Deciphering and fine-tuning of myeloid cells in CNS demyelinating conditions

Demyelination in the central nervous system (CNS) is a characteristic of various neurological disorders, such as multiple sclerosis (MS), neuromyelitis optica (NMO), subacute combined degeneration (SCD), tabes dorsalis (syphilitic myelopathy), and more. Although the causes vary, CNS demyelination is often associated with a significant buildup of inflammatory activated myeloid cells, mainly consisting of CNS resident microglia and infiltrating monocyte-derived macrophages. On one hand, these myeloid cells can contribute to inflammation in the CNS and damage myelin, but on the other hand, they play a role in clearing myelin debris and releasing substances that facilitate myelin regeneration, a process known as remyelination. Therefore, it is crucial to determine the signals that control their specific functions and develop methods for regulating their activity. In this thesis, we investigated the role of TGF-β signaling in regulating myeloid cell function. By using cell-specific targeting mouse tools, we discovered that when the CNS lacks microglia in a specific experimental setting, where peripheral monocytes can enter the CNS and repopulate the microglia pool by transforming into microglia-like macrophages, deleting the TGF-β receptor (TGFBR2) on monocytes prevents their entry into the CNS. Furthermore, when monocyte-derived macrophages are engrafted in the CNS, the depletion of TGFBR2 causes their abnormal activation and failure to adopt a microglia-like signature, leading to spontaneous demyelination in the spinal cord and a progressive, fatal motor disease. The loss of TGF- β signaling in microglia or monocyte-derived microglia-like cells preferentially targets myelin in the dorsal column of the spinal cord, and a subpopulation of microglia closely associated with myelin loss is identified in the dorsal column. We further characterized that this microglial TGF-β signaling loss-induced disease is more severe in female and older mice and uncovered potential molecular mechanisms underlying these gender and age differences in response to the loss of TGF-β signaling. In addition to deciphering the mechanisms governing myeloid function, we also conducted translational studies aiming to provide therapeutic insights for demyelinating diseases. By using a drug screening tool and performing in vitro validation, as well as experiments in mouse models with CNS inflammation and ensuing demyelination, we confirmed the regulatory effect of topotecan, a topoisomerase 1 inhibitor, on myeloid cells, leading to improved disease outcome. We further developed a DNA nanostructure-based drug delivery system to encapsule topotecan and achieve specific targeting of TOP1 in myeloid cells, demonstrating that myeloid cell-specific inhibition of TOP1 could alleviate neuroinflammation. In the final study, within a non-inflammation-driven demyelinating context, we studied the role of TRPV1 activation in remyelination and revealed that the TRPV1 activator capsaicin could enhance microglial clearance of myelin debris following demyelination and promote remyelination. My thesis work thus provides mechanistic understanding of how myeloid cells regulate myelin health and CNS homeostasis, while also providing regulatory strategies for fine-tuning these cells

Disclosure relevance and earnings management in business group: evidence from UK private subsidiaries

Corporate financial disclosure is widely agreed to be important to the general stakeholders as it reduces information asymmetries between managers and investors (Marquardt and Wiedman, 1998; Lang and Lundholm, 2000), arguably improves the information precision in financial statements (Lambert et al., 2012; Hughes and Pae, 2004), provides more financial and non-financial information for valuation and thus mitigates mispricing (Jegadeesh and Livnat, 2006). However, such disclosure requirements are made only to publicly traded companies (business group). Privately held companies do not often have public disclosure requirements from either regulators or standards setters. Only when these private companies engage in related party transactions with a publicly traded business group, such transactions are sometimes required to be disclosed. This may lead to manipulation that could be concealed by a parent company through their private subsidiaries - if manipulated items are excluded from related party transactions. Supported by the evidence that companies do often hide and manipulate information that should be disclosed (Kim and Yi, 2006; Beuselinck and Deloof, 2014; Beatty and Harris, 2001; Weil, 1980), this area can potentially be a grey area where public companies avoid disclosure responsibility and benefit privileged few at the expense of the investing public. The objective of this dissertation is to examine whether disclosure of private subsidiaries matters and to what extent such disclosure matters. Test is done through an investigation of publicly traded companies’ earnings management activity via their private subsidiaries. Earnings management is selected because it often represents reporting quality and also reflects companies’ motivations under different scenarios (Ball and Shivakumar, 2005; Burgstahler et al., 2006). On the one side, companies hope to manage earnings so that their aimed targets can be achieved. On the other side, they also do not want to show a high level of earnings management which is perceived as bad reporting quality. From such conflicted interests, this becomes important to test how company would moderate different interests to balance and maximize the overall utility. Empirical results in this dissertation show subsidiary information disclosure is relevant to group reporting quality, as proxied by earnings management. That is, business group shows a lower level of earnings management and hence better reporting quality when they have qualifying subsidiaries. Qualifying subsidiaries are defined as subsidiaries that are controlled by the group (i.e. a business group having more than 50% of the voting rights), not in regulated industries and non-foreign (i.e. domestic subsidiaries only). Further, there is a substitute effect between group level of earnings management and subsidiary level of earnings management. That is, when group shows a lower level of earnings management, their subsidiaries show a higher level of earnings management. This proves that group firms shift their earnings management needs at subsidiary level, especially private subsidiaries. By taking the cover of being private and being a subsidiary, they are far away from auditor scrutiny and public attention, and hence are the safest channel to satisfy earnings management needs. Further analysis shows that subsidiary number, subsidiary size, subsidiary industry and subsidiary revenue is relevant to group level of earnings management. From that, group firm selection preference may be snooped when they are considering using private subsidiaries to shift the pressure of earnings management and hence improve the reporting quality of themselves. One interesting finding in this dissertation is that auditor is not effective in detecting earnings management at subsidiary level. Although most of the existing literature reveals that Big4 auditors mitigate earnings management, finding in this dissertation shows that such mitigation influence is only effective at business group level but not at subsidiary level. More specifically, there is a positive relationship between subsidiary earnings management and Big4 auditors. That is, subsidiaries audited by Big4 show a higher level of earnings management. This further enhances the assertation that business groups push down their earnings management needs at their subsidiary level. The contributions of this dissertation are threefold. First, as private subsidiaries face substantively minimum disclosure requirements, this dissertation provides evidence and insights to regulators and standard setters on why and how to set up high quality disclosure requirements to better protect stakeholders’ benefits. Second, it contributes to the general stakeholders that existing and potential investors should use the information more cautiously when a private subsidiary is involved. Third, this dissertation also contributes to the literature of earnings management in different ways. While most of the literature on earnings management looks at the final output of the consolidation process with an extensive focus on public companies, this dissertation tries to shed light on earnings management at private companies given their economic importance. I further trace down the earnings management practice at private subsidiaries’ level, which is a relatively new perspective and a new way that has rarely been examined and filed in the past (Bonacchi et al., 2018; Beuselinck et al., 2019). To our best knowledge, this method is the first work in earnings management with a focus of improving disclosure quality. The ongoing debate of the financial reporting quality (FRQ) between public and private companies may also be shaped if private subsidiary plays a role. It may then suggest that debate of FRQ between public and private companies is not that debatable unless the effect of private subsidiary is completely removed, which provides space for future research. Finally, this dissertation provides further insights in terms of auditor effectiveness. In particular, the effectiveness of auditor depends on the level of a firm in a business group. Auditor is more effective at business group level as most of literature shows, but not effective at private subsidiary level. This not only refines the past cognition on auditor role in detecting and preventing earnings management, but also provides spaces for further research in examining overall auditor role at different levels in business groups

PPG-based Heart Rate Estimation with Efficient Sensor Sampling and Learning Models

Recent studies showed that Photoplethysmography (PPG) sensors embedded in wearable devices can estimate heart rate (HR) with high accuracy. However, despite of prior research efforts, applying PPG sensor based HR estimation to embedded devices still faces challenges due to the energy-intensive high-frequency PPG sampling and the resource-intensive machine-learning models. In this work, we aim to explore HR estimation techniques that are more suitable for lower-power and resource-constrained embedded devices. More specifically, we seek to design techniques that could provide high-accuracy HR estimation with low-frequency PPG sampling, small model size, and fast inference time. First, we show that by combining signal processing and ML, it is possible to reduce the PPG sampling frequency from 125 Hz to only 25 Hz while providing higher HR estimation accuracy. This combination also helps to reduce the ML model feature size, leading to smaller models. Additionally, we present a comprehensive analysis on different ML models and feature sizes to compare their accuracy, model size, and inference time. The models explored include Decision Tree (DT), Random Forest (RF), K-nearest neighbor (KNN), Support vector machines (SVM), and Multi-layer perceptron (MLP). Experiments were conducted using both a widely-utilized dataset and our self-collected dataset. The experimental results show that our method by combining signal processing and ML had only 5% error for HR estimation using low-frequency PPG data. Moreover, our analysis showed that DT models with 10 to 20 input features usually have good accuracy, while are several magnitude smaller in model sizes and faster in inference time

COVID-19 Models for Hospital Surge Capacity Planning: A Systematic Review

Objective: Health system preparedness for coronavirus disease (COVID-19) includes projecting the number and timing of cases requiring various types of treatment. Several tools were developed to assist in this planning process. This review highlights models that project both caseload and hospital capacity requirements over time. Methods: We systematically reviewed the medical and engineering literature according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We completed searches using PubMed, EMBASE, ISI Web of Science, Google Scholar, and the Google search engine. Results: The search strategy identified 690 articles. For a detailed review, we selected 6 models that met our predefined criteria. Half of the models did not include age-stratified parameters, and only 1 included the option to represent a second wave. Hospital patient flow was simplified in all models; however, some considered more complex patient pathways. One model included fatality ratios with length of stay (LOS) adjustments for survivors versus those who die, and accommodated different LOS for critical care patients with or without a ventilator. Conclusion: The results of our study provide information to physicians, hospital administrators, emergency response personnel, and governmental agencies on available models for preparing scenario-based plans for responding to the COVID-19 or similar type of outbreak

Relatório de estágio em farmácia comunitária

Relatório de estágio realizado no âmbito do Mestrado Integrado em Ciências Farmacêuticas, apresentado à Faculdade de Farmácia da Universidade de Coimbr

Disclosure relevance and earnings management in business group: evidence from UK private subsidiaries

Corporate financial disclosure is widely agreed to be important to the general stakeholders as it reduces information asymmetries between managers and investors (Marquardt and Wiedman, 1998; Lang and Lundholm, 2000), arguably improves the information precision in financial statements (Lambert et al., 2012; Hughes and Pae, 2004), provides more financial and non-financial information for valuation and thus mitigates mispricing (Jegadeesh and Livnat, 2006). However, such disclosure requirements are made only to publicly traded companies (business group). Privately held companies do not often have public disclosure requirements from either regulators or standards setters. Only when these private companies engage in related party transactions with a publicly traded business group, such transactions are sometimes required to be disclosed. This may lead to manipulation that could be concealed by a parent company through their private subsidiaries - if manipulated items are excluded from related party transactions. Supported by the evidence that companies do often hide and manipulate information that should be disclosed (Kim and Yi, 2006; Beuselinck and Deloof, 2014; Beatty and Harris, 2001; Weil, 1980), this area can potentially be a grey area where public companies avoid disclosure responsibility and benefit privileged few at the expense of the investing public. The objective of this dissertation is to examine whether disclosure of private subsidiaries matters and to what extent such disclosure matters. Test is done through an investigation of publicly traded companies’ earnings management activity via their private subsidiaries. Earnings management is selected because it often represents reporting quality and also reflects companies’ motivations under different scenarios (Ball and Shivakumar, 2005; Burgstahler et al., 2006). On the one side, companies hope to manage earnings so that their aimed targets can be achieved. On the other side, they also do not want to show a high level of earnings management which is perceived as bad reporting quality. From such conflicted interests, this becomes important to test how company would moderate different interests to balance and maximize the overall utility. Empirical results in this dissertation show subsidiary information disclosure is relevant to group reporting quality, as proxied by earnings management. That is, business group shows a lower level of earnings management and hence better reporting quality when they have qualifying subsidiaries. Qualifying subsidiaries are defined as subsidiaries that are controlled by the group (i.e. a business group having more than 50% of the voting rights), not in regulated industries and non-foreign (i.e. domestic subsidiaries only). Further, there is a substitute effect between group level of earnings management and subsidiary level of earnings management. That is, when group shows a lower level of earnings management, their subsidiaries show a higher level of earnings management. This proves that group firms shift their earnings management needs at subsidiary level, especially private subsidiaries. By taking the cover of being private and being a subsidiary, they are far away from auditor scrutiny and public attention, and hence are the safest channel to satisfy earnings management needs. Further analysis shows that subsidiary number, subsidiary size, subsidiary industry and subsidiary revenue is relevant to group level of earnings management. From that, group firm selection preference may be snooped when they are considering using private subsidiaries to shift the pressure of earnings management and hence improve the reporting quality of themselves. One interesting finding in this dissertation is that auditor is not effective in detecting earnings management at subsidiary level. Although most of the existing literature reveals that Big4 auditors mitigate earnings management, finding in this dissertation shows that such mitigation influence is only effective at business group level but not at subsidiary level. More specifically, there is a positive relationship between subsidiary earnings management and Big4 auditors. That is, subsidiaries audited by Big4 show a higher level of earnings management. This further enhances the assertation that business groups push down their earnings management needs at their subsidiary level. The contributions of this dissertation are threefold. First, as private subsidiaries face substantively minimum disclosure requirements, this dissertation provides evidence and insights to regulators and standard setters on why and how to set up high quality disclosure requirements to better protect stakeholders’ benefits. Second, it contributes to the general stakeholders that existing and potential investors should use the information more cautiously when a private subsidiary is involved. Third, this dissertation also contributes to the literature of earnings management in different ways. While most of the literature on earnings management looks at the final output of the consolidation process with an extensive focus on public companies, this dissertation tries to shed light on earnings management at private companies given their economic importance. I further trace down the earnings management practice at private subsidiaries’ level, which is a relatively new perspective and a new way that has rarely been examined and filed in the past (Bonacchi et al., 2018; Beuselinck et al., 2019). To our best knowledge, this method is the first work in earnings management with a focus of improving disclosure quality. The ongoing debate of the financial reporting quality (FRQ) between public and private companies may also be shaped if private subsidiary plays a role. It may then suggest that debate of FRQ between public and private companies is not that debatable unless the effect of private subsidiary is completely removed, which provides space for future research. Finally, this dissertation provides further insights in terms of auditor effectiveness. In particular, the effectiveness of auditor depends on the level of a firm in a business group. Auditor is more effective at business group level as most of literature shows, but not effective at private subsidiary level. This not only refines the past cognition on auditor role in detecting and preventing earnings management, but also provides spaces for further research in examining overall auditor role at different levels in business groups

Axonal mitochondria adjust in size depending on g-ratio of surrounding myelin during homeostasis and advanced remyelination

Demyelinating pathology is common in many neurological diseases such as multiple sclerosis, stroke, and Alzheimer's disease and results in axonal energy deficiency, dysfunctional axonal propagation, and neurodegeneration. During myelin repair and also during myelin homeostasis, mutual regulative processes between axons and myelin sheaths are known to be essential. However, proficient tools are lacking to characterize axon-myelin interdependence during (re)myelination. Thus, we herein investigated adaptions in myelin sheath g-ratio as a proxy for myelin thickness and axon metabolic status during homeostasis and myelin repair, by using axonal mitochondrial size as a proxy for axonal metabolic status. We found that axons with thinner myelin sheaths had larger axonal mitochondria; this was true for across different central nervous system tracts as well as across species, including humans. The link between myelin sheath thickness and mitochondrial size was temporarily absent during demyelination but reestablished during advanced remyelination, as shown in two commonly used animal models of toxic demyelination. By further exploring this association in mice with either genetically induced mitochondrial or myelin dysfunction, we show that axonal mitochondrial size adjusts in response to the thickness of the myelin sheath but not vice versa. This pinpoints the relevance of mitochondrial adaptation upon myelin repair and might open a new therapeutic window for remyelinating therapies

Can Digital Inclusive Finance Improve the Financial Performance of SMEs?

Our paper takes the sample of listed companies from Shanghai and Shenzhen A-share SMEs and then theoretically analyzes and empirically tests the impact of digital inclusive finance on the financial performance of SMEs. The results show that financial performance of SMEs located in areas with a higher level of digital inclusive finance is significantly higher. Digital inclusive finance can play a role in expanding the scale of innovative investment, reducing the cost of debt financing and improving the ability of risk-taking, thereby strengthening the financial performance of SMEs. Our findings enrich the academic research on the topic of digital inclusive finance from the perspective of SMEs and provide suggestions to the government, banks and SMEs to continually implement the digital inclusive finance policy

Can Digital Inclusive Finance Improve the Financial Performance of SMEs?

Our paper takes the sample of listed companies from Shanghai and Shenzhen A-share SMEs and then theoretically analyzes and empirically tests the impact of digital inclusive finance on the financial performance of SMEs. The results show that financial performance of SMEs located in areas with a higher level of digital inclusive finance is significantly higher. Digital inclusive finance can play a role in expanding the scale of innovative investment, reducing the cost of debt financing and improving the ability of risk-taking, thereby strengthening the financial performance of SMEs. Our findings enrich the academic research on the topic of digital inclusive finance from the perspective of SMEs and provide suggestions to the government, banks and SMEs to continually implement the digital inclusive finance policy