Structure defining of ultrapotent neutralizing nanobodies against MERS-CoV with novel epitopes on receptor binding domain.

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe and fatal acute respiratory disease in humans. High fatality rates and continued infectiousness remain a pressing concern for global health preparedness. Antibodies targeted at the receptor-binding domain (RBD) are major countermeasures against human viral infection. Here, we report four potent nanobodies against MERS-CoV, which are isolated from alpaca, and especially the potency of Nb14 is highest in the pseudotyped virus assay. Structural studies show that Nb14 framework regions (FRs) are mainly involved in interactions targeting a novel epitope, which is entirely distinct from all previously reported antibodies, and disrupt the protein-carbohydrate interaction between residue W535 of RBD and hDPP4 N229-linked carbohydrate moiety (hDPP4-N229-glycan). Different from Nb14, Nb9 targets the cryptic face of RBD, which is distinctive from the hDPP4 binding site and the Nb14 epitope, and it induces the ß5-ß6 loop to inflect towards a shallow groove of the RBD and dampens the accommodation of a short helix of hDPP4. The particularly striking epitopes endow the two Nbs administrate synergistically in the pseudotyped MERS-CoV assays. These results not only character unprecedented epitopes for antibody recognition but also provide promising agents for prophylaxis and therapy of MERS-CoV infection.

Discovery of novel DNA-damaging agents through phenotypic screening for DNA double-strand break.

DNA double-strand breaks (DSBs) seriously damage DNA and promote genomic instability that can lead to cell death. They are the source of conditions such as carcinogenesis and aging, but also have important applications in cancer therapy. Therefore, rapid detection and quantification of DSBs in cells are necessary for identifying carcinogenic and anticancer factors. In this study, we detected DSBs using a flow cytometry-based high-throughput method to analyze γH2AX intensity. We screened a chemical library containing 9600 compounds and detected multiple DNA-damaging compounds, although we could not identify mechanisms of action through this procedure. Thus, we also profiled a representative compound with the highest DSB potential, DNA-damaging agent-1 (DDA-1), using a bioinformatics-based method we termed "molecular profiling." Prediction and verification analysis revealed DDA-1 as a potential inhibitor of topoisomerase IIα, different from known inhibitors such as etoposide and doxorubicin. Additional investigation of DDA-1 analogs and xenograft models suggested that DDA-1 is a potential anticancer drug. In conclusion, our findings established that combining high-throughput DSB detection and molecular profiling to undertake phenotypic analysis is a viable method for efficient identification of novel DNA-damaging compounds for clinical applications.

CDK1 inhibitor controls G2/M phase transition and reverses DNA damage sensitivity.

CDK1 plays key roles in cell cycle progression through the G2/M phase transition and activation of homologous recombination (HR) DNA repair pathway. Accordingly, various CDK1 inhibitors have been developed for cancer therapy that induce prolonged G2 arrest and/or sensitize cells to DNA damaging agents in tumor cells, resulting in cell death. However, CDK1 inhibition can induce resistance to DNA damage in certain conditions. The mechanism of different DNA damage sensitivity is not completely understood. We performed immunofluorescence and flow cytometry analysis to investigate DNA damage responses in human tumor cells during low and high dose treatments with RO-3306, a selective CDK1 inhibitor. This comparative investigation demonstrated that RO-3306-induced G2 arrest prevented cells with DNA double-strand breaks from transitioning into the M-phase and that the cells maintained their DNA repair capacity in G2-phase, even under RO-3306 dose-dependent DNA repair inhibition. These findings reveal that CDK1 inhibitor-induced DNA repair inhibition and cell cycle control, which regulate each other during the G2/M phase transition determine the cellular sensitivity to DNA damage, providing insight useful for developing clinical strategies targeting CDK1 inhibition in tumor cells.

Accelerating Electron-Transfer and Tuning Product Selectivity Through Surficial Vacancy Engineering on CZTS/CdS for Photoelectrochemical CO2 Reduction.

Copper-based chalcogenides have been considered as potential photocathode materials for photoelectrochemical (PEC) CO2 reduction due to their excellent photovoltaic performance and favorable conduction band alignment with the CO2 reduction potential. However, they suffer from low PEC efficiency due to the sluggish charge transfer kinetics and poor selectivity, resulting from random CO2 reduction reaction pathways. Herein, a facile heat treatment (HT) of a Cu2 ZnSnS4 (CZTS)/CdS photocathode is demonstrated to enable significant improvement in the photocurrent density (-0.75 mA cm-2 at -0.6 V vs RHE), tripling that of pristine CZTS, as a result of the enhanced charge transfer and promoted band alignment originating from the elemental inter-diffusion at the CZTS/CdS interface. In addition, rationally regulated CO2 reduction selectivity toward CO or alcohols can be obtained by tailoring the surficial sulfur vacancies by HT in different atmospheres (air and nitrogen). Sulfur vacancies replenished by O-doping is shown to favor CO adsorption and the CC coupling pathway, and thereby produce methanol and ethanol, whilst the CdS surface with more S vacancies promotes CO desorption capability with higher selectivity toward CO. The strategy in this work rationalizes the interface charge transfer optimization and surface vacancy engineering simultaneously, providing a new insight into PEC CO2 reduction photocathode design.

Brain connectivity markers in advanced Parkinson's disease for predicting mild cognitive impairment.

OBJECTIVES: Mild cognitive impairment (MCI) is a well-defined non-motor manifestation and a harbinger of dementia in Parkinson's disease. This study is to investigate brain connectivity markers of MCI using diffusion tensor imaging and resting-state functional MRI, and help MCI diagnosis in PD patients. METHODS: We evaluated 131 advanced PD patients (disease duration > 5 years; 59 patients with MCI) and 48 healthy control subjects who underwent a diffusion-weighted and resting-state functional MRI scanning. The patients were randomly assigned to training (n = 100) and testing (n = 31) groups. According to the Brainnetome Atlas, ROI-based structural and functional connectivity analysis was employed to extract connectivity features. To identify features with significant discriminative power for patient classification, all features were put into an all-relevant feature selection procedure within cross-validation loops. RESULTS: Nine features were identified to be significantly relevant to patient classification. They showed significant differences between PD patients with and without MCI and positively correlated with the MoCA score. Five of them did not differ between general MCI subjects and healthy controls from the ADNI database, which suggested that they could uniquely play a part in the MCI diagnosis of PD. On basis of these relevant features, the random forest model constructed from the training group achieved an accuracy of 83.9% in the testing group, to discriminate patients with and without MCI. CONCLUSIONS: The results of our study provide preliminary evidence that structural and functional connectivity abnormalities may contribute to cognitive impairment and allow to predict the outcome of MCI diagnosis in PD. KEY POINTS: • Nine MCI markers were identified using an all-relevant feature selection procedure. • Five of nine markers differed between MCI and NC in PD, but not in general persons. • A random forest model achieved an accuracy of 83.9% for MCI diagnosis in PD.

A Label-Free Fluorometric Glutathione Assay Based on a Conformational Switch of G-quadruplex.

In this paper, a label-free fluorescent method for glutathione (GSH) detection based on a thioflavin T/G-quadruplex conformational switch is developed. The sensing assay is fabricated depending on the virtue of mercury ions to form a thymine-thymine mismatch, which collapses the distance between two ssDNA and directs the guanine-rich part to form an intra-strand asymmetric split G-quadruplex. The newly formed G-quadruplex efficiently reacts with thioflavin T and enhances the fluorescent intensity. In the presence of GSH, Hg2+ is absorbed, destroying the G-quadruplex formation with a significant decrease in fluorescence emission. The proposed fluorescent assay exhibits a linear range between 0.03-5 µM of GSH with a detection limit of 9.8 nM. Furthermore, the efficacy of this method is examined using human serum samples to detect GSH. Besides GSH, other amino acids are also investigated in standard samples, which display satisfactory sensitivity and selectivity. Above all, we develop a method with features including potentiality, facility, sensitivity, and selectivity for analyzing GSH for clinical diagnostics.

Design, Synthesis, and Antibacterial Evaluation of Novel Ocotillol Derivatives and Their Synergistic Effects with Conventional Antibiotics.

The improper use of antibiotics has led to the development of bacterial resistance, resulting in fewer antibiotics for many bacterial infections. Especially, the drug resistance of hospital-acquired methicillin-resistant Staphylococcus aureus (HA-MRSA) is distinctly serious. This research designed and synthesized two series of 3-substituted ocotillol derivatives in order to improve their anti-HA-MRSA potency and synergistic antibacterial activity. Among the synthesized compounds, 20-31 showed minimum inhibitory concentration (MIC) values of 1-64 µg/mL in vitro against HA-MRSA 18-19, 18-20, and S. aureus ATCC29213. Compound 21 showed the best antibacterial activity, with an MIC of 1 µg/mL and had synergistic inhibitory effects. The fractional inhibitory concentration index (FICI) value was 0.375, when combined with chloramphenicol (CHL) or kanamycin (KAN). The structure-activity relationships (SARs) of ocotillol-type derivatives were also summarized. Compound 21 has the potential to be developed as a novel antibacterial agent or potentiator against HA-MRSA.

Hole-Storage Enhanced a-Si Photocathodes for Efficient Hydrogen Production.

Ferrihydrite (Fh) has been demonstrated as an effective interfacial layer for photoanodes to achieve outstanding photoelectrochemical (PEC) performance for water oxidation reaction owing to its unique hole-storage function. However, it is unknown whether such a hole-storage layer can be used to construct highly efficient photocathodes for hydrogen evolution reaction (HER). In this work, we report Fh interfacial engineering of amorphous silicon photocathode (with nickel as HER cocatalyst) achieving a photocurrent density of 15.6 mA cm-2 at 0 V vs. the reversible hydrogen electrode and a half-cell energy conversion efficiency of 4.08 % in alkaline solution, outperforming most of reported a-Si based photocathodes including multi-junction configurations integrated with noble metal cocatalysts in acid solution. Besides, the photocurrent density is maintained above 14 mA cm-2 for 175 min with 100 % Faradaic efficiency for HER in alkaline solution. Our results demonstrate a feasible approach to construct efficient photocathodes via the application of a hole-storage layer.

Brain connectivity markers for the identification of effective contacts in subthalamic nucleus deep brain stimulation.

The clinical benefit of deep brain stimulation (DBS) for Parkinson's disease (PD) is relevant to the tracts adjacent to the stimulation site, but it remains unclear what connectivity pattern is associated with effective DBS. The aim of this study was to identify clinically effective electrode contacts on the basis of brain connectivity markers derived from diffusion tensor tractography. We reviewed 77 PD patients who underwent bilateral subthalamic nucleus DBS surgery. The patients were assigned into the training (n = 58) and validation (n = 19) groups. According to the therapeutic window size, all contacts were classified into effective and ineffective groups. The whole-brain connectivity of each contact's volume of tissue activated was estimated using tractography with preoperative diffusion tensor data. Extracted connectivity features were put into an all-relevant feature selection procedure within cross-validation loops, to identify features with significant discriminative power for contact classification. A total of 616 contacts on 154 DBS leads were discriminated, with 388 and 228 contacts being classified as effective and ineffective ones, respectively. After the feature selection, the connectivity of contacts with the thalamus, pallidum, hippocampus, primary motor area, supplementary motor area and superior frontal gyrus was identified to significantly contribute to contact classification. Based on these relevant features, the random forest model constructed from the training group achieved an accuracy of 84.9% in the validation group, to discriminate effective contacts from the ineffective. Our findings advanced the understanding of the specific brain connectivity patterns associated with clinical effective electrode contacts, which potentially guided postoperative DBS programming.

Surface strategies for catalytic CO2 reduction: from two-dimensional materials to nanoclusters to single atoms.

Redox catalysis, including photocatalysis and (photo)electrocatalysis, may alleviate global warming and energy crises by removing excess CO2 from the atmosphere and converting it to value-added resources. Nano-to-atomic two-dimensional (2D) materials, clusters and single atoms are superior catalysts because of their engineerable ultrathin/small dimensions and large surface areas and have attracted worldwide research interest. Given the current gap between research and applications in CO2 reduction, our review systematically and constructively discusses nano-to-atomic surface strategies for catalysts reported to date. This work is expected to drive and benefit future research to rationally design surface strategies with multi-parameter synergistic impacts on the selectivity, activity and stability of next-generation CO2 reduction catalysts, thus opening new avenues for sustainable solutions to climate change, energy and environmental issues, and the potential industrial economy.

Redox/NIR dual-responsive MoS2 for synergetic chemo-photothermal therapy of cancer.

BACKGROUND: The construction of a multifunctional drug delivery system with a variety of advantageous features, including targeted delivery, controlled release and combined therapy, is highly attractive but remains a challenge. RESULTS: In this study, we developed a MoS2-based hyaluronic acid (HA)-functionalized nanoplatform capable of achieving targeted delivery of camptothecin (CPT) and dual-stimuli-responsive drug release. HA was connected to MoS2 via a disulfide linkage, forming a sheddable HA shell on the surface of MoS2. This unique design not only effectively prevented the encapsulated CPT from randomly leaking during blood circulation but also significantly accelerated the drug release in response to tumor-associated glutathione (GSH). Moreover, the MoS2-based generated heat upon near-infrared (NIR) irradiation could further increase the drug release rate as well as induce photothermal ablation of cancer cells. The results of in vitro and in vivo experiments revealed that MoS2-SS-HA-CPT effectively suppressed cell proliferation and inhibited tumor growth in lung cancer cell-bearing mice under NIR irradiation via synergetic chemo-photothermal therapy. CONCLUSIONS: The as-prepared MoS2-SS-HA-CPT with high targeting ability, dual-stimuli-responsive drug release, and synergistic chemo-photothermal therapy may provide a new strategy for cancer therapy.

Functionalized MoS2-erlotinib produces hyperthermia under NIR.

BACKGROUND: Molybdenum disulfide (MoS2) has been widely explored for biomedical applications due to its brilliant photothermal conversion ability. In this paper, we report a novel multifunctional MoS2-based drug delivery system (MoS2-SS-HA). By decorating MoS2 nanosheets with hyaluronic acid (HA), these functionalized MoS2 nanosheets have been developed as a tumor-targeting chemotherapeutic nanocarrier for near-infrared (NIR) photothermal-triggered drug delivery, facilitating the combination of chemotherapy and photothermal therapy into one system for cancer therapy. RESULTS: The nanocomposites (MoS2-SS-HA) generated a uniform diameter (ca. 125 nm), exhibited great biocompatibility as well as high stability in physiological solutions, and could be loaded with the insoluble anti-cancer drug erlotinib (Er). The release of Er was greatly accelerated under near infrared laser (NIR) irradiation, showing that the composites can be used as responsive systems, with Er release controllable through NIR irradiation. MTT assays and confocal imaging results showed that the MoS2-based nanoplatform could selectively target and kill CD44-positive lung cancer cells, especially drug resistant cells (A549 and H1975). In vivo tumor ablation studies prove a better synergistic therapeutic effect of the joint treatment, compared with either chemotherapy or photothermal therapy alone. CONCLUSION: The functionalized MoS2 nanoplatform developed in this work could be a potent system for targeted drug delivery and synergistic chemo-photothermal cancer therapy.

Fabrication of an ionic-liquid-based polymer monolithic column and its application in the fractionation of proteins from complex biosamples.

An ionic-liquid-based polymer monolithic column was synthesized by free radical polymerization within the confines of a stainless-steel column (50 mm × 4.6 mm id). In the processes, ionic liquid and stearyl methacrylate were used as dual monomers, ethylene glycol dimethacrylate as the cross-linking agent, and polyethylene glycol 200 and isopropanol as co-porogens. Effects of the prepolymerization solution components on the properties of the resulting monoliths were studied in detail. Scanning electron microscopy, nitrogen adsorption-desorption measurements, and mercury intrusion porosimetry were used to investigate the morphology and pore size distribution of the prepared monoliths, which showed that the homemade ionic-liquid-based monolith column possessed a relatively uniform macropore structure with a total macropore specific surface area of 44.72 m2 /g. Compared to a non-ionic-liquid-based monolith prepared under the same conditions, the ionic-liquid-based monolith exhibited excellent selectivity and high performance for separating proteins from complex biosamples, such as egg white, snailase, bovine serum albumin digest solution, human plasma, etc., indicating promising applications in the fractionation and analysis of proteins from the complex biosamples in proteomics research.

[Effects of different concentrations of nitrogen,phosphorus and potash on Glycyrrhiza uralensis and its relationship with soil element content].

With annual Glycyrrhiza uralensis seedlings as experimental material, using "3414" optimal regression design and applied fertilizer, through the sampling of G. uralensis at harvest, root fresh weight and content of active components were measured in Lanzhou, Bayan Nur city, Chifeng, Jiuquan. Combined with NPK content in soil, potted experiments were used to study the effects of different nitrogen and phosphorus ratios on the dry matter accumulation and accumulation of active components of G. uralensis. The results reported as follows: the optimum fertilizer treatment in Lanzhou, Bayan Nur city, Chifeng, Jiuquan was N1P2K1,N2P2K1,N1P1K2 and N2P1K2, respectively. The efforts of single fertilizer on the fresh root weight acted as parabolic type.There was no significant effect of fertilizer treatment on the accumulation of active components of G. uralensis. Furthermore, in terms of nitrogen and phosphorus, the type of fertilizers that restricted the growth of the region was the type of elements with lower content in the soil. The optimal fertilizer usage was in inverse proportion to content of elements in soil. When the content of phosphorus in soil was low, nitrogen fertilizer and potash fertilizer showed positive interaction with phosphorus fertilizer, whereas, they showed negative interaction.

Separation of proteins from complex bio-matrix samples using a double-functionalized polymer monolithic column.

A double-functionalized polymer monolithic column was fabricated within the confines of a stainless-steel column (50 mm × 4.6 mm i.d.) via a facile method using iron porphyrin, ionic liquid (1-allyl-3-methylimidazolium chloride) and 1,10-decanediol dimethacrylate as tri-monomers; ethylene dimethacrylate as a crosslinker; polyethylene glycol 400 and N,N-dimethylformamide as co-porogens; benzoyl peroxide and N,N-dimethyl aniline as the redox initiation system. Results obtained from scanning electron microscopy, nitrogen adsorption-desorption, and mercury intrusion porosimetry confirmed the uniform pore structure and the pore size distribution of macro-pores. The home-made monolith was further characterized by elemental analysis to investigate the elemental composition of Fe supplied by iron porphyrin, confirming the synthetic process. The resulting optimized monolithic column was used as the stationary phase in high performance liquid chromatography for separating proteins, such as mixture of standard proteins, egg white, and human plasma, exhibiting good selectivity and high performance. It is worth noting that the home-made double-functionalized polymer monolithic column shows excellent selectivity for fractionation separation of human plasma proteins, and it is a promising separation tool for complex bio-samples in proteomic research.

[Effects of different concentrations of nitrogen and phosphorus on growth and active components of Salvia miltiorrhiza].

With annual Salvia miltiorrhiza seedlings as experimental material, using "3414" optimal regression design recommended by the Ministry of Agriculture and regularly watered with nutrient solution, through the dynamic sampling of S. miltiorrhiza in different growing stages, and the growth index, dry weight of plant root and content of active components were measured. The potted experiments were applied to study the effects of different nitrogen and phosphorus ratios on the growth, dry matter accumulation and accumulation of active components of S. miltiorrhiza, in order to explore a compatible fertilization method of nitrogen and phosphorus ratio that are suitable for production and quality of S. miltiorrhiza. The results reported as follows：①High concentrations of nitrogen fertilizer was beneficial to dry matter accumulation of S. miltiorrhiza aerial parts, and low concentration of nitrogen fertilizer transferred the dry matter accumulation to underground, and N1P1 could make the transfer ahead of time;②Regression analysis showed that in the early growth stage (before early July), we could use the nitrogen and phosphorus as basic fertilizer at a concentration of 1.521,0.355 g•L⁻¹ respectively to promote the growth of S. miltiorrhiza and at a concentration of 2.281,0.710 g•L⁻¹ respectively to promote the dry matter accumulation of root (after mid-August);③Five kinds of active components of S. miltiorrhiza decreased with the increase of nitrogen concentration, and increased with the increase of the concentration of phosphate fertilizer. Nitrogenous fertilizer, phosphate fertilizer in N-P=2∶3 ratio was more suitable for the accumulation of salvianolic acids, in N-P=1∶2 ratio was more suitable for the accumulation of tanshinone.

Amber rainbow ribbon effect in broadband optical metamaterials.

Using the trapped rainbow effect to slow down or even stop light has been widely studied. However, high loss and energy leakage severely limited the development of rainbow devices. Here, we observed the negative Goos-Hänchen effect in film samples across the entire visible spectrum. We also discovered an amber rainbow ribbon and an optical black hole due to perfect back reflection in optical waveguides, where little light leaks out. Not only does the amber rainbow ribbon effect show an automatic frequency selection response, as predicted by single frequency theoretical models and confirmed by experiments, it also shows spatial periodic regulation, resulting from broadband omnidirectional visible metamaterials prepared by disordered assembly systems. This broadband light trapping system could play a crucial role in the fields of optical storage and information processing when being used to construct ultra-compact modulators and other tunable devices.

Intercropping with maize and sorghum-induced saikosaponin accumulation in Bupleurum chinense DC. by liquid chromatography-mass spectrometry-based metabolomics.

Bupleuri Radix is an important medicinal plant, which has been used in China and other Asian countries for thousands of years. Cultivated Bupleurum chinense DC. (B. chinense) is the main commodity of Bupleuri Radix. The benefits of intercropping with various crops for B. chinense have been recognized; however, the influence of intercropping on the chemical composition of B. chinense is still unclear yet. In this study, intercropping with sorghum and maize exhibited little effect on the root length, root diameter, and single root mass of B. chinense. Only the intercropping with sorghum increased the root length of B. chinense slightly compared to the monocropping. In addition, 200 compounds were identified by UHPLC-Q-TOF-MS, and metabolomic combined with the Venn diagram and heatmap analysis showed apparent separation between the intercropped and monocropped B. chinense samples. Intercropping with sorghum and maize could both increase the saikosaponins, fatty acyls, and organic acids in B. chinense while decreasing the phospholipids. The influence of intercropping on the saikosaponin biosynthesis was probably related with the light intensity and hormone levels in B. chinense. Moreover, we found intercropping increased the anti-inflammatory activity of B. chinense. This study provides a scientific reference for the beneficial effect of intercropping mode of B. chinense.

Structural Brain Connectivity Guided Optimal Contact Selection for Deep Brain Stimulation of the Subthalamic Nucleus.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective therapy in ameliorating the motor symptoms of Parkinson disease. However, postoperative optimal contact selection is crucial for achieving the best outcome of deep brain stimulation of the subthalamic nucleus surgery, but the process is currently a trial-and-error and time-consuming procedure that relies heavily on surgeons' clinical experience. METHODS: In this study, we propose a structural brain connectivity guided optimal contact selection method for deep brain stimulation of the subthalamic nucleus. Firstly, we reconstruct the DBS electrode location and estimate the stimulation range using volume of tissue activated from each DBS contact. Then, we extract the structural connectivity features by concatenating fractional anisotropy and the number of streamlines features of activated regions and the whole brain regions. Finally, we use a convolutional neural network with convolutional block attention module to identify the structural connectivity features for the optimal contact selection. RESULTS: We review the data of 800 contacts from 100 patients with Parkinson disease for the experiment. The proposed method achieves promising results, with the average accuracy of 97.63%, average precision of 94.50%, average recall of 94.46%, and average specificity of 98.18%, respectively. Our method can provide the suggestion for optimal contact selection. CONCLUSIONS: Our proposed method can improve the efficiency and accuracy of DBS optimal contact selection, reduce the dependence on surgeons' experience, and has the potential to facilitate the development of advanced DBS technology.

Multimodal MRI segmentation of key structures for microvascular decompression via knowledge-driven mutual distillation and topological constraints.

PURPOSE: Microvascular decompression (MVD) is a widely used neurosurgical intervention for the treatment of cranial nerves compression. Segmentation of MVD-related structures, including the brainstem, nerves, arteries, and veins, is critical for preoperative planning and intraoperative decision-making. Automatically segmenting structures related to MVD is still challenging for current methods due to the limited information from a single modality and the complex topology of vessels and nerves. METHODS: Considering that it is hard to distinguish MVD-related structures, especially for nerve and vessels with similar topology, we design a multimodal segmentation network with a shared encoder-dual decoder structure and propose a clinical knowledge-driven distillation scheme, allowing reliable knowledge transferred from each decoder to the other. Besides, we introduce a class-wise contrastive module to learn the discriminative representations by maximizing the distance among classes across modalities. Then, a projected topological loss based on persistent homology is proposed to constrain topological continuity. RESULTS: We evaluate the performance of our method on in-house dataset consisting of 100 paired HR-T2WI and 3D TOF-MRA volumes. Experiments indicate that our model outperforms the SOTA in DSC by 1.9% for artery, 3.3% for vein and 0.5% for nerve. Visualization results show our method attains improved continuity and less breakage, which is also consistent with intraoperative images. CONCLUSION: Our method can comprehensively extract the distinct features from multimodal data to segment the MVD-related key structures and preserve the topological continuity, allowing surgeons precisely perceiving the patient-specific target anatomy and substantially reducing the workload of surgeons in the preoperative planning stage. Our resources will be publicly available at https://github.com/JaronTu/Multimodal_MVD_Seg .