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Carbamoyl phosphate synthetase 1 (CPS1) drives ammonia conversion to carbamoyl phosphate, and its overexpression supports pyrimidine synthesis and tumor growth, highlighting the potential of CPS1 inhibition as a therapeutic target. In this issue of Cell Chemical Biology, Yao et al. (2020) introduce H3B-120 as a promising novel inhibitor of CPS1. BACKGROUND Frailty is increasingly recognized as an important prognostic marker in surgical populations. The effects of frailty on outcomes after mitral valve replacement (MVR) is less clear given the inherent complexity of this patient population. We evaluated the influences of frailty on outcomes and readmission rates after MVR. METHODS Adult patients undergoing isolated MVR were queried from the National Readmissions Database from 2010 to 2014. Frailty was defined using the Johns Hopkins Adjusted Clinical Groups frailty-defining diagnoses indicator, a validated instrument developed for use in health administrative data. Multivariable logistic regression was used to determine hospital- and patient-level risk factors for readmission, postoperative complications, and death. RESULTS Among 50,410 patients who underwent MVR, 7.9% met frailty criteria. Frail patients were more likely to be older, have nonprivate insurance, an index admission from the emergency department, and teaching hospital care (all P less then .001). Frail patients had significantly more postoperative complications (77% vs 47%, P less then .001), more discharges to a facility (50% vs 21%, P less then .001), and higher in-hospital mortality (12% vs 4%, P less then .001). Index hospitalization costs were almost doubled in frail patients, and of those who survived to discharge, 30-day readmissions were more frequent (28% vs 20%, P less then .001). Frailty independently increased the risk of index hospitalization composite complications (adjusted odds ratio [AOR], 3.28; 95% confidence interval [CI], 2.61-4.12), in-hospital mortality (AOR, 2.35; 95% CI, 1.90-2.92), and 30-day readmission (AOR, 1.47; 95% CI, 1.20-1.78). CONCLUSIONS Frailty is an independent predictor of morbidity, death, and increased costs after MVR. Frailty metrics should be increasingly understood among patients requiring mitral valve intervention as percutaneous approaches for intervention become increasingly used. Cell heterogeneity of tumor tissues is one of the causes of cancer recurrence after chemotherapy. Cell subtype identification in tumor tissues of specific cancer is critical for precision medicine and prognosis. As the structural and functional components of cells, lipids are closely related to the apparent morphology of cells. gp91ds-tat They are potential biomarkers of species of cancers and can be used to classify different cancer cell types, but it remains a challenge to establish a stable cell differentiation model and extend it to tumor tissue cell subtype differentiation. Here we describe a lipid profiling method based on nanostructure assisted laser desorption/ionization mass spectrometry (NALDI-MS), which could classify five hepatocellular carcinoma (HCC) cell lines and discriminate subtype of mixed cells and tumor tissues. The NALDI target was patterned with array of sample spots containing vertical silicon nanowires (Si NWs). Owing to its high ability to absorb laser energy, the vertical Si NWs can help to generate abundant lipid ions of cell extracts without need of organic matrix. Combined with statistical analysis methods, twenty-two ion peaks distributed in four MS peak clusters were selected as potential biomarkers to distinguish the subtype of the five HCC cell lines. Peak normalization was performed within each MS peak cluster to reduce the variation of peak intensity in batch to batch analysis. Compared to full-spectrum normalization method, the inner-cluster normalization method could help to distinguish cell subtype more stably and accurately. The molecular structure of these biomarkers was identified and sorted into two classes including phosphatidylcholine (PE, PI, PG, PA, PS) and glycosphingolipid (LacCer, ST). Furthermore, the established method was successfully applied to identify the major HCC cell subtype in mixed cell samples and xenograft tumor tissues as well as drug response test, showing great potential in precision medicine and prognosis. We report a flow-cytometry based method capable of detecting a range of analytes by monitoring the analyte-induced clustering of magnetic and fluorescent nanoparticles with flow cytometry. Using the dengue viral antigen (NS1) as an example, antibodies were conjugated to magnetic and fluorescent nanoparticles in a sandwich immunoassay format. These nanoparticles formed clusters when NS1 was present in a sample and the cluster formation was directly proportional to the concentration of antigen. Simultaneous flow cytometry measurement of cluster size, as detected by the forward scatter channel, combined with fluorescence intensity led to a reduction in the assay background signal, resulting in improved analytical sensitivity. We were able to detect 2.5 ng mL-1 of NS1 in serum samples by quantifying the clusters, a two-log fold improvement in the assay limit of detection over total fluorescence quantification alone. A sensitive, rapid, precise and specific analytical method of hydrophilic interaction ultra-performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (HILIC-UHPLC-QTRAP®/MS2) combined with a high-efficiency and easy sample preparation technology of ultrasound-assisted ionic liquid dispersive liquid-liquid microextraction (UA-IL-DLLME) was developed to investigate neurotransmitters (NTs) in mild cognitive impairment, mild dementia and moderate dementia patients' urine samples. Firstly, the UA-IL-DLLME parameters were optimized using Plackett-Burman screening and rotatable central composite design, and the main optimal conditions were obtained ultrasound power of 307 W, ultrasound time of 4.3 min and agitation time of 4.8 min. Secondly, HILIC-UHPLC-QTRAP®/MS2 method was developed to simultaneously determine 15 underivatized NTs in urine samples. The analysis results of clinical samples showed that some NTs such as γ-aminobutyric acid (GABA), acetylcholine (Ach) and glutamic acid (Glu) presented significant differences in different dementia stages.