Multi-scale signaling and tumor evolution in high-grade gliomas.

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

Multiomic foundations of human prefrontal cortex tissue function.

The prefrontal cortex (PFC) is a region of the brain that in humans is involved in the production of higher-order functions such as cognition, emotion, perception, and behavior. Neurotransmission in the PFC produces higher-order functions by integrating information from other areas of the brain. At the foundation of neurotransmission, and by extension at the foundation of higher-order brain functions, are an untold number of coordinated molecular processes involving the DNA sequence variants in the genome, RNA transcripts in the transcriptome, and proteins in the proteome. These "multiomic" foundations are poorly understood in humans, perhaps in part because most modern studies that characterize the molecular state of the human PFC use tissue obtained when neurotransmission and higher-order brain functions have ceased (i.e., the postmortem state). Here, analyses are presented on data generated for the Living Brain Project (LBP) to investigate whether PFC tissue from individuals with intact higher-order brain function has characteristic multiomic foundations. Two complementary strategies were employed towards this end. The first strategy was to identify in PFC samples obtained from living study participants a signature of RNA transcript expression associated with neurotransmission measured intracranially at the time of PFC sampling, in some cases while participants performed a task engaging higher-order brain functions. The second strategy was to perform multiomic comparisons between PFC samples obtained from individuals with intact higher-order brain function at the time of sampling (i.e., living study participants) and PFC samples obtained in the postmortem state. RNA transcript expression within multiple PFC cell types was associated with fluctuations of dopaminergic, serotonergic, and/or noradrenergic neurotransmission in the substantia nigra measured while participants played a computer game that engaged higher-order brain functions. A subset of these associations - termed the "transcriptional program associated with neurotransmission" (TPAWN) - were reproduced in analyses of brain RNA transcript expression and intracranial neurotransmission data obtained from a second LBP cohort and from a cohort in an independent study. RNA transcripts involved in TPAWN were found to be (1) enriched for RNA transcripts associated with measures of neurotransmission in rodent and cell models, (2) enriched for RNA transcripts encoded by evolutionarily constrained genes, (3) depleted of RNA transcripts regulated by common DNA sequence variants, and (4) enriched for RNA transcripts implicated in higher-order brain functions by human population genetic studies. In PFC excitatory neurons of living study participants, higher expression of the genes in TPAWN tracked with higher expression of RNA transcripts that in rodent PFC samples are markers of a class of excitatory neurons that connect the PFC to deep brain structures. TPAWN was further reproduced by RNA transcript expression patterns differentiating living PFC samples from postmortem PFC samples, and significant differences between living and postmortem PFC samples were additionally observed with respect to (1) the expression of most primary RNA transcripts, mature RNA transcripts, and proteins, (2) the splicing of most primary RNA transcripts into mature RNA transcripts, (3) the patterns of co-expression between RNA transcripts and proteins, and (4) the effects of some DNA sequence variants on RNA transcript and protein expression. Taken together, this report highlights that studies of brain tissue obtained in a safe and ethical manner from large cohorts of living individuals can help advance understanding of the multiomic foundations of brain function.

Pan-cancer proteogenomics characterization of tumor immunity.

Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.

RECCIPE: A new framework assessing localized cell-cell interaction on gene expression in multicellular ST data.

Cell-cell interaction (CCI) plays a pivotal role in cellular communication within the tissue microenvironment. The recent development of spatial transcriptomics (ST) technology and associated data analysis methods has empowered researchers to systematically investigate CCI. However, existing methods are tailored to single-cell resolution datasets, whereas the majority of ST platforms lack such resolution. Additionally, the detection of CCI through association screening based on ST data, which has complicated dependence structure, necessitates proper control of false discovery rates due to the multiple hypothesis testing issue in high dimensional spaces. To address these challenges, we introduce RECCIPE, a novel method designed for identifying cell signaling interactions across multiple cell types in spatial transcriptomic data. RECCIPE integrates gene expression data, spatial information and cell type composition in a multivariate regression framework, enabling genome-wide screening for changes in gene expression levels attributed to CCIs. We show that RECCIPE not only achieves high accuracy in simulated datasets but also provides new biological insights from real data obtained from a mouse model of Alzheimer's disease (AD). Overall, our framework provides a useful tool for studying impact of cell-cell interactions on gene expression in multicellular systems.

Proteogenomic data and resources for pan-cancer analysis.

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer.

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

Design, Synthesis, and Biological Evaluation of Marine Lissodendrins B Analogues as Modulators of ABCB1-Mediated Multidrug Resistance.

Multidrug resistance (MDR) caused by ATP-Binding Cassette Subfamily B Member 1 (ABCB1, P-glycoprotein, P-gp) is a major barrier for the success of chemotherapy in clinics. In this study, we designed and synthesized a total of 19 Lissodendrins B analogues and tested their ABCB1-mediated MDR reversal activity in doxorubicin (DOX)-resistant K562/ADR and MCF-7/ADR cells. Among all derivatives, compounds D1, D2, and D4 with a dimethoxy-substituted tetrahydroisoquinoline fragment possessed potent synergistic effects with DOX and reversed ABCB1-mediated drug resistance. Notably, the most potent compound D1 merits multiple activities, including low cytotoxicity, the strongest synergistic effect, and effectively reversing ABCB1-mediated drug resistance of K562/ADR (RF = 1845.76) and MCF-7/ADR cells (RF = 207.86) to DOX. As a reference substance, compound D1 allows for additional mechanistic studies on ABCB1 inhibition. The synergistic mechanisms were mainly related to the increased intracellular accumulation of DOX via inhibiting the efflux function of ABCB1 rather than from affecting the expression level of ABCB1. These studies suggest that compound D1 and its derivatives might be potential MDR reversal agents acting as ABCB1 inhibitors in clinical therapeutics and provide insight into a design strategy for the development of ABCB1 inhibitors.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness.

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Chinese physical fitness standard for campus football players: A pilot study of 765 children aged 9 to 11.

Objectives: In 2022, 55 million Chinese children participate in campus football; however, there is no physical fitness standard, making it a priority task to enhance the current national program. This study aimed to explore a pilot method for the development of a reliable physical fitness standard. Methods: This study examined 765 male football players aged 9 to 11 in 2020 and 2022. The anthropometric and physical fitness assessments were conducted in accordance with the Chinese Football Association's field manuel. Physical fitness tests include sit and reach test, t test, 30 m run test, and vertical jump test. Physical fitness standard was modeled using the generalized additive models for location, scale, and shape (GAMLSS). Data were fitted with appropriate GAMLSS distributions and smoothing term. P-splines were applied to smooth the model's parameters using the default local maximum likelihood method and link functions. Following diagnostics of fitted models, age-specific centile estimations were computed for physical fitness tests. In addition, players in each age group were categorized according to their body mass index as normal weight or overweight/obese. Welch's t-test was utilized to compare the group differences in physical fitness testing. The significance level was chosen at p < 0.05. Results: Sit and reach test, t test, 30 m run test, and vertical jump test data were fitted with original Sinh-Arcsinh, Box-Cox power exponential, Box-Cox power exponential, and Box-Cox Cole and Green, respectively. Physical fitness standard for each age group is presented as tabulated centiles (1p, 3p, 5p, 15p, 25p, 50p, 75p, 85p, 95p, 97p, 99p). Overweight/obese campus football players did significantly worse (p < 0.05) on the t test, 30 m run test, and vertical jump test than their normal-weight peers of the same age. Conclusion: This study developed the first physical fitness standard for 9 to 11-year-old campus football players in China. We made three recommendations to Chinese policymakers on sample size, data management, and field procedure for the creation of a national physical fitness standard.

Antiperspirant effects and mechanism investigation of Mulisan decoction in rats based on plasma metabolomics.

CONTEXT: Mulisan decoction (MLS) is a classic formula of traditional Chinese medicine for treating hyperhidrosis. The mechanism remains unclear. OBJECTIVE: To investigate the antiperspirant effect and underlying mechanisms of MLS. MATERIALS AND METHODS: Fifty rats were divided into control, model, and three doses of MLS intervention groups (n = 10). Rats except for control group were induced diseases features of the applicable scope of MLS via i.p. reserpine (0.5 mg/kg/d) for 10 days. From day 11, MLS groups were administrated orally MLS at 0.6, 3, and 15 g/kg once a day for 14 days, respectively. After the last administration, sweating was induced in all rats via s.c. pilocarpine (25 mg/kg), the right hind foot of rats was stained, and sweat point numbers were observed. Rat serum was collected to detect IL-2, IL-6, IFN-γ, and TNF-α. Rat plasma was collected for endogenous metabolite analysis via UPLC-QE-Focus-MS. RESULTS: Rats treated with MLS presented a significant decrease in sweat point numbers (13.5%), increase in body weight (13.2%), and promotion in the balance of Th1/Th2 cytokine ratio via increasing IL-2 (38.3%), IFN-γ (20.1%), and TNF-α (22.0%) and decreasing IL-6 (24.7%) compared with the model group (p < 0.05). Plasma metabolomics disclosed 15 potential biomarkers related to model rats, of which two could be significantly reversed by MLS (p < 0.05). The involved pathways were pantothenate and CoA biosynthesis, and porphyrin metabolism. CONCLUSIONS: MLS demonstrated a good antiperspirant effect and metabolism improvement. These findings inspire more clinical study validation on immune improvement and antiperspirant effect.

Cell division control 42 elevates during infliximab therapy, and its increment relates to treatment response in ulcerative colitis patients.

BACKGROUND: Cell division control 42 (CDC42) regulates multiple processes of inflammation and/or immunity in autoimmune diseases and also relates to the treatment efficacy of biologic regimens clinically. This study aimed to explore the longitudinal change in CDC42 during infliximab (IFX) treatment and its correlation with IFX response in ulcerative colitis (UC) patients. METHODS: Active UC patients (N = 48) who received IFX were recruited, and their CDC42 expressions in peripheral blood mononuclear cells (PBMCs) were detected before treatment (W0) and at 12 weeks after treatment (W12) using RT-qPCR. Also, CDC42 in PBMCs from UC patients with remission (N = 20) and health controls (HCs) (N = 20) were detected. RESULTS: CDC42 was reduced in active UC patients compared with UC patients with remission (p = 0.014) and HCs (p < 0.001). Besides, CDC42 was negatively correlated with CRP (p = 0.025), TNF-α (p = 0.024), IL-1ß (p = 0.045), IL-17A (p = 0.039), and Mayo score (p = 0.015) in active UC patients, but did not relate to ESR, disease duration, or IL-6 (all p > 0.05), while CDC42 was only negatively related to CRP in UC patients with remission (p = 0.046). Interestingly, CDC42 was increased at W12 after IFX treatment in active UC patients (p < 0.001). Specifically, CDC42 was elevated during treatment in active UC patients with IFX response (p < 0.001), but did not obviously change in those without IFX response (p = 0.061). Furthermore, CDC42 at W12 was higher in active UC patients with IFX response compared with those without IFX response (p = 0.049). CONCLUSION: Cell division control 42 serves as a potential biomarker for monitoring disease progression and IFX response in UC patients.

Stimulating the Hematopoietic Effect of Simulated Digestive Product of Fucoidan from Sargassum fusiforme on Cyclophosphamide-Induced Hematopoietic Damage in Mice and Its Protective Mechanisms Based on Serum Lipidomics.

Hematopoietic damage is a serious side effect of cytotoxic drugs, and agents promoting hematopoiesis are quite important for decreasing the death rate in cancer patients. In our previous work, we prepared the simulated digestive product of fucoidan from Sargassum fusiforme, DSFF, and found that DSFF could activate macrophages. However, more investigations are needed to further evaluate whether DSFF could promote hematopoiesis in the chemotherapy process. In this study, the protective effect of DSFF (1.8-7.2 mg/kg, i.p.) on cyclophosphamide-induced hematopoietic damage in mice and the underlying mechanisms were investigated. Our results show that DSFF could restore the numbers of white blood cells, neutrophils, and platelets in the peripheral blood, and could also retard bone marrow cell decrease in mice with cyclophosphamide-induced hematopoietic damage. UPLC/Q-Extraction Orbitrap/MS/MS-based lipidomics results reveal 16 potential lipid biomarkers in a serum that responded to hematopoietic damage in mice. Among them, PC (20:1/14:0) and SM (18:0/22:0) were the key lipid molecules through which DSFF exerted protective actions. In a validation experiment, DSFF (6.25-100 µg/mL) could also promote K562 cell proliferation and differentiation in vitro. The current findings indicated that DSFF could affect the blood cells and bone marrow cells in vivo and thus showed good potential and application value in alleviating the hematopoietic damage caused by cyclophosphamide.

Semisynthesis and biological evaluation of (+)-sclerotiorin derivatives as antitumor agents for the treatment of hepatocellular carcinoma.

Hepatocellular carcinoma is one of the most common primary hepatic malignancy. Herein, a series of semisynthesized derivatives (2-30) of the natural product (+)-sclerotiorin (1) was prepared and evaluated the cytotoxic activities against six cancer cell lines. Among them, 3 and 5 were the most effective compounds against human hepatocellular carcinoma Bel-7402 cell line with IC50 values of 1.45 and 1.15 µM, respectively. Molecular mechanism study showed that 5 disrupted the mitochondrial membrane potential and induced apoptosis in a caspase-dependent manner. In addition, 5 affected AKT and ERK signaling pathways and induced AKT and ERK proteins degradation through ubiquitin-proteasome system. Furthermore, 5 displayed significant in vivo anticancer effects in the xenograft models with decreasing the tumor mass by 52.5%. The safety evaluation was confirmed by acute toxicity subchronic toxicity tests, paraffin sections of mice organ and blood routine examination. Taken together, 5 can be developed as a potential therapeutic agent for hepatocellular carcinoma.

Comparative assessment of standard and immune response criteria for evaluation of response to PD-1 monotherapy in unresectable HCC.

PURPOSE: To assess response to programmed death-1 (PD-1) monotherapy (nivolumab) in hepatocellular carcinoma (HCC) patients using RECIST1.1, modified RECIST (mRECIST), and immune RECIST (iRECIST). A secondary objective was to identify clinicolaboratory and imaging variables predictive of progressive disease (PD) and overall survival (OS). METHODS: Patients with HCC treated with nivolumab at a single institution from 5/2016 to 12/2019 with MRI or CT performed ≥ 4 weeks post treatment were retrospectively assessed. Patients who received concurrent locoregional, radiation, or other systemic therapies were excluded. Response was assessed by 2 observers in consensus using RECIST1.1, mRECIST, and iRECIST at 3/6/9/12-month time points. Time to progression (TTP) and OS were recorded. Clinicolaboratory and imaging variables were evaluated as predictors of PD and OS using uni-/multivariable and Cox regression analyses. RESULTS: Fifty-eight patients (42M/16F) were included. 118 target lesions (TL) were identified before treatment. Baseline mean TL size was 49.1 ± 43.5 mm (range 10-189 mm) for RECIST1.1/iRECIST and 46.3 ± 42.3 mm (range 10-189 mm) for mRECIST. Objective response rate (ORR) was 21% for mRECIST/iRECIST/RECIST1.1, with no cases of pseudoprogression. Median OS and median TTP were 717 days and 127 days for RECIST1.1/mRECIST/iRECIST-iUPD (unconfirmed PD). Older age, MELD/Child-Pugh scores, AFP, prior transarterial radioembolization (TARE), and larger TL size were predictive of PD and/or poor OS using mRECIST/iRECIST. The strongest predictor of PD (HR = 2.49, 95% CI 1.29-4.81, p = 0.007) was TARE. The strongest predictor of poor OS was PD by mRECIST/iRECIST at 3 months (HR = 2.26, 95% CI 1.00-5.10, p = 0.05) with borderline significance. CONCLUSION: Our results show ORR of 21%, equivalent for mRECIST, iRECIST, and RECIST1.1 in patients with advanced HCC clinically treated with nivolumab.

Menopausal Women's Health Care Method Based on Computer Nursing Diagnosis Intelligent System.

Taking into account the current feature extraction speed and recognition effect of intelligent diagnosis of menopausal women's health care behavior, this paper proposes to use a cross-layer convolutional neural network to extract behavior features autonomously and use support vector machine multiclass behavior classifier to classify behavior. Compared with the feature images extracted by traditional methods, the behavioral features extracted in this paper are related to the individual menopausal women and have better semantic information, and the feature description ability in the time domain and the space domain has been enhanced. Through Matlab software, using the database established in this paper to compare its feature extraction time, test classification time, and final recognition accuracy with ordinary convolutional neural networks, it is concluded that the cross-layer CNN-SVM model can ensure the speed of feature extraction. It proves that the method in this paper can be applied to the behavioral intelligent diagnosis system for intelligently nursing menopausal women and has good practical value. This paper designs a home care bed intelligent monitoring system, which can automatically detect the posture of the care bed, and not only can change the posture of the bed under the control of personnel, but also can automatically complete the posture conversion according to the setting. At the same time, the system has the function of monitoring the physical condition of the person being cared for and can detect the heart rate, blood oxygen, and other physiological indicators of the bedridden person. In addition, the system can also provide a remote diagnosis function, allowing nursing staff to remotely view the current state of the nursing bed and the physical condition of the person. After testing, the system works stably, improves the automation and safety of the nursing bed control, and enriches the functions of the nursing bed.

Effects of simulated digestion in vitro on the structure and macrophages activation of fucoidan from Sargassum fusiforme.

Molecular size and spatial structure affect the bioactivities of polysaccharides. SFF is a fucoidan extracted from Sargassum fusiforme. The possible changes of SFF affected by gastrointestinal tract and subsequently changes of its physicochemical property or its bioactivity have yet to be systematically investigated. Our results showed that DSFF, the gastrointestinal digestion product of SFF, has increased reducing sugar content, increased proportion of low molecular weight components, and a more clustered island-like morphology. Both SFF and DSFF activate RAW 264.7 macrophages evidenced by the increasing level of NO, intracellular ROS, and macrophages cytokines. Further investigation showed that DSFF induced M1 phenotype polarization in RAW 264.7 cells. DSFF also showed stronger macrophage activation and phenotype polarization than SFF. Our present work showed that SFF could be digested by simulated gastrointestinal environment in vitro and the digested product DSFF showed higher efficiency in macrophages activation and phenotype polarization.

Importance of applying Mixed Generalized Additive Model (MGAM) as a method for assessing the environmental health impacts: Ambient temperature and Acute Myocardial Infarction (AMI), among elderly in Shanghai, China.

Association between acute myocardial infarction (AMI) morbidity and ambient temperature has been examined with generalized linear model (GLM) or generalized additive model (GAM). However, the effect size by these two methods might be biased due to the autocorrelation of time series data and arbitrary selection of degree of freedom of natural cubic splines. The present study analyzed how the climatic factors affected AMI morbidity for older adults in Shanghai with Mixed generalized additive model (MGAM) that addressed these shortcomings mentioned. Autoregressive random effect was used to model the relationship between AMI and temperature, PM10, week days and time. The degree of freedom of time was chosen based on the seasonal pattern of temperature. The performance of MGAM was compared with GAM on autocorrelation function (ACF), partial autocorrelation function (PACF) and goodness of fit. One-year predictions of AMI counts in 2011 were conducted using MGAM with the moving average. Between 2007 and 2011, MGAM adjusted the autocorrelation of AMI time series and captured the seasonal pattern after choosing the degree of freedom of time at 5. Using MGAM, results were well fitted with data in terms of both internal (R2 = 0.86) and external validity (correlation coefficient = 0.85). The risk of AMI was relatively high in low temperature (Risk ratio = 0.988 (95% CI 0.984, 0.993) for under 12°C) and decreased as temperature increased and speeded up within the temperature zone from 12°C to 26°C (Risk ratio = 0.975 (95% CI 0.971, 0.979), but it become increasing again when it is 26°C although not significantly (Risk ratio = 0.999 (95% CI 0.986, 1.012). MGAM is more appropriate than GAM in the scenario of response variable with autocorrelation and predictors with seasonal variation. The risk of AMI was comparatively higher when temperature was lower than 12°C in Shanghai as a typical representative location of subtropical climate.

A community effort to identify and correct mislabeled samples in proteogenomic studies.

Sample mislabeling or misannotation has been a long-standing problem in scientific research, particularly prevalent in large-scale, multi-omic studies due to the complexity of multi-omic workflows. There exists an urgent need for implementing quality controls to automatically screen for and correct sample mislabels or misannotations in multi-omic studies. Here, we describe a crowdsourced precisionFDA NCI-CPTAC Multi-omics Enabled Sample Mislabeling Correction Challenge, which provides a framework for systematic benchmarking and evaluation of mislabel identification and correction methods for integrative proteogenomic studies. The challenge received a large number of submissions from domestic and international data scientists, with highly variable performance observed across the submitted methods. Post-challenge collaboration between the top-performing teams and the challenge organizers has created an open-source software, COSMO, with demonstrated high accuracy and robustness in mislabeling identification and correction in simulated and real multi-omic datasets.

Determination of 13 antidepressants in blood by UPLC-MS/MS with supported liquid extraction pretreatment.

Antidepressants are widely used nowadays. Due to the potential detrimental consequences and involvement in forensic cases, therapeutic drug monitoring of antidepressants is desired. Herein we report a method for sensitive determination of 13 commonly used antidepressants in blood. An ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method with supported liquid extraction (SLE) was developed for analysis of imipramine, desipramine, fluoxetine, norfluoxetine, paroxetine, maprotiline, sertraline, citalopram, clomipramine, trazodone, doxepin, clozapine and amitriptyline in this study. The limits of detection (LODs) are in the range of 0.0003-0.003 ng/mL, which are lower than other reported methods by several orders of magnitude. The linear ranges are 0.01-200 ng/mL for norfluoxetine, paroxetine and doxepin, while the linear ranges are 0.001-200 ng/mL for the rest antidepressants. The correlation coefficients are over 0.99. Extraction recoveries (ER) ranging in 82.4-101.5% were obtained for the target analytes. The intra-day relative standard deviations (RSDs) range in 4.5-10.3% and inter-day RSDs range in 5.1-12.7%. Reasonable values of matrix effect (ME) ranging in 82.5-110.4% were obtained for quality control samples. The present methodology was used for the analysis of antidepressants in real cases and is expected to have a wide usage for analysis of antidepressants in biomedical area and forensic practice.