The discovery of new active natural products is hampered by laborious purification processes that often end up to the re-isolation of known compounds. We demonstrate here that, spectral data reflecting concentration fluctuations of components can correlate statistically with measurable dose-dependent properties on the basis of a Heterocovariance approach deconvoluting the active components structure. Variance of extract constituents was achieved through statistically meaningful collections of plants from different families, genus, and species. This fluctuation was also obtained through the fractionation of a single plant extract by separation techniques. The NMR and HRMS spectra of the extracts and fractions were recorded, as well as their ability to inhibit tyrosinase or 5-lipoxygenase enzymes. Biological activity was statistically correlated with spectral data deciphering the active compounds through the Heterocovariance approach prior to any purification. Natural products (NPs) possess significant and well-documented biological properties representing a bioactivity hotspot in the chemical space. [1] However, the great majority of existing chemodiversity remains still unexplored as only a minute fraction of biodiversity has been chemically characterised. [2] The complexity of plant extracts in terms of number, concentration levels and nature of contained metabolites renders this goal rather challenging. Traditional isolation and scale-up proce-dures are inefficient and often become a bottleneck resulting to the constant re-isolation and re-identification of known compounds. Thus, dereplication methods have been emerged aiming to accelerate and rationalize the entire discovery process. [3] Recently, there is a considerable interest by the NP scientific community to adopt metabolomics approaches introducing a more holistic concept in the analysis of complex mixtures. [4][5][6] Metabolomics have found several applications in the area of NPs by means of metabolic profiling and fingerprinting. [7][8][9] They have been successfully employed for chemotaxonomic studies exploring the proximity of different plant species, origins or organs in respect to their metabolite profile. [10] Interestingly, different metabolomics studies have contributed significantly in the quality assessment of botanical preparations enabling the monitoring of the metabolome composition. [11,12] Metabolomics studies are based on the combined application of spectroscopic techniques and multivariate statistical approaches. [13] Among these lines, specific statistical methods for the analysis of the complex spectroscopic data were developed in order to identify components of a complex mixture. The statistical total correlation spectroscopy (STOCSY) [14] can detect multiple NMR peaks from the same molecule based on their intensities multi-colinearity in a set of NMR spectra. Moreover, correlation can be achieved between MS and NMR data in statistical heterospectroscopy (SHY). [15] It has been reported recently a new approach based on MS and activit...
Objective: Although a number of familiar syndromes are associated with primary hyperparathyroidism (PHP), there is no information regarding the prevalence of PHP in other sporadic neuroendocrine diseases. The aim of this study is to investigate the prevalence of PHP in our group of patients with gastric carcinoid (GC) type 1 tumors. Methods: Twenty-six patients with biopsy-proven GC type 1 tumors were retrospectively studied. The diagnosis of PHP was suspected following elevated or high-normal serum calcium levels and elevated or inappropriate normal parathyroid hormone levels. Further tests for the localization of the hyperfunctioning parathyroid glands included neck ultrasound, 99mTc-SESTAMIBI scanning, and cervical or upper mediastinal MR imaging studies. Four control groups were also studied: two age- and sex-matched groups of individuals with (n = 49) and without (n = 34) thyroid autoimmunity and normal endoscopy of the stomach, a third group with nongastric neuroendocrine tumors (n = 68), and a fourth group with atrophic gastritis and hypergastrinemia, without gastric endocrine tumors (n = 30). Results: PHP was diagnosed in 4 (15.38%) patients with GC type 1 tumors compared to none of the 4 control groups. Three of the 4 patients with PHP were operated and proved to have a parathyroid adenoma. No statistically significant differences were observed between patients with or without PHP in mean gastrin and chromogranin A levels, number of lesions, ki-67 labeling index expression, and maximum GC type 1 tumor diameter. Conclusion: PHP seems to be relatively common, approximately 15% in the present cohort, in patients with GC type 1 tumors. PHP should be actively looked for in such patients and treated accordingly.
ObJEctIVE: Gastric neuroendocrine neoplasms type 1 (GEN type 1) are mostly localized indolent tumors, with only a minority developing lymph node or distant metastasis. Although they are usually managed conservatively, large, invasive, recurrent and grade 2 lesions may require surgical treatment. the aim of this case series is to evaluate the validity of current guidelines regarding surgical management of patients with GEN type 1. cAsEs: seven patients (5 female) with GEN type 1 underwent peri-gastric lymphadenectomy when at least one of the following criteria employed in previous guidelines was present: (i) multiple recurrent lesions, (ii) lesions with positive margins following endoscopic resection, (iii) lesions with malignant potential (deep gastric parietal wall invasion, lymph node enlargement, Ki67 proliferative index >2%), or (iv) presence of metastatic disease. Four patients met one and three two of the previously defined criteria; fifteen to thirty-six peri-gastric lymph nodes were resected. Following surgery there was no alteration in tumor staging status compared to pre-surgical staging. During a median follow-up of 34 months, all patients remain without any evidence of disease recurrence. cONcLUsION: Peri-gastric lymphadenectomy did not prove to be necessary for localized GEN type 1, neither for staging nor for therapeutical reasons. Further parameters need to be evaluated to identify the small subset of patients that will develop more aggressive disease.
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