Nearly one-third of patients with inflammatory breast cancer (IBC) present with de novo stage IV disease. There are limited data on frequency and clinical outcomes of contralateral axillary metastasis (CAM) in IBC with no consensus diagnostic and treatment guidelines. Frequency of synchronous CAM was calculated in unilateral IBC patients at a single center (10/2004-6/2019). Clinicopathologic variables, diagnostic evaluation, treatment received, and overall survival (OS) were assessed and compared. Of 588 unilateral IBC patients, 49 (8.3%) had synchronous CAM. Of these, 32 (65.3%) also presented with metastatic disease at another distant site. CAM was not associated with age, tumor laterality, breast cancer subtype, grade, or cN stage (p > 0.05). The sensitivity/specificity to detect CAM was as follows mammography (18.2%/99.2%), ultrasound (92.3%/95.5%), PET (90.1/99.1%), and MRI (76.0%/98.6%). Following systemic therapy, 22 patients had contralateral axillary surgery, and 18 received adjuvant contraluch-needed prospective clinical trials evaluating management and outcomes of CAM in IBC. The advent of immune checkpoint blockade (ICB) has led to significantly improved disease outcome in lung adenocarcinoma (ADC), but response of ALK/EGFR-positive tumors to immune therapy is limited. The underlying immune biology is incompletely understood. We performed comparative mRNA expression profiling of 31 ALK-positive, 40 EGFR-positive and 43 ALK/EGFR-negative lung ADC focused on immune gene expression. The presence and levels of tumor infiltration lymphocytes (TILs) as well as fourteen specific immune cell populations were estimated from the gene expression profiles. While total TILs were not lower in ALK-positive and EGFR-positive tumors compared to ALK/EGFR-negative tumors, specific immunosuppressive characteristics were detected in both subgroups In ALK-positive tumors, regulatory T cells were significantly higher compared to EGFR-positive (fold change FC = 1.9, p = 0.0013) and ALK/EGFR-negative tumors (FC = 2.1, p = 0.00047). In EGFR-positive tumors, cytotoxic cells were significantly lower cg cancer biopsies. Significant immune reactivity including specific immunosuppressive characteristics in ALK- and EGFR-positive lung ADC, but not a total absence of immune infiltration supports further clinical evaluation of immune-modulators as partners of ICB in such tumors. Patients with Lynch syndrome have a high probability of developing colorectal and other carcinomas. This review provides a comprehensive assessment of the immunologic aspects of Lynch syndrome pathogenesis and provides an overview of potential immune interventions for patients with Lynch syndrome polyps and Lynch syndrome-associated carcinomas. Immunogenic properties of the majority of Lynch syndrome polyps and associated cancers include microsatellite instability leading to a high mutational burden and the development of novel frameshift peptides, i.e., neoantigens. In addition, patients with Lynch syndrome develop T cell responses in the periphery and in the tumor microenvironment (TME) to tumor-associated antigens, and a proinflammatory cytokine TME has also been identified. However, Lynch syndrome lesions also possess immunosuppressive entities such as alterations in MHC class I antigen presentation, TGFβ receptor mutations, regulatory T cells, and upregulation of PD-L1 on tumor-associated lymphocytesn, TGFβ receptor mutations, regulatory T cells, and upregulation of PD-L1 on tumor-associated lymphocytes. The rich immune microenvironment of Lynch syndrome polyps and associated carcinomas provides an opportunity to employ the spectrum of immune-mediating agents now available to induce and enhance host immune responses and/or to also reduce immunosuppressive entities. These agents can be employed in the so-called prevention trials for the treatment of patients with Lynch syndrome polyps and for trials in patients with Lynch syndrome-associated cancers.The case-cohort design, among many two-phase sampling designs, substantially reduces the cost of an epidemiological study by selecting more informative participants within the full cohort for expensive variable measurements. Despite their benefits, additive hazards models, which estimate hazard differences, have rarely been used for the analysis of case-cohort studies due to the lack of software and application examples. In this paper, we describe a newly developed estimation method that fits the additive hazards models to general two-phase sampling studies along with the R package addhazard that implements it. It allows for missing covariates among cases, cohort stratification, robust variances, and the incorporation of auxiliary information from the full cohort to enhance inference precision. We demonstrate the use of this tool to estimate the association of the risk of coronary heart disease (CHD) with biomarkers high-sensitivity C-reactive protein (hs-CRP) and Lipoprotein-associated phospholipase A2 (Lp-Pthe high-risk population of CHD that the traditional risk factors such as the LDL-C may miss. Epidemiologists are encouraged to use this new tool to analyze other case-cohort studies and incorporate auxiliary variables embedded in the full cohort in their analysis.This study aimed to investigate the self-reported measures of concurrent disorders (stress, social anxiety, anxiety, depression and alcohol use) among electronic gaming machine (EGM) gamblers with varying levels of gambling severity and to examine its relationship to decision-making. see more This cross-sectional study in New Zealand involved an online survey that utilised validated questionnaires to assess self-reported measures of concurrent disorders and the Iowa gambling task (IGT) to analyse decision-making. The study comprised of active EGM gamblers (n = 153) who were divided into two groups non-problem gambling (NPG, n = 71) and problem gambling (PG, n = 82) based on the cut-off point of the South Oaks Gambling Screen (SOGS). Multiple logistic regression models were performed to analyse co-occurring disorders separately and simultaneously, and a log-linear model was developed to define the associations between significant variables. The first model showed a strong correlation between gambling severity and measures for depression (p  less then  0.