Developing a Trusted Human-AI Network for Humanitarian Benefit

Humans and artificial intelligences (AI) will increasingly participate digitally and physically in conflicts yet there is a lack of trusted communications across agents and platforms. For example, humans in disasters and conflict already use messaging and social media to share information, however, international humanitarian relief organisations treat this information as unverifiable and untrustworthy. AI may reduce the ‘fog-of-war’ and improve outcomes, however current AI implementations are often brittle, have a narrow scope of application and wide ethical risks. Meanwhile, human error causes significant civilian harms even by combatants committed to complying with international humanitarian law. AI offers an opportunity to help reduce the tragedy of war and better deliver humanitarian aid to those who need it. However, to be successful, these systems must be trusted by humans and their information systems, overcoming flawed information flows in conflict and disaster zones that continue to be marked by intermittent communications, poor situation awareness, mistrust and human errors. In this paper, we consider the integration of a communications protocol (the ‘Whiteflag protocol’), distributed ledger technology, and information fusion with artificial intelligence (AI), to improve conflict communications called “Protected Assurance Understanding Situation & Entities” PAUSE. Such a trusted human-AI communication network could provide accountable information exchange regarding protected entities, critical infrastructure; humanitarian signals and status updates for humans and machines in conflicts. Trust-based information fusion provides resource-efficient use of diverse data sources to increase the reliability of reports. AI can be used to catch human mistakes and complement human decision making, while human judgment can direct and override AI recommendations. We examine several case studies for the integration of these technologies into a trusted human-AI network for humanitarian benefit including mapping a conflict zone with civilians and combatants in real time, preparation to avoid incidents and using the network to manage misinformation

Secreted Cytokines within the Urine of AKI Patients Modulate TP53 and SIRT1 Levels in a Human Podocyte Cell Model

Acute kidney injury (AKI) is a major kidney disease with a poor clinical outcome. It is a common complication, with an incidence of 10–15% of patients admitted to hospital. This rate even increases for patients who are admitted to the intensive care unit, with an incidence of >50%. AKI is characterized by a rapid increase in serum creatinine, decrease in urine output, or both. The associated symptoms include feeling sick or being sick, diarrhoea, dehydration, decreased urine output (although occasionally the urine output remains normal), fluid retention causing swelling in the legs or ankles, shortness of breath, fatigue and nausea. However, sometimes acute kidney injury causes no signs or symptoms and is detected by lab tests. Therefore, the identification of cytokines for the early detection and diagnosis of AKI is highly desirable, as their application might enable the prevention of the progression from AKI to chronic kidney disease (CKD). In this study, we analysed the secretome of the urine of an AKI patient cohort by employing a kidney-biomarker cytokine assay. Based on these results, we suggest ADIPOQ, EGF and SERPIN3A as potential cytokines that might be able to detect AKI as early as 24 h post-surgery. For the later stages, as common cytokines for the detection of AKI in both male and female patients, we suggest VEGF, SERPIN3A, TNFSF12, ANPEP, CXCL1, REN, CLU and PLAU. These cytokines in combination might present a robust strategy for identifying the development of AKI as early as 24 h or 72 h post-surgery. Furthermore, we evaluated the effect of patient and healthy urine on human podocyte cells. We conclude that cytokines abundant in the urine of AKI patients trigger processes that are needed to repair the damaged nephron and activate TP53 and SIRT1 to maintain the balance between proliferation, angiogenesis, and cell cycle arrest

Secreted Cytokines within the Urine of AKI Patients Modulate TP53 and SIRT1 Levels in a Human Podocyte Cell Model

Acute kidney injury (AKI) is a major kidney disease with a poor clinical outcome. It is a common complication, with an incidence of 10–15% of patients admitted to hospital. This rate even increases for patients who are admitted to the intensive care unit, with an incidence of >50%. AKI is characterized by a rapid increase in serum creatinine, decrease in urine output, or both. The associated symptoms include feeling sick or being sick, diarrhoea, dehydration, decreased urine output (although occasionally the urine output remains normal), fluid retention causing swelling in the legs or ankles, shortness of breath, fatigue and nausea. However, sometimes acute kidney injury causes no signs or symptoms and is detected by lab tests. Therefore, the identification of cytokines for the early detection and diagnosis of AKI is highly desirable, as their application might enable the prevention of the progression from AKI to chronic kidney disease (CKD). In this study, we analysed the secretome of the urine of an AKI patient cohort by employing a kidney-biomarker cytokine assay. Based on these results, we suggest ADIPOQ, EGF and SERPIN3A as potential cytokines that might be able to detect AKI as early as 24 h post-surgery. For the later stages, as common cytokines for the detection of AKI in both male and female patients, we suggest VEGF, SERPIN3A, TNFSF12, ANPEP, CXCL1, REN, CLU and PLAU. These cytokines in combination might present a robust strategy for identifying the development of AKI as early as 24 h or 72 h post-surgery. Furthermore, we evaluated the effect of patient and healthy urine on human podocyte cells. We conclude that cytokines abundant in the urine of AKI patients trigger processes that are needed to repair the damaged nephron and activate TP53 and SIRT1 to maintain the balance between proliferation, angiogenesis, and cell cycle arrest