Feasibility Of Such Approaches Research Articles

Effects of a 10-Week Integrated Curriculum Intervention on Physical Activity, Resting Blood Pressure, Motor Skills, and Well-Being in 6- to 7-Year-Olds.

Integrated curriculum interventions have been suggested as an effective means to increase physical activity (PA) and health. The feasibility of such approaches in children living in deprivation is unknown. This study sought to pilot an integrated curriculum pedometer intervention in children living in deprivation on school-based PA, body fatness, resting blood pressure, motor skills, and well-being. Using a pilot cluster randomized intervention design, children (6-7y old, n = 64) from 2 schools in central England undertook: (1)10-week integrated curriculum intervention or (2)control (regular school-based activity). School-based PA, body fatness, resting blood pressure, motor skills, and well-being were assessed preintervention and postintervention. For the intervention group, PA was higher on school days when children had physical education lessons or there were physically active integrated curriculum activities. Body fatness significantly decreased, and well-being and perceived physical competence increased, pre-post for the intervention group compared with the control group. Accelerometer-derived PA, motor skills, and resting blood pressure were not significantly different pre-post for intervention or control groups. A 10-week integrated curriculum PA intervention is feasible to conduct and can positively impact aspects of health in 6- to 7-year-old children in England.

Web Application to Enable Online Social Interactions in a Parkinson Disease Risk Cohort: Feasibility Study and Social Network Analysis.

There is evidence that social interaction has an inverse association with the development of neurodegenerative diseases. PREDICT-Parkinson Disease (PREDICT-PD) is an online UK cohort study that stratifies participants for risk of future Parkinson disease (PD). This study aims to explore the methodological approach and feasibility of assessing the digital social characteristics of people at risk of developing PD and their social capital within the PREDICT-PD platform, making hypotheses about the relationship between web-based social engagement and potential predictive risk indicators of PD. A web-based application was built to enable social interaction through the PREDICT-PD portal. Feedback from existing members of the cohort was sought and informed the design of the pilot. Dedicated staff used weekly engagement activities, consisting of PD-related research, facts, and queries, to stimulate discussion. Data were collected by the hosting platform. We examined the pattern of connections generated over time through the cumulative number of posts and replies and ego networks using social network analysis. We used network metrics to describe the bonding, bridging, and linking of social capital among participants on the platform. Relevant demographic data and Parkinson risk scores (expressed as an odd 1:x) were analyzed using descriptive statistics. Regression analysis was conducted to estimate the relationship between risk scores (after log transformation) and network measures. Overall, 219 participants took part in a 4-month pilot forum embedded in the study website. In it, 200 people (n=80, 40% male and n=113, 57% female) connected in a large group, where most pairs of users could reach one another either directly or indirectly through other users. A total of 59% (20/34) of discussions were spontaneously started by participants. Participation was asynchronous, with some individuals acting as "brokers" between groups of discussions. As more participants joined the forum and connected to one another through online posts, distinct groups of connected users started to emerge. This pilot showed that a forum application within the cohort web platform was feasible and acceptable and fostered digital social interaction. Matching participants' web-based social engagement with previously collected data at individual level in the PREDICT-PD study was feasible, showing potential for future analyses correlating online network characteristics with the risk of PD over time, as well as testing digital social engagement as an intervention to modify the risk of developing neurodegenerative diseases. The results from the pilot suggest that an online forum can serve as an intervention to enhance social connectedness and investigate whether patterns of online engagement can impact the risk of developing PD through long-term follow-up. This highlights the potential of leveraging online platforms to study the role of social capital in moderating PD risk and underscores the feasibility of such approaches in future research or interventions.

Affibody PET Imaging of HER2-Expressing Cancers as a Key to Guide HER2-Targeted Therapy.

Human epidermal growth factor receptor 2 (HER2) is a major prognostic and predictive marker overexpressed in 15-20% of breast cancers. The diagnostic reference standard for selecting patients for HER2-targeted therapy is based on the analysis of tumor biopsies. Previously patients were defined as HER2-positive or -negative; however, with the approval of novel treatment options, specifically the antibody-drug conjugate trastuzumab deruxtecan, many breast cancer patients with tumors expressing low levels of HER2 have become eligible for HER2-targeted therapy. Such patients will need to be reliably identified by suitable diagnostic methods. Biopsy-based diagnostics are invasive, and repeat biopsies are not always feasible. They cannot visualize the heterogeneity of HER2 expression, leading to a substantial number of misdiagnosed patients. An alternative and highly accurate diagnostic method is molecular imaging with radiotracers. In the case of HER2, various studies demonstrate the clinical utility and feasibility of such approaches. Radiotracers based on Affibody® molecules, small, engineered affinity proteins with a size of ~6.5 kDa, are clinically validated molecules with favorable characteristics for imaging. In this article, we summarize the HER2-targeted therapeutic landscape, describe our experience with imaging diagnostics for HER2, and review the currently available clinical data on HER2-Affibody-based molecular imaging as a novel diagnostic tool in breast cancer and beyond.

Hybrid deep learning models based emotion recognition with speech signals

Emotion recognition is one of the most important components of human-computer interaction, and it is something that can be performed with the use of voice signals. It is not possible to optimise the process of feature extraction as well as the classification process at the same time while utilising conventional approaches. Research is increasingly focusing on many different types of “deep learning” in an effort to discover a solution to these difficulties. In today’s modern world, the practise of applying deep learning algorithms to categorization problems is becoming increasingly important. However, the advantages available in one model is not available in another model. This limits the practical feasibility of such approaches. The main objective of this work is to explore the possibility of hybrid deep learning models for speech signal-based emotion identification. Two methods are explored in this work: CNN and CNN-LSTM. The first model is the conventional one and the second is the hybrid model. TESS database is used for the experiments and the results are analysed in terms of various accuracy measures. An average accuracy of 97% for CNN and 98% for CNN-LSTM is achieved with these models.

Assessing the utility of liquid biopsy for detecting actionable genetic mutations among indigenous Ghanaian women with metastatic breast cancer.

e13017 Background: Breast cancer is the leading cancer diagnosis in women worldwide, and the leading cause of cancer-related mortality in Ghanaian women. Up to 70% of breast cancer diagnoses in Ghanaian women are advanced-stage, leading to fewer opportunities for early intervention. Late presentation of breast cancer may be attributed to lack of comprehensive screening programs, among other factors. Next-Generation Sequencing (NGS)-based liquid biopsy of circulating free DNA (cfDNA) is non-invasive and been demonstrated to support diagnosis, monitoring and treatment selection in cancer. Unfortunately, people of African ancestry are under-represented in evaluations of this technology and little is known about the feasibility of such approaches in low-resource settings. Methods: The AMBER-01 study recruited 20 newly diagnosed, histologically confirmed, treatment-naive women with metastatic breast cancer at the Cape Coast Teaching Hospital. Testing was conducted at CAP and CLIA accredited laboratories (Lucence, Palo Alto; Singapore). Tissue NGS and cfDNA liquid biopsy analysis was ordered on a total of 20 patients following tissue quality analysis outcomes. All 20/20 (100%) liquid biopsy samples were acceptable for analysis, whereas only 6/20 (30%) passed QC for tissue NGS testing. cfDNA liquid biopsy and tissue NGS analyses were performed using Lucence LiquidHALLMARK and Tissue500 technology, respectively. Results: Liquid biopsy detected 42 cfDNA mutations in 17/20 patients. Of the 17 patients found to have mutations on liquid biopsy, 3 (17.6%) patients had mutations associated with African ancestry, including BRCA K719E, ARAF S262I and GATA3 G125dup. Eight actionable mutations specific to breast cancer were found in 7/17 (41.2%) patients while actionable mutations non-specific to breast cancer were detected in 12/17 (70.6%) patients. Tissue biopsy analysis detected mutations in all 6 patients tested, with 3/6 (50%) patients presenting actionable mutations specific to breast cancer. Of the 20 patients recruited, liquid biopsy was able to identify actionable treatments for 7 patients, while tissue was only able to identify actionable treatment for 3 patients. Of the 6 patients with matched liquid and tissue results, liquid biopsy detected additional mutations in 3 (50%) patients that were not detected by tissue analysis including: BRCA2 Q1379E, GNAQ Q176*, and a low Microsatellite Instability (MSI) reported as stable in tissue. Conclusions: Liquid biopsy detected multiple actionable variants in Ghanaian women with breast cancer that a tissue-only workflow missed. cfDNA analysis featured less variations in sample preparation which is a key consideration in resource-limited settings. Further work will optimize NGS panels to account for novel ancestry specific variants. Liquid biopsy presents a great opportunity to improve cancer care in Africa.

Immunoinformatics Approaches in Designing Vaccines Against COVID-19.

Since the onset of the COVID-19 pandemic, a number of approaches have been adopted by the scientific communities for developing efficient vaccine candidate against SARS-CoV-2. Conventional approaches of developinga vaccine require a long time and a series of trials and errors which indeed limit the feasibility of such approaches for developing a dependablevaccine in an emergency situation like theCOVID-19 pandemic. Hitherto, most of the available vaccines have been developed against a particular antigen of SARS-CoV, spike protein in most of the cases, and intriguingly, these vaccines are not effective against all the pathogenic coronaviruses. In this context, immunoinformatics-based reverse vaccinology approaches enable a robust design of efficacious peptide-based vaccines against all the infectious strains of coronaviruses within a short frame of time. In this chapter, we enumerate the methodological trajectory of developing a universal anti-SARS-CoV-2 vaccine, namely, "AbhiSCoVac," through advanced computational biology-based immunoinformatics approach and itsin-silico validation using molecular dynamics simulations.

Feasibility of employing the restarting process to evaluate the self-starting ability for hypersonic inlets

Accurate evaluation of hypersonic inlet self-starting performance is very crucial for the stable and efficient operation of scramjet engines. However, few ground hypersonic wind tunnels could provide a continuously and slowly accelerating free stream conditions to directly validate the self-starting ability of hypersonic inlets so far. Some experimental restarting approaches have been explored to evaluate the self-starting performance of hypersonic inlets. To clarify the feasibility of such approaches, the self-starting process and the restarting process caused by withdrawing plug at the exit of a two-dimensional hypersonic inlet were studied using unsteady numerical simulation in this paper. The results show that, even though the freestream Mach number (5.54) of the restarting process is lower than the self-starting Mach number (5.715), the hypersonic inlet can finally rebuild the started flow field owing to the significantly higher moving speed downstream across the inlet internal contraction section caused by the big buzz. Hence, the additional unsteady effect should be suppressed as far as possible during the initial pre-blockage process in the restarting experiment applied to evaluate the self-starting performance of hypersonic inlets.

Recent Advances in Probabilistic Dose-Response Assessment to Inform Risk-Based Decision Making.

Paradoxically, risk assessments for the majority of chemicals lack any quantitative characterization as to the likelihood, incidence, or severity of the risks involved. The relatively few cases where "risk" is truly quantified are based on either epidemiologic data or extrapolation of experimental animal cancer bioassay data. The paucity of chemicals and health endpoints for which such data are available severely limits the ability of decisionmakers to account for the impacts of chemical exposures on human health. The development by the World Health Organization International Programme on Chemical Safety (WHO/IPCS) in 2014 of a comprehensive framework for probabilistic dose-response assessment has opened the door to a myriad of potential advances to better support decision making. Building on the pioneering work of Evans, Hattis, and Slob from the 1990s, the WHO/IPCS framework provides both a firm conceptual foundation as well as practical implementation tools to simultaneously assess uncertainty, variability, and severity of effect as a function of exposure. Moreover, such approaches do not depend on the availability of epidemiologic data, nor are they limited to cancer endpoints. Recent work has demonstrated the broad feasibility of such approaches in order to estimate the functional relationship between exposure level and the incidence or severity of health effects. While challenges remain, such as better characterization of the relationship between endpoints observed in experimental animal or in vitro studies and human health effects, the WHO/IPCS framework provides a strong basis for expanding the breadth of risk management decision contexts supported by chemical risk assessment.

Optical characterizations of nanoporous anodic alumina for thickness measurements using interference oscillations

Highly-ordered nanoporous anodic alumina (NAA) with varying thicknesses were prepared by changing the anodization time from 10 min to 10 h, using a two-step electrochemical oxidation in oxalic acid. Three optical characterizations, namely, Ultraviolet–Visible–Near Infrared (UV–VIS–NIR), Photoluminescence (PL), and Reflective interference spectra were used to measure NAA’s thicknesses. All three types of spectra displayed oscillations due to the optical interferences which were used for the extraction of NAA thickness using two approaches (i) Fabry–Perot fringe equation and (ii) Bragg’s interference condition equation. Both these approaches yielded the matching thicknesses. The results are coincident for all three measurement techniques. The obtained thicknesses are in good agreement with the cross-sectional SEM images showcasing the feasibility of such approaches. Measurements were carried out on NAA up to ∼10μm thickness beyond which no oscillations were observed. Out of the three, reflective interference spectroscopy turns out to be an inexpensive alternative for the NAA thickness measurement. Such nondestructive optical characterization methods are important from the device development point of view for chemical, optical and biosensing applications.

Toward Small-Molecule Inhibition of Protein-Protein Interactions: General Aspects and Recent Progress in Targeting Costimulatory and Coinhibitory (Immune Checkpoint) Interactions.

Protein-Protein Interactions (PPIs) that are part of the costimulatory and coinhibitory (immune checkpoint) signaling are critical for adequate T cell response and are important therapeutic targets for immunomodulation. Biologics targeting them have already achieved considerable clinical success in the treatment of autoimmune diseases or transplant recipients (e.g., abatacept, belatacept, and belimumab) as well as cancer (e.g., ipilimumab, nivolumab, pembrolizumab, atezolizumab, durvalumab, and avelumab). In view of such progress, there have been only relatively limited efforts toward developing small-molecule PPI inhibitors (SMPPIIs) targeting these cosignaling interactions, possibly because they, as all other PPIs, are difficult to target by small molecules and were not considered druggable. Nevertheless, substantial progress has been achieved during the last decade. SMPPIIs proving the feasibility of such approaches have been identified through various strategies for a number of cosignaling interactions including CD40-CD40L, OX40-OX40L, BAFFR-BAFF, CD80-CD28, and PD-1-PD-L1s. Here, after an overview of the general aspects and challenges of SMPPII-focused drug discovery, we review them briefly together with relevant structural, immune-signaling, physicochemical, and medicinal chemistry aspects. While so far only a few of these SMPPIIs have shown activity in animal models (DRI-C21045 for CD40-D40L, KR33426 for BAFFR-BAFF) or reached clinical development (RhuDex for CD80-CD28, CA-170 for PD-1-PD-L1), there is proof-of-principle evidence for the feasibility of such approaches in immunomodulation. They can result in products that are easier to develop/ manufacture and are less likely to be immunogenic or encounter postmarket safety events than corresponding biologics, and, contrary to them, can even become orally bioavailable.

Psychotherapeutic Applications of Mobile Phone-based Technologies: A Systematic Review of Current Research and Trends.

There is a growing interest in using mobile phone technology to offer real-time psychological interventions and support. However, questions remain on the clinical effectiveness and feasibility of such approaches in psychiatric populations. Our aim was to systematically review the published literature on mobile phone apps and other mobile phone-based technology for psychotherapy in mental health disorders. To achieve this, electronic searches of PubMed, ScienceDirect, and Google Scholar were carried out in January 2016. Generated abstracts were systematically screened for eligibility to be included in the review. Studies employing psychotherapy in any form, being delivered through mobile-based technology and reporting core mental health outcomes in mental illness were included in the study. We also included trials in progress with published protocols reporting at least some outcome measures of such interventions. From a total of 1563 search results, 24 eligible articles were identified and reviewed. These included trials in anxiety disorders (8), substance use disorders (5), depression (4), bipolar disorders (3), schizophrenia and psychotic disorders (3), and attempted suicide (1). Of these, eight studies involved the use of smartphone apps and others involved personalized text messages, automated programs, or delivered empirically supported treatments. Trial lengths varied from 6 weeks to 1 year. Good overall retention rates indicated that the treatments were feasible and largely acceptable. Benefits were reported on core outcomes in mental health illness indicating efficacy of such approaches though sample sizes were small. To conclude, mobile phone-based psychotherapies are a feasible and acceptable treatment option for patients with mental disorders. However, there remains a paucity of data on their effectiveness in real-world settings, especially from low- and middle-income countries.

Beyond Empathy: Strategies and Ideals of Democratic Deliberation

This paper problematizes empathy-centered approaches to deliberation, challenging the feasibility of such approaches as well as the suitability of empathy as a central goal or ideal in models of democratic deliberation. With the deliberative turn in democratic theory came a new emphasis on empathy. Empathy on the part of citizens – the ability to engage in perspective taking and to feel empathic concern for others – is often cited as crucial for the success and improvement of democratic discourse. I first identify several limits to achieving empathy in practice. I then show that even when achieved, empathy does not sustain deliberative practices. In place of empathy, I propose a “difference approach” to improving democratic deliberation. I argue that differences rather than commonalities are a more democratic resource for helping citizens cultivate greater openness and better listening practices. The difference approach better reflects the ideals of the deliberative model of democracy.

Digital life storybooks for people with dementia living in care homes: an evaluation.

Background and aimThere is increasing interest in using information and communication technology to help older adults with dementia to engage in reminiscence work. Now, the feasibility of such approaches is beginning to be established. The purpose of this study was to establish an evidence-base for the acceptability and efficacy of using multimedia digital life storybooks with people with dementia in care homes, in comparison with conventional life storybooks, taking into account the perspectives of people with dementia, their relatives, and care staff.MethodsParticipatory design was used to create a life story movie based on a previously completed conventional life storybook with six older adults with dementia (four females; mean age 82 years). Relatives were involved in helping the participant to provide additional information and materials for the digital life storybook. In this multiple case study design, both quantitative and qualitative approaches were used. For quantitative purposes, a set of questionnaires that had been completed three times before and after the conventional life storybook was developed were repeated 4 weeks after the life story movie was completed. Semistructured interview questions were designed to collect feedback from participants, relatives, and care staff.ResultsThe result indicated that five of the six participants showed additional improvement in measures of quality of life and autobiographical memory. All participants showed improvement or stability in depression scores. Thematic analysis showed that, participants, relatives, and care home staff viewed digital life storybooks as a very useful tool triggering memories and (largely) positive emotions. Participants’ case vignettes were presented to document the impact of digital life storybook.

Toward 4D mechanical correlation

The goal of the present study is to illustrate the full integration of sensor and imaging data into numerical procedures for the purpose of identification of constitutive laws and their validation. The feasibility of such approaches is proven in the context of in situ tests monitored by tomography. The bridging tool consists of spatiotemporal (i.e., 4D) analyses with dedicated (integrated) correlation algorithms. A tensile test on nodular graphite cast iron sample is performed within a lab tomograph. The reconstructed volumes are registered via integrated digital volume correlation (DVC) that incorporates a finite element modeling of the test, thereby performing a mechanical integration in 4D registration of a series of 3D images. In the present case a non-intrusive procedure is developed in which the 4D sensitivity fields are obtained with a commercial finite element code, allowing for a large versatility in meshing and incorporation of complex constitutive laws. Convergence studies can thus be performed in which the quality of the discretization is controlled both for the simulation and the registration. Incremental DVC analyses are carried out with the scans acquired during the in situ mechanical test. For DVC, the mesh size results from a compromise between measurement uncertainties and its spatial resolution. Conversely, a numerically good mesh may reveal too fine for the considered material microstructure. With the integrated framework proposed herein, 4D registrations can be performed and missing boundary conditions of the reference state as well as mechanical parameters of an elastoplastic constitutive law are determined in fair condition both for DVC and simulation.

Utilizing small nutrient compounds as enhancers of exercise-induced mitochondrial biogenesis.

Endurance exercise, when performed regularly as part of a training program, leads to increases in whole-body and skeletal muscle-specific oxidative capacity. At the cellular level, this adaptive response is manifested by an increased number of oxidative fibers (Type I and IIA myosin heavy chain), an increase in capillarity and an increase in mitochondrial biogenesis. The increase in mitochondrial biogenesis (increased volume and functional capacity) is fundamentally important as it leads to greater rates of oxidative phosphorylation and an improved capacity to utilize fatty acids during sub-maximal exercise. Given the importance of mitochondrial biogenesis for skeletal muscle performance, considerable attention has been given to understanding the molecular cues stimulated by endurance exercise that culminate in this adaptive response. In turn, this research has led to the identification of pharmaceutical compounds and small nutritional bioactive ingredients that appear able to amplify exercise-responsive signaling pathways in skeletal muscle. The aim of this review is to discuss these purported exercise mimetics and bioactive ingredients in the context of mitochondrial biogenesis in skeletal muscle. We will examine proposed modes of action, discuss evidence of application in skeletal muscle in vivo and finally comment on the feasibility of such approaches to support endurance-training applications in humans.

TNF superfamily protein-protein interactions: feasibility of small- molecule modulation.

The tumor necrosis factor (TNF) superfamily (TNFSF) contains about thirty structurally related receptors (TNFSFRs) and about twenty protein ligands that bind to one or more of these receptors. Almost all of these cell surface protein-protein interactions (PPIs) represent high-value therapeutic targets for inflammatory or immune modulation in autoimmune diseases, transplant recipients, or cancers, and there are several biologics including antibodies and fusion proteins targeting them that are in various phases of clinical development. Small-molecule inhibitors or activators could represent possible alternatives if the difficulties related to the targeting of protein-protein interactions by small molecules can be addressed. Compounds proving the feasibility of such approaches have been identified through different drug discovery approaches for a number of these TNFSFR-TNFSF type PPIs including CD40-CD40L, BAFFR-BAFF, TRAIL-DR5, and OX40-OX40L. Corresponding structural, signaling, and medicinal chemistry aspects are briefly reviewed here. While none of these small-molecule modulators identified so far seems promising enough to be pursued for clinical development, they provide proof-of-principle evidence that these interactions are susceptible to small-molecule modulation and can serve as starting points toward the identification of more potent and selective candidates.

Getting serious about mining the technosphere: a review of recent landfill mining and urban mining research

This study reviews the articles in a special volume of Journal of Cleaner Production on urban mining and landfill mining, identifying what is seen as relevant for exploring the feasibility of such approaches and which societal changes and research areas are essential for their further dissemination. In doing so, we put the articles in relation to previous research and a modified resilience model displaying dimensions of relevance for socio-ecological transitions, i.e., Metabolic flows, Governance & knowledge, Business dynamics and Infrastructure & markets. The main contributions of the articles in the special volume are in regards to metabolic issues (e.g. characterization of technospheric material stocks and societal impacts of landfill mining) and business dimensions (e.g. economics, organizational issues and management tools). Two articles also provide original contributions by conceptualizing these emerging approaches and defining what makes them different from existing recycling strategies and practices. We conclude that urban mining and landfill mining show high potential but that state-of-the-art is theoretical, implying a need for applied approaches to develop applicable methods and technology and to assess performance of such activities in practice. However, realization of these approaches faces interdisciplinary and long-term challenges, which apart from technology and facts also needs to address non-technical conditions in terms of governance, market dynamics and organizational structures and cultures.

Assessment of two complementary liquid chromatography coupled to high resolution mass spectrometry metabolomics strategies for the screening of anabolic steroid treatment in calves

Anabolic steroids are banned in food producing livestock in Europe. Efficient methods based on mass spectrometry detection have been developed to ensure the control of such veterinary drug residues. Nevertheless, the use of “cocktails” composed of mixtures of low amounts of several substances as well as the synthesis of new compounds of unknown structure prevent efficient prevention. New analytical tools able to detect such abuse are today mandatory. In this context, metabolomics may represent new emerging strategies for investigating the global physiological effects associated to a family of substances and therefore, to suspect the administration of steroids. The purpose of the present study was to set up, assess and compare two complementary mass spectrometry-based metabolomic strategies as new tools to screen for steroid abuse in cattle and demonstrate the feasibility of such approaches. The protocols were developed in two European laboratories in charge of residues analysis in the field of food safety. Apart from sample preparation, the global process was different in both laboratories from LC-HRMS fingerprinting to multivariate data analysis through data processing and involved both LC-Orbitrap-XCMS and UPLC-ToF-MS-MetAlign strategies. The reproducibility of both sample preparation and MS measurements were assessed in order to guarantee that any differences in the acquired fingerprints were not caused by analytical variability but reflect metabolome modifications upon steroids administration. The protocols were then applied to urine samples collected on a large group of animals consisting of 12 control calves and 12 calves administrated with a mixture of 17β-estradiol 3-benzoate and 17β-nandrolone laureate esters according to a protocol reflecting likely illegal practices. The modifications in urine profiles as indicators of steroid administration have been evaluated in this context and proved the suitability of the approach for discriminating anabolic treated animals from control ones. Such an approach may therefore open a new way for the screening of anabolic steroid administration through targeted monitoring of relevant biomarkers highlighted as a result of the metabolomics study.

Trials and tribulations of immunotherapy as a treatment option for patients with squamous cell carcinoma of the head and neck.

Head and neck squamous cell carcinoma (HNSCC) is an aggressive epithelial malignancy that is the sixth most common neoplasm in the world. Despite numerous advances in treatments involving surgery, radiation, and chemotherapy, the 5-year survival has remained at less than 50% for the last 30 years primarily due to local recurrences [66]. Consequently, the possibility of developing immunotherapeutic approaches as a treatment for HNSCC has gained interest. The present review has 3 objectives pertaining to immunotherapeutic means to treat HNSCC patients: (1) to summarize the feasibility of such approaches, (2) to provide an overview of the obstacles to attaining protective immune reactivity, and (3) to consider how these obstacles can be overcome to stimulate immune reactivity to HNSCC. These objectives will also be considered in the context of what lessons have been learned from immunotherapeutic trials for other solid malignancies and the applicability of this information to HNSCC.

Comparative bioinformatic analysis of complete proteomes and protein parameters for cross-species identification in proteomics.

Peptide mass fingerprinting (PMF) remains the most amenable technique for protein identification in proteomics, using mass spectrometry as the primary analytical technique coupled with bioinformatics. This relies on the presence of the amino acid sequence of the protein in the current databanks. Despite this, it is desirable to be able to use the technique for organisms whose genomes are not yet fully sequenced and apply cross-species protein identification. In this study, we have re-examined the feasibility of such approaches by considering the extent of protein similarity between genome sequences using a data set of 29 complete bacterial and two eukaryotic genomes. A range of protein and peptide features are considered, including protein isoelectric focussing point, protein mass, and amino acid conservation. The effectiveness of PMF approaches has then been tested with a series of computer simulations with varying peptide number and mass accuracy for several cross-species tests. The results show that PMF alone is unsuitable in general for divergent species jumps, or when protein similarity is less than 70% identity. Despite this, there exists a considerable enrichment above random of tryptic peptide conservation and PMF promises to remain useful when combined with other data than just peptide masses for cross-species protein identification.