bluuebunny/crossref_metadata_2025 huggingface dataset:
Differentiable Programming: Neural Networks and Selection Cuts Working Together
Authors: Watts Gordon
Published: May 2024

Differentiable Programming could open even more doors in HEP analysis and computing to Artificial Intelligence/Machine Learning. Current common uses of AI/ML in HEP are deep learning networks – providing us with sophisticated ways of separating signal from background, classifying physics, etc. This is only one part of a full analysis – normally skims are made to reduce dataset sizes by applying selection cuts, further selection cuts are applied, perhaps new quantities calculated, and all of that is fed to a deep learning network. Only the deep learning network stage is optimized using the AI/ML gradient decent technique. Differentiable programming offers us a way to optimize the full chain, including selection cuts that occur during skimming. This contribution investigates applying selection cuts in front of a simple neural network using differentiable programming techniques to optimize the complete chain on toy data. There are several well-known problems that must be solved – e.g., selection cuts are not differentiable, and the interaction of a selection cut and a network during training is not well understood. This investigation was motived by trying to automate reduced dataset skims and sizes during analysis – HL-LHC analyses have potentially multi-TB dataset sizes and an automated way of reducing those dataset sizes and understanding the trade-offs would help the analyser make a judgement between time, resource usages, and physics accuracy. This contribution explores the various techniques to apply a selection cut that are compatible with differentiable programming and how to work around issues when it is bolted onto a neural network. Code is available.
Digital Twins for Storage Systems and RAID Pools: Enhancing Data Management in High Energy Physics
Authors: Al-Maeeni Abdalaziz , Temirkhanov Aziz , Ryzhikov Artem , Maevskiy Dmitry , Ratnikov Fedor , Hushchyn Mikhail
Published: May 2024

In high-energy physics experiments, the acquisition of vast quantities of data poses formidable challenges in terms of efficient storage and management. We explore the application of the digital twin concept for SSD RAID pools, wherein digital replicas of physical systems are created to augment the efficiency of data storage within HEP experiments. By developing digital twins of storage systems, this research seeks to facilitate the continuous monitoring, comprehensive analysis, and strategic optimization of various workloads within the HEP domain. The key objectives of this study include the development of a digital twin for a data storage system and the formulation of generative models to assess the performance of the data storage system performance under specific configurations and data load parameters.
Efficient Search for New Physics Using Active Learning in the ATLAS Experiment
Authors: Bhatti Zubair , Cranmer Kyle , Espejo Irina , Heinrich Lukas , Gadow Phillip , Rieck Patrick , von Ahne Janik
Published: May 2024

Searches for new physics set exclusion limits in parameter spaces of typically up to 2 dimensions. However, the relevant theory parameter space is usually of a higher dimension but only a subspace is covered due to the computing time requirements of signal process simulations. An Active Learning approach is presented to address this limitation. Compared to the usual grid sampling, it reduces the number of parameter space points for which exclusion limits need to be determined. Hence it allows to extend interpretations of searches to higher dimensional parameter spaces and therefore to raise their value, e.g. via the identification of barely excluded subspaces which motivate dedicated new searches. In an iterative procedure, a Gaussian Process is fit to excluded signal cross-sections. Within the region close to the exclusion contour predicted by the Gaussian Process, Poisson disc sampling is used to determine further parameter space points for which the cross-section limits are determined. The procedure is aided by a warm-start phase based on computationally inexpensive, approximate limit estimates such as total signal cross-sections. The procedure is applied to a dark matter search on data collected by the ATLAS detector at the LHC, extending its interpretation from a 2 to a 4-dimensional parameter space while keeping the computational effort at a low level. The result is published in two formats: on one hand there is a publication of the Gaussian Process model. On the other hand, a visualization of the full 4-dimensional contour is presented as a collection of 2-dimensional exclusion contours where the 2 remaining parameters are chosen by the user.
End-to-end deep learning inference with CMSSW via ONNX using Docker
Authors: Chaudhari Purva , Chaudhari Shravan , Chudasama Ruchi , Gleyzer Sergei
Published: May 2024

Deep learning techniques have been proven to provide excellent performance for a variety of high-energy physics applications, such as particle identification, event reconstruction and trigger operations. Recently, we developed an end-to-end deep learning approach to identify various particles using low-level detector information from high-energy collisions. These models will be incorporated in the CMS software framework (CMSSW) to enable their use for particle reconstruction or for trigger operation in real time. Incorporating these computational tools in the experimental framework presents new challenges. This paper reports an implementation of the end-to-end deep learning inference with the CMS software framework. The inference has been implemented on GPU for faster computation using ONNX. We have benchmarked the ONNX inference with GPU and CPU using NERSC’s Perlmutter cluster by building a Docker image of the CMS software framework.
HyperTrack: Neural Combinatorics for High Energy Physics
Authors: Mieskolainen Mikael
Published: May 2024

Combinatorial inverse problems in high energy physics span enormous algorithmic challenges. This work presents a new deep learning driven clustering algorithm that utilizes a space-time non-local trainable graph constructor, a graph neural network, and a set transformer. The model is trained with loss functions at the graph node, edge and object level, including contrastive learning and meta-supervision. The algorithm can be applied to problems such as charged particle tracking, calorimetry, pile-up discrimination, jet physics, and beyond. We showcase the effectiveness of this cutting-edge AI approach through particle tracking simulations. The code is available online.
Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
Authors: Voigt Johann Christoph
Published: May 2024

With the High-Luminosity upgrade of the LHC, the number of simultaneous proton-proton collisions will be increased to up to 200. This requires an extensive overhaul of the detector systems. For the ATLAS Liquid Argon calorimeter electronics, 556 high performance FPGAs will be installed to reconstruct the energy for all 182 468 cells at the LHC bunch crossing frequency of 40 MHz. However, the current digital filter used for energy reconstruction (optimal filter) decreases in performance under these high pileup conditions. We demonstrate, that small recurrent or convolutional neural networks can outperform the optimal filter. Prototype implementations of the respective inference code in VHDL show, that the use of these networks on FPGAs is feasible and the resulting firmware fits onto the planned Intel Agilex devices. The full design is capable of processing 384 detector cells per FPGA, by combining parallel instances of the firmware with time division multiplexing.
Muon and Pion Identification at BESIII Based on Machine Learning Algorithm
Authors: Zhai Yuncong , Li Teng , Huang Xingtao , Yin Na
Published: May 2024

BESIII is designed to study physics in the τ-charm energy region utilizing the high luminosity BEPCII. For collision physics experiments like the BESIII experiment, particle identification (PID) is one of the most important and commonly used tools for physics analysis. The effective µ/π identification performance is of great significance for most of BESIII physics analysis. However, due to the close masses of these two particles, as well as the intrinsic correlation between multiple detector information, traditional methods at BESIII is facing challenges in µ/π identification. In recent decades, machine learning (ML) techniques have been rapidly developed and have shown successful applications in HEP experiments. The PID based on ML provides powerful capability of combining more detection information from all sub-detectors with the data-driven approach. In this article, targeting at the µ/π identification problem at the BESIII experiment, we have developed a new PID algorithm based on the gradient boosted decision tree (BDT) model. Preliminary results show that the XGBoost classifier provides obviously higher discrimination power than traditional methods. In addition, based on the substantial amount of high-quality data taken by the BESIII detector, a method of evaluating and suppressing the systematical error of the ML model is also introduced, which is critical for applying the model to physics studies.
Resilient VAE: Unsupervised Anomaly Detection at the SLAC Linac Coherent Light Source
Authors: Humble Ryan , Colocho William , O’Shea Finn , Ratner Daniel , Darve Eric
Published: May 2024

Significant advances in utilizing deep learning for anomaly detection have been made in recent years. However, these methods largely assume the existence of a normal training set (i.e., uncontaminated by anomalies) or even a completely labeled training set. In many complex engineering systems, such as particle accelerators, labels are sparse and expensive; in order to perform anomaly detection in these cases, we must drop these assumptions and utilize a completely unsupervised method. This paper introduces the Resilient Variational Autoencoder (ResVAE), a deep generative model specifically designed for anomaly detection. ResVAE exhibits resilience to anomalies present in the training data and provides feature-level anomaly attribution. During the training process, ResVAE learns the anomaly probability for each sample as well as each individual feature, utilizing these probabilities to effectively disregard anomalous examples in the training data. We apply our proposed method to detect anomalies in the accelerator status at the SLAC Linac Coherent Light Source (LCLS). By utilizing shot-to-shot data from the beam position monitoring system, we demonstrate the exceptional capability of ResVAE in identifying various types of anomalies that are visible in the accelerator.
Transformers for Generalized Fast Shower Simulation
Authors: Raikwar Piyush , Cardoso Renato , Chernyavskaya Nadezda , Jaruskova Kristina , Pokorski Witold , Salamani Dalila , Srivatsa Mudhakar , Tsolaki Kalliopi , Vallecorsa Sofia , Zaborowska Anna
Published: May 2024

Recently, transformer-based foundation models have proven to be a generalized architecture applicable to various data modalities, ranging from text to audio and even a combination of multiple modalities. Transformers by design should accurately model the non-trivial structure of particle showers thanks to the absence of strong inductive bias, better modeling of long-range dependencies, and interpolation and extrapolation capabilities. In this paper, we explore a transformer-based generative model for detector-agnostic fast shower simulation, where the goal is to generate synthetic particle showers, i.e., the energy depositions in the calorimeter. When trained with an adequate amount and variety of showers, these models should learn better representations compared to other deep learning models, and hence should quickly adapt to new detectors. In this work, we will show the prototype of a transformer-based generative model for fast shower simulation, as well as explore certain aspects of transformer architecture such as input data representation, sequence formation, and the learning mechanism for our unconventional shower data.
Use of Anomaly Detection algorithms to unveil new physics in Vector Boson Scattering
Authors: Lavizzari Giulia , Boldrini Giacomo , Gennai Simone , Govoni Pietro
Published: May 2024

A new methodology to improve the sensitivity to new physics contributions to the Standard Model processes at LHC is presented.

A Variational AutoEncoder trained on Standard Model processes is used to identify Effective Field Theory contributions as anomalies. While the output of the model is supposed to be very similar to the inputs for Standard Model events, it is expected to deviate significantly for events generated through new physics processes. The reconstruction loss can then be used to select a signal enriched region which is by construction independent of the nature of the chosen new physics process. In order to improve further the discrimination power, an adversarial layer is introduced with a cross entropy term added to the loss function, optimizing at the same time the reconstruction of the input variables of the Standard Model and classification of new physics processes. This procedure ensures that the model is optimized for discrimination, with a small price in terms of model dependency to physics process.

In this work I will discuss in detail the above-mentioned method using generator level Vector Boson Scattering events produced at LHC assuming an integrated luminosity of 350/fb.
Acceleration beyond lowest order event generation. An outlook on further parallelism within MadGraph5_aMC@NLO
Authors: Wettersten Zenny , Mattelaer Olivier , Roiser Stefan , Schöfbeck Robert , Valassi Andrea
Published: May 2024

An important area of high energy physics studies at the Large Hadron Collider (LHC) currently concerns the need for more extensive and precise comparison data. Important tools in this realm are event reweighing and evaluation of more precise next-to-leading order (NLO) processes via Monte Carlo event generators, especially in the context of the upcoming High Luminosity LHC. Current event generators need to improve throughputs for these studies. MadGraph5_aMC@NLO (MG5aMC) is an event generator being used by LHC experiments which has been accelerated considerably with a port to GPU and vector CPU architectures, but as of yet only for leading order processes. In this contribution a prototype for event reweighing using the accelerated MG5aMC software, as well as plans for an NLO implementation, are presented.
Control Simulation for an ESnet-JLab FPGA Accelerated Transport Load Balancer
Authors: Howard Derek , Goodrich Michael , Timmer Carl , Kumar Yatish , Heyes Graham , Lawrence David , Sheldon Stacey , Gyurjyan Vardan
Published: May 2024

The Thomas Jefferson National Accelerator Facility collaborates with Lawrence Berkeley National Lab to implement a dynamic UDP load balancer (LB) for high-throughput scientific data processing. This study employs a simulation to compare the efficacy of Proportional, Integrative, Derivative (PID) controllers and Q-Learning based controllers for configuring the load balancer. Two cluster configurations, homogeneous and heterogeneous, were examined. The simulation results indicate that PID control is superior in both configurations. In homogeneous clusters, PID achieved a 50% reduction in aggregate queue levels and maintained an even distribution across computational nodes (CNs). In contrast, Q-Learning was less effective in heterogeneous environments, exacerbating queue levels compared to the no-control case and failing to achieve balance across the cluster. Our findings suggest that PID control should be used for the ESnet-JLab FPGA Accelerated Transport (EJFAT) system.
Integrating LHCb Offline Workflows on Supercomputers State of Practice
Authors: Boyer Alexandre F. , Stagni Federico , Haen Christophe , Burr Christopher , Romanovskiy Vladimir , Bozzi Concezio
Published: May 2024

To better understand experimental conditions and performances of its experiment, the LHCb collaboration executes tens of thousands of looselycoupled and CPU-intensive Monte Carlo simulation workflows per hour. To meet the increasing LHC computing needs, funding agencies encourage the collaboration to exploit High-Performance Computing resources, and more specifically supercomputers, which offer a significant additional amount of computing resources but also come with higher integration challenges. This state-ofpractice paper outlines years of integration of LHCb simulation workflows on several supercomputers. The main contributions of this paper are: (i) an extensive description of the gap to address to run High-Energy Physics Monte Carlo simulation workflows on supercomputers; (ii) various methods and proposals to maximize the use of allocated CPU resources; (iii) a comprehensive analysis of LHCb production workflows running on diverse supercomputers.
ARMing HEP for the future Energy Efﬁciency of WLCG sites (ARM vs. x86)
Authors: Simili Emanuele , Stewart Gordon , Skipsey Samuel , Spiteri Dwayne , Borbely Albert , Britton David
Published: May 2024

We present a case for ARM chips as an alternative to standard x86 at WLCG sites to help reduce power consumption. New measurements are presented on the performance and energy consumption of two machines (one ARM and one x86), that were otherwise similar in speciﬁcation and cost. The comparison was extended to a dual socket x86 node, representative of our site. These new results include the energy-eﬃciency and speed of singleand multithreaded jobs; the eﬀect of hyper-threading; and an initial look at clock throttling as a way of shaping power-load. We observe signiﬁcantly lower power consumption and often slightly better performance on the ARM machine and, noting the increased availability of ARM software builds from all LHC experiments and beyond, we plan to install a 2k-core ARM cluster at our WLCG Tier2 site at Glasgow in the summer of 2023. This will enable testing, physicsvalidation, and eventually an ARM production environment that will inform and inﬂuence other WLCG sites in the UK and worldwide.
Evaluating Performance Portability with the CMS Heterogeneous Pixel Reconstruction code
Authors: Andriotis Nikolaos , Bocci Andrea , Cano Eric , Cappelli Laura , Di Pilato Tony , Ferragina Luca , Hugo Gabrielle , Kortelainen Matti J. , Kwok Martin , Olivera Loyola Juan Jose , Pantaleo Felice , Perego Aurora , Redjeb Wahid , Dewing Mark , Esseiva Julien
Published: May 2024

In the past years the landscape of tools for expressing parallel algorithms in a portable way across various compute accelerators has continued to evolve significantly. There are many technologies on the market that provide portability between CPU, GPUs from several vendors, and in some cases even FPGAs. These technologies include C++ libraries such as Alpaka and Kokkos, compiler directives such as OpenMP, the SYCL open specification that can be implemented as a library or in a compiler, and standard C++ where the compiler is solely responsible for the offloading. Given this developing landscape, users have to choose the technology that best fits their applications and constraints. For example, in the CMS experiment the experience so far in heterogeneous reconstruction algorithms suggests that the full application contains a large number of relatively short computational kernels and memory transfer operations. In this work we use a stand-alone version of the CMS heterogeneous pixel reconstruction code as a realistic use case of HEP reconstruction software that is capable of leveraging GPUs effectively. We summarize the experience of porting this code base from CUDA to Alpaka, Kokkos, SYCL, std::par, and OpenMP offloading. We compare the event processing throughput achieved by each version on NVIDIA and AMD GPUs as well as on a CPU, and compare those to what a native version of the code achieves on each platform.
Parallelizing Air Shower Simulation for Background Characterization in IceCube
Authors: Meagher Kevin , van Santen Jakob
Published: May 2024

The IceCube Neutrino Observatory is a cubic kilometer neutrino telescope located at the Geographic South Pole. For every observed neutrino event, there are over 106 background events caused by cosmic ray air shower muons. In order to properly separate signal from background, it is necessary to produce Monte Carlo simulations of these air showers. Although to-date, IceCube has produced large quantities of background simulation, these studies still remain statistics limited. The first stage of simulation requires heavy CPU usage while the second stage requires heavy GPU usage. Processing both of these stages on the same node will result in an underutilized GPU but using different nodes will encounter bandwidth bottlenecks. Furthermore, due to the power-law energy spectrum of cosmic rays, the memory footprint of the detector response often exceeded the limit in unpredictable ways. This proceeding presents new client–server code which parallelizes the first stage onto multiple CPUs on the same node and then passes it on to the GPU for photon propagation. This results in GPU utilization of greater than 90% as well as more predictable memory usage and an overall factor of 20 improvement in speed over previous techniques.
Application of quantum computing techniques in particle tracking at LHC
Authors: Chan Wai Yuen , Akiyama Daiya , Arakawa Koki , Ganguly Sanmay , Kaji Toshiaki , Minami Juri , Sawada Ryu , Tanaka Junichi , Terashi Koji , Yorita Kohei
Published: May 2024

After the next planned upgrades to the LHC, the luminosity it delivers will more than double, substantially increasing the already large demand on computing resources. Therefore an efficient way to reconstruct physical objects is required. Recent studies show that one of the quantum computing techniques, quantum annealing (QA), can be used to perform particle tracking with efficiency higher than 90% in the high pileup region in the high luminosity environment. The algorithm starts by determining the connection between the hits, and classifies the topological objects with their pattern. The current study aims to improve the pre-processing efficiency in the QA-based tracking algorithm by implementing a graph neural network (GNN), which is expected to efficiently generate the topological object needed for the annealing process. Tracking performance with a different setup of the original algorithm is also studied with data collected by the ATLAS experiment.
Benchmarking machine learning models for quantum state classification
Authors: Pedicillo Edoardo , Pasquale Andrea , Carrazza Stefano
Published: May 2024

Quantum computing is a growing field where the information is processed by two-levels quantum states known as qubits. Current physical realizations of qubits require a careful calibration, composed by different experiments, due to noise and decoherence phenomena. Among the different characterization experiments, a crucial step is to develop a model to classify the measured state by discriminating the ground state from the excited state. In this proceedings we benchmark multiple classification techniques applied to real quantum devices.
Leadership, Equity, Inclusion, Diversity, and Accessibility in Particle Physics Research
Authors: Gladney Larry
Published: May 2024

Big science is represented by projects like those in particle physics. Big engineering is the application of engineering principles to large-scale projects that have a significant impact on society, like popular use of AI/ML (think ChatGPT and Google Bard). Both big science and big engineering are among the noblest and boldest applications of the human intellect to understanding the universe and humanity’s place in it. Both depend on human collaboration to generate the ingenuity needed to make their impacts positive ones. Both are marred by evidence of bias, particularly racial bias, that lessens intellectual diversity and hence excellence. LEIDA – Leadership on Equity, Inclusion, Diversity, and Access is needed to ensure that opportunities lost in the past due to marginalization of particular communities eventually ends and the full breadth of creativity and innovation possible determines the future of our field.
Computing within the 2021 Snowmass process
Authors: Elvira V. Daniel
Published: May 2024

We present different elements of the 2021–2022 Computational Frontier (CompF) effort within the Snowmass process, including organization, events, and highlights of the final report [1]. With focus in the next 10–15 years, we analyze the impact of newly established and emerging technologies, identify challenges within theoretical, experimental and observational research programs, and present the report recommendations. We emphasize the main recommendation, which is the formation of a Coordinating Panel for Software and Computing (CPSC).
Robots, firm relocation, and air pollution: unveiling the unintended spatial spillover effects of emerging technology
Authors: Wang Yanying , Wu Qingyang
Published: May 2024

Amidst the global upsurge in industrial robot deployment, there remains a notable gap in our understanding of their environmental impact. This paper explores how the introduction of industrial robots has changed air quality at both the local and neighborhood levels in China. Using the Spatial Durbin Model, we investigate the regional spillovers of PM 2.5 concentration and the diffusion of this innovative technology. Our findings reveal that the rise of robots significantly reduces air pollution in the local area, while exacerbating it in neighboring regions. This contrast is mainly because pollution-intensive industries are more inclined to relocate to neighboring regions than their cleaner counterparts, after the local use of robots increases. Throughout the process, internal costs rather than external costs dominate firms’ relocation decisions. This study provides novel insights into the complex environmental externalities associated with the spread of industrial robots and highlights the critical issue of growing environmental inequality in the era of emerging technologies.
Prosodic features of polite speech
Authors: Brown Lucien , Oh Grace Eunhae , Idemaru Kaori
Published: May 2024

This paper uses interactional data to investigate the acoustic characteristics of polite or deferential speech in
Korean. We asked fourteen Korean speakers to perform two tasks with two different interlocutors: a status superior and a friend.
Consistent with previous studies of non-interactional data, deferential speech has lower pitch and shimmer, and quieter final
syllables. However, divergent from previous studies, deferential speech featured higher jitter (in some locations), higher shimmer
and higher H1-H2 (on one task). Through analysis of different locations in prosodic structure, we found that females used more
pitch variation on final syllables in deferential speech. We argue that these mixed results show the importance of context in
signalling vocal politeness, and also complexities of using interactional data. The findings advance the study of multimodal
politeness beyond the analysis of experimental data.
Inflection class interactions and valency changes in Matlatzinca
Authors: Palancar Enrique L. , Carranza Martínez Leonardo
Published: May 2024

In this paper, we explore how changes in the inflection class membership of verbs in Matlatzinca (Oto-Pamean, Oto-Manguean, Mexico) lead to changes in both their valency and meaning. In Matlatzinca, verbs often exhibit multiple class membership so that a given verb may be inflected as transitive in one class but as intransitive in another. For instance, the verb chun+ta, when inflected in different classes, can encompass diverse meanings: the action of ‘waking someone up’; the result state of ‘being awake’; and the spontaneous event of ‘waking up’. This linguistic phenomenon is intriguing from both a typological and a theoretical perspective as it challenges our understanding of lexical representation by prompting the question of whether these meanings represent distinct lexical entries or various construals of the same verb (Spencer 2013).
Epilogue
Authors: Berend Nora
Published: May 2024

A very brief epilogue reflects on Eric Hobsbawm’s famous dictum, ‘Historians are to nationalism what poppy-growers in Pakistan are to heroin-addicts: we supply the essential raw material for the market.’
Sporadic Creutzfeldt-Jakob disease in adults over 80 years: a 10-year review of United Kingdom surveillance
Authors: McDermott Eugene Ace , Watson Neil , Tam Johnny , Centola John , Kurucu King Hatice , Mackenzie Jan , Summers David , Green Alison , Barria Marcelo A , Smith Colin , Pal Suvankar
Published: May 2024

Introduction

Sporadic Creutzfeldt-Jakob disease (sCJD) is a rapidly progressive neurodegenerative disease with public health implications. Mean age of onset is 68 years. Age-specific incidence declines after 80 years. This may arise from under-ascertainment or other biological features of the disease. Accurate characterisation of late-onset sCJD is important for early diagnosis, avoiding unnecessary investigations and improving ascertainment for public health purposes.

Objective

To phenotype the clinical features and investigation profile of sCJD in adults >80 years.

Methods

We analysed all probable and definite sCJD cases identified by the UK National CJD Research & Surveillance Unit over a 10-year period (2011–2021). Individuals were grouped by age of onset. Clinical features and investigation profiles were compared.

Results

10.3% (123/1196) had an age of onset over 80. Median survival was shorter (3.2 vs 4.3 months; P < 0.001). Pyramidal signs (48.3% vs 34.2%; P = 0.008) and akinetic mutism (55.1% vs 33.2%; P < 0.001) were more frequent. Psychiatric symptoms (26.3% vs 39.6%; P = 0.01) and cerebellar signs (65.4% vs 78.6%, P = 0.007) were less frequent. Cognitive impairment and myoclonus were highly prevalent regardless of age. Between age groups, the diagnostic sensitivity of cerebrospinal fluid real-time quaking-induced conversion (CSF RT-QuIC) (92.9% vs 91.9%, P = 0.74) was comparable, electroencephalography was superior (41.5% vs 25.4%; P = 0.006) and MRI was inferior (67.8% vs 91.4%; P < 0.001).

Conclusions

Late-onset sCJD has distinct clinical features, shorter survival and a different profile of investigation sensitivity. CSF RT-QuIC, MRI brain and specialist CJD review is recommended in older adults with a rapidly progressive neurological disorder. Autopsy is valuable when the cause remains elusive.
Sarcopenia prevalence using handgrip strength or chair stand performance in adults living with type 2 diabetes mellitus
Authors: Belfield Archie E , Wilkinson Thomas J , Henson Joseph , Sargeant Jack A , Breen Leigh , Hall Andrew P , Davies Melanie J , Yates Thomas
Published: May 2024

Background

The updated European Working Group on Sarcopenia in Older People (EWGSOP2) recommends handgrip strength (HGS) and the chair stand test (CST) to assess muscle strength, with the CST being a convenient proxy for lower limb strength. However, adiposity may differentially influence these strength criteria and produce discrepant sarcopenia prevalence.

Objective

To determine the prevalence of sarcopenia using HGS or the CST, and to investigate the associations between these strength criteria and adiposity in adults with type 2 diabetes mellitus.

Methods

The EWGSOP2 definition was used to assess the prevalence of probable (low muscle strength), confirmed (plus low muscle mass) and severe (plus poor physical performance) sarcopenia. Linear regression models were used to study the association between different measures of muscle strength and adiposity.

Results

We used data from 732 adults with type 2 diabetes mellitus (35.7% female, aged 64 ± 8 years, body mass index 30.7 ± 5.0 kg/m2). Using the CST compared with HGS produced a higher prevalence of probable (31.7% vs. 7.1%), confirmed (5.6% vs. 1.6%) and severe (1.0% vs. 0.3%) sarcopenia, with poor agreement between strength criteria to identify probable sarcopenia. CST performance, but not HGS, was significantly associated with all measures of adiposity in unadjusted and adjusted models.

Conclusions

Higher levels of adiposity may impact CST performance, but not HGS, resulting in a higher prevalence of sarcopenia in adults with type 2 diabetes mellitus. Consideration should be paid to the most appropriate measure of muscle function in this population.
How do primary care clinicians approach the management of frailty? A qualitative interview study
Authors: Seeley Anna , Glogowska Margaret , Hayward Gail
Published: May 2024

Background

Around 15% of adults aged over 65 live with moderate or severe frailty. Contractual requirements for management of frailty are minimal and neither incentivised nor reinforced. Previous research has shown frailty identification in primary care is ad hoc and opportunistic, but there has been little focus on the challenges of frailty management, particularly within the context of recent introduction of primary care networks and an expanding allied health professional workforce.

Aim

Explore the views of primary care clinicians in England on the management of frailty.

Design and setting

Semi-structured interviews were conducted with clinicians across England, including general practitioners (GPs), physician associates, nurse practitioners, paramedics and clinical pharmacists. Thematic analysis was facilitated through NVivo (Version 12).

Results

A total of 31 clinicians participated. Frailty management was viewed as complex and outside of clinical guidelines with medication optimisation highlighted as a key example. Senior clinicians, particularly experienced GPs, were more comfortable with managing risk. Relational care was important in prioritising patient wishes and autonomy, for instance to remain at home despite deteriorations in health. In settings where more formalised multidisciplinary frailty services had been established this was viewed as successful by clinicians involved.

Conclusion

Primary care clinicians perceive frailty as best managed through trusted relationships with patients, and with support from experienced clinicians. New multidisciplinary working in primary care could enhance frailty services, but must keep continuity in mind. There is a lack of evidence or guidance for specific interventions or management approaches.
Insubordination and the rise of absolutism: the Mercure françois under Richelieu
Authors: Paton Caspar
Published: May 2024

It is often argued that Cardinal Richelieu appropriated the Mercure françois, France’s first printed newspaper, immediately upon entering the king’s council in 1624. This consensus originates in a questionable nineteenth-century work by Louis Dedouvres yet has not been seriously challenged, seemingly because it tallies neatly with traditional étatiste understandings of Richelieu as a great state-builder. By refuting Richelieu’s control over the Mercure during the 1620s, this article buttresses revisionist re-evaluations of his influence over the French state during that period. It extends such revisionism to Richelieu’s regulation of the mainstream press and public sphere, and suggests the Mercure represents a valuable alternative source through which the earliest years of his second ministry might be better apprehended.
Benfotiamine improves dystrophic pathology and exercise capacity in mdx mice by reducing inflammation and fibrosis
Authors: Coles Chantal A , Woodman Keryn G , Gibbs Elizabeth M , Crosbie Rachelle H , White Jason D , Lamandé Shireen R
Published: May 2024

Duchenne Muscular Dystrophy (DMD) is a progressive and fatal neuromuscular disease. Cycles of myofibre degeneration and regeneration are hallmarks of the disease where immune cells infiltrate to repair damaged skeletal muscle. Benfotiamine is a lipid soluble precursor to thiamine, shown clinically to reduce inflammation in diabetic related complications. We assessed whether benfotiamine administration could reduce inflammation related dystrophic pathology. Benfotiamine (10 mg/kg/day) was fed to male mdx mice (n = 7) for 15 weeks from 4 weeks of age. Treated mice had an increased growth weight (5–7 weeks) and myofibre size at treatment completion. Markers of dystrophic pathology (area of damaged necrotic tissue, central nuclei) were reduced in benfotiamine mdx quadriceps. Grip strength was increased and improved exercise capacity was found in mdx treated with benfotiamine for 12 weeks, before being placed into individual cages and allowed access to an exercise wheel for 3 weeks. Global gene expression profiling (RNAseq) in the gastrocnemius revealed benfotiamine regulated signalling pathways relevant to dystrophic pathology (Inflammatory Response, Myogenesis) and fibrotic gene markers (Col1a1, Col1a2, Col4a5, Col5a2, Col6a2, Col6a2, Col6a3, Lum) towards wildtype levels. In addition, we observed a reduction in gene expression of inflammatory gene markers in the quadriceps (Emr1, Cd163, Cd4, Cd8, Ifng). Overall, these data suggest that benfotiamine reduces dystrophic pathology by acting on inflammatory and fibrotic gene markers and signalling pathways. Given benfotiamine’s excellent safety profile and current clinical use, it could be used in combination with glucocorticoids to treat DMD patients.
In vitro activity of cefiderocol in Pseudomonas aeruginosa isolates from people with cystic fibrosis recovered during three multicentre studies in Spain
Authors: Maruri-Aransolo Ainhize , López-Causapé Carla , Hernández-García Marta , García-Castillo María , Caballero-Pérez Juan de Dios , Oliver Antonio , Cantón Rafael
Published: May 2024

Objectives

Despite the introduction of cystic fibrosis transmembrane conductance regulator (CFTR) modulators, Pseudomonas aeruginosa is still a major pathogen in people with cystic fibrosis (pwCF). We determine the activity of cefiderocol and comparators in a collection of 154 P. aeruginosa isolates recovered from pwCF during three multicentre studies performed in 17 Spanish hospitals in 2013, 2017 and 2021.

Methods

ISO broth microdilution was performed and MICs were interpreted with CLSI and EUCAST criteria. Mutation frequency and WGS were also performed.

Results

Overall, 21.4% were MDR, 20.8% XDR and 1.3% pandrug-resistant (PDR). Up to 17% of the isolates showed a hypermutator phenotype. Cefiderocol demonstrated excellent activity; only 13 isolates (8.4%) were cefiderocol resistant by EUCAST (none using CLSI). A high proportion of the isolates resistant to ceftolozane/tazobactam (71.4%), meropenem/vaborbactam (70.0%), imipenem/relebactam (68.0%) and ceftazidime/avibactam (55.6%) were susceptible to cefiderocol. Nine out of 13 cefiderocol-resistant isolates were hypermutators (P < 0.001). Eighty-three STs were detected, with ST98 being the most frequent. Only one isolate belonging to the ST175 high-risk clone carried blaVIM-2. Exclusive mutations affecting genes involved in membrane permeability, AmpC overexpression (L320P-AmpC) and efflux pump up-regulation were found in cefiderocol-resistant isolates (MIC = 4–8 mg/L). Cefiderocol resistance could also be associated with mutations in genes related to iron uptake (tonB-dependent receptors and pyochelin/pyoverdine biosynthesis).

Conclusions

Our results position cefiderocol as a therapeutic option in pwCF infected with P. aeruginosa resistant to most recent β-lactam/β-lactamase inhibitor combinations.
Influencing attitudes towards antimicrobial use and resistance in companion animals—the impact on pet owners of a short animation in a randomized controlled trial
Authors: Wright Emma , Jessen Lisbeth Rem , Tompson Alice , Rutland Catherine , Singleton David , Battersby Ian , Gajanayake Isuru , Mosher Margo , Pfleger Sharon , Gemmill Toby , Sparks Tim , Sørensen Tina M , Allerton Fergus
Published: May 2024

Objectives

Antimicrobial resistance (AMR) is a vital One Health issue; the rational use of antimicrobials is essential to preserve their efficacy. Veterinarians cite pressure from pet owners as a contributor to antimicrobial prescription. Engaging pet owners in antimicrobial stewardship could reduce this pressure. A short educational animation could facilitate communication of this message. The impact of the animation on participant’s opinions relating to antimicrobial prescribing and awareness of AMR was assessed via a randomized controlled trial.

Methods

A survey was created based on the health belief model. Owners attending six UK veterinary centres were randomized to the intervention or control group (ratio 1:1). All owners completed an agreement level survey of two questions followed by 18 statements scored using a Likert agreement scale. The control group responded without interruption, whereas the animation group was shown the animation after answering the first two questions and five statements.

Results

In total, 647 owners participated in the study; 350 complete responses were analysed. Responses to 10 of 13 statements asked after the animation were significantly different (all P < 0.050) between groups, whereas there was no significant difference between groups in response to any of the statements asked before the animation. The animation group were more likely to agree that lower antimicrobial use would help maintain future efficacy (P < 0.001) and that requesting antimicrobials from their vet could increase unnecessary use (P < 0.001). The animation group were more likely to disagree that they would expect antimicrobials if their pet had diarrhoea (P = 0.048).

Conclusions

Pet owners that watched a short AMR engagement animation displayed greater awareness of the impact of AMR and were more likely to support measures in line with antimicrobial stewardship. This behavioural-nudge resource could support owners towards contributing to a multi-faceted approach to AMR.
Clinical significance of cefazolin inoculum effect in serious MSSA infections: a systematic review
Authors: Lo Calvin Ka-Fung , Sritharan Ashwin , Zhang Jiesi , Li Nicole , Zhang Cindy , Wang Frank , Loeb Mark , Bai Anthony D
Published: May 2024

Background

The cefazolin inoculum effect (CzIE) is a phenomenon whereby some MSSA isolates demonstrate resistance to cefazolin when a high bacterial inoculum is used for susceptibility testing. The clinical significance of this phenotypic phenomenon remains unclear. We conducted a systematic review to answer the following question: In patients with serious MSSA infection treated with cefazolin, does infection due to CzIE-positive MSSA isolates result in worse clinical outcomes than infection due to CzIE-negative MSSA isolates?

Methods

Ovid MEDLINE, Embase, Cochrane CENTRAL, medRxiv and bioRxiv were searched from inception until 12 April 2023. Studies were included if they tested for CzIE in clinical isolates from MSSA infections in humans. Two independent reviewers extracted data and conducted risk-of-bias assessment. Main outcomes were treatment failure and mortality. Pooling of study estimates was not performed given the heterogeneity of patient populations and outcome definitions.

Results

Twenty-three observational studies were included. CzIE presence amidst MSSA isolates ranged from 0% to 55%. There was no statistically significant mortality difference in two studies that compared MSSA infections with and without CzIE, with ORs ranging from 0.72 to 19.78. Of four studies comparing treatment failure, ORs ranged from 0.26 to 13.00. One study showed a significantly higher treatment failure for the CzIE group, but it did not adjust for potential confounders.

Conclusions

The evidence on CzIE is limited by small observational studies. In these studies, CzIE did not predict higher mortality in MSSA infections treated with cefazolin. Our findings do not support CzIE testing in clinical practice currently.
Intravenous cefuroxime as a first-line treatment for women hospitalized for pyelonephritis
Authors: Everard Céline , Schampaert Axelle , Doyen Louise , Verbelen Valérie , Marot Jean-Christophe , Wieërs Grégoire
Published: May 2024

Background

Empirical treatment of pyelonephritis in the emergency ward includes broad-spectrum antibiotics. Such a strategy favours broad-spectrum antibiotic overuse. Local antibiotic stewardship teams can propose local recommendations to adapt empirical antibiotic treatment devoted to spare precious molecules that remain active on MDR bacteria, such as fluoroquinolones or other broad-spectrum antibiotics.

Objectives

We aimed to evaluate the incidence of urinary tract infection recurrence within 3 months after hospital discharge following empirical antibiotic therapy with cefuroxime in women with pyelonephritis in the emergency room.

Patients and methods

We conducted a retrospective, single-centre study. We identified 109 women treated for pyelonephritis, 95 with cefuroxime at any time, and 14 with only other antibiotics, and divided them into subgroups based on antibiotic switch to other molecules. We compared the incidence of urinary tract infection recurrence in the subgroups.

Results

In the group of patients treated with cefuroxime only, we identified five cases of recurrence (9.4%) in a total of 53 patients, but only 1 (1.9%) case of recurrence associated with the same uropathogen. No significant difference in clinical outcome, length of antibiotic treatment, or urinary tract infection recurrence was observed between the subgroups.

Conclusions

Our study supports that a strategy elaborated by an antibiotic stewardship team based on local ecology and aimed at proposing the narrowest-spectrum antibiotic upon treatment initiation in the emergency room is safe.
Ataxia telangiectasia and Rad3-related (ATR) inhibitor camonsertib dose optimization in patients with biomarker-selected advanced solid tumors (TRESR study)
Authors: Fontana Elisa , Rosen Ezra , Lee Elizabeth K , Højgaard Martin , Mettu Niharika B , Lheureux Stephanie , Carneiro Benedito A , Cote Gregory M , Carter Louise , Plummer Ruth , Mahalingam Devalingam , Fretland Adrian J , Schonhoft Joseph D , Silverman Ian M , Wainszelbaum Marisa , Xu Yi , Ulanet Danielle , Koehler Maria , Yap Timothy A
Published: May 2024

Background

Camonsertib is a selective oral inhibitor of ataxia telangiectasia and Rad3-related (ATR) kinase with demonstrated efficacy in tumors with DNA damage response gene deficiencies. On-target anemia is the main drug-related toxicity typically manifesting after the period of dose-limiting toxicity evaluation. Thus, dose and schedule optimization requires extended follow-up to assess prolonged treatment effects.

Methods

Long-term safety, tolerability, and antitumor efficacy of 3 camonsertib monotherapy dosing regimens were assessed in the TRESR study dose-optimization phase: 160 mg once daily (QD) 3 days on, 4 days off (160 3/4; the preliminary recommended Phase II dose [RP2D]) and two step-down groups of 120 mg QD 3/4 (120 3/4) and 160 mg QD 3/4, 2 weeks on, 1 week off (160 3/4, 2/1w). Safety endpoints included incidence of treatment-related adverse events (TRAEs), dose modifications, and transfusions. Efficacy endpoints included overall response rate, clinical benefit rate, progression-free survival, and circulating tumor DNA (ctDNA)-based molecular response rate.

Results

The analysis included 119 patients: 160 3/4 (n = 67), 120 3/4 (n = 25), and 160 3/4, 2/1w (n = 27) treated up to 117.1 weeks as of the data cutoff. The risk of developing grade 3 anemia was significantly lower in the 160 3/4, 2/1w group compared with the preliminary RP2D group (hazard ratio = 0.23, 2-sided P = .02), translating to reduced transfusion and dose reduction requirements. The intermittent weekly schedule did not compromise antitumor activity.

Conclusion

The 160 3/4, 2/1w dose was established as an optimized regimen for future camonsertib monotherapy studies offering a substantial reduction in the incidence of anemia without any compromise to efficacy.

Clinical Trial ID

NCT04497116.