41 research outputs found

    Peak CK-MB has a strong association with chronic scar size and wall motion abnormalities after revascularized non-transmural myocardial infarction - a prospective CMR study

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    Background: Large myocardial infarction (MI) is associated with adverse left ventricular (LV) remodeling (LVR). We studied the nature of LVR, with specific attention to non-transmural MIs, and the association of peak CK-MB with recovery and chronic phase scar size and LVR. Methods: Altogether 41 patients underwent prospectively repeated cardiovascular magnetic resonance at a median of 22 (interquartile range 9-29) days and 10 (8-16) months after the first revascularized MI. Transmural MI was defined as >= 75% enhancement in at least one myocardial segment. Results: Peak CK-MB was 86 (40-216) mu g/L in median, while recovery and chronic phase scar size were 13 (3-23) % and 8 (2-19) %. Altogether 33 patients (81%) had a non-transmural MI. Peak CK-MB had a strong correlation with recovery and chronic scar size (r >= 0.80 for all, r >= 0.74 for non-transmural MIs; p = 0.75 for all, r >= 0.73 for non-transmural MIs; p <0.001). There was proportional scar size and LV mass resorption of 26% (0-50%) and 6% (-2-14%) in median. Young age (<60 years, median) was associated with greater LV mass resorption (median 9% vs. 1%, p = 0.007). Conclusions: Peak CK-MB has a strong association with chronic scar size and wall motion abnormalities after revascularized non-transmural MI. Considerable infarct resorption happens after the first-month recovery phase. LV mass resorption is related to age, being more common in younger patients.Peer reviewe

    ANO1 Expression Orchestrates p27Kip1/MCL1-Mediated Signaling in Head and Neck Squamous Cell Carcinoma

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    Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous group of tumors that derive from the mucosal epithelium of the upper aerodigestive tract and present high mortality rate. Lack of efficient targeted-therapies and biomarkers towards patients’ stratification are caveats in the disease treatment. Anoctamin 1 (ANO1) gene is amplified in 30% of HNSCC cases. Evidence suggests involvement of ANO1 in proliferation, migration, and evasion of apoptosis; however, the exact mechanisms remain elusive. Aim of this study was to unravel the ANO1-dependent transcriptional programs and expand the existing knowledge of ANO1 contribution to oncogenesis and drug response in HNSCC. We cultured two HNSCC cell lines established from primary tumors harboring amplification and high expression of ANO1 in three-dimensional collagen. Differential expression analysis of ANO1-depleted HNSCC cells demonstrated downregulation of MCL1 and simultaneous upregulation of p27Kip1 expression. Suppressing ANO1 expression led to redistribution of p27Kip1 from the cytoplasm to the nucleus and associated with a cell cycle arrested phenotype. ANO1 silencing or pharmacological inhibition resulted in reduction of cell viability and ANO1 protein levels, as well as suppression of pro-survival BCL2 family proteins. Collectively, these data provide insights of ANO1 involvement in HNSCC carcinogenesis and support the rationale that ANO1 is an actionable drug target

    ANO1 Expression Orchestrates p27Kip1/MCL1-Mediated Signaling in Head and Neck Squamous Cell Carcinoma

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    Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous group of tumors that derive from the mucosal epithelium of the upper aerodigestive tract and present high mortality rate. Lack of efficient targeted-therapies and biomarkers towards patients’ stratification are caveats in the disease treatment. Anoctamin 1 (ANO1) gene is amplified in 30% of HNSCC cases. Evidence suggests involvement of ANO1 in proliferation, migration, and evasion of apoptosis; however, the exact mechanisms remain elusive. Aim of this study was to unravel the ANO1-dependent transcriptional programs and expand the existing knowledge of ANO1 contribution to oncogenesis and drug response in HNSCC. We cultured two HNSCC cell lines established from primary tumors harboring amplification and high expression of ANO1 in three-dimensional collagen. Differential expression analysis of ANO1-depleted HNSCC cells demonstrated downregulation of MCL1 and simultaneous upregulation of p27Kip1 expression. Suppressing ANO1 expression led to redistribution of p27Kip1 from the cytoplasm to the nucleus and associated with a cell cycle arrested phenotype. ANO1 silencing or pharmacological inhibition resulted in reduction of cell viability and ANO1 protein levels, as well as suppression of pro-survival BCL2 family proteins. Collectively, these data provide insights of ANO1 involvement in HNSCC carcinogenesis and support the rationale that ANO1 is an actionable drug target. </p

    Fibrosis and wall thickness affect ventricular repolarization dynamics in hypertrophic cardiomyopathy

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    Background Hypertrophic cardiomyopathy (HCM) is characterized by ventricular repolarization abnormalities and risk of ventricular arrhythmias. Our aim was to study the association between the phenotype and ventricular repolarization dynamics in HCM patients. Methods Results HCM patients with either the MYBPC3-Q1061X or TPM1-D175N mutation (n = 46) and control subjects without mutation and hypertrophy (n = 35) were studied with 24-hr ambulatory ECG recordings by measuring time intervals of rate-adapted QT (QTe), maximal QT, and T-wave apex to wave end (TPE) intervals and the QTe/RR slope. Findings were correlated to specified echocardiographic and cardiac magnetic resonance imaging (CMRI) findings. Rate-adapted QTe interval was progressively longer in HCM patients with decreasing heart rates compared to control subjects (p = 0.020). The degree of hypertrophy correlated with measured QTe values. HCM patients with maximal wall thickness higher than the mean (20.6 mm) had longer maximum QTe and median TPE intervals compared to control subjects and HCM patients with milder hypertrophy (p p = 0.014, respectively). HCM patients with late gadolinium enhancement (LGE) on CMRI had steeper QTe/RR slopes compared to HCM patients without LGE and control subjects (p = 0.044 and p = 0.001, respectively). LGE was an independent predictor of QTe/RR slope (p = 0.023, B = 0.043). Conclusion Dynamics of ventricular repolarization in HCM are affected by hypertrophy and fibrosis. LGE may confer an independent effect on QT dynamics which may increase the arrhythmogenic potential in HCM.Peer reviewe

    Compressive stress-mediated p38 activation required for ER alpha plus phenotype in breast cancer

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    Breast cancer is now globally the most frequent cancer and leading cause of women's death. Two thirds of breast cancers express the luminal estrogen receptor-positive (ER alpha + ) phenotype that is initially responsive to antihormonal therapies, but drug resistance emerges. A major barrier to the understanding of the ER alpha-pathway biology and therapeutic discoveries is the restricted repertoire of luminal ER alpha + breast cancer models. The ER alpha + phenotype is not stable in cultured cells for reasons not fully understood. We examine 400 patient-derived breast epithelial and breast cancer explant cultures (PDECs) grown in various three-dimensional matrix scaffolds, finding that ER alpha is primarily regulated by the matrix stiffness. Matrix stiffness upregulates the ER alpha signaling via stress-mediated p38 activation and H3K27me3-mediated epigenetic regulation. The finding that the matrix stiffness is a central cue to the ER alpha phenotype reveals a mechanobiological component in breast tissue hormonal signaling and enables the development of novel therapeutic interventions. Subject terms: ER-positive (ER + ), breast cancer, ex vivo model, preclinical model, PDEC, stiffness, p38 SAPK. Reliable luminal estrogen receptor (ER alpha+) breast cancer models are limited. Here, the authors use patient derived breast epithelial and breast cancer explant cultures grown in several extracellular matrix scaffolds and show that ER alpha expression is regulated by matrix stiffness via stress-mediated p38 activation and H3K27me3-mediated epigenetic regulation.Peer reviewe

    Turvemaiden digitaalinen kartoitus ja turvepeltolohkojen tunnistaminen

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    Maatalouden turvemaiden ilmasto- ja vesistöpäästöjen vähentäminen edellyttää turvepeltolohkojen tunnistamista, mutta maaperätieto ei ole ollut riittävän tarkkaa tähän tarkoitukseen. Raportissa esitellyn työn tavoitteena oli tuottaa tarkennettua paikkatietoa turvemaiden esiintymisestä ja paksuudesta turvepeltolohkojen tunnistamiseksi. Uusi paikkatietoaineisto turvemaiden esiintymisestä ja paksuudesta luotiin hyödyntämällä koneoppimismallinnusta. Mallinnus tehtiin Random Forest -menetelmällä. Turpeen esiintymistä selittäviksi aineistoiksi valmisteltiin 117 kpl koko maan kattavia satelliitti- ja lentoalustoilta mitattuja kaukokartoitusaineistoja ja geologista paikkatietoaineistoa. Koneoppimismallin opettamista ja testausta varten koottiin 3,5 miljoonaa maaperähavaintoa, josta 70 % käytettiin mallin opetukseen ja 30 % mallin riippumattomaan testaukseen. Mallinnuksessa ennustettiin turvepaksuusluokkien ≥ 10 cm, ≥ 30 cm, ≥ 40 cm ja > 60 cm esiintymistä 50 m × 50 m rasteriresoluutiossa ja ennusteet tuotettiin maankäyttömuodosta riippumatta kaikille maa-alueille. Malliennusteiden tarkkuus oli korkea. Turvepaksuusluokat pystyttiin erottelemaan muista maalajeista ja turvepaksuusluokista 89–96 % tarkkuudella. Tarkkuudet olivat korkeimmillaan ohuissa turvepaksuusluokissa ja hieman heikompia paksuissa luokissa. Maatalousmailla vähintään 30 cm paksun turvemaan alaksi arvoitiin 273 000 ha, mikä on noin 11 % maatalousmaa-alasta. Tästä pinta-alasta 73 % turvekerros oli > 60 cm. Saamamme arvio maatalousmaiden turvemaiden (≥ 30 cm) pinta-alasta on 8 600 ha suurempi kuin mitä mittakaavaltaan 1:200 000 maaperäkartasta voidaan arvioida. Peltolohkokohtainen tarkastelu osoitti, että turve-ennusteet mahdollistavat turvealan ja -paksuuden arvioimisen yksittäisillä peltolohkoilla. Esimerkiksi turvepeltolohkot, joilla on vähintään 50 % alastaan ≥30 cm paksu turvekerros, tunnistettiin yli 90 % tarkkuudella. Uusi paikkatietoaineisto Turpeen paksuus 1.0/2023 tarkentaa aikaisempaa tietoa turvemaiden esiintymisestä ja paksuudesta koko maassa. Aineiston luokittelutarkkuus ja alueellinen erottelukyky ovat olemassa olevia maaperäkartta-aineistoja parempia ja sen avulla tunnistetaan aikaisemmin kartoittamattomia turvemaita. Yleistarkkuusmetriikat raportoidaan jokaiselle luokittelulle erikseen ja epävarmuuksien hajautuminen on esitetty Random Forest -puiden yksimielisyyden avulla rasterisolukohtaisesti. Uudet turve-ennusteet tuovat uusia mahdollisuuksia maaperään ja maankäyttöön liittyvien toimintojen suunnittelun, ohjaukseen ja vaikutusten arviointiin, sekä tutkimukseen
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