FBXO22 is a potential therapeutic target for recurrent chondrosarcoma.

Chondrosarcoma (CHS) is a malignant bone tumor with insensitivity to both radiotherapy and chemotherapy, and a high recurrence rate. However, the latent mechanism of recurrent CHS (Re-CHS) remains elusive. Here, we discovered that FBXO22 was highly expressed in clinical samples of Re-CHS. FBXO22 played a significant role in various cancers. However, the role of FBXO22 in Re-CHS remained unclear. Our research demonstrated that suppressing FBXO22 abated the proliferation and migration of CHS cells and facilitated their apoptosis. In addition, suppressing FBXO22 raised the expression of PD-L1 in Re-CHS. All these findings provide new evidence for using FBXO22 and PD-L1 as combined targets to prevent and treat Re-CHS, which may prove to be a novel strategy for immunotherapy of CHS, especially Re-CHS.

HydrogelFinder: A Foundation Model for Efficient Self-Assembling Peptide Discovery Guided by Non-Peptidal Small Molecules.

Self-assembling peptides have numerous applications in medicine, food chemistry, and nanotechnology. However, their discovery has traditionally been serendipitous rather than driven by rational design. Here, HydrogelFinder, a foundation model is developed for the rational design of self-assembling peptides from scratch. This model explores the self-assembly properties by molecular structure, leveraging 1,377 self-assembling non-peptidal small molecules to navigate chemical space and improve structural diversity. Utilizing HydrogelFinder, 111 peptide candidates are generated and synthesized 17 peptides, subsequently experimentally validating the self-assembly and biophysical characteristics of nine peptides ranging from 1-10 amino acids-all achieved within a 19-day workflow. Notably, the two de novo-designed self-assembling peptides demonstrated low cytotoxicity and biocompatibility, as confirmed by live/dead assays. This work highlights the capacity of HydrogelFinder to diversify the design of self-assembling peptides through non-peptidal small molecules, offering a powerful toolkit and paradigm for future peptide discovery endeavors.

Theoretical Perspective on the Design of Surface Frustrated Lewis Pairs for Small-Molecule Activation.

The excellent reactivity of frustrated Lewis pairs (FLP) to activate small molecules has gained increasing attention in recent decades. Though the development of surface FLP (SFLP) is prompting the application of FLP in the chemical industry, the design of SFLP with superior activity, high density, and excellent stability for small-molecule activation is still challenging. Herein, we review the progress of designing SFLP by surface engineering, screening natural SFLP, and the dynamic formation of SFLP from theoretical perspectives. We highlight the breakthrough in fine-tuning the activity, density, and stability of the designed SFLP studied by using computational methods. We also discuss future challenges and directions in designing SFLP with outstanding capabilities for small-molecule activation.

RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders.

RNA-protein interactions (RPIs) play an important role in several fundamental cellular physiological processes, including cell motility, chromosome replication, transcription and translation, and signaling. Predicting RPI can guide the exploration of cellular biological functions, intervening in diseases, and designing drugs. Given this, this study proposes the RPI-gated graph convolutional network (RPI-GGCN) method for predicting RPI based on the gated graph convolutional neural network (GGCN) and co-regularized variational autoencoder (Co-VAE). First, different types of feature information were extracted from RNA and protein sequences by nine feature extraction methods. Second, Co-VAEs are used to eliminate the redundancy of fused features and generate optimal features. Finally, this study introduces gated cyclic units into graph convolutional networks (GCNs) to construct a model for RPI prediction, which efficiently extracts topological information and improves the model's interpretable feature learning and expression capabilities. In the fivefold cross-validation test, the RPI-GGCN method achieved prediction accuracies of 97.27%, 97.32%, 96.54%, 95.76%, and 94.98% on the RPI369, RPI488, RPI1446, RPI1807, and RPI2241 datasets. To test the generalization performance of the model, we used the model trained on RPI369 to predict the independent NPInter v3.0 dataset and achieved excellent performance in all six independent validation sets. By visualizing the RPI network graph based on the prediction results, we aim to provide a new perspective and reference for studying RPI mechanisms and exploring new RPIs. Extensive experimental results demonstrate that RPI-GGCN can provide an efficient, accurate, and stable RPI prediction method.

Drymariamides A-J, Antiadipogenic Cyclopeptides Incorporating Noncanonical Amino Acids from Drymaria cordata.

Herein, we report an extensive phytochemical study on the whole plant of Drymaria cordata, which led to the isolation of ten new orbitides, named drymariamides A-J (1-10). Compounds 2, 3, and 5 incorporate rare residues of noncanonical amino acids of kynurenine (Kyn) or 3a-hydroxypyrroloindoline (HPI). Their structures with absolute configurations were elucidated by a combination of spectroscopic analysis, advanced Marfey's method, X-ray diffraction, and electronic circular dichroism analysis. Compounds 1-10 exhibited antiadipogenic effects in 3T3-L1 adipocytes, and the most potent compound 7 showed an EC50 value of 1.17 ± 0.19 µM.

Waveguide-integrated twisted bilayer graphene photodetectors.

Graphene photodetectors have exhibited high bandwidth and capability of being integrated with silicon photonics (SiPh), holding promise for future optical communication devices. However, they usually suffer from a low photoresponsivity due to weak optical absorption. In this work, we have implemented SiPh-integrated twisted bilayer graphene (tBLG) detectors and reported a responsivity of 0.65 A W-1 for telecom wavelength 1,550 nm. The high responsivity enables a 3-dB bandwidth of >65 GHz and a high data stream rate of 50 Gbit s-1. Such high responsivity is attributed to the enhanced optical absorption, which is facilitated by van Hove singularities in the band structure of high-mobility tBLG with 4.1o twist angle. The uniform performance of the fabricated photodetector arrays demonstrates a fascinating prospect of large-area tBLG as a material candidate for heterogeneous integration with SiPh.

Effect of Chinese quince proanthocyanidins on the inhibition of heterocyclic amines and quality of fried chicken meatballs and tofu.

Heterocyclic amines (HCAs) have potential carcinogenic and mutagenic activity and are generated in cooked protein-rich foods. Adding proanthocyanidins (PAs) to these foods before frying is an effective way to reduce HCAs. In this study, polymeric PAs (PPA) and ultrasound-assisted acid-catalyzed/catechin nucleophilic depolymerized PAs (UAPA, a type of oligomeric PA) were prepared from Chinese quince fruits (CQF). Different levels of PPA and UAPA (0.05%, 0.1%, and 0.15%) were added to chicken meatballs and tofu; then these foods were fried, and the content of HCAs in them after frying was investigated. The results showed that PPA and, particularly, UAPA significantly inhibited the formation of HCAs in fried meatballs and tofu, and this inhibition was dose-dependent. The inhibition of HCAs by both PPA and UAPA was stronger in the chicken meatballs than in fried tofu. The level of total HCAs was significantly reduced by 57.84% (from 11.93 to 5.03 ng/g) after treatment of meatballs with 0.15% UAPA, with inhibition rates of 78.94%, 50.37%, and 17.81% for norharman, harman, and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), respectively. Of note, there was a negative correlation between water, lipid, protein, creatine, and glucose content and HCA content in the crust, interior, and whole (crust-plus-interior) measurements of all fried samples. Interestingly, PPA and UAPA were found more effective in inhibiting HCAs in the exterior crust than in the interior of the fried chicken meatballs. These results provide evidence that further studies on the reduction of the formation of harmful HCAs in fried foods by adding CQF PAs could be valuable to the fried food industry. PRACTICAL APPLICATION: Chinese quince proanthocyanidins treatments significantly inhibited the generation of heterocyclic amines (HCAs) in chicken meatballs and tofu when deep-fried. These results suggest that Chinese quince proanthocyanidins can be used as natural food additive for reducing HCAs in fried foods, laying the foundation for using Chinese quince fruit proanthocyanidins for HCA inhibition in the food industry.

Optimization of hydrolysis conditions of alginate based on high performance liquid chromatography.

Alginate is the most abundant polysaccharide compound in brown algae, which is widely used in various fields. At present, the determination of the content of alginate is mostly carried out using sulfuric acid and trifluoroacetic acid hydrolysis followed by the determination of the content, but the results are not satisfactory, and there are problems such as low hydrolysis degree and low recovery rate. Therefore, in this study, based on the optimization of high performance liquid chromatographic conditions for pre-column derivatization of 1-phenyl-3-methyl-5-pyrazolone (PMP), the hydrolysis effects of sulfuric acid, trifluoroacetic acid (TFA), oxalic acid, and formic acid were compared and the hydrolysis conditions were optimized. The results showed that formic acid was the best hydrolyzing acid. The optimal hydrolysis conditions were 95 % formic acid at 110 °C for 10 h. The hydrolysis effect was stable, with high recovery and low destruction of monosaccharides, which made it possible to introduce formic acid into the subsequent polysaccharide hydrolysis. The pre-column derivatization high performance liquid chromatography method established in this study was accurate and reliable, and the hydrolysis acid with better effect was screened, which provided a theoretical basis for the subsequent determination of alginate content.

AI identifies potent inducers of breast cancer stem cell differentiation based on adversarial learning from gene expression data.

Cancer stem cells (CSCs) are a subpopulation of cancer cells within tumors that exhibit stem-like properties and represent a potentially effective therapeutic target toward long-term remission by means of differentiation induction. By leveraging an artificial intelligence approach solely based on transcriptomics data, this study scored a large library of small molecules based on their predicted ability to induce differentiation in stem-like cells. In particular, a deep neural network model was trained using publicly available single-cell RNA-Seq data obtained from untreated human-induced pluripotent stem cells at various differentiation stages and subsequently utilized to screen drug-induced gene expression profiles from the Library of Integrated Network-based Cellular Signatures (LINCS) database. The challenge of adapting such different data domains was tackled by devising an adversarial learning approach that was able to effectively identify and remove domain-specific bias during the training phase. Experimental validation in MDA-MB-231 and MCF7 cells demonstrated the efficacy of five out of six tested molecules among those scored highest by the model. In particular, the efficacy of triptolide, OTS-167, quinacrine, granisetron and A-443654 offer a potential avenue for targeted therapies against breast CSCs.

SIRT1 maintains bone homeostasis by regulating osteoblast glycolysis through GOT1.

The silent information regulator T1 (SIRT1) is linked to longevity and is a crucial mediator of osteoblast function. We investigated the direct role of Sirt1 during bone modeling and remodeling stages in vivo using Tamoxifen-inducible osteoblast-specific Sirt1 conditional knockout (cKO) mice. cKO mice exhibited lower trabecular and cortical bone mass in the distal femur. These phenotypes were coupled with lower bone formation and bone resorption. Metabolomics analysis revealed that the metabolites involved in glycolysis were significantly decreased in cKO mice. Further analysis of the quantitative acetylome revealed 11 proteins with upregulated acetylation levels in both the femur and calvaria of cKO mice. Cross-analysis identified four proteins with the same upregulated lysine acetylation site in both the femur and calvaria of cKO mice. A combined analysis of the metabolome and acetylome, as well as immunoprecipitation, gene knockout, and site-mutation experiments, revealed that Sirt1 deletion inhibited glycolysis by directly binding to and increasing the acetylation level of Glutamine oxaloacetic transaminase 1 (GOT1). In conclusion, our study suggested that Sirt1 played a crucial role in regulating osteoblast metabolism to maintain bone homeostasis through its deacetylase activity on GOT1. These findings provided a novel insight into the potential targeting of osteoblast metabolism for the treatment of bone-related diseases.

Comparison of brain gray matter volume changes in peritoneal dialysis and hemodialysis patients with chronic kidney disease: a VBM study.

Objective: This study aims to compare gray matter volume changes in patients with chronic kidney disease (CKD) undergoing peritoneal dialysis (PD) and hemodialysis (HD) using voxel-based morphometry (VBM). Methods: A total of 27 PD patients, 25 HD patients, and 42 healthy controls were included. VBM analysis was performed, and cognitive function was assessed using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment Scale (MoCA). The correlation between cognitive function and changes in brain gray matter volume was analyzed. Results: Both peritoneal dialysis and hemodialysis patients had partial gray matter volume reduction compared to the controls, but the affected brain regions were not uniform. The hemodialysis patients had greater volume reduction in certain brain regions than the PD patients. The MMSE and MoCA scores were positively correlated with gray matter volume changes. Conclusion: Different dialysis modalities cause damage to specific areas of the brain, which can be detected using VBM. VBM, combined with cognitive function assessment, can help detect structural brain changes and cognitive impairment in patients with different dialysis modalities. The comprehensive application of VBM in the field of neurological function deserves further exploration.

Stochastic process is main factor to affect plateau river fish community assembly.

Plateau river ecosystems are often highly vulnerable and responsive to environmental change. The driving mechanism of fish diversity and community assembly in plateau rivers under changing environments presents a significant complexity to the interdisciplinary study of ecology and environment. This study integrated molecular biological techniques and mathematical models to identify the mechanisms influencing spatial heterogeneity of freshwater fish diversity and driving fish community assembly in plateau rivers. By utilizing environmental-DNA metabarcoding and the null model, this study revealed the impact of the stochastic process on fish diversity variations and community assembly in the Huangshui Plateau River of the Yellow River Basin (YRB) in China. This research identified 30 operational taxonomic units (OTUs), which correspond to 20 different fish species. The findings of this study revealed that the fish α-diversity in the upstream region of Xining is significantly higher than in the middle-lower reach (Shannon index: P=0.017 and Simpson: P=0.035). This pattern was not found to be related to any other environmental factors besides altitude (P=0.023) that we measured. Further, the study indicated that the assembly of fish communities in the Huangshui River primarily depends on stochastic ecological processes. These findings suggested that elevation was not the primary factor impacting the biodiversity patterns of fish in plateau rivers. In plateau rivers, spatial heterogeneity of fish community on elevation is mainly determined by stochastic processes under habitat fragmentation, rather than any other physicochemical environmental factors. The limitations of connectivity in the downstream channel of the river could be taken the mainly responsibility for stochastic processes of fish community in Huangshui River. Incorporating ecological processes in the eDNA approach holds great potential for future monitoring and evaluation of fish biodiversity and community assembly in plateau rivers.

Palladium-Catalyzed Ligand-Controlled Switchable Hetero-(5 + 3)/Enantioselective [2σ+2σ] Cycloadditions of Bicyclobutanes with Vinyl Oxiranes.

For nearly 60 years, significant research efforts have been focused on developing strategies for the cycloaddition of bicyclobutanes (BCBs). However, higher-order cycloaddition and catalytic asymmetric cycloaddition of BCBs have been long-standing formidable challenges. Here, we report Pd-catalyzed ligand-controlled, tunable cycloadditions for the divergent synthesis of bridged bicyclic frameworks. The dppb ligand facilitates the formal (5+3) cycloaddition of BCBs and vinyl oxiranes, yielding valuable eight-membered ethers with bridged bicyclic scaffolds in 100% regioselectivity. The Cy-DPEphos ligand promotes selective hetero-[2σ+2σ] cycloadditions to access pharmacologically important 2-oxabicyclo[3.1.1]heptane (O-BCHeps). Furthermore, the corresponding catalytic asymmetric synthesis of O-BCHeps with 94-99% ee has been achieved using chiral (S)-DTBM-Segphos, representing the first catalytic asymmetric cross-dimerization of two strained rings. The obtained O-BCHeps are promising bioisosteres for ortho-substituted benzenes.

Exploring Antiviral Drugs on Monolayer Black Phosphorene: Atomistic Theory and Explainable Machine Learning-Assisted Platform.

Favipiravir (FP) and ebselen (EB) belong to a diverse class of antiviral drugs known for their significant efficacy in treating various viral infections. Utilizing molecular dynamics (MD) simulations, machine learning, and van der Waals density functional theory, we accurately elucidate the binding properties of these antiviral drugs on a phosphorene single-layer. To further investigate these characteristics, this study employs four distinct machine learning models-Random Forest, Gradient Boosting, XGBoost, and CatBoost. The Hamiltonian of antiviral molecules within a monolayer of phosphorene is appropriately trained. The key aspect of utilizing machine learning (ML) in drug design revolves around training models that are efficient and precise in approximating density functional theory (DFT). Furthermore, the study employs SHAP (SHapley Additive exPlanations) to elucidate model predictions, providing insights into the contribution of each feature. To explore the interaction characteristics and thermodynamic properties of the hybrid drug, we employ molecular dynamics and DFT calculations in a vacuum interface. Our findings suggest that this functionalized 2D complex exhibits robust thermostability, indicating its potential as an effective and enabled entity. The observed variations in free energy at different surface charges and temperatures suggest the adsorption potential of FP and EB molecules from the surrounding environment.

Molecular characterization of vascular endothelial growth factor b from spotted sea bass (Lateolabrax maculatus) and its potential roles in decreasing lipid deposition.

Vascular endothelial growth factor B (VEGFB), a member of the VEGF family, exhibits limited angiogenic activity in mammals but plays an unexpected role in targeting lipids to peripheral tissues. However, its role in lipid metabolism in fish is unknown. In this study, the vegfb gene was cloned and characterized from spotted sea bass (Lateolabrax maculatus). It encodes 254 amino acids and possesses the typical characteristics of the Vegfb family, demonstrating high homology with those from other vertebrate species. The vegfb gene exhibits the highest expression levels in the liver, followed by the gills, intestine, and adipose tissues in spotted sea bass. In vivo, high-lipid diets decreased vegfb expression and increased lipid deposition in liver of fish. In vitro, palmitic acid + oleic acid treatment or vegfb knockdown significantly increased TG and TC contents, promoting lipid droplet deposition in hepatocytes. Vegfb overexpression has the opposite effects, inhibiting lipid deposition and downregulating fatty acid transport and adipogenesis genes. In contrast, the vegfb knockdown significantly upregulated the expression levels of c/ebpα, plin2, and dgat1 (P < 0.05). These results demonstrate that Vegfb may play an important role in reducing lipid deposition by regulating fatty acid transport and adipogenesis in the hepatocytes of spotted sea bass.

In situ single iron atom doping on Bi2WO6 monolayers triggers efficient photo-fenton reaction.

Developing an efficient photocatalytic system for hydrogen peroxide (H2O2) activation in Fenton-like processes holds significant promise for advancing water purification technologies. However, challenges such as high carrier recombination rates, limited active sites, and suboptimal H2O2 activation efficiency impede optimal performance. Here we show that single-iron-atom dispersed Bi2WO6 monolayers (SIAD-BWOM), designed through a facile hydrothermal approach, can offer abundant active sites for H2O2 activation. The SIAD-BWOM catalyst demonstrates superior photo-Fenton degradation capabilities, particularly for the persistent pesticide dinotefuran (DNF), showcasing its potential in addressing recalcitrant organic pollutants. We reveal that the incorporation of iron atoms in place of tungsten within the electron-rich [WO4]2- layers significantly facilitates electron transfer processes and boosts the Fe(II)/Fe(III) cycle efficiency. Complementary experimental investigations and theoretical analyses further elucidate how the atomically dispersed iron induces lattice strain in the Bi2WO6 monolayer, thereby modulating the d-band center of iron to improve H2O2 adsorption and activation. Our research provides a practical framework for developing advanced photo-Fenton catalysts, which can be used to treat emerging and refractory organic pollutants more effectively.

How Coparenting Is Linked to Depression among Chinese Young Girls and Boys: Evidence from a Network Analysis.

This study aimed to explore the relationship between parental coparenting and depression among Chinese young adolescents and potential gender differences via network analysis. Thus, 793 fourth-grade students (girls: 281 (35.40%), Mage = 9.99 years, SD = 0.59 years) were recruited from three primary schools in Northern China. The young adolescents rated their depression and perceived paternal and maternal coparenting. Network analysis was used to detect the central nodes and bridge mechanisms among coparenting and depressive components. The results indicated that paternal and maternal consistency as well as maternal conflict were the most central components in the coparenting-depression network. Paternal consistency, maternal conflict and paternal disparagement in coparenting, as well as somatic complaints and positive affect in adolescents' depression, exhibited high bridge strengths, suggesting those constructs served as vital bridges to connect the two subnetworks. Moreover, paternal consistency showed a higher bridge strength in the boys' network than the girls' one, whereas the edge linking adolescents' positive affect to paternal disparagement and integrity was stronger in the girls' network. This study contributes to the understanding of associations between parental coparenting and young adolescents' depression and offered insights into targeted interventions for early adolescent depression by enhancing parental coparenting.

Advances in Biosensors for the Rapid Detection of Marine Biotoxins: Current Status and Future Perspectives.

Marine biotoxins (MBs), harmful metabolites of marine organisms, pose a significant threat to marine ecosystems and human health due to their diverse composition and widespread occurrence. Consequently, rapid and efficient detection technology is crucial for maintaining marine ecosystem and human health. In recent years, rapid detection technology has garnered considerable attention for its pivotal role in identifying MBs, with advancements in sensitivity, specificity, and accuracy. These technologies offer attributes such as speed, high throughput, and automation, thereby meeting detection requirements across various scenarios. This review provides an overview of the classification and risks associated with MBs. It briefly outlines the current research status of marine biotoxin biosensors and introduces the fundamental principles, advantages, and limitations of optical, electrochemical, and piezoelectric biosensors. Additionally, the review explores the current applications in the detection of MBs and presents forward-looking perspectives on their development, which aims to be a comprehensive resource for the design and implementation of tailored biosensors for effective MB detection.

Patient privacy in AI-driven omics methods.

Artificial intelligence (AI) in omics analysis raises privacy threats to patients. Here, we briefly discuss risk factors to patient privacy in data sharing, model training, and release, as well as methods to safeguard and evaluate patient privacy in AI-driven omics methods.

Gene expression prognostic of early relapse risk in low-risk B-cell acute lymphoblastic leukaemia in children.

ETV6::RUNX1 is the most common fusion gene in childhood acute lymphoblastic leukaemia (ALL) and is associated with favorable outcomes, especially in low-risk children. However, as many as 10% of children relapse within 3 years, and such early relapses have poor survival. Identifying children at risk for early relapse is an important challenge. We interrogated data from 87 children with low-risk ETV6::RUNX1-positive B-cell ALL and with available preserved bone marrow samples (discovery cohort). We profiled somatic point mutations in a panel of 559 genes and genome-wide transcriptome and single-nucleotide variants. We found high TIMD4 expression (> 85th-percentile value) at diagnosis was the most important independent prognostic factor of early relapse (hazard ratio [HR] = 5.07 [1.76, 14.62]; p = 0.03). In an independent validation cohort of low-risk ETV6::RUNX1-positive B-cell ALL (N = 68) high TIMD4 expression at diagnosis had an HR = 4.78 [1.07, 21.36] (p = 0.04) for early relapse. In another validation cohort including 78 children with low-risk ETV6::RUNX1-negative B-cell ALL, high TIMD4 expression at diagnosis had an HR = 3.93 [1.31, 11.79] (p = 0.01). Our results suggest high TIMD4 expression at diagnosis in low-risk B-cell ALL in children might be associated with high risk for early relapse.