Audience Prospecting for Dynamic-Product-Ads in Native Advertising

With yearly revenue exceeding one billion USD, Yahoo Gemini native advertising marketplace serves more than two billion impressions daily to hundreds of millions of unique users. One of the fastest growing segments of Gemini native is dynamic-product-ads (DPA), where major advertisers, such as Amazon and Walmart, provide catalogs with millions of products for the system to choose from and present to users. The subject of this work is finding and expanding the right audience for each DPA ad, which is one of the many challenges DPA presents. Approaches such as targeting various user groups, e.g., users who already visited the advertisers' websites (Retargeting), users that searched for certain products (Search-Prospecting), or users that reside in preferred locations (Location-Prospecting), have limited audience expansion capabilities. In this work we present two new approaches for audience expansion that also maintain predefined performance goals. The Conversion-Prospecting approach predicts DPA conversion rates based on Gemini native logged data, and calculates the expected cost-per-action (CPA) for determining users' eligibility to products and optimizing DPA bids in Gemini native auctions. To support new advertisers and products, the Trending-Prospecting approach matches trending products to users by learning their tendency towards products from advertisers' sites logged events. The tendency scores indicate the popularity of the product and the similarity of the user to those who have previously engaged with this product. The two new prospecting approaches were tested online, serving real Gemini native traffic, demonstrating impressive DPA delivery and DPA revenue lifts while maintaining most traffic within the acceptable CPA range (i.e., performance goal). After a successful testing phase, the proposed approaches are currently in production and serve all Gemini native traffic.Comment: In Proc. IeeeBigData'2023 (Industry and Government Program

A reference map of potential determinants for the human serum metabolome

The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment(1). The origins of specific compounds are known, including metabolites that are highly heritable(2,3), or those that are influenced by the gut microbiome(4), by lifestyle choices such as smoking(5), or by diet(6). However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts(7,8) that were not available to us when we trained the algorithms. We used feature attribution analysis(9) to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.The levels of 1,251 metabolites are measured in 475 phenotyped individuals, and machine-learning algorithms reveal that diet and the microbiome are the determinants with the strongest predictive power for the levels of these metabolites

CCL24 regulates biliary inflammation and fibrosis in primary sclerosing cholangitis

ˆCCL24 is a pro-fibrotic, pro-inflammatory chemokine expressed in several chronic fibrotic diseases. In the liver, CCL24 plays a role in fibrosis and inflammation, and blocking CCL24 led to reduced liver injury in experimental models. We studied the role of CCL24 in primary sclerosing cholangitis (PSC) and evaluated the potential therapeutic effect of blocking CCL24 in this disease. Multidrug resistance gene 2-knockout (Mdr2-/-) mice demonstrated CCL24 expression in liver macrophages and were used as a relevant experimental PSC model. CCL24-neutralizing monoclonal antibody, CM-101, significantly improved inflammation, fibrosis, and cholestasis-related markers in the biliary area. Moreover, using spatial transcriptomics, we observed reduced proliferation and senescence of cholangiocytes following CCL24 neutralization. Next, we demonstrated that CCL24 expression was elevated under pro-fibrotic conditions in primary human cholangiocytes and macrophages, and it induced proliferation of primary human hepatic stellate cells and cholangiocytes, which was attenuated following CCL24 inhibition. Correspondingly, CCL24 was found to be highly expressed in liver biopsies of patients with PSC. CCL24 serum levels correlated with Enhanced Liver Fibrosis score, most notably in patients with high alkaline phosphatase levels. These results suggest that blocking CCL24 may have a therapeutic effect in patients with PSC by reducing liver inflammation, fibrosis, and cholestasis

Prediction of acute myeloid leukaemia risk in healthy individuals

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure(1). The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion(2,3). However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)(4-8). Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention

Low Norton Scale Score Predicts Worse Outcomes for Parkinson’s Disease Patients Hospitalized Due to Infection

Background: Parkinson’s disease (PD) patients are prone to infections leading to hospitalization. We used the Norton Scale score (NSS) as a prognostic tool for these patients. Method: Retrospective analysis of consecutive PD patients, all had NSS appreciation upon admission. Analyses were made to establish the association between NSS upon admission, short-term, and long-term clinical outcomes. Results: Five hundred twenty-eight PD patients’ records were reviewed, of which 81 were eligible for analysis. Patients who died during hospitalization had a significantly lower NSS (10.0 vs. 13.1, p = .026). Among surviving patients, those who were discharged to more intensive care facilities relative to their original place of arrival also had a significantly lower NSS (10.38 vs. 13.63, p = .0002). Lower NSS was found to increase the risk for 1-year mortality (odds ratio = 1.3; 95% confidence interval = [1.09, 1.56], p = .003). Conclusion: Lower NSS upon admission of PD patients, suffering from infection is associated with worse clinical outcomes

A pilot study exploring the use of hyaluronic acid in treating insertional achilles tendinopathy

Purpose This study explores the use of ultrasound-guided Hyaluronic Acid (HA) injections for Insertional Achilles Tendinopathy (IAT). Methods A cohort of 15 ankles diagnosed with IAT received three weekly ultrasound-guided HA injections. The Victorian Institute of Sport Assessment – Achilles (VISA-A) questionnaire scored the severity of symptoms and functional impairment before treatment, and at one and six months post-treatment. Results Significant improvement was observed in VISA-A scores post-treatment, rising from an average baseline of 34.8 ± 15.2 (11-63) to 53.6 ± 20.9 (15-77) after one month, and then to 50.7 ± 18.6 (20-75) after six months. No adverse reactions were noted, underscoring the safety of the intervention. Conclusion The pilot study presents HA injections as a potentially effective treatment for IAT, while interpretation of these findings must take into account the variability in results, indicating a range of patient responses. It encourages further research to confirm these findings and to explore HA’s full potential in managing IAT, despite the limitations of a small sample size and lack of control group