Kidney stones pose a significant health concern, and early detection can lead to timely intervention and improved patient outcomes. This research endeavours to predict the presence of kidney stones based on urine analysis, utilizing a neural network model. A dataset of 552 urine specimens, comprising six essential physical characteristics (specific gravity, pH, osmolarity, conductivity, urea concentration, and calcium concentration), was collected and prepared. Our proposed neural network architecture, featuring three layers (input, hidden, output), was trained and validated, achieving (...) an impressive accuracy of 98.67% and an average error of 0.012. In addition to model performance, feature importance analysis was conducted to determine the most influential factors in predicting kidney stone presence. The findings underscore the significance of urea concentration, specific gravity, calcium concentration, conductivity, osmolarity, and pH as key indicators. This research contributes to the early diagnosis of kidney stones and demonstrates the potential of neural networks in medical diagnostics. The clinical implications of these findings are discussed, emphasizing the importance of timely intervention in managing kidney stone-related health issues. (shrink)

Janet Radcliffe Richards’ The Ethics of Transplants outlines a novel framework for moral inquiry in practical contexts and applies it to the topic of paid living kidney donation. In doing so, Radcliffe Richards makes two key claims: that opponents of organ markets bear the burden of proof, and that this burden has not yet been satisfied. This paper raises four related objections to Radcliffe Richards’ methodological framework, focusing largely on how Radcliffe Richards uses this framework in her discussion of (...) kidney sales. We conclude that Radcliffe Richards’ method of inquiry hinders our ability to answer the very question that it ought to help us resolve: What is there best reason to do, all things considered? (shrink)

There is a global shortage of organs for transplantation and despite many governments making significant changes to their organ donation systems, there are not enough kidneys available to meet the demand. This has led scientists and clinicians to explore alternative means of meeting this organ shortfall. One of the alternatives to human organ transplantation is xenotransplantation, which is the transplantation of organs, tissues, or cells between different species. The resurgence of interest in xenotransplantation and recent scientific breakthroughs suggest that genetically-engineered (...) pigs may soon present a realistic alternative as sources of kidneys for clinical transplantation. It is therefore important for nurses and allied health professionals to understand what is involved in xenotransplantation and its future implications for their clinical practices. First, we explore the insufficiency of different organ donation systems to meet the kidney shortage. Second, we provide a background and a summary of the progress made so far in xenotransplantation research. Third, we discuss some of the scientific, technological, ethical, and economic issues associated with xenotransplantation. Finally, we summarise the literature on the attitudes of healthcare professionals toward xenotransplantation. (shrink)

In Canada, there are currently no guidelines at either the federal or provincial level regarding the provision of kidney transplantation services to foreign nationals (FN). Renal transplant centres have, in the past, agreed to put refugee claimants and other FNs on the renal transplant waiting list, in part, because these patients (refugee claimants) had health insurance through the Interim Federal Health Programme to cover the costs of medication and hospital care. However, severe cuts recently made to this programme have (...) forced clinicians to question whether they should continue with transplants for FNs, for financial and ethical reasons. This paper first examines different national policies (eg, in Canada, USA, France and the UK) to map the diversity of approaches regarding transplantation for FNs, and then works through different considerations commonly used to support or oppose the provision of organs to these patients: (1) the organ shortage; (2) the free-rider problem; (3) the risk of becoming a transplant destination; (4) the impact on organ donation rates; (5) physicians’ duties; (6) economic concerns; (7) vulnerability. Using a Canadian case as a focus, and generalising through a review of various national policies, we analyse the arguments for and against transplantation for FNs with a view to bringing clarity to what is a sensitive political and clinical management issue. Our aim is to help transplant centres, clinicians and ethicists reflect on the merits of possible options, and the rationales behind them. (shrink)

People tend to be repulsed by the idea of cash markets in kidneys, but support the trading of kidneys through paired exchanges or chains. We reject anti-commodification accounts of this reaction and offer an egalitarian one. We argue that the morally significant difference between cash markets and kidney chains is that the former allow the wealthy greater access to kidneys, while the latter do not. The only problem with kidney chains is that they do not go far enough (...) in addressing equality concerns, and we show how the introduction of cash payments by the state could remedy this. (shrink)

Chronic Kidney Disease (CKD) is a significant global health issue, often leading to kidney failure and requiring costly medical treatments such as dialysis or transplants. Early detection of CKD is essential for timely intervention and improved patient outcomes. This project aims to develop a machine learning-based predictive model for diagnosing CKD at an early stage. By utilizing a range of clinical features such as age, blood pressure, blood sugar, and other relevant biomarkers, we employ machine learning algorithms, including (...) Decision Trees, Random Forests, and Support Vector Machines (SVM), to predict the likelihood of a patient developing CKD. The dataset used in this study includes medical records of patients with various kidney conditions, and preprocessing techniques such as normalization and missing data handling are applied to ensure the model’s robustness. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score to ensure reliable predictions. (shrink)

This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.

The dataset used in this study includes medical records of patients with various kidney conditions, and preprocessing techniques such as normalization and missing data handling are applied to ensure the model’s robustness. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score to ensure reliable predictions. This approach not only aims to improve diagnostic accuracy but also provides a data-driven solution to assist healthcare professionals in making informed decisions. The outcome of this project (...) can contribute to better management of CKD, ultimately helping to reduce the burden on healthcare systems and improving patient care. (shrink)

Chronic Kidney Disease (CKD) is a significant global health issue, often leading to kidney failure and requiring costly medical treatments such as dialysis or transplants. Early detection of CKD is essential for timely intervention and improved patient outcomes. This project aims to develop a machine learning-based predictive model for diagnosing CKD at an early stage. By utilizing a range of clinical features such as age, blood pressure, blood sugar, and other relevant biomarkers, we employ machine learning algorithms, including (...) Decision Trees, Random Forests, and Support Vector Machines (SVM), to predict the likelihood of a patient developing CKD. The dataset used in this study includes medical records of patients with various kidney conditions, and preprocessing techniques such as normalization and missing data handling are applied to ensure the model’s robustness. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score to ensure reliable predictions. This approach not only aims to improve diagnostic accuracy but also provides a data-driven solution to assist healthcare professionals in making informed decisions. The outcome of this project can contribute to better management of CKD, ultimately helping to reduce the burden on healthcare systems and improving patient care. (shrink)

An important argument against prohibiting organ sales is that it removes the best option available to individuals in dire circumstances. However, this line of reasoning fails to recognise that selling a kidney on a regulated market is only the best option in a very narrow comparison, where a regulated organ market is compared with banning organ sales. Once we acknowledge this narrowness, selling a kidney is not the best option. This paves the way for a distributive justice-based critique (...) of the ‘best option’ argument for organ markets, which illuminates that organ markets should be compared with a broader set of alternatives. If providing the option of selling a kidney is not the best option, but rather the best option we are willing to provide, and one which means that many people will remain in poverty and unjust circumstances, then this reflects poorly on those societies willing to offer only this option and not a better one. (shrink)

Chronic Kidney Disease (CKD) is a significant global health issue, often leading to kidney failure and requiring costly medical treatments such as dialysis or transplants. Early detection of CKD is essential for timely intervention and improved patient outcomes. This project aims to develop a machine learning-based predictive model for diagnosing CKD at an early stage. By utilizing a range of clinical features such as age, blood pressure, blood sugar, and other relevant biomarkers, we employ machine learning algorithms, including (...) Decision Trees, Random Forests, and Support Vector Machines (SVM), to predict the likelihood of a patient developing CKD. (shrink)

Chronic Kidney Disease (CKD) is a significant global health issue, often leading to kidney failure and requiring costly medical treatments such as dialysis or transplants. Early detection of CKD is essential for timely intervention and improved patient outcomes. This project aims to develop a machine learning-based predictive model for diagnosing CKD at an early stage. By utilizing a range of clinical features such as age, blood pressure, blood sugar, and other relevant biomarkers, we employ machine learning algorithms, including (...) Decision Trees, Random Forests, and Support Vector Machines (SVM), to predict the likelihood of a patient developing CKD. The dataset used in this study includes medical records of patients with various kidney conditions, and preprocessing techniques such as normalization and missing data handling are applied to ensure the model’s robustness. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score to ensure reliable predictions. This approach not only aims to improve diagnostic accuracy but also provides a data-driven solution to assist healthcare professionals in making informed decisions. The outcome of this project can contribute to better management of CKD, ultimately helping to reduce the burden on healthcare systems and improving patient care. (shrink)

Every year, hundreds of patients in England die whilst waiting for a kidney transplant, and this is evidence that the current system of altruistic-based donation is not sufficient to address the shortage of kidneys available for transplant. To address this problem, we propose a monopsony system whereby kidney donors can opt-in to receive financial compensation, whilst still preserving the right of individuals to donate without receiving any compensation. A monopsony system describes a market structure where there is only (...) one ‘buyer’—in this case the National Health Service. By doing so, several hundred lives could be saved each year in England, wait times for a kidney transplant could be significantly reduced, and it would lessen the burden on dialysis services. Furthermore, compensation would help alleviate the common disincentives to living kidney donation, such as its potential associated health and psychological costs, and it would also help to increase awareness of living kidney donation. The proposed system would also result in significant cost savings that could then be redirected towards preventing kidney disease and reducing health disparities. While concerns about exploitation, coercion, and the ‘crowding out’ of altruistic donors exist, we believe that careful implementation can mitigate these issues. Therefore, we recommend piloting financial compensation for living kidney donors at a transplant centre in England. (shrink)

Introduction: The having extremely detailed macroscopic anatomy knowledge of the present medicine literature has been result of the information accumulation throughout the hundreds years. The numerous science hero have contributed for this purpose. The scientists being ahead of his time by their knowledge and scientific perspective have contributed worthy to development process of medicine. -/- Materials and Methods: The chapters related to the kidney anatomy in El-Kânûn Fi’t-Tıbb was written by İbn-i Sînâ in the 11th century, Kitab-ı Teşrihü’l-Ebdan Min (...) e’t-Tıb is one of the first illustrated anatomy books that was written by Mansur b. Muhammed b. Ahmed in 14th century, Teşrih-ülEbdan ve Tercümânı Kıbale-i Feylesûfan is the first illustrated Turkish anatomy book that was written by Şemseddîn-i İtâkî in 17th century were evaluated. -/- Results: The informations were compared in three books and were interpreted by the present informations. These books have contributed to development of anatomy although some of the informations in them are faulted. -/- Conclusion: All three books are valuable in point of showing the development of medicine. The extensive evaluation of books which have important place in history of medicine will give valuable information about development process of medicine. (shrink)

Julian Koplin, drawing extensively on empirical data, has argued that vendors, even in well-regulated kidney markets, are likely to be significantly harmed. I contend that his reasoning to this conclusion is dangerously mistaken. I highlight two failures. First, Koplin is insufficiently attentive to the differences between existing markets and the regulated markets proposed by advocates. On the basis of this error, he wrongly concludes that many harms will persist even in a well-regulated system. Second, Koplin misunderstands the utilitarian assessment (...) of the market. He focuses on the costs and benefits of the transaction for the vendor. But, the relevant comparison is between an individual’s welfare across different courses of action, namely, vending and the nonvending alternative. Although Koplin’s empirically informed contribution is a welcome addition to this literature, the mistakes that pervade his interpretation of the data demand correction. (shrink)

In the absence of kidney markets, alternative institutions for exchanging kidneys have arisen to give donors incentives to donate. I examine thirteen such institutions, and ask whether moral arguments against markets, such as commodification, apply to them or not. I find that most arguments against kidney arguments also argue against these alternative institutions, meaning those arguments are not strong enough to prevent society from using institutions to exchange kidneys. Two arguments that do explain which kidney exchange institutions (...) are socially accepted and which are not are that institutions should not be want-regarding and should not be exploitative.Screening donors to eliminate those with socially unacceptable motives for donation and those who are in a position of being exploited could make kidney markets acceptable, since they would then only be vulnerable to arguments which have not prevented alternative exchange institutions from functioning. (shrink)

The application of this system can lead to higher crop yields, sustainable farming practices, and reduced risks associated with poor crop choices. Through rigorous evaluation using standard classification metrics, the model's performance demonstrates its potential to revolutionize farming practices by aiding farmers in making informed decisions. The system has the potential to be an invaluable tool for agricultural consultants, farmers, and policymakers, ensuring long-term sustainability and improved productivity.

This project aims to develop a machine learning-based predictive model for diagnosing CKD at an early stage. By utilizing a range of clinical features such as age, blood pressure, blood sugar, and other relevant biomarkers, we employ machine learning algorithms, including Decision Trees, Random Forests, and Support Vector Machines (SVM), to predict the likelihood of a patient developing CKD. The dataset used in this study includes medical records of patients with various kidney conditions, and preprocessing techniques such as normalization (...) and missing data handling are applied to ensure the model’s robustness. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score to ensure reliable predictions. (shrink)

Worldwide 1.2 million people are dying from kidney failure each year, and in the USA alone, approximately 100 000 people are currently on the waiting list for a kidney transplant. One possible solution to the kidney shortage is for governments to pay donors for one of their healthy kidneys and distribute these kidneys according to need. There are, however, compelling objections to this government-monopsony model. To avoid these objections, I propose a small adjustment to the model. I (...) suggest we reward kidney sellers with both money and a ceremony that celebrates their noble act. They should, in other words, receive a prize rather than a price. (shrink)

Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality rate, and it induces other diseases. There are no obvious incidental effects during the starting periods of CKD, patients routinely disregard to see the sickness. Early disclosure of CKD enables patients to seek helpful treatment to improve the development of this disease. AI models can effectively assist clinical with achieving this objective on account of their fast and exact affirmation execution. In this appraisal, proposed a (...) Logistic relapse framework for diagnosing CKD. Proposed calculation like NAIVE BAYES , DECISION TREE , KSTAR , LOGISITIC , AND SVM and look at these calculation and get the most noteworthy precision .AI store, which has an enormous number of missing qualities. Missing characteristics are for the most part found, taking everything into account, clinical conditions since patients might miss a couple of assessments for various reasons. By separating the misjudgements delivered by the set up models and proposed a fused model that unites determined backslide and sporadic woods by using perceptron. (shrink)

The dataset used in this study includes medical records of patients with various kidney conditions, and preprocessing techniques such as normalization and missing data handling are applied to ensure the model’s robustness. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score to ensure reliable predictions. This approach not only aims to improve diagnostic accuracy but also provides a data-driven solution to assist healthcare professionals in making informed decisions. The outcome of this project (...) can contribute to better management of CKD, ultimately helping to reduce the burden on healthcare systems and improving patient care. (shrink)

By utilizing a range of clinical features such as age, blood pressure, blood sugar, and other relevant biomarkers, we employ machine learning algorithms, including Decision Trees, Random Forests, and Support Vector Machines (SVM), to predict the likelihood of a patient developing CKD. The dataset used in this study includes medical records of patients with various kidney conditions, and preprocessing techniques such as normalization and missing data handling are applied to ensure the model’s robustness. T.

Early detection of CKD is essential for timely intervention and improved patient outcomes. This project aims to develop a machine learning-based predictive model for diagnosing CKD at an early stage. By utilizing a range of clinical features such as age, blood pressure, blood sugar, and other relevant biomarkers, we employ machine learning algorithms, including Decision Trees, Random Forests, and Support Vector Machines (SVM), to predict the likelihood of a patient developing CKD.

The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score to ensure reliable predictions. This approach not only aims to improve diagnostic accuracy but also provides a data-driven solution to assist healthcare professionals in making informed decisions. The outcome of this project can contribute to better management of CKD, ultimately helping to reduce the burden on healthcare systems and improving patient care.

Obituary of an American philosopher born in Latvia. Family fled Russians, migrated to Milwaukee. John became first non-identical twin to receive a kidney transplant, wrote about new technology.

Selgelid and Koplin’s article ‘Kidney Sales and the Burden of Proof’ (K&S 2019) presents a series of detailed and persuasive arguments, intended to demolish my own arguments against the prohibition of organ selling. And perhaps they might succeed, if the case described by the authors were anything like the one I actually make. However, notwithstanding the extensive quotations and the detailed explanations of the way I supposedly argue, this account of my position comprehensively mistakes both the conclusions I reach (...) and the arguments I give for them. -/- I know that there are around many misconceptions about my views on this subject, but I have always hoped they could not survive a reading of what I had actually written. I have just—after a gap of many years—looked again at the two most recent of the texts Koplin and Selgelid refer to, and it goes without saying that I can see various things I could now do better; but I do still find these misinterpretations hard to understand. And since anyone with nothing to go on but this article would reasonably conclude that the original texts were not worth reading, I am grateful to the editors for the opportunity to try to set the record straight. -/- I presume not many readers would be interested in a detailed comparative commentary on the texts, showing where this account gets my intentions wrong. I shall try instead to explain how what I do mean—and what I think I say—diverges from what is said here, and then go on to a brief outline of what my arguments and conclusions really are. I hope this may also give some sense of why, for all the opposition I have encountered since I was first drawn into this debate, I persist in thinking that the work I have been doing is important not only for this topic but for analysis in practical ethics more generally. (shrink)

Background: Arthritis is very common but is not well understood. Actually, “arthritis” is not a single disease; it is an informal way of referring to joint pain or joint disease. There are more than 100 different types of arthritis and related conditions. People of all ages, sexes and races can and do have arthritis, and it is the leading cause of disability in America. More than 50 million adults and 300,000 children have some type of arthritis. It is most common (...) among women and occurs more frequently as people get older. Common arthritis joint symptoms include swelling, pain, stiffness and decreased range of motion. Symptoms may come and go. They can be mild, moderate or severe. They may stay about the same for years, but may progress or get worse over time. Severe arthritis can result in chronic pain, inability to do daily activities and make it difficult to walk or climb stairs. Arthritis can cause permanent joint changes. These changes may be visible, such as knobby finger joints, but often the damage can only be seen on X-ray. Some types of arthritis also affect the heart, eyes, lungs, kidneys and skin as well as the joints. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment and give the appropriate method of treatment through several tips that concern the disease and how to treat it and we will see it through the application on the expert system. Methods: in this paper the design of the proposed Expert System which was produced to help Orthopedist in diagnosing Arthritis disease through its symptoms such as: pain on pressure in a joint , Inflammation indicated by joint swelling, Stiffness especially in the morning , Loss of flexibility of joint, Limited, joint movement, Deformity of the joints , Weight loss and fatigue , Non-specific fever and Crepitus. The proposed expert system presents an overview about Arthritis disease is given, the cause of diseases is outlined and the treatment of disease whenever possible is given out. SL5 Object Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Arthritis disease diagnosis expert system was evaluated by Orthopedics students and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for Orthopedist, patients with arthritis and newly graduated Orthopedics students. (shrink)

There has been considerable debate over regulated organ markets. Especially current markets, where people sell one of their kidneys while still alive, have received increased attention. Futures markets remain an interesting and under-discussed alternative specification of a market-based solution to the organ shortage. Futures markets pertain to the sale of the right to procure people’s organs after they die. There is a wide range of possible specifications of the futures market. There are, however, some major unaddressed efficiency concerns. This article (...) presents this class of concerns and discusses the implication for organ futures markets. It identifies a number of inefficiency sources pertaining to crowding out, bad organs, costs and missed opportunities, family refusals, moral hazard and strength of the provided incentive. However, a complete assessment of futures market requires better knowledge regarding the potential reaction from donors, families and health professionals. (shrink)

I defend a theory of mental representation that satisfies naturalistic constraints. Briefly, we begin by distinguishing (i) what makes something a representation from (ii) given that a thing is a representation, what determines what it represents. Representations are states of biological organisms, so we should expect a unified theoretical framework for explaining both what it is to be a representation as well as what it is to be a heart or a kidney. I follow Millikan in explaining (i) in (...) terms of teleofunction, explicated in terms of natural selection. -/- To explain (ii), we begin by recognizing that representational states do not have content, that is, they are neither true nor false except insofar as they both “point to” or “refer” to something, as well as “say” something regarding whatever it is they are about. To distinguish veridical from false representations, there must be a way for these separate aspects to come apart; hence, we explain (ii) by providing independent theories of what I call f-reference and f-predication (the ‘f’ simply connotes ‘fundamental’, to distinguish these things from their natural language counterparts). -/- Causal theories of representation typically founder on error, or on what Fodor has called the disjunction problem. Resemblance or isomorphism theories typically founder on what I’ve called the non-uniqueness problem, which is that isomorphisms and resemblance are practically unconstrained and so representational content cannot be uniquely determined. These traditional problems provide the motivation for my theory, the structural preservation theory, as follows. F-reference, like reference, is a specific, asymmetric relation, as is causation. F-predication, like predication, is a non-specific relation, as predicates typically apply to many things, just as many relational systems can be isomorphic to any given relational system. Putting these observations together, a promising strategy is to explain f-reference via causal history and f-predication via something like isomorphism between relational systems. -/- This dissertation should be conceptualized as having three parts. After motivating and characterizing the problem in chapter 1, the first part is the negative project, where I review and critique Dretske’s, Fodor’s, and Millikan’s theories in chapters 2-4. Second, I construct my theory about the nature of representation in chapter 5 and defend it from objections in chapter 6. In chapters 7-8, which constitute the third and final part, I address the question of how representation is implemented in biological systems. In chapter 7 I argue that single-cell intracortical recordings taken from awake Macaque monkeys performing a cognitive task provide empirical evidence for structural preservation theory, and in chapter 8 I use the empirical results to illustrate, clarify, and refine the theory. (shrink)

The accumulation of potentially toxic elements (PTEs) has raised public awareness due to harmful contamination to both human and marine creatures. This study was designed to determine the concentration of copper (Cu), zinc (Zn), cadmium (Cd), and nickel (Ni) in the intestine, kidney, muscle, gill, and liver tissues of local commercial edible fish, fourfinger threadfin (Eleutheronema tetradactylum), and black pomfret (Parastromateus niger) collected from Morib (M) and Kuala Selangor (KS). Among the studied PTEs, Cu and Zn were essential elements (...) to regulate body metabolism with certain dosages required while Cd and Ni were considered as non-essential elements that posed chronic and carcinogenic risk. The concentration of PTEs in fish tissue samples was analyzed using flame atomic absorption spectrometry (F-AAS). By comparing the concentration of PTEs in fish tissues as a bioindicator, the environmental risk of Morib was more serious than Kuala Selangor because both fish species collected from Morib resulted in a higher PTEs concentration. For an average 62 kg adult with a fish ingestion rate (FIR) of 0.16 kg/person/day in Malaysia, the estimated weekly intake (EWI) of Cd from the consumption of E. tetradactylum (M: 0.0135 mg/kg; KS: 0.0134 mg/kg) and P. niger (M: 0.0140 mg/kg; KS: 0.0132 mg/kg) had exceeded the provisional tolerable weekly intake (Cd: 0.007 mg/kg) established by the Joint FAO/WHO Expert Committee on Food Additives (JECFA) and oral reference dose (ORD) values of Cd (0.001 mg/kg/day) as provided by the United States Environmental Protection Agency (USEPA) regional screening level, thus it posed chronic risks for daily basis consumption. Besides, the value of the carcinogenic risk of Cd (0.7−3 to 0.8−3) and Ni (0.5−3 to 0.6−3) were in between the acceptable range (10−6 to 10−4) of the health index that indicates a relatively low possibility cancer occurrence to the consumers in both Morib and Kuala Selangor. This study recommended FIR to be 0.80 kg/person/day to reduce the possibility of posing chronic and carcinogenic risks while at the same time obtaining the essential nutrients from the fish. (shrink)

Some sacrifices—like giving a kidney or heroically dashing into a burning building—are supererogatory: they are good deeds beyond the call of duty. But if such deeds are really so good, philosophers ask, why shouldn’t morality just require them? The standard answer is that morality recognizes a special role for the pursuit of self-interest, so that everyone may treat themselves as if they were uniquely important. This idea, however, cannot be reconciled with the compelling picture of morality as impartial—the view (...) that we are each anyone’s equal. I propose an alternative Self-Other Symmetric account of our moral freedom: the limits on what morality may demand of us are set by the duties we owe to ourselves. I begin with a defense of the Self-Other Symmetry: the idea that we owe the same duties to ourselves—and have the same rights against ourselves—as any relevantly similar other. Because we are consenting parties to our own actions, I argue, our rights against ourselves do not function like the rights of unwilling others. Instead, they play a permissive function, allowing us to block the demand to give up what is ours. I conclude by uniting, aggravating, and trying to solve some paradoxes of supererogatory permissions, guided by the idea that morality cannot be reduced to a ranking of options from best-to-worst. Rights against oneself are an irreducible second dimension, one that we need if we are to unify rights and supererogation into an impartial moral vision. (shrink)

For a long time discussion about scarce health care resource allocation was limited to allocation of medical resources, with the paradigmatic case being kidney transplants. However, a narrow focus on medical resources prevents us from seeing that there are many cases-- perhaps the majority-- in which less dramatic but equally important issues of rationing occur. The allocation of nurses' time is one such issue.

Metformin is considered the first-line treatment as a monotherapy for patients with type 2 diabetes mellitus. Emerging evidence suggests that metformin may have a renoprotective role; therefore, understanding the impact of metformin dose and therapy duration on renal function may significantly improve renal outcomes in type 2 diabetes patients. This study aims to investigate the renoprotective effects of metformin by analyzing its dose-dependent impacts on the estimated glomerular filtration rate in patients with type 2 diabetes mellitus. A retrospective cross-sectional study (...) design was used from September 2022 to October 2023. Data from 302 type 2 diabetes patients were collected from patient files at the Benghazi Diabetic Center and the Aljabal Al-Alkdar Diabetic Center, including all with type 2 diabetes mellitus patients on varying doses of metformin. The collected data included age, gender, metformin dose, duration of metformin therapy, urea, and creatinine. Exclusion criteria included patients with significant comorbidities such as chronic kidney disease (other than diabetic nephropathy), liver disease, heart failure, or malignancy; those taking nephrotoxic medications; individuals with recent acute illnesses or surgical procedures; pregnant or lactating women; participants with inadequate medical records; and patients who were non-adherent to metformin therapy. Survival analysis was conducted to evaluate the effect of different metformin doses on the estimated glomerular filtration rate. The study analyzed 302 diabetic patients, of whom 46.0% were male and 54.0% were female. The age was 58.3±11.9 years. The HbA1c was 7.7%±1.3%. The duration of diabetes was 11.4±8.1 years. The creatinine was 1.0±0.9 mg/dL, and the urea was 36.7±23.8 mg/dL. Data analysis revealed a statistically significant difference in survival distribution across the dose groups. Different metformin doses significantly impact the estimated glomerular filtration rate, suggesting that dosage plays a crucial role in maintaining renal function. (shrink)

There is a widely acknowledged shortage of and an increasing demand for transplantable human organs and tissues (e.g., kidney, heart, lung, liver, cornea) in developed and developing countries around the world. In response to this need, Lott and Savulescu (2007) propose the creation of a human embryonic stem (hESC) bank to facilitate the equitable and efficient dissemination of human leukocyte anti- gen (HLA) matched tissues and organs to patients in need of replacement. Although not an unreasonable proposal, the authors (...) go on to make a much stronger claim. They argue that hESCs are such important tools for addressing the massive unmet global need for organs that it is ethically justified to require mandatory banking of spare embryos, and they argue for the use of financial (or other) inducements to procure embryos for the derivation of hESCs. (shrink)

Commodification is a broad and crosscutting issue that spans debates in ethics (from prostitution to global market practices) and bioethics (from the sale of body parts to genetic enhancement). There has been disagreement, however, over what constitutes commodification, whether it is happening, and whether it is of ethical import. This chapter focuses on one area of the discussion in bioethics – the commodification of human tissue – and addresses these questions – about the characteristics of commodification, its pervasiveness, and ethical (...) significance – in order to clarify and map the commodificatory debate. The chapter does this in three parts. First, it defines commodification as the shift from “persons” to “things” and from “relationships” to services for “contract.” Second, using examples of kidney and gamete sale and commercial surrogacy, it argues that commodification is rife in bioethics. Third, it contends that commodification is an ethical problem for three key reasons: First, because it leads to exploitation; second, because some things should not be for sale; and third, because it damages social goods. The chapter concludes that commodification and commodificatory practices should be resisted. (shrink)

Libertarian self-ownership views in the tradition of Locke, Nozick, and the left-libertarians have supposed that we enjoy very powerful deontological protections against infringing upon our property. Such a conception makes sense when we are focused on property that is very important to its owner, such as a person’s kidney. However, this stringency of our property rights is harder to credit when we consider more trivial infringements such as very mildly toxic pollution or trivial risks such having planes fly overhead. (...) Maintaining that our rights against all infringements are very powerful threatens to implausibly make such pollution and trivial risk broadly impermissible. This paper suggests that self-ownership views have tended to inappropriately conflate the seriousness of different types of infringements and that treating all infringements so seriously is implausible because it would make too much impermissible. I consider several ways to avoid this result within a self-ownership framework and conclude that the best approach is to allow that the strength of the protection against infringements should be tied to the seriousness of the harm of the infringement. (shrink)

The 2013 Rostock Symposium on Systems Biology and Bioinformatics in Aging Research was again dedicated to dissecting the aging process using in silico means. A particular focus was on ontologies, as these are a key technology to systematically integrate heterogeneous information about the aging process. Related topics were databases and data integration. Other talks tackled modeling issues and applications, the latter including talks focussed on marker development and cellular stress as well as on diseases, in particular on diseases of (...) class='Hi'>kidney and skin. (shrink)

We describe the rationale for an application ontology covering the domain of human body fluids that is designed to facilitate representation, reuse, sharing and integration of diagnostic, physiological, and biochemical data, We briefly review the Blood Ontology (BLO), Saliva Ontology (SALO) and Kidney and Urinary Pathway Ontology (KUPO) initiatives. We discuss the methods employed in each, and address the project of using them as starting point for a unified body fluids ontology resource. We conclude with a description of how (...) the body fluids ontology initiative may provide support to basic and translational science. (shrink)

-/- Extending Human Lifespan: Scientific and Technological Possibilities -/- The quest for extending human lifespan has fascinated humanity for centuries. Advances in genetics, medicine, artificial intelligence, and bioengineering are bringing us closer to significantly prolonging life, potentially even achieving biological immortality. This essay explores various scientific and technological approaches to extending human life, from genetic modifications to mind uploading. -/- 1. Genetic Engineering & Cellular Reprogramming -/- One of the most promising fields in lifespan extension is genetic engineering. Our DNA (...) holds the key to aging, and modifying it could slow or even reverse the aging process. -/- Gene Therapy: Scientists are exploring ways to edit genes associated with aging and longevity, such as the FOXO3 and SIRT genes. CRISPR gene-editing technology allows precise modifications to enhance DNA repair mechanisms and eliminate age-related mutations. -/- Telomere Extension: Telomeres, the protective caps at the ends of chromosomes, shorten with age. Techniques like telomerase activation could extend telomeres, effectively delaying cellular aging. -/- Epigenetic Reprogramming: Aging is influenced by chemical changes in DNA called epigenetic markers. Scientists like Dr. David Sinclair are working on methods to reset these markers, restoring youthful function in cells. -/- 2. Anti-Aging Drugs & Therapies -/- Medical research is identifying compounds that slow aging and enhance longevity. Some of the most promising drugs and therapies include: -/- Senolytics: These drugs target and remove senescent cells, which accumulate with age and contribute to inflammation and tissue damage. Removing them has been shown to extend lifespan in mice. -/- Metformin & Rapamycin: Metformin, a common diabetes drug, has shown promise in reducing cellular stress and extending lifespan. Rapamycin, originally used for transplant patients, has been found to mimic calorie restriction, enhancing longevity in animals. -/- NAD+ Boosters: Nicotinamide adenine dinucleotide (NAD+) is a molecule essential for cellular energy production. As we age, NAD+ levels decline, leading to cellular dysfunction. Boosters like NMN and NR are being tested to restore energy metabolism and promote longer lifespans. -/- 3. Regenerative Medicine & Organ Replacement -/- Aging is often associated with organ failure, but regenerative medicine could help replace worn-out body parts. -/- Stem Cell Therapy: Stem cells have the potential to repair or replace damaged tissues, offering a biological rejuvenation strategy. Scientists are investigating methods to grow new skin, bones, and even organs using stem cells. -/- 3D Bioprinting & Artificial Organs: Advances in 3D printing allow researchers to create lab-grown organs, such as artificial hearts, kidneys, and livers, which could replace failing ones without the need for donors. -/- Cloning & Tissue Engineering: Personalized tissue regeneration using a patient’s own cells could eliminate transplant rejection risks. Scientists are also exploring ways to clone healthy organs for transplantation. -/- 4. Enhancing Brain & Cognitive Function -/- Longevity is meaningless without maintaining cognitive function. Neurodegenerative diseases like Alzheimer’s pose a significant threat to longevity, but new technologies are emerging to counteract cognitive decline. -/- Neural Implants & Brain-Computer Interfaces (BCIs): Companies like Neuralink are developing brain implants that could enhance memory, prevent neurological diseases, and even allow direct communication with AI. -/- Cryopreservation: Some futurists believe in cryonics, the process of freezing the brain (or entire body) after death in the hope of future revival using advanced medical technology. -/- AI Integration: Artificial intelligence could assist in decision-making, memory enhancement, and mental health support, preserving cognitive abilities well into old age. -/- 5. Lifestyle & Environmental Optimization -/- While high-tech solutions are promising, natural lifestyle changes have been shown to promote longevity. -/- Diet & Caloric Restriction: Studies indicate that intermittent fasting and calorie restriction can extend lifespan by reducing oxidative stress and inflammation. -/- Exercise & Hormesis: Regular physical activity helps maintain muscle mass, cardiovascular health, and brain function. Hormesis—exposing the body to mild stress, like cold showers or sauna therapy—has also been linked to longevity. -/- Microbiome Optimization: A healthy gut microbiome influences the immune system, metabolism, and overall health. Prebiotics, probiotics, and personalized microbiome therapies could extend lifespan by reducing chronic diseases. -/- 6. Nanotechnology & Molecular Repair -/- Future breakthroughs in nanotechnology may allow precise control over aging processes at the molecular level. -/- Nanomedicine: Tiny robots (nanobots) could patrol the bloodstream, repairing cellular damage, removing toxins, and targeting diseases at the microscopic level. -/- Artificial Blood Cells: Scientists are developing synthetic blood that can enhance oxygen delivery and immune function, potentially extending life. -/- Targeted Drug Delivery: Advanced drug delivery systems using nanoparticles can deliver medication exactly where needed, reducing side effects and increasing effectiveness. -/- 7. Mind Uploading & Post-Biological Life -/- The most radical vision for immortality involves leaving behind the biological body altogether. -/- Whole Brain Emulation: Researchers are exploring the idea of scanning and copying a human brain into a digital system. If successful, this would allow a person’s consciousness to continue in a virtual or robotic form. -/- Consciousness Transfer: Some futurists speculate that advanced AI or quantum computing might enable transferring human consciousness into an artificial body, bypassing biological aging altogether. -/- Conclusion: The Future of Human Longevity -/- While full immortality remains theoretical, science is making rapid progress in extending human life and improving quality of life. A combination of genetic engineering, regenerative medicine, AI integration, nanotechnology, and lifestyle optimization may push human lifespan beyond 120 years, potentially even eliminating aging as a cause of death. -/- However, ethical, social, and economic challenges must also be addressed. Who will have access to these life-extending technologies? How will society handle overpopulation and resource distribution? These are critical questions as humanity moves toward a longer and healthier future. -/- . (shrink)

This paper explores some ways in which artificial intelligence (AI) could be used to improve human moral judgments in bioethics by avoiding some of the most common sources of error in moral judgment, including ignorance, confusion, and bias. It surveys three existing proposals for building human morality into AI: Top-down, bottom-up, and hybrid approaches. Then it proposes a multi-step, hybrid method, using the example of kidney allocations for transplants as a test case. The paper concludes with brief remarks about (...) how to handle several complications, respond to some objections, and extend this novel method to other important moral issues in bioethics and beyond. (shrink)

Critics of commodification often claim that the buying and selling of some good communicates disrespect or some other inappropriate attitude. Such semiotic critiques have been leveled against markets in sex, pornography, kidneys, surrogacy, blood, and many other things. Brennan and Jaworski (2015a) have recently argued that all such objections fail. They claim that the meaning of a market transaction is a highly contingent, socially constructed fact. If allowing a market for one of these goods can improve the supply, access or (...) quality of the good, then instead of banning the market on semiotic grounds, they urge that we should revise our semiotics. In this reply, I isolate a part of the meaning of a market transaction that is not socially constructed: our market exchanges always express preferences. I then show how cogent semiotic critiques of some markets can be constructed on the basis of this fact. (shrink)

The ‘limits of markets’ debate broadly concerns the question of when it is (im)permissible to have a market in some good. Markets can be of tremendous benefit to society, but many have felt that certain goods should not be for sale (e.g., sex, kidneys, bombs). Their sale is argued to be corrupting, exploitative, or to express a form of disrespect. InMarkets without Limits, Jason Brennan and Peter Jaworski have recently argued to the contrary: For any good, as long as it (...) is permissible to give it for free, then it is permissible to give it for money. Their thesis has led to a number of engaging objections, and I leverage recent work on the nature of feasibility within political philosophy to offer a new challenge.I argue that feasibility offers a constraint on which markets can be permissibly implemented. Though it may be possible to create a morally acceptable version of an otherwise repugnant market, some of these markets may be infeasible, and so we are not permitted to implement them. After laying out this challenge, I consider several replies. They concern the relevance of feasibility, and whether any markets really are infeasible. This provides an opportunity to explore the dangers of pursuing the infeasible and with markets generally. I conclude by considering what might lead us to pursue these markets despite their infeasibility, or how knowledge of infeasibility may prove useful regardless. (shrink)

For a long time, discussion about scarce health care resource allocation was limited to allocation of medical resources, with the paradigmatic case being kidney transplants. This narrow focus on medical resource prevents us from seeing that there are many cases-- perhaps even the majority--in which time is the real scarce resource, particularly nurse time. What ethical principles should apply to nurse time as a scarce health care resource?

Per- and poly-fluoroalkyl substances (PFAS)—nicknamed “forever chemicals” due to their extreme environmental persistence—are synthetic compounds found in various products and industries, including food packaging, water and stain-repellant fabrics, fire-fighting foams, and semiconductor manufacturing. While much attention has been paid to their link with cancer, infertility, diseases of the liver, kidney, and immune dysfunction in adults, growing concern centers on how PFAS exposure during pregnancy and early childhood may impair brain development in children.

O presente trabalho teve como objetivo avaliar o efeito da terminação de cordeiros confinados usando resíduo úmido de cervejaria como fonte de volumoso ofertado em diferentes frequências de alimentação sobre as características da carcaça e não componentes da carcaça. Foram utilizados 30 cordeiros machos não castrados, oriundos de um cruzamento alternado entre as raças Texel e Ile de France. Os animais apresentaram ao início do confinamento idade média de 72,7±6 dias e peso médio de 25,44±4,1 kg. Os tratamentos eram constituídos (...) de três diferentes frequências de alimentação, sendo: uma vez ao dia (08:00 horas), duas vezes ao dia (08:00 e 18:00 horas) e três vezes ao dia (08:00, 13:00 e 18:00 horas). A relação volumoso:concentrado usada foi de 46,9:53,1 com base na matéria seca. Os cordeiros foram abatidos quando atingiram o peso vivo de fazenda, de 38 kg. Houve diferença estatística (P<0,05) para as variáveis peso e rendimento de costelas, peso e proporção de Rins e peso de Rum+Ret. As demais variáveis não diferiram (P>0,05) entre os tratamentos. Em função dos resultados podemos recomendar uma única oferta diária como manejo alimentar para cordeiros terminados em confinamento recebendo resíduo úmido de cervejaria como fonte de volumoso. Palavras-chave: Cordeiro, Carcaça, Resíduo de Cervejaria, Confinamento. -/- ABSTRACT The present work aimed to evaluate the effect of finishing confined lambs using wet brewery residue as a source of roughage offered at different feeding frequencies on the characteristics of the carcass and non-carcass components. 30 uncastrated male lambs were used, coming from an alternating cross between the Texel and Ile de France breeds. At the beginning of confinement, the animals had an average age of 72.7±6 days and an average weight of 25.44±4.1 kg. The treatments consisted of three different feeding frequencies: once a day (08:00), twice a day (08:00 and 18:00) and three times a day (08:00, 13:00). 00 and 18:00 hours). The roughage:concentrate ratio used was 46.9:53.1 based on dry matter. Lambs were slaughtered when they reached farm live weight of 38 kg. There was a statistical difference (P<0.05) for the variables weight and yield of ribs, weight and proportion of Kidneys and weight of Rum+Ret. The other variables did not differ (P>0.05) between treatments. Based on the results, we can recommend a single daily supply as a dietary management for lambs finished in confinement receiving wet brewery residue as a source of roughage. Keywords: Lambs, Carcass, Brewery Residue, Confinement. RESUMEN El presente trabajo tuvo como objetivo evaluar el efecto del acabado de corderos confinados utilizando residuos húmedos de cervecería como fuente de forraje ofrecido en diferentes frecuencias de alimentación sobre las características de los componentes de la carcasa y no carcasa. Se utilizaron 30 corderos machos sin castrar, procedentes de un cruce alterno entre las razas Texel e Ile de France. Al inicio del confinamiento, los animales tenían una edad promedio de 72,7±6 días y un peso promedio de 25,44±4,1 kg. Los tratamientos consistieron en tres frecuencias de alimentación diferentes: una vez al día (08:00), dos veces al día (08:00 y 18:00) y tres veces al día (08:00, 13:00 y 18:00). horas). La relación forraje:concentrado utilizada fue 46,9:53,1 basada en materia seca. Los corderos fueron sacrificados cuando alcanzaron un peso vivo en granja de 38 kg. Hubo diferencia estadística (P<0,05) para las variables peso y rendimiento de costillas, peso y proporción de Riñones y peso de Ron+Ret. Las demás variables no difirieron (P>0.05) entre tratamientos. Con base en los resultados, podemos recomendar un suministro único diario como manejo dietético para corderos terminados en confinamiento que reciben residuos húmedos de cervecería como fuente de forraje. Palabras clave: Cordero, Carcasa, Residuos de Cervecería, Confinamiento. (shrink)

After a long search, Jonathan has finally found someone willing to donate a kidney to him and thereby free him from dialysis. Meredith is Jonathan's second cousin, and she considers herself a generous person, so although she barely knows Jonathan, she is willing to help. However, as Meredith learns more about the donation process, she begins to ask questions about Jonathan: “Is he HIV positive? I heard he got it using drugs. Has he been in jail? He's already had (...) one live donor, so what happened to the first kidney? Did he forget to take his drugs or something?” The transplant center must, then, decide if Meredith is, in fact, entitled to answers to these kinds of questions. According to the Consensus Statement on the Live Organ Donor, “It is incumbent on the transplant center to provide full and accurate disclosure to potential donors of all pertinent information regarding risk and benefit to the donor and recipient.” But whether answers to the Meredith's questions count as “pertinent information regarding the risk and benefit” is the issue at hand. (shrink)

Chronic diseases such as diabetes, cardiovascular conditions, and chronic kidney disease are major global health concerns. Early detection of these conditions significantly improves patient outcomes and reduces healthcare costs. This paper explores the development and implementation of artificial intelligence (AI) algorithms to identify early signs of chronic diseases using electronic health records (EHRs) and patient-generated health data. By applying machine learning models such as decision trees, support vector machines, and deep learning neural networks, we demonstrate improved prediction accuracy for (...) disease onset. Our approach also integrates feature engineering techniques and interpretable AI to enhance clinical applicability. (shrink)

Unlike other organs that operate continuously, such as the heart and kidneys, many of the operations of the nervous system shut down during sleep. The evolutionarily conserved unconscious state of sleep that puts animals at risk from predators indicates that it is an indispensable integral part of systems operation. A reasonable expectation is that any hypothesis for the mechanism of the nervous system functions should be able to provide an explanation for sleep. In this regard, the semblance hypothesis is examined. (...) Postsynaptic membranes are continuously being depolarized by the quantally released neurotransmitter molecules arriving from their presynaptic terminals. In this context, an incidental lateral activation of the postsynaptic membrane is expected to induce a semblance (cellular hallucination of arrival of activity from its presynaptic terminal, which forms a unit for internal sensation) of the arrival of activity from its presynaptic terminal as a systems property. This restricts induction of semblance to a context of a very high ratio of the duration of the default state of neurotransmitter-induced postsynaptic depolarization to the total duration of incidental lateral activations of the postsynaptic membrane. This requirement spans within a time-bin of a few sleep-wake cycles. Since the duration of quantal release remains maximized, the above requirement can be achieved only by ceiling the total duration of incidental lateral activations of the postsynaptic membrane, which necessitates a state of sleep. (shrink)

The advancement of machine learning (ML) has revolutionized healthcare by enabling the early detection and diagnosis of multiple diseases. This paper presents a Multiple Disease Prediction System using machine learning algorithms to analyze patient data and predict the likelihood of diseases such as diabetes, heart disease, and kidney disease. The proposed model utilizes various ML classifiers, including Decision Trees, Random Forest, Support Vector Machines (SVM), and Neural Networks, to enhance prediction accuracy. The system aims to provide a costeffective, accurate, (...) and efficient tool for healthcare professionals and patients. (shrink)