Objective: Amyotrophic lateral sclerosis (ALS) is an adult-onset fatal neurodegenerative disease which lacks identified biological markers. A label-free plasma surface-enhanced Raman spectroscopy (SERS) method was developed to explore a simple and noninvasive test for ALS. Methods: ALS patients were enrolled serially and plasma samples were collected at the time of diagnosis prior to the start of ALS treatment. SERS spectra were recorded using a Renishaw micro-Raman system. Results: To exclude the interference by varying disease severity, we enrolled three groups of ALS patients, including ALS-1 (n = 60; ALSFRS-R ≥ 42 and time interval ≤ 12 months), ALS-2 (n = 61; ALSFRS-R < 42 and time interval ≤ 12 months), and ALS-3 (n = 61; ALSFRS-R ≥ 38 and time interval> 12 months). The SERS spectra were analyzed using principal component analysis (PCA), which showed that ALS-1, ALS-2, ALS-3, and control groups were separated significantly. Then, decision tree (DT) models and receiver operating characteristic curves were employed and identified that bands at 722 and 739 cm À1 , and ratios of 635-722 cm À1 and 635-739 cm À1 were able to distinguish ALS from controls significantly. Finally, we highlighted six metabolism pathways correlated with ALS, including phenylalanine-tyrosine-tryptophan biosynthesis, aminoacyl-tRNA biosynthesis, phenylalanine metabolism, pantothenate and CoA biosynthesis, porphyrin and chlorophyll metabolism, and pyrimidine metabolism. Interpretation: Plasma SERS could be a promising tool for the detection of ALS. The bands at 722 and 739 cm À1 , and the ratios of 635-722 cm À1 and 635-739 cm À1 could serve as potential indicator for ALS.

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by complex molecular and cytogenetic abnormalities. New approaches to predict the prognosis of AML have increasingly attracted attention. There were 98 non‐M3 AML cases and 48 healthy controls were enrolled in the current work. Clinically routine assays for cytogenetic and molecular genetic analyses were performed on the bone marrow samples of patients with AML. Meanwhile, metabolic profiling of these AML subjects was also performed on the serum samples by combining Ag nanoparticle‐based surface‐enhanced Raman spectroscopy (SERS) with proton nuclear magnetic resonance (NMR) spectroscopy. Although most of the routine biochemical test showed no significant differences between the M0–M2 and M5 groups, the metabolic profiles were significantly different either between AML subtypes or between prognostic risk subgroups. Specific SERS bands were screened to serve as potential markers for AML subtypes. The results demonstrated that the classification models for M0–M2 and M5 shared two bands (i.e., 1328 and 741 cm−1), all came from nucleic acid signals. Furthermore, Metabolic profiles provided various differential metabolites responsible for different AML subtypes, and we found altered pathways mainly included energy metabolism like glycolysis, pyruvate metabolism, and metabolisms of nucleic acid bases as well as specific amino acid metabolisms. It is concluded that integration of SERS and NMR provides the rational and could be reliable to reveal AML differentiation, and meanwhile lay the basis for experimental and clinical practice to monitor disease progression and prognostic evaluation.

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Multidrug resistance (MDR) is highly associated with poor prognosis of chronic myeloid leukemia (CML). This work aims to explore whether the laser tweezers Raman spectroscopy (LTRS) could be practical in separating adriamycin (ADR) resistance CML cells K562/ADR from its parental cells K562, and to explore the potential mechanisms. Detection of LTRS initially reflected the spectral differences caused by chemoresistance including bands assigned to carbohydrates, amino acid, protein, lipids and nucleic acid. In addition, principal components analysis (PCA) as well as the classification and regression trees (CRT) algorithms showed that the specificity and sensitivity were above 90%. Moreover, the band data-based CRT model and receiver operating characteristic (ROC) curve further determined some important bands and band intensity ratios to be reliable indexes in discriminating K562 chemoresistance status. Finally, we highlighted three metabolism pathways correlated with chemoresistance. This work demonstrates that the label-free LTRS analysis combined with multivariate statistical analyses have great potential to be a novel analytical strategy at the single-cell level for rapid evaluation the chemoresistance status of K562 cells.

Diabetic retinopathy (DR) is a common condition of diabetes, and approaches to detecting early DR using the unique characteristics of the retinal pigment epithelium-Bruch’s membrane complex (RBC) have increasingly attracted attention. A diabetic model was established in Sprague-Dawley rats via streptozocin (STZ) injection for 1 (DM1) and 6 months (DM6), confirmed by weekly blood glucose measurement. Serum and retinal tissue-based advanced glycation endproducts (AGE) levels significantly elevated in diabetic rats, and RBC was evaluated by transmission electron microscopy and Raman spectroscopy. The results showed that whole Raman spectra and all marked band intensities could respectively achieve almost equal and accurate discrimination of all animal groups, along with the determination of important molecules from the band data. Further quantitative analyses indicated series of metabolic disturbance due to hyperglycemia were involved while the body self-regulation mechanism still played a role with different effects during the disease progression. Given this, Raman spectroscopy can reliably distinguish the early characterization of DR in addition to providing intrinsic key molecules that is sensitive to identify the early disease progression.