Angiotensin-converting enzyme 2 is reduced in Alzheimer's disease in association with increasing amyloid-β and tau pathology

BACKGROUND: Hyperactivity of the classical axis of the renin-angiotensin system (RAS), mediated by angiotensin II (Ang II) activation of the angiotensin II type 1 receptor (AT1R), is implicated in the pathogenesis of Alzheimer’s disease (AD). Angiotensin-converting enzyme-2 (ACE-2) degrades Ang II to angiotensin 1–7 (Ang (1-7)) and counter-regulates the classical axis of RAS. We have investigated the expression and distribution of ACE-2 in post-mortem human brain tissue in relation to AD pathology and classical RAS axis activity. METHODS: We measured ACE-2 activity by fluorogenic peptide substrate assay in mid-frontal cortex (Brodmann area 9) in a cohort of AD (n = 90) and age-matched non-demented controls (n = 59) for which we have previous data on ACE-1 activity, amyloid β (Aβ) level and tau pathology, as well as known ACE1 (rs1799752) indel polymorphism, apolipoprotein E (APOE) genotype, and cerebral amyloid angiopathy severity scores. RESULTS: ACE-2 activity was significantly reduced in AD compared with age-matched controls (P < 0.0001) and correlated inversely with levels of Aβ (r = −0.267, P < 0.001) and phosphorylated tau (p-tau) pathology (r = −0.327, P < 0.01). ACE-2 was reduced in individuals possessing an APOE ε4 allele (P < 0.05) and was associated with ACE1 indel polymorphism (P < 0.05), with lower ACE-2 activity in individuals homozygous for the ACE1 insertion AD risk allele. ACE-2 activity correlated inversely with ACE-1 activity (r = −0.453, P < 0.0001), and the ratio of ACE-1 to ACE-2 was significantly elevated in AD (P < 0.0001). Finally, we show that the ratio of Ang II to Ang (1–7) (a proxy measure of ACE-2 activity indicating  conversion of Ang II to Ang (1–7)) is reduced in AD. CONCLUSIONS: Together, our findings indicate that ACE-2 activity is reduced in AD and is an important regulator of the central classical ACE-1/Ang II/AT1R axis of RAS, and also that dysregulation of this pathway likely plays a significant role in the pathogenesis of AD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13195-016-0217-7) contains supplementary material, which is available to authorized users

The Impact of Governance Mechanism on Performance and Survival of Entrepreneurial Firms

The dissertation consists of two essays. The first essay studies governance structures and their effectiveness for start-up companies and their survival. We utilize data from the Kauffman Survey, which tracks a sample of firms from their inceptions through their first eight years of existence. We hypothesize and find evidence that a startup\u27s governance system affects its survivability as well as its performance. We show that controlling for the firm size and the industry, cross-sectional variations in the performance of the start-up firms can be explained by governance variables; the presence of one or more independent board member on the board, the separation between the person holding the CEO position and the chair of the board. From the startup survival perspective, we show that the presence of one or more independent board member(s), the separation between CEO and board chair, and external funding are effective factors that promote a start-up\u27s longevity. The second essay studies the direct and indirect relations between Governance and firm survival and performance through Entrepreneurial Orientation. Entrepreneurial orientation (EO) is defined as the attributes, including innovativeness, autonomy, risk-taking attitude, proactiveness, and competitive aggressiveness, that a business organization displays at the time of entry. Several researchers have studied the linkage between EO and organizational performance as well as the survival rate of new firms and find conflicting results. Reasons for the contradictory results might very well be the way the researchers have defined the EO attributes and the data source they use which is based on subjective responses. In the hopes of reducing inconsistent results, we propose that it is the governance factors that influence the performance and survival of these firm via mediating role of entrepreneurial orientation. Governance factors remove the definition as well as data measurement problems. By using the 8-year longitudinal data of 4928 startups, we show that governance system significantly impacts a start-up’s performance and survival via entrepreneurial orientation

The Impact of Governance Mechanism on Performance and Survival of Entrepreneurial Firms

The dissertation consists of two essays. The first essay studies governance structures and their effectiveness for start-up companies and their survival. We utilize data from the Kauffman Survey, which tracks a sample of firms from their inceptions through their first eight years of existence. We hypothesize and find evidence that a startup\u27s governance system affects its survivability as well as its performance. We show that controlling for the firm size and the industry, cross-sectional variations in the performance of the start-up firms can be explained by governance variables; the presence of one or more independent board member on the board, the separation between the person holding the CEO position and the chair of the board. From the startup survival perspective, we show that the presence of one or more independent board member(s), the separation between CEO and board chair, and external funding are effective factors that promote a start-up\u27s longevity. The second essay studies the direct and indirect relations between Governance and firm survival and performance through Entrepreneurial Orientation. Entrepreneurial orientation (EO) is defined as the attributes, including innovativeness, autonomy, risk-taking attitude, proactiveness, and competitive aggressiveness, that a business organization displays at the time of entry. Several researchers have studied the linkage between EO and organizational performance as well as the survival rate of new firms and find conflicting results. Reasons for the contradictory results might very well be the way the researchers have defined the EO attributes and the data source they use which is based on subjective responses. In the hopes of reducing inconsistent results, we propose that it is the governance factors that influence the performance and survival of these firm via mediating role of entrepreneurial orientation. Governance factors remove the definition as well as data measurement problems. By using the 8-year longitudinal data of 4928 startups, we show that governance system significantly impacts a start-up’s performance and survival via entrepreneurial orientation

Isolation and identification of bioactive compounds from conradina canescens gray

Natural products have been used in traditional medicine throughout history. All drugs and medicinal agents were derived from natural substances or inspired by a natural product. The major source of these remedies is higher plants which are great sources for new compounds that have a wide variety of activity. Conradina canescens Gray (false rosemary) is a common evergreen shrub, endemic to a small area of west Florida and adjacent Alabama and southern parts of Mississippi, USA. There are very limited studies on the chemical composition of this plant species. According to the available literature, this species has not been tested for bioactivity or cytotoxicity, except for allelopathy. In this work, the essential oil was isolated using hydrodistillation and was analyzed using GC/MS. The essential oil of C. canescens was found to be rich in monoterpenoids, particularly 1,8-cineole, myrtenal, p-cymene, camphor, myrtenol, myrtenyl acetate, and α-pinene. C. canescens oil was screened for antimicrobial activity and cytotoxic activity but was found to be inactive. However, the oil showed remarkable allelopathic effects on both Lactuca sativa and Lolium perenne. Because its oil chemical composition is comparable to rosemary, C. canescens may be a useful and beneficial herb. A total of six compounds, namely ursolic acid (62.40%), betulin (8.41%), β-amyrin (4.60%), myrtenic acid (2.88%), n-tetracosane (1.44%), and oleanolic acid (1.05%), were isolated. The structures of the isolated compounds were established by spectroscopic studies using NMR and IR spectroscopy. The crude extract and isolated compounds were subjected to cytotoxicity, antimicrobial and antileishmanial bioassays. The crude extract showed substantial cytotoxic, antimicrobial and antileishmanial activities. Ursolic acid and betulin showed significant cytotoxic effects against human breast cancer (MCF-7 and MDA-MB-231) and bladder cancer (5637) cell lines emphasizing a medicinal importance of the plant. n-Tetracosane exhibited the most antibacterial activity while myrtenic acid showed the highest antifungal activity. Almost all the tested compounds, except betulin and n-tetracosane, showed significant germination inhibition of both L. sativa and L. perenne in a concentration-dependent manner, with ursolic acid being the most active. The results of the current study emphasize the potential medicinal and economic importance of C. canescens

Authentication Solutions in Industrial Internet of Things: A Survey

With the rapid growth of industry 4.0, the Industrial Internet of Things (IIoT) is considered to be a promising solution for converting normal operations to ‘smart’ operations in industrial sectors and systems. The well-known characteristics of IIoT has greatly improved the productivity and quality of many industrial sectors. IIoT allows the connectivity of many industrial smart devices such as, sensors, actuators and gateways. The connectivity feature makes this critical environment vulnerable to various cybersecurity attacks. Subsequently, maintaining the security of IIoT sys-tems remains a challenge to ensure their success. In particular, authenticating the connected IIoT devices is a must to ensure that they can be trusted and prevent any malicious attempts. Hence, the objective of this survey is to overview, discuss and analyze the different solutions related to de-vice authentication in the domain of IIoT. Also, we analyze the IIoT environment in terms of characteristics, architecture and security requirements. Similarly, we highlight the role of (machine-to-machine) M2M communication in IIoT. We further contribute to this survey by outlining several open issues that must be considered when designing authentication schemes for IIoT. Fi-nally, we highlight a number of research directions and open challenges

The Effects of TeleWound Management on Use of Service and Financial Outcomes

This study investigated the effects of a TeleWound program on the use of service and financial outcomes among homebound patients with chronic wounds. The TeleWound program consisted of a Web-based transmission of digital photographs together with a clinical protocol. It enabled homebound patients with chronic pressure ulcers to be monitored remotely by a plastic surgeon. Chronic wounds are highly prevalent among chronically ill patients in the United States (U.S.). About 5 million chronically ill patients in the U.S. have chronic wounds, and the aggregate cost of their care exceeds $20 billion annually. Although 25% of home care referrals in the U.S. are for wounds, less than 0.2% of the registered nurses in the U.S. are wound care certified. This implies that the majority of patients with chronic wounds may not be receiving optimal care in their home environments. We hypothesized that TeleWound management would reduce visits to the emergency department (ED), hospitalization, length of stay, and visit acuity. Hence, it would improve financial performance for the hospital. A quasi-experimental design was used. A sample of 19 patients receiving this intervention was observed prospectively for 2 years. This was matched to a historical control group of an additional 19 patients from hospital records. Findings from the study revealed that TeleWound patients had fewer ED visits, fewer hospitalizations, and shorter length of stay, as compared to the control group. Overall, they encumbered lower cost. The results of this clinical study are striking and provide strong encouragement that a single provider can affect positive clinical and financial outcomes using a telemedicine wound care program. TeleWound was found to be a credible modality to manage pressure ulcers at lower cost and possibly better health outcomes. The next step in this process is to integrate the model into daily practice at bellwether medical centers to determine programmatic effectiveness in larger clinical arenas.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63389/1/tmj.2007.9971.pd

Convolutional neural network in the classification of COVID-19

Covid-19 spread out rapidly around the world, forcing many countries to full shutdown, and economical and social consequences. Resulting in rapid need for new and effective methods to deal with this crisis and control it. X-ray lung images is considered one of the most effective and safe method for diagnosing Covid-19, since it could provide solid proof of the existing of the disease, and it has limited effect on the health of the human comparing with other radiography methods. In this proposed work, CNN model is designed and trained to classify Covid-19 X-ray images, by using the COVID-19 Radiography Database, which is published and available online. This database is collected by researchers and experts from various universities around the world. The database contains total of 15153 lung x-ray images, divided into three classes. The classification classes are: Normal, Covid-19, and Viral Pneumonia. The model is trained and tested on publicly available dataset. The dataset is divided into three parts: training, validation, and testing datasets. The model is evaluated based on the three of these datasets. Totally, the evaluation metrics include Accuracy, F1-score, Area Under Curve (AUC), Precision, and Recall, with values of greater than 98% for all of the evaluation metrics. Comparing the results with state of arts publications, which used the same dataset, the proposed method outperformed the state of arts publications depending on the evaluation metrics. The number of the trainable parameters in the proposed CNN model is about 25.4 millions

Convolutional neural network in the classification of COVID-19

Covid-19 spread out rapidly around the world, forcing many countries to full shutdown, and economical and social consequences. Resulting in rapid need for new and effective methods to deal with this crisis and control it. X-ray lung images is considered one of the most effective and safe method for diagnosing Covid-19, since it could provide solid proof of the existing of the disease, and it has limited effect on the health of the human comparing with other radiography methods. In this proposed work, CNN model is designed and trained to classify Covid-19 X-ray images, by using the COVID-19 Radiography Database, which is published and available online. This database is collected by researchers and experts from various universities around the world. The database contains total of 15153 lung x-ray images, divided into three classes. The classification classes are: Normal, Covid-19, and Viral Pneumonia. The model is trained and tested on publicly available dataset. The dataset is divided into three parts: training, validation, and testing datasets. The model is evaluated based on the three of these datasets. Totally, the evaluation metrics include Accuracy, F1-score, Area Under Curve (AUC), Precision, and Recall, with values of greater than 98% for all of the evaluation metrics. Comparing the results with state of arts publications, which used the same dataset, the proposed method outperformed the state of arts publications depending on the evaluation metrics. The number of the trainable parameters in the proposed CNN model is about 25.4 millions