Comparative evaluation of reproductive organ-preserving versus standard radical cystectomy in female: a meta-analysis and systematic review of perioperative, oncological, and functional outcomes.

BACKGROUND: To evaluate the perioperative, oncological, and functional outcomes of reproductive organ-preserving radical cystectomy (ROPRC) compared to standard radical cystectomy (SRC) in the treatment of female bladder cancer. METHODS: A systematic search was conducted in November 2023 across several scientific databases. We executed a systematic review and cumulative meta-analysis of the primary outcomes of interest, adhering to the PRISMA and AMSTAR guidelines. The study was registered in PROSPERO (CRD42024501522). RESULTS: The meta-analysis included 10 studies with a total of 2015 participants. ROPRC showed a significant reduction in operative time and postoperative fasting period compared to SRC (MD - 45.69, 95% CI - 78.91 ~ - 12.47, p = 0.007, and MD - 0.69, 95% CI - 1.25 ~ - 0.13, p = 0.02, respectively). Functional outcomes, both daytime continence rate (OR 4.94, 95% CI 1.53 ~ 15.91, p = 0.008) and nighttime continence rate (OR 5.91, 95% CI 1.94 ~ 18.01, p = 0.002), and sexual function measured by the Female Sexual Function Index (MD 5.72, 95% CI 0.19 ~ 11.26, p = 0.04), were significantly improved in the ROPRC group. There were no significant differences between ROPRC and SRC in terms of estimated blood loss, length of hospital stay, overall postoperative complications, minor complications or major complications. Oncologically, both procedures showed comparable outcomes with no significant differences in positive surgical margins, tumor recurrence rates, overall survival, cancer-specific survival, recurrence-free survival, or progression-free survival. CONCLUSIONS: ROPRC is a viable and effective alternative to SRC in female bladder cancer patients, offering enhanced functional outcomes and similar oncological safety. These findings suggest that ROPRC can improve the quality of life in female bladder cancer patients without compromising the efficacy of cancer treatment.

Neddylation of EphB1 Regulates Its Activity and Associates with Liver Fibrosis.

Liver fibrosis is a pathological process characterized by the excessive synthesis and accumulation of extracellular matrix proteins (ECMs) contributed mainly by the activated hepatic stellate cells (HSCs). Currently, no direct and effective anti-fibrotic agents have been approved for clinical use worldwide. Although the dysregulation of Eph receptor tyrosine kinase EphB2 has been reported to associate with the development of liver fibrosis, the involvement of other Eph family members in liver fibrosis remains underexplored. In this study, we found that the expression of EphB1 is significantly increased accompanying remarkable neddylation in activated HSCs. Mechanistically, this neddylation enhanced the kinase activity of EphB1 by the prevention of its degradation, thereby promoting the proliferation, migration, and activation of HSCs. Our findings revealed the involvement of EphB1 in the development of liver fibrosis through its neddylation, which provides new insights into the Eph receptor signaling and a potential target for the treatment of liver fibrosis.

Hollow Cobalt Oxide/Carbon Hybrids Aid Metabolic Encoding for Active Systemic Lupus Erythematosus during Pregnancy.

A noninvasive, easy operation, and accurate diagnostic protocol is highly demanded to assess systemic lupus erythematosus (SLE) activity during pregnancy, promising real-time activity monitoring during the whole gestational period to reduce adverse pregnancy outcomes. Here, machine learning of serum metabolic fingerprints (SMFs) is developed to assess the SLE activity for pregnant women. The SMFs are directly extracted through a hollow-cobalt oxide/carbon (Co3 O4 /C)-composite-assisted laser desorption/ionization mass spectrometer (LDI MS) platform. The Co3 O4 /C composite owns enhanced light absorption, size-selective trapping, and better charge-hole separation, enabling improved ionization efficiency and selectivity for LDI MS detection toward small molecules. Metabolic fingerprints are collected from ≈0.1 µL serum within 1 s without enrichment and encoded by the optimized elastic net algorithm. The averaged area under the curve (AUC) value in the differentiation of active SLE from inactive SLE and healthy controls reaches 0.985 and 0.990, respectively. Further, a simplified panel based on four identified metabolites is built to distinguish SLE flares in pregnant women with the highest AUC value of 0.875 for the blind test. This work sets an accurate and practical protocol for SLE activity assessment during pregnancy, promoting precision diagnosis of disease status transitions in clinics.

Design of Multi-Shelled Hollow Cr2 O3 Spheres for Metabolic Fingerprinting.

Schizophrenia (SZ) detection enables effective treatment to improve the clinical outcome, but objective and reliable SZ diagnostics are still limited. An ideal diagnosis of SZ suited for robust clinical screening must address detection throughput, low invasiveness, and diagnosis accuracy. Herein, we built a multi-shelled hollow Cr2 O3 spheres (MHCSs) assisted laser desorption/ionization mass spectrometry (LDI MS) platform for the direct metabolic profiling of biofluids towards SZ diagnostics. The MHCSs displayed strong light absorption for enhanced ionization and microscale surface roughness with stability for the effective LDI of metabolites. We profiled urine and serum metabolites (≈1 µL) with the enhanced LDI efficacy in seconds. We discriminated SZ patients (SZs) from healthy controls (HCs) with the highest area under the curve (AUC) value of 1.000 for the blind test. We identified four compounds with optimal diagnostic power as a simplified metabolite panel for SZ and demonstrated the metabolite quantification for clinic use. Our approach accelerates the growth of new platforms toward a precision diagnosis in the near future.

Intravesical gemcitabine versus mitomycin for non-muscle invasive bladder cancer: a systematic review and meta-analysis of randomized controlled trial.

BACKGROUND: Mitomycin (MMC) has been frequently used as the compound for intravesical treatment. The relatively new pyrimidine analog gemcitabine (GEM) has exhibited anticancer effect on various solid cancers, such as the advanced bladder cancer. In this study, the GEM and MMC in treating non-muscle invasive bladder cancer (NMIBC) cases was compared through systemic review. METHODS: In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, the electronic databases, including Embase, PubMed, Chinese biomedicine literature database, the Cochrane Library, the National Institute for Health and Clinical Excellence, NHS Evidence, Chinese technological periodical full-text database, and Chinese periodical full-text database, were systemically reviewed from inception to October 2018. Then, the RevMan 5.0 software was applied for data analysis. Five randomized controlled trials (RCTs) involving a total of 335 patients were included. RESULTS: For MMC group, the recurrence rate in the mitomycin arm increased compared with that in GEM group (OR = 0.44 95% CI [0.24, 0.78]), and the difference was statistically significant between the two groups. GEM was associated with reduced incidence of chemical cystitis compared with that of MMC (OR = 0.23 95% CI [0.12, 0.44]). Differences in hematuria (OR = 0.46 95% CI [0.16, 1.31]), skin reaction (OR = 0.49 95% CI [0.14, 1.70]) and liver and kidney function damage (OR = 0.51 95% CI [0.09, 2.85]) displayed no statistical significance between the two groups. CONCLUSION: Findings in our study demonstrate the superior efficacy of GEM over MMC in reducing the relapse rate among NMIBC patients following transurethral resection (TUR). In addition, GEM is associated with reduced local toxic effects on the bladder compared with those of MMC. However, more future studies are needed to examine GEM safety when used as the monotherapy or polytherapy for bladder patients. More RCTs with high quality are also required to validate our findings due to the limitations of the current meta-analysis.

FeOOH@Metal-Organic Framework Core-Satellite Nanocomposites for the Serum Metabolic Fingerprinting of Gynecological Cancers.

High-throughput metabolic analysis is of significance in diagnostics, while tedious sample pretreatment has largely hindered its clinic application. Herein, we designed FeOOH@ZIF-8 composites with enhanced ionization efficiency and size-exclusion effect for laser desorption/ionization mass spectrometry (LDI-MS)-based metabolic diagnosis of gynecological cancers. The FeOOH@ZIF-8-assisted LDI-MS achieved rapid, sensitive, and selective metabolic fingerprints of the native serum without any enrichment or purification. Further analysis of extracted serum metabolic fingerprints successfully discriminated patients with gynecological cancers (GCs) from healthy controls and also differentiated three major subtypes of GCs. Given the low cost, high-throughput, and easy operation, our approach brings a new dimension to disease analysis and classification.

A robust method for high-precision quantification of the complex three-dimensional vasculatures acquired by X-ray microtomography.

The quantification of micro-vasculatures is important for the analysis of angiogenesis on which the detection of tumor growth or hepatic fibrosis depends. Synchrotron-based X-ray computed micro-tomography (SR-µCT) allows rapid acquisition of micro-vasculature images at micrometer-scale spatial resolution. Through skeletonization, the statistical features of the micro-vasculature can be extracted from the skeleton of the micro-vasculatures. Thinning is a widely used algorithm to produce the vascular skeleton in medical research. Existing three-dimensional thinning methods normally emphasize the preservation of topological structure rather than geometrical features in generating the skeleton of a volumetric object. This results in three problems and limits the accuracy of the quantitative results related to the geometrical structure of the vasculature. The problems include the excessively shortened length of elongated objects, eliminated branches of blood vessel tree structure, and numerous noisy spurious branches. The inaccuracy of the skeleton directly introduces errors in the quantitative analysis, especially on the parameters concerning the vascular length and the counts of vessel segments and branching points. In this paper, a robust method using a consolidated end-point constraint for thinning, which generates geometry-preserving skeletons in addition to maintaining the topology of the vasculature, is presented. The improved skeleton can be used to produce more accurate quantitative results. Experimental results from high-resolution SR-µCT images show that the end-point constraint produced by the proposed method can significantly improve the accuracy of the skeleton obtained using the existing ITK three-dimensional thinning filter. The produced skeleton has laid the groundwork for accurate quantification of the angiogenesis. This is critical for the early detection of tumors and assessing anti-angiogenesis treatments.

Towards automated quantitative vasculature understanding via ultra high-resolution imagery.

This chapter presents an approach to processing ultra high-resolution, large-size biomedical imaging data for the purposes of detecting and quantifying vasculature and microvasculature . Capturing early signs of any changes in vasculature may have significant values for early-diagnosis and treatment assessment due to the well understood observation that vascular changes precede cancerous growth and metastasis metastasis . With the advent of key enabling technologies for extremely high-resolution imaging, such as synchrotron radiation synchrotron radiation based computed tomography (CT) computed tomography , the required levels of detail have become accessible. However, these technologies also present challenges in data analysis. This chapter aims to offer some insights as to how these changes might be best dealt with. We argue that the necessary steps in quantitative understanding of vasculatures include targeted data enhancement enhancement , information reduction aimed at characterizing the linear structure of vessels vessels , and quantitatively describing the vessel hierarchy. We present results on cerebral and liver vasculatures of a mouse captured at the Shanghai Synchrotron Radiation Facility (SSRF). These results were achieved with a processing pipeline comprising of our empirically selected component for each of the above steps. Towards the end, we discuss how alternative and additional components may be incorporated for improved speed and robustness.

Designed Nanomaterials-Assisted Proteomics and Metabolomics Analysis for In Vitro Diagnosis.

In vitro diagnosis (IVD) is pivotal in modern medicine, enabling early disease detection and treatment optimization. Omics technologies, particularly proteomics and metabolomics, offer profound insights into IVD. Despite its significance, omics analyses for IVD face challenges, including low analyte concentrations and the complexity of biological environments. In addition, the direct omics analysis by mass spectrometry (MS) is often hampered by issues like large sample volume requirements and poor ionization efficiency. Through manipulating their size, surface charge, and functionalization, as well as the nanoparticle-fluid incubation conditions, nanomaterials have emerged as a promising solution to extract biomolecules and enhance the desorption/ionization efficiency in MS detection. This review delves into the last five years of nanomaterial applications in omics, focusing on their role in the enrichment, separation, and ionization analysis of proteins and metabolites for IVD. It aims to provide a comprehensive update on nanomaterial design and application in omics, highlighting their potential to revolutionize IVD.

Device-assisted intravesical chemotherapy versus bacillus Calmette-Guerin for intermediate or high-risk non-muscle invasive bladder cancer: a systematic reviewer and meta-analysis.

PURPOSE: To investigate the effectiveness and safety of device-assisted intravesical chemotherapy compared to Bacillus Calmette-Guerin (BCG) in the treatment of patients with intermediate- and high-risk non-muscle-invasive bladder cancer (NMIBC). METHODS: In February 2023, a systematic search was conducted on the PubMed, Cochrane, and Embase databases. Following the PRISMA guidelines, a systematic review and meta-analysis of the primary outcomes of interest were performed. The review was prospectively registered on PROSPERO under the registration number CRD42023398559. RESULTS: A total of 10 studies involving 1160 patients were included. The results of the meta-analysis showed that compared to BCG, device-assisted chemotherapy had a lower recurrence rate (OR: 0.63, 95% CI: 0.48-0.84, p = 0.001), longer recurrence-free survival (OR: 0.64, 95% CI: 0.47-0.88, p = 0.006), and lower incidence of fever (OR: 0.18, 95% CI: 0.08-0.44, p = 0.0002). However, no significant differences were observed between the two groups in terms of progression, overall survival, progression-free survival, disease-free survival, overall adverse events, serious adverse events, hematuria, allergy, and general discomfort. Subgroup analysis revealed that neither chemohyperthermia (CHT) nor electromotive drug administration (EMDA) showed statistically significant differences in oncological outcomes compared to BCG. Regarding adverse events, both CHT and EMDA groups showed lower rates of fever compared to the BCG group (OR: 0.26, 95% CI: 0.10-0.67, p = 0.005, and OR: 0.14, 95% CI: 0.05-0.37, p < 0.0001, respectively). No significant differences were observed in the remaining adverse events between either the CHT or EMDA group and the BCG group. CONCLUSION: Device-assisted intravesical chemotherapy appears to be a safe and viable alternative to BCG for patients with intermediate and high-risk NMIBC, showing comparable oncological outcomes and adverse events.

The combination of tetracyclines effectively ameliorates liver fibrosis via inhibition of EphB1/2.

Eph receptor tyrosine kinase EphB1/2 contributes to the development of liver fibrosis, suggesting the rationale that EphB1/2 inhibitors may be effective in liver fibrosis therapy. Since tetracycline antibiotics were recently demonstrated as EphB kinase inhibitors, in present study we investigated their therapeutic potential against liver fibrosis. Our results showed that the tetracycline combination of demeclocycline (D), chlortetracycline (C), and minocycline (M) inhibited the activation of hepatic stellate cells (HSCs) in vitro and alleviated CCl4-induced animal model of liver fibrosis in vivo. Mechanistically, DCM combination inhibited EphB1/2 phosphorylation and subsequent activation of the MAPK signaling. Moreover, we found that short-term and low-dose DCM combination treatment decreased tissue inflammation and improved liver fibrosis in mice. Thus, our study indicates that tetracyclines may be repurposed for the treatment of liver fibrosis.

Sertraline Alleviates Chronic Prostatitis by Regulating the TRPV1 Channel.

Introduction: Although sertraline has been widely used for chronic prostatitis (CP), the mechanisms are unclear. Herein, we explored the mechanisms of sertraline in treating CP. Methods: Network pharmacology methods were used to explore the potential targets and molecular mechanisms. LPS was used to stimulate RWPE-1 cells to construct an in vitro model of CP. An experimental autoimmune prostatitis (EAP) mice model was built. CCK-8 assay, EdU assay, BrdU detection, and Tunel assay were performed to evaluate the proliferation and apoptosis process of cells or tissues, respectively. DCFH-DA and Fluo-4 fluorescence probes were used to detect intracellular ROS and calcium concentrations. Von Frey filaments and open-field tests were utilized to evaluate pain response and depressive-like behavior of mice. Histopathology was evaluated through hematoxylin and eosin staining. RT-qPCR, Western blot, immunofluorescence, and immunohistochemistry were utilized to evaluate the transcription, expression, and location of related proteins. Molecular dynamics (MD) simulation and surface plasmon resonance (SPR) assay were performed to measure the binding capacity of sertraline and related proteins. Results: Through a network pharmacology analysis, 27 potential targets of sertraline for CP were obtained, and 5 key targets (CHRM1, ADRA1B, HTR2B, HTR2A, and TRPV1) were finally identified. Functional experiments suggested that TRPV1 was involved in the proliferation, apoptosis inhibition, and ROS production of LPS-induced RWPE-1 cells. In vitro experiments showed that sertraline significantly inhibited cell proliferation, ROS generation, and transcription of inflammation cytokines of LPS-induced RWPE-1 cells. Additionally, sertraline markedly promoted the apoptosis level of LPS-stimulated RWPE-1 cells and elevated the expression level of BAX while reducing the expression levels of Bcl2 and Caspase-3. MD simulation and SPR assay confirmed the direct binding of sertraline to TRPV1. Moreover, sertraline significantly down-regulated the expression level of TRPV1 and inhibited calcium influx of LPS-induced RWPE-1 cells. TRPV1 agonist (Capsaicin) significantly restored the effects on proliferation, apoptosis, ROS production, and calcium influx of sertraline on LPS-induced RWPE-1 cells. Mice experiments demonstrated that sertraline treatment could reduce pain response, improve depression-like symptoms, and relieve local prostate inflammation of EAP mice, as well as down-regulated the expression level of TRPV1, inhibit the proliferation, and promote apoptosis of prostate tissues in EAP mice. Discussion: The results revealed the anti-inflammatory effect of sertraline for RWPE-1 cells and EAP mice, and the potential mechanism was regulating the TRPV1 channel. It indicated that sertraline might serve as a complementary anti-inflammatory agent for CP.

Vacancy-Driven High-Performance Metabolic Assay for Diagnosis and Therapeutic Evaluation of Depression.

Depression is one of the most common mental illnesses and is a well-known risk factor for suicide, characterized by low overall efficacy (<50%) and high relapse rate (40%). A rapid and objective approach for screening and prognosis of depression is highly desirable but still awaits further development. Herein, a high-performance metabolite-based assay to aid the diagnosis and therapeutic evaluation of depression by developing a vacancy-engineered cobalt oxide (Vo-Co3O4) assisted laser desorption/ionization mass spectrometer platform is presented. The easy-prepared nanoparticles with optimal vacancy achieve a considerable signal enhancement, characterized by favorable charge transfer and increased photothermal conversion. The optimized Vo-Co3O4 allows for a direct and robust record of plasma metabolic fingerprints (PMFs). Through machine learning of PMFs, high-performance depression diagnosis is achieved, with the areas under the curve (AUC) of 0.941-0.980 and an accuracy of over 92%. Furthermore, a simplified diagnostic panel for depression is established, with a desirable AUC value of 0.933. Finally, proline levels are quantified in a follow-up cohort of depressive patients, highlighting the potential of metabolite quantification in the therapeutic evaluation of depression. This work promotes the progression of advanced matrixes and brings insights into the management of depression.

Network pharmacological analysis and experimental study of melatonin in chronic prostatitis/chronic pelvic pain syndrome.

This study is aimed at exploring the potential mechanisms of melatonin (MT) in treating chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) using network pharmacology and experimental study. The target genes of MT were acquired from the Swiss Target Prediction, SuperPred, SEA, and PharmMapper databases, and the CP/CPPS targets were collected based on OMIM, DisGeNET, and GeneCards databases. The intersection of MT and CP/CPPS target genes was analyzed. A PPI network was constructed using Cytoscape to identify core targets. The shared targets underwent GO and KEGG enrichment analyses by Using R software. Molecular docking of MT with core targets was performed using AutoDock and PyMOL. GROMACS software was used for molecular dynamics simulation. And using cell experiments to verify the potential effect of MT in CP/CPPS. Network pharmacology analysis reveals 284 shared targets between MT and CP/CPPS, with AKT1, SRC, HSP90AA1, PTGS2, BCL2L1, ALB, CASP3, NFKB1, HIF1A, and ESR1 identified as key targets. Enrichment analysis indicates that MT affects CP/CPPS through various biological processes, and pathway analysis emphasizes the significance of PI3K-Akt, MAPK, Ras, FoxO, HIF-1, EGFR, and apoptosis pathways. Molecular docking confirms strong binding between MT and core targets. It is worth noting that the molecular dynamics simulation showed that the average binding free energy of AKT1, PTGS2, ALB, HSP90AA1 proteins, and MT was - 26.15, - 29.48, - 18.59, and - 20.09 kcal/mol, respectively. These results indicated that AKT1, PTGS2, ALB, and HSP90AA1 proteins were strongly bound to MT. Cell experiments demonstrate that MT can inhibit the secretion of IL-1ß, IL-6, and TNF-α in LPS-induced RWPE-1 cells, alleviate inflammation, and suppress cell apoptosis and oxidative stress. Network pharmacology, molecular docking, molecular dynamics simulation, and cell experiments showed that MT could play a role in CP/CPPS by regulating multiple targets and pathways. These findings provide an important scientific basis for further exploration of the molecular mechanism and clinical application of MT in CP/CPPS treatment and are expected to provide new ideas and directions for the development of novel therapeutic strategies.

Probing the Interaction Between Supercarrier RBC Membrane and Nanoparticles for Optimal Drug Delivery.

Red blood cell (RBC) membrane-hitchhiking nanoparticles (NPs) have been an increasingly popular supercarrier for targeted drug delivery. However, the kinetic details of the shear-induced NP detachment process from RBC in blood flow remain unclear. Here, we perform detailed computational simulations of the traversal dynamics of an RBC-NP composite supercarrier with tunable properties. We show that the detachment of NPs from RBC occurs in a shear-dependent manner which is consistent with previous experiment results. We quantify the NP detachment rate in the microcapillary flow, and our simulation results suggest that there may be an optimal adhesion strength span of 25-40 µJ/m2 for rigid spherical NPs to improve the supercarrier performance and targeting efficiency. In addition, we find that the stiffness and the shape of NPs alter the detachment efficiency by changing the RBC-NP contact areas. Together, these findings provide unique insights into the shear-dependent NP release from the RBC surface, facilitating the clinical utility of RBC-NP composite supercarriers in targeted and localized drug delivery with high precision and efficiency.

Construction of a ternary component chip with enhanced desorption efficiency for laser desorption/ionization mass spectrometry based metabolic fingerprinting.

Introduction: In vitro metabolic fingerprinting encodes diverse diseases for clinical practice, while tedious sample pretreatment in bio-samples has largely hindered its universal application. Designed materials are highly demanded to construct diagnostic tools for high-throughput metabolic information extraction. Results: Herein, a ternary component chip composed of mesoporous silica substrate, plasmonic matrix, and perfluoroalkyl initiator is constructed for direct metabolic fingerprinting of biofluids by laser desorption/ionization mass spectrometry. Method: The performance of the designed chip is optimized in terms of silica pore size, gold sputtering time, and initiator loading parameter. The optimized chip can be coupled with microarrays to realize fast, high-throughput (∼second/sample), and microscaled (∼1 µL) sample analysis in human urine without any enrichment or purification. On-chip urine fingerprints further allow for differentiation between kidney stone patients and healthy controls. Discussion: Given the fast, high throughput, and easy operation, our approach brings a new dimension to designing nano-material-based chips for high-performance metabolic analysis and large-scale diagnostic use.

Designed Concave Octahedron Heterostructures Decode Distinct Metabolic Patterns of Epithelial Ovarian Tumors.

Epithelial ovarian cancer (EOC) is a polyfactorial process associated with alterations in metabolic pathways. A high-performance screening tool for EOC is in high demand to improve prognostic outcome but is still missing. Here, a concave octahedron Mn2 O3 /(Co,Mn)(Co,Mn)2 O4 (MO/CMO) composite with a heterojunction, rough surface, hollow interior, and sharp corners is developed to record metabolic patterns of ovarian tumors by laser desorption/ionization mass spectrometry (LDI-MS). The MO/CMO composites with multiple physical effects induce enhanced light absorption, preferred charge transfer, increased photothermal conversion, and selective trapping of small molecules. The MO/CMO shows ≈2-5-fold signal enhancement compared to mono- or dual-enhancement counterparts, and ≈10-48-fold compared to the commercialized products. Subsequently, serum metabolic fingerprints of ovarian tumors are revealed by MO/CMO-assisted LDI-MS, achieving high reproducibility of direct serum detection without treatment. Furthermore, machine learning of the metabolic fingerprints distinguishes malignant ovarian tumors from benign controls with the area under the curve value of 0.987. Finally, seven metabolites associated with the progression of ovarian tumors are screened as potential biomarkers. The approach guides the future depiction of the state-of-the-art matrix for intensive MS detection and accelerates the growth of nanomaterials-based platforms toward precision diagnosis scenarios.

Hollow multishelled heterostructures with enhanced performance for laser desorption/ionization mass spectrometry based metabolic diagnosis.

High-performance metabolic diagnosis-based laser desorption/ionization mass spectrometry (LDI-MS) improves the precision diagnosis of diseases and subsequent treatment. Inorganic matrices are promising for the detection of metabolites by LDI-MS, while the structure and component impacts of the matrices on the LDI process are still under investigation. Here, we designed a multiple-shelled ZnMn2O4/(Co, Mn)(Co, Mn)2O4 (ZMO/CMO) as the matrix from calcined MOF-on-MOF for detecting metabolites in LDI-MS and clarified the synergistic impacts of multiple-shells and the heterostructure on LDI efficiency. The ZMO/CMO heterostructure allowed 3-5 fold signal enhancement compared with ZMO and CMO with the same morphology. Furthermore, the ZMO/CMO heterostructure with a triple-shelled hollow structure displayed a 3-fold signal enhancement compared to its nanoparticle counterpart. Taken together, the triple-shelled hollow ZMO/CMO exhibits 102-fold signal enhancement compared to the commercial matrix products (e.g., DHB and DHAP), allowing for sensitive metabolic profiling in bio-detection. We directly extracted metabolic patterns by the optimized triple-shelled hollow ZMO/CMO particle-assisted LDI-MS within 1 s using 100 nL of serum and used machine learning as the readout to distinguish hepatocellular carcinoma from healthy controls with the area under the curve value of 0.984. Our approach guides us in matrix design for LDI-MS metabolic analysis and drives the development of a nanomaterial-based LDI-MS platform toward precision diagnosis.

Enhanced spin-orbit torque and field-free switching in Au/TMDs/Ni hybrid structures.

Spin-orbit torque (SOT) plays a significant role in spintronic logic and memory devices. However, due to the limited spin Hall angle and SOT symmetry in a heavy-metal-ferromagnet bilayer, further improving SOT efficiency and all-electric magnetization manipulation remain a challenge. Here we report enhanced SOT efficiency and all-electric switching in Au based magnetic structures, by inserting two-dimensional transition metal dichalcogenides (2D TMDs) with large spin-orbit coupling. With the TMD spacer insert, both damping-like and field-like SOTs are improved, and an unconventional out-of-plane damping-like SOT is induced, due to the interface orbital hybridization, modified spin-mixing conductance and orbital current. Moreover, current induced field-free magnetization switching is demonstrated in Au/WTe2/Ni and Au/MoS2/Ni devices, and it shows multiple intermediate states and can be efficiently controlled by an electric current. Our results open a path for increasing torques and expand the application of 2D TMDs in spintronic devices for neuromorphic computing.