Inside the world of chemometrics, a fundamental role is played by the experimental design. Although introduced almost a century ago (1935), it is still not widely employed by chemists and its usefulness continues to be underestimated. When asking why, the answers are often the following: it is too difficult to apply and too much experimental effort is required. Actually, a deeper knowledge on the topic could offer a different point of view. The aim of the present tutorial is to introduce the experimental design to beginners, by providing the theoretical basic principles as well as a practical guide to use the most common designs, from the experimental plan to the final optimization. Response surface methodology will be discussed, and the main terms related to model computation and statistical evaluations usually performed by software will be explained, in order to give suitable tools to properly use them.

Background: Early diagnosis of hepatocellular carcinoma (HCC) is essential towards the improvement of prognosis and patient survival. Circulating markers such as α-fetoprotein (AFP) and micro-RNAs represent useful tools but still have limitations. Identifying new markers can be fundamental to improve both diagnosis and prognosis. In this approach, we harness the potential of metabolomics and lipidomics to uncover potential signatures of HCC. Methods: A combined untargeted metabolomics and lipidomics plasma profiling of 102 HCV-positive patients was performed by HILIC and RP-UHPLC coupled to Mass Spectrometry. Biochemical parameters of liver function (AST, ALT, GGT) and liver cancer biomarkers (AFP, CA19.9 e CEA) were evaluated by standard assays. Results: HCC was characterized by an elevation of short and long-chain acylcarnitines, asymmetric dimethylarginine, methylguanine, isoleucylproline and a global reduction of lysophosphatidylcholines. A supervised PLS-DA model showed that the predictive accuracy for HCC class of metabolomics and lipidomics was superior to AFP for the test set (100.00% and 94.40% vs 55.00%). Additionally, the model was applied to HCC patients with AFP values < 20 ng/mL, and, by using only the top 20 variables selected by VIP scores achieved an Area Under Curve (AUC) performance of 0.94. Conclusion: These exploratory findings highlight how metabo-lipidomics enables the distinction of HCC from chronic HCV conditions. The identified biomarkers have high diagnostic potential and could represent a viable tool to support and assist in HCC diagnosis, including AFP-negative patients. Graphical

Background: Sodium–glucose cotransporter 2 (SGLT2) inhibitors constitute the gold standard treatment for type 2 diabetes mellitus (T2DM). Among them, empagliflozin (EMPA) has shown beneficial effects against heart failure. Because cardiovascular diseases (mainly diabetic cardiomyopathy) are the leading cause of death in diabetic patients, the use of EMPA could be, simultaneously, cardioprotective and antidiabetic, reducing the risk of death from cardiovascular causes and decreasing the risk of hospitalization for heart failure in T2DM patients. Interestingly, recent studies have shown that EMPA has positive benefits for people with and without diabetes. This finding broadens the scope of EMPA function beyond glucose regulation alone to include a more intricate metabolic process that is, in part, still unknown. Similarly, this significantly increases the number of people with heart diseases who may be eligible for EMPA treatment. Methods: This study aimed to clarify the metabolic effect of EMPA on the human myocardial cell model by using orthogonal metabolomics, lipidomics, and proteomics approaches. The untargeted and multivariate analysis mimicked the fasting blood sugar level of T2DM patients (hyperglycemia: HG) and in the average blood sugar range (normal glucose: NG), with and without the addition of EMPA. Results: Results highlighted that EMPA was able to modulate and partially restore the levels of multiple metabolites associated with cellular stress, which were dysregulated in the HG conditions, such as nicotinamide mononucleotide, glucose-6-phosphate, lactic acid, FA 22:6 as well as nucleotide sugars and purine/pyrimidines. Additionally, EMPA regulated the levels of several lipid sub-classes, in particular dihydroceramide and triacylglycerols, which tend to accumulate in HG conditions resulting in lipotoxicity. Finally, EMPA counteracted the dysregulation of endoplasmic reticulum-derived proteins involved in cellular stress management. Conclusions: These results could suggest an effect of EMPA on different metabolic routes, tending to rescue cardiomyocyte metabolic status towards a healthy phenotype. Graphical

Salivary gland tumors are relatively uncommon neoplasms that represent less than 5% of head and neck tumors, and about 90% are in the parotid gland. The wide variety of histologies and tumor characteristics makes diagnosis and treatment challenging. In the present study, Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) was used to discriminate the pathological regions of patient-derived biopsies of parotid neoplasms by metabolomic and lipidomic profiles. Fresh frozen parotid tissues were analyzed by MALDI time-of-flight (TOF) MSI, both in positive and negative ionization modes, and additional MALDI-Fourier-transform ion cyclotron resonance (FT-ICR) MSI was carried out for metabolite annotation. MALDI-TOF-MSI spatial segmentation maps with different molecular signatures were compared with the histologic annotation. To maximize the information related to specific alterations between the pathological and healthy tissues, unsupervised (principal component analysis, PCA) and supervised (partial least squares-discriminant analysis, PLS-DA) multivariate analyses were performed presenting a 95.00% accuracy in cross-validation. Glycerophospholipids significantly increased in tumor tissues, while sphingomyelins and triacylglycerols, key players in the signaling pathway and energy production, were sensibly reduced. In addition, a significant increase of amino acids and nucleotide intermediates, consistent with the bioenergetics request of tumor cells, was observed. These results underline the potential of MALDI-MSI as a complementary diagnostic tool to improve the specificity of diagnosis and monitoring of pharmacological therapies.