Defining Heart Failure Based on Imaging the Heart and Beyond

Water and salt retention, in other words congestion, are fundamental to the pathophysiology of heart failure and are important therapeutic targets. Echocardiography is the key tool with which to assess cardiac structure and function in the initial diagnostic workup of patients with suspected heart failure and is essential for guiding treatment and stratifying risk. Ultrasound can also be used to identify and quantify congestion in the great veins, kidneys and lungs. More advanced imaging methods might further clarify the aetiology of heart failure and its consequences for the heart and periphery, thereby improving the efficiency and quality of care tailored with greater precision to individual patient need

HDAC6 Inhibitors Modulate Lys49 Acetylation and Membrane Localization of β-Catenin in Human iPSC-Derived Neuronal Cells

We examined the effects of isoform-specific histone deacetylase (HDAC) inhibitors on β-catenin posttranslational modifications in neural progenitor cells (NPCs) derived from human induced pluripotent stem cells (iPSCs). β-catenin is a multifunctional protein with important roles in the developing and adult central nervous system. Activation of the Wnt pathway results in stabilization and nuclear translocation of β-catenin, resulting in activation of multiple target genes. In addition, β-catenin forms a complex with cadherins at the plasma membrane as part of the adherens junctions. The N-terminus of β-catenin has phosphorylation, ubiquitination, and acetylation sites that regulate its stability and signaling. In the absence of a Wnt signal, Ser33, Ser37, and Thr41 are constitutively phosphorylated by glycogen synthase kinase 3β (GSK3β). β-Catenin phosphorylated at these sites is recognized by β-transducin repeat-containing protein (βTrCP), which results in ubiquitination and degradation by the ubiquitin-proteasome pathway. The N-terminal regulatory domain of β-catenin also includes Ser45, a phosphorylation site for Casein Kinase 1α (CK1α) and Lys49, which is acetylated by the acetyltransferase p300/CBP-associated factor (PCAF). The relevance of Lys49 acetylation and Ser45 phosphorylation to the function of β-catenin is an active area of investigation. We find that HDAC6 inhibitors increase Lys49 acetylation and Ser45 phosphorylation but do not affect Ser33, Ser37, and Thr41 phosphorylation. Lys49 acetylation results in decreased ubiquitination of β-catenin in the presence of proteasome inhibition. While increased Lys49 acetylation does not affect total levels of β-catenin, it results in increased membrane localization of β-catenin

Niche-Based Screening in Multiple Myeloma Identifies a Kinesin-5 Inhibitor with Improved Selectivity over Hematopoietic Progenitors

SummaryNovel therapeutic approaches are urgently required for multiple myeloma (MM). We used a phenotypic screening approach using co-cultures of MM cells with bone marrow stromal cells to identify compounds that overcome stromal resistance. One such compound, BRD9876, displayed selectivity over normal hematopoietic progenitors and was discovered to be an unusual ATP non-competitive kinesin-5 (Eg5) inhibitor. A novel mutation caused resistance, suggesting a binding site distinct from known Eg5 inhibitors, and BRD9876 inhibited only microtubule-bound Eg5. Eg5 phosphorylation, which increases microtubule binding, uniquely enhanced BRD9876 activity. MM cells have greater phosphorylated Eg5 than hematopoietic cells, consistent with increased vulnerability specifically to BRD9876’s mode of action. Thus, differences in Eg5-microtubule binding between malignant and normal blood cells may be exploited to treat multiple myeloma. Additional steps are required for further therapeutic development, but our results indicate that unbiased chemical biology approaches can identify therapeutic strategies unanticipated by prior knowledge of protein targets

A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48 h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the case-fatality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48 h after admission (adjusted R-squared = 0.48). We developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients in the Emergency Department, or during hospitalization. Although it is reasonable to assume that the model is also applicable in not-hospitalized persons, only appropriate studies can assess the accuracy of the model also for persons at home

Niche-Based Screening in Multiple Myeloma Identifies a Kinesin-5 Inhibitor with Improved Selectivity over Hematopoietic Progenitors

Novel therapeutic approaches are urgently required for multiple myeloma (MM). We used a phenotypic screening approach using co-cultures of MM cells with bone marrow stromal cells to identify compounds that overcome stromal resistance. One such compound, BRD9876, displayed selectivity over normal hematopoietic progenitors and was discovered to be an unusual ATP non-competitive kinesin-5 (Eg5) inhibitor. A novel mutation caused resistance, suggesting a binding site distinct from known Eg5 inhibitors, and BRD9876 inhibited only microtubule-bound Eg5. Eg5 phosphorylation, which increases microtubule binding, uniquely enhanced BRD9876 activity. MM cells have greater phosphorylated Eg5 than hematopoietic cells, consistent with increased vulnerability specifically to BRD9876’s mode of action. Thus, differences in Eg5-microtubule binding between malignant and normal blood cells may be exploited to treat multiple myeloma. Additional steps are required for further therapeutic development, but our results indicate that unbiased chemical biology approaches can identify therapeutic strategies unanticipated by prior knowledge of protein targets

Analysis of macrobenthic communities in the river basins of Central Italy

The macrobenthic communities of many river basins of Central Italy were sampled and analysed with the Extended Biotic Index, modified for Italian rivers (I.B.E.); 101 watercourses of various typologies were sampled and the total number of taxa detected was 130, among which 117 were useful for the determination of the I.B.E. A preliminary analysis was performed in order to determine the correlation between the frequencies of the different Systematic Units (S.U.) and the I.B.E. values. The data were processed in order to develop an index, the Survey Frequency Index (S.F.I.), which computes the presence of a single S.U. at a given I.B.E. score, in relation to the number of sampling sites showing the same score (I = Ay/nBy). The presence of a faunal group - Index of Group Presence (I.G.P.) - and of taxon - Index of Taxon Presence (I.T.P.) - was evaluated estimating the average of the mean families and the taxon presence respectively. The comparison between the autoecology of a given taxon and its relative I.B.E. and Quality Class (Q.C.) index value provides a preliminary interpretation of a reference community structure within a watershed. The analysis of the macrobenthic community has revealed abnormal distributions of some taxa in relation to the water quality in all of the considered river bio-typologies. In particular, some taxa (i.e. Isoperla, Hydropsychidae, Rhyacophilidae and Ephemerella) have showed higher adaptation levels than expected by the I.B.E. scores. This first contribution has underlined the importance of the disposal of basic elements on the autoecology of single indicative taxa for a critical approach on the composition of the reference communities and the ecotypes identification.Las comunidades macrobentónicas de varias cuencas de Italia Central fueron analizadas mediante el método del Índice Biológico Extendido modificado para los rios italianos (I.B.E.). Fueron realizados muestreos en 101 cursos de agua de diferente tipología y el número total de taxones identificados fue 130, de los cuales 117 fueron utilizados para calcular el índice I.B.E. Un análisis fue realizado para determinar la correlación entre las frecuencias de las Unidades Sistemáticas (U.S.) y los valores de I.B.E. Los datos fueron procesados para desarrollar un índice, el Survey Frequency Index (S.F.I.) que considera la presencia de cada U.S. en cada valor de I.B.E. y con relación al número de estaciones de muestreo que presentan la misma puntuación (I=Ay/nBy). Las presencias de grupo faunístico -Índice de grupo (I.G.P.)- y de taxón -Índice de Presencia de Taxón (I.T.P.)- han sido evaluadas calculando las presencias medias de las familias y de los taxones respectivamente. La comparación entre la autoecología de cada taxón y los valores de I.B.E. y las respectivas Clases de Calidad ofrece una interpretación preliminar de la estructura de la comunidad de referencia dentro de la cuenca. El análisis de las comunidades macrobentónicas ha mostrado distribuciones anormales de varios taxones con relación a la calidad del agua en todas las bio-tipologías consideradas. En particular, algunos taxones (por ejemplo Isoperla, Hydropsichidae, Rhyacophilidae y Ephemerella) evidencian niveles de adaptación más elevados de lo que se esperaba según los valores obtenidos de I.B.E. Este trabajo demuestra la importancia de utilizar los elementos de autoecología de los taxones para establecer las comunidades de referencia y la identificación de los ecotipos