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Oral anticoagulant therapy (OAT) for managing atrial fibrillation (AF) encompasses vitamin K antagonists (VKAs, such as warfarin), which was the mainstay of anticoagulation therapy before 2010, and direct-acting oral anticoagulants (DOACs, namely dabigatran etexilate, rivaroxaban, apixaban, edoxaban), approved for the prevention of AF stroke over the last thirteen years. Due to the lower risk of major bleeding associated with DOACs, anticoagulant switching is a common practice in AF patients. Nevertheless, there are issues related to OAT switching that still need to be fully understood, especially for patients in whom AF and heart failure (HF) coexist. Herein, the effective impact of the therapeutic switching from warfarin to DOACs in HF patients with AF, in terms of cardiac remodeling, clinical status, endothelial function and inflammatory biomarkers, was assessed by a machine learning (ML) analysis of a clinical database, which ultimately shed light on the real positive and pleiotropic effects mediated by DOACs in addition to their anticoagulant activity. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to empirically test the economic convergence that operate between five selected Asian countries (namely Thailand, Singapore, Malaysia, the Philippines and Indonesia). In particular, it seeks to investigate how increased economic integration has impacted the inter-country income levels among the five founding members of ASEAN. Design/methodology/approach: A new Machine Learning (ML) approach is applied along with a panel data analysis (GMM), and the application of KOF Globalization Index. Findings: The Generalized Method of Moments (GMM) results highlight that the endogenous growth theory seems to be supported for the selected Asian countries, indicating evidence of diverging forces resulting from unequal growth and polarization dynamics. Overcoming the technical issues raised by the econometric approach, the new ML algorithm brings contrasted but interesting results. Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members. Originality/value: Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members. As a matter of fact, the new LSTM algorithm has provided consistent evidence supporting the existence of converging forces. In fact, the results highlighted the effectiveness of the experiments and the algorithm we chose. The high predictability of the authors' model and the absence of self-alignment in the values showed a convergence be-tween the economies. [ABSTRACT FROM AUTHOR]

• Oil product consumption and CO 2 emissions sharply influence the transport logistics indexes. • A feedback relationship is discovered for environmental pollution, indicating that oil use is not significantly driven by supply chain performance. • We found empirical sustain for the "feedback hypothesis" for Germany and Japan. This paper critically assesses the effect of fossil fuel dependence and polluting emissions from the transport sector on the performance of logistics operations in the context of Green Supply Chain Management (GSCM). We collected macro-level time-series data for a sample of 27 European Union (EU) countries over the period 2007–2018. A new Artificial Neural Networks (ANNs) algorithm is adopted in a multivariate framework to investigate the dynamic interactions among a range of Logistics Performance Indexes (LPI), the demand for oil products, and carbon dioxide (CO 2) emissions from fuel combustion in the transport sector. Empirical findings show that oil product consumption and CO 2 emissions sharply influence the transport logistics indexes. However, a feedback relationship is discovered for environmental pollution, indicating that oil use is not significantly driven by supply chain performance. Based on our empirical insights, adequate policy recommendations are provided to help turning the logistics sector towards a more sustainable path in the European area. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the innovations introduced in the functions of the International Monetary Fund in the context of the 2008 economic and financial crisis. This promoted an action that aimed to strengthen the surveillance function through the adoption of the Integrated Surveillance. Thus, alongside the traditional conditionality based on an a posteriori implementation of adequate economic policies, a criterion of ex ante conditionality in the precautionary branches was also introduced or based on the economic characteristics of the country to be financed. Concerning traditional conditionality, it will be asked whether the IMF has adopted a less extensive approach than its role. [ABSTRACT FROM AUTHOR]

China, India, and the USA are the world's biggest energy consumers and CO 2 emitters. Being the leading contributors to climate change, these economies are also at the core of environmental solutions. This paper investigates the causal relationship among solar and wind energy production, coal consumption, economic growth, and CO 2 emissions for these three countries. To do so, we use an advanced methodology in Machine Learning to verify the predictive causal linkages among variables. The Causal Direction from Dependency (D2C) algorithm set CO 2 emissions as the target variable. The obtained results were disaggregated and estimated in a supervised prediction model. The findings, confirmed by three different Machine Learning procedures, showed an interesting output. While a reduction in overall carbon emissions is predicted in China and the US (resulting from the intensive use of renewable sources of energy), India displays critical predictions of a rise in CO 2 emissions. This indicates that curbing CO 2 emissions cannot be achieved without conducting a comprehensive shift from fossil to renewable resources, although China and the U.S. present a more promising path to sustainability than India. Being an emerging renewable energy leader, India should further enhance the use of low-carbon sources in its power supply and limit its dependence on coal. • Renewable energies, coal consumption, economic growth, and CO 2 we examine. • We investigate the causal predicted relationship on China, India, and the USA. • An advanced methodology in Machine Learning is used. • India has a prediction of an increase in emissions of CO 2. • China and the U.S. present a more promising path to sustainability than India. [ABSTRACT FROM AUTHOR]

• A bidirectional causal relationship between municipal solid waste generation and GDP emerges. • Waste recovery (recycling and composting) is a key driver in mitigating greenhouse gas emissions. • The D2C algorithm shows that more waste coincides with higher consumption and more significant economic growth. Municipal solid waste generation is becoming a prominent issue in the environmental arena. The aim of this paper is to investigate the relationship among municipal waste generation, greenhouse gas emissions, and GDP in Switzerland over the period 1990–2017. We apply both time series procedures (stationarity and causality tests) and a Machine Learning approach. Empirical findings underline a bidirectional causal relationship between municipal solid waste generation and GDP, indicating that the Environmental Kuznets Curve hypothesis holds for Switzerland. Moreover, we found that waste recovery (recycling and composting) is a key driver in mitigating greenhouse gas emissions. In fact, in the Tree Model, the probability that a change in the waste recovery variable could lead to a reduction in the greenhouse gas emissions registered a value of 87%. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Inflammatory Breast Cancer (IBC) is a distinct and rare type of breast cancer accounting for up to 6% of all breast cancer cases in Europe. The aim of this study was to investigate diagnostic methods, treatments, and outcome after IBC in patients treated at a single institution in Denmark. METHOD: All patients treated for IBC at Aarhus University Hospital between 2000 and 2014 were identified and included in the cohort. Survival was assessed using Kaplan-Meier curves and log-rank statistics. RESULTS: A total of 89 patients were identified with a median follow up of 3.6 years. The overall survival at 5 and 10 years were 41% and 18%, respectively. The disease free survival at 5 and 10 years were 47% and 27%, respectively. Thirty-four percent had distant metastasis at time of diagnosis. Patients with ER positive tumors had a significantly better overall survival than patients with ER negative tumors (p = 0.01). CONCLUSION: Despite a more aggressive systemic and loco-regional treatment today, IBC is still a very serious disease with a high mortality. [ABSTRACT FROM AUTHOR]

In case of unexplained post‐PCI coronary thrombosis, a HIT should be always considered. A pragmatic approach with bivalirudin may be reasonable, even in absence of confirmed laboratory diagnosis. [ABSTRACT FROM AUTHOR]

The aim of this study is to explore the nexus among CO2 emissions, energy use, and GDP in Russia using annual data ranging from 1970 to 2017. We first conduct time-series analyses (stationarity, structural breaks, and cointegration tests). Then, we present a new D2C algorithm, and we run a Machine Learning experiment. Comparing the results of the two approaches, we conclude that economic growth causes energy use and CO2 emissions. However, the critical analysis underlines how the variance decomposition justifies the qualitative approach of using economic growth to immediately implement expenses for the use of alternative energies able to reduce polluting emissions. Finally, robustness checks to validate the results through a new D2C algorithm are performed. In essence, we demonstrate the existence of causal links in sub-permanent states among these variables. [ABSTRACT FROM AUTHOR]

Carcinosarcoma of the breast is an extremely rare and highly aggressive breast tumor. It has two distinct malignant cell lines involving epithelial (carcinomatous) and mesenchymal (sarcomatous) components. The literature on the topic is sparse. We report a rare case of carcinosarcoma of the breast containing a small fraction of a pancytokeratin positive sarcomatous-appearing cell population i.e. a metaplastic cell population. The patient was treated with a multidisciplinary approach. [ABSTRACT FROM AUTHOR]

Metabolic and biochemical changes during breast carcinogenesis enhance cellular acid production. Extrusion of the acid load from the cancer cells raises intracellular pH, while it decreases extracellular pH creating an inverted pH gradient across the plasma membrane compared to normal cells and promoting cancer cell metabolism, proliferation, migration, and invasion. We investigated the effects of breast carcinogenesis on the mechanisms of cellular pH control using multicellular epithelial organoids freshly isolated from human primary breast carcinomas and matched normal breast tissue. Intracellular pH was measured by fluorescence microscopy, while protein expression was investigated by immunofluorescence imaging and immunoblotting. We found that cellular net acid extrusion increased during human breast carcinogenesis due to enhanced Na,HCO-cotransport, which created an alkaline shift (~0.3 units of magnitude) in steady-state intracellular pH of human primary breast carcinomas compared to normal breast tissue. Na/H-exchange activity and steady-state intracellular pH in the absence of CO/HCO were practically unaffected by breast carcinogenesis. These effects were evident under both acidic (pH 6.8, representative of the tumor microenvironment) and physiological (pH 7.4) extracellular conditions. Protein expression of the Na,HCO-cotransporter NBCn1 (SLC4A7), which has been linked to breast cancer susceptibility in multiple genome-wide association studies, was twofold higher in human breast carcinomas compared to matched normal breast tissue. Protein expression of the Na/H-exchanger NHE1 (SLC9A1) was markedly less affected. We propose that upregulated NBCn1 during human breast carcinogenesis contributes to the characteristic acid distribution within human breast carcinomas and thereby plays a pathophysiological role for breast cancer development and progression. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the causal links among export diversification, per capita income, and energy demand for 20 Asia-Pacific Economic Cooperation (APEC) countries. Human capital, industry share, and Foreign Direct Investments (FDI) are included within a multivariate framework. Using data covering the 1995–2018 period, an innovative sequential Artificial Neural Networks experiment is developed. Empirical results highlight that the export diversification index negatively affects the neural target corresponding to energy demand. Conversely, per capita GDP displays a significant influence on the acceleration of the same energy target. Hence, findings suggest that export diversification plays a mitigating role in the demand for energy, which is congruent with the literature. Moreover, economic growth is found to be substantially driven by export diversification, while no evidence of a causal effect is found among export diversification, human capital, and FDI. Such inferences are finally corroborated by a Decision Tree model, conducted as a final robustness check. In line with the Sustainable Development Goals (SDGs), adequate measures are suggested to improve energy savings along the supply chain, without hindering the economic performance of the Asian region. [ABSTRACT FROM AUTHOR]

A carcinoma arising in a fibroadenoma is a rare event, which often entails a diagnostic challenge. The most common type is the lobular carcinoma and secondary a ductal carcinoma. We present an extremely rare case of malignant development of an invasive apocrine carcinoma in a complex fibroadenoma and underline the importance for clinicians to recognize the possibility of benign and malignant co-existence especially in older women. [ABSTRACT FROM AUTHOR]

Background: Locoregional recurrence (LRR) after breast cancer is an independent predictor for later systemic disease and poor long-term outcome. As the surgical treatment is complex and often leaves the patient with extensive defects, reconstructive procedures involving flaps, and thus plastic surgical assistance, are often required. The aim of the present study was to evaluate our institution's approach to surgical treatment for locoregional recurrence of a breast cancer. Methods: In the present retrospective, single-centre study, we evaluate our experience with 12 patients who underwent surgery for locally recurrent breast cancer at Aarhus University Hospital between 2006 and 2010. Nine patients underwent wide local excision. The remaining three patients underwent full thickness chest wall resection. Results: There was no perioperative mortality and no major complications. Minor complications occurred in four (33 %) of the patients. Median overall survival was 22 months, regardless of the surgery being curative or palliative. A median disease-free survival of 18 months was achieved for patients having achieved radicality. Conclusions: Both wide local excision and full thickness chest wall resection offer the opportunity of local control and palliation in patients with LRR. The plastic surgical reconstructive procedures are associated with a low complication rate, and thus not postponing further adjuvant therapy. However, a multidisciplinary approach with a highly careful patient selection is critical in order to ensure the best outcome for the patient. Level of Evidence: Level IV, therapeutic study. [ABSTRACT FROM AUTHOR]

• The Belgium nuclear phase-out plan is analyzed. • A multivariate model through time-series analyses is implemented over the 1974–2019 period. • We develop and apply an innovative partial differential equations (PDE) algorithm. • Time-series and machine learning findings demonstrate suggests that the nuclear phase-out might neither adversely impact the economy's growth nor threaten the emission reduction target in the long-run. By 2025, Belgium will phase-out nuclear power. Unassessed so far, this policy reform may modify the economic and environmental channels through which energy and society interfere in this country. In this paper, we investigate whether this structural energy change may adversely impact the growth of the Belgian economy (i) and its ability to meet its long-term greenhouse gas emission targets (ii). A multivariate model comprising production factors (labor, capital, and exports), nuclear and renewable energy uses, total primary energy supply, economic growth, and CO 2 emissions from the power and heating sector is combined with real time-series data spanning the 1974–2019 period. The analysis consists in sequentially assessing two distinct nexuses (energy-economy and energy-economy-environment) over reduced- and augmented frameworks (excluding and including nuclear energy), and through a two-stage empirical strategy: time-series econometric estimations (Toda-Yamamoto causality test, Impulse Response Functions (IRFs), and the Auto-Regressive Distributed Lags (ARDL) and Machine Learning (ML) experiments with a Partial Differential Equations (PDEs) algorithm. For robustness purposes, we conduct two seminal tests which relate to dynamic predictive processes (T-Mat and Verticality tests). Besides confirming the time-series findings, our ML results highlight the necessity to timely manage the process of nuclear phase-out, along with a progressive deployment of installed renewable energy capacity. This should avoid additional economic costs, energy security threats, and undermining of climate targets. In doing so, this study combines macro-level nexus investigations with the politics and institutional determinants of nuclear energy reliance and seeks to bring inclusive knowledge on this topic. [ABSTRACT FROM AUTHOR]

This paper examines the linkages among Information and Communication Technologies (ICT) penetration, electricity consumption, economic growth, urbanization, and environmental pollution for 25 OECD countries over the 1990–2017 period. We first conduct several panel data analyses and then write and apply a new Machine Learning (ML) algorithm. Empirical findings show that ICT usage enhances economic growth, and it is also a crucial driver of electricity consumption, which, in turn, translates into polluting emissions. The ML results highlight internet usage emerges as a substantial CO 2 emissions-enabler, thus corroborating our panel data findings. Potential policy measures are discussed. • A unidirectional causal link from urbanization to carbon emissions is discovered. • The constant variation in the ICT penetration generates a predictive causality variation of the electricity consumption. • A unidirectional relationship from ICT penetration to CO 2 emissions emerges. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the causal relationship among renewable energy technologies, biomass energy consumption, per capita GDP, and CO 2 emissions for Germany. We constructed an innovative algorithm, the Quantum model, and applied it with Machine Learning experiments – through a software capable of emulating a quantum system – to data over the period of 1990–2018. This process is possible after eliminating the "irreversibility" of classical computations (unitary transformations) by making the process "reversible". The empirical findings support the powerful role of biomass energy in reducing carbon dioxide emissions, although the effect of renewable energy technology displays a much stronger magnitude. Moreover, income remains an important determinant of environmental pollution in Germany. • An innovative Machine Learning algorithm (the Quantum model) has been constructed and applied. • The empirical findings support the powerful role of biomass energy in reducing CO 2 emissions. • GDP represents an important determinant of environmental pollution in Germany. [ABSTRACT FROM AUTHOR]

The aim of this paper is to assess the relationship between COVID-19-related deaths, economic growth, PM 10 , PM 2.5, and NO 2 concentrations in New York state using city-level daily data through two Machine Learning experiments. PM 2.5 and NO 2 are the most significant pollutant agents responsible for facilitating COVID-19 attributed death rates. Besides, we found only six out of many tested causal inferences to be significant and true within the AUPRC analysis. In line with the causal findings, a unidirectional causal effect is found from PM 2.5 to Deaths, NO 2 to Deaths, and economic growth to both PM 2.5 and NO 2. Corroborating the first experiment, the causal results confirmed the capability of polluting variables (PM 2.5 to Deaths, NO 2 to Deaths) to accelerate COVID-19 deaths. In contrast, we found evidence that unsustainable economic growth predicts the dynamics of air pollutants. This shows how unsustainable economic growth could increase environmental pollution by escalating emissions of pollutant agents (PM 2.5 and NO 2) in New York state. [Display omitted] • We assess the effect of economic growth, PM 2.5 and NO 2 variations on COVID-19 deaths. • We employ two experimental approaches based on Deep Machine Learning. • PM 2.5 and NO 2 are the most significant air pollutant responsible for COVID-19 deaths. • Increasing levels of economic growth spur air pollution in New York state. [ABSTRACT FROM AUTHOR]

While Germany and Japan are going through major energy reforms, natural gas consumption is taking a growing share in their energy supply. This paper adopts a Machine Learning approach to assess the causal link between natural gas consumption and economic growth for both economies. A Causal Direction from Dependency (D2C) algorithm with the interconnection of the sub-class is employed using yearly data from 1970 to 2018. The interconnections of the sub-classes are found for both economies, indicating evidence of causalities operating in both directions. In addition, the propagation over the seven eras is linear and homogeneously continue for Japan, while this effect meets a stabilization phase in the fifth era for Germany. The empirical findings claim strong support for the existence of a bidirectional causality between these variables in Germany and Japan, which is in line with the "feedback hypothesis". Although the strength of this bidirectional relationship is clear for both economies, its time-propagation is expected to be longer for Japan. Accordingly, this study claims that the gas supply should be further strengthened to progressively replace the most polluting fuels (oil and coal) and ensure a feasible transition towards a renewable path. • The causal link between natural gas consumption and economic growth exists for both countries. • Predictive analysis highlights a propagation effect between natural gas consumption and economic growth for both economies. • We found empirical sustain for the "feedback hypothesis" for Germany and Japan. [ABSTRACT FROM AUTHOR]

This study represents the first empirical estimation of threshold values between nitrogen dioxide (NO 2) concentrations and COVID-19-related deaths in France. The concentration of NO 2 linked to COVID-19-related deaths in three major French cities were determined using Artificial Neural Networks experiments and a Causal Direction from Dependency (D2C) algorithm. The aim of the study was to evaluate the potential effects of NO 2 in spreading the epidemic. The underlying hypothesis is that NO 2 , as a precursor to secondary particulate matter formation, can foster COVID-19 and make the respiratory system more susceptible to this infection. Three different neural networks for the cities of Paris, Lyon and Marseille were built in this work, followed by the application of an innovative tool of cutting the signal from the inputs to the selected target. The results show that the threshold levels of NO 2 connected to COVID-19 range between 15.8 μg/m3 for Lyon, 21.8 μg/m3 for Marseille and 22.9 μg/m3 for Paris, which were significantly lower than the average annual concentration limit of 40 μg/m³ imposed by Directive 2008/50/EC of the European Parliament. • Machine Learning approach based on ANNs techniques is proposed on NO 2 concentrations and COVID-19 deaths. • Hourly data (41 consecutive days) for three French cities we use for our analysis. • Analysis on the effects of three different threshold levels of NO 2 compared to COVID-19 deaths. • New threshold values on NO 2 concentrations are proposed to policy makers. [ABSTRACT FROM AUTHOR]

Municipal solid waste (MSW) is one of the most urgent issues associated with economic growth and urban population. When untreated, it generates harmful and toxic substances spreading out into the soils. When treated, they produce an important amount of Greenhouse Gas (GHG) emissions directly contributing to global warming. With its promising path to sustainability, the Danish case is of high interest since estimated results are thought to bring useful information for policy purposes. Here, we exploit the most recent and available data period (1994–2017) and investigate the causal relationship between MSW generation per capita, income level, urbanization, and GHG emissions from the waste sector in Denmark. We use an experiment based on Artificial Neural Networks and the Breitung-Candelon Spectral Granger-causality test to understand how the variables, object of the study, manage to interact within a complex ecosystem such as the environment and waste. Through numerous tests in Machine Learning, we arrive at results that imply how economic growth, identifiable by changes in per capita GDP, affects the acceleration and the velocity of the neural signal with waste emissions. We observe a periodical shift from the traditional linear economy to a circular economy that has important policy implications. Unlabelled Image • In-depth assessment of Municipal Solid Waste Sustainability is presented. • We assess the effect of wealth and urban sprawl on sustainable waste management. • We observe that urbanization is the backbone of GHG emissions from waste. • We find a gradual shift from linear economy to circular economy. • Other countries can learn from Denmark's path towards sustainable waste management. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze the relationship among iron and steel industries, air pollution and economic growth in China. Using monthly time series from 2000 to 2017, we adopt a Long Short Term Memory (LSTM) approach. The empirical results show that the relationship between economic growth and steel production is very strong in the first stage. Furthermore, in our model, we can see that the reduction of polluting emissions is linked to the principle of sustainable development. In particular, this phenomenon lies in the economic growth model responsible for the future generation. [ABSTRACT FROM AUTHOR]

Being heavily dependent to oil products (mainly gasoline and diesel), the French transport sector is the main emitter of Particulate Matter (PMs) whose critical levels induce harmful health effects for urban inhabitants. We selected three major French cities (Paris, Lyon, and Marseille) to investigate the relationship between the Coronavirus Disease 19 (COVID-19) outbreak and air pollution. Using Artificial Neural Networks (ANNs) experiments, we have determined the concentration of PM 2.5 and PM 10 linked to COVID-19-related deaths. Our focus is on the potential effects of Particulate Matter (PM) in spreading the epidemic. The underlying hypothesis is that a pre-determined particulate concentration can foster COVID-19 and make the respiratory system more susceptible to this infection. The empirical strategy used an innovative Machine Learning (ML) methodology. In particular, through the so-called cutting technique in ANNs, we found new threshold levels of PM 2.5 and PM 10 connected to COVID-19: 17.4 µg/m3 (PM 2.5) and 29.6 µg/m3 (PM 10) for Paris; 15.6 µg/m3 (PM 2.5) and 20.6 µg/m3 (PM 10) for Lyon; 14.3 µg/m3 (PM 2.5) and 22.04 µg/m3 (PM 10) for Marseille. Interestingly, all the threshold values identified by the ANNs are higher than the limits imposed by the European Parliament. Finally, a Causal Direction from Dependency (D2C) algorithm is applied to check the consistency of our findings. [ABSTRACT FROM AUTHOR]

Introduction. Melanocyte colonization of breast carcinoma by nonneoplastic melanocytes of epidermal origin is a rare and serious condition first described in 1977. We report on the exceptional clinical and pathological features of this migration phenomenon in a 74-year-old patient. Discussion. The pathogenesis by which melanocyte migration takes place is not known, but a breached basement membrane is considered essential. Conclusion. Histological examination and additional staining of skin are essential to differentiate breast cancer melanosis from malignant melanoma. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Breast adenomyoepithelioma is a very uncommon tumor, which is generally considered to be benign, however malignant transformation has been reported. PRESENTATION OF CASE: We report two cases of two women with breast adenomyoepithelioma. CONCLUSION: Diagnosis of adenomyoepithelioma is challenging because tumor may mimic other breast diseases. It has neither specific clinical signs nor radiological features, and the diagnosis is based on histopathological examination of the lesion. The treatment of choice is surgery. The type of surgery depends on the tumor factors and breast size. In malignant cases treatment such as radiotherapy, chemotherapy, immunotherapy may be used as well. It is very important to give an adequate treatment, otherwise the risk of tumor recurrence, growth or even metastatic spread, when tumor has malignant potential, increases. [ABSTRACT FROM AUTHOR]

Background: Na+,HCO3–-cotransporter NBCn1/Slc4a7 accelerates murine breast carcinogenesis. Lack of specific pharmacological tools previously restricted therapeutic targeting of NBCn1 and identification of NBCn1-dependent functions in human breast cancer. Methods: We develop extracellularly-targeted anti-NBCn1 antibodies, screen for functional activity on cells, and evaluate (a) mechanisms of intracellular pH regulation in human primary breast carcinomas, (b) proliferation, cell death, and tumor growth consequences of NBCn1 in triple-negative breast cancer, and (c) association of NBCn1-mediated Na+,HCO3–-cotransport with human breast cancer metastasis. Results: We identify high-affinity (KD ≈ 0.14 nM) anti-NBCn1 antibodies that block human NBCn1-mediated Na+,HCO3–-cotransport in cells, without cross-reactivity towards human NBCe1 or murine NBCn1. These anti-NBCn1 antibodies abolish Na+,HCO3–-cotransport activity in freshly isolated primary organoids from human breast carcinomas and lower net acid extrusion effectively in primary breast cancer tissue from patients with macrometastases in axillary lymph nodes. Inhibitory anti-NBCn1 antibodies decelerate tumor growth in vivo by ~50% in a patient-derived xenograft model of triple-negative breast cancer and pH-dependently reduce colony formation, cause G2/M-phase cell cycle accumulation, and increase apoptosis of metastatic triple-negative breast cancer cells in vitro. Conclusions: Inhibitory anti-NBCn1 antibodies block net acid extrusion in human breast cancer tissue, particularly from patients with disseminated disease, and pH-dependently limit triple-negative breast cancer growth. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to contribute to the collected knowledge of prognostic factors in primary breast sarcomas (PBS) to the benefit of possible future prospective studies and therapeutic guidelines.Method: All patients with pathologically verified PBS in the period of 1979–2014 were extracted from a hospital-based database at Aarhus University Hospital. All records were reviewed for patient and tumor characteristics. Primary endpoints were overall survival, disease-free survival (DFS) and disease-specific survival (DSS). Adjustments were made for age, tumor location, surgical strategy, size, histological classification, prior radiation and grade. Prognostic factors were determined by the use of Cox proportional hazard ratio.Results: In total 42 patients were identified. Surgical resection was the main method of treatment. Nineteen (45%) patients were initially selected for lumpectomy, of these 68% needed at least one re-excision to attain wide margins. In total 55% experienced recurrence, loco regional in 43%. Five-years overall survival was 49%, five-year DFS was 48% and five-year DSS was 40%. Significant prognostic factors were size and grade. A trend towards better survival in those with superficial tumors was observed as well as an increased incidence in radiation-induced angiosarcoma (AS) of the breast, however, prognosis was no different from non-radiation-induced AS.Conclusion: Prognostic factors in PBS patients were size and grade with a trend towards better survival in those with superficial tumors. There was no difference in survival between radiation-induced and spontaneous breast sarcomas. High rate of local recurrence suggests the need for aggressive surgical approach or the routine addition of postoperative radiotherapy in those selected for breast conserving surgery (BCS). [ABSTRACT FROM PUBLISHER]

Cardiac remodelling is an adverse phenomenon linked to heart failure progression and an important contributor to heart failure severity. Cardiac remodelling could represent the real therapeutic goal in the treatment of patients with heart failure with reduced ejection fraction, being potentially reversed through different pharmacotherapies. Currently, there are well-established drugs such as angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers and β-blockers with anti-remodelling effects; recently, angiotensin receptor neprilysin inhibitor effects on inhibiting cardiac remodelling (improving N-terminal pro-B-type natriuretic peptide levels, echocardiographic parameters of reverse cardiac remodelling and right ventricular function in patients with heart failure with reduced ejection fraction) were demonstrated. More recently, hemodynamic consequences of gliflozins, reduced cardiac hydrostatic pressure as a possible cause of ventricular remodelling and hypertrophy were proposed to explain potential anti-remodelling effects of gliflozins. Gliflozins exert their cardioprotective effects by attenuating myofibroblast activity and collagen-mediated remodelling. Another postulated mechanism is represented by the reduction in sympathetic activity, through the reduction in renal afferent nervous activity and the suppression of central reflex mechanisms. Benefits of gliflozins on left ventricular hypertrophy, dilation, and systolic and diastolic function were also described. In this review, we aimed to provide a wide overview on cardiac remodelling with a particular focus on possible anti-remodelling effects of angiotensin receptor neprilysin inhibitors and gliflozins. [ABSTRACT FROM AUTHOR]

decreased risk of breast cancer has been reported among patients given bisphosphonates. The present aims were to study potential associations between different antiosteoporosis drugs, including bisphosphonates, and the risk of breast cancer before and after start of treatment and to appraise possible dose-effect relationships. From national Danish registers, all female users of bisphosphonates aged ≥40 years and other drugs against osteoporosis between 1996 and 2006 were identified ( n = 87,104). This cohort was compared with a control group, where each patient was matched on age with three nonexposed women from the general population ( n = 261,322). Before start of most drugs against osteoporosis an increased risk of breast cancer was seen compared to controls (e.g., adjusted OR = 1.09, 95% CI 1.04-1.16 for alendronate). This excess risk was higher in younger women (e.g., OR = 4.48, 95% CI 2.98-6.75 for alendronate in women ≤50 years) and disappeared in women older than 70 years (e.g., OR = 0.95, 95% CI 0.88-1.01 for alendronate). In contrast, a decreased risk of breast cancer was seen after start of alendronate (HR = 0.53, 95% CI 0.38-0.73), etidronate (HR = 0.80, 95% CI 0.73-0.89), and raloxifene (HR = 0.53, 95% CI 0.38-0.73). No dose-response relationship was present for alendronate and etidronate, whereas a decreasing risk was seen with increasing daily dose of raloxifene. Bisphosphonate treatment in women was associated with a reduced risk of breast cancer. However, no causal relationship seemed to be present. [ABSTRACT FROM AUTHOR]

Breast cancer heterogeneity in histology and molecular subtype influences metabolic and proliferative activity and hence the acid load on cancer cells. We hypothesized that acid-base transporters and intracellular pH (pHi) dynamics contribute inter-individual variability in breast cancer aggressiveness and prognosis. We show that Na+,HCO3 -- cotransport and Na+/H+ exchange dominate cellular net acid extrusion in human breast carcinomas. Na+/H+ exchange elevates pHi preferentially in estrogen receptor-negative breast carcinomas, whereas Na+,HCO3 -- cotransport raises pHi more in invasive lobular than ductal breast carcinomas and in higher malignancy grade breast cancer. HER2-positive breast carcinomas have elevated protein expression of Na+/H+ exchanger NHE1/SLC9A1 and Na+,HCO3 -- cotransporter NBCn1/SLC4A7. Increased dependency on Na+,HCO3 -- cotransport associates with severe breast cancer: enlarged CO2/HCO3 -- -dependent rises in pHi predict accelerated cell proliferation, whereas enhanced CO2/HCO3 ---dependent net acid extrusion, elevated NBCn1 protein expression, and reduced NHE1 protein expression predict lymph node metastasis. Accordingly, we observe reduced survival for patients suffering from luminal A or basal-like/triple-negative breast cancer with high SLC4A7 and/or low SLC9A1 mRNA expression. We conclude that the molecular mechanisms of acid-base regulation depend on clinicopathological characteristics of breast cancer patients. NBCn1 expression and dependency on Na+,HCO3 -- cotransport for pHi regulation, measured in biopsies of human primary breast carcinomas, independently predict proliferative activity, lymph node metastasis, and patient survival. [ABSTRACT FROM AUTHOR]

Background:Validation studies of the Danish Breast Cancer Group (DBCG) registry show good agreement with medical records for adjuvant treatment data, but inconsistent recurrence information. No studies have validated changes in menopausal status or endocrine therapy during follow-up. In a longitudinal study, we validated DBCG data using medical records as the gold standard. Material and methods:From a cohort of 5959 premenopausal women diagnosed during 2002–2010 with stage I–III breast cancer, we selected 151 patients – 77 estrogen-receptor-positive and 74 estrogen-receptor-negative – from three hospitals. We assessed the validity of DBCG registry data on patient, tumor, and treatment factors, and follow-up information on menopausal transition, changes in endocrine therapy, and recurrence. We computed positive predictive values (PPVs) with 95% confidence intervals (95%CI). Results:Agreement was near perfect for tumor size, lymph node involvement, receptor status, surgery type, and receipt of radiotherapy, chemotherapy, or tamoxifen treatment. The PPV for a change in endocrine therapy in the DBCG was 96% (95%CI = 83, 100). The PPV for menopausal transition was 61% (95%CI = 42, 77). The PPV for DBCG-recorded recurrence was 100%. However, of 19 patients who had a recurrence documented in their medical record, 13 had the recurrence registered in DBCG. Conclusions:DBCG data are valid for most epidemiological studies of breast cancer treatment. Data on menopausal transition may be less valid, though this interpretation depends on the suitability of medical records for making this assessment. Although recurrence is missing for some, this would not bias most ratio measures of association. [ABSTRACT FROM PUBLISHER]

Cardiorenal syndrome encompasses a spectrum of disorders involving heart and kidney dysfunction, and sharing common risk factors, such as hypertension and diabetes. Clinical studies have shown that patients with and without diabetes may benefit from using sodium-glucose cotransporter 2 inhibitors to reduce the risk of heart failure and ameliorate renal endpoints. Because the underlying mechanisms remain elusive, we investigated the effects of dapagliflozin on the progression of renal damage, using a model of non-diabetic cardiorenal disease. Dahl salt-sensitive rats were fed a high-salt diet for five weeks and then randomized to dapagliflozin or vehicle for the following six weeks. After treatment with dapagliflozin, renal function resulted ameliorated as shown by decrease of albuminuria and urine albumin-to-creatinine ratio. Functional benefit was accompanied by a decreased accumulation of extracellular matrix and a reduced number of sclerotic glomeruli. Dapagliflozin significantly reduced expression of inflammatory and endothelial activation markers such as NF-κB and e-selectin. Upregulation of pro-oxidant-releasing NADPH oxidases 2 and 4 as well as downregulation of antioxidant enzymes were also counteracted by drug treatment. Our findings also evidenced the modulation of both classic and non-classic renin-angiotensin-aldosterone system (RAAS), and effects of dapagliflozin on gene expression of ion channels/transporters involved in renal homeostasis. Thus, in a non-diabetic model of cardiorenal syndrome, dapagliflozin provides renal protection by modulating inflammatory response, endothelial activation, fibrosis, oxidative stress, local RAAS and ion channels. [Display omitted] [ABSTRACT FROM AUTHOR]