Machine learning is playing an increasingly important role in the healthcare industry by transforming the way cancer is diagnosed and treated. By analyzing patient data, genomic data, and imaging data, machine learning algorithms can identify molecular signatures that distinguish cancer patients from healthy patients. Biomarkers that can accurately detect and diagnose cancer can be identified through analysis of these data sources. Additionally, personalized cancer therapies can be developed by identifying the most effective treatments based on individual patient characteristics and cancer type. Some of the machine learning techniques used for cancer biomarker discovery include deep learning and support vector machines, which can respectively identify complex patterns in data and classify data to identify relevant biomarkers. The benefits of using machine learning for cancer biomarker discovery are significant, including more precise and personalized treatments, improved patient outcomes, and the potential to transform cancer diagnosis and treatment. However, there are also challenges associated with using machine learning for cancer biomarker discovery, such as data collection and privacy issues, as well as the need for more powerful computational resources. This article explores the potential of machine learning in cancer biomarker discovery and argues that ongoing research in this field has the potential to revolutionize cancer diagnosis and treatment. Future research directions should focus on further developing machine learning algorithms and effective data collection and privacy protocols.

The present paper empirically examines the validity of the environmental Kuznets curve (EKC) hypothesis, which posits an inverted U-shaped relationship between CO2 emissions and economic growth, in Egypt, India, Mexico, Pakistan, Thailand, and Turkey for the period 1970-2020. The EKC validity is highly debated due to varying results across countries. This study is significant to addresses this controversy by estimating the EKC's robustness while considering the influence of financial development, globalization, and government expenditure. We employ two cointegration techniques, the autoregressive distributed lag (ARDL) and vector error correction model (VECM), also considering potential structural breaks in the data. Out key findings indicate that the EKC hypothesis is supported in India, Pakistan, and Turkey, with carbon emissions eventually declining after reaching a peak. The hypothesis is not supported in Egypt and Thailand, where emissions rise monotonically with economic growth. In Mexico, the results are mixed, with ARDL suggesting a U-shaped relationship and VECM supporting the EKC. From our empirical analysis of the EKC hypothesis, we derive the following policy implications: 1) countries should adopt comprehensive policy strategies that integrate these goals and fully consider the long-term environmental and societal impacts of their decisions; 2) countries should invest heavily in research and development to accelerate the creation of new technologies that can effectively reduce carbon emissions; and 3) countries must actively raise awareness about the environmental repercussions of economic growth.

There is a considerable amount of debate on the impact of capital liberalization on economic performance. Using Three-Stage Least Squares (3SLS) estimation technique introduced by Zellner and Theil (1962), we synthesize studies on the determinants of governance and capital flows. We find evidence of a revolving door relationship. Foreign aid has a negative impact on governance and, thereby reduces capital inflows since bad governance hinders capital inflows. The need to fill the gap created by private capital outflows encourages inflow of foreign aid, which in turn harms governance. Therefore, capital liberalization could grease a revolving door and undermine economic development in the aid receiving countries.

Using an international dataset, this letter finds that high stock returns are associated with increased death rates from drug use disorders. Although the out-of-pocket expenditure on healthcare also rises following a stock market surge, the net effect on life expectancy is significantly negative.

We examine the impact of environmental provisions in regional trade agreements (RTAs) on the environmentally harmful exports. Results show that environmental clauses in RTAs help reduce “dirty” exports, whereas RTA depth promotes exports. The exporting country may divert its polluting exports to its trading partner if it faces more environmental provisions with other countries.

Cancer, a global health menace, continues to pose significant challenges in terms of incidence and mortality, necessitating innovative therapeutic strategies. Despite existing treatments, the limitations persist, prompting a quest for novel approaches. The emergence of immunotherapy marked a transformative era in solid tumor treatments, yet its efficacy is constrained by adverse effects. Concurrently, the integration of advanced technologies into cancer treatment explores the vast potential residing at the molecular level through gene analysis and manipulation. This review articulates the role of state-of-the-art genome editing technology, notably clustered regularly interspaced short palindromic repeats (CRISPR-Cas9), in overcoming the constraints of immunotherapy for cancers. Unveiling the intricacies of CRISPR-Cas9-mediated genome editing, the review introduces the formidable CRISPR toolbox. A spotlight is cast on the transformative impact of CRISPR-induced double-strand breaks (DSBs) on cancer immunotherapy, encompassing knockout and knock-in strategies. The utilization of CRISPR/Cas9 technology in pre-clinical cancer research has demonstrated notable success; however, its transition to the clinical setting remains in the nascent stages of development. This review aims to elucidate the fundamental aspects of CRISPR technology and offer a comprehensive survey of its existing applications while outlining its prospective role in the realm of cancer therapies. Through an exploration of CRISPR's mechanisms, current applications, and anticipated future potentials, this review provides valuable insights into the evolving landscape of CRISPR-based cancer treatment strategies.

Although docetaxel treatment yields a high survival rate for prostate cancer (PCa), resistance eventually develops in many patients. Understanding the underlying mechanisms of docetaxel resistance is essential for improving treatment strategies. Cytokines, which play a role in cell signaling and immune responses, have been implicated in drug resistance mechanisms. The study revealed that interleukin-8 (IL-8) was consistently overexpressed in both docetaxel-resistant PCa cell lines. Thus, the expression levels of cytokines released from docetaxel-sensitive (PC-3- and DU-145) and resistant (PC-3/R-DU-145/R) PCa cells were compared. IL-8 was found to be commonly expressed in resistant cell lines. This finding led to the hypothesis that IL-8 could play a key role in mediating PCa cell resistance to docetaxel. IL-8 siRNA treatment increased docetaxel sensitivity in both resistant cells. To demonstrate the mechanism of IL-8-related resistance, MDR1 expression was evaluated. After IL-8 siRNA treatment MDR1 expression was reduced in both resistant cells suggesting that IL-8 regulates the docetaxel resistance of PCa cells via modulation of multidrug resistance 1 (MDR1). By expanding the knowledge of the cytokines and their effect mechanisms, novel approaches can be developed for the treatment of docetaxel-resistant prostate cancer. Further investigations into the role of IL-8 in docetaxel resistance could offer valuable insights into the development of effective treatment strategies for PCa patients.

The aim of this article is to model a negotiation between shareholders in high-technology-risk industries and local residents on the safety investments to be implemented. The methodology used is a Nash bargaining model, with a DE curve representing shareholders' dividend demands and an NS curve representing the safety demands of local residents' associations. The model is used to determine the level of safety investment required. One of the main results is that the estimation of a higher accident risk is accompanied by both a higher safety investment and a higher dividend payout. The most obvious implication of this result is that it is undoubtedly necessary to give greater weight to local residents in investment decision-making, in order to improve the well-being of all stakeholders.

The paper focuses on younger online viewers’ motivation to watch video game live streaming on live streaming platforms. Unlike existing scholars, it analyses younger online viewers’ watching motivation through a positive perspective and draws on the Play-Others-Downtime theory (P-O-D theory) and the motivation theory to establish the research model. By analysing 397 samples based on the variance-based structural equation modelling and partial least squares path modelling (SEM-PLS), the results present that younger viewers’ entertainment, social and leisure purposes positively affect their watching motivation. Control variables (i.e., gender, education background, and income level) demonstrate insignificant effects across the model. Considering the influence of the COVID-19 pandemic, watching video game live streaming is essential entertainment and social activities for younger adults. Future studies should identify the positive impact of video game live streaming and guide younger viewers to participate appropriately in this activity.

This paper examines the link between informality and corruption, two interlinked phenomena that have negative impacts on economic development. The paper presents a neoclassical model simulation that illustrates how informality can drive corruption in the economy, emphasizing the incentives for corruption in an economy with informal and formal sectors. The model provides insights into the mechanisms that promote corruption and how policymakers can reduce it through formalisation. The paper reviews the existing literature on informality and corruption, highlighting the empirical evidence and theoretical models that support the relationship between the two. The research finds that countries with larger informal sectors tend to have higher levels of corruption. The study contributes to the ongoing debate on how to reduce corruption and promote formalisation, which are crucial for sustainable economic growth.

In this study, we examined the efficiency of cryptocurrencies Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), Ripple (XRP), DASH, EOS, and MONERO from March 1, 2018, to March 1, 2023. We separated the sample into four subperiods for this purpose: a Tranquil period that includes the period from March 1, 2018, to December 31, 2019; a First Wave that includes the year 2020; a Second Wave that includes the year 2021; and a fourth subperiod that includes Russia's invasion of Ukraine in 2022-2023. The results are mixed, with some cryptocurrencies exhibiting equilibrium and others exhibiting autocorrelation and predictability in their pricing. When the sample is divided into subperiods, most digital currencies have long memories in their returns during the Tranquil period, BTC, LTC, and XRP exhibit efficiency during the First Wave of the pandemic, while BTC, ETH, and MONERO indicate efficiency during the Second Wave. Most assessed digital currencies showed equilibrium by 2022, with the exception of ETH and MONERO, which exhibit long memories, and LTC, which demonstrates anti-persistence. These results hold significance for investors in these alternative markets, as they suggest that some cryptocurrencies may be more predictable and therefore potentially profitable, whereas others may require greater caution and risk management strategies.

This study examined the determinants of the exchange rate in a mono-resource economy, during the period of currency and oil price fall in Nigeria. The aim of the study is to ascertain the potentiality of economic diversification (non-oil export) in saving the falling value of the domestic currency, as well as, its stability. The study employed the use of monthly data from the Central Bank of Nigeria and Nigeria National Petroleum Corporation from January 2008 to December 2020 using the ARDL and NARDL models to achieve the stated objectives. In the literature, several empirical studies analyzed the relationship between exchange rates, oil price, and oil export and came to the logical conclusion that a rise in the price of oil would bring about a rise in the exchange rate, all things being equal while the reverse is the case. To add to the existing body of knowledge this study did not only look at the relationship between the variables but also examined the determinants of the exchange rate in a mono-resource economy and ascertained the potentiality of economic diversification in bringing succor to the falling exchange rate in the midst of falling oil price. The NARDL result corroborates the findings of previous studies on the relationship between exchange rate, oil price, and the performance of non-oil export. It maintains that positive changes in oil prices would lead to the appreciation of domestic currency while negative changes in oil prices would lead to the depreciation of the domestic currency. With this analysis, the study recommends the diversification of the economy and revitalization of the non-oil sector. Since import proves to have a negative impact on the exchange rate, the revitalization of the non-oil sector stimulates domestic consumption and thus reduces import bills which raise the demand for the dollar and weakens the naira.

The claim that “there is no third way” besides the economic models of capitalism and communism has faced a challenge from a new and growing body of research into a “third way” economic paradigm known as democratic planning. In this paper, we explore one of these democratic planning models–Robin Hahnel and Michael Albert’s model of a participatory economy, focusing in particular on its allocation mechanism–a non-market, non-command-planning procedure known as “participatory planning.” This procedure has recently been implemented in computer programs to explore its feasibility, the encouraging results of which have been published elsewhere and which we summarize here. But I present here for the first time the detailed algorithms and related pseudocode powering all of these computer programs for others to consider, examine, and build as their own programs. I also describe future directions for this avenue of research.

The clean energy revolution is a global concern. Cross-border collaboration is crucial for sharing knowledge, pooling resources, and tackling complex challenges on a global scale. International partnerships can accelerate innovation by drawing on diverse knowledge and experience from different regions. Access to capital is a key driver of innovation and entrepreneurship in clean energy. Institutional investors and financial institutions increasingly recognize the potential for high returns from the clean energy sector. This research aimed to understand whether "dirty" energies, such as the Brent Crude Spot, WTI, FTSE 350 Oil, Gas & Coal, EURO STOXX Oil & Gas, influence the formation of sustainable energy prices, namely Geothermal Index, Solar Energy Index, NASDAQ OMX Bio Clean Fuels Index, Wind Energy Index, WilderHill Clean Energy Index, during the 2020 Covid-19 pandemic and the Russian invasion of Ukraine in 2022. When comparing the two sub-periods, the results show that the level of autocorrelation in price formation has increased, i.e., the mean rhoDCCA went from 32 to 45, the weak correlation coefficients without trend decreased from 30 to 19, and the anti-persistence has also decreased from 8 to 4. The strong rhoDCCA increased from 2 to 4; during the Tranquil period, the FTSE 350 / EURO STOXX Oil index pairs had a rhoDCCA of 0.76. While in the Stress subperiod, the NASDAQ OMX Bio / Solar Energy pairs had a slope of 0.70, and the FTSE 350 / EURO STOXX Oil indices had a rhoDCCA of 0.91. Evidence shows a notable dissociation between fossil energy prices and sustainable energy sources. This dissociation is characterized by various degrees of influence between fossil energy prices and sustainable energy indices, from low to moderate. This dissociation between fossil energy prices and sustainable energy prices suggests that investments in sustainable energy can offer diversification opportunities.

Objective: The DSS was utilized to construct colitis model of mouse. The colitis mice were colonized with gut microbiota. The effects of gut microbial metabolites on colitis were studied. The mechanisms of gut microbial metabolites to improve intestinal immunity were also further explored. Methods: The male BALB/c mice were selected to construct colitis mouse model with DSS and colonized with gut microbiota. The content of short-chain fatty acids in intestinal metabolites of mice during modeling were detected with GC-MS. After the mice were sacrificed, the colon tissue was stained to observe the colitis in different groups of mice. The contents of IL-22 and IL-17 in colon tissue was determined with ELISA method. To study the mechanism of relieving colitis, qRT-PCR and western blotting were used to study the horizontal of Ffar2 gene and pSTAT3 and pAKT in colon tissue, respectively. The congenital lymphocytes were isolated and purified, and the migration ability of the congenital lymphocytes was examined by cell scratch plane migration test. Results: The colonization of the gut microbiota had significant effects on the contents of short-chain fatty acids in the intestinal metabolites of colitis mice, of which the effect on the content of acetic acid and butyric acid was more significant. The colonization of gut microbiota could effectively relieve colitis in mice and effectively promote the secretion of IL-22 in colon tissue. Studying the remission mechanism indicated that colonization of gut microbiota with colitis could effectively promote the expression of Ffar2 gene in colon tissue and increase the expression of pSTAT3 and pAKT protein. The migration ability of the lymphocyte was significantly upregulated in the model group compared with the other groups, demonstrating that DSS can effectively activate the lymphocyte; The migration of congenital lymphocyte in the experimental group was significantly alleviated than that in the model group, but it was up-regulated than that in the positive control group, and the colonic tissue of the positive control group was similar to that of the normal group. Conclusion: The short-chain fatty acids in the intestinal flora metabolites can promote the gene expression of the metabolite-sensitive receptor Ffar2. The effective combination of short-chain fatty acids and Ffar2 receptors can promote the phosphorylation of STAT3 and AKT proteins, effectively promote the secretion of IL-22 in intestinal ILC3 cells, alleviate colitis in mice, and thereby improve their intestinal immune function.

We develop a four-party model involving banks, merchants, consumers, and platform firms to explain why large shopping malls can offer interest-free installment services to consumers. Using a collaboration between an online shopping platform firm and multiple banks to issue co-branded credit cards as a natural experiment, we find that consumers’ spending on the platform fulfills the requirements for merchants and banks to choose a four-way model. This study highlights the pivotal role of platform firms in the credit card market.

Environmental concerns are increasing and business firms are inclined towards adoption of eco-friendly products and services. They are hiring employees via set of green HRM practices and struggling to become an environmentally sustainable firm. Pakistani food industry is booming day by day. However, less is known about the green HRM practices executed in the fast food industry of Pakistan. Therefore, this research is interested in examining the impact of Green recruitment and selection, green training and development and green performance and compensation management on the P-O fit, affective commitment and green recovery performance in Pakistan’s fast food industry. The moderating effects of transformational leadership will be examined between Green HRM practices and green recovery performance. A sample of 408 employees who are working at different designations were selected to accomplish the purpose of the research. These managers will be selected through convenient sampling technique. There were 21 fast food restaurants (Burger Joints) selected from all over Karachi, few of them includes; KFC, Burger Lab, Burger O Clock, Vintage, Plan B and more. The collected primary data will be tested through the application of structural equation modeling technique. Smart PLS software is used to assess the objectives. The results of the study revealed significant association between Green R&S, Green T&D and P-O fit. A non-significant association is found between Green P& C and P-O Fit. The study affirmed that Affective commitment posit a direct influence on GRP. The Green R&S and Green P&C revealed insignificant impacts on the green recovery performance within the fast food industry. The indirect association was analyzed between P&C, P-O fit, AF and GRP and revealed an insignificant result. Likewise, an indirect association is found between R/S, P-O Fit, AF and GRP. The future researchers are recommended to analysis the remaining elements of GHRM and investigate their impacts on the fast food industry of Pakistan. There is a need to create awareness regarding green HRM practices and their influence on the Green recovery performance in Pakistan. Policy makers are recommended to develop such policies that promotes GHRM in Pakistan.

This study delves into the complex relationship between China's international trade and economic growth, specifically focusing on emission intensity and its environmental ramifications within the context of energy efficiency. The primary objective is to provide a comprehensive understanding of how China's international trade dynamics influence economic growth, emphasizing emission intensity and employing a model that considers the nonlinear impact of trade on output. Through this model, structural breakpoints are identified, revealing distinct outcomes for China amidst positive and negative shocks from 1972 to 2021. The study uncovers the dual nature of the energy sector, acting both as a source of environmental degradation and a potential avenue for positive change through increased efficiency. Complex interplays among economic activities, inflation, and investment on carbon intensity are revealed. Additionally, the varying effects of export volume on carbon emissions intensity across lag thresholds underscore the significance of global trade dynamics for environmental sustainability. The study concludes by emphasizing the importance of balancing economic prosperity with environmental responsibility, advocating for carefully balanced policies that foster sustainable growth. Recommendations include considering the dual nature of the energy sector and implementing policies promoting increased efficiency. Policymakers are urged to adopt growth models prioritizing environmental responsibility, balancing economic activities, inflation, and investment to mitigate carbon intensity while acknowledging the diverse effects of global trade dynamics on environmental sustainability.

I will show that if the propensity to consume from savings satisfies appropriate conditions, the debt-GDP ratio will not grow infinitely large and fiscal collapse will not occur. Using a basic macroeconomic model, with an overlapping generations model in mind, we show the following results: 1) The budget deficit including interest payments on the government bonds equals an increase in the savings from a period to the next period. 2) If the savings in the first period is positive, we need budget deficit to maintain full employment under constant prices or inflation in the later periods. 3) Under an appropriate assumption about the propensity to consume from savings, the debt-GDP ratio converges to a finite value. It does not diverge to infinity. The larger the propensity to consume from savings, the smaller the budget deficit required to achieve full employment. The larger the propensity to consume from savings, the less likely it is that the debt-GDP ratio will become large.

Motivated by the Blackorby-Schworm (1993) observation that market outcomes may differ from those originating in market-actor optimization, this paper claims that the number of banks in the market is larger than the number justified by bank profit maximization alone or in combination with bank depositor welfare maximization. This claim is made within the context of bilateral monopoly banks and intertemporal utility maximization by bank depositors. The basic policy implication towards bank population rationalization is a minimization of the deviation away from the optimal interest rate margin at every stage of the business cycle. It is meant to be an acyclical policy though the target of optimal bank population is attainable by active countercyclical policy as well. The nature of this policy issue makes the use of macroprudential measures imperative, jointly perhaps with a fiscal-monetary policy mix. A dynamic version of the model in a Cournot environment is akin to the modeling of Minsky's hypothesis of financial fragility.