SUCLG1 restricts POLRMT succinylation to enhance mitochondrial biogenesis and leukemia progression.

Mitochondria are cellular powerhouses that generate energy through the electron transport chain (ETC). The mitochondrial genome (mtDNA) encodes essential ETC proteins in a compartmentalized manner, however, the mechanism underlying metabolic regulation of mtDNA function remains unknown. Here, we report that expression of tricarboxylic acid cycle enzyme succinate-CoA ligase SUCLG1 strongly correlates with ETC genes across various TCGA cancer transcriptomes. Mechanistically, SUCLG1 restricts succinyl-CoA levels to suppress the succinylation of mitochondrial RNA polymerase (POLRMT). Lysine 622 succinylation disrupts the interaction of POLRMT with mtDNA and mitochondrial transcription factors. SUCLG1-mediated POLRMT hyposuccinylation maintains mtDNA transcription, mitochondrial biogenesis, and leukemia cell proliferation. Specifically, leukemia-promoting FMS-like tyrosine kinase 3 (FLT3) mutations modulate nuclear transcription and upregulate SUCLG1 expression to reduce succinyl-CoA and POLRMT succinylation, resulting in enhanced mitobiogenesis. In line, genetic depletion of POLRMT or SUCLG1 significantly delays disease progression in mouse and humanized leukemia models. Importantly, succinyl-CoA level and POLRMT succinylation are downregulated in FLT3-mutated clinical leukemia samples, linking enhanced mitobiogenesis to cancer progression. Together, SUCLG1 connects succinyl-CoA with POLRMT succinylation to modulate mitochondrial function and cancer development.

Three-stage ultrafast demagnetization dynamics in a monolayer ferromagnet.

Intense laser pulses can be used to demagnetize a magnetic material on an extremely short timescale. While this ultrafast demagnetization offers the potential for new magneto-optical devices, it poses challenges in capturing coupled spin-electron and spin-lattice dynamics. In this article, we study the photoinduced ultrafast demagnetization of a prototype monolayer ferromagnet Fe3GeTe2 and resolve the three-stage demagnetization process characterized by an ultrafast and substantial demagnetization on a timescale of 100 fs, followed by light-induced coherent A1g phonon dynamics which is strongly coupled to the spin dynamics in the next 200-800 fs. In the third stage, chiral lattice vibrations driven by nonlinear phonon couplings, both in-plane and out-of-plane are produced, resulting in significant spin precession. Nonadiabatic effects are found to introduce considerable phonon hardening and suppress the spin-lattice couplings during demagnetization. Our results advance our understanding of dynamic charge-spin-lattice couplings in the ultrafast demagnetization and evidence angular momentum transfer between the phonon and spin degrees of freedom.

Unveiling the repressive mechanism of a PPS-like regulator (PspR) in polyhydroxyalkanoates biosynthesis network.

Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) is a type of polyhydroxyalkanoates (PHA) that exhibits numerous outstanding properties and is naturally synthesized and elaborately regulated in various microorganisms. However, the regulatory mechanism involving the specific regulator PhaR in Haloferax mediterranei, a major PHBV production model among Haloarchaea, is not well understood. In our previous study, we showed that deletion of the phosphoenolpyruvate (PEP) synthetase-like (pps-like) gene activates the cryptic phaC genes in H. mediterranei, resulting in enhanced PHBV accumulation. In this study, we demonstrated the specific function of the PPS-like protein as a negative regulator of phaR gene expression and PHBV synthesis. Chromatin immunoprecipitation (ChIP), in situ fluorescence reporting system, and in vitro electrophoretic mobility shift assay (EMSA) showed that the PPS-like protein can bind to the promoter region of phaRP. Computational modeling revealed a high structural similarity between the rifampin phosphotransferase (RPH) protein and the PPS-like protein, which has a conserved ATP-binding domain, a His domain, and a predicted DNA-binding domain. Key residues within this unique DNA-binding domain were subsequently validated through point mutation and functional evaluations. Based on these findings, we concluded that PPS-like protein, which we now renamed as PspR, has evolved into a repressor capable of regulating the key regulator PhaR, and thereby modulating PHBV synthesis. This regulatory network (PspR-PhaR) for PHA biosynthesis is likely widespread among haloarchaea, providing a novel approach to manipulate haloarchaea as a production platform for high-yielding PHA. KEY POINTS: • The repressive mechanism of a novel inhibitor PspR in the PHBV biosynthesis was demonstrated • PspR is widespread among the PHA accumulating haloarchaea • It is the first report of functional conversion from an enzyme to a trans-acting regulator in haloarchaea.

Evolving immune evasion and transmissibility of SARS-CoV-2: The emergence of JN.1 variant and its global impact.

The continuous evolution of SARS-CoV-2 variants constitutes a significant impediment to the public health. The World Health Organization (WHO) has designated the SARS-CoV-2 variant JN.1, which has evolved from its progenitor BA.2.86, as a Variant of Interest (VOI) in light of its enhanced immune evasion and transmissibility. The proliferating dissemination of JN.1 globally accentuates its competitive superiority and the potential to instigate fresh surges of infection, notably among cohorts previously infected by antecedent variants. Notably, prevailing evidence does not corroborate an increase in pathogenicity associated with JN.1, and antiviral agents retain their antiviral activity against both BA.2.86 and JN.1. The sustained effectiveness of antiviral agents offers a beacon of hope. Nonetheless, the variant's adeptness at eluding the immunoprotective effects conferred by extant vaccines highlights the imperative for the development of more effective vaccines and therapeutic approaches. Overall, the distinct evolutionary trajectories of BA.2.86 and JN.1 underscore the necessity for ongoing surveillance and scholarly inquiry to elucidate their implications for the pandemic's evolution, which requires the international communities to foster collaboration through the sharing of data, exchange of insights, and collective scientific endeavors.

Remotely Bonded Bridging Dioxygen Ligands Enhance Hydrogen Transfer in a Silica-Supported Tetrairidium Cluster Catalyst.

A longstanding challenge in catalysis by noble metals has been to understand the origin of enhancements of rates of hydrogen transfer that result from the bonding of oxygen near metal sites. We investigated structurally well-defined catalysts consisting of supported tetrairidium carbonyl clusters with single-atom (apical iridium) catalytic sites for ethylene hydrogenation. Reaction of the clusters with ethylene and H2 followed by O2 led to the onset of catalytic activity as a terminal CO ligand at each apical Ir atom was removed and bridging dioxygen ligands replaced CO ligands at neighboring (basal-plane) sites. The presence of the dioxygen ligands caused a 6-fold increase in the catalytic reaction rate, which is explained by the electron-withdrawing capability induced by the bridging dioxygen ligands, consistent with the inference that reductive elimination is rate-determining. Electronic-structure calculations demonstrate an additional role of the dioxygen ligands, changing the mechanism of hydrogen transfer from one involving equatorial hydride ligands to that involving bridging hydride ligands. This mechanism is made evident by an inverse kinetic isotope effect observed in ethylene hydrogenation reactions with H2 and, alternatively, with D2 on the cluster incorporating the dioxygen ligands and is a consequence of quasi-equilibrated hydrogen transfer in this catalyst. The same mechanism accounts for rate enhancements induced by the bridging dioxygen ligands for the catalytic reaction of H2 with D2 to give HD. We posit that the mechanism involving bridging hydride ligands facilitated by oxygen ligands remote from the catalytic site may have some generality in catalysis by oxide-supported noble metals.

Passionfruit Genomic Database (PGD): a comprehensive resource for passionfruit genomics.

Passionfruit (Passiflora edulis) is a significant fruit crop in the commercial sector, owing to its high nutritional and medicinal value. The advent of high-throughput genomics sequencing technology has led to the publication of a vast amount of passionfruit omics data, encompassing complete genome sequences and transcriptome data under diverse stress conditions. To facilitate the efficient integration, storage, and analysis of these large-scale datasets, and to enable researchers to effectively utilize these omics data, we developed the first passionfruit genome database (PGD). The PGD platform comprises a diverse range of functional modules, including a genome browser, search function, heatmap, gene expression patterns, various tools, sequence alignment, and batch download, thereby providing a user-friendly interface. Additionally, supplementary practical tools have been developed for the PGD, such as gene family analysis tools, gene ontology (GO) terms, a pathway enrichment analysis, and other data analysis and mining tools, which enhance the data's utilization value. By leveraging the database's robust scalability, the intention is to continue to collect and integrate passionfruit omics data in the PGD, providing comprehensive and in-depth support for passionfruit research. The PGD is freely accessible via http://passionfruit.com.cn .

NEAT1 repression by MED12 creates chemosensitivity in p53 wild-type breast cancer cells.

Breast cancer is often treated with chemotherapy. However, the development of chemoresistance results in treatment failure. Long non-coding RNA nuclear paraspeckle assembly transcript 1 (NEAT1) has been shown to contribute to chemoresistance in breast cancer cells. In studying the transcriptional regulation of NEAT1 using multi-omics approaches, we showed that NEAT1 is up-regulated by 5-fluorouracil in breast cancer cells with wild-type cellular tumor antigen p53 but not in mutant-p53-expressing breast cancer cells. The regulation of NEAT1 involves mediator complex subunit 12 (MED12)-mediated repression of histone acetylation marks at the promoter region of NEAT1. Knockdown of MED12 but not coactivator-associated arginine methyltransferase 1 (CARM1) induced histone acetylation at the NEAT1 promoter, leading to elevated NEAT1 mRNAs, resulting in a chemoresistant phenotype. The MED12-dependent regulation of NEAT1 differs between wild-type and mutant p53-expressing cells. MED12 depletion led to increased expression of NEAT1 in a wild-type p53 cell line, but decreased expression in a mutant p53 cell line. Chemoresistance caused by MED12 depletion can be partially rescued by NEAT1 knockdown in p53 wild-type cells. Collectively, our study reveals a novel mechanism of chemoresistance dependent on MED12 transcriptional regulation of NEAT1 in p53 wild-type breast cancer cells.

Members of the class Candidatus Ordosarchaeia imply an alternative evolutionary scenario from methanogens to haloarchaea.

The origin of methanogenesis can be traced to the common ancestor of non-DPANN archaea, whereas haloarchaea (or Halobacteria) are believed to have evolved from a methanogenic ancestor through multiple evolutionary events. However, due to the accelerated evolution and compositional bias of proteins adapting to hypersaline habitats, Halobacteria exhibit substantial evolutionary divergence from methanogens, and the identification of the closest methanogen (either Methanonatronarchaeia or other taxa) to Halobacteria remains a subject of debate. Here, we obtained five metagenome-assembled genomes with high completeness from soda-saline lakes on the Ordos Plateau in Inner Mongolia, China, and we proposed the name Candidatus Ordosarchaeia for this novel class. Phylogenetic analyses revealed that Ca. Ordosarchaeia is firmly positioned near the median position between the Methanonatronarchaeia and Halobacteria-Hikarchaeia lineages. Functional predictions supported the transitional status of Ca. Ordosarchaeia with the metabolic potential of nonmethanogenic and aerobic chemoheterotrophy, as did remnants of the gene sequences of methylamine/dimethylamine/trimethylamine metabolism and coenzyme M biosynthesis. Based on the similarity of the methyl-coenzyme M reductase genes mcrBGADC in Methanonatronarchaeia with the phylogenetically distant methanogens, an alternative evolutionary scenario is proposed, in which Methanonatronarchaeia, Ca. Ordosarchaeia, Ca. Hikarchaeia, and Halobacteria share a common ancestor that initially lost mcr genes. However, certain members of Methanonatronarchaeia subsequently acquired mcr genes through horizontal gene transfer from distantly related methanogens. This hypothesis is supported by amalgamated likelihood estimation, phylogenetic analysis, and gene arrangement patterns. Altogether, Ca. Ordosarchaeia genomes clarify the sisterhood of Methanonatronarchaeia with Halobacteria and provide new insights into the evolution from methanogens to haloarchaea.

The role of macrophages in gastric cancer.

As one of the deadliest cancers of the gastrointestinal tract, there has been limited improvement in long-term survival rates for gastric cancer (GC) in recent decades. The poor prognosis is attributed to difficulties in early detection, minimal opportunity for radical resection and resistance to chemotherapy and radiation. Macrophages are among the most abundant infiltrating immune cells in the GC stroma. These cells engage in crosstalk with cancer cells, adipocytes and other stromal cells to regulate metabolic, inflammatory and immune status, generating an immunosuppressive tumour microenvironment (TME) and ultimately promoting tumour initiation and progression. In this review, we summarise recent advances in our understanding of the origin of macrophages and their types and polarisation in cancer and provide an overview of the role of macrophages in GC carcinogenesis and development and their interaction with the GC immune microenvironment and flora. In addition, we explore the role of macrophages in preclinical and clinical trials on drug resistance and in treatment of GC to assess their potential therapeutic value in this disease.

Comparison of Clinicopathological Features and Prognosis of Mucinous Gastric Carcinoma and other Gastric Cancers: A Retrospective Study of 4,417 Patients.

BACKGROUND: Mucinous gastric carcinoma (MGC) is a distinct histologic subtype of gastric cancer (GC) that is often diagnosed at an advanced stage. The clinicopathological characteristics and prognosis of MGC, when compared to adenocarcinoma and signet-ring cell carcinoma (SRCC), are currently subjects of debate and require further investigation. METHODS: In this study, we conducted an investigation on 4,417 patients who were hospitalized with GC at Zhejiang Cancer Hospital between April 2008 and December 2019. The objective was to compare the prognosis and clinicopathological characteristics of MGC with other types of GC. RESULTS: In comparison to adenocarcinoma, MGC patients exhibited more advanced tumor infiltration (p < 0.001), lower tumor differentiation (p < 0.001), and higher rates of preoperative tumor marker positivity (except for AFP and CA125) (all p < 0.05). However, after propensity score matching (PSM) to eliminate confounding factors, MGC patients surprisingly exhibited a better prognosis than adenocarcinoma patients (p = 0.008), and the results in multifactorial COX regression were similar (HR = 0.792, 95% CI 0.629-0.997, p = 0.047). Among patients with MGC, age, pN stage, as well as preoperative levels of CA125 and CA724 (all p < 0.05), emerged as independent prognostic markers. While overall survival did not significantly differ between MGC and SRCC (p = 0.196), significant survival disparities emerged in advanced-stage patients (p = 0.009), with MGC showing better survival rates. Furthermore, a nomogram was developed to predict 1-, 3-, and 5-year survival in gastric cancer patients based on various factors, achieving a C-index of 0.772 (95% CI: 0.745-0.799). CONCLUSIONS: While the poorer prognosis associated with MGC may be linked to its advanced stage and lower degree of differentiation, its biological behavior could contribute to improved survival.

A-GCL: Adversarial graph contrastive learning for fMRI analysis to diagnose neurodevelopmental disorders.

Accurate diagnosis of neurodevelopmental disorders is a challenging task due to the time-consuming cognitive tests and potential human bias in clinics. To address this challenge, we propose a novel adversarial self-supervised graph neural network (GNN) based on graph contrastive learning, named A-GCL, for diagnosing neurodevelopmental disorders using functional magnetic resonance imaging (fMRI) data. Taking advantage of the success of GNNs in psychiatric disease diagnosis using fMRI, our proposed A-GCL model is expected to improve the performance of diagnosis and provide more robust results. A-GCL takes graphs constructed from the fMRI images as input and uses contrastive learning to extract features for classification. The graphs are constructed with 3 bands of the amplitude of low-frequency fluctuation (ALFF) as node features and Pearson's correlation coefficients (PCC) of the average fMRI time series in different brain regions as edge weights. The contrastive learning creates an edge-dropped graph from a trainable Bernoulli mask to extract features that are invariant to small variations of the graph. Experiment results on three datasets - Autism Brain Imaging Data Exchange (ABIDE) I, ABIDE II, and attention deficit hyperactivity disorder (ADHD) - with 3 atlases - AAL1, AAL3, Shen268 - demonstrate the superiority and generalizability of A-GCL compared to the other GNN-based models. Extensive ablation studies verify the robustness of the proposed approach to atlas selection and model variation. Explanatory results reveal key functional connections and brain regions associated with neurodevelopmental disorders.

Deep Learning-Assisted Quantitative Susceptibility Mapping as a Tool for Grading and Molecular Subtyping of Gliomas.

This study aimed to explore the value of deep learning (DL)-assisted quantitative susceptibility mapping (QSM) in glioma grading and molecular subtyping. Forty-two patients with gliomas, who underwent preoperative T2 fluid-attenuated inversion recovery (T2 FLAIR), contrast-enhanced T1-weighted imaging (T1WI + C), and QSM scanning at 3.0T magnetic resonance imaging (MRI) were included in this study. Histopathology and immunohistochemistry staining were used to determine glioma grades, and isocitrate dehydrogenase (IDH) 1 and alpha thalassemia/mental retardation syndrome X-linked gene (ATRX) subtypes. Tumor segmentation was performed manually using Insight Toolkit-SNAP program (www.itksnap.org). An inception convolutional neural network (CNN) with a subsequent linear layer was employed as the training encoder to capture multi-scale features from MRI slices. Fivefold cross-validation was utilized as the training strategy (seven samples for each fold), and the ratio of sample size of the training, validation, and test dataset was 4:1:1. The performance was evaluated by the accuracy and area under the curve (AUC). With the inception CNN, single modal of QSM showed better performance in differentiating glioblastomas (GBM) and other grade gliomas (OGG, grade II-III), and predicting IDH1 mutation and ATRX loss (accuracy: 0.80, 0.77, 0.60) than either T2 FLAIR (0.69, 0.57, 0.54) or T1WI + C (0.74, 0.57, 0.46). When combining three modalities, compared with any single modality, the best AUC/accuracy/F1-scores were reached in grading gliomas (OGG and GBM: 0.91/0.89/0.87, low-grade and high-grade gliomas: 0.83/0.86/0.81), predicting IDH1 mutation (0.88/0.89/0.85), and predicting ATRX loss (0.78/0.71/0.67). As a supplement to conventional MRI, DL-assisted QSM is a promising molecular imaging method to evaluate glioma grades, IDH1 mutation, and ATRX loss. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00087-6.

A Priori Design of Dual-Atom Alloy Sites and Experimental Demonstration of Ethanol Dehydrogenation and Dehydration on PtCrAg.

Single-atom catalysts have received significant attention for their ability to enable highly selective reactions. However, many reactions require more than one adjacent site to align reactants or break specific bonds. For example, breaking a C-O or O-H bond may be facilitated by a dual site containing an oxophilic element and a carbophilic or "hydrogenphilic" element that binds each molecular fragment. However, design of stable and well-defined dual-atom sites with desirable reactivity is difficult due to the complexity of multicomponent catalytic surfaces. Here, we describe a new type of dual-atom system, trimetallic dual-atom alloys, which were designed via computation of the alloying energetics. Through a broad computational screening we discovered that Pt-Cr dimers embedded in Ag(111) can be formed by virtue of the negative mixing enthalpy of Pt and Cr in Ag and the favorable interaction between Pt and Cr. These dual-atom alloy sites were then realized experimentally through surface science experiments that enabled the active sites to be imaged and their reactivity related to their atomic-scale structure. Specifically, Pt-Cr sites in Ag(111) can convert ethanol, whereas PtAg and CrAg are unreactive toward ethanol. Calculations show that the oxophilic Cr atom and the hydrogenphilic Pt atom act synergistically to break the O-H bond. Furthermore, ensembles with more than one Cr atom, present at higher dopant loadings, produce ethylene. Our calculations have identified many other thermodynamically favorable dual-atom alloy sites, and hence this work highlights a new class of materials that should offer new and useful chemical reactivity beyond the single-atom paradigm.

Targeting CLDN18.2 in cancers of the gastrointestinal tract: New drugs and new indications.

Cancers of the gastrointestinal (GI) tract greatly contribute to the global cancer burden and cancer-related death. Claudin-18.2(CLDN18.2), a transmembrane protein, is a major component of tight junctions and plays an important role in the maintenance of barrier function. Its characteristic widespread expression in tumour tissues and its exposed extracellular loops make it an ideal target for researchers to develop targeted strategies and immunotherapies for cancers of the GI tract. In the present review, we focus on the expression pattern of CLDN18.2 and its clinical significance in GI cancer. We also discuss the tumour-promoting and/or tumour-inhibiting functions of CLDN18.2, the mechanisms regulating its expression, and the current progress regarding the development of drugs targeting CLDN18.2 in clinical research.

Integrative proteomic characterization of adenocarcinoma of esophagogastric junction.

The incidence of adenocarcinoma of the esophagogastric junction (AEG) has been rapidly increasing in recent decades, but its molecular alterations and subtypes are still obscure. Here, we conduct proteomics and phosphoproteomics profiling of 103 AEG tumors with paired normal adjacent tissues (NATs), whole exome sequencing of 94 tumor-NAT pairs, and RNA sequencing in 83 tumor-NAT pairs. Our analysis reveals an extensively altered proteome and 252 potential druggable proteins in AEG tumors. We identify three proteomic subtypes with significant clinical and molecular differences. The S-II subtype signature protein, FBXO44, is demonstrated to promote tumor progression and metastasis in vitro and in vivo. Our comparative analyses reveal distinct genomic features in AEG subtypes. We find a specific decrease of fibroblasts in the S-III subtype. Further phosphoproteomic comparisons reveal different kinase-phosphosubstrate regulatory networks among AEG subtypes. Our proteogenomics dataset provides valuable resources for understanding molecular mechanisms and developing precision treatment strategies of AEG.

Adipocyte Thyroid Hormone ß Receptor-Mediated Hormone Action Fine-tunes Intracellular Glucose and Lipid Metabolism and Systemic Homeostasis.

Thyroid hormone (TH) has a profound effect on energy metabolism and systemic homeostasis. Adipose tissues are crucial for maintaining whole-body homeostasis; however, whether TH regulates systemic metabolic homeostasis through its action on adipose tissues is unclear. Here, we demonstrate that systemic administration of triiodothyronine (T3), the active form of TH, affects both inguinal white adipose tissue (iWAT) and whole-body metabolism. Taking advantage of the mouse model lacking adipocyte TH receptor (TR) α or TRß, we show that TRß is the major TR isoform that mediates T3 action on the expression of genes involved in multiple metabolic pathways in iWAT, including glucose uptake and use, de novo fatty acid synthesis, and both UCP1-dependent and -independent thermogenesis. Moreover, our results indicate that glucose-responsive lipogenic transcription factor in iWAT is regulated by T3, thereby being critically involved in T3-regulated glucose and lipid metabolism and energy dissipation. Mice with adipocyte TRß deficiency are susceptible to diet-induced obesity and metabolic dysregulation, suggesting that TRß in adipocytes may be a potential target for metabolic diseases. ARTICLE HIGHLIGHTS: How thyroid hormone (TH) achieves its diverse biological activities in the regulation of metabolism is not fully understood. Whether TH regulates systemic metabolic homeostasis via its action on white adipose tissue is unclear. Adipocyte TH receptor (TR) ß mediates the triiodothyronine effect on multiple metabolic pathways by targeting glucose-responsive lipogenic transcription factor in white adipose tissue; mice lacking adipocyte TRß are susceptible to high-fat diet-induced metabolic abnormalities. TRß in white adipocytes controls intracellular and systemic metabolism and may be a potential target for metabolic diseases.

TW-Net: Transformer Weighted Network for Neonatal Brain MRI Segmentation.

Accurate neonatal brain MRI segmentation is valuable for investigating brain growth patterns and tracking the progression of neurodevelopmental disorders. However, it is a challenging task to use intensity-based methods to segment neonatal brain structures because of small contrast differences between brain regions caused by the inherent myelination process. Although convolutional neural networks offer the potential to segment brain structures in an intensity-independent manner, they suffer from lack of in-plane long-range dependency which is essential for the segmentation. To solve this problem, we propose a novel Transformer-Weighted network (TW-Net) to incorporate in-plane long-range dependency information. TW-Net employs a conventional encoder-decoder architecture with a Transformer module in the middle. The Transformer module uses a rotate-and-flip layer to better calculate the similarity between two patches in a slice to leverage similar patterns of geometrical and texture features within brain structures. In addition, a deep supervision module and squeeze-and-excitation blocks are introduced to incorporate boundary information of brain structures. Compared with state-of-the-art deep learning algorithms, TW-Net outperforms these methods for multiple-label tasks in 2D and 2.5D configurations on two independent public datasets, demonstrating that TW-Net is a promising method for neonatal brain MRI segmentation.

MouseGAN++: Unsupervised Disentanglement and Contrastive Representation for Multiple MRI Modalities Synthesis and Structural Segmentation of Mouse Brain.

Segmenting the fine structure of the mouse brain on magnetic resonance (MR) images is critical for delineating morphological regions, analyzing brain function, and understanding their relationships. Compared to a single MRI modality, multimodal MRI data provide complementary tissue features that can be exploited by deep learning models, resulting in better segmentation results. However, multimodal mouse brain MRI data is often lacking, making automatic segmentation of mouse brain fine structure a very challenging task. To address this issue, it is necessary to fuse multimodal MRI data to produce distinguished contrasts in different brain structures. Hence, we propose a novel disentangled and contrastive GAN-based framework, named MouseGAN++, to synthesize multiple MR modalities from single ones in a structure-preserving manner, thus improving the segmentation performance by imputing missing modalities and multi-modality fusion. Our results demonstrate that the translation performance of our method outperforms the state-of-the-art methods. Using the subsequently learned modality-invariant information as well as the modality-translated images, MouseGAN++ can segment fine brain structures with averaged dice coefficients of 90.0% (T2w) and 87.9% (T1w), respectively, achieving around +10% performance improvement compared to the state-of-the-art algorithms. Our results demonstrate that MouseGAN++, as a simultaneous image synthesis and segmentation method, can be used to fuse cross-modality information in an unpaired manner and yield more robust performance in the absence of multimodal data. We release our method as a mouse brain structural segmentation tool for free academic usage at https://github.com/yu02019.

Force and Velocity Analysis of Particles Manipulated by Toroidal Vortex on Optoelectrokinetic Microfluidic Platform.

The rapid electrokinetic patterning (REP) technique has been demonstrated to enable dynamic particle manipulation in biomedical applications. Previous studies on REP have generally considered particles with a size less than 5 µm. In this study, a REP platform was used to manipulate polystyrene particles with a size of 3~11 µm in a microfluidic channel sandwiched between two ITO conductive glass plates. The effects of the synergy force produced by the REP electrothermal vortex on the particle motion were investigated numerically for fixed values of the laser power, AC driving voltage, and AC driving frequency, respectively. The simulation results showed that the particles were subject to a competition effect between the drag force produced by the toroidal vortex, which prompted the particles to recirculate in the bulk flow adjacent to the laser illumination spot on the lower electrode, and the trapping force produced by the particle and electrode interactions, which prompted the particles to aggregate in clusters on the surface of the illuminated spot. The experimental results showed that as the laser power increased, the toroidal flow range over which the particles circulated in the bulk flow increased, while the cluster range over which the particles were trapped on the electrode surface reduced. The results additionally showed that the particle velocity increased with an increasing laser power, particularly for particles with a smaller size. The excitation frequency at which the particles were trapped on the illuminated hot-spot reduced as the particle size increased. The force and velocity of polystyrene particles by the REP toroidal vortex has implications for further investigating the motion behavior at the biological cell level.

Tuning reactivity in trimetallic dual-atom alloys: molecular-like electronic states and ensemble effects.

Single-atom alloys (SAAs) have drawn significant attention in recent years due to their excellent catalytic properties. Controlling the geometry and electronic structure of this type of localized catalytic active site is of fundamental and technological importance. Dual-atom alloys (DAAs) consisting of a heterometallic dimer embedded in the surface layer of a metal host would bring increased tunability and a larger active site, as compared to SAAs. Here, we use computational studies to show that DAAs allow tuning of the active site electronic structure and reactivity. Interestingly, combining two SAAs into a dual-atom site can result in molecular-like hybridization by virtue of the free-atom-like electronic d states exhibited by many SAAs. DAAs can inherit the weak d-d interaction between dopants and hosts from the constituent SAAs, but exhibit new electronic and reactive properties due to dopant-dopant interactions in the DAA. We identify many heterometallic DAAs that we predict to be more stable than either the constituent SAAs or homometallic dual-atom sites of each dopant. We also show how both electronic and ensemble effects can modify the strength of CO adsorption. Because of the molecular-like interactions that can occur, DAAs require a different approach for tuning chemical properties compared to what is used for previous classes of alloys. This work provides insights into the unique catalytic properties of DAAs, and opens up new possibilities for tailoring localized and well-defined catalytic active sites for optimal reaction pathways.