New insight into primary hyperparathyroidism using untargeted metabolomics.

Primary Hyperparathyroidism (PHPT) is characterized by excessive parathormone (PTH) secretion and disrupted calcium homeostasis. Untargeted metabolomics offers a valuable approach to understanding the complex metabolic alterations associated with different diseases, including PHPT. Plasma untargeted metabolomics was applied to investigate the metabolic profiles of PHPT patients compared to a control group. Two complementary liquid-phase separation techniques were employed to comprehensively explore the metabolic landscape in this retrospective, single-center study. The study comprised 28 female patients diagnosed following the current guidelines of PHPT diagnosis and a group of 30 healthy females as a control group. To evaluate their association with PHPT, we identified changes in plasma metabolic profiles in patients with PHPT compared to the control group. The primary outcome measure included detecting plasma metabolites and discriminating PHPT patients from controls. The study unveiled specific metabolic imbalances that may link L-amino acids with peptic ulcer disease, gamma-glutamyls with oxidative stress, and asymmetric dimethylarginine (ADMA) with cardiovascular complications. Several metabolites, such as gamma-glutamyls, caffeine, sex hormones, carnitine, sphingosine-1-phosphate (S-1-P), and steroids, were connected with reduced bone mineral density (BMD). Metabolic profiling identified distinct metabolic patterns between patients with PHPT and healthy controls. These findings provided valuable insights into the pathophysiology of PHPT.

Imaging and Metabolic Diagnostic Methods in the Stage Assessment of Rectal Cancer.

Rectal cancer (RC) is a prevalent malignancy with significant morbidity and mortality rates. The accurate staging of RC is crucial for optimal treatment planning and patient outcomes. This review aims to summarize the current literature on imaging and metabolic diagnostic methods used in the stage assessment of RC. Various imaging modalities play a pivotal role in the initial evaluation and staging of RC. These include magnetic resonance imaging (MRI), computed tomography (CT), and endorectal ultrasound (ERUS). MRI has emerged as the gold standard for local staging due to its superior soft tissue resolution and ability to assess tumor invasion depth, lymph node involvement, and the presence of extramural vascular invasion. CT imaging provides valuable information about distant metastases and helps determine the feasibility of surgical resection. ERUS aids in assessing tumor depth, perirectal lymph nodes, and sphincter involvement. Understanding the strengths and limitations of each diagnostic modality is essential for accurate staging and treatment decisions in RC. Furthermore, the integration of multiple imaging and metabolic methods, such as PET/CT or PET/MRI, can enhance diagnostic accuracy and provide valuable prognostic information. Thus, a literature review was conducted to investigate and assess the effectiveness and accuracy of diagnostic methods, both imaging and metabolic, in the stage assessment of RC.

Exploring protein relative relations in skeletal muscle proteomic analysis for insights into insulin resistance and type 2 diabetes.

The escalating prevalence of insulin resistance (IR) and type 2 diabetes mellitus (T2D) underscores the urgent need for improved early detection techniques and effective treatment strategies. In this context, our study presents a proteomic analysis of post-exercise skeletal muscle biopsies from individuals across a spectrum of glucose metabolism states: normal, prediabetes, and T2D. This enabled the identification of significant protein relationships indicative of each specific glycemic condition. Our investigation primarily leveraged the machine learning approach, employing the white-box algorithm relative evolutionary hierarchical analysis (REHA), to explore the impact of regulated, mixed mode exercise on skeletal muscle proteome in subjects with diverse glycemic status. This method aimed to advance the diagnosis of IR and T2D and elucidate the molecular pathways involved in its development and the response to exercise. Additionally, we used proteomics-specific statistical analysis to provide a comparative perspective, highlighting the nuanced differences identified by REHA. Validation of the REHA model with a comparable external dataset further demonstrated its efficacy in distinguishing between diverse proteomic profiles. Key metrics such as accuracy and the area under the ROC curve confirmed REHA's capability to uncover novel molecular pathways and significant protein interactions, offering fresh insights into the effects of exercise on IR and T2D pathophysiology of skeletal muscle. The visualizations not only underscored significant proteins and their interactions but also showcased decision trees that effectively differentiate between various glycemic states, thereby enhancing our understanding of the biomolecular landscape of T2D.

The Influence of Lifestyle on Male Fertility in the Context of Insulin Resistance-Identification of Factors That Influence Semen Quality.

Background: Male fertility is known to have been negatively influenced by the progress of civilization. Another condition whose incidence has been on the increase for the same reason is insulin resistance (IR). In addition, men increasingly often resign from the pursuit of active forms of leisure, preferring more sedentary ones. Considering these trends, this aim of this study was to investigate the relationships between lifestyle factors, insulin resistance, and male fertility in men with and without the condition. A further aim was to select those lifestyle factors that would make it possible to predict the level of male fertility, especially when IR is concerned. Methods: This study was performed in a group of 73 participants, divided into groups based on their insulin resistance status. Their physical activity, diet, perceived stress, sleep quality, libido level, and duration of sexual abstinence were assessed on the basis of a number of parameters, including indices proposed by the authors. In addition, relevant anthropometric measurements were taken and tests related to glucose metabolism and semen quality were carried out. On the basis of these data, statistical tests were performed to establish or disprove relationships between lifestyle choices and semen quality, as measured my sperm motility. Results: The results of this study highlighted the associations between a number of parameters, i.e., micronutrient and vitamin intake, diet quality, body composition, insulin resistance, and the duration of sexual abstinence, and semen quality, as measured by sperm motility. Significantly, the presence or absence of IR was linked to male fertility. A multivariate model was developed, incorporating parameters such as the Matsuda index, vitamin intake, and sexual abstinence duration, to predict motility scores. Conclusions: This study underscores the negative impact of modern civilization's lifestyle choices on male fertility. Notably, vitamin and mineral consumption, especially from antioxidant-rich diets like the Mediterranean diet, emerged as key modifiable factors affecting fertility. Routine diagnostics for insulin resistance in fertility-related interventions is recommended. This study also highlights the importance of considering sexual abstinence duration during semen collection for accurate diagnostic results. Future research should focus on validating the proposed multivariate model and exploring the effects of lifestyle modifications, particularly vitamin supplementation, on fertility outcomes in men, especially in the context of IR.

Metabolic profiling reveals the nutraceutical effect of Gongolaria abies-marina and Rosmarinus officinalis extracts in a type 1 diabetes animal model.

Nutraceuticals have gained increasing interest, prompting the need to investigate plant extracts for their beneficial properties and potential side effects. This study aimed to assess the nutraceutical effects of environmentally clean extracts from Rosmarinus officinalis and Gongolaria abies-marina (formerly Cystoseira abies-marina (Phaeophyceae)) on the metabolic profile of streptozotocin-induced diabetic rats. We conducted untargeted LC-QTOF-MS metabolic profiling on six groups of rats: three diabetic groups receiving either a placebo, R. officinalis, or G. abies-marina extracts, and three corresponding control groups. The metabolic analysis revealed significant alterations in the levels of various glycerophospholipids, sterol lipids, and fatty acyls. Both extracts influenced the metabolic profile, partially mitigating diabetes-induced changes. Notably, G. abies-marina extract had a more pronounced impact on the animals' metabolic profiles compared to R. officinalis. In conclusion, our findings suggest that environmentally clean extracts from R. officinalis and G. abies-marina possess nutraceutical potential, as they were able to modulate the metabolic profile in streptozotocin-induced diabetic rats. G. abies-marina extract exhibited a more substantial effect on metabolic alterations induced by diabetes compared to R. officinalis. These results warrant further exploration of these plant extracts for their potential in managing diabetes-related metabolic disturbances.

Patient classification and attribute assessment based on machine learning techniques in the qualification process for surgical treatment of adrenal tumours.

Adrenal gland incidentaloma is frequently identified through computed tomography and poses a common clinical challenge. Only selected cases require surgical intervention. The primary aim of this study was to compare the effectiveness of selected machine learning (ML) techniques in proper qualifying patients for adrenalectomy and to identify the most accurate algorithm, providing a valuable tool for doctors to simplify their therapeutic decisions. The secondary aim was to assess the significance of attributes for classification accuracy. In total, clinical data were collected from 33 patients who underwent adrenalectomy. Histopathological assessments confirmed the proper selection of 21 patients for surgical intervention according to the guidelines, with accuracy reaching 64%. Statistical analysis showed that Supported Vector Machines (linear) were significantly better than the baseline (p < 0.05), with accuracy reaching 91%, and imaging features of the tumour were found to be the most crucial attributes. In summarise, ML methods may be helpful in qualifying patients for adrenalectomy.

First insight about the ability of specific glycerophospholipids to discriminate non-small cell lung cancer subtypes.

Introduction: Discrimination between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) subtypes in non-small cell lung cancer (NSCLC) patients is a significant challenge in oncology. Lipidomics analysis provides a promising approach for this differentiation. Methods: In an accompanying paper, we explored oxPCs levels in a cohort of 200 NSCLC patients. In this research, we utilized liquid chromatography coupled with mass spectrometry (LC-MS) to analyze the lipidomics profile of matching tissue and plasma samples from 25 NSCLC patients, comprising 11 ADC and 14 SCC cases. This study builds upon our previous findings, which highlighted the elevation of oxidised phosphatidylcholines (oxPCs) in NSCLC patients. Results: We identified eight lipid biomarkers that effectively differentiate between ADC and SCC subtypes using an untargeted approach. Notably, we observed a significant increase in plasma LPA 20:4, LPA 18:1, and LPA 18:2 levels in the ADC group compared to the SCC group. Conversely, tumour PC 16:0/18:2, PC 16:0/4:0; CHO, and plasma PC 16:0/18:2; OH, PC 18:0/20:4; OH, PC 16:0/20:4; OOH levels were significantly higher in the ADC group. Discussion: Our study is the first to report that plasma LPA levels can distinguish between ADC and SCC patients in NSCLC, suggesting a potential role for LPAs in NSCLC subtyping. This finding warrants further investigation into the mechanisms underlying these differences and their clinical implications.

Assessing the impact of body composition, metabolic and oxidative stress parameters on insulin resistance as a prognostic marker for reactive hypoglycemia: a cross-sectional study in overweight, obese, and normal weight individuals.

Oxidative stress (OS) plays a pivotal role in the pathogenesis of insulin resistance (IR), particularly in its association with obesity. This study evaluate both the diagnostic and clinical significance of assessing oxidative status in patients affected by overweight and obesity displaying IR, especially with reactive hypoglycemic episodes (RH). A comprehensive examination of OS biomarkers was carried out, encompassing measurements of total oxidative capacity (TOC) and total antioxidant capacity (TAC). Our analysis results reveal noteworthy connections between OS levels and the severity of IR in overweight and obese patients. Moreover, in the study, we demonstrated the diagnostic utility of serum concentrations of TAC and TOC as indicators of the risk of RH, the occurrence of which, even at the stage of overweight, may be associated with increased OS and further development of obesity. Our findings imply that the evaluation of oxidative status could serve as a crucial diagnostic and prognostic tool for patients observed with IR and overweight and obesity. In conclusion, our study underscores the potential utility of assessing oxidative status in the context of IR and highlights the possibility of identifying novel therapeutic targets for the treatment of overweight and obese patients.

The BDNF protein is associated with glucose homeostasis and food intake in carriers of common BDNF gene variants.

CONTEXT: The brain-derived neurotrophic factor (BDNF) concentrations may differ between BDNF gene genotype carriers. These changes occur in individuals with metabolic and mental disorders. OBJECTIVE: The aim of this study was to assess the associations of glucose homeostasis parameters and the frequency of food consumption with BDNF protein concentrations based on the BDNF single-nucleotide polymorphisms (SNPs). METHODS: Among the 439 participants, some common rs10835211 BDNF gene variants were analyzed. We evaluated BDNF concentration, fasting glucose and insulin concentrations and during oral glucose tolerance tests. Anthropometric measurements, body composition, and body fat distribution were assessed, and 3-day food intake diary and food frequency questionnaire were completed. RESULTS: We noticed significant differences in concentration of BDNF between AA and AG genotype rs10835211 carriers (p=0.018). The group of AA genotype holders were older, and positive correlation was found between age and BDNF in the whole study population (p=0.012) and in the GG genotype carriers (p=0.023). Moreover, BDNF protein correlated with fasting insulin (p=0.015), HOMA-IR (p=0.031), HOMA-B (p=0.010) , and the VAT/SAT ratio (p=0.026) in the GG genotype individuals. Presence of the GG genotype was negatively correlated with nut and seed (p=0.047), lean pork consumption (p=0.015) and the BDNF protein. Moreover, we observed correlations between the frequency of chicken (p=0.028), pasta (p=0.033) and sweet food intake (p=0.040) and BDNF concentration in the general population. Among carriers of the AA genotype, we observed a positive correlation between the consumption of rice (p=0.048) and sweet food (p=0.028) and the BDNF protein level. CONCLUSION: Peripheral BDNF may be associated with visceral fat content and insulin concentrations in the GG genotype carriers and may depend on variable food intake, which warrants further investigation.

Identification of MicroRNA Profiles in Fetal Spina Bifida: The Role in Pathomechanism and Diagnostic Significance.

Distinct miRNA expression patterns may reflect anomalies related to fetal congenital malformations such as spinal bifida (SB). The aim of this preliminary study was to determine the maternal miRNA expression profile of women carrying fetuses with SB. Therefore, six women carrying fetuses with SB and twenty women with euploid healthy fetuses were enrolled in this study. Using NanoString technology, we evaluated the expression level of 798 miRNAs in both plasma and amniotic fluid samples. A downregulation of miR-1253, miR-1290, miR-194-5p, miR-302d-3p, miR-3144-3p, miR-4536-5p, miR-548aa + miR-548t-3p, miR-548ar-5p, miR-548n, miR-590-5p, miR-612, miR-627-5p, miR-644a, and miR-122-5p, and an upregulation of miR-320e, let-7b-5p, miR-23a-3p, miR-873-3p, and miR-30d-5p were identified in maternal amniotic fluid samples in SB when compared to the control group. The target genes of these miRNAs play a predominant role in regulating the synthesis of several biological compounds related to signaling pathways such as those regulating the pluripotency of stem cells. Moreover, the maternal plasma expression of miR-320e was increased in pregnancies with SB, and this marker could serve as a valuable non-invasive screening tool. Our results highlight the SB-specific miRNA signature and the differentially expressed miRNAs that may be involved in SB pathogenesis. Our findings emphasize the role of miRNA as a predictive factor that could potentially be useful in prenatal genetic screening for SB.

Circulating serum miR-362-3p and miR-6721-5p as potential biomarkers for classification patients with adult-type diffuse glioma.

According to the fifth edition of the WHO Classification of Tumours of the Central Nervous System (CNS) published in 2021, grade 4 gliomas classification includes IDH-mutant astrocytomas and wild-type IDH glioblastomas. Unfortunately, despite precision oncology development, the prognosis for patients with grade 4 glioma remains poor, indicating an urgent need for better diagnostic and therapeutic strategies. Circulating miRNAs besides being important regulators of cancer development could serve as promising diagnostic biomarkers for patients with grade 4 glioma. Here, we propose a two-miRNA miR-362-3p and miR-6721-5p screening signature for serum for non-invasive classification of identified glioma cases into the highest-grade 4 and lower-grade gliomas. A total of 102 samples were included in this study, comprising 78 grade 4 glioma cases and 24 grade 2-3 glioma subjects. Using the NanoString platform, seven miRNAs were identified as differentially expressed (DE), which was subsequently confirmed via RT-qPCR analysis. Next, numerous combinations of DE miRNAs were employed to develop classification models. The dual panel of miR-362-3p and miR-6721-5p displayed the highest diagnostic value to differentiate grade 4 patients and lower grade cases with an AUC of 0.867. Additionally, this signature also had a high AUC = 0.854 in the verification cohorts by RT-qPCR and an AUC = 0.842 using external data from the GEO public database. The functional annotation analyses of predicted DE miRNA target genes showed their primary involvement in the STAT3 and HIF-1 signalling pathways and the signalling pathway of pluripotency of stem cells and glioblastoma-related pathways. For additional exploration of miRNA expression patterns correlated with glioma, we performed the Weighted Gene-Co Expression Network Analysis (WGCNA). We showed that the modules most associated with glioma grade contained as many as six DE miRNAs. In conclusion, this study presents the first evidence of serum miRNA expression profiling in adult-type diffuse glioma using a classification based on the WHO 2021 guidelines. We expect that the discovered dual miR-362-3p and miR-6721-5p signatures have the potential to be utilised for grading gliomas in clinical applications.

imputomics: web server and R package for missing values imputation in metabolomics data.

MOTIVATION: Missing values are commonly observed in metabolomics data from mass spectrometry. Imputing them is crucial because it assures data completeness, increases the statistical power of analyses, prevents inaccurate results, and improves the quality of exploratory analysis, statistical modeling, and machine learning. Numerous Missing Value Imputation Algorithms (MVIAs) employ heuristics or statistical models to replace missing information with estimates. In the context of metabolomics data, we identified 52 MVIAs implemented across 70 R functions. Nevertheless, the usage of those 52 established methods poses challenges due to package dependency issues, lack of documentation, and their instability. RESULTS: Our R package, 'imputomics', provides a convenient wrapper around 41 (plus random imputation as a baseline model) out of 52 MVIAs in the form of a command-line tool and a web application. In addition, we propose a novel functionality for selecting MVIAs recommended for metabolomics data with the best performance or execution time. AVAILABILITY AND IMPLEMENTATION: 'imputomics' is freely available as an R package (github.com/BioGenies/imputomics) and a Shiny web application (biogenies.info/imputomics-ws). The documentation is available at biogenies.info/imputomics.

Examining the clinical relevance of metformin as an antioxidant intervention.

In physiological concentrations, reactive oxygen species play a vital role in regulating cell signaling and gene expression. Nevertheless, oxidative stress is implicated in the pathogenesis of numerous diseases and can inflict damage on diverse cell types and tissues. Thus, understanding the factors that mitigate the deleterious effects of oxidative stress is imperative for identifying new therapeutic targets. In light of the absence of direct treatment recommendations for reducing oxidative stress, there is a continuing need for fundamental research that utilizes innovative therapeutic approaches. Metformin, known for its multifaceted beneficial properties, is acknowledged for its ability to counteract the adverse effects of increased oxidative stress at both molecular and cellular levels. In this review, we delve into recent insights regarding metformin's antioxidant attributes, aiming to expand its clinical applicability. Our review proposes that metformin holds promise as a potential adjunctive therapy for various diseases, given its modulation of oxidative stress characteristics and regulation of diverse metabolic pathways. These pathways include lipid metabolism, hormone synthesis, and immunological responses, all of which may experience dysregulation in disease states, contributing to increased oxidative stress. Furthermore, our review introduces potential novel metformin-based interventions that may merit consideration in future research. Nevertheless, the necessity for clinical trials involving this drug remains imperative, as they are essential for establishing therapeutic dosages and addressing challenges associated with dose-dependent effects.

Enhancing Angioinvasion Assessment in Papillary Thyroid Cancer Via a Biomarker Panel Involving TAC, 8-OHdG, and Sortilin.

CONTEXT: Papillary thyroid cancer (PTC) aggressiveness and metastatic potential are closely associated with angioinvasion. Identifying angioinvasion accurately is imperative for treatment planning and prognosis. OBJECTIVE: This study explores serum biomarkers, including 8-hydroxydeoxyguanosine (8-OHdG) and oxidative status markers (total oxidative capacity, total antioxidant capacity [TAC], and sortilin), as potential indicators of angioinvasion in PTC. DESIGN: A cross-sectional study involving 50 angioinvasive patients with PTC (study group) and 30 patients with PTC with low-risk features (reference group). Serum levels of biomarkers were analyzed to determine their association with angioinvasion. SETTING: Patients were recruited from Department of Endocrinology, Diabetology, and Internal Diseases, Medical University of Bialystok, Poland, ensuring representation from a diverse clinical context. PATIENTS OR OTHER PARTICIPANTS: Participants included patients with PTC, with 50 in the study group and 30 in the reference group. Selection criteria, matching characteristics, and participant completion rates were duly recorded. INTERVENTION(S): Serum biomarkers were measured to evaluate their association with PTC angioinvasion. MAIN OUTCOME MEASURE(S): Primary outcome measures included serum levels of 8-OHdG, total oxidative capacity, TAC, and sortilin. RESULTS: Serum levels of 8-OHdG and sortilin were significantly elevated in angioinvasive PTC, whereas TAC showed a notable decrease (all P < .01). A regression panel combining TAC, 8-OHdG, and sortilin demonstrated a high area under the curve value (0.963) for angioinvasion discernment. CONCLUSION: Measuring TAC, 8-OHdG, and sortilin levels may serve as potential biomarkers for identifying angioinvasion in PTC. The combined assessment of these biomarkers enhances angioinvasion discernment, aiding risk stratification and personalized treatment decisions. Further validation studies are required before integrating these biomarkers into routine clinical practice. The study adheres to the provided structure, providing concise and supported conclusions based on the results.

Exploring the clinical utility of DPP-IV and SGLT2 inhibitors in papillary thyroid cancer: a literature review.

In the realm of clinical management, Papillary Thyroid Cancer (PTC) stands out as a prevalent thyroid malignancy, characterized by significant metabolic challenges, particularly in the context of carbohydrate metabolism. Recent studies have unveiled promising applications of Dipeptidyl Peptidase-IV (DPP-IV) and Sodium-Glucose Cotransporter 2 (SGLT2) inhibitors, which are conventionally employed in the treatment of type 2 diabetes mellitus (T2DM), as potential adjuncts in anticancer therapy. DPP-IV and SGLT2 inhibitors can be imply to counteract the Warburg effect in cancer, with a specific focus on PTC, owing to their potential metabolic advantages and their influence on the tumor microenvironment, achieved by imposing restrictions on glucose accessibility. Consequently, a comprehensive review has been undertaken, involving meticulous examination of the existing body of evidence pertaining to the utilization of DPP-IV and SGLT2 inhibitors in the context of PTC. The mechanisms of action inherent to these inhibitors have been thoroughly explored, drawing upon insights derived from preclinical investigations. Furthermore, this review initiates discussions concerning the implications for future research directions and the formulation of innovative therapeutic strategies for PTC. As the intricate interplay between carbohydrate metabolism, the Warburg effect, and cancer progression garners increasing attention, attaining a comprehensive understanding of the roles played by DPP-IV and SGLT2 inhibitors in PTC management may serve as the cornerstone for novel approaches aimed at enhancing patient care and broadening the spectrum of available therapeutic modalities.

Multiple sclerosis susceptibility may be associated with the coding rs20541 (R130Q) IL-13 gene polymorphism in the Polish population.

Some of the multiple autoimmune diseases have been already associated with IL-13 single-nucleotide polymorphisms (SNPs). However, there are only few studies regarding multiple sclerosis (MS) risk and IL-13 rs20541 (R130Q) polymorphism, and their results are conflicting. Therefore, the aim of our study was to investigate the frequency of the IL-13 gene rs20541 (R130Q) polymorphism in MS participants and its association with MS clinical subsets in the Polish population. We conducted a case‒control study including 94 relapsing remitting MS patients and 160 healthy volunteers. We genotyped the rs20541 polymorphism in the IL-13 gene and analysed the genotype frequency, age of MS onset and clinical condition (EDSS values) of the MS participants. Fisher's exact test was used for statistical analysis, and the log-linear model was applied to test for associations. Allele A, as well as the AA and AG genotypes, was observed to be significantly more common in the MS subjects. The OR (odds ratio) for the A compared to the G allele was 1.71 (1.14-2.56), whereas OR 2.33 (0.86-6.26) and OR 1.92 (1.11-3.30) were obtained for the AA and AG genotypes, respectively. We did not identify any significant associations of the studied IL-13 SNP with the investigated clinical parameters of the MS participants. Our results suggest that the rs20541 polymorphism in the IL-13 gene may play an important role in MS predisposition but not in investigated clinical parameters in MS subjects of the Polish population.

Exploring the clinical utility of angioinvasion markers in papillary thyroid cancer: a literature review.

Papillary thyroid cancer (PTC) is the most common type of thyroid cancer, and angioinvasion, the invasion of blood vessels by cancer cells, is a crucial pathological feature associated with disease progression and poor prognosis. Thus, a comprehensive search of scientific databases was conducted to identify relevant studies investigating angioinvasion markers in PTC. The selected studies were reviewed and analyzed to assess the clinical significance and potential utility of these markers in predicting angioinvasion and guiding treatment decisions. Numerous studies have investigated various markers associated with angioinvasion in PTC, including oxidative stress, vascular endothelial growth factor (VEGF), matrix metalloproteinases (MMPs), and other angiogenic factors. The results indicate that increased expression of these markers is correlated with the presence and extent of angioinvasion in PTC. Moreover, some studies suggest that these markers can serve as prognostic indicators and guide therapeutic strategies, such as selecting patients for more aggressive treatment approaches or targeted therapies. The findings from the reviewed literature highlight the potential clinical utility of angioinvasion markers in PTC. The identification and validation of reliable markers can aid in assessing the risk of angioinvasion, predicting disease progression, and optimizing treatment decisions for patients with PTC. However, further research and validation on larger patient cohorts are necessary to establish the robustness and generalizability of these markers in clinical practice.

Metabolomic profile of acute myeloid leukaemia parallels of prognosis and response to therapy.

The heterogeneity of acute myeloid leukemia (AML), a complex hematological malignancy, is caused by mutations in myeloid cells affecting their differentiation and proliferation. Thus, various cytogenetic alterations in AML cells may be characterized by a unique metabolome and require different treatment approaches. In this study, we performed untargeted metabolomics to assess metabolomics differences between AML patients and healthy controls, AML patients with different treatment outcomes, AML patients in different risk groups based on the 2017 European LeukemiaNet (ELN) recommendations for the diagnosis and management of AML, AML patients with and without FLT3-ITD mutation, and a comparison between patients with FLT3-ITD, CBF-AML (Core binding factor acute myelogenous leukemia), and MLL AML (mixed-lineage leukemia gene) in comparison to control subjects. Analyses were performed in serum samples using liquid chromatography coupled with mass spectrometry (LC-MS). The obtained metabolomics profiles exhibited many alterations in glycerophospholipid and sphingolipid metabolism and allowed us to propose biomarkers based on each of the above assessments as an aid for diagnosis and eventual classification, allowing physicians to choose the best-suited treatment approach. These results highlight the application of LC-MS-based metabolomics of serum samples as an aid in diagnostics and a potential minimally invasive prognostic tool for identifying various cytogenetic and treatment outcomes of AML.

Glioma and post-translational modifications: A complex relationship.

Post-translational modifications (PTMs) are common covalent processes in biochemical pathways that alter protein function and activity. These modifications occur through proteolytic cleavage or attachment of modifying groups, such as phosphoryl, methyl, glycosyl, or acetyl groups, with one or more amino acid residues of a single protein. Some PTMs also present crosstalk abilities that affect both protein functionality and structure, creating new proteoforms. Any alteration in organism homeostasis may be a cancer hallmark. Cataloging PTMs and consequently, emerging proteoforms, present new therapeutic targets, approaches, and opportunities to discover additional discriminatory biomarkers in disease diagnostics. In this review, we focus on experimentally confirmed PTMs and their potential crosstalk in glioma research to introduce new opportunities for this tumor type, which emerge within the PTMomics area.