Energy-Efficient Cooperative Protocols for Full-Duplex Relay Channels

In this work, energy-efficient cooperative protocols are studied for full-duplex relaying (FDR) with loopback interference. In these protocols, relay assistance is only sought under certain conditions on the different link outages to ensure effective cooperation. Recently, an energy-efficient selective decode-and-forward protocol was proposed for FDR, and was shown to outperform existing schemes in terms of outage. Here, we propose an incremental selective decode-and-forward protocol that offers additional power savings, while keeping the same outage performance. We compare the performance of the two protocols in terms of the end-to-end signal-to-noise ratio cumulative distribution function via closed-form expressions. Finally, we corroborate our theoretical results with simulation, and show the relative relay power savings in comparison to non-selective cooperation in which the relay cooperates regardless of channel conditions

Normative reference and cut-offs values of maximal aerobic speed-20 m shuttle run test and maximal oxygen uptake for Tunisian adolescent (elite) soccer players

This study aimed to develop reference curves of aerobic parameters of 20 m shuttle run test for Tunisian soccer players. The study was conducted in the 2022/2023 pre-season. The reference curves of the maximal aerobic speed (MAS) and the maximal oxygen uptake (VO2max) were developed according to the Lambda, Mu and Sigma (LMS) method, using data from 742 Tunisian premier league soccer players aged 11–18 years. Measured variables included: weight, height, body mass index and maximal heart rate (HRmax). HRmax was measured when the participants completed the maximal aerobic speed. VO2max was estimated using the 20 m shuttle run test protocol (speed increment every minute). Our results presented the smoothed percentiles (3rd, 10th, 25th, 50th, 75th, 90th and 97th) of MAS (km/h) and VO2max (ml/kg•min⁻1) according to age. In addition, raw data showed that VO2 max was positively correlated with age (r = 0.333; P < 0.001), height (cm) (r = 0.279; P < 0.001), weight (kg) (r = 0.266; P < 0.001), practice period (years) (r = 0.324; P < 0.001) and BMI (kg/m2) (r = 0.10; P < 0.05). However, it was negatively correlated to HRmax (bpm) (r = 0.247; P < 0.001). Only the measurements within the age group [12–12.99] are significantly higher (p < 0.001; ES = 0.63) compared with the previous age group [11–11.99]. Finally, regarding prevalence, our findings showed that 15.5 % of the players in our sample had VO2max values above the 87.7th percentile cut-off, while only 0.3 % exceeded the 99.18th percentile. The development of normative curves could help coaches and physical trainers to more accurately detect weaknesses in the aerobic performance of their players in order to sustain high-intensity repetitive actions during a soccer match.info:eu-repo/semantics/publishedVersio

Moving Beyond the Stigma: Understanding and Overcoming the Resistance to the Acceptance and Adoption of Artificial Intelligence Chatbots

Artificial intelligence chatbots may fundamentally transform academic research, automate mundane tasks, and enhance productivity. However, the integration of artificial intelligence chatbots (AIc) is impeded by a complex stigma deeply rooted in individuals’ misconceptions and apprehension, including concerns about academic integrity, job displacement, data privacy, and algorithmic bias. The aim of this study was to scrutinize the origins and impacts of the stigma associated with artificial intelligence chatbots within the realm of academic research and to propose strategies to mitigate such stigmas. This study draws parallels between the reception of artificial intelligence chatbots and previous transformative technologies, presenting case studies illustrating the spectrum of responses to the integration of artificial intelligence chatbots into academic research. This study identifies the need for a shift in mindset from perceiving artificial intelligence chatbots as threats to recognizing them as facilitators of efficiency and innovation. It also underscores the importance of understanding these models as tools that aid researchers but do not replace the need for human expertise and judgment. We further highlighted the role of education, transparency, regulation, and ethical guidelines in overcoming the stigma associated with artificial intelligence chatbots. Given how adaptable people are, the surrounding stigma will likely fade with time. We support a cooperative strategy with continuing education and discussion to maximize the benefits of artificial intelligence chatbots while minimizing their drawbacks, hopefully paving the way for their ethical and successful application in scholarly research

Using artificial intelligence for exercise prescription in personalised health promotion: A critical evaluation of OpenAI’s GPT-4 model

The rise of artificial intelligence (AI) applications in healthcare provides new possibilities for personalized health management. AI-based fitness applications are becoming more common, facilitating the opportunity for individualised exercise prescription. However, the use of AI carries the risk of inadequate expert supervision, and the efficacy and validity of such applications have not been thoroughly investigated, particularly in the context of diverse health conditions. The aim of the study was to critically assess the efficacy of exercise prescriptions generated by OpenAI’s Generative Pre-Trained Transformer 4 (GPT-4) model for five example patient profiles with diverse health conditions and fitness goals. Our focus was to assess the model’s ability to generate exercise prescriptions based on a singular, initial interaction, akin to a typical user experience. The evaluation was conducted by leading experts in the field of exercise prescription. Five distinct scenarios were formulated, each representing a hypothetical individual with a specific health condition and fitness objective. Upon receiving details of each individual, the GPT-4 model was tasked with generating a 30-day exercise program. These AI-derived exercise programs were subsequently subjected to a thorough evaluation by experts in exercise prescription. The evaluation encompassed adherence to established principles of frequency, intensity, time, and exercise type; integration of perceived exertion levels; consideration for medication intake and the respective medical condition; and the extent of program individualization tailored to each hypothetical profile. The AI model could create general safety-conscious exercise programs for various scenarios. However, the AI-generated exercise prescriptions lacked precision in addressing individual health conditions and goals, often prioritizing excessive safety over the effectiveness of training. The AI-based approach aimed to ensure patient improvement through gradual increases in training load and intensity, but the model’s potential to fine-tune its recommendations through ongoing interaction was not fully satisfying. AI technologies, in their current state, can serve as supplemental tools in exercise prescription, particularly in enhancing accessibility for individuals unable to access, often costly, professional advice. However, AI technologies are not yet recommended as a substitute for personalized, progressive, and health condition specific prescriptions provided by healthcare and fitness professionals. Further research is needed to explore more interactive use of AI models and integration of real-time physiological feedback

The T cell differentiation landscape is shaped by tumour mutations in lung cancer

Tumour mutational burden (TMB) predicts immunotherapy outcome in non-small cell lung cancer (NSCLC), consistent with immune recognition of tumour neoantigens. However, persistent antigen exposure is detrimental for T cell function. How TMB affects CD4 and CD8 T cell differentiation in untreated tumours and whether this affects patient outcomes is unknown. Here, we paired high-dimensional flow cytometry, exome, single-cell and bulk RNA sequencing from patients with resected, untreated NSCLC to examine these relationships. TMB was associated with compartment-wide T cell differentiation skewing, characterized by loss of TCF7-expressing progenitor-like CD4 T cells, and an increased abundance of dysfunctional CD8 and CD4 T cell subsets with strong phenotypic and transcriptional similarity to neoantigen-reactive CD8 T cells. A gene signature of redistribution from progenitor-like to dysfunctional states was associated with poor survival in lung and other cancer cohorts. Single-cell characterization of these populations informs potential strategies for therapeutic manipulation in NSCLC

Allele-Specific HLA Loss and Immune Escape in Lung Cancer Evolution

Immune evasion is a hallmark of cancer. Losing the ability to present neoantigens through human leukocyte antigen (HLA) loss may facilitate immune evasion. However, the polymorphic nature of the locus has precluded accurate HLA copy-number analysis. Here, we present loss of heterozygosity in human leukocyte antigen (LOHHLA), a computational tool to determine HLA allele-specific copy number from sequencing data. Using LOHHLA, we find that HLA LOH occurs in 40% of non-small-cell lung cancers (NSCLCs) and is associated with a high subclonal neoantigen burden, APOBEC-mediated mutagenesis, upregulation of cytolytic activity, and PD-L1 positivity. The focal nature of HLA LOH alterations, their subclonal frequencies, enrichment in metastatic sites, and occurrence as parallel events suggests that HLA LOH is an immune escape mechanism that is subject to strong microenvironmental selection pressures later in tumor evolution. Characterizing HLA LOH with LOHHLA refines neoantigen prediction and may have implications for our understanding of resistance mechanisms and immunotherapeutic approaches targeting neoantigens. Video Abstract [Figure presented] Development of the bioinformatics tool LOHHLA allows precise measurement of allele-specific HLA copy number, improves the accuracy in neoantigen prediction, and uncovers insights into how immune escape contributes to tumor evolution in non-small-cell lung cancer

Fc-Optimized Anti-CD25 Depletes Tumor-Infiltrating Regulatory T Cells and Synergizes with PD-1 Blockade to Eradicate Established Tumors

CD25 is expressed at high levels on regulatory T (Treg) cells and was initially proposed as a target for cancer immunotherapy. However, anti-CD25 antibodies have displayed limited activity against established tumors. We demonstrated that CD25 expression is largely restricted to tumor-infiltrating Treg cells in mice and humans. While existing anti-CD25 antibodies were observed to deplete Treg cells in the periphery, upregulation of the inhibitory Fc gamma receptor (FcγR) IIb at the tumor site prevented intra-tumoral Treg cell depletion, which may underlie the lack of anti-tumor activity previously observed in pre-clinical models. Use of an anti-CD25 antibody with enhanced binding to activating FcγRs led to effective depletion of tumor-infiltrating Treg cells, increased effector to Treg cell ratios, and improved control of established tumors. Combination with anti-programmed cell death protein-1 antibodies promoted complete tumor rejection, demonstrating the relevance of CD25 as a therapeutic target and promising substrate for future combination approaches in immune-oncology

Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.

The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies

Infections urinaires à Escherichia coli : prévalence et évolution de la résistance aux antibiotiques de 2004 à 2008 A l'hopital militaire d''instruction Mohammed V

Les infections urinaires sont un motif fréquent de consultation et de prescription d’antibiotiques et constitue un vrai problème de santé publique. Escherichia coli est par ordre de fréquence la bactérie la plus souvent isolée. Nous avons procédé à une étude rétrospective durant une période de cinq ans allant du 01 janvier 2004 au 31decembre 2008 et ont été inclus des prélèvements urinaires de malades hospitalisés dans plusieurs services de l'hôpital militaire d'instruction Mohammed V de Rabat, ainsi que des malades externes. Seuls les prélèvements positifs à Escherichia coli ont été retenus. Sur cette période de cinq ans 4421 ECBU répondaient aux critères d’IU, 2235 étaient positifs à Escherichia coli ce qui représente une prévalence de 50%. 40% de ces infections concernaient des patients hospitalisés et 60% ceux suivis à titre externe, La majorité des sujets étaient de sexe féminin avec un sex-ratio F/H de 1,63. L’âge des patients est essentiellement entre 30 et 70 ans. Cette étude a mis en évidence une évolution des souches cliniques vers la résistance vis-à-vis de presque la totalité des antibiotiques. En effet, le taux de résistance acquise le plus élevé chez E. coli a été observé avec l’Amoxicilline qui est passé de 55% en 2004 à 74% en 2008, de 41,6% à 65% pour l’ Amoxicilline+acide clavulanique, de 21,6% à 36,6% pour la Norfloxacine, de 37,6% à 34,4% pour le sulfaméthoxazole– triméthoprime, certaines études la situent entre 20 et 40%. Certaines molécules comme la Fosfomycine, l’Imipénème, les aminosides et Les Nitrofuranes gardent une excellente activité sur E. coli. Ces résultats ne permettent plus d’utiliser l’amoxicilline , l’amoxicilline -acide clavulanique ou le sulfaméthoxazole– triméthoprime en antibiothérapie probabiliste, et nous incite à : réduire la prescription non documentée des fluoroquinolones,d’adopter d’autres alternatives thérapeutiques, et de mettre en place un système de surveillance continue de l’antibiorésistance

Communiquer sur l’authenticité d’un patrimoine architectural : le cas du grand ksar de Temacine dans le Sud-Est algérien

At a time when tourism and/or culture are strongly affected by online information growth, enhancement of architectural sites—in addition classified protected sectors—arises more than ever. How to develop an architectural heritage as “tourism product” while respecting its preservation and authenticity? Through public and territorial communication, we will focus on enhancing the Temacine ksar, located near the Oued Righ in the Algerian Sahara. First, we will analyze the different communication actions of institutions and associations for the preservation and promotion of that heritage site. Then, two aspects of the communication objectives of the heritage of authenticity will be discussed: the creation of meaning and economic value. Finally, we will advocate a communication strategy combining patrimonial and tourist development of cultural heritage