A new group of potent histone deacetylase inhibitors (HDACis) capable of inhibiting cell growth and affecting cell-cycle progression in Tohoku Hospital Pediatrics-1 (THP-1) monocytic leukaemia cells was synthesized. The inhibitors belong to a series of hydroxamic acid derivatives. We designed and synthesized a series of 22 N-hydroxycinnamamide derivatives, out of which 20 are new compounds. These compounds contain various substituted anilides as the surface recognition moiety (SRM), a p-hydroxycinnamate linker, and hydroxamic acids as the zinc-binding group (ZBG). The whole series of synthesized hydroxamic acids inhibited THP-1 cell proliferation. Compounds 7d and 7p, which belong to the category of derivatives with the most potent antiproliferative properties, exert a similar effect on cell-cycle progression as vorinostat and induce apoptosis in THP-1 cells. Furthermore, compounds 7d and 7p were demonstrated to inhibit HDAC class I and II in THP-1 cells with comparable potency to vorinostat and increase acetylation of histones H2a, H2b, H3, and H4. Molecular modelling was used to predict the probable binding mode of the studied HDACis in class I and II histone deacetylases in terms of Zn2+ ion chelation by the hydroxamate group.
- MeSH
- Apoptosis * drug effects MeSH
- Cell Cycle drug effects MeSH
- Histone Deacetylases metabolism MeSH
- Histone Deacetylase Inhibitors * pharmacology chemical synthesis chemistry MeSH
- Hydroxamic Acids * pharmacology chemical synthesis chemistry MeSH
- Coumaric Acids * pharmacology chemistry chemical synthesis MeSH
- Humans MeSH
- Molecular Structure MeSH
- Cell Line, Tumor MeSH
- Cell Proliferation drug effects MeSH
- Antineoplastic Agents * pharmacology chemical synthesis chemistry MeSH
- Drug Screening Assays, Antitumor MeSH
- Molecular Docking Simulation MeSH
- THP-1 Cells MeSH
- Dose-Response Relationship, Drug MeSH
- Structure-Activity Relationship MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Staufferov syndróm je zriedkavý paraneoplastický syndróm klasicky spojený s renálnym svetlobunkovým karcinómom (clear cell renal carninoma, ccRCC), raritne aj inými malignitami. Ide o ochorenie nejasnej patofyziológie charakterizovaný reverzibilným anikterickým, zriedkavo ikterickým, zvýšením pečeňových enzýmov, sedimentácie, trombocytózou, predĺžením aktivovaného parciálneho tromboplastínového času (activated partial thromboplastin time, aPTT) a hepatosplenomegáliou pri absencii hepatobiliárnej obštrukcie. Preto je dôležité vziať do úvahy pri nevysvetliteľnej cholestáze pri absencii obštrukcie (napr. metastatickej) v pečeni Staufferov syndróm v diferenciálnej diagnostike. To môže umožniť včasné rozpoznanie a liečbu okultnej malignity. Po dosiahnutí remisie sa laboratórny nález parciálne alebo úplne upravuje. Kazuistika popisuje prípad pacientky s renálnym zlyhaním, autoimunitnou hemolytickou anémiou a nevysvetliteľnou cholestázou, ktorá môže byť vysvetlená Staufferovým syndrómom. Totiž pacientka exitovala a pri pitve sa zistil karcinóm močovodu.
Stauffer syndrome is a rare paraneoplastic syndrome classically associated with clear cell renal carcinoma, rarely with other malignancies. It is a disease of unclear pathophysiology characterized by reversible anicteric, rarely icteric, elevation of liver enzymes, sedimentation, thrombocytosis, prolongation of activated partial thromboplastin time and hepatosplenomegaly in the absence of hepatobiliary obstruction. Therefore, it is important to consider Stauffer syndrome in the differential diagnosis for unexplained cholestasis in the absence of obstruction (e.g. metastatic) in the liver. This may allow early recognition and treatment of occult malignancy. After achieving remission, the laboratory findings are partially or completely corrected. The case report describes a patient with renal failure, autoimmune hemolytic anemia and unexplained cholestasis, which can be explained by Stauffer syndrome. Namely, the patient exited and during the autopsy, carcinoma of the ureter was found.
- Keywords
- Staufferův syndrom,
- MeSH
- Anemia, Hemolytic, Autoimmune etiology MeSH
- Cholestasis, Intrahepatic etiology MeSH
- Middle Aged MeSH
- Humans MeSH
- Ureteral Neoplasms * diagnosis complications MeSH
- Autopsy MeSH
- Renal Insufficiency * etiology MeSH
- Death MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Female MeSH
- Publication type
- Case Reports MeSH
INTRODUCTION: The immunosuppressive roles of galectin-3 (Gal-3) in carcinogenesis make this lectin an attractive target for pharmacological inhibition in immunotherapy. Although current clinical immunotherapies appear promising in the treatment of solid tumors, their efficacy is significantly weakened by the hostile immunosuppressive tumor microenvironment (TME). Gal-3, a prominent TME modulator, efficiently subverts the elimination of cancer, either directly by inducing apoptosis of immune cells or indirectly by binding essential effector molecules, such as interferon-gamma (IFNγ). METHODS: N-(2-Hydroxypropyl)methacrylamide (HPMA)-based glycopolymers bearing poly-N-acetyllactosamine-derived tetrasaccharide ligands of Gal-3 were designed, synthesized, and characterized using high-performance liquid chromatography, dynamic light scattering, UV-Vis spectrophotometry, gel permeation chromatography, nuclear magnetic resonance, high-resolution mass spectrometry and CCK-8 assay for evaluation of glycopolymer non-toxicity. Pro-immunogenic effects of purified glycopolymers were tested by apoptotic assay using flow cytometry, competitive ELISA, and in vitro cell-free INFγ-based assay. RESULTS: All tested glycopolymers completely inhibited Gal-3-induced apoptosis of monocytes/macrophages, of which the M1 subtype is responsible for eliminating cancer cells during immunotherapy. Moreover, the glycopolymers suppressed Gal-3-induced capture of glycosylated IFNγ by competitive inhibition to Gal-3 carbohydrate recognition domain (CRD), which enables further inherent biological activities of this effector, such as differentiation of monocytes into M1 macrophages and repolarization of M2-macrophages to the M1 state. CONCLUSION: The prepared glycopolymers are promising inhibitors of Gal-3 and may serve as important supportive anti-cancer nanosystems enabling the infiltration of proinflammatory macrophages and the reprogramming of unwanted M2 macrophages into the M1 subtype.
- MeSH
- Acrylamides chemistry pharmacology MeSH
- Apoptosis drug effects MeSH
- Galectin 3 * antagonists & inhibitors MeSH
- Galectins MeSH
- Interferon-gamma * metabolism MeSH
- Blood Proteins MeSH
- Humans MeSH
- Macrophages drug effects MeSH
- Monocytes * drug effects MeSH
- Tumor Microenvironment drug effects MeSH
- Polymers * chemistry pharmacology MeSH
- Antineoplastic Agents * pharmacology chemistry MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Background: Activities of Daily Living (ADLs) are essential tasks performed at home and used in healthcare to monitor sedentary behavior, track rehabilitation therapy, and monitor chronic obstructive pulmonary disease. The Barthel Index, used by healthcare professionals, has limitations due to its subjectivity. Human activity recognition (HAR) is a more accurate method using Information and Communication Technologies (ICTs) to assess ADLs more accurately. This work aims to create a singular, adaptable, and heterogeneous ADL dataset that integrates information from various sources, ensuring a rich representation of different individuals and environments. Methods: A literature review was conducted in Scopus, the University of California Irvine (UCI) Machine Learning Repository, Google Dataset Search, and the University of Cauca Repository to obtain datasets related to ADLs. Inclusion criteria were defined, and a list of dataset characteristics was made to integrate multiple datasets. Twenty-nine datasets were identified, including data from various accelerometers, gyroscopes, inclinometers, and heart rate monitors. These datasets were classified and analyzed from the review. Tasks such as dataset selection, categorization, analysis, cleaning, normalization, and data integration were performed. Results: The resulting unified dataset contained 238,990 samples, 56 activities, and 52 columns. The integrated dataset features a wealth of information from diverse individuals and environments, improving its adaptability for various applications. Conclusions: In particular, it can be used in various data science projects related to ADL and HAR, and due to the integration of diverse data sources, it is potentially useful in addressing bias in and improving the generalizability of machine learning models.
- Publication type
- Journal Article MeSH
Background/Objectives: Activities of Daily Living (ADLs) are crucial for assessing an individual's autonomy, encompassing tasks such as eating, dressing, and moving around, among others. Predicting these activities is part of health monitoring, elderly care, and intelligent systems, improving quality of life, and facilitating early dependency detection, all of which are relevant components of personalized health and social care. However, the automatic classification of ADLs from sensor data remains challenging due to high variability in human behavior, sensor noise, and discrepancies in data acquisition protocols. These challenges limit the accuracy and applicability of existing solutions. This study details the modeling and evaluation of real-time ADL classification models based on batch learning (BL) and stream learning (SL) algorithms. Methods: The methodology followed is the Cross-Industry Standard Process for Data Mining (CRISP-DM). The models were trained with a comprehensive dataset integrating 23 ADL-centric datasets using accelerometers and gyroscopes data. The data were preprocessed by applying normalization and sampling rate unification techniques, and finally, relevant sensor locations on the body were selected. Results: After cleaning and debugging, a final dataset was generated, containing 238,990 samples, 56 activities, and 52 columns. The study compared models trained with BL and SL algorithms, evaluating their performance under various classification scenarios using accuracy, area under the curve (AUC), and F1-score metrics. Finally, a mobile application was developed to classify ADLs in real time (feeding data from a dataset). Conclusions: The outcome of this study can be used in various data science projects related to ADL and Human activity recognition (HAR), and due to the integration of diverse data sources, it is potentially useful to address bias and improve generalizability in Machine Learning models. The principal advantage of online learning algorithms is dynamically adapting to data changes, representing a significant advance in personal autonomy and health care monitoring.
- Publication type
- Journal Article MeSH
INTRODUCTION: Idiopathic inflammatory myopathies (IIM) are a group of rare systemic autoimmune diseases characterized by muscle weakness, histopathological signs of inflammation in muscle tissues, elevated serum levels of muscle-associated enzymes, inflammatory mononuclear cells infiltrating muscle tissue and progressive symmetrical proximal muscle weakness. The current view is that they begin by immune activation in response to environmental factors in genetically predisposed people, but despite the number of investigations into the genetic background, the detailed etiopathogenesis remains unknown. The aim of this study was to examine the relationship between select polymorphisms located in the human major histocompatibility complex (MHC) and IIM. These genetic markers may take part in the onset of the autoimmune process, and their identification could aid in the diagnosis and classification of IIM subtypes. MATERIAL AND METHODS: One hundred and fifty-two adult patients suffering from IIM (82 dermatomyositis and 70 polymyositis) and 150 healthy controls were analyzed in this study. All were from the Czech Republic. SNPs of the HSP70 genes HSPA1A (rs1008438, rs1043618), HSPA1B (rs1061581, rs539689, pentanucleotide tandem duplication rs9281590) and HSPA1L (rs2227956) were analyzed in all patients and controls. For the detection of HLA polymorphisms, we used commercial kits from CareDx. Haplotypes were created using Arlequin 3.5. RESULTS: Our results confirm the association of IIM with the ancestral haplotype HLA-DRB1*03-DQB1*02. The most important MHC haplotype related to IIM and covering all polymorphisms was HLA-DQB1*02-DRB1*03:01-T-C-C-G-C-INS (p < 0.05, OR = 1.90, 95% CI: 1.15-3.13). This haplotype is associated with the risk of IIM development. CONCLUSIONS: Our results show that polymorphism typing within the MHC might be a very strong tool for recognition of IIM.
- Publication type
- Journal Article MeSH
Advanced metastatic colorectal cancer (CRC) with deficient DNA mismatch repair (MMR-d), or immune-hot CRCs, show significantly improved clinical outcomes compared to MMR-proficient (MMR-p), or immune-cold CRCs. While the prior represents about 5% of all CRCs, the latter represent 95% and are characterized by low immunogenicity. This study investigates bis-diethyldithiocarbamate (CuET), a novel anticancer compound, and its impact on the colorectal cancer tumor microenvironment (TME). CuET is shown to convert immunologically inactive tumors into hotbeds of antitumor immune responses, marked by increased lymphocyte infiltration, heightened cytotoxicity of natural killer (NK) and T cells, and enhanced non-self recognition by lymphocytes. The potent anticancer cytotoxicity and in vivo safety and efficacy of CuET are established. In summary, CuET transforms the colorectal cancer TME, bolstering NK and T cell cytotoxicity and refining tumor cell recognition through non-classical activation via the NKG2D/NKG2DL axis. This study unveils a novel mechanism of action for CuET: a potent immunomodulator capable of turning cold tumors hot.
- MeSH
- Killer Cells, Natural immunology drug effects metabolism MeSH
- Ditiocarb * pharmacology MeSH
- Colorectal Neoplasms * drug therapy immunology metabolism pathology MeSH
- NK Cell Lectin-Like Receptor Subfamily K * metabolism MeSH
- Humans MeSH
- Copper MeSH
- Mice MeSH
- Cell Line, Tumor MeSH
- Tumor Microenvironment * drug effects immunology MeSH
- Antineoplastic Agents pharmacology MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Mice MeSH
- Female MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
Methoxphenidine (MXP) is classified as a new psychoactive substance that has recently emerged on the illicit drug market. Understanding the pharmacological and behavioural profiles of newly emerging drugs is essential for a better understanding of their psychotropic effects and potential toxicity. Therefore, in this study, we investigated a broad range of effects of acute MXP administration: pharmacokinetics in the brain and serum; behaviour (open field and prepulse inhibition), systemic toxicity (lethal dose; LD 50), and histopathology changes in parenchymal organs of Wistar rats. MXP rapidly crossed the blood-brain barrier, reaching peak median concentrations in both serum and brain 30 min post-administration, followed by an elimination phase with a half-life of 2.15 h. Locomotor activity in the open field test displayed a dose-response effect at low to moderate doses (10-20 mg/kg MXP). At higher doses (40 mg/kg), locomotor activity decreased. All doses of MXP significantly disrupted prepulse inhibition and the effect was present during the onset of its action as well as 60 min after treatment. Additionally, MXP demonstrated moderate acute toxicity, with an estimated LD50 of 500 mg/kg when administered subcutaneously. In summary, MXP exhibited a profile similar to typical dissociative anesthetics, producing stimulant and anxiogenic effects at lower doses, sedative effects at higher doses, and disrupting sensorimotor gating. The accumulation of MXP in brain tissue is likely to contribute to acute intoxication in humans, potentially leading to negative experiences. Our findings highlight the potentially dangerous effects of recreational MXP use and underscore the risks of inducing serious adverse health outcomes.
- MeSH
- Behavior, Animal drug effects MeSH
- Rats MeSH
- Lethal Dose 50 MeSH
- Brain drug effects metabolism MeSH
- Piperidines pharmacokinetics pharmacology MeSH
- Motor Activity drug effects MeSH
- Rats, Wistar * MeSH
- Prepulse Inhibition drug effects MeSH
- Open Field Test drug effects MeSH
- Dose-Response Relationship, Drug * MeSH
- Animals MeSH
- Check Tag
- Rats MeSH
- Male MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
Cardiorespiratory signals have long been treated as "noise" in functional magnetic resonance imaging (fMRI) research, with the goal of minimizing their impact to isolate neural activity. However, there is a growing recognition that these signals, once seen as confounding variables, provide valuable insights into brain function and overall health. This shift reflects the dynamic interaction between the cardiovascular, respiratory, and neural systems, which together support brain activity. In this review, we explore the role of cardiorespiratory dynamics-such as heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and changes in blood flow, oxygenation, and carbon dioxide levels-embedded within fMRI signals. These physiological signals reflect critical aspects of neurovascular coupling and are influenced by factors such as physiological stress, breathing patterns, and age-related changes. We also discuss the complexities of distinguishing these signals from neuronal activity in fMRI data, given their significant contribution to signal variability and interactions with cerebrospinal fluid (CSF). Recognizing the influence of these cardiorespiratory dynamics is crucial for improving the interpretation of fMRI data, shedding light on heart-brain and respiratory-brain connections, and enhancing our understanding of circulation, oxygen delivery, and waste elimination within the brain.
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a respiratory virus that emerged in late 2019 and rapidly spread worldwide, causing the COVID-19 pandemic. The spike glycoprotein (S protein) plays a crucial role in viral target recognition and entry by interacting with angiotensin, converting enzyme 2 (ACE2), the functional receptor for the virus, via its receptor binding domain (RBD). The RBD availability for this interaction can be influenced by external factors, such as fatty acids. Linoleic acid (LA), a free fatty acid, has been shown to bind the S protein, modulating the viral infection by reducing initial target recognition. LA interacts with the fatty acid binding pocket (FABP), a potential drug target against SARS-CoV-2. In this study, we aimed to exploit the FABP as a drug target by performing a docking-based virtual screening with a library of commercially available, drug-like compounds. The virtual hits identified were then assessed in in vitro assays for the inhibition of the virus-host interaction and cytotoxicity. Binding assays targeting the spike-ACE2 interaction identified multiple compounds with inhibitory activity and low cytotoxicity.
- MeSH
- Angiotensin-Converting Enzyme 2 * metabolism chemistry MeSH
- Antiviral Agents pharmacology chemistry metabolism MeSH
- COVID-19 virology metabolism MeSH
- COVID-19 Drug Treatment MeSH
- Spike Glycoprotein, Coronavirus * metabolism chemistry MeSH
- Linoleic Acid metabolism chemistry MeSH
- Humans MeSH
- Fatty Acid-Binding Proteins metabolism MeSH
- SARS-CoV-2 * metabolism drug effects MeSH
- Molecular Docking Simulation * MeSH
- Protein Binding * MeSH
- Binding Sites MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
