Identifying Outcomes and Gaps Impacting Tobacco Control and Prevention in African American Communities

Great racial disparities exist in smoking and related health outcomes in the United States. African American (AA) smokers start smoking later and smoke less than white smokers but are less likely to quit. In 2008, the CDC’s Office on Smoking and Health funded the National African American Tobacco Prevention Network (NAATPN) to focus tobacco control leadership, expertise and promotion in the AA community. In 2012, NAATPN sought to determine significant outcomes of tobacco control efforts impacting Black and AA communities by conducting a qualitative document search and series of interviews with experts in the field. Thirteen identified outcomes were categorized into five broad classifications: 1) Menthol: Emergence of menthol as a focus for advocacy, policy and research; 2) Policy and Legal: Public policy and legal action aimed at reducing tobacco usage and consumption; 3) Advocacy: Focus on national networking to facilitate growth of local, organic, and grassroots capacity in AA communities; 4) Diversity: Emergence of diversity and inclusivity as values and principles used in shaping/driving policy, advocacy, and outreach; and 5) Cessation: Creation of a cessation guide for the AA community. The identified outcomes can be used by public health practitioners in furthering their efforts to address and reduce tobacco use disparities in the AA community

Immunoglobulin-resistant delayed hemolytic transfusion reaction treated with rituximab in an adult sickle cell patient.

Clinical presentation of the immunoglobulin (Ig)-resistant DHTR episode in a adult patient with SC

Prosodic tools for language learning

In this paper we will be concerned with the role played by prosody in language learning and by the speech technology already available as commercial product or as prototype, capable to cope with the task of helping language learner in improving their knowledge of a second language from the prosodic point of view. The paper has been divided into two separate sections: Section One, dealing with Rhythm and all related topics; Section Two dealing with Intonation. In the Introduction we will argue that the use of ASR (Automatic Speech Recognition) as Teaching Aid should be under-utilized and should be targeted to narrowly focussed spoken exercises, disallowing open-ended dialogues, in order to ensure consistency of evaluation. Eventually, we will support the conjoined use of ASR technology and prosodic tools to produce GOP useable for linguistically consistent and adequate feedback to the student. This will be illustrated by presenting State of the Art for both sections, with systems well documented in the scientific literature of the respective field. In order to discuss the scientific foundations of prosodic analysis we will present data related to English and Italian and make comparisons to clarify the issues at hand. In this context, we will also present the Prosodic Module of a courseware for computer-assisted foreign language learning called SLIM—an acronym for Multimedia Interactive Linguistic Software, developed at the University of Venice (Delmonte et al. in Convegno GFS-AIA, pp. 47–58, 1996a; Ed-Media 96, AACE, pp. 326–333, 1996b). The Prosodic Module has been created in order to deal with the problem of improving a student’s performance both in the perception and production of prosodic aspects of spoken language activities. It is composed of two different sets of Learning Activities, the first one dealing with phonetic and prosodic problems at word level and at syllable level; the second one dealing with prosodic aspects at phonological phrase and utterance suprasegmental level. The main goal of Prosodic Activities is to ensure consistent and pedagogically sound feedback to the student intending to improve his/her pronunciation in a foreign language

Efficacy of nivolumab in pre-treated non-small-cell lung cancer patients harbouring KRAS mutations

Background: The present study investigated the efficacy and safety of nivolumab in pre-treated patients with advanced NSCLC harbouring KRAS mutations. Methods: Clinical data and KRAS mutational status were analysed in patients treated with nivolumab within the Italian Expanded Access Program. Objective response rate, progression-free survival and overall survival were evaluated. Patients were monitored for adverse events using the National Cancer Institute Common Terminology Criteria for Adverse Events. Results: Among 530 patients evaluated for KRAS mutations, 206 (39%) were positive while 324 (61%) were KRAS wild-type mutations. KRAS status did not influence nivolumab efficacy in terms of ORR (20% vs 17%, P = 0.39) and DCR (47% vs 41%, P = 0.23). The median PFS and OS were 4 vs 3 months (P = 0.5) and 11.2 vs 10 months (P = 0.8) in the KRAS-positive vs the KRAS-negative group. The 3-months PFS rate was significantly higher in the KRAS-positive group as compared to the KRAS-negative group (53% vs 42%, P = 0.01). The percentage of any grade and grade 3–4 AEs were 45% vs 33% (P = 0.003) and 11% vs 6% (P = 0.03) in KRAS-positive and KRAS-negative groups, respectively. Conclusions: Nivolumab is an effective and safe treatment option for patients with previously treated, advanced non-squamous NSCLC regardless of KRAS mutations

Detection of ice core particles via deep neural networks

Insoluble particles in ice cores record signatures of past climate parameters like vegetation, volcanic activity or aridity. Their analytical detection depends on intensive bench microscopy investigation and requires dedicated sample preparation steps. Both are laborious, require in-depth knowledge and often restrict sampling strategies. To help overcome these limitations, we present a framework based on Flow Imaging Microscopy coupled to a deep neural network for autonomous image classification of ice core particles. We train the network to classify 7 commonly found classes: mineral dust, felsic and basaltic volcanic ash (tephra), three species of pollen (Corylus avellana, Quercus robur, Quercus suber) and contamination particles that may be introduced onto the ice core surface during core handling operations. The trained network achieves 96.8 % classification accuracy at test time. We present the system’s potentials and limitations with respect to the detection of mineral dust, pollen grains and tephra shards, using both controlled materials and real ice core samples. The methodology requires little sample material, is non destructive, fully reproducible and does not require any sample preparation step. The presented framework can bolster research in the field, by cutting down processing time, supporting human-operated microscopy and further unlocking the paleoclimate potential of ice core records by providing the opportunity to identify an array of ice core particles. Suggestions for an improved system to be deployed within a continuous flow analysis workflow are also presented

Autoantibodies Against Proteins Previously Associated With Autoimmunity in Adult and Pediatric Patients With COVID-19 and Children With MIS-C

The antibody profile against autoantigens previously associated with autoimmune diseases and other human proteins in patients with COVID-19 or multisystem inflammatory syndrome in children (MIS-C) remains poorly defined. Here we show that 30% of adults with COVID-19 had autoantibodies against the lung antigen KCNRG, and 34% had antibodies to the SLE-associated Smith-D3 protein. Children with COVID-19 rarely had autoantibodies; one of 59 children had GAD65 autoantibodies associated with acute onset of insulin-dependent diabetes. While autoantibodies associated with SLE/Sjögren's syndrome (Ro52, Ro60, and La) and/or autoimmune gastritis (gastric ATPase) were detected in 74% (40/54) of MIS-C patients, further analysis of these patients and of children with Kawasaki disease (KD), showed that the administration of intravenous immunoglobulin (IVIG) was largely responsible for detection of these autoantibodies in both groups of patients. Monitoring in vivo decay of the autoantibodies in MIS-C children showed that the IVIG-derived Ro52, Ro60, and La autoantibodies declined to undetectable levels by 45-60 days, but gastric ATPase autoantibodies declined more slowly requiring >100 days until undetectable. Further testing of IgG and/or IgA antibodies against a subset of potential targets identified by published autoantigen array studies of MIS-C failed to detect autoantibodies against most (16/18) of these proteins in patients with MIS-C who had not received IVIG. However, Troponin C2 and KLHL12 autoantibodies were detected in 2 of 20 and 1 of 20 patients with MIS-C, respectively. Overall, these results suggest that IVIG therapy may be a confounding factor in autoantibody measurements in MIS-C and that antibodies against antigens associated with autoimmune diseases or other human proteins are uncommon in MIS-C

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19

Background: We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15–20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases. Methods: We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded. Results: No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5–528.7, P = 1.1 × 10−4) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3–8.2], P = 2.1 × 10−4). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1–2635.4], P = 3.4 × 10−3), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3–8.4], P = 7.7 × 10−8). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years; P = 1.68 × 10−5). Conclusions: Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old