Search

Abstract Bystander‐killing payloads can significantly overcome the tumor heterogeneity issue and enhance the clinical potential of antibody‐drug conjugates (ADC), but the rational design and identification of effective bystander warheads constrain the broader implementation of this strategy. Here, graph attention networks (GAT) are constructed for a rational bystander killing scoring model and ADC construction workflow for the first time. To generate efficient bystander‐killing payloads, this model is utilized for score‐directed exatecan derivatives design. Among them, Ed9, the most potent payload with satisfactory permeability and bioactivity, is further used to construct ADC. Through linker optimization and conjugation, novel ADCs are constructed that perform excellent anti‐tumor efficacy and bystander‐killing effect in vivo and in vitro. The optimal conjugate T‐VEd9 exhibited therapeutic efficacy superior to DS‐8201 against heterogeneous tumors. These results demonstrate that the effective scoring approach can pave the way for the discovery of novel ADC with promising bystander payloads to combat tumor heterogeneity.

Grapefruit (Citrus × paradisi Macf.) peel, a by-product of the citrus-processing industry, possesses an important economic value due to the richness of bioactive compounds. In this study, boron-linked covalent organic frameworks integrated with molecularly imprinted polymers (CMIPs) were developed via a facile one-pot bulk polymerization approach for the selective extraction of naringenin from grapefruit peel extract. The obtained CMIPs possessed a three-dimensional network structure with uniform pore size distribution, large surface areas (476 m2/g), and high crystallinity. Benefiting from the hybrid functional monomer APTES-MAA, the acylamino group can coordinate with the boronate ligands of the boroxine-based framework to form B-N bands, facilitating the integration of imprinted cavities with the aromatic skeleton. The composite materials exhibited a high adsorption capacity of 153.65 mg/g, and a short adsorption equilibrium time of 30 min for naringenin, together with favorable selectivity towards other flavonoid analogues. Additionally, the CMIPs captured the template molecules through π–π* interaction and hydrogen bonding, as verified by FT-IR and XPS. Furthermore, they had good performance when employed to enrich naringenin in grapefruit peels extract compared with the common adsorbent materials including AB-8, D101, cationic exchange resin, and active carbon. This research highlights the potential of CMIPs composite materials as a promising alternative adsorbent for naringenin extraction from grapefruit peel.

While neuroblastoma accounts for 15% of childhood tumor-related deaths, treatments against neuroblastoma remain scarce and mainly consist of cytotoxic chemotherapeutic drugs. Currently, maintenance therapy of differentiation induction is the standard of care for neuroblastoma patients in clinical, especially high-risk patients. However, differentiation therapy is not used as a first-line treatment for neuroblastoma due to low efficacy, unclear mechanism, and few drug options. Through compound library screening, we accidently found the potential differentiation-inducing effect of AKT inhibitor Hu7691. The protein kinase B (AKT) pathway is an important signaling pathway for regulating tumorigenesis and neural differentiation, yet the relation between the AKT pathway and neuroblastoma differentiation remains unclear. Here, we reveal the anti-proliferation and neurogenesis effect of Hu7691 on multiple neuroblastoma cell lines. Further evidence including neurites outgrowth, cell cycle arrest, and differentiation mRNA marker clarified the differentiation-inducing effect of Hu7691. Meanwhile, with the introduction of other AKT inhibitors, it is now clear that multiple AKT inhibitors can induce neuroblastoma differentiation. Furthermore, silencing AKT was found to have the effect of inducing neuroblastoma differentiation. Finally, confirmation of the therapeutic effects of Hu7691 is dependent on inducing differentiation in vivo, suggesting that Hu7691 is a potential molecule against neuroblastoma. Through this study, we not only define the key role of AKT in the progression of neuroblastoma differentiation but also provide potential drugs and key targets for the application of differentiation therapies for neuroblastoma clinically.

Abstract Immune checkpoint blockade therapies targeting the PD-L1/PD-1 axis have demonstrated clear clinical benefits. Improved understanding of the underlying regulatory mechanisms might contribute new insights into immunotherapy. Here, we identify transmembrane and ubiquitin-like domain-containing protein 1 (TMUB1) as a modulator of PD-L1 post-translational modifications in tumor cells. Mechanistically, TMUB1 competes with HECT, UBA and WWE domain-containing protein 1 (HUWE1), a E3 ubiquitin ligase, to interact with PD-L1 and inhibit its polyubiquitination at K281 in the endoplasmic reticulum. Moreover, TMUB1 enhances PD-L1 N-glycosylation and stability by recruiting STT3A, thereby promoting PD-L1 maturation and tumor immune evasion. TMUB1 protein levels correlate with PD-L1 expression in human tumor tissue, with high expression being associated with poor patient survival rates. A synthetic peptide engineered to compete with TMUB1 significantly promotes antitumor immunity and suppresses tumor growth in mice. These findings identify TMUB1 as a promising immunotherapeutic target.

Abstract High-grade B-cell lymphoma with translocations involving MYC and BCL2 or BCL6, usually referred to as double hit lymphoma (DHL), is an aggressive hematological malignance with distinct genetic features and poor clinical prognosis. Current standard chemoimmunotherapy fails to confer satisfying outcomes and few targeted therapeutics are available for the treatment against DHL. Recently, the delineating of the genetic landscape in tumors has provided insight into both biology and targeted therapies. Therefore, it is essential to understand the altered signaling pathways of DHL to develop treatment strategies with better clinical benefits. Herein, we summarized the genetic alterations in the two DHL subtypes (DHL-BCL2 and DHL-BCL6). We further elucidate their implications on cellular processes, including anti-apoptosis, epigenetic regulations, B-cell receptor signaling, and immune escape. Ongoing and potential therapeutic strategies and targeted drugs steered by these alterations were reviewed accordingly. Based on these findings, we also discuss the therapeutic vulnerabilities that coincide with these genetic changes. We believe that the understanding of the DHL studies will provide insight into this disease and capacitate the finding of more effective treatment strategies.

Cinnamaldehyde (CA) is a promising antimicrobial agent for the preservation of fruits and vegetables due to its excellent antibacterial activity. The application is however, limited by its unstable and volatile properties. A biocompatible carbon dots hybrid γ-cyclodextrin-based metal organic framework (CD/MOF) was developed by the seed-mediated method to improve the encapsulation and sustained continuous release of CA. CD/MOF-0.5 exhibited a CA loading efficiency of 28.42% and a sustained release duration time of more than 15 days at 8 oC. The release kinetics results showed that the release behavior of CD/MOF-0.5 fitted well with the Korsmeyer–Peppas release kinetics model, indicating that its sustained release is mainly controlled by diffusion. Both the Fourier-transform infrared spectroscopy and X-ray photoelectron spectroscopy analyses revealed that CD/MOF-0.5 and CA molecules were linked by hydrogen bonds. Due to the high sustained release performance, CA-loaded CD/MOF-0.5 considerably inhibited the growth of Escherichia coli, hence preventing the spoilage of fresh-cut cantaloupes. CD/MOF-0.5/CA treatment also maintained the qualities of the fresh-cut cantaloupes, prolonging their edibility to five days. This work provides a promising strategy for the prevention of spoilage in food industry.

Highly photoluminescent nitrogen and sulfur co-doped carbon dots (N,S-CDs) derived from the granatum as carbon source and ammonium persulfate as passivator was developed as a probe for the detection of tetracyclines (DOC, TC, OTC, and CTC) in milk products. Transmission electron microscopy (TEM) exhibited that the as-prepared N,S-CDs were quasi-spherical particles with an average diameter of ∼5.5 nm. X-ray diffraction (XRD) showed that the N,S-CDs possessed a graphitic-like structure. Fourier-transform infrared (FT-IR) and X-ray photoelectron spectroscopy (XPS) confirmed the existence of -OH, -COOH, R-SO3H and -NH2 on the surface of N,S-CDs. The amidation reaction between the -COOH of N,S-CDs and -CO-NH2 of TCs combined with the inner-filter effect resulted in the fluorescence (FL) quenching. The FL quenching efficiencies reached 98.5%, 51.6%, 46.5%, and 39.4% after introducing DOC, TC, OTC, and CTC. Highly fluoresce quenched for DOC was ascribed to the existence of H on C6 of DOC induced weak electrostatic repulsion between N,S-CDs and DOC. The nanosensor allowed the detecting TCs in the range of 0.08∼3.05 µmol L-1 for DOC with the detection limit of 2.87 nmol L-1, 0.32∼5.85 µmol L-1 for TC with 14.57 nmol L-1, 0.31∼6.29 µmol L-1 for OTC with 16.99 nmol L-1, and 0.30∼6.06 µmol L-1 for CTC with 17.11 nmol L-1 (S/N=3). Recoveries of 83.93∼126.22% and RSDs of 1.11%∼5.83% were achieved for TCs detection in milk product samples, indicating the optical sensor provided an alternative strategy for real applications in food safety control.

Abstract Background Alternaria sp. MG1, an endophytic fungus isolated from grape, is a native producer of resveratrol, which has important application potential. However, the metabolic characteristics and physiological behavior of MG1 still remains mostly unraveled. In addition, the resveratrol production of the strain is low. Thus, the whole-genome sequencing is highly required for elucidating the resveratrol biosynthesis pathway. Furthermore, the metabolic network model of MG1 was constructed to provide a computational guided approach for improving the yield of resveratrol. Results Firstly, a draft genomic sequence of MG1 was generated with a size of 34.7 Mbp and a GC content of 50.96%. Genome annotation indicated that MG1 possessed complete biosynthesis pathways for stilbenoids, flavonoids, and lignins. Eight secondary metabolites involved in these pathways were detected by GC–MS analysis, confirming the metabolic diversity of MG1. Furthermore, the first genome-scale metabolic network of Alternaria sp. MG1 (named iYL1539) was reconstructed, accounting for 1539 genes, 2231 metabolites, and 2255 reactions. The model was validated qualitatively and quantitatively by comparing the in silico simulation with experimental data, and the results showed a high consistency. In iYL1539, 56 genes were identified as growth essential in rich medium. According to constraint-based analysis, the importance of cofactors for the resveratrol biosynthesis was successfully demonstrated. Ethanol addition was predicted in silico to be an effective method to improve resveratrol production by strengthening acetyl-CoA synthesis and pentose phosphate pathway, and was verified experimentally with a 26.31% increase of resveratrol. Finally, 6 genes were identified as potential targets for resveratrol over-production by the recently developed methodology. The target-genes were validated using salicylic acid as elicitor, leading to an increase of resveratrol yield by 33.32% and the expression of gene 4CL and CHS by 1.8- and 1.6-fold, respectively. Conclusions This study details the diverse capability and key genes of Alternaria sp. MG1 to produce multiple secondary metabolites. The first model of the species Alternaria was constructed, providing an overall understanding of the physiological behavior and metabolic characteristics of MG1. The model is a highly useful tool for enhancing productivity by rational design of the metabolic pathway for resveratrol and other secondary metabolites.

Nuclear export protein 1 (XPO1), a member of the nuclear export protein-p (Karyopherin-P) superfamily, regulates the transport of “cargo” proteins. To facilitate this important process, which is essential for cellular homeostasis, XPO1 must first recognize and bind the cargo proteins. To inhibit this process, small molecule inhibitors have been designed that inhibit XPO1 activity through covalent binding. However, the scaffolds for these inhibitors are very limited. While virtual screening may be used to expand the diversity of the XPO1 inhibitor skeleton, enormous computational resources would be required to accomplish this using traditional screening methods. In the present study, we report the development of a hybrid virtual screening workflow and its application in XPO1 covalent inhibitor screening. After screening, several promising XPO1 covalent molecules were obtained. Of these, compound 8 performed well in both tumor cell proliferation assays and a nuclear export inhibition assay. In addition, molecular dynamics simulations were performed to provide information on the mode of interaction of compound 8 with XPO1. This research has identified a promising new scaffold for XPO1 inhibitors, and it demonstrates an effective and resource-saving workflow for identifying new covalent inhibitors.

Interleukin-1 receptor associated kinase-1 (IRAK1) exhibits important roles in inflammation, infection, and autoimmune diseases; however, only a few inhibitors have been discovered. In this study, at first, a discriminatory structure-based virtual screening (SBVS) was employed, but only one active compound (compound 1, IC50 = 2.25 μM) was identified. The low hit rate (2.63%) which derives from the weak discriminatory power of docking among high-scored molecules was observed in our virtual screening (VS) process for IRAK1 inhibitor. Furthermore, an artificial intelligence (AI) method, which employed a support vector machine (SVM) model, integrated information of molecular docking, pharmacophore scoring and molecular descriptors was constructed to enhance the traditional IRAK1-VS protocol. Using AI, it was found that VS of IRAK1 inhibitors excluded by over 50% of the inactive compounds, which could significantly improve the prediction accuracy of the SBVS model. Moreover, four active molecules (two of which exhibited comparative IC50 with compound 1) were accurately identified from a set of highly similar candidates. Amongst, compounds with better activity exhibited good selectivity against IRAK4. The AI assisted workflow could serve as an effective tool for enhancement of SBVS.

Metastatic cancer is considered a fatal progression of cancer worldwide. It has been shown that a key player in this scenario is the CXC chemokine receptor 2 (CXCR2). To identify novel CXCR2 antagonists, a pharmacophore model was built with the HipHop program by screening a database containing compounds which were designed based on the known structure–activity relationship (SAR) of the diarylurea series CXCR2 antagonists. Compound 1a bearing the novel skeleton was selected from database screening and subjected to the in vitro biological test which showed a moderate CXCR2 antagonist potential. With further modification and exploration of SAR, compound 1e demonstrated improved CXCR2 antagonist activity with an IC50 value of 14.8 µM. Furthermore, wound healing assay using the NCI-H1299 cell line indicated that 1e showed an excellent anti-cancer metastatic effect (72% inhibition in cell migration at 50 µg ml−1).

Alternaria sp. MG1, an endophytic fungus previously isolated from Merlot grape, produces resveratrol from glucose, showing similar metabolic flux to the phenylpropanoid biosynthesis pathway, currently found solely in plants. In order to identify the resveratrol biosynthesis pathway in this strain at the gene level, de novo transcriptome sequencing was conducted using Illumina paired-end sequencing. A total of 22,954,434 high-quality reads were assembled into contigs and 18,570 unigenes were identified. Among these unigenes, 14,153 were annotated in the NCBI non-redundant protein database and 5,341 were annotated in the Swiss-Prot database. After KEGG mapping, 2,701 unigenes were mapped onto 115 pathways. Eighty-four unigenes were annotated in major pathways from glucose to resveratrol, coding 20 enzymes for glycolysis, 10 for phenylalanine biosynthesis, 4 for phenylpropanoid biosynthesis, and 4 for stilbenoid biosynthesis. Chalcone synthase was identified for resveratrol biosynthesis in this strain, due to the absence of stilbene synthase. All the identified enzymes indicated a reasonable biosynthesis pathway from glucose to resveratrol via glycolysis, phenylalanine biosynthesis, phenylpropanoid biosynthesis, and stilbenoid pathways. These results provide essential evidence for the occurrence of resveratrol biosynthesis in Alternaria sp. MG1 at the gene level, facilitating further elucidation of the molecular mechanisms involved in this strain’s secondary metabolism.

Pinoresinol diglucoside (PDG) and pinoresinol (Pin) are normally produced by plant cells via the phenylpropanoid pathway. This study reveals the existence of a related pathway in Phomopsis sp. XP-8, a PDG-producing fungal strain isolated from the bark of the Tu-chung tree (Eucommiaulmoides Oliv.). After addition of 0.15 g/L glucose to Phomopsis sp. XP-8, PDG and Pin formed when phenylalanine, tyrosine, leucine, cinnamic acid, and p-coumaric acid were used as the substrates respectively. No PDG formed in the absence of glucose, but Pin was detected after addition of all these substrates except leucine. In all systems in the presence of glucose, production of PDG and/or Pin and the accumulation of phenylalanine, cinnamic acid, or p-coumaric acid correlated directly with added substrate in a time- and substrate concentration- dependent manner. After analysis of products produced after addition of each substrate, the mass flow sequence for PDG and Pin biosynthesis was defined as: glucose to phenylalanine, phenylalanine to cinnamic acid, then to p-coumaric acid, and finally to Pin or PDG. During the bioconversion, the activities of four key enzymes in the phenylpropanoid pathway were also determined and correlated with accumulation of their corresponding products. PDG production by Phomopsis sp. exhibits greater efficiency and cost effectiveness than the currently-used plant-based system and will pave the way for large scale production of PDG and/or Pin for medical applications.

Net primary productivity（NPP） directly and truly reflected the dynamic changing process of terrestrial vegetation ecosystem.Understanding the driving mechanism of climate change and human activities on vegetation change was of great scientific significance to ecological protection and sustainable development.Based on MOD17A3/NPP product， using linear trend analysis， Mann-Kendall significance analysis， Hurst index and partial correlation analysis， the temporal and spatial distribution characteristics of vegetation NPP in Yunnan Province from 2001 to 2021， the future sustainability and the relationship between vegetation NPP and meteorological conditions were discussed.Residual analysis used to quantitatively assess the relative contributions and combined action of climate change and human activities to the vegetation NPP.The result as follow： （1）Spatially， the annual mean NPP value of Yunnan vegetation from 2001 to 2021 was high in the south and low in the north.The order of values from the high to low was woodland （1106.7 gC∙m-2）， shrub （964.4 gC∙m-2）， agricultural land （946.6 gC∙m-2） and grassland （878.8 gC∙m-2） in different vegetation types.The vegetation NPP increased and then decreased with increasing altitude.（2）During the study period the annual mean vegetation NPP was 1020.8 ± 30.7 gC∙m-2， with minimum and maximum values occurring in 2010 （950.0 gC∙m-2） and 2019 （1062.1 gC∙m-2）， respectively.The vegetation NPP showed a significant increase with an increase rate of 2.1 gC∙m-2∙a-1 （p farmland （3.5 gC∙m-2∙a-1）> shrub （2.8 gC∙m-2∙a-1）>forestland （1.3 gC∙m-2∙a-1）.The average value of the Hurst index was 0.60.The proportion of the area that would continue to increase and change from decrease to increase was 55.5% and 9.3%， respectively.This indicated that the vegetation NPP would continue to increase in most areas in the future.（3）The average temperature in Yunnan Province showed a significant increase from 2001 to 2021， while precipitation and solar radiation showed a fluctuating decrease.These climatic factors positively correlated with vegetation NPP in most areas， and the effect of temperature on vegetation NPP was greater than that of precipitation and solar radiation.（4） The relative contribution rates of climate change and human activities to vegetation NPP change in Yunnan were 27.1% and 72.9%， respectively， with positive contributions accounting for 59.4% and 64.6% of the total area of the study area， and relative contribution rate greater than 60% accounting for 12.7% and 73.4% of the area， respectively.The impact of human activities on vegetation NPP was greater than that of climate change in most areas.The vegetation improvement in Yunnan was mainly caused by the combined effect of climate change and human activities， while the degradation was mainly caused by the human activities and the combined effect.The ecological protection and restoration projects had a significant contribution to the improvement of vegetation NPP in Yunnan.

The improvement of detection accuracy without loss of rapidity and sensitivity by optical sensors in complex food analysis is still full of challenges owing to the matrix interference. Herein, a novel and simple self-calibration colorimetric/fluorescence/surface-enhanced Raman spectroscopy (SERS) tri-modal optical sensor based on aminated Rhodamine 6G (R6G-NH2) was developed for highly rapid, sensitive, and accurate detection of Hg2+ in food samples. The high recognition specificity of R6G-NH2 for Hg2+ can be achieved through the metal chelation interaction between Hg2+ and -NH2, -COOH groups in R6G-NH2 with formation of R6G-NH2-Hg2+-R6G-NH2 complex. The DFT and FDTD simulations were adopted to confirm the theoretical feasibility in Hg2+ detection by tri-modal optical. Under the optimum conditions, the analytical method based on self-calibration tri-modal optical sensor for Hg2+ detection was established with promising properties (rapidity, linearity, linear range, LOD, and LOQ), providing a strategy in rapid, selective, sensitive, and accurate detection for food safety.

Objective: This study aims to analyze the quantitative parameters and morphological indices of three-dimensional (3D) visualization to differentiate lepidic predominant adenocarcinoma (LPA) from non-LPA subtypes, which include acinar predominant adenocarcinoma (APA), papillary predominant adenocarcinoma (PPA), micropapillary predominant adenocarcinoma (MPA), and solid predominant adenocarcinoma (SPA). Methods: A group of 178 individuals diagnosed with lung adenocarcinoma were chosen and categorized into two groups: the LPA group and the non-LPA group, according to their pathological results. Quantitative parameters and morphological indexes such as 3D volume, solid proportion, and vascular cluster sign were obtained using 3D visualization and reconstruction techniques. Results: Significant differences were observed in the vascular cluster sign, spiculation, shape, air bronchogram, bubble-like lucency, margin, pleural indentation, lobulation, maximum tumor diameter, 3D mean CT value, 3D volume, 3D mass, 3D density, and solid proportion between two groups (P

Abstract Novel biologics in MG therapy research is on the rise. This research aimed to investigate the characteristics of registered trials on novel therapies for myasthenia gravis on ClinicalTrials.gov. This cross-sectional study used a descriptive approach to assess the features of the included trials on ClinicalTrials.gov. We found 62 registered trials from 2007 to 2023 on ClinicalTrials.gov. The results showed a yearly rise in the number of registered trials (r = 0.76, p

Abstract Background Annexin (ANN) is calcium (Ca2+)-dependent and phospholipid binding protein family, which is involved in plant growth and development and response to various stresses. However, little known about ANN genes were identified from crape myrtle, an ornamental horticultural plant widely cultivated in the world. Results Here, 9 LiANN genes were identified from Lagerstroemia indica, and their characterizations and functions were investigated in L. indica for the first time. The LiANN genes were divided into 2 subfamilies. The gene structure, chromosomal location, and collinearity relationship were also explored. In addition, the GO annotation analysis of these LiANNs indicated that they are enriched in molecular functions, cellular components, and biological processes. Moreover, transcription factors (TFs) prediction analysis revealed that bHLH, MYB, NAC, and other TFs can interact with the LiANN promoters. Interestingly, the LiANN2/4/6–9 were demonstrated to play critical roles in the branching architecture of crape myrtle. Furthermore, the LiANN2/6/8/9 were differentially expressed under salt treatment, and a series of TFs regulating LiANN2/6/8/9 expression were predicted to play essential roles in salt resistance. Conclusions These results shed light on profile and function of the LiANN gene family, and lay a foundation for further studies of the LiANN genes.

We demonstrate a compact, partially end-pumping Innoslab laser based on a micro-cylindrical lens array homogenizer. A dimension of 12 × 0.4 mm2 flat-top pumping line with a Gaussian intensity distribution across the line was simulated by the ray tracing technique. The rate equations considering the asymmetric transverse spatial distributions are theoretically developed. The simulation results are in good agreement with the experimental results. Preliminary data shows that for a pump power of 260 W, a maximum pulse energy of 15.7 mJ was obtained with a pulse width of 8.5 ns at a repetition frequency of 1 kHz. The beam quality M2 factors in the unstable and stable directions were 1.732 and 1.485, respectively. The technology has been successfully applied to temperature and humidity profiling lidar and ozone lidar and has been productized, yielding direct economic value.

Understanding the spatiotemporal patterns and variations in vapor pressure deficit (VPD) is essential for effective water resource management in the face of climate change. VPD serves as a fundamental indicator of atmospheric dryness, directly impacting plant evapotranspiration rates, thereby affecting overall ecosystem functioning. In this study, VPD changes in five subregions and four ecological types of land in Yunnan from 1980 to 2021 were investigated using data from 108 meteorological stations. We found increasing trends in annual VPD that were larger during warmer spring and summer seasons. Among the subregions, the highland subtropical southern broadleaved evergreen forest ecoregion exhibited the largest drying trend (0.04 kPa / decade), while the subtropical (eastern) humid broadleaved evergreen forest ecoregion had the smallest drying trend (0.01 kPa / decade). Among the ecological barriers, the dry-hot valleys had significantly higher increases in VPD compared to other Yunnan regions. Increases in VPD from 1990s to 2000s in several regions of Yunnan exceeded atmospheric drying trends reported elsewhere. Additionally, we documented smaller VPD declines at higher elevations. Across different ecological land types, Shrubland exhibited the largest VPD trend (0.07 kPa / decade), while Forest displayed the smallest (0.03 kPa / decade). Decreased relative humidity through time explained 65% of the increase in VPD in Yunnan, while increasing temperatures accounted for 25%. These findings provide valuable insights into climatic dynamics of Yunnan, with implications for ecological, hydrological, and atmospheric studies.

The occurrence of ovarian cancer (OC) is a major factor in women’s mortality rates. Despite progress in medical treatments, like new drugs targeting homologous recombination deficiency, survival rates for OC patients are still not ideal. The tumor microenvironment (TME) includes cancer cells, fibroblasts linked to cancer (CAFs), immune-inflammatory cells, and the substances these cells secrete, along with non-cellular components in the extracellular matrix (ECM). First, the TME mainly plays a role in inhibiting tumor growth and protecting normal cell survival. As tumors progress, the TME gradually becomes a place to promote tumor cell progression. Immune cells in the TME have attracted much attention as targets for immunotherapy. Immune checkpoint inhibitor (ICI) therapy has the potential to regulate the TME, suppressing factors that facilitate tumor advancement, reactivating immune cells, managing tumor growth, and extending the survival of patients with advanced cancer. This review presents an outline of current studies on the distinct cellular elements within the OC TME, detailing their main functions and possible signaling pathways. Additionally, we examine immunotherapy rechallenge in OC, with a specific emphasis on the biological reasons behind resistance to ICIs.

The development of a soft crawling robot (SCR) capable of quick folding and recovery has important application value in the field of biomimetic engineering. This article proposes an origami-inspired vacuum-actuated foldable soft crawling robot (OVFSCR), which is composed of entirely soft foldable mirrored origami actuators with a Kresling crease pattern, and possesses capabilities of realizing multimodal locomotion incorporating crawling, climbing, and turning movements. The OVFSCR is characterized by producing periodically foldable and restorable body deformation, and its asymmetric structural design of low front and high rear hexahedral feet creates a friction difference between the two feet and contact surface to enable unidirectional movement. Combining an actuation control sequence with an asymmetrical structural design, the body deformation and feet in contact with ground can be coordinated to realize quick continuous forward crawling locomotion. Furthermore, an efficient dynamic model is developed to characterize the OVFSCR’s motion capability. The robot demonstrates multifunctional characteristics, including crawling on a flat surface at an average speed of 11.9 mm/s, climbing a slope of 3°, carrying a certain payload, navigating inside straight and curved round tubes, removing obstacles, and traversing different media. It is revealed that the OVFSCR can imitate contractile deformation and crawling mode exhibited by soft biological worms. Our study contributes to paving avenues for practical applications in adaptive navigation, exploration, and inspection of soft robots in some uncharted territory.

The production management of lactating sows is a crucial aspect of pig farm operations, as their health directly impacts the farm’s production efficiency. The feeding behavior of lactating sows can reflect their health and welfare status, and monitoring this behavior is essential for precise feeding and management. To address the issues of time-consuming and labor-intensive manual inspection of lactating sows’ feeding behavior and the reliance on breeders’ experience, we propose a method based on the improved YOLO (You Only Look Once) v5s algorithm and image segmentation for detecting the feeding behavior of lactating sows. Based on the YOLOv5s algorithm, the SE (Squeeze-and-Excitation) attention module was added to enhance the algorithm’s performance and reduce the probability of incorrect detection. Additionally, the loss function was replaced by WIoU (Weighted Intersection over Union) to accelerate the model’s convergence speed and improve detection accuracy. The improved YOLOv5s-C3SE-WIoU model is designed to recognize pre-feeding postures and feed trough conditions by detecting images of lactating sows. Compared to the original YOLOv5s, the improved model achieves an 8.9% increase in mAP@0.5 and a 4.7% increase in mAP@0.5 to 0.95. This improvement satisfies the requirements for excellent detection performance, making it suitable for deployment in large-scale pig farms. From the model detection results, the trough remnant image within the detection rectangle was extracted. This image was further processed using image processing techniques to achieve trough remnant image segmentation and infer the remnant amount. Based on the detection model and residue inference method, video data of lactating sows’ feeding behavior were processed to derive the relationship between feeding behavior, standing time, and residue amount. Using a standing duration of 2 s and a leftover-feed proportion threshold of 2% achieves the highest accuracy, enabling the identification of abnormal feeding behavior. We analyzed the pre-feeding postures and residual feed amounts of abnormal and normal groups of lactating sows. Our findings indicated that standing time was significantly lower and residual feed amount was higher in the abnormal groups compared to the normal groups. By combining standing time and residual feed amount information, accurate detection of the feeding status of lactating sows can be realized. This approach facilitates the accurate detection of abnormal feeding behaviors of lactating sows in large-scale pig farm environments.

Abstract The power generation of the photovoltaic plant is related to the cleanliness of the photovoltaic modules. The accumulation of natural dust is the main source of pollution, which is affected by human activities and meteorological factors such as temperature, humidity, wind speed, and rainfall concentration in the current region. On the basis of particle swarm optimization (PSO) and the least‐squares support vector machine (LSSVM), the density of dust on photovoltaic modules was estimated. The authors proposed that the inertia weight decreased as a concave function to improve the efficiency of optimization and let the two positive constants change dynamically to improve convergence performance. The dust accumulation prediction model was established considering natural rainfall and the authors obtained the attenuation rate of the photovoltaic power output. Finally, the experiments in Hangzhou showed that the model can predict the density of accumulated dust quickly, which provides a theory for predicting PV power generation and managing the cleaning frequency.

ABSTRACTThe emergence and nosocomial spread of the multidrug-resistant Candida auris pose a severe public health threat. Most C. auris clinical isolates are fluconazole resistant. In this study, we conduct transposon-mediated screens to profile genes whose inactivation causes fluconazole resistance in C. auris. We discover that mutation of genes encoding the Ubr2/Mub1 ubiquitin-ligase complex results in high fluconazole resistance by stabilizing the transcription activator, Rpn4. Global transcriptomic analysis, quantitative PCR, and combinatorial gene deletion reveal that Rpn4 causes fluconazole resistance by upregulating four efflux pump genes, SNQ21, SNQ22, MDR1, and CDR1, increasing efflux activity of the cell. Rpn4 autoactivates its own expression by binding to a PACE element in its promoter, forming a positive autoregulatory loop. Rpn4 also promotes CDR1 expression by binding to a PACE element in the CDR1 promoter. Furthermore, using the published genome sequence data of 304 clinical isolates, we identified a UBR2 A316T mutation in isolates from clades I and III. Although complementation of the ubr2Δ mutant with the UBR2A316T allele resulted in increased susceptibility to fluconazole, the UBR2A316T mutant was still more resistant to fluconazole compared to wild type, suggesting that acquisition of the mutation is sufficient to confer an increase in fluconazole resistance. In conclusion, this study identifies Rpn4 as a critical transcription factor that regulates fluconazole resistance via the Rpn4-efflux pump axis in C. auris.IMPORTANCECandida auris is a recently emerged pathogenic fungus of grave concern globally due to its resistance to conventional antifungals. This study takes a whole-genome approach to explore how C. auris overcomes growth inhibition imposed by the common antifungal drug fluconazole. We focused on gene disruptions caused by a “jumping genetic element” called transposon, leading to fluconazole resistance. We identified mutations in two genes, each encoding a component of the Ubr2/Mub1 ubiquitin-ligase complex, which marks the transcription regulator Rpn4 for degradation. When either protein is absent, stable Rpn4 accumulates in the cell. We found that Rpn4 activates the expression of itself as well as the main drug efflux pump gene CDR1 by binding to a PACE element in the promoter. Furthermore, we identified an amino acid change in Ubr2 in many resistant clinical isolates, contributing to Rpn4 stabilization and increased fluconazole resistance.

Background With the establishment of the cardiac-gut axis concept, increasing evidence has suggested the involvement and important regulatory role of the gut microbiota (GM) and short chain fatty acid (SCFA) in cardiovascular diseases. However, the relationship between GM and atrial fibrillation (AF) is still poorly understood. Objectives The aim of this study was to investigate whether there were differences in GM and SCFA between AF patients and healthy controls. Methods In this study, we enrolled 30 hospitalized patients with AF and 30 matched patients with sinus rhythm (SR). GM species in fecal samples were evaluated through amplicon sequencing targeting the 16Sribosomal RNA gene. The feces SCFAs were describe step by step the quantitative analysis using gas chromatography-mass spectrometry (GC-MS). GM species richness, diversity, differential abundance of individual taxa between AF and SR were analyzed. Results AF patients showed decreased species richness and α-diversity compared to SR patients, but there was no statistical difference. The phylogenetic diversity was significant decreased in AF group. The β-diversity indexes revealed significant differences in GM community structure between the AF group and the SR group. After investigated the individual taxa, AF group showed altered relative abundance in several taxa compared to the SR group. linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed, a significant decrease in Bifidobacterium and a greater abundance of Lactobacillus, Fusobacterium, Haemophilus in AF group compared with the SR group. The abundance of haemophilus was negative correlated with isovaleric acid and isobutyric acid. Conclusions In AF patients, the GM phylogenetic diversity and β-diversity decreased, the relative abundance altered in several taxa and the bacterial community structure changed as well as the SCFA level. GM and SCFA dysbiosis might play a crucial part in the occurrence and development of AF.

Traditional vision methods for solar cell defect detection have problems such as low accuracy and few types of detection, so this paper proposes an optimized YOLOv5 model for more accurate and comprehensive identification of defects in solar cells. The model firstly integrates five data enhancement methods, namely Mosaic, Mixup, hsv transform, scale transform and flip, to expand the existing data set to improve the feature training accuracy and enhance the robustness of the model; secondly, CA attention mechanism is introduced to improve the feature extraction ability of the model; to address the problems of different target defect classification and localization concerns, the detection head in the original model is replaced with a decoupling head, which significantly improve the detection accuracy of the model without affecting the convergence speed of the model. The results show that the optimized model achieves an mAP of 96.1% on the publicly available dichotomous ELPV dataset, and can identify and locate a variety of common defects in the PVEL-AD dataset, while the mAP can reach 87.4%, an improvement of 10.38% compared with the original YOLOv5 model, which enables the model to perform more accurately while ensuring the real-time requirement of solar cell surface defects detection task.

Abstract Background In insects, an interplay between the activities of distinct hormones, such as juvenile hormone (JH) and 20-hydroxyecdysone (20E), regulates the progression through numerous life history hallmarks. As a crucial endocrine factor, JH is mainly synthesized in the corpora allata (CA) to regulate multiple physiological and developmental processes, including molting, metamorphosis, and reproduction. During the last century, significant progress has been achieved in elucidating the JH signal transduction pathway, while less progress has been made in dissecting the regulatory mechanism of JH biosynthesis. Previous work has shown that receptor tyrosine kinase (RTK) signaling regulates hormone biosynthesis in both insects and mammals. Here, we performed a systematic RNA interference (RNAi) screening to identify RTKs involved in regulating JH biosynthesis in the CA of adult Blattella germanica females. Results We found that the epidermal growth factor receptor (Egfr) is required for promoting JH biosynthesis in the CA of adult females. The Egf ligands Vein and Spitz activate Egfr, followed by Ras/Raf/ERK signaling, and finally activation of the downstream transcription factor Pointed (Pnt). Importantly, Pnt induces the transcriptional expression of two key enzyme-encoding genes in the JH biosynthesis pathway: juvenile hormone acid methyltransferase (JHAMT) and methyl farnesoate epoxidase (CYP15A1). Dual-luciferase reporter assay shows that Pnt is able to activate a promoter region of Jhamt. In addition, electrophoretic mobility shift assay confirms that Pnt directly binds to the − 941~ − 886 nt region of the Jhamt promoter. Conclusions This study reveals the detailed molecular mechanism of Egfr signaling in promoting JH biosynthesis in the German cockroach, shedding light on the intricate regulation of JH biosynthesis during insect development.

In recent decades, severe drought conditions have become increasingly frequent in Yunnan, Southwest China. The extreme drought events cause huge losses to agricultural economy, ecological security and human health. To uncover the reasons behind the worsening drought conditions, this study investigates the interdecadal variability (IDV) of summer precipitation in Yunnan during 1961–2019 and its association with the Indo-Pacific Sea surface temperature (SST) configuration based on gauge observation and reanalysis data. The dominant mode of summer precipitation IDV in Yunnan shows a uniform pattern characterizing the alternations of flood and drought. Specifically, a relatively wet period persists from the early 1990s to the early 2000s, followed by a relatively dry period from the early 2000s to the late 2010s. The IDV of precipitation is consistent with the IDV of the column-integrated water vapor flux divergence, where the wind anomalies play a major role in modulating the moisture supply. The main SST forcings of the IDV of precipitation include the sea surface temperature anomalies (SSTAs) over the Bay of Bengal (BOB), the Western Pacific Warm Pool (WPWP), and the western North Pacific (WNP). The negative SSTAs over the BOB and the WPWP trigger a Gill-Matsuno-type response that enhances the cyclonic curvature over Yunnan. The SSTAs over the WNP show a tripole pattern that weakens the WNP subtropical high and further enhances the cyclonic anomaly over Yunnan. The above SST configuration also favors moisture transport to Yunnan. Numerical experiments verify the key physical processes.

A quasi-continuous-wave (QCW) laser diode (LD) driver is commonly used to drive diode bars and stacks designed specifically for QCW operations in solid-state lasers. Such drivers are optimized to deliver peak current and voltage pulses to LDs while maintaining low average power levels. As a result, they are widely used in laser processing devices and laser instruments. Traditional high-energy QCW LD drivers primarily use capacitors as energy storage components and pulsed constant-current sources with op-amps and power metal-oxide-semiconductor field-effect transistors (MOSFETs) as their core circuits for generating repeated constant-current pulses. The drawback of this type of driver is that the driver’s output voltage needs to be manually adjusted according to the operating voltage of the load before use to maximize driver efficiency while providing a sufficient current. Another drawback is its inability to automatically adjust the output voltage to maintain high efficiency when the load changes during the driver operation. Drastic changes in the load can cause the driver to fail to function properly in extreme cases. Based on the above traditional circuit structure, this study designed a stability compensation circuit and realized a QCW LD driver for driving a GS20 diode stack with a maximum repetition rate of 100 Hz, a constant current of approximately 300 A, a load voltage of approximately 10 V, and a pulse width of approximately 300 μs. In particular, a high-efficiency, load-adaptive driving method was used with the MOSFETs in the critical saturation region (i.e., between the linear and saturated regions), controlling its power loss effectively while achieving maximum output current of the driver. The experiments demonstrated that the driver efficiency could be maintained at more than 80% when the load current varied from 50 to 300 A.