bluuebunny/crossref_metadata_2025 huggingface dataset:
Bayesian optimization for ion beam centroid correction
Authors: Ghelfi E. , Katrusiak A. , Baartman R. , Fedorko W. , Kester O. , Kogler Anele G. , Shelbaya O. , Tanyer D.
Published: February 2025

An activity of the TRIUMF automatic beam tuning program, the Bayesian optimization for Ion Steering (BOIS) method has been developed to perform corrective centroid steering of beams at the TRIUMF ISAC facility. BOIS exclusively controls the steerers for centroid correction after the transverse optics have been set according to theory. The method is fully online, easy to deploy, and has been tested in low energy and post-accelerated beams at ISAC, achieving results comparable to human operators. scaleBOIS and boundBOIS are naïve proof-of-concept solutions to preferably select beam paths with minimal steering. Repeatable and robust automated steering reduces reliance on operator expertise and operational overhead, ensuring reliable beam delivery to the experiments and thereby supporting TRIUMF’s scientific mission.
Origin of the change in giant magnetoresistance effects of Fe/V multilayer by hydrogen absorption
Authors: Akamaru Satoshi , Miyake Kyosuke
Published: February 2025

This study investigated the giant magnetoresistance (GMR) effect of a Fe/V(001) multilayer under different hydrogen concentrations in a hydrogen–nitrogen gas mixture to elucidate the effect of hydrogen absorption in the V layer on the exchange interactions between each Fe layer. The resistance against hydrogen concentration in the gas mixture revealed a phase boundary that was dependent on the V thickness in Fe/V, between hydrogen dissolved in the V metal and V hydride phases. The magnetoresistance in Fe/V with a V thickness of 1.7–2.0 nm demonstrated a GMR effect, which was reduced under low hydrogen concentration in the gas mixture, corresponding to the hydrogen dissolved phase in the V layer. However, Fe/V samples with V thicknesses within the range of 2.2–2.7 nm exhibited the GMR effect during the formation of the V hydride phase, although these samples did not display any GMR behavior under nitrogen gas. These behaviors were reversible to hydrogen concentration in the gas mixture. The dependence of the exchange coupling coefficient on the V layer thickness was estimated from the GMR behavior, revealing that the exchange coupling coefficient was governed by the change in the crystalline phase from the V metal to the hydride and not by the thickness of the V layer. In the V hydride phase, the GMR effect was gradually reduced following hydrogen absorption, suggesting that the induced structural disorder and/or stress in the V layer due to excess hydrogen absorption inhibited the exchange interactions between each Fe layer.
Modeling and simulation of droplet spreading on different wettability substrates
Authors: Huo Ye , Zhong Yuguang , Xin Minyan , Li Songcheng , Chen Yongheng , Wu Peng
Published: February 2025

The flow behavior of droplet on substrates is widespread in industry and nature, and it is a complex process of multi-field coupling, involving two-phase flow and droplet–substrate interaction. In this manuscript, we focus on the fluid interfacial behavior at the junction of gas–liquid–solid phases and propose a robust and stable implementation algorithm to capture physical phenomena such as the spreading of droplet on substrates with different wettability, using the gas–liquid surface tension and the equilibrium contact angle as input parameters. We apply the algorithm under flat and curved substrates with different wettability, and the simulation results are in good agreement with the theoretical values, which verifies the accuracy, convergence, and applicability of the proposed droplet spreading model on different wettability substrates.
Construction of oriented Zn (002) facets via 3D conductive frameworks for enhanced performance in fiber-based zinc-ion batteries
Authors: Lei Hang , Zhou Xincheng , Chen Zhiheng , Liang Yongyin , Qiu Daping , Yang Xuelin , Wang Zilong , Mai Wenjie
Published: February 2025

Zinc-ion batteries (ZIBs) are poised to play a pivotal role in the future energy storage market. However, the undesired growth of zinc dendrites and the prevalence of side reactions pose significant challenges that limit the practical application of ZIBs. The sophisticated structural design and crystal orientation of the Zn anode can effectively suppress the occurrence of zinc dendrites and side reactions. Herein, a highly oriented Zn (002) lattice plane on 3D conductive frameworks [Zn/TiN nanotubes (NTs)] is designed to address uncontrolled dendrite growth, water-induced side reactions, and suboptimal Zn metal utilization in ZIBs. By leveraging an abundance of active sites for Zn2+ adsorption, minimal charge transfer resistance, and the controlled growth of Zn crystal facets, the reversibility and stability of ZIBs can be significantly enhanced during the Zn plating/stripping process. Remarkably, fiber-ZIBs based on Zn/TiN NTs exhibit a large specific capacity, long-term cycling durability, and excellent mechanical properties. This work proposes an approach to achieve highly reversible zinc anodes from the perspective of nanostructure and crystal orientation.
On projective stochastic-gradient type methods for solving large scale systems of nonlinear ill-posed equations: applications to machine learning
Authors: Rabelo J C , Saporito Y , Leitão A , Madureira A L
Published: February 2025

We propose and analyze a stochastic-gradient type method for solving systems of nonlinear ill-posed equations. The method considered here extends the stochastic gradient descent (SGD) type iteration introduced in Rabelo et al (2022 Inverse Problems
38 025003) for solving linear ill-posed systems. A distinctive feature of our method resides in the adaptive choice of the stepsize, which promotes a relaxed orthogonal projection of the current iterate onto a conveniently chosen convex set. This characteristic distinguish our method from other SGD type methods in the literature (where the stepsize is typically chosen a priori) and accounts for the faster convergence observed in the numerical experiments conducted in this manuscript. The convergence analysis discussed here includes: monotonicity and mean square convergence of the iteration error (exact data case), stability and semi-convergence (noisy data case). In the later case, our method is coupled with an a priori stopping rule. Numerical experiments are presented for two large scale nonlinear inverse problems in machine learning (both with real data): (i) we address, using neural networks, the big data problem of CO-concentration prediction considered in the above cited article; (ii) we tackle the classification problem for the MNIST database (http://yann.lecun.com/exdb/mnist/). Additionally, a parameter identification problem in a 3D elliptic PDE system is considered.
Ab initio investigations on the effect of pressure on the structural, electronic, optical and vibrational properties of SnS
Authors: Afzal Basha M I , Meher S R
Published: February 2025

SnS is a promising material for optoelectronic devices due to its earth abundance, low cost, and narrow band gap. In this study, we employed ab-initio density functional theory to investigate the structural, electronic, optical, and vibrational properties of SnS under varying hydrostatic pressures ranging from 0 to 16 GPa. Our results indicate that pressure significantly affects the lattice parameters, bond lengths, and bond angles. The onset of phase transition from α-SnS to β-SnS begins at  ∼  4 GPa which involves the continuous movement of atoms along the z-direction till 12 GPa. Orbital projected electronic density of states and band structure reveal that hybridization between S-3p, Sn-5p, and Sn-5s orbitals forms the valence band and conduction band edges. At 0 GPa, the indirect band gap is observed to be 0.69 eV, while the direct band gap is found to be 0.81 eV using generalized gradient approximation based exchange-correlation. However, the Hubbard U correction yield more accurate results of 1.07 eV and 1.20 eV for indirect and direct band gap respectively. The applied hydrostatic pressure reduces the band gap and induces a transition from a semiconducting to a metallic state at 10 GPa, as the valence band maxima and conduction band minima cross the Fermi level. Optical properties demonstrate a red-shift in the absorption coefficients with increasing pressure, reflecting changes in the electronic structure. Phonon calculations reveal a gap between acoustic and optical phonon branches, attributed to the mass difference between Sn and S atoms. The absence of imaginary modes across the Brillouin zone indicates the dynamical stability of α-SnS, at lower pressures (0 GPa, 3 GPa and 6 GPa). At higher pressures, the appearance of imaginary modes suggests the onset of material instability.
A graphene based multi-band antenna array for next generation IoT networks in THz spectrum
Authors: D Kaleeswaran , Kavitha R , Anchitaalagammai J V
Published: February 2025

A novel two-element MIMO (Multiple-Input-Multiple-Output) antenna with THz radiation for next-generation communication networks is designed and analysed in this paper. The antenna is constructed using graphene-thin films developed on a polyimide substrate. Each element in the MIMO scheme consists of a series-fed radiating element that is structurally modified to yield quad-band radiation centred around 0.18, 0.36, 0.54, and 0.68 THz, with fractional bandwidths (at a −10 dB reflection coefficient) of 13.2%, 10.3%, 8.62%, and 7.4%, respectively. The conventional square patch-based series-fed antenna array is loaded with bow-tie slots, and the transmission lines connecting the patch radiators are optimised to realize the four frequency bands with |S11| ≤ −10 dB. The electrical size of the designed antenna is 0.383λeff × 0.173λeff, and the inherent inter-port isolation exceeds 30 dB in all realised frequency bands. The antenna exhibits directional radiation characteristics, offering precision communication with directivity and gain greater than 8 dBi and 4 dBi, respectively. The realized MIMO antenna array is subjected to performance evaluation under different channel conditions. The analysis suggests that the proposed array is a promising space-saving solution with miniaturized configuration for next-generation wireless sensor networks with nano-sensors designed for Internet of Things (IoT) communications that demand high data rate, good throughput and improved coverage through enhanced antenna radiation properties such as gain and efficiency.
Predicting chaos in permanent magnet synchronous motor using dual reservoir interaction with high-order state reservoir computing
Authors: Ye Zuo Wei , Wei Du Qu
Published: February 2025

Permanent Magnet Synchronous Motor (PMSM), as core driving components of new energy vehicles, face significant challenges in performance and stability due to their complex chaotic behavior. Accurate prediction of chaotic behavior is crucial for the modeling and control of PMSM. This paper proposes a novel approach based on Reservoir Computing—the Dual Reservoir Interacting with High-Order State Reservoir Computing (DRI-HOSRC)—for predicting chaos in PMSM. By introducing high-order state expansion and the dual reservoir interaction mechanism, this method significantly enhances the ability to capture the nonlinear dynamic characteristics of PMSM. Experimental results show that the proposed DRI-HOSRC model outperforms traditional methods in terms of both prediction accuracy and time range, enabling a more precise capture of the system’s complex chaotic features. These results validate the model’s potential for application in PMSM, providing an innovative solution for accurate forecasting. The research also demonstrates the advantages of the dual reservoir interacting with high-order state reservoir model in nonlinear dynamics modeling and offers an effective pathway for long-term predictions of complex systems.
Probing the Cosmological Principle with weak lensing shear
Authors: Adam James , Maartens Roy , Larena Julien , Clarkson Chris
Published: February 2025

The Cosmological Principle is a cornerstone of the standard model of cosmology and shapes how we view the Universe and our place within it. It is imperative, then, to devise multiple observational tests which can identify and quantify possible violations of this foundational principle. One possible method of probing large-scale anisotropies involves the use of weak gravitational lensing. We revisit this approach in order to analyse the imprint of late-time anisotropic expansion on cosmic shear. We show that the cross-correlation of shear E- and B-modes on large scales can be used to constrain the magnitude (and possibly direction) of anisotropic expansion. We estimate the signal to noise for multipoles 10 ≲ ℓ ≲ 100 that is achievable by a Euclid-like survey. Our findings suggest that such a survey could detect the E-B signal for reasonable values of the late-time anisotropy parameter.
On the rework and development of new Geant4 Cherenkov models
Authors: Đurnić B. , Potylitsyn A. , Bogdanov A. , Gogolev S.
Published: February 2025

A recent experiment showed that a Cherenkov radiation
spectrum from thin radiators with a wavelength-dependent refractive
index could transform into quasi-monochromatic spectral
lines. Simulations based on the standard Geant4 toolkit could not
correctly describe the experimental results because Geant4 uses the
traditional Frank-Tamm theory developed for an ideal (infinitely
thick) radiator. Because of that, we endeavor to present a new way
of utilizing Cherenkov radiation using newly developed Geant4 models
and comparing simulation results with the experimental ones. Now,
one can analyze quasi-monochromatic Cherenkov spectral lines using
Geant4, which is a significant milestone for investigating the
possibilities of this technique. Also, this paper should be used as
a text to help people understand the Cherenkov process in Geant4 and
what one can expect from various models.
A cell-based drug screening assay on a centrifugal platform
Authors: Shih Chia-Tse , Guo Huan-Jun , Shih Chih-Hsin , Li Yi-Chen Ethan
Published: February 2025

Drug screening is an indispensable procedure in drug development and pharmaceutical research. For cell-based drug testing, cells were treated with compounds at different concentrations, and their responses were measured to assess the compounds’ effects on cellular behavior. A concentration gradient test creates a growth environment with different compound concentrations for cultured cells, facilitating faster determination of the compound concentration’s effect on cellular responses. However, most concentration gradient tests on cell cultures were carried out manually, which is labor-intensive and time-consuming. Microfluidic technology enables drug screening to be conducted in microstructures, which not only improves efficiency and sensitivity but also reduces reagent usage and operating time. Centrifugal microfluidics utilizes the rotation of a disk platform to perform complex fluid functions such as pumping, metering, and mixing. The complete process can be carried out with a low-cost motor without the need for an expensive pumping system. In this work, a centrifugal platform for drug screening is presented. The microfluidic platform can be divided into two parts. The inner disk features branch structures designed to establish a concentration gradient for cell growth. The outer ring contains fluidics for cell culturing, which can discharge the waste fluid when the nutrient is exhausted and replenish the new culture medium by spinning the platform. In conclusion, the proposed centrifugal platform can provide a rapid generation of the concentration gradients and automate the operation of cell culturing. It provides an efficient and low-cost platform for drug screening.
Electronic and structural properties of atomically thin metallenes
Authors: Abidi Kameyab Raza , Koskinen Pekka
Published: February 2025

Although metallic elements favor three-dimensional (3D) geometries due to their isotropic, metallic bonding, experiments have reported metals also with two-dimensional allotropes, the so-called metallenes. And while bulk metals’ electronic and structural properties are well known, the corresponding knowledge for atomically thin metallenes remains scattered. Therefore, in this work, we use density-functional theory to investigate the electronic and structural properties of 45 elemental metals with honeycomb, square, and hexagonal lattices, along with their buckled counterparts, resulting in a comprehensive catalog of 270 metallenes with their properties. We systematically present their structural, energetic, and electronic structure properties and discuss similarities and differences compared to their 3D counterparts. As a result, simple and noble metals exhibit similar characteristics and lack buckled hexagonal lattice. Apart from scattered exceptions, the trends in several properties, such as bond lengths, cohesion energies, and projected densities of states, are governed by coordination numbers and exhibit systematic patterns. This systematic reporting provides a necessary reference for the selection and categorization of metallenes for further experimental efforts to develop them for catalytic, sensing, plasmonic, and nanoelectronics applications.
Validating large-scale quantum machine learning: efficient simulation of quantum support vector machines using tensor networks
Authors: Chen Kuan-Cheng , Li Tai-Yue , Wang Yun-Yuan , See Simon , Wang Chun-Chieh , Wille Robert , Chen Nan-Yow , Yang An-Cheng , Lin Chun-Yu
Published: February 2025

We present an efficient tensor-network-based approach for simulating large-scale quantum circuits exemplified by quantum support vector machines (QSVMs). Experimentally, leveraging the cuTensorNet library on multiple GPUs, our method effectively reduces the exponential runtime growth to near-quadratic scaling with respect to the number of qubits in practical scenarios. Traditional state-vector simulations become computationally infeasible beyond approximately 50 qubits; in contrast, our simulator successfully handles QSVMs with up to 784 qubits, executing simulations within seconds on a single high-performance GPU. Furthermore, utilizing the message passing interface for multi-GPU environments, our method demonstrates strong linear scalability, effectively decreasing computation time as dataset sizes increase. We validate our framework using the MNIST and Fashion MNIST datasets, achieving successful multiclass classification and highlighting the potential of QSVMs for high-dimensional data analysis. By integrating tensor-network techniques with advanced high-performance computing resources, this work demonstrates both the feasibility and scalability of simulating large-qubit quantum machine learning models, providing a valuable validation tool within the emerging Quantum-HPC ecosystem.
Learning group invariant Calabi–Yau metrics by fundamental domain projections
Authors: Hendi Yacoub , Larfors Magdalena , Walden Moritz
Published: February 2025

We present new invariant machine learning models that approximate the Ricci-flat metric on Calabi–Yau (CY) manifolds with discrete symmetries. We accomplish this by combining state of the art models for predicting such metrics, based on the so-called φ-model of the cymetric package, with non-trainable, G-invariant, canonicalization layers that project the φ-model’s input data (i.e. points sampled from the CY geometry) to the fundamental domain of a given symmetry group G. These G-invariant layers are easy to concatenate, provided one compatibility condition is fulfilled, and combine well with both standard and spectral versions of the φ-model. Through experiments on different CY geometries, we find that, for fixed point sample size and training time, canonicalized models give slightly more accurate metric approximations than the standard φ-model. On highly symmetric spaces, we also observe significantly faster convergence upon training. The method may also be used to compute the Ricci-flat metric on smooth CY quotients. We demonstrate this aspect by experiments on a smooth

Z

5
2

quotient of a 5-parameter quintic CY manifold.
Enhanced feature encoding and classification on distributed quantum hardware
Authors: Moretti R , Giachero A , Radescu V , Grossi M
Published: February 2025

The steady progress of quantum hardware is motivating the search for novel quantum algorithm optimization strategies for near-term, real-world applications. In this study, we propose a novel feature map optimization strategy for quantum support vector machines (QSVMs), designed to enhance binary classification while taking into account backend-specific parameters, including qubit connectivity, native gate sets, and circuit depth, which are critical factors in noisy intermediate scale quantum devices. The dataset we utilised belongs to the neutrino physics domain, with applications in the search for neutrinoless double beta decay. A key contribution of this work is the parallelization of the classification task to commercially available superconducting quantum hardware to speed up the genetic search processes. The study was carried out by partitioning each quantum processing unit (QPU) into several sub-units with the same topology to implement individual QSVM instances. We conducted parallelization experiments with three IBM backends with more than 100 qubits, ranking the sub-units based on their susceptibility to noise. Data-driven simulations show how, under certain restrictions, parallelized genetic optimization can occur with the tested devices when retaining the top 20% ranked sub-units in the QPU.
Performance enhancement of passive and low-consumption cooling strategies in tropical climates by integrating control systems: a case study in Panama
Authors: Chen Austin Miguel , Salado Rodrigo
Published: February 2025

Countries in tropical climate systems adhere to higher cooling needs than other latitudes; thus, climate change and population growth urge sustainable cooling strategies. Bioclimatic principles provide a range of passive solutions at the buildings’ envelope and surroundings, where increasing air velocity near occupants could provide thermal comfort even at high temperatures. Such passive strategies combined with control strategies may enhance performance and reduce energy consumption. Thus, this work reviews passive and low-consumption strategies implemented in tropical countries to highlight research interests and trends and presents a case study in a humid tropical developing country such as Panama. Nine cases are studied with different low-consumption solutions to find optimal combinations through simple control strategies to reduce overall energy consumption. The performance of such cases is assessed via energy intensity, relative annual indoor temperature to comfort limits, and the predictive mean vote.
Contextualising a multi-dimensional perspective on energy poverty for South Africa’s just energy transition: a systematic literature review
Authors: Tshabalala Thandeka , Davies Megan , Mohlakoana Nthabiseng
Published: February 2025

Energy poverty is a multifaceted and urgent issue in the Global South, especially in South Africa, where, despite an electrification rate exceeding 90%, a substantial 40% of the population still experiences energy poverty. This paper presents a systematic review of literature on energy poverty in South Africa, covering the period from 1994 to 2023. The review identifies eleven key themes that offer a multi-dimensional perspective on such energy poverty. It offers insights into addressing critical issues for advancing an equitable and just energy system. Understanding the extent and nature of energy poverty could facilitate a deeper understanding of (in)justices entrenched in South Africa’s socio-technical energy system, for policymakers, practitioners and experts alike. Energy justice is employed as an analytical framework to examine the implications of energy poverty through the lenses of restorative, distributive, procedural, and recognitional justice. The analysis seeks to contribute to South Africa’s just transition (JT) Framework, which currently addresses energy poverty primarily as a matter of restorative justice. South Africa’s just energy transition cannot be achieved in an inclusive and transformative manner without accounting for multifaceted dynamics at the household level; here, energy poverty serves to bring about a more intersectional focus on the justice dimensions inherent in energy transitions. The findings underscore the need to address energy poverty at the household level, where it intersects with broader socio-technical dynamics. Such a multi-dimensional perspective on energy poverty in South Africa could help to inform targeted policies and initiatives to meet the specific needs of energy-poor households, while broader socio-technical changes are accelerated as part of the energy transition, thus more strongly meeting the goals spelled out in the JT Framework.
Duplex sequencing identifies unique characteristics of ENU-induced mutations in male mouse germ cells
Authors: LeBlanc Danielle P M , Zhou Gu , Williams Andrew , Meier Matthew J , Valentine Charles C , Salk Jesse J , Yauk Carole L , Marchetti Francesco
Published: February 2025

Germ cell mutagenicity testing is increasingly required for chemical risk assessment. Duplex Sequencing (DS) is rapidly gaining acceptance as a method to assess in vivo mutagenesis, and as a valid alternative to transgenic rodent (TGR) mutation models such as the MutaMouse. We used a DS panel of 20 genomic targets and the TGR assay to measure mutations in the germ cells of MutaMouse males exposed to 0, 1, 2, or 5 mg/kg N-ethyl-N-nitrosourea (ENU) for 28 days. Germ cells from the seminiferous tubules were collected 28 days post-exposure. The TGR assay showed a significant increase in mutant frequencies at the high (p < 0.001) and medium (p = 0.01) ENU doses relative to controls, while DS revealed a significant increase (p < 0.001) in ENU-induced mutations only at the high-dose. DS mutation frequencies were lower in genic than in intergenic targets, suggesting a protective role for transcription-coupled repair. Interestingly, we observed several unique germ cell characteristics with respect to DS data from rodent somatic tissues: 1) larger inter-animal variability in clonally expanded mutations that affects the ability to detect significant increases in mutation frequency; 2) a target on chromosome 2 showing much higher susceptibility to spontaneous and chemical-induced mutagenesis than other targets; and 3) a mutation spectrum consistent with that observed in the offspring of ENU-treated males but not with the spectrum in bone marrow of directly-exposed males. These results suggest that DS is a promising approach for characterizing germ cell mutagenesis and that mutagenic mechanisms operating in germ cells differ from those in somatic tissues.
Testable implications of outcome-independent missingness not at random in covariates
Authors: Sjölander A , Hägg S
Published: February 2025

A common aim of empirical research is to regress an outcome on a set of covariates, when some covariates are subject to missingness. If the probability of missingness is conditionally independent of the outcome, given the covariates, then a complete-case analysis is unbiased for parameters conditional on covariates. We derive all testable constraints that such outcome-independent missingness not at random implies on the observed data distribution, for settings where both the outcome and covariates are categorical. By assessing if these constraints are violated for a particular observed data distribution, the analyst can infer whether the assumption of outcome-independent missingness not at random is violated for that distribution. The constraints are formulated implicitly, in terms of consistency requirements on certain linear equation systems. We also derive explicit inequality constraints that are more easily assessable, but also more permissive than the implicit constraints.
18F-FDG PET or PET/CT in detecting high-grade transformation of chronic lymphocytic leukaemia and indolent lymphomas: A systematic review and meta-analysis
Authors: Lee Osher N Y , Kuruvilla John , Hodgson David C , Veit-Haibach Patrick , Metser Ur
Published: February 2025

Objectives

To evaluate the diagnostic accuracy of 18F-FDG PET or PET/CT in detecting histological transformation (HT) of indolent lymphomas.

Methods

A systematic search of articles up to July 2024 was performed in Embase and Medline. Eligible studies included adults with histologically proven indolent lymphoma, 18F-FDG PET or PET/CT as the index test, and sufficient data to assess diagnostic performance. Summary receiver operating characteristic curves were plotted using a bivariate model to estimate diagnostic accuracy with area under the curve (AUC).

Results

Fifteen studies with 1,307 participants were included. Ten studies assessed PET ability to detect Richter’s transformation, and 5 studies focussed on HT in follicular lymphoma and other subtypes. A meta-analysis of the former showed pooled sensitivity of 0.90 (95% CI, 0.84–0.93) and specificity of 0.54 (95% CI, 0.28–0.77) when using a SUVmax threshold of around 5. AUC was 0.89. Pooled sensitivity was 0.74 (95% CI, 0.54–0.87) and specificity was 0.84 (95% CI, 0.67–0.93) when using a SUVmax threshold of around 10. AUC was 0.84. For detecting HT in follicular lymphoma, thresholds were found higher than those for Richter’s transformation.

Conclusions

18F-FDG PET or PET/CT demonstrates good diagnostic accuracy to detect Richter’s transformation, best when employing SUVmax ≥ 5. SUVmax thresholds may be limited in discriminating follicular lymphoma from HT, and alternatives should be sought.

Advances in knowledge

If biopsy is feasible, SUVmax ≥ 5 can guide biopsy in patients with clinically suspicious Richter’s transformation. If biopsy is infeasible, SUVmax ≥ 10 can better identify HT and guide patient management.
The inferior fronto-occipital fasciculus: bridging phylogeny, ontogeny and functional anatomy
Authors: Giampiccolo Davide , Herbet Guillaume , Duffau Hugues
Published: February 2025

The inferior-fronto-occipital fasciculus is a long-range white matter tract that connects the prefrontal cortex with parietal, posterior temporal and occipital cortices. First identified in the nineteenth century through the pioneering studies of Mayo and Meynert using blunt dissection, its anatomy and function remain contentious topics. Structurally, its projections are well-documented in human blunt dissection and tractography literature, yet its existence has been questioned by tract-tracing studies in macaques. Functionally, while traditional results from direct white matter stimulation during awake surgery suggested a contribution to language, recent evidence from stimulation and lesion data may indicate a broader role in executive control, extending to attention, motor cognition, memory, reading, emotion recognition, and theory of mind.

This review begins by examining anatomical evidence suggesting that the inferior fronto-occipital fasciculus evolved in non-human primates to connect temporal and occipital cortices to prefrontal regions involved in context-dependent selection of visual features for action. We then integrate developmental, electrophysiological, functional and anatomical evidence for the human inferior fronto-occipital fasciculus to propose it has a similar role in manipulation of visual features in our species—particularly when inhibition of overriding but task-irrelevant stimuli is required to prioritize a second, task-relevant stimulus.

Next, we introduce a graded model in which dorsal (orbitofrontal, superior and middle frontal to precuneal, angular and supero-occipital projections) and ventral (inferior frontal to posterotemporal, basal temporal and infero-occipital) projections of the inferior fronto-occipital fasciculus support perceptual or conceptual control of visual representations for action, respectively. Leveraging this model, we address controversies in the current literature regarding language, motor cognition, attention and emotion under the unifying view of cognitive control. Finally, we discuss surgical implications for this model and its impact on predicting and preventing neurological deficits in neurosurgery.
Ventromedial prefrontal cortex lesions disrupt learning to reward others
Authors: Gueguen Margot , Cutler Jo , Drew Daniel , Apps Matthew A J , Jeyaretna Deva Sanjeeva , Husain Masud , Manohar Sanjay G , Lockwood Patricia L
Published: February 2025

Reinforcement learning is a fundamental process for how humans and other animals attain rewards for themselves. However, to act prosocially, we must also learn how our choices reward others. The ventromedial prefrontal cortex has been independently linked to reinforcement learning and prosocial behaviour, yet its causal impact on prosocial reinforcement learning and the roles of its multiple subregions remain unknown.

Here, a large group of adults with rare focal ventromedial prefrontal cortex damage (n=28), and two carefully age- and gender-matched control groups (lesions elsewhere, n=21; healthy controls, n=124) completed a reinforcement learning task where they learnt to win rewards for another person (prosocial), for themselves (self), or in a control condition where participants saw points but they were not translated into rewards for either individual (no one, control condition) on separate trials.

A novel computational model which incorporated separate learning rates for positive and negative prediction errors best explained behaviour in all groups. Importantly, compared to both control groups, patients with ventromedial prefrontal cortex damage were less accurate and had lower learning rates from positive prediction errors when rewarding another person relative to when no one benefitted, and higher learning rates for negative prediction errors when learning for others relative to self. Unlike controls, ventromedial prefrontal cortex lesion patients also showed a reduced self-benefitting advantage. They were equally accurate and learnt at a similar rate from positive prediction errors for self and neither individual. Strikingly, voxel-based lesion-symptom mapping revealed that damage to subgenual anterior cingulate cortex and anterior cingulate cortex gyrus specifically disrupted prosocial reinforcement learning.

These findings highlight the importance of ventromedial prefrontal cortex integrity for multiple aspects of reinforcement learning, with damage to subgenual anterior cingulate cortex and anterior cingulate cortex gyrus critical for learning to reward others.
Machine learning reveals connections between preclinical type 2 diabetes subtypes and brain health
Authors: Yi Fan , Yuan Jing , Han Fei , Somekh Judith , Peleg Mor , Wu Fei , Jia Zhilong , Zhu Yi-Cheng , Huang Zhengxing
Published: February 2025

Previous research has established Type 2 Diabetes Mellitus as a significant risk factor for various disorders, adversely impacting human health. While evidence increasingly links type 2 diabetes to cognitive impairment and brain disorders, understanding the causal effects of its preclinical stage on brain health is yet to be fully known. This knowledge gap hinders advancements in screening and preventing neurological and psychiatric diseases. To address this gap, we employed a robust machine learning algorithm (Subtype and Stage Inference, SuStaIn) with cross-sectional clinical data from the UK Biobank (20,277 preclinical type 2 diabetes participants and 20,277 controls) to identify underlying subtypes and stages for preclinical type 2 diabetes.

Our analysis revealed one subtype distinguished by elevated circulating leptin levels and decreased leptin receptor levels, coupled with increased body mass index, diminished lipid metabolism, and heightened susceptibility to psychiatric conditions such as anxiety disorder, depression disorder, and bipolar disorder. Conversely, individuals in the second subtype manifested typical abnormalities in glucose metabolism, including rising glucose and hemoglobin A1c levels, with observed correlations with neurodegenerative disorders. Over ten-year follow-up of these individuals revealed differential declines in brain health and significant clinical outcome disparities between subtypes. The first subtype exhibited a faster progression and higher risk for psychiatric conditions, while the second subtype was associated with more severe progression in Alzheimer’s disease, Parkinson’s disease, and a faster progression to type 2 diabetes. Our findings highlight that monitoring and addressing the brain health needs of individuals in the preclinical stage of type 2 diabetes is imperative.
Integrated primary and secondary care optimises the management of people with CKD - The LUCID project
Authors: Major Rupert W , Lakhani Niraj , Ahmed Yaseen , Atkin Jade , Baines Richard , Balment Rose , Cheung Chee Kay , Graham-Brown Matthew P , Ellwood Claire , Harding Laura , Iyasere Osasuyi , Jesa Tracy , Jesus-Silva Jorge , Jinadu Yusuf , Khalid Arshad , Khatri Jibran , Makkeyah Yahya , Martinez Maria , Mather Helen , Medcalf James F , Moore Kirk , Ogle James , Oseya Eleanor , Patel Dipesh , Patel Reena , Pollard Tracy , Priestman William , Rastogi Amit , Sanganee Nil , Shaffu Mark , Steiner Michael , Than Tun , Xu Gang , Rizvi Fahad , Burton James O
Published: February 2025

Early diagnosis, risk stratification and medication optimisation are essential to improve the management of chronic kidney disease and other long-term conditions. The introduction of Integrated Care Systems in England provides the opportunity to revolutionise the management of these conditions. Annual NHS kidney disease costs are ∼£6.4 billion.

We designed, piloted and implemented at scale an Integrated Care System-level virtual care programme for chronic kidney disease, the ‘Leicester, Leicestershire, and Rutland Chronic Kidney Disease Integrated Care Delivery Project’ (LUCID), based on the principles of patient and professional education, early disease identification, medicines optimisation and disease surveillance.

In April 2022 virtual multi-disciplinary meetings were piloted in Leicester, Leicestershire and Rutland, UK. Since April 2023 virtual MDT meetings have been available to all general practices in Leicester, Leicestershire and Rutland representing a population of approximately 1.2 million people . As of 31st March 2024, general practices representing an estimated population of 700 000 (58.3%) were participating in the LUCID programme. 1085 consultations took place for 821 patients, 590 (54.4%) of which were medicines optimisation consultations.

LUCID may represent an efficient and cost-effective model to deliver patient and professional education, medicine optimisation and risk stratification for people living with CKD at an Integrated Care System-wide population level. This model may be adaptable for other long-term physical and mental health conditions.
May Measurement Month 2022: an analysis of blood pressure screening results from Kenya
Authors: Mbau Lilian , Samia Bernard , Nguchu Hellen , Onyango Elizabeth , Beaney Thomas , Kerr Gabriele , Poulter Neil R , Ogola Elijah
Published: February 2025

Hypertension is the largest contributor to the burden of disease globally, but awareness, treatment and control rates remain low. In response to this, the annual global May Measurement Month campaign was initiated by the International Society of Hypertension in 2017. This paper summarizes the results of the 2022 MMM campaign in Kenya.

Adults aged ≥ 18 years were recruited across 8 counties in Kenya. Three seated blood pressure (BP) readings were taken for each participant, along with completion of a questionnaire on demographics, lifestyle factors, and comorbidities. Hypertension was defined as a systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg or being on antihypertensive medication. Controlled BP was defined as being on antihypertensive medication with a BP <140/90 mmHg. Multiple imputation was used to estimate any missing BP readings. In total, 9605 were screened, with a mean age of 43.0 years, 43.9% females and 3406 (35.5%) for the first time. Of all participants, 3167 (33.0%) had hypertension, of whom 982 (31.0%) were aware, and 936 (29.6%) were on antihypertensive medication. Of those on antihypertensive medication, 346 (37.0%) had controlled BP, and of all participants with hypertension, 10.9% had controlled BP. Of those on medication, the majority were on two (517; 55.2%) anti-hypertensive medication classes.

The campaign identified significant numbers of participants with either untreated or inadequately treated hypertension. Hypertension control remains alarmingly low necessitating critical evaluation of possible contributors including awareness and treatment optimization.
May Measurement Month 2022: an analysis of blood pressure screening results in Greece
Authors: Menti Ariadni , Kollias Anastasios , Milionis Haralampos , Liontos Angelos , Gkaliagkousi Eugenia , Kotsis Vasileios , Savopoulos Christos , Triantafyllou Areti , Zarifis Ioannis , Papadakis John A , Marketou Maria , Nikitas George , Maragkoudakis Spyridon , Makaris Emmanouil , Krokidis Xenophon , Goumenos Dimitrios , Papachristou Evangelos , Sarakis Vasilios , Lanaras Leonidas , Grassos Charalampos , Kalaitzidis Rigas G , Kallistratos Manolis S , Katsi Vasiliki , Konstantinidis Dimitrios , Kyriakoulis Konstantinos G , Makris Thomas , Manios Efstathios , Manolis Athanasios , Papadopoulos Dimitrios , Pikilidou Maria I , Protogerou Athanasios , Sarafidis Pantelis , Theodorakopoulou Marieta , Zebekakis Pantelis , Tsioufis Konstantinos , Doumas Michael , Stergiou George S
Published: February 2025

Hypertension remains a major public health challenge with inadequate control globally. The May Measurement Month (MMM) global survey initiated by the International Society of Hypertension (ISH) was implemented in Greece in 2022 aiming to raise hypertension awareness and control.

Adult volunteers were recruited through opportunistic screening in 11 urban areas. Information on medical history and three sitting blood pressure (BP) measurements were obtained using validated automated upper-arm devices and the data were submitted online through a custom-designed app of the global MMM survey. Hypertension was defined as average systolic BP at least 140 mmHg and/or diastolic 90 mmHg, or self-reported use of drugs for hypertension. A total of 6353 individuals were included (mean age 54.8±16.2 years, 49% men, 30.5% current smokers, 11.5% had diabetes, 5.1% myocardial infarction). The prevalence of hypertension (42.6%) was higher in men (48.8%) and in older individuals (74%). Among individuals with hypertension, 27.5% were unaware of their diagnosis, 22.2% were treated but uncontrolled (≥140 mmHg systolic and/or ≥90 mmHg diastolic BP) and 47.9% were treated and controlled. Among treated hypertensives, 58.2% were on monotherapy and at least one-third of them were uncontrolled.

The prevalence of hypertension in Greece seems to be high, and is often undiagnosed, untreated, and uncontrolled. Public health initiatives and campaigns aiming at improving hypertension diagnosis and control need to be implemented.
Identification of CXCR4 inhibitory activity in natural compounds using cheminformatics-guided machine learning algorithms
Authors: Tripathi Rahul , Kumar Pravir
Published: February 2025

Neurodegenerative disorders are characterised by progressive damage to neurons that leads to cognitive impairment and motor dysfunction. Current treatment options focus only on symptom management and palliative care, without addressing their root cause. In our previous study, we reported the upregulation of the CXC motif chemokine receptor 4 (CXCR4), in Alzheimer’s disease (ad) and Parkinson’s disease (PD). We reached this conclusion by analysing gene expression patterns of ad and PD patients, compared to healthy individuals of similar age. We used RNA sequencing data from Gene Expression Omnibus to carry out this analysis. Herein, we aim to identify natural compounds that have potential inhibitory activity against CXCR4 through cheminformatics-guided machine learning, to aid drug discovery for neurodegenerative disorders, especially ad and PD. Natural compounds are gaining prominence in the treatment of neurodegenerative disorders due to their biocompatibility and potential neuroprotective properties, including their ability to modulate CXCR4 expression. Recent advances in artificial intelligence (AI) and machine learning (ML) algorithms have opened new avenues for drug discovery research across various therapeutic areas, including neurodegenerative disorders. We aim to produce an ML model using cheminformatics-guided machine learning algorithms using data of compounds with known CXCR4 activity, retrieved from the Binding Database, to analyse various physicochemical attributes of natural compounds obtained from the COCONUT Database and predict their inhibitory activity against CXCR4.

Insight Box This work extends our previous study published in Integrative Biology (DOI: 10.1093/intbio/zyad012). We aim to demonstrate the effectiveness of AI and ML in identifying potential treatment options for Alzheimer’s and Parkinson’s diseases. By analysing vast amounts of data and identifying patterns that may not be apparent to human researchers, AI-powered systems can provide valuable insight into potential treatment options that may have been overlooked through traditional research methods. Our study underscores the significance of interdisciplinary collaboration between computational and experimental scientists in drug discovery and in developing a robust pipeline to identify potential leads for drug development.
Marine spatial planning as a potential practical approach to manage setiu wetland as an ecologically sensitive area
Authors: Lua W Y , Aziz N , Idris I , Rahman M A A , Ghazali F , Talaat W I A W
Published: February 2025

Using Marine Spatial Planning (MSP) as a management tool for long-term sustainability is relatively new in Malaysia. This paper addresses and discusses the potential MSP has to manage Setiu Wetland as an ecologically sensitive area. Setiu Wetland is the largest natural wetland in the east coast of Peninsular Malaysia. The enabling environment for the adoption of MSP in Setiu Wetland is explored to foresee potential in managing the wetland’s conflicting uses. Located in Terengganu, the wetland provides various ecosystem services to humans, birds, reptiles, mammals, invertebrates, and bivalves. The Setiu Wetland ‘s coastal and marine natural ecosystems provide various benefits to the well-being of the population there. However, the human population growth in Setiu Wetland and the surrounding areas is increasingly contributing to the natural resource exploitation in this ecologically sensitive area causing detrimental effects on the wetland ecosystem. This paper aims to review the threats to the ecosystems in Setiu Wetland from multiple development activities and existing uses to examine the potential implementation of MSP in managing the wetland as an ecologically sensitive area. In conclusion, this study proposes the adoption of MSP as the best management process to protect the natural habitat and preserve the ecological functions of the wetland without compromising the local communities’ livelihood.