Sphingolipid profiling reveals differential functions of sphingolipid biosynthesis isozymes of Caenorhabditis elegans.

Multiple isozymes are encoded in the Caenorhabditis elegans genome for the various sphingolipid biosynthesis reactions, but the contributions of individual isozymes are characterized only in part. We developed a simple but effective reversed-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS) method that enables simultaneous identification and quantification of ceramides (Cer), glucosylceramides (GlcCer), and sphingomyelins (SM) from the same MS run. Validating this sphingolipid profiling method, we show that nearly all 47 quantifiable sphingolipid species found in young adult worms were reduced upon RNA interference (RNAi) of sptl-1 or elo-5, which are both required for synthesis of the id17:1 sphingoid base. We also confirm that HYL-1 and HYL-2, but not LAGR-1, constitute the major ceramide synthase activity with different preference for fatty acid substrates, and that CGT-3, but not CGT-1 and CGT-2, plays a major role in producing GlcCers. Deletion of sms-5 hardly affected SM levels. RNAi of sms-1, sms-2, and sms-3 all lowered the abundance of certain SMs with an odd-numbered N-acyl chains (mostly C21 and C23, with or without hydroxylation). Unexpectedly, sms-2 RNAi and sms-3 RNAi elevated a subset of SM species containing even-numbered N-acyls. This suggests that sphingolipids containing even-numbered N-acyls could be regulated separately, sometimes in opposite directions, from those containing odd-numbered N-acyls, which are presumably monomethyl branched chain fatty acyls. We also find that ceramide levels are kept in balance with those of GlcCers and SMs. These findings underscore the effectiveness of this RPLC-MS/MS method in studies of C. elegans sphingolipid biology.

Selective Enrichment via TiO2 Magnetic Nanoparticles Enables Deep Profiling of Circulating Neutral Glycosphingolipids.

Circulating neutral glycosphingolipids (neutral GSLs (nGSLs)) are a unique subset of nGSLs that detach from organs or cell membranes and enter the bloodstream. Altered molecular distribution of circulating nGSL is increasingly associated with diseases. However, profiling of circulating nGSLs presents a lasting challenge due to their low abundances and structural complexity. Although TiO2 magnetic nanoparticles (TiO2 MNPs) were effective for the enrichment of nGSLs in brain tissue, the protocol showed limited selectivity for circulating nGSLs because their abundances were 100-times lower in human plasma than in brain tissue. In this work, we optimized the key parameters of selective enrichment by TiO2 MNPs and achieved 1:10,000 selectivity for nGSLs over interfering phospholipids, while maintaining ∼70% recovery for different subclasses of nGSLs. By integrating TiO2 MNP-based selective enrichment with reversed-phase liquid chromatography mass spectrometry and charge-tagging Paternò-Büchi derivatization, we achieved deep profiling of over 300 structures of nGSLs and sulfatides across 5 orders of magnitude in relative abundances, a significant leap regarding lipid coverage. We also depicted the structural atlas of nGSLs with defined headgroup, long-chain base, N-acyl chain, the location of desaturation, and 2-hydroxylation. Such information provides a valuable resource for lipidomic studies concerning the roles of circulating nGSLs in health and diseases.

Ultrathin carbon film as ultrafast rechargeable cathode for hybrid sodium dual-ion capacitor.

The development of electrochemical energy storage devices has a decisive impact on clean renewable energy. Herein, novel ultrafast rechargeable hybrid sodium dual-ion capacitors (HSDICs) were designed by using ultrathin carbon film (UCF) as the cathode material. The UCF is synthesized by a simple low temperature catalytic route followed by an acid leaching process. UCF owns a large adsorption interface and number of additional active sites, which is due to the nitrogen doping. In addition, there exists several short-range order carbons on the surface of UCF, which are beneficial for anionic storage. An ultrafast rechargeable remarkable performance, remarkable anion hybrid storage capability and outstanding structure stability is fully tapped employing UCF as cathode for HSDICs. The electrochemical performance of UCF in a half-cell system at the operating voltage between 1.0 and 4.8 V, achieving an admirable specific discharge capacity of 358.52 mAh·g-1at 500 mA·g-1, and a high capacity retention ratio of 98.42% after cycling 2500 times at 1000 mA·g-1, respectively. Besides, with the support ofex-situTEM and EDS mapping, the structural stability principle and anionic hybrid storage mechanism of UCF electrode are investigated in depth. In the full-cell system, HSDICs with the UCF as cathode and hard carbon as anode also presents a super-long cycle stability (80.62% capacity retention ratio after cycling 1300 times at 1000 mA·g-1).

[Multi-Voiced Narrative of Home-Based Palliative Care:Report of One Case].

Terminally ill patients face multiple difficulties in home care.Home-based palliative care adhering to the concept of whole-person,whole-family,whole-team,and whole-course care is able to meet the needs of terminally ill patients and their families.In this paper,we reported the care history and home-based palliative care process of a patient with end-stage breast tumor and summarized the experience,aiming to provide reference for the future work of home-based palliative care.

Surface-anchored microbial enzyme-responsive solid lipid nanoparticles enabling colonic budesonide release for ulcerative colitis treatment.

Colon-targeted oral drug delivery systems (CDDSs) are desirable for the treatment of ulcerative colitis (UC), which is a disease with high relapse and remission rates associated with immune system inflammation and dysregulation localized within the lining of the large bowel. However, the success of current available approaches used for colon-targeted therapy is limited. Budesonide (BUD) is a corticosteroid drug, and its rectal and oral formulations are used to treat UC, but the inconvenience of rectal administration and the systemic toxicity of oral administration restrict its long-term use. In this study, we designed and prepared colon-targeted solid lipid nanoparticles (SLNs) encapsulating BUD to treat UC by oral administration. A negatively charged surfactant (NaCS-C12) was synthesized to anchor cellulase-responsive layers consisting of polyelectrolyte complexes (PECs) formed by negatively charged NaCS and cationic chitosan onto the SLNs. The release rate and colon-specific release behavior of BUD could be easily modified by regulating the number of coated layers. We found that the two-layer BUD-loaded SLNs (SLN-BUD-2L) with a nanoscale particle size and negative zeta potential showed the designed colon-specific drug release profile in response to localized high cellulase activity. In addition, SLN-BUD-2L exhibited excellent anti-inflammatory activity in a dextran sulfate sodium (DSS)-induced colitis mouse model, suggesting its potential anti-UC applications.

Exploring the needs and coping strategies of family caregivers taking care of dying patients at home: a field study.

BACKGROUND: Most Chinese patients chose to die at home, therefore there is a reliance on the family caregivers to be involved in their palliative care. The needs and coping strategies of family caregivers in home-based palliative care are rooted in culture. Little is known about the needs and coping strategies of family caregivers taking care of dying patients at home. METHODS: A field study using semi-structured interview, participant observation, documents and records collection was employed. The study was conducted in two palliative care outpatient departments in tertiary hospitals and four communities in Beijing, China from March 2021 to July 2022. Using purposive sampling, twenty-five family caregivers were recruited. All collected data were analyzed using content analysis approach. RESULTS: Five themes emerged, including three care needs and two coping strategies. Family caregivers need to learn care skills and acquire care resources, including (i) decision-making about home-based palliative care, (ii) improving patient's quality of life, and (iii) signs of final hours and funeral procedures. In facing the care burden, family caregivers coped by (iv) balancing the roles of caregivers and individuals: giving priority to patient care while maintaining their own normal life. In facing the death of a loved one, family caregivers responded by (v) making room for coming death by facing death indirectly and "rescuing" patients for consolation while preparing for the coming death. CONCLUSION: Family caregivers strive to balance the roles of being caregivers and being themselves. As caregivers, they actively prepare patients for good death with no regrets. As individuals, they preserve themselves from being hurt to maintain normal life. The needs of family caregivers focus on caregiver role and are manifested in care skills and resources. TRIAL REGISTRATION: Not registered.

Social Networking Service, Patient-Generated Health Data, and Population Health Informatics: National Cross-sectional Study of Patterns and Implications of Leveraging Digital Technologies to Support Mental Health and Well-being.

BACKGROUND: The emerging health technologies and digital services provide effective ways of collecting health information and gathering patient-generated health data (PGHD), which provide a more holistic view of a patient's health and quality of life over time, increase visibility into a patient's adherence to a treatment plan or study protocol, and enable timely intervention before a costly care episode. OBJECTIVE: Through a national cross-sectional survey in the United States, we aimed to describe and compare the characteristics of populations with and without mental health issues (depression or anxiety disorders), including physical health, sleep, and alcohol use. We also examined the patterns of social networking service use, PGHD, and attitudes toward health information sharing and activities among the participants, which provided nationally representative estimates. METHODS: We drew data from the 2019 Health Information National Trends Survey of the National Cancer Institute. The participants were divided into 2 groups according to mental health status. Then, we described and compared the characteristics of the social determinants of health, health status, sleeping and drinking behaviors, and patterns of social networking service use and health information data sharing between the 2 groups. Multivariable logistic regression models were applied to assess the predictors of mental health. All the analyses were weighted to provide nationally representative estimates. RESULTS: Participants with mental health issues were significantly more likely to be younger, White, female, and lower-income; have a history of chronic diseases; and be less capable of taking care of their own health. Regarding behavioral health, they slept <6 hours on average, had worse sleep quality, and consumed more alcohol. In addition, they were more likely to visit and share health information on social networking sites, write online diary blogs, participate in online forums or support groups, and watch health-related videos. CONCLUSIONS: This study illustrates that individuals with mental health issues have inequitable social determinants of health, poor physical health, and poor behavioral health. However, they are more likely to use social networking platforms and services, share their health information, and actively engage with PGHD. Leveraging these digital technologies and services could be beneficial for developing tailored and effective strategies for self-monitoring and self-management.

Immobilization of titanium dioxide/ions on magnetic microspheres for enhanced recognition and extraction of mono- and multi-phosphopeptides.

The authors are presenting a novel strategy for global phosphoproteome recognition in practical samples. It integrates metal oxide affinity chromatography (MOAC) and immobilization metal ion affinity chromatography (IMAC). This resulted in a kind of titanium dioxide/ion-based multifunctional probe (dubbed T2M). The T2M combines the features of MOAC and IMAC including their recognition preferences towards mono- and multi-phosphorylated peptides. Hence, they exhibit an outstanding recognition capability towards global phosphoproteome, high sensitivity (the limit of detection of which is merely 10 fmol) and excellent specificity in MALDI-TOF MS detection. Their performance is further demonstrated by the identification of the phosphoproteome in non-fat milk and human saliva. By combining T2M with nano LC-MS/MS, remarkable results are obtained in the tryptic digestion of healthy eye lens and cataract lens phosphoproteomes. A total of 658 and 162 phosphopeptides, respectively, were identified. This indicates that phosphorylation and the appearance of cataract can be related to each other. Graphical abstract Schematic presentation of the preparation of titanium dioxide/ion-based multifunctional magnetic nanomaterials (T2M). The T2M based enrichment protocol exhibits outstanding recognition capability towards global phosphoproteome. This protocol shows great prospect for clarifying mechanism of phosphorylation-related diseases via further information acquisition.

Cobalt-Nickel Layered Double Hydroxides Modified on TiO2 Nanotube Arrays for Highly Efficient and Stable PEC Water Splitting.

TiO2 -based photoanodes have attracted extensive attention worldwide for photoelectrochemical (PEC) water splitting, but these materials still suffer from poor electron-hole separation and low photoconversion efficiency. Here, the high PEC water splitting activity and long-term stability against photocorrosion of well-aligned hierarchical TiO2 @CoNi-layered double hydroxides nanotube arrays (TiO2 @CoNi-LDHs NTAs) are reported. The typical TiO2 @CoNi-LDHs NTAs exhibits enhancing photocurrent density of 4.4 mA cm-2 at a potential of 1.23 V (vs reversible hydrogen electrode) under AM 1.5G simulated sunlight (100 mW cm-2 ), 3.3 times higher than that of the pristine TiO2 sample. Moreover, this hierarchical electrode displays excellent stability against photocorrosion with initial activity loss no more than 1.0% even after 10 h irradiation in Na2 SO4 electrolyte solution (pH 6.8), much competitive to those reported TiO2 -based photoelectrodes. This work may offer a combinatorial synthesis strategy for the preparation of hierarchical architectures with high PEC performances.

Analysis on Node Position of Imperfect Resonators for Cylindrical Shell Gyroscopes.

For cylindrical shell gyroscopes, node position of their operating eigenmodes has an important influence on the gyroscopes' performance. It is considered that the nodes are equally separated from each other by 90° when the resonator vibrates in the standing wave eigenmode. However, we found that, due to manufacturing errors and trimming, the nodes may not be equally distributed. This paper mainly analyzes the influences of unbalanced masses on the cylindrical resonators' node position, by using FEM simulation and experimental measurement.

Multimodal Data Hybrid Fusion and Natural Language Processing for Clinical Prediction Models.

This study aims to propose a novel approach for enhancing clinical prediction models by combining structured and unstructured data with multimodal data fusion. We presented a comprehensive framework that integrated multimodal data sources, including textual clinical notes, structured electronic health records (EHRs), and relevant clinical data from National Electronic Injury Surveillance System (NEISS) datasets. We proposed a novel hybrid fusion method, which incorporated state-of-the-art pre-trained language model, to integrate unstructured clinical text with structured EHR data and other multimodal sources, thereby capturing a more comprehensive representation of patient information. The experimental results demonstrated that the hybrid fusion approach significantly improved the performance of clinical prediction models compared to traditional fusion frameworks and unimodal models that rely solely on structured data or text information alone. The proposed hybrid fusion system with RoBERTa language encoder achieved the best prediction of the Top 1 injury with an accuracy of 75.00% and Top 3 injuries with an accuracy of 93.54%. Our study highlights the potential of integrating natural language processing (NLP) techniques with multimodal data fusion for enhancing clinical prediction models' performances. By leveraging the rich information present in clinical text and combining it with structured EHR data, the proposed approach can improve the accuracy and robustness of predictive models. The approach has the potential to advance clinical decision support systems, enable personalized medicine, and facilitate evidence-based health care practices. Future research can further explore the application of this hybrid fusion approach in real-world clinical settings and investigate its impact on improving patient outcomes.

Illuminating the dark space of neutral glycosphingolipidome by selective enrichment and profiling at multi-structural levels.

Glycosphingolipids (GSLs) are essential components of cell membranes, particularly enriched in the nervous system. Altered molecular distributions of GSLs are increasingly associated with human diseases, emphasizing the significance of lipidomic profiling. Traditional GSL analysis methods are hampered by matrix effect from phospholipids and the difficulty in distinguishing structural isomers. Herein, we introduce a highly sensitive workflow that harnesses magnetic TiO2 nanoparticle-based selective enrichment, charge-tagging Paternò-Büchi reaction, and liquid chromatography-tandem mass spectrometry. This approach enables mapping over 300 distinct GSLs in brain tissues by defining sugar types, long chain bases, N-acyl chains, and the locations of desaturation and hydroxylation. Relative quantitation of GSLs across multiple structural levels provides evidence of dysregulated gene and protein expressions of FA2H and CerS2 in human glioma tissue. Based on the structural features of GSLs, our method accurately differentiates human glioma with/without isocitrate dehydrogenase genetic mutation, and normal brain tissue.

Exposure to volatile organic compounds and growth indicators in adolescents: Unveiling the association and potential intervention strategies.

Environmental pollutant is considered to be one of the important factors affecting adolescent growth. However, the effects of volatile organic compounds (VOCs) exposure on adolescent growth have not been assessed. Data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 was used to examine the associations between VOCs exposure and adolescent growth indicators through three statistical models. The mediating effect of bone mineral density (BMD) on these associations was examined. The potential pathways and key targets were identified by the network pharmacology analysis methods. This study included 746 adolescents. Three statistical methods consistently showed a negative correlation between VOCs exposure and adolescent growth indicators. Furthermore, BMD mediated the relationship between VOCs exposure and adolescent growth indicators, with mediated proportion ranging from 4.3 % to 53.4 %. Network pharmacology analysis found a significant enrichment in IL-17 signaling pathway. Moreover, the adverse effects of VOCs exposure on adolescent growth were observed to significantly attenuate in adolescents with high serum vitamin D levels. Our results suggested that VOCs exposure was an adverse factor affecting adolescent growth, with BMD playing a significant regulatory role, and IL-17 signaling pathway was the underlying mechanism. Vitamin D supplementation may be a viable strategy to prevent VOCs exposure from affecting adolescent growth.

Super-resolution ultrasound imaging reveals temporal cerebrovascular changes with disease progression in female 5×FAD mouse model of Alzheimer's disease: correlation with pathological impairments.

BACKGROUND: Vascular dysfunction is closely associated with the progression of Alzheimer's disease (AD). A critical research gap exists that no studies have explored the in vivo temporal changes of cerebrovascular alterations with AD progression in mouse models, encompassing both structure and flow dynamics at micron-scale resolution across the early, middle, and late stages of the disease. METHODS: In this study, ultrasound localisation microscopy (ULM) was applied to image the cerebrovascular alterations of the transgenic female 5×FAD mouse model across different stages of disease progression: early (4 months), moderate (7 months), and late (12 months). Age-matched non-transgenic (non-Tg) littermates were used as controls. Immunohistology examinations were performed to evaluate the influence of disease progression on the ß-amyloid (Aß) load and microvascular alterations, including morphological changes and the blood-brain barrier (BBB) leakage. FINDINGS: Our findings revealed a significant decline in both vascular density and flow velocity in the retrosplenial cortex of 5×FAD mice at an early stage, which subsequently became more pronounced in the visual cortex and hippocampus as the disease progressed. Additionally, we observed a reduction in vascular length preceding diminished flow velocities in cortical penetrating arterioles during the early stages. The quantification of vascular metrics derived from ULM imaging showed significant correlations with those obtained from vascular histological images. Immunofluorescence staining identified early vascular abnormalities in the retrosplenial cortex. As the disease advanced, there was an exacerbation of Aß accumulation and BBB disruption in a regionally variable manner. The vascular changes observed through ULM imaging exhibited a negative correlation with amyloid load and were associated with the compromise of the BBB integrity. INTERPRETATION: Through high-resolution, in vivo imaging of cerebrovasculature, this study reveals significant spatiotemporal dysfunction in cerebrovascular dynamics accompanying disease progression in a mouse model of AD, enhancing our understanding of its pathophysiology. FUNDING: This study is supported by grants from National Key Research and Development Program of China (2020YFA0908800), National Natural Science Foundation of China (12074269, 82272014, 82327804, 62071310), Shenzhen Basic Science Research (20220808185138001, JCYJ20220818095612027, JCYJ20210324093006017), STI 2030-Major Projects (2021ZD0200500) and Guangdong Natural Science Foundation (2024A1515012591, 2024A1515011342).

Leveraging natural language processing and geospatial time series model to analyze COVID-19 vaccination sentiment dynamics on Tweets.

Objective: To develop and apply a natural language processing (NLP)-based approach to analyze public sentiments on social media and their geographic pattern in the United States toward coronavirus disease 2019 (COVID-19) vaccination. We also aim to provide insights to facilitate the understanding of the public attitudes and concerns regarding COVID-19 vaccination. Methods: We collected Tweet posts by the residents in the United States after the dissemination of the COVID-19 vaccine. We performed sentiment analysis based on the Bidirectional Encoder Representations from Transformers (BERT) and qualitative content analysis. Time series models were leveraged to describe sentiment trends. Key topics were analyzed longitudinally and geospatially. Results: A total of 3 198 686 Tweets related to COVID-19 vaccination were extracted from January 2021 to February 2022. 2 358 783 Tweets were identified to contain clear opinions, among which 824 755 (35.0%) expressed negative opinions towards vaccination while 1 534 028 (65.0%) demonstrated positive opinions. The accuracy of the BERT model was 79.67%. The key hashtag-based topics include Pfizer, breaking, wearamask, and smartnews. The sentiment towards vaccination across the states showed manifest variability. Key barriers to vaccination include mistrust, hesitancy, safety concern, misinformation, and inequity. Conclusion: We found that opinions toward the COVID-19 vaccination varied across different places and over time. This study demonstrates the potential of an analytical pipeline, which integrates NLP-enabled modeling, time series, and geospatial analyses of social media data. Such analyses could enable real-time assessment, at scale, of public confidence and trust in COVID-19 vaccination, help address the concerns of vaccine skeptics, and provide support for developing tailored policies and communication strategies to maximize uptake.

Magnetic metal oxide affinity chromatography-based molecularly imprinted approach for effective separation of serous and urinary phosphoprotein biomarker.

Many phosphoprotein biomarkers have been proved to exist in body fluids such as serum and urine, however, there is absence of rapid and efficient separation and identification method. In this study, we proposed to combine metal oxide affinity chromatography (MOAC), molecular imprinting technology (MIT) and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) to establish an effective approach to solve this problem. To verify the feasibility of this approach, we selected a typical phosphoprotein lysozyme (Lys) as template and magnetic TiO2 as substrate to prepare the molecularly imprinted nanoparticles (denoted as Fe3O4@TiO2@Lys MIPs). A point worth noting is that polydopamine (PDA) as polymer layer made Fe3O4@TiO2@Lys MIPs more hydrophilic and biocompatible. Thanks to the recognition sites of phosphate and the template-shaped cavities, Fe3O4@TiO2@Lys MIPs showed great sensitivity (0.01 ng*µL-1) and selectivity (Lysozyme: BSA: ß-casein = 1:100:100, mass ratio) in standard phosphoprotein solution. At the end, the Fe3O4@TiO2@Lys MIPs showed great separation ability to lysozyme phosphoprotein in both human serum and urine samples. Therefore, the MOAC-based molecularly imprinted approach is worthy to be expected in effective separation of phosphoprotein biomarker in complex body fluid, which will be a promising one in future.

A rational route to hybrid aptamer-molecularly imprinted magnetic nanoprobe for recognition of protein biomarkers in human serum.

Although antibody has played a great role in highly specific recognition of protein biomarkers, it faces poor stability, reproducibility, high-cost and time-consuming preparation, etc. Here, aptamer and molecularly imprinted polymers (MIPs), both as promising substitutes of antibody, were integrated onto magnetic nanoparticles by Au-S bonds and SiO2 as imprinted layer for preparing a new nanoprobe. Highly specific and sensitive recognition of different protein biomarkers, such as insulin for diabetes and alpha-fetoprotein (AFP) for hepatic carcinoma, were achieved respectively by the system of combining hybrid aptamer-molecularly imprinted magnetic nanoprobe and mass spectrometry. With the double affinities offered by aptamer-MIPs, insulin can be detected at 0.5 ng mL-1 in human serum dilution, the equlibrium dissociation constant between nanoprobe and insulin is measured as 23.61 ± 2.27 µM. Likewise, AFP can be sufficiently detected in human saliva dilution from 1000 ng mL-1 to 20 ng mL-1, and two patients with hepatic carcinoma are discriminated from healthy person due to the abnormally high expression of AFP in serum.

Development of metformin hydrochloride loaded dissolving tablets with novel carboxymethylcellulose/poly-l-lysine/TPP complex.

Natural polymers like polysaccharides, polypeptides and their derivatives are broadly applied in drug delivery due to excellent biocompatibility and biodegradability. In this study, the dissolving tablets, formed with carboxymethylcellulose/poly-l-lysine/tripolyphosphate (CMC/PLL/TPP) complex, were prepared using metformin hydrochloride (MetHCl) as model drug. Confocal laser scanning microscopy observation manifested that FITC-labeled PLL interacted with CMC and formed a uniform interior microstructure. Scanning electron microscope images showed the drug-loaded tablets had well-formed shapes with smooth surfaces. MetHCl embedded interior the microstructures of the tablets and represented in a crystal form. Thermo-gravimetric analysis and differential scanning calorimetry indicated that the drug-loaded tablets had stable thermal properties with less moisture content (3.52%). Fourier transform infrared spectrometer confirmed that the CMC/PLL/TPP complex was fabricated via the electrostatic interactions between -NH3+, -COO- and -[P2O54-]- groups. The drug-loaded tablets had a high drug loading efficiency of 85.76% and drug encapsulation efficiency of 81.47%, and a shorter wetting time of 2.16 min in SSF (pH 6.8) and lower swelling ratio of 233.34%. The drug loaded in the samples could be released completely within 10 min in simulated saliva fluid (SSF pH 6.8), indicating a rapid drug release and dissolving profile in the environment, which could be developed for dissolving tablets.

A promising nanoprobe based on hydrophilic interaction liquid chromatography and immobilized metal affinity chromatography for capture of glycopeptides and phosphopeptides.

Glycosylation and phosphorylation are two important mechanisms in organism, both of which can finely regulate protein function respectively or simultaneously. Functional nanoprobes with various reversible interactions of aiming at glycan or phosphate group have been advanced dramatically, however, the comprehensive analysis towards them is largely restricted by the challenge to capture glycopeptides and phosphopeptides at the same time from complex samples due to the limitation of nanoprobe functionalization. Here, we fabricate a promising nanoprobe using the hydrophilic l-cysteine and titanium ions to enhance the phosphopeptides capture, meanwhile, realize the glycopeptides capture. We test the performance of the promising nanoprobe, showing that it is not only equipped with good unbiased ability in glycopeptides capture with high sensitivity and selectivity, but also highly effective for phosphopeptides capture. More importantly, the promising nanoprobe enables the simultaneous capture and analysis of glycosylated and phosphorylated peptides from mouse brain, as well as human eye lens of normal and cataract. The identification of glycosylated and phosphorylated sites within normal and cataract reflects their differential expression and offers an excellent insight to glycosylation/phosphorylation-related human eye diseases, indicating its great potential in glycoproteomics and phosphoproteomics researches.

Aptamer-functionalized magnetic metal organic framework as nanoprobe for biomarkers in human serum.

Human serum is a huge bioinformatics database of human physiological and pathological state, many proteins/peptides among which can serve as biomarkers for monitoring human's health condition, thereby being worth exploring. The simple and fast capture of biomarkers from human serum is the first key step to realize their accurate detection. In this work, we developed the aptamer functionalized magnetic metal organic framework nanoprobe, and furtherly combined with mass spectrometry technology to establish an efficient method of identifying biomarkers. Taking insulin as example of biomarker in human serum, we developed sulfhydryl human insulin aptamer functionalized magnetic metal organic framework (denoted as Mag MOF@Au@HIA) through the post-synthetic modification of MIL-101(Cr)-NH2 for testing the applicability of the established method. Depending on the strong magnetic responsiveness and high specific area as well as high-loaded human insulin aptamers, the limit of detection of insulin was down to 1 ng/mL and 2 ng/mL in the standard insulin solution and human serum, respectively. Moreover, a good linear relationship (R2 = 0.998) was obtained by using standard insulin solution with concentration range from 100 ng/mL to 5 ng/mL, based on which the capture recovery of insulin with Mag MOF@Au@HIA from human serum was demonstrated to be excellent. All of the results indicate that the aptamer-functionalized magnetic metal organic framework is a promising nanoprobe for biomarkers capture in human serum.