MD = −13.03, 95% CI −19.56 to −6.49, P

Abstract Targeting the programmed cell death 1/programmed cell death ligand 1 (PD‐1/PD‐L1) pathway has been identified as a successful approach for tumor immunotherapy. Here, we identified that the small molecule 5,7,4′‐trimethoxyflavone (TF) from Kaempferia parviflora Wall reduces PD‐L1 expression in colorectal cancer cells and enhances the killing of tumor cells by T cells. Mechanistically, TF targets and stabilizes the ubiquitin ligase HMG‐CoA reductase degradation protein 1 (HRD1), thereby increasing the ubiquitination of PD‐L1 and promoting its degradation through the proteasome pathway. In mouse MC38 xenograft tumors, TF can activate tumor‐infiltrating T‐cell immunity and reduce the immunosuppressive infiltration of myeloid‐derived suppressor cells and regulatory T cells, thus exerting antitumor effects. Moreover, TF synergistically exerts antitumor immunity with CTLA‐4 antibody. This study provides new insights into the antitumor mechanism of TF and suggests that it may be a promising small molecule immune checkpoint modulator for cancer therapy.

The landslide susceptibility map estimates the quantitative relationship between known landslides and control factors, and it has been used for site selection of infrastructures and geo-disaster management. As landslides and rockfalls occur frequently in mountainous areas in Hebei Province, China, due to road construction, the managing government needs to evaluate the vulnerability of geo-disasters in the road slopes to avoid unfavorable site selection for subsequent road constructions. Some typical collector road slopes were used as the study area in Pingshan County, Hebei Province. By analyzing the landslide triggering factors, we determined classification criteria and proposed a comprehensive method for determining the weighting. The respective weighting was calculated by the AHP and CRITIC method, and the combination weighting was determined by the game theory method. The landslide susceptibility of collector roads was evaluated and mapped using the ArcGIS platform. The susceptibility map was validated using landslide field investigation. The validation results show the effectiveness of the susceptibility methods, given the good number of correctly classified landslides. The landslide susceptibility map could have a significant impact on reducing the vulnerability of infrastructure to landslides in Hebei Province, China.

Ultrasound-guided radiofrequency ablation (RFA) emerges as a minimally invasive strategy for papillary thyroid microcarcinoma (PTMC), offering advantages over traditional surgical approaches. RFA employs high-frequency electric currents under precise ultrasound guidance to ablate cancerous tissue. Clinical trials consistently demonstrate RFA’s efficacy in tumor control and patient-reported outcomes. However, long-term studies are essential to validate its durability and monitor for potential complications. Collaborative efforts among various medical disciplines ensure procedural accuracy and comprehensive postoperative care. Technological innovations, such as enhanced ultrasound imaging and temperature control, promise to refine RFA’s precision and effectiveness. Nevertheless, challenges persist, including the need for standardized protocols and comparative studies with traditional treatments. Future research should focus on long-term outcomes, patient selection criteria, and optimization of procedural techniques to solidify RFA’s role in PTMC management. RFA presents a promising avenue for PTMC treatment, warranting further investigation and refinement in clinical practice.

BackgroundKawasaki Disease (KD) is a pediatric vasculitic disorder characterized by systemic small vasculitis, notably coronary arteritis, with unclear pathogenesis. This explorative case-control study investigated the association between folic acid (FA), vitamin D3 (VD3), and vitamin B12 (VB12) levels and the different types of Kawasaki Disease, as well as the incidence of coronary artery lesions (CALs).MethodsIn this explorative case control study, 365 KD children admitted to our hospital from January 1, 2022 to June 30, 2023 were included as the KD group. Simultaneously, 365 healthy children who received physical examination during the same period were included as the control group. The KD group was divided into typical KD group and incomplete KD group (IKD group), CALs group and non-CALS group, and IVIG sensitive group and IVIG resistant group. The children with CALs were divided into small tumor group, medium tumor group and large tumor group. Serum levels of FA, VB12, and VD3 were compared across all groups.ResultsSerum levels of FA and VD3 were significantly decreased in both the KD and CALs groups (p

Enterococcus faecium is a microbiota species in humans that can modulate host immunity (Griffin and Hang, 2022), but has also acquired antibiotic resistance and is a major cause of hospital-associated infections (Van Tyne and Gilmore, 2014). Notably, diverse strains of E. faecium produce SagA, a highly conserved peptidoglycan hydrolase that is sufficient to promote intestinal immunity (Rangan et al., 2016; Pedicord et al., 2016; Kim et al., 2019) and immune checkpoint inhibitor antitumor activity (Griffin et al., 2021). However, the functions of SagA in E. faecium were unknown. Here, we report that deletion of sagA impaired E. faecium growth and resulted in bulged and clustered enterococci due to defective peptidoglycan cleavage and cell separation. Moreover, ΔsagA showed increased antibiotic sensitivity, yielded lower levels of active muropeptides, displayed reduced activation of the peptidoglycan pattern-recognition receptor NOD2, and failed to promote cancer immunotherapy. Importantly, the plasmid-based expression of SagA, but not its catalytically inactive mutant, restored ΔsagA growth, production of active muropeptides, and NOD2 activation. SagA is, therefore, essential for E. faecium growth, stress resistance, and activation of host immunity.

The carbon storage potential of planted shelterbelts was gradually recognized in recent years, but there was a lack of shelterbelt knowledge for carbon inventory analyses because of their narrow linear feature and extensive distribution. Considering its own characteristics of the shelterbelt, this paper proposed a new remote sensing model for estimating the carbon storage of farmland shelterbelt (CSBelt) based on the single tree carbon storage and tree numbers. In this model, the single tree carbon storage model was established by shelterbelt age, which could be identified from time series images. Tree numbers of each shelterbelt, as another important parameter in the CSBelt model, was detected by numbers of rows, columns, and preservation rate, which were monitored by high resolution remote sensing image and geographic information system method. Finally, overall accuracy (OA), mean absolute error (MAE), and mean error (ME) was used to validate the remotely identified data. The results showed that, the OA of the single tree carbon storage was 80.4% within the error range of 0.05 MgC/tree, the MAE was 0.036 MgC/tree, and ME was 0.020 MgC/tree; the OA of tree numbers was 71.7% within the error range of 100 trees/km, the MAE was 94 trees/km, and ME was 73 trees/km; the OA of shelterbelt carbon storage was 82.6% within the error range of 100 MgC/km, the MAE was 49.63 MgC/km, and ME was 33.78 MgC/km. Compared to other carbon storage models, this model requires fewer parameters and is not restricted by the stand conditions, which has better universality and realizability. This research is helpful for the accurate assessment of shelterbelt ecosystem carbon storage, which is of great significance for predicting climate change and formulating strategies. The results of this research will also provide data support for shelterbelt management on a regional scale.

The presence of asymptomatic carriers, often unrecognized as infectious disease vectors, complicates epidemic management, particularly when inter-community migrations are involved. We introduced a SAIR (susceptible-asymptomatic-infected-recovered) infectious disease model within a network framework to explore the dynamics of disease transmission amid asymptomatic carriers. This model facilitated an in-depth analysis of outbreak control strategies in scenarios with active community migrations. Key contributions included determining the basic reproduction number, $ R_0 $, and analyzing two equilibrium states. Local asymptotic stability of the disease-free equilibrium is confirmed through characteristic equation analysis, while its global asymptotic stability is investigated using the decomposition theorem. Additionally, the global stability of the endemic equilibrium is established using the Lyapunov functional theory.

In environmental epidemiological research, extensive non-random environmental exposures and complex confounding biases pose significant challenges when attempting causal inference. In recent years, the introduction of causal inference methods into observational studies has provided a broader range of statistical tools for causal inference research in environmental epidemiology. The instrumental variable (IV) approach, as a causal inference technique for effectively controlling unmeasured confounding factors, has gradually found application in the field of environmental epidemiological research. This article reviewed the basic principles of IV and summarized the current research progress and limitations of applying IV for causal inference in environmental epidemiology. IV application in the field of environmental epidemiology is still in the initial stage. Rational use of IV and effective integration with other causal inference methods will become the focus of the development of causal inference in environmental epidemiology. The aim of this paper is to provide a methodological reference and basis for future studies involving causal inference to target population health effects of environmental exposures in China.

Abstract Background Several approaches are commonly used to estimate the effect of diet on changes of various intermediate disease markers in prospective studies, including “change-score analysis”, “concurrent change-change analysis” and “lagged change-change analysis”. Although empirical evidence suggests that concurrent change-change analysis is most robust, consistent, and biologically plausible, in-depth dissection and comparison of these approaches from a causal inference perspective is lacking. We intend to explicitly elucidate and compare the underlying causal model, causal estimand and interpretation of these approaches, intuitively illustrate it with directed acyclic graph (DAG), and further clarify strengths and limitations of the recommended concurrent change-change analysis through simulations. Methods Causal model and DAG are deployed to clarify the causal estimand and interpretation of each approach theoretically. Monte Carlo simulation is used to explore the performance of distinct approaches under different extents of time-invariant heterogeneity and the performance of concurrent change-change analysis when its causal identification assumptions are violated. Results Concurrent change-change analysis targets the contemporaneous effect of exposure on outcome (measured at the same survey wave), which is more relevant and plausible in studying the associations of diet and intermediate biomarkers in prospective studies, while change-score analysis and lagged change-change analysis target the effect of exposure on outcome after one-period timespan (typically several years). Concurrent change-change analysis always yields unbiased estimates even with severe unobserved time-invariant confounding, while the other two approaches are always biased even without time-invariant heterogeneity. However, concurrent change-change analysis produces almost linearly increasing estimation bias with violation of its causal identification assumptions becoming more serious. Conclusions Concurrent change-change analysis might be the most superior method in studying the diet and intermediate biomarkers in prospective studies, which targets the most plausible estimand and circumvents the bias from unobserved individual heterogeneity. Importantly, careful examination of the vital identification assumptions behind it should be underscored before applying this promising method.

Abstract Multivalent drugs targeting homo-oligomeric viral surface proteins, such as the SARS-CoV-2 trimeric spike (S) protein, have the potential to elicit more potent and broad-spectrum therapeutic responses than monovalent drugs by synergistically engaging multiple binding sites on viral targets. However, rational design and engineering of nanoscale multivalent protein drugs are still lacking. Here, we developed a computational approach to engineer self-assembling trivalent microproteins that simultaneously bind to the three receptor binding domains (RBDs) of the S protein. This approach involves four steps: structure-guided linker design, molecular simulation evaluation of self-assembly, experimental validation of self-assembly state, and functional testing. Using this approach, we first designed trivalent constructs of the microprotein miniACE2 (MP) with different trimerization scaffolds and linkers, and found that one of the constructs (MP-5ff) showed high trimerization efficiency, good conformational homogeneity, and strong antiviral neutralizing activity. With its trimerization unit (5ff), we then engineered a trivalent nanobody (Tr67) that exhibited potent and broad neutralizing activity against the dominant Omicron variants, including XBB.1 and XBB.1.5. Cryo-EM complex structure confirmed that Tr67 stably binds to all three RBDs of the Omicron S protein in a synergistic form, locking them in the “3-RBD-up” conformation that could block human receptor (ACE2) binding and potentially facilitate immune clearance. Therefore, our approach provides an effective strategy for engineering potent protein drugs against SARS-CoV-2 and other deadly coronaviruses. Graphical Abstract

In order to ensure a precisely controlled electro hydraulic servo system, a sliding mode control algorithm based on nonlinear disturbance observers (NDOB-SMC) is developed in this study. Firstly, the basic principles of hydraulic actuators and electro-hydraulic position servo control mathematics are studied, and theoretical models are utilized to derive the state equations of the controlled system. Furthermore, considering that the sliding mode control is invariant to external disturbances and parameter changes, it is designed to be resilient against the unreliable hydraulic position servo system. In the meanwhile, nonlinear disturbance observers are added to the system to offset its output and enhance tracking capabilities even more. The Lyapunov theory is used to demonstrate the stability of the control strategy. Finally, the efficacy and dynamic performance of the NDOB-SMC method are preliminary confirmed using the co-simulation platform of AMESim and Matlab/Simulink. The numerical simulation results show that the suggested approach offers greater control accuracy and improved robustness for hydraulic position servo systems when compared to the conventional PI and sliding mode control methods.

The monitoring and fault diagnosis of axle-box bearings in high-speed trains is crucial for ensuring safe train operations. The vibration signals of these bearings exhibit non-stationary and non-linear characteristics. To further enhance the accuracy of identifying rolling bearing faults, a fault diagnosis method is proposed. This method is based on the improved Dung Beetle Optimization (DBO) algorithm for optimizing Variational Mode Decomposition (VMD) combined with Stacked Sparse Autoencoder (SSAE). Firstly, the DBO algorithm is enhanced to improve its optimization precision and global optimization capability. It is then utilized for the adaptive selection of two parameters: the number of decomposition modes and the penalty factor in VMD. These improvements address issues such as mode mixing, signal loss, and excessive decomposition, which arise from poor parameter selection in the traditional VMD method. Subsequently, components of Intrinsic Mode Functions (IMFs) that are highly correlated with the original signal are selected. The time-domain and frequency-domain features of these IMF components are used to construct the dataset. The feature set is then inputted into the deep machine learning model SSAE for training and testing. Through diagnostic experiments on various types and levels of rolling bearing faults, the model demonstrates a higher rate of fault diagnosis recognition.

We propose the Enhanced Predictive Recurrent Neural Network (EnPredRNN) based on PredRNN to extend the period of spatio-temporal prediction. To better capture global spatial dependencies, we integrate the Self-Attention (SA) module into PredRNN’s basic unit, forming the Enhanced Long Short-Term Memory (EnLSTM). Aiming at the problem that the standard temporal memory state in PredRNN contains insufficient information about inter-frame motion, we propose the Enhanced Temporal Memory (ETM) by aggregating past multi-step temporal memory states. Aiming at the gradient vanishing problem in Recurrent Neural Networks (RNN), the Alleviating Gradient Vanishing (AGV) structure is used to construct the high-speed path that facilitates gradient propagation. Experimental results show that EnPredRNN effectively extends spatio-temporal prediction from ten to thirty time-steps.

Monitoring the actual surface deformation caused by subsurface fluid activities is crucial for comprehending the subsurface fluid mutation process. Incorporation of InSAR observations in a prior volume strain model can facilitate the estimation of subsurface fluid volumetric changes and three-dimensional (3-D) surface deformation. However, the model parameters, i.e., the thickness and depth of the subsurface fluid reservoir, are assumed to be known a priori. Therefore, it is impossible to acquire the precise model parameters in practice. Therefore, we proposed a novel approach for adaptive estimation of the model parameters by utilizing the black hole strategy method integrated with the particle swarm optimization algorithm. First, the performance of this method was tested through simulation experiments. The results suggest that the proposed method can precisely determine the model parameters and 3-D deformations of the subsurface fluids. Finally, the proposed model was tested using actual data from the Shale gas area in Texas and the Kilauea Caldera volcano in Hawaii, USA. For long-term, slow small deformations or sudden large deformations caused by the subsurface fluids, the proposed algorithm can obtain corresponding 3-D deformations, especially in the presence of incoherent regions, which can still obtain a complete 3-D deformation field.

The combination of mobile edge computing (MEC) and radio frequency-based wireless power transfer (WPT) presents a promising technique for providing sustainable energy supply and computing services at the network edge. This study considers a wireless-powered mobile edge computing system that includes a hybrid access point (HAP) equipped with a computing unit and multiple Internet of Things (IoT) devices. In particular, we propose a novel multi-user cooperation scheme to improve computation performance, where collaborative clusters are dynamically formed. Each collaborative cluster comprises a source device (SD) and an auxiliary device (AD), where the SD can partition the computation task into various segments for local processing, offloading to the HAP, and remote execution by the AD with the assistance of the HAP. Specifically, we aims to maximize the weighted sum computation rate (WSCR) of all the IoT devices in the network. This involves jointly optimizing collaboration, time and data allocation among multiple IoT devices and the HAP, while considering the energy causality property and the minimum data processing requirement of each device. Initially, an optimization algorithm based on the interior-point method is designed for time and data allocation. Subsequently, a priority-based iterative algorithm is developed to search for a near-optimal solution to the multi-user collaboration scheme. Finally, a deep learning-based approach is devised to further accelerate the algorithm’s operation, building upon the initial two algorithms. Simulation results show that the performance of the proposed algorithms is comparable to that of the exhaustive search method, and the deep learning-based algorithm significantly reduces the execution time of the algorithm.

Enhanced ultraviolet-B (UV-B) radiation promotes anthocyanin biosynthesis in leaves, flowers and fruits of plants. However, the effects and underlying mechanisms of enhanced UV-B radiation on the accumulation of anthocyanins in the tubers of potatoes (Solanum tuberosum L.) remain unclear. Herein, reciprocal grafting experiments were first conducted using colored and uncolored potatoes, demonstrating that the anthocyanins in potato tubers were synthesized in situ, and not transported from the leaves to the tubers. Furthermore, the enhanced UV-B radiation (2.5 kJ·m−2·d−1) on potato stems and leaves significantly increased the contents of total anthocyanin and monomeric pelargonidin and peonidin in the red-fleshed potato ‘21-1’ tubers, compared to the untreated control. A comparative transcriptomic analysis showed that there were 2139 differentially expressed genes (DEGs) under UV-B treatment in comparison to the control, including 1724 up-regulated and 415 down-regulated genes. The anthocyanin-related enzymatic genes in the tubers such as PAL, C4H, 4CL, CHS, CHI, F3H, F3’5’H, ANS, UFGTs, and GSTs were up-regulated under UV-B treatment, except for a down-regulated F3’H. A known anthocyanin-related transcription factor StbHLH1 also showed a significantly higher expression level under UV-B treatment. Moreover, six differentially expressed MYB transcription factors were remarkably correlated to almost all anthocyanin-related enzymatic genes. Additionally, a DEGs enrichment analysis suggested that jasmonic acid might be a potential UV-B signaling molecule involved in the UV-B-induced tuber biosynthesis of anthocyanin. These results indicated that enhanced UV-B radiation in potato stems and leaves induced anthocyanin accumulation in the tubers by regulating the enzymatic genes and transcription factors involved in anthocyanin biosynthesis. This study provides novel insights into the mechanisms of enhanced UV-B radiation that regulate the anthocyanin biosynthesis in potato tubers.

Abstract Objective Previous studies proved the effect of long-term exposure to air pollution or physical activity (PA) on the risk of systemic inflammation-induced multimorbidity (SIIM), while the evidence regarding their joint effects was rare, especially in low- and middle-income countries. Therefore, we aimed to examine the extent of interaction or joint relations of PA and air pollution with SIIM. Methods This study included 72,172 participants from China Multi-Ethnic Cohort.The average concentrations of ambient particulate matter pollutants (PM1, PM2.5, and PM10) were estimated using satellite-based random forest models. Self-reported information on a range of physical activities related to occupation, housework, commuting, and leisure activities was collected by an interviewer-administered questionnaire. A total of 11 chronic inflammatory systemic diseases were assessed based on self-reported lifetime diagnosis or medical examinations. SIIM was defined as having ≥ 2 chronic diseases related to systemic inflammation. Logistic regression models were used to assess the complex associations of air pollution particulate matter and PA with SIIM. Results We found positive associations between long-term air pollution particulates exposure and SIIM, with odds ratios (95%CI) of 1.07 (1.03 to 1.11), 1.18 (1.13 to 1.24), and 1.08 (1.05 to 1.12) per 10 µg/m3 increase in PM1, PM2.5, and PM10. No significant multiplicative interaction was found between ambient air pollutant exposure and PA on SIIM, whereas negative additive interaction was observed between long-term exposure to PM2.5 and PA on SIIM. The positive associations between low volume PA and SIIM were stronger among those exposed to high-level air pollution particulates. Compared with individuals engaged in high volume PA and exposed to low-level ambient air pollutants, those engaged in low volume PA and exposed to high-level ambient air pollutants had a higher risk of SIIM (OR = 1.49 in PM1 exposure, OR = 1.84 in PM2.5 exposure, OR = 1.19 in PM10 exposure). Conclusions Long-term (3 years average) exposure to PM1, PM2.5, and PM10 was associated with an increased risk of SIIM. The associations were modified by PA, highlighting PA’s importance in reducing SIIM for all people, especially those living in high-level air pollution regions.