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Abstract Purpose To explore the effects of a single dose of uridine adenosine tetraphosphate (Up4A) administered through the tail vein, on the blood pressure of mice. Methods The mice were separated into three groups: the Up4A group, the norepinephrine (NA) group, and the α, β-methylene adenosine triphosphate (α, β-meATP) group. Each group of mice were injected drugs through the tail vein at 1, 3, 10, and 30 nmol/kg doses in an ascending order. Additionally, six mice were injected Up4A through the tail vein at 20, 40, 60, and 80 nmol/kg doses in an ascending order. The administration intervals for each dose were 20 min. Results Mice in these groups experienced a rapid increase in blood pressure, reaching its peak within 10 s after drug administration. It took approximately 120 s for the blood pressure to return to baseline levels after the administration of the drugs in both the NA and α, β-meATP groups. After higher doses of Up4A were administered to the mice, their blood pressure exhibited biphasic changes. Initially, blood pressure of the mice rapidly dropped to a minimum within 10 s, then rose rapidly to a peak within 30 s. Subsequently, it gradually declined, taking around 10 min to return to the levels before the drug administration. Conclusion Compared to NA and α, β-meATP, Up4A, which contains purine and pyrimidine components, displayed a weaker blood pressure-elevating potency. Through its corresponding structure, Up4A exerted vasodilatory and vasoconstrictive effects throughout the entire experiment resulting in biphasic changes in blood pressure.

Several mitochondrial dysfunctions in obesity and diabetes include impaired mitochondrial membrane potential, excessive mitochondrial reactive oxygen species generation, reduced mitochondrial DNA, increased mitochondrial Ca2+ flux, and mitochondrial dynamics disorders. Mitophagy, specialized autophagy, is responsible for clearing dysfunctional mitochondria in physiological and pathological conditions. As a paradox, inhibition and activation of mitophagy have been observed in obesity and diabetes-related heart disorders, with both exerting bidirectional effects. Suppressed mitophagy is beneficial to mitochondrial homeostasis, also known as benign mitophagy. On the contrary, in most cases, excessive mitophagy is harmful to dysfunctional mitochondria elimination and thus is defined as detrimental mitophagy. In obesity and diabetes, two classical pathways appear to regulate mitophagy, including PTEN-induced putative kinase 1 (PINK1)/Parkin-dependent mitophagy and receptors/adapters-dependent mitophagy. After the pharmacologic interventions of mitophagy, mitochondrial morphology and function have been restored, and cell viability has been further improved. Herein, we summarize the mitochondrial dysfunction and mitophagy alterations in obesity and diabetes, as well as the underlying upstream mechanisms, in order to provide novel therapeutic strategies for the obesity and diabetes-related heart disorders.

Abstract The programmed death 1 (PD‐1)/programmed death ligand 1 (PD‐L1) axis inhibits T cell activity, impairing anti‐tumor immunity. Blocking this axis with therapeutic antibodies is one of the most promising anti‐tumor immunotherapies. It has long been recognized that PD‐1/PD‐L1 blockade reinvigorates exhausted T (TEX) cells already present in the tumor microenvironment (TME). However, recent advancements in high‐throughput gene sequencing and bioinformatic tools have provided researchers with a more granular and dynamic insight into PD‐1/PD‐L1 blockade‐responding cells, extending beyond the TME and TEX populations. This review provides an update on the cell identity, spatial distribution, and treatment‐induced spatiotemporal dynamics of PD‐1/PD‐L1 blockade responders. It also provides a synopsis of preliminary reports of potential PD‐1/PD‐L1 blockade responders other than T cells to depict a panoramic picture. Important questions to answer in further studies and the translational and clinical potential of the evolving understandings are also discussed.

Abstract As a key factor in determining testis size and sperm number, sertoli cells (SCs) play a crucial role in male infertility. Heat stress (HS) reduces SCs counts, negatively impacting nutrient transport and supply to germ cells, and leading to spermatogenesis failure in humans and animals. However, how HS affects the number of SCs remains unclear. We hypothesized that changes in SC metabolism contribute to the adverse effects of HS. In this study, we first observed an upregulation of arachidonic acid (AA), an unsaturated fatty acid after HS exposure by LC-MS/MS metabolome detection. By increasing ROS levels, expression of KEAP1 and NRF2 proteins as well as LC3 and LAMP2, 100 µM AA induced autophagy in SCs by activating oxidative stress (OS). We observed adverse effects of AA on mitochondria under HS with a decrease of mitochondrial number and an increase of mitochondrial membrane potential (MMP). We also found that AA alternated the oxygen transport and absorption function of mitochondria by increasing glycolysis flux and decreasing oxygen consumption rate as well as the expression of mitochondrial electron transport chain (ETC) proteins Complex I, II, V. However, pretreatment with 5 mM NAC (ROS inhibitor) and 2 µM Rotenone (mitochondrial ETC inhibitor) reversed the autophagy induced by AA. In summary, AA modulates autophagy in SCs during HS by disrupting mitochondrial ETC function, inferring that the release of AA is a switch-like response, and providing insight into the underlying mechanism of high temperatures causing male infertility.

Abstract Background The pathogenesis of memory impairment, a common complication of chronic neuropathic pain (CNP), has not been fully elucidated. Schwann cell (SC)-derived extracellular vesicles (EVs) contribute to remote organ injury. Here, we showed that SC-EVs may mediate pathological communication between SCs and hippocampal neurons in the context of CNP. Methods We used an adeno-associated virus harboring the SC-specific promoter Mpz and expressing the CD63-GFP gene to track SC-EVs transport. microRNA (miRNA) expression profiles of EVs and gain-of-function and loss-of-function regulatory experiments revealed that miR-142-5p was the main cargo of SC-EVs. Next, luciferase reporter gene and phenotyping experiments confirmed the direct targets of miR-142-5p. Results The contents and granule sizes of plasma EVs were significantly greater in rats with chronic sciatic nerve constriction injury (CCI)than in sham rats. Administration of the EV biogenesis inhibitor GW4869 ameliorated memory impairment in CCI rats and reversed CCI-associated dendritic spine damage. Notably, during CCI stress, SC-EVs could be transferred into the brain through the circulation and accumulate in the hippocampal CA1-CA3 regions. miR-142-5p was the main cargo wrapped in SC-EVs and mediated the development of CCI-associated memory impairment. Furthermore, α-actinin-4 (ACTN4), ELAV-like protein 4 (ELAVL4) and ubiquitin-specific peptidase 9 X-linked (USP9X) were demonstrated to be important downstream target genes for miR-142-5p-mediated regulation of dendritic spine damage in hippocampal neurons from CCI rats. Conclusion Together, these findings suggest that SCs-EVs and/or their cargo miR-142-5p may be potential therapeutic targets for memory impairment associated with CNP.

Abstract Background The impact of sodium intake on cardiovascular disease (CVD) health and mortality has been studied for decades, including the well-established association with blood pressure. However, non-linear patterns, dose–response associations, and sex differences in the relationship between sodium and potassium intakes and overall and cause-specific mortality remain to be elucidated and a comprehensive examination is lacking. Our study objective was to determine whether intake of sodium and potassium and the sodium–potassium ratio are associated with overall and cause-specific mortality in men and women. Methods We conducted a prospective analysis of 237,036 men and 179,068 women in the National Institutes of Health-AARP Diet and Health Study. Multivariable-adjusted Cox proportional hazard regression models were utilized to calculate hazard ratios. A systematic review and meta-analysis of cohort studies was also conducted. Results During 6,009,748 person-years of follow-up, there were 77,614 deaths, 49,297 among men and 28,317 among women. Adjusting for other risk factors, we found a significant positive association between higher sodium intake (≥ 2,000 mg/d) and increased overall and CVD mortality (overall mortality, fifth versus lowest quintile, men and women HRs = 1.06 and 1.10, Pnonlinearity

Surgery is one of the primary treatments for solid tumors. However, the incomplete resection of tumor cells and the immunosuppressive microenvironment make the issue of postsurgical tumor recurrence a great challenge. Furthermore, a wide range of requirements, including ensuring effective hemostasis, implementing prophylactic measures against infection, and promoting wound healing, were also raised in the postsurgical management of tumors. To fulfill these demands, multiple hydrogel local drug delivery systems (HLDDS) were developed recently. These HLDDS are expected to offer numerous advantages in the postsurgical management of tumors, such as achieving high local drug concentrations at the lesion, efficient delivery to surgical microcavities, mitigating systemic side effects, and addressing the diverse demand. Thus, in this review, a detailed discussion of the diverse demands of postsurgical management of tumors is provided. And the current publication trend on HLDDS in the postsurgical management of tumors is analyzed and discussed. Then, the applications of different types of HLDDS, in-situ HLDDS and non-in-situ HLDDS, in postsurgical management of tumors were introduced and summarized. Besides, the current problems and future perspectives are discussed. The review is expected to provide an overview of HLDDS in postsurgical management of tumors and promote their clinical application.

Background Chronic stress can induce stress-related hormones; norepinephrine (NE) is considered to have the highest potential in cancer. NE can stimulate the expression of hypoxia-inducible factor-1α (HIF-1α), which is associated with vascular endothelial growth factor (VEGF) secretion and tumor angiogenesis. However, the underlying mechanisms are poorly understood.Methods Tumor-bearing mice were subjected to chronic restraint stress and treated with normal saline, human monoclonal VEGF-A neutralizing antibody bevacizumab, or β-adrenergic receptor (β-AR) antagonist (propranolol). Tumor growth and vessel density were also evaluated. Human colorectal adenocarcinoma cells were treated with NE, propranolol, or the inhibitor of transforming growth factor-β (TGF-β) receptor Type I kinase (Ly2157299) in vitro. TGF-β1 in mouse serum and cell culture supernatants was quantified using ELISA. The expression of HIF-1α was measured using Real time-PCR and western blotting. Cell migration and invasion were tested.Results Chronic restraint stress attenuated the efficacy of bevacizumab and promoted tumor growth and angiogenesis in a colorectal tumor model. Propranolol blocked this effect and inhibited TGF-β1 elevation caused by chronic restraint stress or NE. NE upregulated HIF-1α expression, which was reversed by propranolol or Ly2157299. Propranolol and Ly2157199 blocked NE-stimulated cancer cell migration and invasion.Conclusions Our results demonstrate the effect of NE on tumor angiogenesis and the critical role of TGF-β1 signaling during this process. In addition, β-AR/TGF-β1 signaling/HIF-1α/VEGF is a potential signaling pathway. This study also indicates that psychosocial stress might be a risk factor which weakens the efficacy of anti-angiogenic therapy.

Climate-related disasters have been escalating worldwide, incurring major losses. Landslides have become one of the most destructive disasters, especially in China's mountainous areas. To address this, constructing emergency shelters and designing evacuation routes are critical to ensure public safety and minimize impacts on affected residents. This study proposes a novel two-phase, people-centric approach. The first phase applies stakeholder theory and risk economics to develop a landslide hazard assessment model considering vulnerable populations. The model effectively classified 28 landslide points in Bazhou Town, with 35.71 % deemed high-risk and low-risk 64.29 %, reflecting the model's comprehensive risk differentiation capability. The second phase utilizes public choice theory to construct a bi-level multiple objective programming (BLMOP) model addressing conflicting government and resident goals. The algorithm produced 4 Pareto-optimal shelter plans for each village assessed, results demonstrate the proposed approach generates shelter plans meeting government aims while maximizing resident satisfaction, accounting for local conditions. Grounded in field data and a people-focused lens, this two-stage methodology provides a multiple objective optimization framework balancing stakeholder need. A case study of Bazhou Town validates the method's effectiveness.

Summary: Nanoparticles have shown great potential for tumor targeting delivery via enhanced permeability and retention effect. However, the tumor mechanical microenvironment, characterized by dense extracellular matrix (ECM), high tumor stiffness and solid stress, leads to only 0.7% of administered dose accumulating in solid tumors and even fewer (∼0.0014%) reaching tumor cells, limiting the therapeutic efficacy of nanoparticles. Furthermore, the tumor mechanical microenvironment can regulate tumor cell stemness, promote tumor invasion, metastasis and reduce treatment efficacy. In this review, methods detecting the mechanical are introduced. Strategies for modulating the mechanical microenvironment including elimination of dense ECM by physical, chemical and biological methods, disruption of ECM formation, depletion or inhibition of cancer-associated fibroblasts, are then summarized. Finally, prospects and challenges for further clinical applications of mechano-modulating strategies to enhance the therapeutic efficacy of nanomedicines are discussed. This review may provide guidance for the rational design and application of nanoparticles in clinical settings.

To improve the prediction accuracy of chaotic time series and reconstruct a more reasonable phase space structure of the prediction network, we propose a convolutional neural network (CNN)-long short-term memory (LSTM) prediction model based on the incremental attention mechanism. Firstly, a traversal search is conducted through the traversal layer for finite parameters in the phase space. Then, an incremental attention layer is utilized for parameter judgment based on the dimension weight criteria (DWC). The phase space parameters that best meet DWC are selected and fed into the input layer. Finally, the constructed CNN-LSTM network extracts spatiotemporal features and provides the final prediction results. The model is verified using Logistic, Lorenz, and sunspot chaotic time series, and the performance is compared from the two dimensions of prediction accuracy and network phase space structure. Additionally, the CNN-LSTM network based on incremental attention is compared with LSTM, CNN, recurrent neural network (RNN), and support vector regression (SVR) for prediction accuracy. The experiment results indicate that the proposed composite network model possesses enhanced capability in extracting temporal features and achieves higher prediction accuracy. Also, the algorithm to estimate the phase space parameter is compared with the traditional CAO, false nearest neighbor, and C–C, three typical methods for determining the chaotic phase space parameters. The experiments reveal that the phase space parameter estimation algorithm based on the incremental attention mechanism is superior in prediction accuracy compared with the traditional phase space reconstruction method in five networks, including CNN-LSTM, LSTM, CNN, RNN, and SVR.

Abstract Emerging and recurrent infectious diseases caused by human coronaviruses (HCoVs) continue to pose a significant threat to global public health security. In light of this ongoing threat, the development of a broad-spectrum drug to combat HCoVs is an urgently priority. Herein, we report a series of anti-pan-coronavirus ssDNA aptamers screened using Systematic Evolution of Ligands by Exponential Enrichment (SELEX). These aptamers have nanomolar affinity with the nucleocapsid protein (NP) of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and also show excellent binding efficiency to the N proteins of both SARS, MERS, HCoV-OC43 and -NL63 with affinity KD values of 1.31 to 135.36 nM. Such aptamer-based therapeutics exhibited potent antiviral activity against both the authentic SARS-CoV-2 prototype strain and the Omicron variant (BA.5) with EC50 values at 2.00 nM and 41.08 nM, respectively. The protein docking analysis also evidenced that these aptamers exhibit strong affinities for N proteins of pan-coronavirus and other HCoVs (−229E and -HKU1). In conclusion, we have identified six aptamers with a high pan-coronavirus antiviral activity, which could potentially serve as an effective strategy for preventing infections by unknown coronaviruses and addressing the ongoing global health threat.

This paper proposes a novel relay algorithm to optimize the communication throughput of unmanned aerial vehicle (UAV) mobile relay formations while considering the challenges posed by obstacle avoidance, channel complexity, high dynamics of UAVs, and real-time mission requirements. To tackle the non-convex nature of this problem, we develop the unscented Kalman filter and hybrid particle swarm optimization (UKF-HPSO) algorithm. Initially, real-time prediction of the source and destination of UAV positions is accomplished using the UKF. Subsequently, these predicted coordinates serve as inputs for achieving the optimal deployment of relay UAVs under the constraints imposed by HPSO. The superiority of the UKF-HPSO algorithm compared to baseline approaches is demonstrated through extensive simulations. System throughput is effectively optimized while maintaining real-time performance by our proposed algorithm, which addresses the unique challenges of UAV communication in dynamic environments.

Nuclear transporter importin-β1 is emerging as an attractive target by virtue of its prevalence in many cancers. However, the lack of druggable inhibitors restricts its therapeutic proof of concept. In the present work, we optimized a natural importin-β1 inhibitor DD1 to afford an improved analog DD1-Br with better tolerability (>25 folds) and oral bioavailability. DD1-Br inhibited the survival of castration-resistant prostate cancer (CRPC) cells with sub-nanomolar potency and completely prevented tumor growth in resistant CRPC models both in monotherapy (0.5 mg/kg) and in enzalutamide-combination therapy. Mechanistic study revealed that by targeting importin-β1, DD1-Br markedly inhibited the nuclear accumulation of multiple CRPC drivers, particularly AR-V7, a main contributor to enzalutamide resistance, leading to the integral suppression of downstream oncogenic signaling. This study provides a promising lead for CRPC and demonstrates the potential of overcoming drug resistance in advanced CRPC via targeting importin-β1.

This paper utilizes prevalent deep learning techniques, such as Convolutional Neural Networks (CNNs) and Residual Neural Networks (ResNets), along with the well-established machine learning technique, Random Forest, to efficiently distinguish between common lithologies including coal, sandstone, limestone, and others. This approach is highly significant for resource extraction—such as coal, oil, natural gas, and groundwater—by streamlining the process and minimizing the need for the time-consuming manual interpretation of geophysical logging data. The natural gamma ray, density, and resistivity log data were collected from 22 wells in the mountainous region of Southern Sichuan, China, yielding approximately 70,000 samples for developing lithofacies prediction models. All the models achieved around 80% accuracy in classifying carbonaceous lithologies and up to 88% accuracy in predicting other lithologies. The trained models were applied to the logging data in the validation dataset, and the outputs were validated against geological core data, showing overall consistency, although variations in the classification results were observed across different wells. These findings suggest that deep learning techniques have the potential to develop a general model for effectively handling lithology classification with well logging data.

Abstract Given the escalating prevalence of electromagnetic pollution, there is an urgent need for the development of high‐performance electromagnetic interference (EMI) shielding materials. Herein, wood‐based electromagnetic shielding materials have gained significant popularity due to their exceptional performance as building materials. In this study, a novel wood‐based composite with electromagnetic shielding properties is developed. Through the in situ growth of zeolitic imidazolate framework‐8 (ZIF‐8) crystals on wood fibers, coupled with uniform integration of carbon nanotubes (CNTs), a multifunctional composite named ZIF‐8/Poplar‐CNT composite is synthesized via a one‐step thermoforming process. The incorporation of CNTs endows the composites with excellent EMI shielding effectiveness (EMI SE). Among these elements, despite ZIF‐8 crystals not possessing intrinsic electromagnetic shielding functionality, their distinctive dodecahedral structure proves adept at scattering and reflecting electromagnetic waves within the composites, further improving the electromagnetic shielding effect. Hence, the ZIF‐8/Poplar‐CNT composite (56.95 dB) has ≈10 dB higher EMI SE compared to that of the composites without ZIF‐8 crystals. Meanwhile, ZIF‐8 crystals endow the materials with excellent tensile strength (54.84 MPa, enhanced by 4 times). Moreover, the introduction of Zn2+ provides superior antibacterial properties. The potential applications of ZIF‐8/Poplar‐CNT composites extend to diverse areas such as building decoration, electronic products, and medical equipment.

AimThis study was aimed to summarize the complications and their management associated with XEN gel stent implantation.MethodsA systematic review of literature was conducted using Medline (via PubMed), EMBASE, the Cochrane Library databases, and China National Knowledge Infrastructure, from their inception to February 1, 2024.ResultsA total of 48 studies published between 2017 and 2024 were identified and included in the systematic review, including 16 original studies (retrospective or prospective clinical studies), 28 case reports, and 4 case series, which followed patients for up to 5 years. Early postoperative complications of XEN gel stent implantation include hypotony maculopathy (1.9–4.6%), occlusion (3.9–8.8%), suprachoroidal hemorrhage (SCH), choroidal detachment (0–15%), conjunctival erosion, and exposure of the XEN gel stent (1.1–2.3%), wound and bleb leaks (2.1%) and malignant glaucoma (MG) (2.2%). Mid-postoperative complications of XEN gel stent implantation included migration of XEN (1.5%), ptosis (1.2%), endophthalmitis (0.4–3%), macular edema (1.5–4.3%), hypertrophic bleb (8.8%) and subconjunctival XEN gel stent fragmentation (reported in 2 cases). Late postoperative complications reported in cases included spontaneous dislocation and intraocular degradation.ConclusionXEN gel stent implantation is a minimally invasive glaucoma surgery (MIGS) procedure for glaucoma, known for its potential to minimize tissue damage and reduce surgical duration. However, it is crucial to note that despite these advantages, there remains a risk of severe complications, including endophthalmitis, SCH, and MG. Therefore, postoperative follow-up and early recognition of severe complications are essential for surgical management.

Abstract N6‐methyladenosine (m6A) modification orchestrates cancer formation and progression by affecting the tumor microenvironment (TME). For hepatocellular carcinoma (HCC), immune evasion and angiogenesis are characteristic features of its TME. The role of YTH N6‐methyladenosine RNA binding protein 2 (YTHDF2), as an m6A reader, in regulating HCC TME are not fully understood. Herein, it is discovered that trimethylated histone H3 lysine 4 and H3 lysine 27 acetylation modification in the promoter region of YTHDF2 enhanced its expression in HCC, and upregulated YTHDF2 in HCC predicted a worse prognosis. Animal experiments demonstrated that Ythdf2 depletion inhibited spontaneous HCC formation, while its overexpression promoted xenografted HCC progression. Mechanistically, YTHDF2 recognized the m6A modification in the 5′‐untranslational region of ETS variant transcription factor 5 (ETV5) mRNA and recruited eukaryotic translation initiation factor 3 subunit B to facilitate its translation. Elevated ETV5 expression induced the transcription of programmed death ligand‐1 and vascular endothelial growth factor A, thereby promoting HCC immune evasion and angiogenesis. Targeting YTHDF2 via small interference RNA‐containing aptamer/liposomes successfully both inhibited HCC immune evasion and angiogenesis. Together, this findings reveal the potential application of YTHDF2 in HCC prognosis and targeted treatment.

Abstract Kidney fibrosis is a common fate of chronic kidney diseases (CKDs), eventually leading to renal dysfunction. Yet, no effective treatment for this pathological process has been achieved. During the bioassay‐guided chemical investigation of the medicinal plant Wikstroemia chamaedaphne, a daphne diterpenoid, daphnepedunin A (DA), is characterized as a promising anti‐renal fibrotic lead. DA shows significant anti‐kidney fibrosis effects in cultured renal fibroblasts and unilateral ureteral obstructed mice, being more potent than the clinical trial drug pirfenidone. Leveraging the thermal proteome profiling strategy, cell division cycle 42 (Cdc42) is identified as the direct target of DA. Mechanistically, DA targets to reduce Cdc42 activity and down‐regulates its downstream phospho‐protein kinase Cζ(p‐PKCζ)/phospho‐glycogen synthase kinase‐3β (p‐GSK‐3β), thereby promoting β‐catenin Ser33/37/Thr41 phosphorylation and ubiquitin‐dependent proteolysis to block classical pro‐fibrotic β‐catenin signaling. These findings suggest that Cdc42 is a promising therapeutic target for kidney fibrosis, and highlight DA as a potent Cdc42 inhibitor for combating CKDs.

Abstract Immune checkpoint blockade (ICB) therapy, particularly antibodies targeting the programmed death receptor 1 (PD-1) and its ligand (PD-L1), has revolutionized cancer treatment. However, its efficacy as a standalone therapy remains limited. Although ICB therapy in combination with chemotherapy shows promising therapeutic responses, the challenge lies in amplifying chemotherapy-induced antitumor immunity effectively. This relies on efficient drug delivery to tumor cells and robust antigen presentation by dendritic cells (DCs). Here, we developed tumor-repopulating cell (TRC)-derived microparticles with exceptional tumor targeting to deliver doxorubicin (DOX@3D-MPs) for improve anti-PD-1 therapy. DOX@3D-MPs effectively elicit immunogenic tumor cell death to release sufficient tumor antigens. Heat shock protein 70 (HSP70) overexpressed in DOX@3D-MPs contributes to capturing tumor antigens, promoting their phagocytosis by DCs, and facilitating DCs maturation, leading to the activation of CD8+ T cells. DOX@3D-MPs significantly enhance the curative response of anti-PD-1 treatment in large subcutaneous H22 hepatoma, orthotopic 4T1 breast tumor and Panc02 pancreatic tumor models. These results demonstrate that DOX@3D-MPs hold promise as agents to improve the response rate to ICB therapy and generate long-lasting immune memory to prevent tumor relapse.

Abstract Background GEM (GTP-binding protein overexpressed in skeletal muscle) is one of the atypical small GTPase subfamily members recently identified as a regulator of cell differentiation. Abnormal chondrogenesis coupled with an imbalance in the turnover of cartilaginous matrix formation is highly relevant to the onset and progression of osteoarthritis (OA). However, how GEM regulates chondrogenic differentiation remains unexplored. Methods Cartilage tissues were obtained from OA patients and graded according to the ORASI and ICRS grading systems. The expression alteration of GEM was detected in the Grade 4 cartilage compared to Grade 0 and verified in OA mimic culture systems. Next, to investigate the specific function of GEM during these processes, we generated a Gem knockdown (Gem-Kd) system by transfecting siRNA targeting Gem into ATDC5 cells. Acan, Col2a1, Sox9, and Wnt target genes of Gem-Kd ATDC5 cells were detected during induction. The transcriptomic sequencing analysis was performed to investigate the mechanism of GEM regulation. Wnt signaling pathways were verified by real-time PCR and immunoblot analysis. Finally, a rescue model generated by treating Gem-KD ATDC5 cells with a Wnt signaling agonist was established to validate the mechanism identified by RNA sequencing analysis. Results A decreased expression of GEM in OA patients’ cartilage tissues and OA mimic chondrocytes was observed. While during chondrogenesis differentiation and cartilage matrix formation, the expression of GEM was increased. Gem silencing suppressed chondrogenic differentiation and the expressions of Acan, Col2a1, and Sox9. RNA sequencing analysis revealed that Wnt signaling was downregulated in Gem-Kd cells. Decreased expression of Wnt signaling associated genes and the total β-CATENIN in the nucleus and cytoplasm were observed. The exogenous Wnt activation exhibited reversed effect on Gem loss-of-function cells. Conclusion These findings collectively validated that GEM functions as a novel regulator mediating chondrogenic differentiation and cartilage matrix formation through Wnt/β-catenin signaling.

Abstract Using point cloud to reconstruct the 3D model of a substation is crucial for smart grid operation. Its main objective is to swiftly capture equipment point cloud data and align each device’s model within the large and noisy point cloud scene of the substation. However, substation reconstruction needs improvement due to the low efficiency of traditional noise-resistant clustering methods and challenges in accurately classifying similar-looking electrical equipment. This paper proposes an automatic modeling framework for large-scale substation point cloud scenes. Firstly, we reduce the substation scene’s dimensionality to improve clustering efficiency and establish relationships between data dimensions using a re-clustering algorithm. Next, a neural network is developed to identify various device types within clusters, even with limited subdivisions. Finally, a model library is employed to register standard models onto the target device’s point cloud, obtaining device types and orientations. Real substation data processing demonstrates the ability to rapidly extract devices from complex and noisy point cloud scenes, effectively avoiding missegmentation issues. The automatic modeling approach achieves a precise substation calculation rate of 92.86%.

Abstract The durable response rate to immune checkpoint blockade such as anti-programmed cell death-1 (PD-1) antibody remains relatively low in hepatocellular carcinoma (HCC), mainly depending on an immunosuppressive microenvironment with limited number of CD8+ T cells, especially stem-like CD8+ T cells, in tumor tissues. Here we develop engineered microparticles (MPs) derived from alpha-fetoprotein (AFP)-overexpressing macrophages to load resiquimod (R848@M2pep-MPsAFP) for enhanced anti-PD-1 therapy in HCC. R848@M2pep-MPsAFP target and reprogram immunosuppressive M2-like tumor-associated macrophages (TAMs) into M1-like phenotype. Meanwhile, R848@M2pep-MPsAFP-reprogrammed TAMs act as antigen-presenting cells, not only presenting AFP antigen to activate CD8+ T cell-mediated antitumor immunity, but also providing an intra-tumoral niche to maintain and differentiate stem-like CD8+ T cells. Combination immunotherapy with anti-PD-1 antibody generates strong antitumor immune memory and induces abundant stem-like CD8+ T cell proliferation and differentiation to terminally exhausted CD8+ T cells for long-term immune surveillance in orthotopic and autochthonous HCC preclinical models in male mice. We also show that the R848-loaded engineered MPs derived from macrophages overexpressing a model antigen ovalbumin (OVA) can improve anti-PD-1 therapy in melanoma B16-OVA tumor-bearing mice. Our work presents a facile and generic strategy for personalized cancer immunotherapy to boost anti-PD-1 therapy.

Abstract Adipose tissue is essential for maintaining systemic metabolic homeostasis through traditional metabolic regulation, endocrine crosstalk, and extracellular vesicle production. Adipose dysfunction is a risk factor for cardiovascular diseases. The heart is a traditional pump organ. However, it has recently been recognized to coordinate interorgan cross-talk by providing peripheral signals known as cardiokines. These molecules include specific peptides, proteins, microRNAs and novel extracellular vesicle-carried cargoes. Current studies have shown that generalized cardiokine-mediated adipose regulation affects systemic metabolism. Cardiokines regulate lipolysis, adipogenesis, energy expenditure, thermogenesis during cold exposure and adipokine production. Moreover, cardiokines participate in pathological processes such as obesity, diabetes and ischemic heart injury. The underlying mechanisms of the cardiac-to-adipose axis mediated by cardiokines will be further discussed to provide potential therapeutic targets for metabolic diseases and support a new perspective on the need to correct adipose dysfunction after ischemic heart injury.

Background: Psoriasis is a common, chronic, and multifactorial inflammatory cutaneous disorder that involves genetic and epigenetic factors. N6-methyladenosine methylation (m6A) is the most prevalent RNA modification implicated in various diseases; however, its role in psoriasis still needs to be further explored. We aimed to explore the mechanisms underlying the effects of m6A in psoriasis pathogenesis, prompting new therapeutic targets. Methods: Three psoriasis-related datasets, including GSE155702, GSE109248, and GSE142582, were collected. Differentially m6A methylated genes (DMGs) between psoriasis lesions of psoriasis patients and healthy skin controls were identified from the GSE155702 dataset, and corresponding Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Differentially expressed genes (DEGs) and the common DEGs between the two groups were screened from the GSE109248 and GSE142582 datasets; the expression and interactions of the m6A regulators were analyzed. The m6A levels of total RNAs and the protein expression levels of METTL3, WTAP, ALKBH5, FTO, and METTL14 in imiquimod (IMQ)-induced psoriasiform lesions were evaluated. Results: 66 significantly upregulated and 381 significantly downregulated m6A peaks were identified, corresponding to 414 genes which were particularly associated with cell and tissue development processes and cell cycle related items. 271 common DEGs were identified, associating with keratinocyte differentiation, epidermis development, cytokine-cytokine receptor interaction, and fatty acid metabolic processes. 15 crucial m6A related differentially expressed genes were obtained after the intersection of the DMGs and common DEGs, including NEU2, GALNT6, MTCL1, DOC2B, CAMK2N1, SNTB1, RNF150, CGNL1, CCDC102A, MEOX2, EEF2K, OBSCN, SLC46A2, CCDC85A, and DACH1. In addition, we found that m6A methylation and these five m6A regulators were both upregulated in psoriatic lesions. Conclusions: It revealed that psoriasis pathophysiological processes encompass m6A epigenetic alterations, and that m6A alterations may specifically influence cell proliferation and neural regulation, and closely associated with osteoarticular involvement and metabolic syndrome in psoriasis.

The probing depth of the transient electromagnetic method (TEM) refers to the depth range at which the underground conductivity changes can be effectively detected. It typically ranges from tens of meters to several kilometers and is influenced by factors such as instrument parameters and the conductivity of the subsurface structure. Rapid and accurate probing depth is useful for the selection of appropriate inversion parameters and improving survey accuracy. However, mainstream methods suffer from issues such as low computational precision, large uncertainties, or high computational requirements, making them unsuitable for processing massive airborne electromagnetic data. In this study, we propose a prediction model based on deep learning that can directly compute the probing depth from the TEM responses, and its effectiveness and accuracy are validated through synthetic models and field measurements. We compared the performance of classic deep learning models, including CNN, RESNET, and RNN, and found that RNN performed the best overall on both synthetic and field data. Furthermore, we apply this algorithm to deep learning-based ATEM inversion by constraining the one-dimensional resistivity model depths in the training set, to reduce the non-uniqueness of the inversion, accelerate the convergence, and improve its prediction accuracy.

Integrated pest management relies upon mutual compatibility among pest control tactics. The fruit-boring moths Carposina sasakii and Grapholita molesta can be devastating pests of pome and stone fruit production. Trichogramma dendrolimi parasitizes the eggs of these pests, preventing their eclosion, but its efficacy can be reduced by other pest control tactics. We tested T. dendrolimi attraction to five colors, and moth attraction to six colors, in laboratory choice tests, and thereafter deployed yellow sticky cards in tandem with releases of T. dendrolimi in field trials in a pear orchard. Yellow sticky cards deployed at high density trapped T. dendrolimi and reduced their numbers post-release. They also trapped adult G. molesta, which appeared to compensate for reduced egg parasitism on this species, but not on C. sasakii, which had higher abundance in plots with yellow sticky cards. The cards also captured adult lacewings, likely reducing their numbers in the field, but did not capture large numbers of lady beetles. The results suggest that yellow sticky cards can be used at high density to control aphids, psyllids and leafhoppers in early spring (March and April) when natural enemies are in low numbers, then removed in May so as not to interfere with augmentative releases of T. dendrolimi that must be timed to coincide with peak flights of fruit-boring moths. This strategy should enhance the compatibility of yellow sticky cards with egg parasitoid releases.

The Xinjiang Uygur Autonomous Region (Xinjiang) borders eight countries and has a complex geographic environment. There are almost 45.696 million herded sheep in Xinjiang, which occupies 13.80% of China’s sheep farming industry. However, there is a scarcity of reports investigating the role of sheep or ticks in Xinjiang in transmitting tick-borne diseases (TBDs). A total of 894 ticks (298 tick pools) were collected from sheep in southern Xinjiang. Out of the 298 tick pools investigated in this study, Rhipicephalus turanicus (Rh. turanicus) and Hyalomma anatolicum (H. anatolicum) were identified through morphological and molecular sequencing. In the southern part of Xinjiang, 142 (47.65%), 86 (28.86%), and 60 (20.13%) tick pools were positive for Rickettsia spp., Theileria spp., and Anaplasma spp., respectively. Interestingly, the infection rate of Rickettsia spp. (73%, 35.10%, and 28.56–41.64%) was higher in Rh. turanicus pools than in H. anatolicum pools (4%, 4.44%, and 0.10–8.79%) in this study. Fifty-one tick pools were found to harbor two pathogens, while nineteen tick pools were detected to have the three pathogens. Our findings indicate the presence of Rickettsia spp., Theileria spp., and Anaplasma spp. potentially transmitted by H. anatolicum and Rh. turanicus in sheep in southern Xinjiang, China.

This study introduces an advanced dual-mode compound attitude control framework for reusable launch vehicles (RLVs), underpinned by an enhanced particle swarm optimization (PSO) algorithm. This innovative strategy is tailored to meet the stringent demands for precision and robust anti-interference capabilities across the entire flight envelope of RLVs. The research commences with the formulation of a comprehensive attitude dynamics model and diverse heterogeneous actuator representations, meticulously crafted to reflect the distinct phases of RLV flight. Building upon this foundation, a synergistic control paradigm is engineered, integrating PID and fuzzy PID controllers and dynamically adjusting the inertia weights and learning factors of the PSO algorithm to achieve the balance between global and local optimization performance, complemented by a refined fitness evaluation function. The crux of the study is the application of an upgraded PSO algorithm to fine-tune the controllers’ weighting coefficients, culminating in an optimized dual-mode compound attitude control system. A series of comparative simulation analyses are thoroughly executed to appraise the system’s responsiveness, stability, precision, and resilience to interference. The simulation outcomes demonstrate an average reduction of 42.21% in step response overshoot, an 18.52% decrease in settling time, a 53.18% decline in steady-state error, a 56.80% drop in the maximum deviation value, a 55.82% improvement in recovery speed, and a 75.61% enhancement in tracking precision for the proposed controller. The findings clearly verify the superior performance of the proposed control system, affirming its contribution to the advancement of RLV attitude control. The proposed controller holds promising potential for real application in attitude control systems and is poised to augment the reliability and mission success rate of RLVs under intricate flight scenarios.