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Trogocytosis is an active process whereby fragments of plasma membrane proteins and cytoplasm are transferred from one cell to another in a cell-cell contact-dependent manner. T cells trogocytose pieces of the cells presenting antigen to them at the site of the immunological synapse. Fragments of the antigen-presenting cell membrane rich in antigen/major histocompatibility (MHC) complexes are internalized by the T cell. Those complexes are redirected to the plasma membrane of the T cell, which subsequently becomes an antigen-presenting cell to other T cells. Removing antigen/MHC complexes from professional and tumoral cells has consequences for the intensity and duration of the immune response. However, the acquired capacity of T cells to present the trogocytosed cognate antigen/MHC complexes also affects the properties of the trogocytotic T cells. Acting as antigen-presenting cells, trogocytotic CD4 T cells influence both the differentiation of cytotoxic T cells and the differentiation of other CD4 T cells into pro-inflammatory effector T cells. Furthermore, trogocytosis of antigen/MHC complexes promotes the differentiation of the trogocytotic CD4 T cells towards regulatory T cells and Th2 effector cells. Trogoctyosis is, therefore, a parallel mechanism to signal transduction by membrane receptors, including the T cell antigen receptor, at the plane of the plasma membrane., (© 2023 The Authors. Published by Elsevier B.V. on behalf of Chang Gung University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Importance: Safe integration of artificial intelligence (AI) into clinical settings often requires randomized clinical trials (RCT) to compare AI efficacy with conventional care. Diabetic retinopathy (DR) screening is at the forefront of clinical AI applications, marked by the first US Food and Drug Administration (FDA) De Novo authorization for an autonomous AI for such use., Objective: To determine the generalizability of the 7 ethical research principles for clinical trials endorsed by the National Institute of Health (NIH), and identify ethical concerns unique to clinical trials of AI., Design, Setting, and Participants: This qualitative study included semistructured interviews conducted with 11 investigators engaged in the design and implementation of clinical trials of AI for DR screening from November 11, 2022, to February 20, 2023. The study was a collaboration with the ACCESS (AI for Children's Diabetic Eye Exams) trial, the first clinical trial of autonomous AI in pediatrics. Participant recruitment initially utilized purposeful sampling, and later expanded with snowball sampling. Study methodology for analysis combined a deductive approach to explore investigators' perspectives of the 7 ethical principles for clinical research endorsed by the NIH and an inductive approach to uncover the broader ethical considerations implementing clinical trials of AI within care delivery., Results: A total of 11 participants (mean [SD] age, 47.5 [12.0] years; 7 male [64%], 4 female [36%]; 3 Asian [27%], 8 White [73%]) were included, with diverse expertise in ethics, ophthalmology, translational medicine, biostatistics, and AI development. Key themes revealed several ethical challenges unique to clinical trials of AI. These themes included difficulties in measuring social value, establishing scientific validity, ensuring fair participant selection, evaluating risk-benefit ratios across various patient subgroups, and addressing the complexities inherent in the data use terms of informed consent., Conclusions and Relevance: This qualitative study identified practical ethical challenges that investigators need to consider and negotiate when conducting AI clinical trials, exemplified by the DR screening use-case. These considerations call for further guidance on where to focus empirical and normative ethical efforts to best support conduct clinical trials of AI and minimize unintended harm to trial participants.

Psychiatry is rapidly adopting digital phenotyping and artificial intelligence/machine learning tools to study mental illness based on tracking participants' locations, online activity, phone and text message usage, heart rate, sleep, physical activity, and more. Existing ethical frameworks for return of individual research results (IRRs) are inadequate to guide researchers for when, if, and how to return this unprecedented number of potentially sensitive results about each participant's real-world behavior. To address this gap, we convened an interdisciplinary expert working group, supported by a National Institute of Mental Health grant. Building on established guidelines and the emerging norm of returning results in participant-centered research, we present a novel framework specific to the ethical, legal, and social implications of returning IRRs in digital phenotyping research. Our framework offers researchers, clinicians, and Institutional Review Boards (IRBs) urgently needed guidance, and the principles developed here in the context of psychiatry will be readily adaptable to other therapeutic areas.

The following sections are included:Workshop DescriptionLearning ObjectivesPresenter InformationAbout the Workshop OrganizersPresentationsSpeaker Presentations.

Numerous ethics guidelines have been handed down over the last few years on the ethical applications of machine learning models. Virtually every one of them mentions the importance of "fairness" in the development and use of these models. Unfortunately, though, these ethics documents omit providing a consensually adopted definition or characterization of fairness. As one group of authors observed, these documents treat fairness as an "afterthought" whose importance is undeniable but whose essence seems strikingly elusive. In this essay, which offers a distinctly American treatment of "fairness," we comment on a number of fairness formulations and on qualitative or statistical methods that have been encouraged to achieve fairness. We argue that none of them, at least from an American moral perspective, provides a one-size-fits-all definition of or methodology for securing fairness that could inform or standardize fairness over the universe of use cases witnessing machine learning applications. Instead, we argue that because fairness comprehensions and applications reflect a vast range of use contexts, model developers and clinician users will need to engage in thoughtful collaborations that examine how fairness should be conceived and operationalized in the use case at issue. Part II of this paper illustrates key moments in these collaborations, especially when inter and intra disagreement occurs among model developer and clinician user groups over whether a model is fair or unfair. We conclude by noting that these collaborations will likely occur over the lifetime of a model if its claim to fairness is to advance beyond "afterthought" status., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Banja et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Big data and AI have enabled digital simulation for prediction of future health states or behaviors of specific individuals, populations or humans in general. "Digital simulacra" use multimodal datasets to develop computational models that are virtual representations of people or groups, generating predictions of how systems evolve and react to interventions over time. These include digital twins and virtual patients for in silico clinical trials, both of which seek to transform research and health care by speeding innovation and bridging the epistemic gap between population-based research findings and their application to the individual. Nevertheless, digital simulacra mark a major milestone on a trajectory to embrace the epistemic culture of data science and a potential abandonment of medical epistemological concepts of causality and representation. In doing so, "data first" approaches potentially shift moral attention from actual patients and principles, such as equity, to simulated patients and patient data.

Background: The COVID-19 pandemic required science to provide answers rapidly to combat the outbreak. Hence, the reproducibility and quality of conducting research may have been threatened, particularly regarding privacy and data protection, in varying ways around the globe. The objective was to investigate aspects of reporting informed consent and data handling as proxies for study quality conduct., Methods: A systematic scoping review was performed by searching PubMed and Embase. The search was performed on November 8th, 2020. Studies with hospitalised patients diagnosed with COVID-19 over 18 years old were eligible for inclusion. With a focus on informed consent, data were extracted on the study design, prestudy protocol registration, ethical approval, data anonymisation, data sharing and data transfer as proxies for study quality. For reasons of comparison, data regarding country income level, study location and journal impact factor were also collected., Results: 972 studies were included. 21.3% of studies reported informed consent, 42.6% reported waivers of consent, 31.4% did not report consent information and 4.7% mentioned other types of consent. Informed consent reporting was highest in clinical trials (94.6%) and lowest in retrospective cohort studies (15.0%). The reporting of consent versus no consent did not differ significantly by journal impact factor (p=0.159). 16.8% of studies reported a prestudy protocol registration or design. Ethical approval was described in 90.9% of studies. Information on anonymisation was provided in 17.0% of studies. In 257 multicentre studies, 1.2% reported on data sharing agreements, and none reported on Findable, Accessible, Interoperable and Reusable data principles. 1.2% reported on open data. Consent was most often reported in the Middle East (42.4%) and least often in North America (4.7%). Only one report originated from a low-income country., Discussion: Informed consent and aspects of data handling and sharing were under-reported in publications concerning COVID-19 and differed between countries, which strains study quality conduct when in dire need of answers., Competing Interests: Competing interests: LAC is funded by the National Institute of Health through the NIBIB R01 grant EB01720., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

As the health-care industry emerges into a new era of digital health driven by cloud data storage, distributed computing, and machine learning, health-care data have become a premium commodity with value for private and public entities. Current frameworks of health data collection and distribution, whether from industry, academia, or government institutions, are imperfect and do not allow researchers to leverage the full potential of downstream analytical efforts. In this Health Policy paper, we review the current landscape of commercial health data vendors, with special emphasis on the sources of their data, challenges associated with data reproducibility and generalisability, and ethical considerations for data vending. We argue for sustainable approaches to curating open-source health data to enable global populations to be included in the biomedical research community. However, to fully implement these approaches, key stakeholders should come together to make health-care datasets increasingly accessible, inclusive, and representative, while balancing the privacy and rights of individuals whose data are being collected., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Smart toilets are a key tool for enabling precision health monitoring in the home, but such passive monitoring has ethical considerations.

The causal mechanisms and manifestations of psychiatric illness cannot be neatly narrowed down or quantified for diagnosis and treatment. Large-scale genome-wide association studies (GWAS) might renew hope for locating genetic predictors and producing precision medicines, however such hopes can also distract from appreciating social factors and structural injustices that demand more socially inclusive and equitable approaches to mental healthcare. A more comprehensive approach begins with recognizing that there is no one type of contributor to mental illness and its duration that should be prioritized over another. We argue that, if the search for biological specificity is to complement the need to alleviate the social distress that produces mental health inequities, psychiatric genomics must incorporate an intersectional dimension to models of mental illness across research priorities, scientific frameworks, and clinical applications. We outline an intersectional framework that will guide all professionals working in the expanding field of psychiatric genomics to better incorporate issues of social context, racial and cultural diversity, and downstream ethical considerations into their work., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Brown, Young and Martinez-Martin.)

Receptor-ligand interactions on the plasma membrane regulate cellular communication and play a key role in viral infection. Despite representing main targets for drug development, the characterization of these interactions remains challenging in part due to the dearth of optimal technologies. Here, we build a comprehensive library of human proteins engineered for controlled cell surface expression. Coupled to tetramer-based screening for increased binding avidity, we develop a high throughput cell-based platform that enables systematic interrogation of receptor-ligand interactomes. Using this technology, we characterize the cell surface proteins targeted by the receptor binding domain (RBD) of the SARS-CoV spike protein. Host factors that specifically bind to SARS CoV-2 but not SARS CoV RBD are identified, including proteins that are expressed in the nervous system or olfactory epithelium. Remarkably, our results show that Contactin-1, a previously unknown SARS CoV-2 spike-specific receptor that is upregulated in COVID-19 patients, significantly enhances ACE2-dependent pseudotyped virus infection. Starting from a versatile platform to characterize cell surface interactomes, this study uncovers host factors specifically targeted by SARS CoV-2, information that may help design improved therapeutic strategies against COVID-19., (© 2022. The Author(s).)

Membrane protein interactions are challenging to identify because of the unique biophysical characteristics of both transmembrane proteins and membrane environments. The Receptor Display in Membranes Interaction Screen (RDIMIS) platform overcomes these challenges by screening transmembrane and membrane-proximal proteins in a membrane environment using recombinant extracellular vesicles (rEVs). The screen has been used to successfully identify interactions for difficult-to-study receptors in an unbiased manner. In this report, we detail how we generate rEVs, characterize the rEVs to ensure screen-readiness, and perform the full interaction screening, with emphasis on the criteria necessary to obtain clear, interpretable results. We also include support protocols for generating a screening library and validating screening results, as well as an alternate protocol for RDIMIS enabling the profiling of naturally occurring extracellular vesicles. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Generating and isolating extracellular vesicles from cells Basic Protocol 2: Characterizing recombinant extracellular vesicles Support Protocol 1: Preparing the receptor screening library Basic Protocol 3: Performing the Receptor Display in Membranes Interaction Screen (RDIMIS) Support Protocol 2: Validating RDIMIS results using microscopy Alternate Protocol: Detecting unlabeled endogenous vesicles., (© 2022 Wiley Periodicals LLC.)

Human cytomegalovirus (HCMV) represents the viral leading cause of congenital birth defects and uses the gH/gL/UL128-130-131A complex (Pentamer) to enter different cell types, including epithelial and endothelial cells. Upon infection, Pentamer elicits the most potent neutralizing response against HCMV, representing a key vaccine candidate. Despite its relevance, the structural basis for Pentamer receptor recognition and antibody neutralization is largely unknown. Here, we determine the structures of Pentamer bound to neuropilin 2 (NRP2) and a set of potent neutralizing antibodies against HCMV. Moreover, we identify thrombomodulin (THBD) as a functional HCMV receptor and determine the structures of the Pentamer-THBD complex. Unexpectedly, both NRP2 and THBD also promote dimerization of Pentamer. Our results provide a framework for understanding HCMV receptor engagement, cell entry, antibody neutralization, and outline strategies for antiviral therapies against HCMV.

The cancer-associated fibroblast (CAF) marker podoplanin (PDPN) is generally correlated with poor clinical outcomes in cancer patients and thus represents a promising therapeutic target. Despite its biomedical relevance, basic aspects of PDPN biology such as its cellular functions and cell surface ligands remain poorly uncharacterized, thus challenging drug development. Here, we utilize a high throughput platform to elucidate the PDPN cell surface interactome, and uncover the neutrophil protein CD177 as a new binding partner. Quantitative proteomics analysis of the CAF phosphoproteome reveals a role for PDPN in cell signaling, growth and actomyosin contractility, among other processes. Moreover, cellular assays demonstrate that CD177 is a functional antagonist, recapitulating the phenotype observed in PDPN-deficient CAFs. In sum, starting from the unbiased elucidation of the PDPN co-receptome, our work provides insights into PDPN functions and reveals the PDPN/CD177 axis as a possible modulator of fibroblast physiology in the tumor microenvironment., Competing Interests: Y.S., S.G., V.C.P., C.C., J.R.L., and S.J.T. are Genentech employees and own shares in the Genentech/Roche group. J.L.A, S.K., B.H., E.V., S.M.P., A.A.P., L.G. and N.M.M. were employees of Roche when the data in this paper was generated.

Cell surface receptors are critical for cell signaling and constitute a quarter of all human genes. Despite their importance and abundance, receptor interaction networks remain understudied because of difficulties associated with maintaining membrane proteins in their native conformation and their typically weak interactions. To overcome these challenges, we developed an extracellular vesicle-based method for membrane protein display that enables purification-free and high-throughput detection of receptor-ligand interactions in membranes. We demonstrate that this platform is broadly applicable to a variety of membrane proteins, enabling enhanced detection of extracellular interactions over a wide range of binding affinities. We were able to recapitulate and expand the interactome for prominent members of the B7 family of immunoregulatory proteins such as PD-L1/CD274 and B7-H3/CD276. Moreover, when applied to the orphan cancer-associated fibroblast protein, LRRC15, we identified a membrane-dependent interaction with the tumor stroma marker TEM1/CD248. Furthermore, this platform enabled profiling of cellular receptors for target-expressing as well as endogenous extracellular vesicles. Overall, this study presents a sensitive and easy to use screening platform that bypasses membrane protein purification and enables characterization of interactomes for any cell surface-expressed target of interest in its native state., Competing Interests: Competing interest statement: All authors except C.M.A. are Genentech employees and own shares in the Roche/Genentech group., (Copyright © 2021 the Author(s). Published by PNAS.)

Background: Digital phenotyping (also known as personal sensing, intelligent sensing, or body computing) involves the collection of biometric and personal data in situ from digital devices, such as smartphones, wearables, or social media, to measure behavior or other health indicators. The collected data are analyzed to generate moment-by-moment quantification of a person's mental state and potentially predict future mental states. Digital phenotyping projects incorporate data from multiple sources, such as electronic health records, biometric scans, or genetic testing. As digital phenotyping tools can be used to study and predict behavior, they are of increasing interest for a range of consumer, government, and health care applications. In clinical care, digital phenotyping is expected to improve mental health diagnoses and treatment. At the same time, mental health applications of digital phenotyping present significant areas of ethical concern, particularly in terms of privacy and data protection, consent, bias, and accountability., Objective: This study aims to develop consensus statements regarding key areas of ethical guidance for mental health applications of digital phenotyping in the United States., Methods: We used a modified Delphi technique to identify the emerging ethical challenges posed by digital phenotyping for mental health applications and to formulate guidance for addressing these challenges. Experts in digital phenotyping, data science, mental health, law, and ethics participated as panelists in the study. The panel arrived at consensus recommendations through an iterative process involving interviews and surveys. The panelists focused primarily on clinical applications for digital phenotyping for mental health but also included recommendations regarding transparency and data protection to address potential areas of misuse of digital phenotyping data outside of the health care domain., Results: The findings of this study showed strong agreement related to these ethical issues in the development of mental health applications of digital phenotyping: privacy, transparency, consent, accountability, and fairness. Consensus regarding the recommendation statements was strongest when the guidance was stated broadly enough to accommodate a range of potential applications. The privacy and data protection issues that the Delphi participants found particularly critical to address related to the perceived inadequacies of current regulations and frameworks for protecting sensitive personal information and the potential for sale and analysis of personal data outside of health systems., Conclusions: The Delphi study found agreement on a number of ethical issues to prioritize in the development of digital phenotyping for mental health applications. The Delphi consensus statements identified general recommendations and principles regarding the ethical application of digital phenotyping to mental health. As digital phenotyping for mental health is implemented in clinical care, there remains a need for empirical research and consultation with relevant stakeholders to further understand and address relevant ethical issues., (©Nicole Martinez-Martin, Henry T Greely, Mildred K Cho. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 28.07.2021.)

Myeloid cells encounter stromal cells and their matrix determinants on a continual basis during their residence in any given organ. Here, we examined the impact of the collagen receptor LAIR1 on myeloid cell homeostasis and function. LAIR1 was highly expressed in the myeloid lineage and enriched in non-classical monocytes. Proteomic definition of the LAIR1 interactome identified stromal factor Colec12 as a high-affinity LAIR1 ligand. Proteomic profiling of LAIR1 signaling triggered by Collagen1 and Colec12 highlighted pathways associated with survival, proliferation, and differentiation. Lair1 -/- mice had reduced frequencies of Ly6C - monocytes, which were associated with altered proliferation and apoptosis of non-classical monocytes from bone marrow and altered heterogeneity of interstitial macrophages in lung. Myeloid-specific LAIR1 deficiency promoted metastatic growth in a melanoma model and LAIR1 expression associated with improved clinical outcomes in human metastatic melanoma. Thus, monocytes and macrophages rely on LAIR1 sensing of stromal determinants for fitness and function, with relevance in homeostasis and disease., Competing Interests: Declarations of interests All authors are stockholders of Genentech/Roche except B.H., A.W., E.V., and S.C., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Human cytomegalovirus (HCMV) infects the majority of the human population and represents the leading viral cause of congenital birth defects. HCMV utilizes the glycoproteins gHgLgO (Trimer) to bind to platelet-derived growth factor receptor alpha (PDGFRα) and transforming growth factor beta receptor 3 (TGFβR3) to gain entry into multiple cell types. This complex is targeted by potent neutralizing antibodies and represents an important candidate for therapeutics against HCMV. Here, we determine three cryogenic electron microscopy (cryo-EM) structures of the trimer and the details of its interactions with four binding partners: the receptor proteins PDGFRα and TGFβR3 as well as two broadly neutralizing antibodies. Trimer binding to PDGFRα and TGFβR3 is mutually exclusive, suggesting that they function as independent entry receptors. In addition, Trimer-PDGFRα interaction has an inhibitory effect on PDGFRα signaling. Our results provide a framework for understanding HCMV receptor engagement, neutralization, and the development of anti-viral strategies against HCMV., Competing Interests: Declaration of interests L.R., C.P.A., H.H., I.K., M.C.J., E.K, A.L.R., N.M.-M., J.P., and C.C. are Genentech/Roche employees and own shares in the Genentech/Roche group. All other authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Dysfunction of embryo transport causes ectopic pregnancy which affects approximately 2% of conceptions in the US and Europe, and is the most common cause of pregnancy-related death in the first trimester. Embryo transit involves a valve-like tubal-locking phenomenon that temporarily arrests oocytes at the ampullary-isthmic junction (AIJ) where fertilisation occurs, but the mechanisms involved are unknown. Here we show that female mice lacking the orphan adhesion G-protein coupled receptor Adgrd1 are sterile because they do not relieve the AIJ restraining mechanism, inappropriately retaining embryos within the oviduct. Adgrd1 is expressed on the oviductal epithelium and the post-ovulatory attenuation of tubal fluid flow is dysregulated in Adgrd1-deficient mice. Using a large-scale extracellular protein interaction screen, we identified Plxdc2 as an activating ligand for Adgrd1 displayed on cumulus cells. Our findings demonstrate that regulating oviductal fluid flow by Adgrd1 controls embryo transit and we present a model where embryo arrest at the AIJ is due to the balance of abovarial ciliary action and the force of adovarial tubal fluid flow, and in wild-type oviducts, fluid flow is gradually attenuated through Adgrd1 activation to enable embryo release. Our findings provide important insights into the molecular mechanisms involved in embryo transport in mice.

Ambient intelligence is increasingly finding applications in health-care settings, such as helping to ensure clinician and patient safety by monitoring staff compliance with clinical best practices or relieving staff of burdensome documentation tasks. Ambient intelligence involves using contactless sensors and contact-based wearable devices embedded in health-care settings to collect data (eg, imaging data of physical spaces, audio data, or body temperature), coupled with machine learning algorithms to efficiently and effectively interpret these data. Despite the promise of ambient intelligence to improve quality of care, the continuous collection of large amounts of sensor data in health-care settings presents ethical challenges, particularly in terms of privacy, data management, bias and fairness, and informed consent. Navigating these ethical issues is crucial not only for the success of individual uses, but for acceptance of the field as a whole., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Social distancing measures due to the COVID-19 pandemic have accelerated the adoption and implementation of digital mental health tools. Psychiatry and therapy sessions are being conducted via videoconferencing platforms, and the use of digital mental health tools for monitoring and treatment has grown. This rapid shift to telehealth during the pandemic has given added urgency to the ethical challenges presented by digital mental health tools. Regulatory standards have been relaxed to allow this shift to socially distanced mental health care. It is imperative to ensure that the implementation of digital mental health tools, especially in the context of this crisis, is guided by ethical principles and abides by professional codes of conduct. This paper examines key areas for an ethical path forward in this digital mental health revolution: privacy and data protection, safety and accountability, and access and fairness., (©Nicole Martinez-Martin, Ishan Dasgupta, Adrian Carter, Jennifer A Chandler, Philipp Kellmeyer, Karola Kreitmair, Anthony Weiss, Laura Y Cabrera. Originally published in JMIR Mental Health (http://mental.jmir.org), 22.12.2020.)

Cell surface receptors and their interactions play a central role in physiological and pathological signaling. Despite its clinical relevance, the immunoglobulin superfamily (IgSF) remains uncharacterized and underrepresented in databases. Here, we present a systematic extracellular protein map, the IgSF interactome. Using a high-throughput technology to interrogate most single transmembrane receptors for binding to 445 IgSF proteins, we identify over 500 interactions, 82% previously undocumented, and confirm more than 60 receptor-ligand pairs using orthogonal assays. Our study reveals a map of cell-type-specific interactions and the landscape of dysregulated receptor-ligand crosstalk in cancer, including selective loss of function for tumor-associated mutations. Furthermore, investigation of the IgSF interactome in a large cohort of cancer patients identifies interacting protein signatures associated with clinical outcome. The IgSF interactome represents an important resource to fuel biological discoveries and a framework for understanding the functional organization of the surfaceome during homeostasis and disease, ultimately informing therapeutic development., Competing Interests: Declaration of Interests B.H., Y. Senbabaoglu, I.L., T.A.A., B.W., C.B., Y.F., P.C., A.W.W., L.C.G., S.M., S.J.T., J.R.L., and N.M.-M. are Genentech employees and own shares in the Roche group., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Digital contact tracing, in combination with widespread testing, has been a focal point for many plans to "reopen" economies while containing the spread of Covid-19. Most digital contact tracing projects in the United States and Europe have prioritized privacy protections in the form of local storage of data on smartphones and the deidentification of information. However, in the prioritization of privacy in this narrow form, there is not sufficient attention given to weighing ethical trade-offs within the context of a public health pandemic or to the need to evaluate safety and effectiveness of software-based technology applied to public health., (© 2020 The Hastings Center.)

Receptors expressed on the plasma membrane and their interacting partners critically regulate cellular communication during homeostasis and disease, and as such represent main therapeutic targets. Despite its importance for drug development, receptor-ligand proteomics has remained a daunting field, in part because of the challenges associated to the study of membrane-expressed proteins. Here, to enable sensitive detection of receptor-ligand interactions in high throughput, we implement a new platform, the Conditioned Media AlphaScreen, for interrogation of a library consisting of most single transmembrane human proteins. Using this method to study key immune receptors, we identify and further validate the interleukin receptor IL20RA as the first binding partner for the checkpoint inhibitor B7-H3. Further, KIR2DL5, a natural killer cell protein that had remained orphan, is uncovered as a functional binding partner for the poliovirus receptor (PVR). This interaction is characterized using orthogonal assays, which demonstrate that PVR specifically engages KIR2DL5 on natural killer cells leading to inhibition of cytotoxicity. Altogether, these results reveal unappreciated links between protein families that may importantly influence receptor-driven functions during disease. Applicable to any target of interest, this technology represents a versatile and powerful approach for elucidation of receptor-ligand interactomes, which is essential to understand basic aspects of the biology of the plasma membrane proteins and ultimately inform the development of novel therapeutic strategies., (© 2019 Husain et al.)

In response to environmental and nutrient stress, adipose tissues must establish a new homeostatic state. Here we show that cold exposure of obese mice triggers an adaptive tissue remodeling in visceral adipose tissue (VAT) that involves extracellular matrix deposition, angiogenesis, sympathetic innervation, and adipose tissue browning. Obese VAT is predominated by pro-inflammatory M1 macrophages; cold exposure induces an M1-to-M2 shift in macrophage composition and dramatic changes in macrophage gene expression in both M1 and M2 macrophages. Antibody-mediated CSF1R blocking prevented the cold-induced recruitment of adipose tissue M2 macrophages, suggesting the role of CSF1R signaling in the process. These cold-induced effects in obese VAT are phenocopied by an administration of the FGF21-mimetic antibody, consistent with its action to stimulate sympathetic nerves. Collectively, these studies illuminate adaptive visceral adipose tissue plasticity in obese mice in response to cold stress and antibody-based metabolic therapy.

IL-17 family cytokines are critical to host defense responses at cutaneous and mucosal surfaces. Whereas IL-17A, IL-17F, and IL-17C induce overlapping inflammatory cascades to promote neutrophil-mediated immunity, IL-17E/IL-25 drives type 2 immune pathways and eosinophil activity. Genetic and pharmacological studies reveal the significant contribution these cytokines play in antimicrobial and autoimmune mechanisms. However, little is known about the related family member, IL-17B, with contrasting reports of both pro- and anti-inflammatory function in rodents. We demonstrate that in the human immune system, IL-17B is functionally similar to IL-25 and elicits type 2 cytokine secretion from innate type 2 lymphocytes, NKT, and CD4 + CRTH2 + Th2 cells. Like IL-25, this activity is dependent on the IL-17RA and IL-17RB receptor subunits. Furthermore, IL-17B can augment IL-33-driven type 2 responses. These data position IL-17B as a novel component in the regulation of human type 2 immunity., (Copyright © 2019 by The American Association of Immunologists, Inc.)