SegEIR-Net: A Robust Histopathology Image Analysis Framework for Accurate Breast Cancer Classification.

BACKGROUND: Breast Cancer (BC) is a significant threat affecting women globally. An accurate and reliable disease classification method is required to get an early diagnosis. However, existing approaches lack accurate and robust classification. OBJECTIVE: This study aims to design a model to classify BC Histopathology images accurately by leveraging segmentation techniques. METHODS: This work proposes a combined segmentation and classification approach for classifying BC using histopathology images to address these issues. Chan-Vese algorithm is used for segmentation to accurately delineate regions of interest within the histopathology images, followed by the proposed SegEIR-Net (Segmentation using EfficientNet, InceptionNet, and ResNet) for classification. Bilateral Filtering is also employed for noise reduction. The proposed model uses three significant networks, ResNet, InceptionNet, and EfficientNet, concatenates the outputs from each block followed by Dense and Dropout layers. The model is trained on the breakHis dataset for four different magnifications and tested on BACH (BreAst Cancer Histology) and UCSB (University of California, Santa Barbara) datasets. RESULTS: SegEIR-Net performs better than the existing State-of-the-Art (SOTA) methods in terms of accuracy on all three datasets, proving the robustness of the proposed model. The accuracy achieved on breakHis dataset are 98.66%, 98.39%, 97.52%, 95.22% on different magnifications, and 93.33% and 96.55% on BACH and UCSB datasets. CONCLUSION: These performance results indicate the robustness of the proposed SegEIR-Net framework in accurately classifying BC from histopathology images.

Response of biochar derives from farm waste on phosphorus sorption and desorption in texturally different soils.

The information on changes in phosphorus (P) sorption and desorption characteristics and transformations after biochar application to high P fixing soils is still unclear. In the present study, we evaluated the differential response of biochar derives from five different farm waste viz. Lucaena sp., Albbizia sp., Mangifera indica, Triticum aestivum and Oryza sativa applied at 1 and 3 g kg-1 (w/w) on P sorption and desorption in three texturally different (silt loam, clay loam and sandy loam) soils. The amount of P sorbed by the clay loam was significantly (p<0.05) higher than the silt loam and sandy loam, regardless of added P concentration. The Freundlich isotherms exhibit a better fit (R2 = 0.564-0.996 in silt loam, 0.640-0.993 in clay loam and 0.724-0.993 in sandy loam soil) to P sorption data as compared with the Langmuir isotherm. Biochar application significantly decreased the P desorption maxima and desorption constant. The R2 values ranged from 0.447 to 0.999 in silt loam, 0.438 to 0.996 in clay loam, 0.545 to 0.989 in sandy loam. Lucaena biochar showed highest adsorption maxima, thereby suggesting highest P release, whereas soils treated with Triticum aestivum biochar had the lowest adsorption maxima in both clay loam and sandy loam soil. These results indicated that biochar application can significantly enhance P availability; the extent of which is determined by soil texture and type of biochar. The results of present study highlight that biochar application would help increase soil P availability by enhancing fertilizer-P use efficiency associated with decreased P sorption capacity due to increased flush of available-P in soil colloidal complex.

Tillage, green manuring and crop residue management impacts on crop productivity, potassium use efficiency and potassium fractions under rice-wheat system.

The conventional crop production practices including intensive tillage and open field crop residue burning in world' largest rice-wheat system (RWS) are adversely affecting crop productivity besides deteriorating natural resources and ecosystems' sustainability. In order to improve system productivity, potassium (K) use efficiency and apparent K balance, adoption of conservation tillage in a RWS with residue management is considered highly effective. We therefore, studied the effect of wheat straw retention and green manure (GM) in rice (main plot treatment), and tillage and rice residue management in subsequent wheat (sub-plot treatments) on crop productivity, K use efficiency and its transformation amongst different fractions of variable solubility. These results revealed that rice straw retention along with GM significantly (p < 0.05) increased the rice yields by ∼5.3-6.7% and wheat yields by ∼10.2-16.9%, compared to the conventional tillage (CT) without GM. Green manuring during the intervening period (CTRW0+GM) significantly increased the rice grain K uptake by ∼36.2% than in plots with no-GM (CTRW0). However, it increased by ∼29.8% under CTRW25+GM, compared with CTRW25-GM treatment. As compared with CTRW0, CTRW0+GM significantly increased the reciprocal internal use efficiency of K of rice by 3.8 kg Mg-1 grain yield (∼29.5%). However, CTRW25+GM increased the RIUEK of rice by 3.3 kg Mg-1 grain yield (∼22.4%), compared with no-GM (CTRW25). Although, apparent K balance was net negative for CTRW25, ZTWR100 treatments, yet there was decreased K mining of 56-262 kg K ha-1 (∼11.9-61.2%) for CTRW25 and ZTWR100 over CTRW0 and ZTWR0. The increased crop yield, K uptake and K use efficiency were significantly related to K enrichment in water soluble K, exchangeable K, non-exchangeable-K, hydrochloric acid extractable-K, lattice-K and total K fractions by ∼1.3, 3.4, 18.6, 11.0 and 34.1%, respectively due to residue retention, compared with no residue. Therefore, conventional tillage with puddled transplanted rice (CTR) with wheat residue and green manure during intervening period (CTRW25+GM), and zero tillage wheat with rice residue retention (ZTWR100) were emerged as highly valuable technological options for mitigating soil degradation effects under intensive RWS for food grains in north-western India.

Structural and molecular insights into tacrine-benzofuran hybrid induced inhibition of amyloid-ß peptide aggregation and BACE1 activity.

Amyloid-ß (Aß) aggregation and ß-amyloid precursor protein cleaving enzyme 1 (BACE1) are the potential therapeutic drug targets for Alzheimer's disease (AD). A recent study highlighted that tacrine-benzofuran hybrid C1 displayed anti-aggregation activity against Aß42 peptide and inhibit BACE1 activity. However, the inhibition mechanism of C1 against Aß42 aggregation and BACE1 activity remains unclear. Thus, molecular dynamics (MD) simulations of Aß42 monomer and BACE1 with and without C1 were performed to inspect the inhibitory mechanism of C1 against Aß42 aggregation and BACE1 activity. In addition, a ligand-based virtual screening followed by MD simulations was employed to explore potent new small-molecule dual inhibitors of Aß42 aggregation and BACE1 activity. MD simulations highlighted that C1 promotes the non aggregating helical conformation in Aß42 and destabilizes D23-K28 salt bridge that plays a vital role in the self-aggregation of Aß42. C1 displays a favourable binding free energy (-50.7 ± 7.3 kcal/mol) with Aß42 monomer and preferentially binds to the central hydrophobic core (CHC) residues. MD simulations highlighted that C1 strongly interacted with the BACE1 active site (Asp32 and Asp228) and active pockets. The scrutiny of interatomic distances among key residues of BACE1 highlighted the close flap (non-active) position in BACE1 on the incorporation of C1. The MD simulations explain the observed high inhibitory activity of C1 against Aß aggregation and BACE1 in the in vitro studies. The ligand-based virtual screening followed by MD simulations identified CHEMBL2019027 (C2) as a promising dual inhibitor of Aß42 aggregation and BACE1 activity.Communicated by Ramaswamy H. Sarma.

PATIENTS SATISFACTION WITH PAIN MEDICATION: A STUDY OF LABORATORY MEDICINE.

Patients in pain have different levels of satisfaction. The experience of patients regarding medication is based on their past treatment. The mental satisfaction of the patients for laboratory medication is necessary for their health recovery. The satisfaction of patients is a challenge for healthcare institutes to provide better facilities to patients. The goal of this research is to investigate the impact of taking patch pain medication, taking oral pain medication, and taking intravenous medication on patients' satisfaction with laboratory pain medication. The model of this research is based on the gap in the literature. 645 responses were considered for data analysis with Smart PLS 3.0 for study findings. The findings disclosed the impact of taking patch pain medication, taking an oral medication, and taking intravenous medication is significant on patients' satisfaction with laboratory pain medication. The study has theoretically enriched the literature with a unique contribution to the study model. Practically, the study has discovered the ways the healthcare sector can improve the satisfaction of patients for their better health and satisfaction. The future directions highlighted by this study are useful for future studies to contribute to patients' satisfaction with laboratory medication.

Pharmaceutical interventions: A solution to stop smoking.

Background: Smoking has become a worldwide problem and the more problematic is when the youth of any country is highly involved in consuming tobacco that is dangerous for the human being. The Indian youth is involved in smoking-like activities that are dangerous for them. Objectives: To analyze the role of new treatment ways including nicotine gum, nicotine patch, and nicotine replacement therapy backed by pharmaceutical interventions to eliminate smoking from Indian society. Method: The hypotheses of this study are formed on the basis of previous studies and the identification of gap in practices. This study is based on the cross-sectional data that was collected with the help of a questionnaire based on a five-point Likert scale from the Indian pharma industry people. The sample size for this study was 340 with a response rate of 50%. Results: In this study, 179 valid questionnaires were collected back from the respondents, and according to the results, nicotine gum, nicotine patch, and nicotine replacement therapies have a significant (p<0.05) effect on smoker attitudes. Conclusion: This study concludes that pharmaceutical interventions are critical to stopping the smoking habit in Indian society, and this contribution is providing a solution to stop smoking by affecting the smoker's attitude and smoking behavior.

Nitrogen and potassium application effects on productivity, profitability and nutrient use efficiency of irrigated wheat (Triticum aestivum L.).

The development of robust nutrient management strategies have played a crucial role in improving crop productivity, profitability and nutrient use efficiency. Therefore, the implementation of efficient nutrient management stratigies is important for food security and environmental safety. Amongst the essential plant nutrients, managing nitrogen (N) and potassium (K) in wheat (Triticum aestivum L.) based production systems is citically important to maximize profitable production with minimal negative environmental impacts. We investigated the effects of different fertilizer-N (viz. 0-240 kg N ha-1; N0-N240) and fertilizer-K (viz. 0-90 kg K ha-1; K0-K90) application rates on wheat productivity, nutrient (N and K) use efficiency viz. partial factor productivity (PFPN/K), agronomic efficiency (AEN/K), physiological efficiency (PEN/K), reciprocal internal use efficiency (RIUEN/K), and profitability in terms of benefit-cost (B-C) ratio, gross returns above fertilizer cost (GRAFC) and the returns on investment (ROI) on fertilizer application. These results revealed that wheat productivity, plant growth and yield attributes, nutrients uptake and use efficiency increased significantly (p<0.05)with fertilizer-N application, although the interaction effect of N x K application was statistically non-significant (p<0.05). Fertilizer-N application at 120 kg N ha-1 (N120) increased the number of effective tillers (8.7%), grain yield (17.3%), straw yield (15.1%), total N uptake (25.1%) and total K uptake (16.1%) than the N80. Fertilizer-N application significantly increased the SPAD reading by ~4.2-10.6% with fertilizer-N application (N80-N240), compared with N0. The PFPN and PFPK increased significantly with fertilizer-N and K application in wheat. The AEN varied between 12.3 and 22.2 kg kg-1 with significantly higher value of 20.8 kg kg-1 in N120. Fertilizer-N application at higher rate (N160) significantly decreased the AEN by ~16.3% over N120. The N120treatment increased the AEK by ~52.6% than N80 treatment. Similarly the RIUEN varied between 10.6 and 25.6 kg Mg-1 grain yield, and increased significantly by ~80.2% with N120 as compared to N0 treatment. The RIUEK varied between 109 and 15.1 kg Mg-1 grain yield, and was significantly higher in N120 treatment. The significant increase in mean gross returns (MGRs) by ~17.3% and mean net returns (MNRs) by ~24.1% increased the B-C ratio by ~15.1% with N120 than the N80 treatment. Fertilizer-N application in N120 treatment increased the economic efficiency of wheat by ~24.1% and GRAFC by ~16.9%. Grain yield was significantly correlated with total N uptake (r = 0.932**, p<0.01), K uptake (r = 0.851**), SPAD value (r = 0.945**), green seeker reading (r = 0.956**), and the RIUEN (r = 0.910**). The artificial neural networks (ANNs) showed highly satisfactory performance in training and simulation of testing data-set on wheat grain yield. The calculated mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) for wheat were 0.0087, 0.834 and 0.052, respectively. The well trained ANNs model was capable of producing consistency for the training and testing correlation (R2 = 0.994**, p<0.01) between the predicted and actual values of wheat grain yield, which implies that ANN model succeeded in wheat grain yield prediction.

Pharmaceutical interventions: A solution to stop smoking

Background: Smoking has become a worldwide problem and the more problematic is when the youth of any country is highly involved in consuming tobacco that is dangerous for the human being. The Indian youth is involved in smoking-like activities that are dangerous for them. Objectives: To analyze the role of new treatment ways including nicotine gum, nicotine patch, and nicotine replacement therapy backed by pharmaceutical interventions to eliminate smoking from Indian society. Method: The hypotheses of this study are formed on the basis of previous studies and the identification of gap in practices. This study is based on the cross-sectional data that was collected with the help of a questionnaire based on a five-point Likert scale from the Indian pharma industry people. The sample size for this study was 340 with a response rate of 50%. Results: In this study, 179 valid questionnaires were collected back from the respondents, and according to the results, nicotine gum, nicotine patch, and nicotine replacement therapies have a significant (p<0.05) effect on smoker attitudes. Conclusion: This study concludes that pharmaceutical interventions are critical to stopping the smoking habit in Indian society, and this contribution is providing a solution to stop smoking by affecting the smoker’s attitude and smoking behavior. (AU)

Analysis of fMRI Signals from Working Memory Tasks and Resting-State of Brain: Neutrosophic-Entropy-Based Clustering Algorithm.

This study applies a neutrosophic-entropy-based clustering algorithm (NEBCA) to analyze the fMRI signals. We consider the data obtained from four different working memory tasks and the brain's resting state for the experimental purpose. Three non-overlapping clusters of data related to temporal brain activity are determined and statistically analyzed. Moreover, we used the Uniform Manifold Approximation and Projection (UMAP) method to reduce system dimensionality and present the effectiveness of NEBCA. The results show that using NEBCA, we are able to distinguish between different working memory tasks and resting-state and identify subtle differences in the related activity of brain regions. By analyzing the statistical properties of the entropy inside the clusters, the various regions of interest (ROIs), according to Automated Anatomical Labeling (AAL) atlas crucial for clustering procedure, are determined. The inferior occipital gyrus is established as an important brain region in distinguishing the resting state from the tasks. Moreover, the inferior occipital gyrus and superior parietal lobule are identified as necessary to correct the data discrimination related to the different memory tasks. We verified the statistical significance of the results through the two-sample t-test and analysis of surrogates performed by randomization of the cluster elements. The presented methodology is also appropriate to determine the influence of time of day on brain activity patterns. The differences between working memory tasks and resting-state in the morning are related to a lower index of small-worldness and sleep inertia in the first hours after waking. We also compared the performance of NEBCA to two existing algorithms, KMCA and FKMCA. We showed the advantage of the NEBCA over these algorithms that could not effectively accumulate fMRI signals with higher variability.

The experiences of Indian people living in New Zealand with stroke.

PURPOSE: Stroke can cause lifelong disability and participatory limitations. Stroke survivors thus manage their recovery long term. Health professionals can support self-management, tailoring this support to be culturally appropriate. This study explored the unique culture and ethnicity specific experiences of Indian people living in New Zealand with stroke, focussing on self-management and facilitators and challenges to recovery. METHODS: Eight individuals with stroke took part in semi-structured interviews. Data were analysed using the General Inductive Approach. RESULTS: Four themes were identified: (1) helping myself, in any way that I can, (2) family and support, (3) social connections, and (4) ethnicity was not a barrier. CONCLUSION: All participants felt well looked after within the New Zealand healthcare context but highlighted the need for long term support. Self-management strategies participants considered important included changes to their diet, acceptance by oneself and society, returning to work, the role of family, and the use of technology and social media. Health professionals should consider these factors when providing self-management support to individuals of Indian ethnicity.IMPLICATIONS FOR REHABILITATIONAdvice and help around diet, lifestyle, and return to work were important priorities identified by our Indian stroke survivor participants.Our Indian stroke survivor participants requested more long-term specialist support and stroke information.Although the family willingly take increased responsibility for the wellbeing of the individual with stroke, it is not a substitute for professional input which needs to be tailored and offered proactively.

A quantum-clustering optimization method for COVID-19 CT scan image segmentation.

The World Health Organization (WHO) has declared Coronavirus Disease 2019 (COVID-19) as one of the highly contagious diseases and considered this epidemic as a global health emergency. Therefore, medical professionals urgently need an early diagnosis method for this new type of disease as soon as possible. In this research work, a new early screening method for the investigation of COVID-19 pneumonia using chest CT scan images has been introduced. For this purpose, a new image segmentation method based on K-means clustering algorithm (KMC) and novel fast forward quantum optimization algorithm (FFQOA) is proposed. The proposed method, called FFQOAK (FFQOA+KMC), initiates by clustering gray level values with the KMC algorithm and generating an optimal segmented image with the FFQOA. The main objective of the proposed FFQOAK is to segment the chest CT scan images so that infected regions can be accurately detected. The proposed method is verified and validated with different chest CT scan images of COVID-19 patients. The segmented images obtained using FFQOAK method are compared with various benchmark image segmentation methods. The proposed method achieves mean squared error, peak signal-to-noise ratio, Jaccard similarity coefficient and correlation coefficient of 712.30, 19.61, 0.90 and 0.91 in case of four experimental sets, namely Experimental_Set_1, Experimental_Set_2, Experimental_Set_3 and Experimental_Set_4, respectively. These four performance evaluation metrics show the effectiveness of FFQOAK method over these existing methods.

Ambiguous D-means fusion clustering algorithm based on ambiguous set theory: Special application in clustering of CT scan images of COVID-19.

Coronavirus Disease 2019 (COVID-19) has been considered one of the most critical diseases of the 21st century. Only early detection can aid in the prevention of personal transmission of the disease. Recent scientific research reports indicate that computed tomography (CT) images of COVID-19 patients exhibit acute infections and lung abnormalities. However, analyzing these CT scan images is very difficult because of the presence of noise and low-resolution. Therefore, this study suggests the development of a new early detection method to detect abnormalities in chest CT scan images of COVID-19 patients. By this motivation, a novel image clustering algorithm, called ambiguous D-means fusion clustering algorithm (ADMFCA), is introduced in this study. This algorithm is based on the newly proposed ambiguous set theory and associated concepts. The ambiguous set is used in the proposed technique to characterize the ambiguity associated with grayscale values of pixels as true, false, true-ambiguous and false-ambiguous. The proposed algorithm performs the clustering operation on the CT scan images based on the entropies of different grayscale values. Finally, a final outcome image is obtained from the clustered images by image fusion operation. The experiment is carried out on 40 different CT scan images of COVID-19 patients. The clustered images obtained by the proposed algorithm are compared to five well-known clustering methods. The comparative study based on statistical metrics shows that the proposed ADMFCA is more efficient than the five existing clustering methods.

A neutrosophic-entropy based adaptive thresholding segmentation algorithm: A special application in MR images of Parkinson's disease.

Brain MR images are composed of three main regions such as gray matter, white matter and cerebrospinal fluid. Radiologists and medical practitioners make decisions through evaluating the developments in these regions. Study of these MR images suffers from two major issues such as: (a) the boundaries of their gray matter and white matter regions are ambiguous and unclear in nature, and (b) their regions are formed with unclear inhomogeneous gray structures. These two issues make the diagnosis of critical diseases very complex. To solve these issues, this study presented a method of image segmentation based on the neutrosophic set (NS) theory and neutrosophic entropy information (NEI). By nature, the proposed method is adaptive to select the threshold value and is entitled as neutrosophic-entropy based adaptive thresholding segmentation algorithm (NEATSA). In this study, experimental results were provided through the segmentation of Parkinson's disease (PD) MR images. Experimental results, including statistical analyses showed that NEATSA can segment the main regions of MR images very clearly compared to the well-known methods of image segmentation available in literature of pattern recognition and computer vision domains.

A neutrosophic-entropy based clustering algorithm (NEBCA) with HSV color system: A special application in segmentation of Parkinson's disease (PD) MR images.

BACKGROUND AND OBJECTIVES: Brain MR images consist of three major regions: gray matter, white matter and cerebrospinal fluid. Medical experts make decisions on different serious diseases by evaluating the developments in these areas. One of the significant approaches used in analyzing the MR images were segmenting the regions. However, their segmentation suffers from two major problems as: (a) the boundaries of their gray matter and white matter regions are ambiguous in nature, and (b) their regions are formed with unclear inhomogeneous gray structures. For these reasons, diagnosis of critical diseases is often very difficult. METHODS: This study presented a new method for MR image segmentation, which consisted of two main parts as: (a) neutrosophic-entropy based clustering algorithm (NEBCA), and (b) HSV color system. The NEBCA's role in this study was to perform segmentation of MR regions, while HSV color system was used to provide better visual representation of features in segmented regions. RESULTS: Application of the proposed method was demonstrated in 30 different MR images of Parkinson's disease (PD). Experimental results were presented individually for the NEBCA and HSV color system. The performance of the proposed method was evaluated in terms of statistical metrics used in an image segmentation domain. Experimental results, including statistical analysis reflected the efficiency of the proposed method over the existing well-known image segmentation methods available in literature. For the proposed method and existing methods, the average CPU time (in nanosecond) was computed and it was found that the proposed method consumed less time to segment MR images. CONCLUSION: The proposed method can effectively segment different regions of MR images and can very clearly represent those segmented regions.

Fatal neutropenic enterocolitis associated with docetaxel use: A review of cases reported to the United States Food and Drug Administration Adverse Event Reporting System.

Docetaxel is a microtubule inhibitor indicated for the treatment of multiple cancers as a single agent or in combination with other antineoplastics. The U.S. Food and Drug Administration (FDA) conducted a postmarketing review of fatal neutropenic enterocolitis cases reported with docetaxel using the FDA Adverse Event Reporting System (FAERS) and literature to determine whether the drug was a potential cause. We searched FAERS and the literature for reports of fatal neutropenic enterocolitis with docetaxel-based treatment reported between 14 May 1996 and 13 March 2017. We characterized the clinical course and severity of neutropenic enterocolitis and utilized the World Health Organization-Uppsala Monitoring Centre rubric to assess drug causality. We identified 41 fatal cases of neutropenic enterocolitis with docetaxel from FAERS and the literature. The median time to onset of neutropenic enterocolitis from last docetaxel dose was seven days (range 2-13 days), and median time to death was nine days (range 3-23 days). The cause of death in 83% (34/41) of patients was neutropenic enterocolitis. We determined the drug-event association as probable in seven cases. Neutropenic enterocolitis with docetaxel monotherapy occurred in six cases; however, in 85% (35/41) of cases, neutropenic enterocolitis occurred when docetaxel was used in combination with other cytotoxic chemotherapy. In some cases, neutropenic enterocolitis occurred despite use of granulocyte colony-stimulating factors. Neutropenic enterocolitis is a severe and potentially fatal complication of docetaxel-based treatment, especially when combined with other antineoplastic treatments known to cause neutropenia. Practitioners should be aware of this safety risk to promptly recognize and manage patients.

Identification of a targeted and testable antiarrhythmic therapy for long-QT syndrome type 2 using a patient-specific cellular model.

Aims: Loss-of-function mutations in the hERG gene causes long-QT syndrome type 2 (LQT2), a condition associated with reduced IKr current. Four different mutation classes define the molecular mechanisms impairing hERG. Among them, Class 2 mutations determine hERG trafficking defects. Lumacaftor (LUM) is a drug acting on channel trafficking already successfully tested for cystic fibrosis and its safety profile is well known. We hypothesize that LUM might rescue also hERG trafficking defects in LQT2 and exert anti-arrhythmic effects. Methods and results: From five LQT2 patients, we generated lines of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) harbouring Class 1 and 2 mutations. The effects of LUM on corrected field potential durations (cFPD) and calcium-handling irregularities were verified by multi electrode array and by calcium transients imaging, respectively. Molecular analysis was performed to clarify the mechanism of action of LUM on hERG trafficking and calcium handling. Long-QT syndrome type 2 induced pluripotent stem cell-derived cardiomyocytes mimicked the clinical phenotypes and showed both prolonged cFPD (grossly equivalent to the QT interval) and increased arrhythmias. Lumacaftor significantly shortened cFPD in Class 2 iPSC-CMs by correcting the hERG trafficking defect. Furthermore, LUM seemed to act also on calcium handling by reducing RyR2S2808 phosphorylation in both Class 1 and 2 iPSC-CMs. Conclusion: Lumacaftor, a drug already in clinical use, can rescue the pathological phenotype of LQT2 iPSC-CMs, particularly those derived from Class 2 mutated patients. Our results suggest that the use of LUM in LQT2 patients not protected by ß-blockers is feasible and may represent a novel therapeutic option.

A Case of Anagrelide-Induced Nonischemic Cardiomyopathy in a Patient With Essential Thrombocythemia.

BACKGROUND: Anagrelide is an established treatment option for essential thrombocythemia (ET). Cardiovascular adverse events can occur with its use including heart failure and cardiomyopathy. CASE REPORT: A 52-year-old African American male with ET presented with chest pain, shortness of breath, and dyspnea on exertion. His ET was managed with hydroxyurea 1500 mg by mouth twice a day and anagrelide 1 mg by mouth 3 times a day. The patient was receiving anagrelide for approximately 2 years prior to presentation. The patient's platelet count was 2.07 × 105 cells/mm3. Transthoracic echocardiography revealed decreased left systolic dysfunction. Also, cardiac magnetic resonance imaging showed an increased left ventricle cavity size with severely depressed systolic dysfunction and an ejection fraction (EF) of 18%. Anagrelide therapy was discontinued and the patient was maintained on hydroxyurea for ET. Three months later, following treatment by a heart failure clinic, the patient's EF was 55%. Five months after discontinuation, the patient improved from New York Heart Association (NYHA) class II to NYHA class I. CONCLUSION: A 52-year-old man with ET presented with an EF of 18% after 2 years of anagrelide therapy. His EF increased from 18% to 55% 3 months after discontinuation of anagrelide.

Acetylated Signal Transducer and Activator of Transcription 3 Functions as Molecular Adaptor Independent of Transcriptional Activity During Human Cardiogenesis.

Activation of signal transducer and activator of transcription 3 (STAT3) is imperative for mammalian development, specifically cardiogenesis. STAT3 phosphorylation and acetylation are key post-translational modifications that regulate its transcriptional activity. Significance of such modifications during human cardiogenesis remains elusive. Using human pluripotent stem cells to recapitulate cardiogenesis, two independently modified STAT3α (92 kDa) isoforms (phosphorylated and acetylated), which perform divergent functions were identified during cardiomyocyte (CM) formation. Phosphorylated STAT3α functioned as the canonical transcriptional activator, while acetylated STAT3α underwent caspase-3-mediated cleavage to generate a novel STAT3ζ fragment (∼45 kDa), which acted as a molecular adaptor integral to the ErbB4-p38γ signaling cascade in driving CM formation. While STAT3α knockdown perturbed cardiogenesis by eliminating both post-translationally modified STAT3α isoforms, caspase-3 knockdown specifically abrogates the function of acetylated STAT3α, resulting in limited STAT3ζ formation thereby preventing nuclear translocation of key cardiac transcription factor Nkx2-5 that disrupted CM formation. Our findings show the coexistence of two post-translationally modified STAT3α isoforms with distinct functions and define a new role for STAT3 as a molecular adaptor that functions independently of its canonical transcriptional activity during human cardiogenesis. Stem Cells 2017;35:2129-2137.

Primary focal segmental glomerulosclerosis recurring rapidly as collapsing glomerulopathy in a renal allograft recipient.

Recurrent focal segmental glomerulosclerosis (FSGS) develops in about 30%-40% of patients of FSGS undergoing renal transplantation. We report a patient who received a live- related renal transplant for end-stage renal disease due to a primary FSGS (not otherwise specified) in the native kidney and presented with graft dysfunction in the immediate posttransplant period. The first and the second biopsy showed no evidence of rejection or glomerular lesion. A repeat biopsy done on the 30th day revealed recurrent FSGS morphologically presenting as collapsing variant. The patient was found to have massive proteinuria. Electron microscopy done retrospectively showed glomerular foot process effacement even in the first biopsy. This case highlights the presence of an early minimal change disease-like phase in recurrent FSGS and the necessity of evaluation for proteinuria even in immediate and early posttransplant period. It also shows that different variants of FSGS may represent a spectrum of the same disease and suggests a likely role of a pathogenic circulating factor even in collapsing FSGS requiring further evaluation.