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Whole-genome sequencing (WGS) for every UK newborn is hailed as a leap towards lifelong personalised medicine, yet policymakers have scarcely examined the informatics iceberg beneath the initiative: where, and at what cost, will millions of genomes be stored? This perspective contends that the research-era reflex of keeping raw reads and alignments in high-performance 'hot' cloud storage is incompatible with NHS budgets and net-zero targets. Drawing on the National Genomic Research Library's current practice (~80 GB per child), I estimate the UK government's 10-year rollout would accumulate more than 0.5 exabytes and incur ~£620 million in standard S3 fees-exceeding NICE's entire core budget over the same period-while driving up data-centre energy demand. By contrast, automatically migrating files to deep-archive tiers 3 months after newborn screening preserves future utility but cuts lifetime storage costs by 91% to about £18 per child and reduces operational power by an order of magnitude; 12-24 hour restore latencies remain clinically acceptable for episodic re-analysis. I argue that newborn sequencing is primarily a logistics challenge rather than a scientific one, and that a national 'screen-then-archive' policy, anchored by a retrieval service-level agreement, would safeguard public funds, support workforce expansion and honour NHS carbon commitments while allowing consent-based re-analysis at adolescence or adulthood. Embedding cold storage economics now will prevent the programme from sinking under an exabyte scale liability.

Hospitals, traditionally classified within the tertiary sector due to their service-oriented nature, nevertheless exhibit energy demands and technical characteristics akin to those of industrial facilities. Motivated by this, this paper redefines hospital energy demand by emphasizing shared energy forms and consumption processes between healthcare and industry. Methodologically, the study conducts a comparative analysis of energy intensity across regions, highlights process-level similarities and regulatory disparities, proposes a hybrid regulatory framework tailored to healthcare buildings, and reviews the literature on Distributed Energy Systems (DES) in hospitals. To complement these analyses with quantitative evidence, a dynamic TRNSYS 18 mini-scenario is introduced for a representative block of Specialities Operating Theatres (OTs). The simulation provides hourly cooling and electrical loads and yields an annual combined electricity intensity of approximately 780 [Formula: see text]m[Formula: see text]yr[Formula: see text], a value that exceeds legacy, medium-size, and even hyperscale data-centre benchmarks. This empirical result supports the claim that critical hospital zones behave energetically as clean-process environments, closer to industrial or infrastructural uses than to conventional tertiary spaces. The findings show that hospitals consume energy at levels closer to industry than to commercial buildings, with critical continuous loads. The industrial sector has already demonstrated rigorous adoption of DES, setting a precedent for their integration in healthcare. Despite progress, the literature lacks comprehensive and region-specific reviews on integrating DES in healthcare, including cogeneration (CHP), trigeneration (CCHP), solar energy systems, and medical waste-to-energy (WtE) recovery. Fully integrated solar-CCHP-WtE systems, in particular, remain underexplored. A novel contribution of this work lies in formulating a hybrid regulatory framework that redefines hospitals as industrial-scale energy hubs, bridging the gap between rigorous industrial DES practices and the specialized operational requirements of the healthcare sector. Overall, the integration of DES presents hospitals with significant opportunities to enhance energy efficiency, improve system reliability, and achieve substantial environmental benefits, all while maintaining the stringent quality standards required in healthcare environments.

Graphical AbstractBalancing clinical benefits and environmental cost of AI in cardiovascular imaging. Top panel. AI provides major benefits in cardiovascular imaging, including faster acquisition and reconstruction, fewer artefacts, automated segmentation and quantification, structured reporting, and clinical decision support. Middle panel. Comparison between Green AI and Red AI paradigms. While clinical performance may be similar, Green AI prioritizes efficiency and transparency, whereas Red AI is associated with disproportionate computational demand and unreported environmental costs. Bottom panel. Proposed framework for a carbon transparency statement, based on measuring energy consumption, accounting for data-centre overhead, converting energy use to carbon emissions, and reporting the full AI development footprint. AI, artificial intelligence; CVI, cardiovascular imaging; CO2, carbon dioxide; GPU, graphics processing unit; kgCO2e, kilograms of carbon dioxide equivalent.For image description, please refer to the figure legend and surrounding text.

Symptoms of lymphomas include peripheral lymphadenopathy, B-symptoms, and other organ-specific symptoms; however, data on initial symptoms incidence in diffuse large B-cell lymphoma (DLBCL) remain limited. We aimed to investigate real-world patterns of initial DLBCL symptoms, correlating them with baseline characteristics and symptom onset-to-diagnosis interval. Patients with DLBCL diagnosed between 2010 and 2021 receiving R-CHOP were screened. 706 individuals with reported initial symptoms were analyzed. 682 (97%) patients had documented symptoms; remaining 24 patients (3%) had incidental findings discovered during examinations for unrelated reasons. Abdominal/gastrointestinal complaints were the most prevalent symptoms (26%), followed by peripheral lymphadenopathy (22%), and B-symptoms (13%). The median symptom-to-diagnosis interval was 10 weeks. Peripheral lymphadenopathy and testicular tumors correlated with low-risk characteristics, with testicular DLBCL featuring a shorter symptom-to-diagnosis interval. Limb pain/swelling and back pain were associated with high-risk characteristics and prolonged symptom-to-diagnosis interval. This analysis enhances our understanding of DLBCL symptomatology, aiding in timely recognition and management.

Quality care in breast cancer is higher if patients are treated in a Breast Center with a dedicated and specialized multidisciplinary team. Quality control is an essential activity to ensure quality care, which has to be based on the monitoring of specific quality indicators. Eusoma has proceeded with the up-dating of the 2017 Quality indicators for non-metastatic breast cancer based on the new diagnostic, locoregional and systemic treatment modalities. To proceed with the updating, EUSOMA setup a multidisciplinary working group of BC experts and patients' representatives. It is a comprehensive set of QIs for early breast cancer care, which are classified as mandatory, recommended, or observational. For the first time patient reported outcomes (PROMs) have been included. As used in the 2017 EUSOMA QIs, evidence levels were based on the short version of the US Agency for Healthcare Research and Quality. This is a set of quality indicators representative for the different steps of the patient pathway in non-metastatic setting, which allow Breast Centres to monitor their performance with referring standards, i.e minimum standard and target. Monitoring these Quality Indicators, within the Eusoma datacentre will allow to have a state of the art picture at European Breast Centres level and the development of challenging research projects.

Electro-optical photonic integrated circuits (PICs) based on lithium niobate (LiNbO3) have demonstrated the vast capabilities of materials with a high Pockels coefficient1,2. They enable linear and high-speed modulators operating at complementary metal-oxide-semiconductor voltage levels3 to be used in applications including data-centre communications4, high-performance computing and photonic accelerators for AI5. However, industrial use of this technology is hindered by the high cost per wafer and the limited wafer size. The high cost results from the lack of existing high-volume applications in other domains of the sort that accelerated the adoption of silicon-on-insulator (SOI) photonics, which was driven by vast investment in microelectronics. Here we report low-loss PICs made of lithium tantalate (LiTaO3), a material that has already been adopted commercially for 5G radiofrequency filters6 and therefore enables scalable manufacturing at low cost, and it has equal, and in some cases superior, properties to LiNbO3. We show that LiTaO3 can be etched to create low-loss (5.6 dB m-1) PICs using a deep ultraviolet (DUV) stepper-based manufacturing process7. We demonstrate a LiTaO3 Mach-Zehnder modulator (MZM) with a half-wave voltage-length product of 1.9 V cm and an electro-optic bandwidth of up to 40 GHz. In comparison with LiNbO3, LiTaO3 exhibits a much lower birefringence, enabling high-density circuits and broadband operation over all telecommunication bands. Moreover, the platform supports the generation of soliton microcombs. Our work paves the way for the scalable manufacture of low-cost and large-volume next-generation electro-optical PICs.

Photonic integrated circuits are widely used in applications such as telecommunications and data-centre interconnects1-5. However, in optical systems such as microwave synthesizers6, optical gyroscopes7 and atomic clocks8, photonic integrated circuits are still considered inferior solutions despite their advantages in size, weight, power consumption and cost. Such high-precision and highly coherent applications favour ultralow-noise laser sources to be integrated with other photonic components in a compact and robustly aligned format-that is, on a single chip-for photonic integrated circuits to replace bulk optics and fibres. There are two major issues preventing the realization of such envisioned photonic integrated circuits: the high phase noise of semiconductor lasers and the difficulty of integrating optical isolators directly on-chip. Here we challenge this convention by leveraging three-dimensional integration that results in ultralow-noise lasers with isolator-free operation for silicon photonics. Through multiple monolithic and heterogeneous processing sequences, direct on-chip integration of III-V gain medium and ultralow-loss silicon nitride waveguides with optical loss around 0.5 decibels per metre are demonstrated. Consequently, the demonstrated photonic integrated circuit enters a regime that gives rise to ultralow-noise lasers and microwave synthesizers without the need for optical isolators, owing to the ultrahigh-quality-factor cavity. Such photonic integrated circuits also offer superior scalability for complex functionalities and volume production, as well as improved stability and reliability over time. The three-dimensional integration on ultralow-loss photonic integrated circuits thus marks a critical step towards complex systems and networks on silicon.

Short intensive chemotherapy is the standard of care for adult patients with Burkitt's leukaemia or lymphoma. Findings from single-arm studies suggest that addition of rituximab to these regimens could improve patient outcomes. Our objective was to test this possibility in a randomised trial. In this randomised, controlled, open-label, phase 3 trial, we recruited patients older than 18 years with untreated HIV-negative Burkitt's lymphoma (including Burkitt's leukaemia) from 45 haematological centres in France. Exclusion criteria were contraindications to any drug included in the chemotherapy regimens, any serious comorbidity, poor renal (creatinine concentration >150 &#x3bc;mol/L) or hepatic (cirrhosis or previous hepatitis B or C) function, pregnancy, and any history of cancer except for non-melanoma skin tumours or stage 0 (in situ) cervical carcinoma. Patients were stratified into two groups based on disease extension (absence [group B] or presence [group C] of bone marrow or central nervous system involvement). Patients were further stratified in group C according to age (<40 years, 40-60 years, and >60 years) and central nervous system involvement. Participants were randomly assigned in each group to either intravenous rituximab injections and chemotherapy (lymphome malin B [LMB]) or chemotherapy alone by the Groupe d'Etude des Lymphomes de l'Adulte datacentre. Randomisation was stratified by treatment group and centre using computer-assisted permuted-block randomisation (block size of four; allocation ratio 1:1). We gave rituximab (375 mg/m(2)) on day 1 and day 6 during the first two courses of chemotherapy (total of four infusions). The primary endpoint is 3 year event-free survival (EFS). We analysed all patients who had data available according to their originally assigned group. This trial is registered with ClinicalTrials.gov, number NCT00180882. Between Oct 14, 2004, and Sept 7, 2010, we randomly allocated 260 patients to rituximab or no rituximab (group B 124 patients [64 no rituximab; 60 rituximab]; group C 136 patients [66 no rituximab; 70 rituximab]). With a median follow-up of 38 months (IQR 24-59), patients in the rituximab group achieved better 3 year EFS (75% [95% CI 66-82]) than did those in the no rituximab group (62% [53-70]; log-rank p stratified by treatment group=0&#xb7;024). The hazard ratio estimated with a Cox model stratified by treatment group, assuming proportionality, was 0&#xb7;59 for EFS (95% CI 0&#xb7;38-0&#xb7;94; p=0&#xb7;025). Adverse events did not differ between the two treatment groups. The most common adverse events were infectious (grade 3-4 in 137 [17%] treatment cycles in the rituximab group vs 115 [15%] in the no rituximab group) and haematological (mean duration of grade 4 neutropenia of 3&#xb7;31 days per cycle [95% CI 3&#xb7;01-3&#xb7;61] vs 3&#xb7;38 days per cycle [3&#xb7;05-3&#xb7;70]) events. Addition of rituximab to a short intensive chemotherapy programme improves EFS in adults with Burkitt's leukaemia or lymphoma. Gustave Roussy Cancer Campus, Roche, Chugai, Sanofi.

This paper reports on the first user/application-driven multi-technology optical sub-wavelength network for intra/inter Data-Centre (DC) communications. Two DCs each with distinct sub-wavelength switching technologies, frame based synchronous TSON and packet based asynchronous OPST are interconnected by a WSON inter-DC communication. The intra/inter DC testbed demonstrates ultra-low latency (packet-delay <270 &#xb5;s and packet-delay-variation (PDV)<10 &#xb5;s) flexible data-rate traffic transfer by point-to-point, point-to-multipoint, and multipoint-to-(multi)point connectivity, highly suitable for cloud based applications and high performance computing (HPC). The extended GMPLS-PCE-SLAE based control-plane enables innovative application-driven end-to-end sub-wavelength path setup and resource reservation across the multi technology data-plane, which has been assessed for as many as 25 concurrent requests.

Chemotherapy-induced neutropenia is the most common adverse effect of chemotherapy and is often complicated by febrile neutropenia (FN). The objective of this study is to validate a classification of aggressiveness of a chemotherapy regimen and to evaluate its usefulness in a risk prediction model of FN in patients with hematological cancer at the beginning of a chemotherapy cycle. Two hundred and sixty-six patients were prospectively enrolled and followed during 1053 cycles. Relevant patient informations were collected at the beginning of the first cycle and the number of days of FN were counted in the follow-up [dichotomized (no FN versus >or= 1 day of FN)]. Aggressive chemotherapy regimen is the major predictor of FN [odds ratio 5.2 (3.2-8.4)]. The other independent predictors are the underlying disease, an involvement of bone marrow, body surface <or= 2 m(2), a baseline monocyte count <150/microl and the interaction between the first cycle in the same treatment line and a baseline hemoglobin dosage. A rule of prediction of FN was computed with these characteristics: sensitivity 78.6%, specificity 62.3%, positive predictive value 42.7% and negative predictive value 89.1%. Further studies are needed to validate this score.

A number of studies suggest that response to antihuman epidermal growth factor receptor-2 (currently known as ERBB2, butreferred to asHER2 in this study) agents differs by estrogen receptor (ER) level status. The clinical relevance of this is unknown. To determine the magnitude of trastuzumab benefit according to quantitative levels of ER and HER2 in the HERceptin Adjuvant (HERA) trial. The HERA trial was an international, multicenter, randomized trial that included 5099 patients with early-stage HER2-positive breast cancer, randomized between 2001 and 2005 to receive either no trastuzumab or trastuzumab, after adjuvant chemotherapy. This is a secondary analysis of the HERA study. Local ER immunohistochemical (IHC) analyses, HER2 fluorescence in situ hybridization (FISH) ratio, and copy number results were available for 3037 patients (59.6%) randomized to observation and trastuzumab (1 or 2 years) (cohort 1). Transcript levels of ESR1 and HER2 genes were available for 615 patients (12.1%) (cohort 2). Patients were randomized to receive either no trastuzumab or 1 year vs 2 years of trastuzumab. Endocrine therapy was given to patients with hormone receptor-positive disease as per local guidelines. Disease-free survival (DFS) and overall survival (OS) were the primary and secondary end points in the intent-to-treat population (ITT). Analyses adjusting for crossover (censored and inverse probability weighted [IPW]) were also performed. Interactions among treatment, ER status, and HER2 amplification using predefined cutoffs were assessed in Cox proportional hazards regression models. Median follow-up time was 8 years. Levels of FISH and HER2 copy numbers were significantly higher in ER-negative patients (P&#x2009;<&#x2009;.001). In cohort 1, for DFS and OS, a significant treatment effect was found for all ER, IHC, and FISH levels, except for the ER-positive/HER2 low FISH ratio (&#x2265;2 to <5) group (DFS: 3-way ITT Pvalue for interaction&#x2009;=&#x2009;.07; censored&#x2009;=&#x2009;.02; IPW&#x2009;=&#x2009;.03; OS ITT Pvalue for interaction&#x2009;=&#x2009;.007; censored&#x2009;=&#x2009;.04; IPW&#x2009;=&#x2009;.03). In cohort 2, consistent with cohort 1, a significant predictive effect of the ESR1 gene for both end points was also observed (DFS Pvalue for interaction&#x2009;=&#x2009;.06; OS&#x2009;=&#x2009;.02), indicating that breast cancers with higher ESR1 levels also derive less benefit from trastuzumab. Patients with HER2-positive breast cancers that are ER-positive by IHC analyses with low FISH ratio (&#x2265;2 to <5), or with higher ESR1 levels derive significantly less benefit from adjuvant trastuzumab after chemotherapy. These data may explain heterogeneity in response to anti-HER2 agents in HER2-positive, ER-positive breast cancers as some may be more luminal-like than HER2 driven. clinicaltrials.gov Identifier: NCT00045032.

We report both experimentally and in theory on the detection of edge features in digital images with an artificial optical spiking neuron based on a vertical-cavity surface-emitting laser (VCSEL). The latter delivers fast (< 100 ps) neuron-like optical spikes in response to optical inputs pre-processed using convolution techniques; hence representing image feature information with a spiking data output directly in the optical domain. The proposed technique is able to detect target edges of different directionalities in digital images by applying individual kernel operators and can achieve complete image edge detection using gradient magnitude. Importantly, the neuromorphic (brain-like) spiking edge detection of this work uses commercially sourced VCSELs exhibiting responses at sub-nanosecond rates (many orders of magnitude faster than biological neurons) and operating at the important telecom wavelength of 1300&#x2005;nm; hence making our approach compatible with optical communication and data-centre technologies.

The main aim of the European Food Information Resource (EuroFIR) project is to develop and disseminate a comprehensive, coherent and validated data bank for the distribution of food composition data (FCD). This can only be accomplished by harmonising food description and data documentation and by the use of standardised thesauri. The data bank is implemented through a network of local FCD storages (usually national) under the control and responsibility of the local (national) EuroFIR partner. The implementation of the system based on the EuroFIR specifications is under development. The data interchange happens through the EuroFIR Web Services interface, allowing the partners to implement their system using methods and software suitable for the local computer environment. The implementation uses common international standards, such as Simple Object Access Protocol, Web Service Description Language and Extensible Markup Language (XML). A specifically constructed EuroFIR search facility (eSearch) was designed for end users. The EuroFIR eSearch facility compiles queries using a specifically designed Food Data Query Language and sends a request to those network nodes linked to the EuroFIR Web Services that will most likely have the requested information. The retrieved FCD are compiled into a specifically designed data interchange format (the EuroFIR Food Data Transport Package) in XML, which is sent back to the EuroFIR eSearch facility as the query response. The same request-response operation happens in all the nodes that have been selected in the EuroFIR eSearch facility for a certain task. Finally, the FCD are combined by the EuroFIR eSearch facility and delivered to the food compiler. The implementation of FCD interchange using decentralised computer systems instead of traditional data-centre models has several advantages. First of all, the local partners have more control over their FCD, which will increase commitment and improve quality. Second, a multicentred solution is more economically viable than the creation of a centralised data bank, because of the lack of national political support for multinational systems.

Modern RL-based post-training for large language models (LLMs) co-locate trajectory sampling and policy optimisation on the same GPU cluster, forcing the system to switch between inference and training workloads. This serial context switching violates the single-program-multiple-data (SPMD) assumption underlying today's distributed training systems. We present Echo, the RL system that cleanly decouples these two phases across heterogeneous "inference" and "training" swarms while preserving statistical efficiency. Echo introduces two lightweight synchronization protocols: a sequential pull mode that refreshes policy weights according to API call for minimal bias, and an asynchronous push-pull mode that streams version-tagged rollouts through a replay buffer to maximise hardware utilisation. Training four representative RL workloads with Qwen3-4B, Qwen2.5-7B, Qwen3-30B-A3B-Thinking-2507 and Qwen3-32B on a geographically distributed cluster, Echo matches a fully co-located Verl baseline in convergence speed and final reward while off-loading trajectory generation to commodity edge hardware. These promising results demonstrate that large-scale RL for LLMs could achieve datacentre-grade

We present LLMQ, an end-to-end CUDA/C++ implementation for medium-sized language-model training, e.g. 3B to 32B parameters, on affordable, commodity GPUs. These devices are characterized by low memory availability and slow communication compared to datacentre-grade GPUs. Consequently, we showcase a range of optimizations that target these bottlenecks, including activation checkpointing, offloading, and copy-engine based collectives. LLMQ is able to train or fine-tune a 7B model on a single 16GB mid-range gaming card, or a 32B model on a workstation equipped with 4 RTX 4090s. This is achieved while executing a standard 8-bit training pipeline, without additional algorithmic approximations, and maintaining FLOP utilization of around 50%. The efficiency of LLMQ rivals that of production-scale systems on much more expensive cloud-grade GPUs.

In this work, we describe our approach to compete in the autoPET3 datacentric track. While conventional wisdom suggests that larger datasets lead to better model performance, recent studies indicate that excluding certain training samples can enhance model accuracy. We find that in the autoPETIII dataset, a model that is trained on the entire dataset exhibits undesirable characteristics by producing a large number of false positives particularly for PSMA-PETs. We counteract this by removing the easiest samples from the training dataset as measured by the model loss before retraining from scratch. Using the proposed approach we manage to drive down the false negative volume and improve upon the baseline model in both false negative volume and dice score on the preliminary test set. Code and pre-trained models are available at github.com/alexanderjaus/autopet3_datadiet.

The exploration of Graph Neural Networks (GNNs) for processing graph-structured data has expanded, particularly their potential for causal analysis due to their universal approximation capabilities. Anticipated to significantly enhance common graph-based tasks such as classification and prediction, the development of a causally enhanced GNN framework is yet to be thoroughly investigated. Addressing this shortfall, our study delves into nine benchmark graph classification models, testing their strength and versatility across seven datasets spanning three varied domains to discern the impact of causality on the predictive prowess of GNNs. This research offers a detailed assessment of these models, shedding light on their efficiency, and flexibility in different data environments, and highlighting areas needing advancement. Our findings are instrumental in furthering the understanding and practical application of GNNs in diverse datacentric fields

Photonic integrated circuits utilize planar waveguides to process light on a chip, encompassing functions like generation, routing, modulation, and detection. Similar to the advancements in the electronics industry, photonics research is steadily transferring an expanding repertoire of functionalities onto integrated platforms. The combination of best-in-class materials at the wafer-level increases versatility and performance, suitable for large-scale markets, such as datacentre interconnects, lidar for autonomous driving or consumer health. These applications require mature integration platforms to sustain the production of millions of devices per year and provide efficient solutions in terms of power consumption and wavelength multiplicity for scalability. Chip-scale frequency combs offer massive wavelength parallelization, holding a transformative potential in photonic system integration, but efficient solutions have only been reported at the die level. Here, we demonstrate a silicon nitride technology on a 100 mm wafer that aids the performance requirements of soliton microcombs in terms of yield, spectral stability, and power efficiency. Soliton microcombs are reported with an

The recent progression of Large Language Models (LLMs) has witnessed great success in the fields of data-centric applications. LLMs trained on massive textual datasets showed ability to encode not only context but also ability to provide powerful comprehension to downstream tasks. Interestingly, Generative Pre-trained Transformers utilised this ability to bring AI a step closer to human being replacement in at least datacentric applications. Such power can be leveraged to identify anomalies of cyber threats, enhance incident response, and automate routine security operations. We provide an overview for the recent activities of LLMs in cyber defence sections, as well as categorization for the cyber defence sections such as threat intelligence, vulnerability assessment, network security, privacy preserving, awareness and training, automation, and ethical guidelines. Fundamental concepts of the progression of LLMs from Transformers, Pre-trained Transformers, and GPT is presented. Next, the recent works of each section is surveyed with the related strengths and weaknesses. A special section about the challenges and directions of LLMs in cyber security is provided. Finally, possible fut