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Epithelial head and neck cancer survival in Europe: Geographical variation, time trends and long term survival
No full textBackground: Head and neck cancers (HNC) are a heterogeneous group of rare cancers with known risk factors also associated with other tumours and pathologies. Treatment protocols are fast evolving. This paper, within the EUROCARE-6 project, aims to update geographical survival differences, survival progression over time and, for the first time, incorporates other causes of mortality in estimating long-term survival. Methods: We analysed 587,358 primary HNC cases, subdivided into several epithelial cancer entities (squamous cell carcinoma of oral cavity, oropharynx, nasopharynx, nasal cavities, hypopharynx, larynx, epithelial major salivary glands and salivary gland type tumour of the head and neck) from 99 population-based cancer registries. Cases were diagnosed between 1998 and 2013 and followed-up to 2014. Relative survival (RS) was estimated by sex, age, country and period of diagnosis up to 15 years following diagnosis. We also estimated the risk of dying from causes other than HNC, using cause-of-death data from of a selection of cancer registries. Results: Overall, 15-year RS survival for HNC was 30 % for men and 40 % for women. Five-year RS significantly improved over the period (2002–2013), the major increases for oropharyngeal epithelial tumours and for salivary type glands tumour of head and neck. Across European countries discrepancies remained, with poorer survival outcomes in Baltic and Eastern European countries. HNC patients were 2.1 times more likely to die from other causes compared to the general population. Conclusions: HNC are rare tumours which require complex treatment and centralization of care. The European Reference Network must work to reduce geographical discrepancies. The higher risk of death from non-HNC causes may be due to poorer overall health and greater levels of comorbidity associated with tobacco and alcohol use.</p
Multiwavelength Observations of a Jet Launch in Real Time from the Post-changing-look Active Galaxy 1ES 1927+654
No full textWe present results from a high-cadence multiwavelength observational campaign of the enigmatic changing-look active galactic nucleus 1ES 1927+654 from 2022 May to 2024 April, coincident with an unprecedented radio flare (an increase in flux by a factor of ∼60 over a few months) and the emergence of a spatially resolved jet at 0.1–0.3 pc scales. Companion work has also detected a recurrent quasi-periodic oscillation (QPO) in the 2–10 keV band with an increasing frequency (1–2 mHz) over the same period. During this time, the soft X-rays (0.3–2 keV) monotonically increased by a factor of ∼8, while the UV emission remained nearly steady wit
Non-invasive giant panda pregnancy and pseudopregnancy biomonitoring by integrated metabolomics and steroidomics
No full textUnderstanding the reproductive biology of giant pandas is crucial for their breeding success and conservation. Pregnancy monitoring, however, is challenging due to delayed implantation and obligatory pseudopregnancy, which limits the effectiveness of traditional immunoassays (IA). To remedy this, we combined polar metabolomics and steroidomics to enable a comprehensive view of the urinary molecular composition across six different reproductive phases spanning six pregnant and seven pseudopregnant cycles. Statistical comparisons revealed 696 discriminative features, including 174 features in the early luteal stages, well before the current pregnancy diagnostic window. Pregnant and pseudopregnant cycles showed differences in amino acid, energy, and steroid metabolism before and after CL reactivation, with androgen levels being significantly elevated in pregnant females specifically, suggesting a role in embryo implantation. Interestingly, we detected only one existing IA target metabolite, but identified other discriminative metabolites that may underlie IA signal detection. Finally, we demonstrated that classification models comprising biomarker panels may improve (early) pregnancy diagnosis with accuracies ranging from 0.763 to 1.000 across reproductive phases. These findings offer possibilities for assigning new biomarkers and optimizing IA target selection, thereby enhancing pregnancy monitoring sensitivity and reliability while improving our understanding of giant panda reproductive biology to support conservation efforts
Multi-region investigation of 'man' as default in attitudes
No full textPrevious research has studied the extent to which men are the default members of social groups in terms of memory, categorization, and stereotyping, but not attitudes which is critical because of attitudes’ relationship to behavior. Results from our survey (N > 5000) collected via a globally distributed laboratory network in over 40 regions demonstrated that attitudes toward Black people and politicians had a stronger relationship with attitudes toward the men rather than the women of the group. However, attitudes toward White people had a stronger relationship with attitudes toward White women than White men, whereas attitudes toward East Asian people, police officers, and criminals did not have a stronger relationship with attitudes toward either the men or women of each respective group. Regional agreement with traditional gender roles was explored as a potential moderator. These findings have implications for understanding the unique forms of prejudice women face around the world.<br/
Breaking the interference curse in multi-target CF-mMIMO ISAC systems
No full textWe consider a cell-free massive multiple-input and multiple-output (CF-mMIMO) integrated sensing and communication (ISAC) system with multiple communication users and sensing targets. In this system, the transmit access points (TX-APs) send signals to communication users and sensing targets. Subsequently, the receive APs (RX-APs) are utilized to receive the reflected signals from both the sensing targets and communication users. To mitigate interference among users and targets, while maintaining satisfactory communication performance, we apply the active channel sparsification (ACS) concept to represent the ISAC system. A max-min sensing signal-to-interference-plus-noise ratio (SINR) problem, that satisfies the minimum communication SINR and the total power constraint, is proposed. To solve this NP-hard optimization problem, a two-step algorithm is proposed, including a joint beam and user selection scheme and a power control scheme. Finally, our numerical results show that the proposed algorithm achieves at least 136% higher sensing SINR compared to the considered benchmarks
Joint OMA-NOMA cell-free massive MIMO with limited fronthaul
No full textWe consider a joint orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) cell-free massive multiple-input multiple-output (CFmMIMO) system with limited fronthaul capacity. In this system, some users (UEs) are grouped to be served by access points (APs) in NOMA mode, while other UEs are served in OMA mode. We formulate a mixed-integer nonconvex problem of optimizing the power control and AP-group association to maximize the sum spectral efficiency (SE) in the considered system. This problem is subject to minimum SE requirements of each UE, per-AP transmit power, and limited fronthaul capacity. We propose an algorithm based on the successive convex approximation (SCA) optimization technique to obtain a stationary-point solution for the formulated problem. Numerical results demonstrate that the proposed joint optimization approach increases significantly sum SE compared to other heuristic baseline schemes, especially under a tight fronthaul capacity limitation. Also, the joint OMA-NOMA CFmMIMO system provides remarkably higher 95%-likelihood sum SE compared to a CFmMIMO system using only the OMA scheme, especially up to 42% when the coherence interval is short.<br/
Enhancing the real-time solutions of parametric linear systems on a GPU through hybrid coarse-grained transprecision computing
No full textProcessing of parametric linear systems of the form G(P) := X⊤PX is computationally intensive as they use double precision, and matrix X can be large. Many applications can tolerate numerical errors and GPUs support a range of low-precision formats, so a hybrid coarse-grained transprecision computing approach is proposed to improve the performance under a predefined error threshold. In the offline phase, suitable low-precision formats for X and P matrices are identified. In the online phase, incoming Ps are analyzed dynamically and an appropriate low-precision format is selected for computing G(P). A 21.6M × 500 X matrix is processed 14x faster compared to its double precision version, enabling real-time evaluation of one P matrix every 2 seconds on an NVIDIA A100 GPU with an average relative error of less than 0.3%.</p
Mitigating health inequalities in rural European communities through collaborative primary care research: A position paper of the WONCA Europe network EURIPA
No full textRural populations in Europe face health inequalities due to a multitude of factors, including the higher prevalence of multi-morbidity, inadequate access to primary and secondary health care services, and widespread health workforce shortages. Although some challenges are also present in other contexts, the multitude and interconnectedness of these factors induce significant health inequalities. Research is a prime tool to demonstrate these, examine potential rural-specific solutions and serve as an essential advocacy instrument for change. Rural primary care remains however significantly underrepresented in European research, contributing further to the health inequities as policies and interventions are often based on urban-centric data. Therefore, advancing evidence-based solutions for rural primary healthcare requires stronger research collaboration. In response, the Rural Health European Academic Network (RHEAN) was established in 2024 to expand academic partnerships beyond the WONCA Europe network EURIPA, the European Rural and Isolated Practitioners Association. This paper identifies rural-specific primary care challenges emerging from key literature and network discussions that shape RHEAN’s collaborative research agenda. The agenda will be refined through a mapping survey of rural primary healthcare research and education within the networks
