bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced tunneling electroresistance in ferroelectric tunnel junctions achieved through dual interface control
Authors: Ma Zhijun , Zhang Qi , Zhang Zeyu , Guo Yizhong , Ruan Yongqi , Wang Zhiwei , Zhou Peng , Lord Mikayla , Luo Ji , Liu Shuai , Valanoor Nagarajan , Zhang Tianjin
Published: December 2024

Interface engineering in ferroelectric tunnel junctions is a fertile playground to realize large tunneling electroresistance (TER) ratios. Here, the TER effect of Pt/La0.8Ca0.2MnO3 (LCMO)/BaTiO3 (BTO)/Nb: SrTiO3 (NSTO) ferroelectric tunnel junctions (FTJs) is investigated. It is found that the TER is enhanced by 2 orders of magnitude for the FTJ with a 0.5 nm (∼one unit cell) LCMO layer, as compared to its counterpart without LCMO. The observed effect is attributed to the NSTO/BTO and LCMO/BTO interfaces, both of which are responsive to ferroelectric polarization. These interfaces exhibit metallic or insulating behavior synchronously depending on the direction of the polarization in the BTO layer, resulting from the ferroelectric electric field effect and metal–insulator phase transition, respectively. This switching action with polarization reversal significantly increases the contrast in electrical resistance between the high resistance state (OFF state) and the low resistance state (ON state), therefore triggering a large TER. The increase in LCMO thickness (from 0.5 to 1 and 2 nm) leads to the decrease in TER, owing to the decreased barrier height/width at the NSTO/BTO interface, as revealed by the electron transport mechanism of Fowler–Nordheim (FN) tunneling.
Comprehensive modeling of a deflector jet pressure servo valve and analysis of key influences on the front stage
Authors: Liang Na , Yuan Zhaohui , Jiang Ruosong , Kang Jian , Zhang Jianrui
Published: December 2024

The deflector jet pressure servo valve (DJPSV), a critical component of the aircraft brake servo system, requires a precise foundational model for performance analysis, optimization, and enhancement. However, the complexity of the jet process within the V-groove of the deflector plate presents challenges for accurate mathematical modeling. To address this issue, the paper takes the DJPSV as the research object, carries out detailed mathematical modeling of its components, analyzes the influencing factors of the performance of the key component—the front stage—and optimizes the design of the key factors. First, integrating FLUENT velocity field analysis, this study proposes a novel perspective to rationally simplify and parametrically model the injection process in 3D space. Subsequently, a systematic deduction of the mathematical model for DJPSV is undertaken. Employing the AMESim platform and the secondary development module AMESet, a comprehensive simulation model is constructed, facilitating the study of static-dynamic valve characteristics. Additionally, utilizing the Morris theory and an intelligent algorithm, sensitivity analysis, and structural optimization on the critical component, the pre-stage. The results reveal that the width of the receiving diverter wedge (M), the width of the V-groove outlet (b1), and the distance from the V-groove outlet to the receiving diverter wedge (h) exert the most significant influence on the differential pressure of the pre-stage, which are the key parameters affecting the output differential pressure of the pre-stage. The experiment verifies the accuracy of the simulation model, offering a vital theoretical foundation for valve development and related areas.
Response function measurement for a non-destructive gas-sheet beam profile monitor
Authors: Yamada Ippei , Kamiya Junichiro
Published: December 2024

A gas-sheet beam profile monitor enabling non-destructive two-dimensional profile measurements of a high-intensity beam by capturing an image of a beam-induced fluorescence was developed. For quantitative profile measurements, the monitor’s response function comprising, e.g., the gas sheet density distribution and the detector’s sensitivity distributions must be experimentally clarified because the monitor output is a converted profile with the response function. A response function measurement method was devised based on the beam-profile-measurement method formula of the monitor. The response function was obtained by injecting a thin electron beam into the developed monitor and scanning its center position in transverse. The measured response function was evaluated by the J-PARC 3 MeV, 60 mA H− beam profile measurement. The 2-D beam profile was successfully reconstructed with the measured response function within the 2.74% residual of the least-squares method and 6.01% experimental statistic deviation. The projected 1-D profiles agreed well with those measured using a wire-scanning-type profile monitor.
Designs for photovoltaic glass surface texturing to improve transmittance and minimize glare
Authors: Tan Yangping , Sun Xilian , Tang Changxin , Zhou Lang , Wei Xiuqin , Zhang Jikui , Xia Wei , Liu Yaokai , Li Zhiwei
Published: December 2024

Planar glass cover creates optical reflection loss and glare, which is harmful to energy efficiency and effective operation of PV modules, especially at larger angles of incidence (AOIs). Textured surfaces can reduce reflections and glare intensity. In this work, three textured glass surfaces are described and simulated numerically over a wide range of AOIs. The anti-reflection effect and light trapping effect are provided to analyze the transmission gain across a wide range of AOIs. The reflection times is proposed to assess the anti-glare effect of the textured surfaces. It is found that the hexagonal array structured surface exhibits the highest transmission gain and anti-glare effect. The optimized hexagonal array structured surface could improve the average transmission by ∼5% relative to planar surface for AOIs of 0°–80°. In addition, the reflection times is doubled, which helps to diminish the reflection and glare intensity.
Disentangling collective coupling in vibrational polaritons with double quantum coherence spectroscopy
Authors: Schnappinger Thomas , Falvo Cyril , Kowalewski Markus
Published: December 2024

Vibrational polaritons are formed by strong coupling of molecular vibrations and photon modes in an optical cavity. Experiments have demonstrated that vibrational strong coupling can change molecular properties and even affect chemical reactivity. However, the interactions in a molecular ensemble are complex, and the exact mechanisms that lead to modifications are not fully understood yet. We simulate two-dimensional infrared spectra of molecular vibrational polaritons based on the double quantum coherence technique to gain further insight into the complex many-body structure of these hybrid light–matter states. Double quantum coherence uniquely resolves the excitation of hybrid light–matter polaritons and allows one to directly probe the anharmonicities of the resulting states. By combining the cavity Born–Oppenheimer Hartree–Fock ansatz with a full quantum dynamics simulation of the corresponding eigenstates, we go beyond simplified model systems. This allows us to study the influence of self-polarization and the response of the electronic structure to the cavity interaction on the spectral features even beyond the single-molecule case.
Physically interpretable performance metrics for clustering
Authors: Mondal Kinjal , Klauda Jeffery B.
Published: December 2024

Clustering is a type of machine learning technique, which is used to group huge amounts of data based on their similarity into separate groups or clusters. Clustering is a very important task that is nowadays used to analyze the huge and diverse amount of data coming out of molecular dynamics (MD) simulations. Typically, the data from the MD simulations in terms of their various frames in the trajectory are clustered into different groups and a representative element from each group is studied separately. Now, a very important question coming in this process is: what is the quality of the clusters that are obtained? There are several performance metrics that are available in the literature such as the silhouette index and the Davies–Bouldin Index that are often used to analyze the quality of clustering. However, most of these metrics focus on the overlap or the similarity of the clusters in the reduced dimension that is used for clustering and do not focus on the physically important properties or the parameters of the system. To address this issue, we have developed two physically interpretable scoring metrics that focus on the physical parameters of the system that we are analyzing. We have used and tested our algorithm on three different systems: (1) Ising model, (2) peptide folding and unfolding of WT HP35, (3) a protein–ligand trajectory of an enzyme and substrate, and (4) a protein–ligand dissociated trajectory. We show that the scoring metrics provide us clusters that match with our physical intuition about the systems.
Nonlinear optical properties of CVD-synthesized CuS crystals
Authors: Suleiman Abdulsalam Aji , Rahighi Reza , Parsi Amir , Kasirga Talip Serkan
Published: December 2024

Copper sulfide (CuS) is a material of growing interest due to its distinctive electronic, optical, and catalytic properties. In this study, we successfully synthesized ultrathin CuS crystals, with thicknesses as low as 14 nm and lateral dimensions reaching 60 μm, using a single-step chemical vapor deposition process. Detailed structural, compositional, and morphological analyses revealed intrinsic lattice defects, including stacking faults and domain misorientations. These defects disrupt the centrosymmetry of the CuS lattice and are responsible for an unexpected second harmonic generation response, an uncommon behavior in centrosymmetric materials. In addition, we measured the first-order temperature coefficients of Raman shifts, providing insights into the thermal dynamics of the CuS crystal structure. These findings position CuS as a potential material for nonlinear optical applications, while reinforcing its established roles in catalysis and electronics.
Electroosmotic flow in a concentrated suspension of polyelectrolyte-grafted solid cylindrical particles: A particle-in-cell approach
Authors: Saini Amit Kumar , Tiwari Ashish
Published: December 2024

The present study attempts to deal with electrokinetic and hydrodynamic characteristics of mixed electroosmotic and pressure-driven flow through a membrane composed of a swarm of poly-electrolyte-coated solid cylindrical particles. The unit cell model approach is utilized to analyze the hydrodynamic interactions between particles of the multiparticle system. The electroosmotic flow is generated under the influence of an externally applied electric field, and a pressure gradient is assumed in the axial direction of the cylinder. The poly-electrolyte coating over the solid cylindrical particle is considered as a heterogeneous porous medium having variable permeability characteristics. The electrolyte fluid contains charged ions, which can be present and migrate in both inside and outside of the poly-electrolyte layer (PEL). Hence, PEL acts as a semi-permeable porous layer. The PEL is referred to as a fixed charged layer (FCL) owing to an extra number density of immobilized charged ions, fixed on the poly-electrolyte fibers. In order to derive the electric potential distribution in the membrane, the Debye–Hückel approximation is used to linearize the Poisson–Boltzmann equation, which is further used in hydrodynamic governing equations to investigate the electrokinetic effects in the membrane. The flow domain is divided into two subdomains: the FCL region, governed by the Brinkmann–Forchheimer equation, and the clear fluid region, governed by the Stokes equation. The effect of electroosmotic parameters such as electric double layer (EDL) thickness, thickness ratio parameter, and zeta potential, and the membrane parameters such as viscosity ratio, particle volume fraction, stress-jump parameter, Forchheimer number, and variable permeability parameter are analyzed on the flow profile as well as hydrodynamic quantities of the membrane such as hydrodynamic permeability and the Kozeny constant. It is observed that the increasing thickness of the EDL and equivalent EDL reduce the hydrodynamic permeability of the membrane; however, the membrane becomes more hydrodynamic permeable with the enhancement of the zeta potential.
The effects of undulating patterns of the dorsal fin on seahorse swimming performance
Authors: Chen Gong , Li Xiaohu
Published: December 2024

The seahorse, as a unique fish, swims with an upright posture. The dorsal fin of the seahorse exhibits two undulation amplitude envelopes, including the uniform sinusoidal (US) and decaying sinusoidal (DS) modes. The self-propelled swimming of the seahorse with the two modes is numerically studied when the inclination angle of its body is 85° and 30°. The simulation results show that the undulation amplitude envelope has a significant effect on the swimming speed, hydrodynamic force, pressure distribution and vortex structure. In comparison, the US mode is conducive to improving the swimming speed and hydrodynamic forces, particularly when the inclination angle is 30°. Additionally, five high- and low-pressure regions appear on the surface of the dorsal fin in the US mode, while only four pressure regions appear in the DS mode due to the decaying of undulation amplitude. For different undulating modes, the arrangement angle of the vortex in the flow field also changes, which may influence the thrust component. The vortex has been elongated to form a special strip structure in the wake, and the vortex intensity of the US mode is stronger. This work may provide insight into the design of the undulating patterns of the dorsal fin for seahorse-like robotic fish.
Ultrahigh seebeck coefficient and thermoelectric power factor in semimetal WTe2
Authors: Li Yu , Yang Chen , Yang Weifan , Jiang Yiyao , Mao Xinya , Yan Zhaoying , Zhu Shuhao , Luo Jiajun
Published: December 2024

Weyl semimetals are renowned for their intriguing physical properties and ultrahigh transverse thermoelectric power factor, but commonly exhibit exceedingly low Seebeck coefficient, and conventional strategies for the optimization of thermoelectric performance are unable to rectify this issue. In light of the distinct compensatory electronic structure inherent to semimetal materials, we propose an easy mechanism with the potential to achieve exceedingly high Seebeck power factors, by synergistic adjustment of the semimetal Fermi surface feature and temperature-dependent density of states. By diminishing the symmetrical distribution of electrons and holes in proximity to the Fermi surface, alongside the competitive Seebeck effect, we find a considerable surge in the Seebeck coefficient from ∼4/33 to 530/520 μV/K in the armchair/zigzag direction, respectively. Based on the ultrahigh power factor ∼14.6 W/mK2 achieved at 50 K, we highlight the potential of semimetallic materials as candidates for the next generation of flexible, high-performance thermoelectric devices.
An interkinetic envelope surrounds chromosomes between meiosis I and II in C. elegans oocytes
Authors: El Mossadeq Layla , Bellutti Laura , Le Borgne Rémi , Canman Julie C. , Pintard Lionel , Verbavatz Jean-Marc , Askjaer Peter , Dumont Julien
Published: December 2024

At the end of cell division, the nuclear envelope reassembles around the decondensing chromosomes. Female meiosis culminates in two consecutive cell divisions of the oocyte, meiosis I and II, which are separated by a brief transition phase known as interkinesis. Due to the absence of chromosome decondensation and the suppression of genome replication during interkinesis, it has been widely assumed that the nuclear envelope does not reassemble between meiosis I and II. By analyzing interkinesis in C. elegans oocytes, we instead show that an atypical structure made of two lipid bilayers, which we termed the interkinetic envelope, surrounds the surface of the segregating chromosomes. The interkinetic envelope shares common features with the nuclear envelope but also exhibits specific characteristics that distinguish it, including its lack of continuity with the endoplasmic reticulum, unique protein composition, assembly mechanism, and function in chromosome segregation. These distinct attributes collectively define the interkinetic envelope as a unique and specialized structure that has been previously overlooked.
Spectroscopic amplifier for ultrahigh plasmonic-based enhancement of the hyper-Raman scattering procedure
Authors: Alsawafta Mohammed
Published: December 2024

An anisotropic plasmonic trimer is proposed as an effective spectroscopic amplifier for the maximum signal enhancement of the hyper-Raman Scattering (HRS) process. The three-particle system is composed of asymmetric Au nanorings arranged collinearly in a J-aggregate configuration and illuminated by a longitudinally polarized light. The optical properties of the considered trimer have been numerically simulated by the finite-difference time-domain method. The extinction profile of the heterotrimer exhibits the excitation of two plasmonic bands, superradiant and subradiant (Fano interference) modes. From the associated highly enhanced and strongly localized nearfield, the enhancement factor of the surface-enhanced HRS (EFSEHRS) is calculated. The simulation results demonstrate the impact of both the thickness and height of the interacting rings on the Raman factor. To reach the desired value of the EFSEHRS, the thickness of the rings should be maximized, and their height must be minimized. These two factors work together to enormously increase the charge density accumulated in the intercoupling region, the associated nearfield intensity, and therefore significantly augment the corresponding EFSEHRS. The EFSEHRS increases exponentially with decreasing height and increasing thickness of the trimer system. For selected values of both thickness and height, EFSEHRS can reach a value never reported before, as high as 5.6 × 1023.
Lucky Imaging Based Blind Deconvolution Algorithm for Wide Field-of-view Solar GLAO Image
Authors: Bian Qing , Bao Hua , Li Shuiqi , Wang Shuai , Gao Guoqing , Luo Daiyin , Jiang Ning , Rao Changhui
Published: December 2024

This paper proposes a lucky imaging based blind deconvolution algorithm for wide field-of-view (FoV) ground layer adaptive optics (GLAO) solar images. Our method effectively combines the advantages of traditional lucky imaging and blind deconvolution techniques, by segmenting and reconstructing sub-images in different field directions of the captured image sequence, as well as stitching and fusing reconstructed results of multiple regions, which significantly improves the robustness of reconstruction results. High quality wide FoV reconstruction results were obtained for actual GLAO solar images collected by a 1 m New Vacuum Solar Telescope in experiments. After processing, the Image Sharpness Metric Based on the Notion of Just Notifiable Blur improved by 51.39% and 53.65% compared to the average frame of the input image. The algorithm proposed can help achieve good results in every field direction for wide FoV images, which can provide important data support for subsequent research.
Multi-wavelength Classification of Active and Star-forming Galaxies on the BPT Diagram with Supervised Machine Learning Models
Authors: Ding Jaymin , Rodriguez Antonio C.
Published: December 2024

Distinguishing between active galactic nuclei (AGN) and star-forming galaxies (SFGs) in large astronomical surveys is an important challenge with applications to various subfields of astrophysics and cosmology. In particular, this distinction is especially crucial for informing theories of supermassive black hole formation, which are tied to our understanding of the Big Bang and the early Universe. The Baldwin–Phillips–Terlevich (BPT) diagram, which uses flux ratios of optical emission lines, has been the traditional gold standard for differentiating between these galaxies for nearly four decades. Our aim is to investigate the effect that each spectral line and photometric band has on the accuracy of supervised machine learning models in distinguishing between AGN and SFGs. The data set we employ consists of nearly thirty thousand galaxies in a crossmatch of data from the Sloan Digital Sky Survey Data Release 16 with ultraviolet, X-ray, and infrared surveys. We find that machine learning models trained on and applied to photometry alone, are able to achieve above 90% accuracy. We also find that the addition of multi-wavelength data improves upon both the accuracy and precision of the original BPT diagram, increasing the accuracy to approximately 98% when combined with spectroscopy. We also find that adding in X-ray flux data does not improve the models, which could be an indication that the X-ray properties of AGN and SFGs are more similar than what was previously theorized.
Critical collapse in asymptotically anti-de Sitter spacetime*
Authors: Xin 辛 Li-Jie 李杰 , Shao 邵 Cheng-Gang 成刚
Published: December 2024

We investigate the critical collapse of spherically symmetric scalar fields in asymptotically anti-de Sitter spacetime, focusing on two scenarios: real and complex scalar fields with potentials. By fine-tuning the amplitude of the initial scalar field under different cosmological constants, we find a linear relationship between the critical amplitude of the first collapse and the cosmological constant in both scenarios. Furthermore, we observe that the slope of this linear relationship varies linearly with coupling strength.
Numerical studies of the voltage amplitude effect on plasma characteristics in atmospheric pressure driven by dual LF-RF frequency discharge
Authors: Yu Yilin , Zhao Zhibo , Nie Qiuyue , Chen Shu , Zhang Zhonglin
Published: December 2024

Dielectric barrier discharges (DBDs) are primarily utilized as efficient sources of large-volume diffuse plasmas. However, the synergistic interaction of certain key plasma factors limits their broader application. In the present study, we report on numerical investigations of the effects of voltage amplitude in dual-frequency excitation on atmospheric DBDs using a 50 kHz/5 MHz frequency combination. Our results indicate that varying the voltages for LF and RF significantly influences the electron dynamics during discharge, resulting in distinct spatiotemporal distributions of electron and metastable particle densities. These findings contribute to the regulation of discharges under atmospheric pressure conditions and facilitate the attainment of non-equilibrium and nonlinear plasma parameters.
Data driven deep learning fault diagnosis method based on vision transformer and multi-head attention for different working condition
Authors: Lu Jingyu , Ji Weixi , Yu Junjie , Zhang Chaoyang
Published: December 2024

Data-driven deep learning methods have shown excellent performance in bearing fault diagnosis tasks. In application scenarios, the network relies on data needs to adapt to signals under different working conditions. The data in actual scenarios are continuously monitored and consist of multi-source heterogeneous streams, which makes that data-driven fault diagnosis methods need to improve the quality of data with domain differences. Under data normalization and resampling, this paper combines data pre-processing techniques to integrate prior features into the network to improve the accuracy of identifying non-stationary time series data. The improved multi-head attention mechanism is used to further extract features accurately. In the extended multi-head attention mechanism, the dependencies of LSTM and BiGRU on non-stationary time series sequences are combined. By employing the encoder structure of the network, the signal is transformed into STFT images, which are modelled with global dependencies to enable accurate feature extraction. Case studies show that the method has advantages over traditional neural networks under different working conditions and noise levels.
Psychometric validation of the Diagnostic Assessment Research Tool: Alcohol use disorder module
Authors: Garber Molly L , Belisario Kyla , Levitt Emily E , McCabe Randi E , Kelly John , MacKillop James
Published: December 2024

Aims

Structured clinical interviewing is considered the gold standard in psychiatric diagnosis. The Diagnostic Assessment Research Tool (DART) is a novel modularized, non-copywritten, semi-structured interview; however, no studies have examined the psychometric properties of its alcohol use disorder (AUD) module. The primary aims of this study were to: (i) validate the factor structure of the DART AUD module and (ii) examine measurement invariance across several key demographic and subgroup factors.

Methods

Participants were community members in Hamilton, Canada and Boston, USA who self-identified as making a significant AUD recovery attempt (N = 499). Internal reliability was examined via the Kuder–Richardson 20 statistic, and correlations between symptom count and drinking quantity/frequency were examined. Then, symptom-level data were included in a confirmatory factor analysis to examine model fit of a single hypothesized factor structure. Finally, measurement invariance analyses were conducted for sex, age, ethnicity (White vs. racialized), and study site.

Results

This study found evidence for adequate internal reliability (rKR20 = 0.75), and symptom scores correlated with drinking quantity and frequency (r = 0.16–0.43). Confirmatory factor analysis results suggested excellent fit for the unidimensional one-factor AUD model (χ2 = 0.09, confirmatory factor index = 0.99, Tucker Lewis index = 0.99, standardized root mean square residual = 0.06, root mean square error of approximation = 0.02). Measurement invariance analyses revealed that the factor structure was equivalent between sex, age, ethnicity, and study site.

Conclusions

Findings provide strong evidence for the psychometric validity of the DART AUD module and support its use in research and clinical practice. The DART represents a credible alternative to other diagnostic interviewing tools for AUD.
Remote and Cross-Cultural Training of Research Assistants Abroad to Conduct Neuropsychological Tests: Lessons Learned
Authors: Stimmel Marnina B , Adhikari Dristi , Ayers Emmeline , Jacob Soumya , Verghese Joe , Weiss Erica F
Published: December 2024

There are no published guidelines regarding remotely training research assistants (RAs) to conduct neuropsychological tests. With technological advances allowing for increased international collaboration within the medical and research communities, challenges often arise from such partnerships, including linguistic, cultural, and physical barriers. A notable challenge for supervising neuropsychologists in international projects is the physical distance from RAs, sites, and materials, making training/supervision of RAs and monitoring test data quite challenging. In the context of a research collaboration between neuropsychologists based in New York and RAs based in Kerala, India, as part of the Kerala-Einstein Study, we explore the obstacles of remotely training RAs and maintaining neuropsychological data integrity. We share lessons learned and systems developed to optimize remote, multilingual, cross-cultural training of RAs in administration/scoring of neuropsychological tests. One-on-one video training sessions mitigated logistical problems (i.e., time differences, internet connection, language comfort). Individualized training in scoring and a centralized individual to double-score protocols addressed quality assurance of test data. Close collaboration between our teams was necessary for cultural competency, particularly when building an appropriate test battery, creating and translating manuals, and adapting protocols. Finally, frequent and ongoing communication channels ensured excellence in study design, information gathering, and data quality. Future studies should continue highlighting strategies for remotely training psychometrics/RAs in neuropsychological administration.
Real time-PCR a diagnostic tool for reporting copy number variation and relative gene-expression changes in pediatric B-cell acute lymphoblastic leukemia—a pilot study
Authors: Sadaqat Zoha , Joseph Smitha , Verma Chandrika , Muni Reddy Jyothi , Prakash Anand , Thomas Tinku , Bharadwaj Vandana , Vyas Neha
Published: December 2024

Real time-polymerase chain reaction (RT-PCR) is used routinely in clinical practice as a cost-effective method for molecular diagnostics. Research in pediatric B-cell Acute Lymphoblastic Leukemia (ped B-ALL) suggests that apart from cytogenetics and clinical features, there is a need to include Copy number variation (CNV) in select genes at diagnosis, for upfront stratification of patients. Using ped B-ALL as a model, we have developed a RT-PCR-based iterative probability scoring method for reporting CNVs, and relative gene-expression changes. Our work highlights that once genes of interest and hotspots of CNVs are identified in discovery phase, our proposed method can be used as a cost-effective and user-friendly diagnostic tool for the identification of changes at genomic or transcriptomic level. It has the potential to be incorporated in routine diagnostics in resource constrained settings and be tailored for different diseases as per need.
Advances in assessment and cognitive neurorehabilitation of HIV-related neurocognitive impairment
Authors: Fischer Elia L , Renaud Alexis , Grivaz Petr , Di Liberto Giovanni , Ryvlin Philippe , Cavassini Matthias , Du Pasquier Renaud A , Sokolov Arseny A
Published: December 2024

Neurocognitive impairment (NCI) is present in around 40% of people with HIV and substantially affects everyday life, adherence to combined antiretroviral therapy (cART) and overall life expectancy. Suboptimal therapy regimen, opportunistic infections, substance abuse and highly prevalent psychiatric co-morbidities contribute to NCI in people with HIV. In this review, we highlight the need for efficacious treatment of HIV-related NCI through pharmacological approaches and cognitive neurorehabilitation, discussing recent randomized controlled trials in this domain. We also discuss the benefits of a thorough and interdisciplinary diagnostic work-up between specialists in neurology, psychiatry, neuropsychology and infectious diseases, helping to disentangle the various factors contributing to cognitive complaints and deficits in people with HIV. While the advent of cART has contributed to slowing the progression of cognitive deficits in people with HIV and reducing the prevalence of HIV-associated dementia, NCI persists at a significant rate. Adjuvant stimulating or neuroprotective pharmacological agents have shown some potential benefits. Despite promising outcomes, studies on cognitive neurorehabilitation of HIV-related NCI remain sparse and limited in terms of methodological aspects. The access to cognitive neurorehabilitation is also restricted, in particular at the global scale. Novel technology bears a significant potential for restoring cognitive function in people with HIV, affording high degrees of standardization and personalization, along with opportunities for telerehabilitation. Entertaining serious video game environments with immersive graphics can further promote patient motivation, training adherence and impact on everyday life, as indicated by a growing body of evidence, including in seropositive children and older individuals in Africa. Upon validation of technology-assisted cognitive neurorehabilitation for HIV-related NCI in large-scale randomized controlled trials with state-of-the-art methodology, these approaches will promote socio-professional reintegration and quality of life of people with HIV.
Diagnosis of cognitive impairment and dementia: blood plasma and optical coherence tomography
Authors: Jali Vidishaa , Zhang Qinglin , Chong Joyce Ruifen , Wong Damon , Tan Bingyao , Garhöfer Gerhard , Hilal Saima , Lai Mitchell K P , Schmetterer Leopold , Chen Christopher Li-Hsian , Chua Jacqueline
Published: December 2024

Accurate and early diagnosis of Alzheimer's disease and vascular dementia is crucial for enabling timely interventions and improving patient outcomes. This study evaluates the diagnostic performance of plasma biomarkers (neurofilament light chain and phosphorylated tau181) and retinal biomarkers (retinal nerve fibre layer and ganglion cell-inner plexiform layer), individually and in combination, in differentiating moderate cognitive impairment and dementia from mild cognitive impairment and no cognitive impairment. A cross-sectional study was conducted involving 509 participants, aged 50 and older, recruited from a memory clinic. The participants were categorized as normal (n = 100), mild cognitive impairment (n = 144), moderate cognitive impairment (n = 90) or dementia (n = 175) based on detailed clinical assessments, neuropsychological testing and MRI scans. The thickness of the ganglion cell-inner plexiform layer (P < 0.001) and retinal nerve fibre layer (P = 0.030) decreased progressively from normal cognition to cognitive impairment and dementia. The thickest layers were observed in individuals with no cognitive impairment (mean ± standard deviation: ganglion cell-inner plexiform layer: 76 ± 11 µm, retinal nerve fibre layer: 92 ± 10 µm), while the thinnest layers were found in individuals with dementia (ganglion cell-inner plexiform layer: 72 ± 14 µm, retinal nerve fibre layer: 89 ± 12 µm). Plasma biomarker levels increased progressively from normal cognition to cognitive impairment and dementia (P < 0.001). Levels were lowest in individuals with no cognitive impairment [median (interquartile range): neurofilament light chain: 15 (9) pg/mL, phosphorylated tau181: 1.85 (1.00) pg/mL] and highest in those with dementia [neurofilament light chain: 34 (27) pg/mL, phosphorylated tau181: 3.24 (2.81) pg/mL]. After adjusting for retinal scan signal strength, neurofilament light chain showed a stronger negative association with retinal nerve fibre layer thickness [standardized beta estimate (β) = −0.184] and ganglion cell-inner plexiform layer thickness (β = −0.139) compared to phosphorylated tau181, which exhibited weaker associations with ganglion cell-inner plexiform layer (β = −0.091) and retinal nerve fibre layer (β = −0.059). While retinal parameters provided modest discriminatory ability (AUC = 0.60), plasma biomarkers demonstrated superior diagnostic performance (AUC = 0.76). Notably, neurofilament light chain had a stronger association with retinal thinning than phosphorylated tau181 and offered superior diagnostic value for identifying moderate cognitive decline. These findings underscore the potential of plasma biomarkers, particularly neurofilament light chain, for the early detection of dementia.
Perioperative morbidity after primary hiatal hernia repair increases as hernia size increases
Authors: Latorre-Rodríguez Andrés R , Rajan Ajay , Mittal Sumeet K
Published: December 2024

Background

Minimally invasive hiatal hernia (HH) repair is the gold standard for correcting mechanical defects of the crural diaphragm due to its safety and favorable clinical outcomes (i.e., relief of patient symptoms). However, several operative factors, including HH size, may negatively affect the postoperative course. We sought to determine if an increase in HH size was associated with an increased risk of perioperative complications, ICU admission, or hospital readmissions after minimally invasive HH repair.

Methods

We conducted a retrospective observational cohort study of patients who underwent primary HH repair by an experienced foregut surgeon between September 2016 and July 2023. Four groups were defined based on the percentage of stomach at the thorax determined during surgery (small-HH: <25%, moderate-HH: 25–49%, large-HH: 50–74%, and intrathoracic stomach [ITS]: ≥75%). Covariates were compared between the groups, and logistic regressions were performed to identify factors associated with postoperative morbidity.

Results

A total of 391 patients (73.7% female; mean age, 64.4 ± 12.5 years) comprised the groups: small-HH (n = 160), moderate-HH (n = 63), large-HH (n = 64), and ITS (n = 104). Patients with ITS were older (p < 0.001), had longer operations (p < 0.001), greater blood loss (p < 0.001), longer hospital stays (p < 0.001), and an increased risk of early postoperative complications (aOR 2.59 [CI95: 1.28–5.25], p = 0.009) and ICU admission (aOR 13.3 [CI95: 3.10–57.06], p < 0.001).

Conclusion

An increase in HH size was associated with an increased risk of early postoperative complications, ICU admission, and a trend toward higher 30- and 90-day hospital readmissions, likely due to the progressive nature of the disease.
A stuck leaflet after balloon post-dilatation in transcatheter aortic valve implantation with a SAPIEN-3 ultra RESILIA valve: a case report
Authors: Yamazoe Shinji , Ogawa Yasuhiro , Kano Naoaki , Mamiya Keita , Kawaguchi Katsuhiro
Published: December 2024

Background

Transcatheter aortic valve implantation (TAVI) is a safe and effective therapy for patients with severe aortic stenosis. A Stuck leaflet and severe intraprosthetic regurgitation after valve implantation occur rarely but can lead to sudden haemodynamic deterioration. We encountered a case of a stuck leaflet following post-dilatation with the Edwards Sapien 3 Ultra RESILIA valve.

Case summary

A 72-year-old woman was referred to our hospital for severe aortic stenosis with shortness of breath. She underwent transfemoral TAVI. After deployment of a 23 mm Sapien 3 Ultra RESILIA valve, post-dilatation was performed due to the presence of paravalvular leak (PVL). Transoesophageal echocardiography revealed a stuck leaflet and severe intraprosthetic regurgitation. Aortography also demonstrated severe aortic regurgitation. We performed valve-in-valve procedure using the second 23 mm valve. Post-valve-in-valve transoesophageal echocardiography showed no PVL nor aortic regurgitation, and haemodynamics improved.

Discussion

A stuck leaflet is a rare complication following post-dilatation. Severe intraprosthetic regurgitation can lead to sudden haemodynamic changes and may, in some cases, necessitate the use of extracorporeal membrane oxygenation. If haemodynamic changes occur, it is essential to promptly investigate the cause through multiple diagnostic modalities, including transoesophageal echocardiography and angiography.
Silica hydrogels as a carbon-free solid media for the culture of diverse organisms
Authors: Vaid Druhi , Zubir Alisa , Hanak Alistair , Qi Tanda , Delneri Daniela , Wong Lu Shin
Published: December 2024

Bacteriological agar plates are commonly used to carry out experiments for the selective growth of microorganisms and the isolation of single-strain colonies. However, the presence of agar itself may be a confounding factor since it may serve as a source of carbon and energy. Moreover, there have been ongoing constraints on the production and sourcing of agar. These concerns have led to an interest in the development of agar substitutes. Silica hydrogels are entirely inorganic carbon-free polymeric materials that lack any source of micronutrients. Herein, a revised method for the preparation of silica hydrogels as a solid culture medium is reported. These gels can be formulated with a range of nutrient-rich or minimal media supplemented with various carbon sources, and can be manipulated in the same manner as agar gels. Their use for the culture and isolation of diverse microorganisms, including both Gram-positive and Gram-negative bacteria, yeast, and filamentous fungi is demonstrated. These silica hydrogels supplemented with either antibiotics or other molecules of interest can also be used for microbial selection experiments.
TAT-1, a phosphatidylserine flippase, affects molting and regulates membrane trafficking in the epidermis of Caenorhabditis elegans
Authors: Milne Shae M , Edeen Philip T , Fay David S
Published: December 2024

Membrane trafficking is a conserved process required for the import, export, movement, and distribution of proteins and other macromolecules within cells. The Caenorhabditis elegans NIMA-related kinases NEKL-2 (human NEK8/9) and NEKL-3 (human NEK6/7) are conserved regulators of membrane trafficking and are required for the completion of molting. Using a genetic approach, we identified reduction-of-function mutations in tat-1 that suppress nekl-associated molting defects. tat-1 encodes the C. elegans ortholog of mammalian ATP8A1/2, a phosphatidylserine flippase that promotes the asymmetric distribution of phosphatidylserine on the cytosolic leaflet of lipid membrane bilayers. CHAT-1 (human CDC50), a conserved chaperone, was required for the correct localization of TAT-1, and chat-1 inhibition strongly suppressed nekl defects. Using a phosphatidylserine sensor, we found that TAT-1 was required for the normal localization of phosphatidylserine at apical endosomes and that loss of TAT-1 led to aberrant endosomal morphologies. Consistent with these data, TAT-1 localized to early endosomes and to recycling endosomes marked with RME-1, the C. elegans ortholog of the human EPS15 homology domain-containing protein, EHD1. TAT-1, phosphatidylserine biosynthesis, and the phosphatidylserine-binding protein RFIP-2 (human RAB11-FIP2) were all required for the normal localization of RME-1 to apical endosomes. Consistent with these proteins functioning together, inhibition of RFIP-2 or RME-1 led to the partial suppression of nekl molting defects, as did inhibition of phosphatidylserine biosynthesis. We propose that TAT-1 flippase activity, in conjunction with RFIP-2, promotes the recruitment of RME-1 to apical recycling endosomes and that inhibition of TAT-1–RFIP-2–RME-1 can compensate for a reduction in NEKL activities.
Mentorship advances antimicrobial use surveillance systems in low- and middle-income countries
Authors: Bajracharya Kiran Sunder , Luu Susan , Cheah Ron , KC Santosh , Mushtaq Atifa , Elijah Marjorie , Poudel Bhupendra Kumar , Cham Celeste Fernandes Xavier , Mandal Shyamu , Muhi Stephen , Buising Kirsty
Published: December 2024

A shortage of trained personnel poses significant challenges to implementing antimicrobial use (AMU) surveillance systems in low- and middle-income countries (LMICs). Traditional training models, such as workshops, seminars and online courses, often lack the sustained engagement and support necessary for deep learning and skill mastery. This article advocates for mentorship as an effective training method for AMU professionals in LMICs. Drawing on our experiences as mentors and mentees from 1- to 2-year mentorship programmes in Nepal, Pakistan, Papua New Guinea and Timor-Leste between 2019 and 2023, we highlight the challenges and success factors of mentorship. Our insights demonstrate mentorship’s value in building expertise and sustaining capacity in AMU surveillance, offering a promising solution to address the personnel shortage in these regions.
Enhancing patient representation learning with inferred family pedigrees improves disease risk prediction
Authors: Huang Xiayuan , Arora Jatin , Erzurumluoglu Abdullah Mesut , Stanhope Stephen A , Lam Daniel ,   Boehringer Ingelheim—Global Computational Biology and Digital Sciences, Arora Jatin , Erzurumluoglu Abdullah Mesut , Lam Daniel , Khoueiry Pierre , Jensen Jan N , Cai James , Lawless Nathan , Kriegl Jan , Ding Zhihao , de Jong Johann , Zhao Hongyu , Ding Zhihao , Wang Zuoheng , de Jong Johann
Published: December 2024

Background

Machine learning and deep learning are powerful tools for analyzing electronic health records (EHRs) in healthcare research. Although family health history has been recognized as a major predictor for a wide spectrum of diseases, research has so far adopted a limited view of family relations, essentially treating patients as independent samples in the analysis.

Methods

To address this gap, we present ALIGATEHR, which models inferred family relations in a graph attention network augmented with an attention-based medical ontology representation, thus accounting for the complex influence of genetics, shared environmental exposures, and disease dependencies.

Results

Taking disease risk prediction as a use case, we demonstrate that explicitly modeling family relations significantly improves predictions across the disease spectrum. We then show how ALIGATEHR’s attention mechanism, which links patients’ disease risk to their relatives’ clinical profiles, successfully captures genetic aspects of diseases using longitudinal EHR diagnosis data. Finally, we use ALIGATEHR to successfully distinguish the 2 main inflammatory bowel disease subtypes with highly shared risk factors and symptoms (Crohn’s disease and ulcerative colitis).

Conclusion

Overall, our results highlight that family relations should not be overlooked in EHR research and illustrate ALIGATEHR’s great potential for enhancing patient representation learning for predictive and interpretable modeling of EHRs.
CARE-SD: classifier-based analysis for recognizing provider stigmatizing and doubt marker labels in electronic health records: model development and validation
Authors: Walker Andrew , Thorne Annie , Das Sudeshna , Love Jennifer , Cooper Hannah L F , Livingston Melvin , Sarker Abeed
Published: December 2024

Objective

To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques.

Materials and Methods

We first created a lexicon and regular expression lists from literature-driven stem words for linguistic features of stigmatizing patient labels, doubt markers, and scare quotes within EHRs. The lexicon was further extended using Word2Vec and GPT 3.5, and refined through human evaluation. These lexicons were used to search for matches across 18 million sentences from the de-identified Medical Information Mart for Intensive Care-III (MIMIC-III) dataset. For each linguistic bias feature, 1000 sentence matches were sampled, labeled by expert clinical and public health annotators, and used to supervised learning classifiers.

Results

Lexicon development from expanded literature stem-word lists resulted in a doubt marker lexicon containing 58 expressions, and a stigmatizing labels lexicon containing 127 expressions. Classifiers for doubt markers and stigmatizing labels had the highest performance, with macro F1-scores of 0.84 and 0.79, positive-label recall and precision values ranging from 0.71 to 0.86, and accuracies aligning closely with human annotator agreement (0.87).

Discussion

This study demonstrated the feasibility of supervised classifiers in automatically identifying stigmatizing labels and doubt markers in medical text and identified trends in stigmatizing language use in an EHR setting. Additional labeled data may help improve lower scare quote model performance.

Conclusions

Classifiers developed in this study showed high model performance and can be applied to identify patterns and target interventions to reduce stigmatizing labels and doubt markers in healthcare systems.