Sequences of purchases in credit card data reveal life styles in urban populations

Zipf-like distributions characterize a wide set of phenomena in physics, biology, economics and social sciences. In human activities, Zipf-laws describe for example the frequency of words appearance in a text or the purchases types in shopping patterns. In the latter, the uneven distribution of transaction types is bound with the temporal sequences of purchases of individual choices. In this work, we define a framework using a text compression technique on the sequences of credit card purchases to detect ubiquitous patterns of collective behavior. Clustering the consumers by their similarity in purchases sequences, we detect five consumer groups. Remarkably, post checking, individuals in each group are also similar in their age, total expenditure, gender, and the diversity of their social and mobility networks extracted by their mobile phone records. By properly deconstructing transaction data with Zipf-like distributions, this method uncovers sets of significant sequences that reveal insights on collective human behavior.Comment: 30 pages, 26 figure

Synthesis of Indoles and Pyrroles Utilizing Iridium Carbenes Generated from Sulfoxonium Ylides

Accepted manuscript version. Published version available at https://doi.org/10.1002/anie.201610520.Metal carbenes can undergo a myriad of synthetic transformations. Sulfur ylides are potential safe precursors of metal carbenes. Herein, we report cascade reactions that involve carbenoids derived from sulfoxonium ylides for the efficient and regioselective synthesis of indoles and pyrroles. The tandem action of iridium and Brønsted acid catalysts enables rapid assembly of the heterocycles from unmodified anilines or readily accessible enamines under microwave irradiation. The key mechanistic steps are the catalytic transformation of the sulfoxonium ylide into an iridium–carbene complex, followed by N−H or C−H functionalization of an aniline or enamine, respectively, and a final acid‐catalyzed cyclization. The present method was successfully applied to the synthesis of the densely functionalized pyrrole subunit of atorvastatin

Child Marriages and Unions in Latin America: Understanding the Roles of Agency and Social Norms

El propósito de este artículo es demostrar que los matrimonios y las uniones infantiles pueden infringir los derechos sexuales y reproductivos de adolescentes y jóvenes. Indica que las intervenciones promueven cada vez más estrategias para transformar las normas sociales. Presenta los resultados de un análisis de secundario de casos cruzados de tres estudios cualitativos: en Brasil, Guatemala y Honduras. Se trató de entender las prácticas matrimoniales. En los tres casos, la agencia como las normas sociales siempre desempeñaron un papel en el matrimonio y/o uniones de los niños

Climate Change and Global Food Systems: Potential Impacts on Food Security and Undernutrition.

Great progress has been made in addressing global undernutrition over the past several decades, in part because of large increases in food production from agricultural expansion and intensification. Food systems, however, face continued increases in demand and growing environmental pressures. Most prominently, human-caused climate change will influence the quality and quantity of food we produce and our ability to distribute it equitably. Our capacity to ensure food security and nutritional adequacy in the face of rapidly changing biophysical conditions will be a major determinant of the next century's global burden of disease. In this article, we review the main pathways by which climate change may affect our food production systems-agriculture, fisheries, and livestock-as well as the socioeconomic forces that may influence equitable distribution

Use of Machine Learning Consensus Clustering to Identify Distinct Subtypes of Black Kidney Transplant Recipients and Associated Outcomes

Importance: Among kidney transplant recipients, Black patients continue to have worse graft function and reduced patient and graft survival. Better understanding of different phenotypes and subgroups of Black kidney transplant recipients may help the transplant community to identify individualized strategies to improve outcomes among these vulnerable groups. Objective: To cluster Black kidney transplant recipients in the US using an unsupervised machine learning approach. Design, Setting, and Participants: This cohort study performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in Black kidney transplant recipients in the US from January 1, 2015, to December 31, 2019, in the Organ Procurement and Transplantation Network/United Network for Organ Sharing database. Each cluster\u27s key characteristics were identified using the standardized mean difference, and subsequently the posttransplant outcomes were compared among the clusters. Data were analyzed from June 9 to July 17, 2021. Exposure: Machine learning consensus clustering approach. Main Outcomes and Measures: Death-censored graft failure, patient death within 3 years after kidney transplant, and allograft rejection within 1 year after kidney transplant. Results: Consensus cluster analysis was performed for 22 687 Black kidney transplant recipients (mean [SD] age, 51.4 [12.6] years; 13 635 men [60%]), and 4 distinct clusters that best represented their clinical characteristics were identified. Cluster 1 was characterized by highly sensitized recipients of deceased donor kidney retransplants; cluster 2, by recipients of living donor kidney transplants with no or short prior dialysis; cluster 3, by young recipients with hypertension and without diabetes who received young deceased donor transplants with low kidney donor profile index scores; and cluster 4, by older recipients with diabetes who received kidneys from older donors with high kidney donor profile index scores and extended criteria donors. Cluster 2 had the most favorable outcomes in terms of death-censored graft failure, patient death, and allograft rejection. Compared with cluster 2, all other clusters had a higher risk of death-censored graft failure and death. Higher risk for rejection was found in clusters 1 and 3, but not cluster 4. Conclusions and Relevance: In this cohort study using an unsupervised machine learning approach, the identification of clinically distinct clusters among Black kidney transplant recipients underscores the need for individualized care strategies to improve outcomes among vulnerable patient groups

A pro-inflammatory signalome is constitutively activated by C33Y mutant TNF receptor 1 in TNF receptor-associated periodic syndrome (TRAPS)

Mutations in TNFRSF1A encoding TNF receptor 1 (TNFR1) cause the autosomal dominant TNF receptor-associated periodic syndrome (TRAPS): a systemic autoinflammatory disorder. Misfolding, intracellular aggregation, and ligand-independent signaling by mutant TNFR1 are central to disease pathophysiology. Our aim was to understand the extent of signaling pathway perturbation in TRAPS. A prototypic mutant TNFR1 (C33Y), and wild-type TNFR1 (WT), were expressed at near physiological levels in an SK-Hep-1 cell model. TNFR1-associated signaling pathway intermediates were examined in this model, and in PBMCs from C33Y TRAPS patients and healthy controls. In C33Y-TNFR1-expressing SK-Hep-1 cells and TRAPS patients' PBMCs, a subtle, constitutive upregulation of a wide spectrum of signaling intermediates and their phosphorylated forms was observed; these were associated with a proinflammatory/antiapoptotic phenotype. In TRAPS patients' PBMCs, this upregulation of proinflammatory signaling pathways was observed irrespective of concurrent treatment with glucocorticoids, anakinra or etanercept, and the absence of overt clinical symptoms at the time that the blood samples were taken. This study reveals the pleiotropic effect of a TRAPS-associated mutant form of TNFR1 on inflammatory signaling pathways (a proinflammatory signalome), which is consistent with the variable and limited efficacy of cytokine-blocking therapies in TRAPS. It highlights new potential target pathways for therapeutic intervention

Data cooperatives as catalysts for collaboration, data sharing, and the (trans)formation of the digital commons

Network effects, economies of scale, and lock-in-effects increasingly lead to a concentration of digital resources and capabilities, hindering the free and equitable development of digital entrepreneurship (SDG9), new skills, and jobs (SDG8), especially in small communities (SDG11) and their small and medium-sized enterprises (“SMEs”). To ensure the affordability and accessibility of technologies, promote digital entrepreneurship and community well-being (SDG3), and protect digital rights, we propose data cooperatives [1,2] as a vehicle for secure, trusted, and sovereign data exchange [3,4]. In post-pandemic times, community/SME-led cooperatives can play a vital role by ensuring that supply chains to support digital commons are uninterrupted, resilient, and decentralized [5]. Digital commons and data sovereignty provide communities with affordable and easy access to information and the ability to collectively negotiate data-related decisions. Moreover, cooperative commons (a) provide access to the infrastructure that underpins the modern economy, (b) preserve property rights, and (c) ensure that privatization and monopolization do not further erode self-determination, especially in a world increasingly mediated by AI. Thus, governance plays a significant role in accelerating communities’/SMEs’ digital transformation and addressing their challenges. Cooperatives thrive on digital governance and standards such as open trusted Application Programming Interfaces (APIs) that increase the efficiency, technological capabilities, and capacities of participants and, most importantly, integrate, enable, and accelerate the digital transformation of SMEs in the overall process. This policy paper presents and discusses several transformative use cases for cooperative data governance. The use cases demonstrate how platform/data-cooperatives, and their novel value creation can be leveraged to take digital commons and value chains to a new level of collaboration while addressing the most pressing community issues. The proposed framework for a digital federated and sovereign reference architecture will create a blueprint for sustainable development both in the Global South and North