bluuebunny/crossref_metadata_2025 huggingface dataset:
Isomeric effects on the electron impact scattering for selected five membered heterocyclic ring molecules
Authors: Jani Tejas , Vinodkumar P C , Vinodkumar Minaxi
Published: July 2024

We present electron scattering cross-sectional data for selected isomers of the five-membered ring molecules, specifically oxazole and isoxazole, thiazole and isothiazole, and imidazole and pyrazole. The ab-initio R-matrix method, incorporating static exchange polarization approximations, is employed for this calculation from energy range 0.1 eV to 20 eV. Three shape resonances are identified and characterized in each system, consisting of two π* and one σ* shape resonances. Notably, thiazole and isothiazole exhibit additional σ* resonance which is which is at a lower energy than other σ* resonance. The calculated resonance positions align well with available experimental as well as theoretical data. We also performed electronic structure calculations to aid in characterization of resonances. Comparison of the scattering cross-sectional data with their respective isomers reveal marginal differences in the magnitude of the elastic cross section particularly below 1 eV. This discrepancy may be attributed to variations in the long-range electronic dipole contribution to the electron-molecule interaction process. Further, to understand dependency of dipole moment on elastic cross section, we performed a fitting procedure for the elastic cross sections at 0.1 eV with square of the dipole moment of all the five membered ring molecules studied here. The fitting formula so obtained was used to estimate the cross section for other three five membered ring molecules: Furan, Thiophene and Pyrrole. Additionally, total ionization cross sections are computed using the binary-encounter-Bethe (BEB) model, demonstrating nearly identical results when compared with their isomers. Our findings offer insights into the influence of structural changes on the electron scattering data, providing guidance for other theoretical investigations.
Autonomous three-dimensional oscillator with two and four wings attractors embedded in the microcontroller: analysis, amplitude controls, random number generator, and image encryption application
Authors: Alexander Prasina , Emin Berkay , Ngongiah Isidore Komofor , Sekhar D Chandra , Akgül Akif
Published: July 2024

Robust chaotic systems offer unpredictability, complex dynamics, noise-like properties, efficient bifurcation behavior, and the ability to model real-world phenomena, making them valuable in diverse scientific and engineering applications. This paper details on the dynamical appraisal, amplitude controls, microcontroller execution, Random number generator (RNG) of an autonomous three-dimensional (3D) oscillator with two and four wings attractors (ATDOTFWA), and its image encryption application. Thanks to the Routh-Hurwitz criteria, five steady states found in the ATDOTFWA are classified as stable or unstable, depending on its two control parameters. During the numerical simulations employing the Runge–Kutta scheme, the ATDOTFWA exhibit a wide range of dynamic behaviors, including no oscillations, Hopf bifurcation, limit cycle, five distinct presentations of two wings chaotic structures, monostable and bistable two wings chaotic structures, bistable and monostable regular oscillations, chaotic bursting characteristics, coexistence of period-2-oscillations and four wings chaotic structure, and four wings chaotic attractor which were validated experimentally by the microcontroller implementation. The total and partial controls of the amplitude are achieved in the ATDOTFWA. A RNG is designed based on the ATDOTFWA, and the generated random numbers are successfully tested using the ENT and NIST 800–22 statistical test suites, demonstrating the reliability of the ATDOTFWA-based RNG. This reliability is further confirmed through the application of the ATDOTFWA-based RNG in an efficient and secure image encryption process, where the generated random numbers are used as the encryption key. The effectiveness of the image encryption process is validated through comprehensive cryptanalysis, with an encryption time of 0.1923 s for a 512×512 image, an average normalized pixel change rate (NPCR) of 99.6126%, an average unified average changing intensity (UACI) of 33.4578%, and an average information entropy of 7.9994.
Testing secret interaction with astrophysical neutrino point sources
Authors: Döring Christian , Vogl Stefan
Published: July 2024

Recently, the IceCube collaboration observed a neutrino excess in the direction of NGC 1068 with high statistical significance.
This constitutes the second detection of an astrophysical neutrino point source after the discovery of a variable emission originating from the blazar TXS 0506+056. Neutrinos emitted by these sources traverse huge, well-determined distances on their way to Earth. This makes them a promising tool to test new physics in the neutrino sector. We consider secret interactions with the cosmic neutrino background and discuss their impact on the flux of neutrino point sources. The observation of emission from NGC 1068 and TXS 0506+056 can then be used to put
limits on the strength of the interaction. We find that our ignorance of the absolute neutrino masses has a strong impact and, therefore, we present limits in two benchmark scenarios with the sum of the neutrino masses around their lower and upper limits.
Limits on non-relativistic matter during Big-bang nucleosynthesis
Authors: Yeh Tsung-Han , Olive Keith A. , Fields Brian D.
Published: July 2024

Big-bang nucleosynthesis (BBN) probes the cosmic mass-energy density at temperatures ∼  10 MeV to ∼ 100 keV. Here, we consider the effect of a cosmic matter-like species that is non-relativistic and pressureless during BBN. Such a component must decay; doing so during BBN can alter the baryon-to-photon ratio,η, and the effective number of neutrino species. We use light element abundances and the cosmic microwave background (CMB) constraints onη  andNνto place constraints on such a matter component. We find that electromagnetic decays heat the photons relative to neutrinos, and thus dilute the effective number of relativistic species toNeff< 3 for the case of three Standard Model neutrino species. Intriguingly, likelihood results based onPlanckCMB data alone findNν= 2.800 ± 0.294, and when combined with standard BBN and the observations of D and4He giveNν= 2.898 ± 0.141. While both results are consistent with the Standard Model, we find that a nonzero abundance of electromagnetically decaying matter gives a better fit to these results. Our best-fit results are for a matter species that decays entirely electromagnetically with a lifetime  τX= 0.89 sec and pre-decay density that is a fractionξ= (ρX/ρrad|10 MeV  = 0.0026 of the radiation energy density at 10 MeV; similarly good fits are found over a range whereξτX1/2is constant. On the other hand, decaying matter often spoils the BBN+CMB concordance, and we present limits in the (τX,ξ) plane for both electromagnetic and invisible decays. For dark (invisible) decays, standard BBN (i.e.ξ= 0) supplies the best fit. We end with a brief discussion of the impact of future measurements including CMB-S4.
Constraining primordial non-Gaussianity from large scale structure with the wavelet scattering transform
Authors: Peron Matteo , Jung Gabriel , Liguori Michele , Pietroni Massimo
Published: July 2024

We investigate the Wavelet Scattering Transform (WST) as a tool for the study of Primordial non-Gaussianity (PNG) in Large Scale Structure (LSS), and compare its performance with that achievable via a joint analysis with power spectrum and bispectrum (P+B). We consider the three main primordial bispectrum shapes — local, equilateral and orthogonal — and produce Fisher forecast for the correspondingfNLamplitude parameters, jointly with standard cosmological parameters. We analyze simulations from the publicly availableQuijoteandQuijote-pngN-body suites, studying both the dark matter and halo fields. We find that the WST outperforms the power spectrum alone on all parameters, both on thefNL's and on cosmological ones. In particular, onfNLlocalfor halos, the improvement is about 27%. When B is combined with P, halo constraints from WST are weaker forfNLlocal(at ∼ 15% level), but stronger forfNLequil(∼ 25%) andfNLortho(∼ 28%). Our results show that WST, both alone and in combination with P+B, can improve the extraction of information on PNG from LSS data over the one attainable by a standard P+B analysis. Moreover, we identify a class of WST in which the origin of the extra information on PNG can be cleanly isolated.
Linear stability of vector Horndeski black holes
Authors: Chen Che-Yu , Felice Antonio De , Tsujikawa Shinji
Published: July 2024

Horndeski's vector-tensor (HVT) gravity is described by a Lagrangian in which the field strength  fμν=∂μAν-∂νAμ  of a vector fieldAμinteracts with a double dual Riemann tensorLμναβin the form  βLμναβFμνFαβ, whereβis a constant. In Einstein-Maxwell-HVT theory, there are static and spherically symmetric black hole (BH) solutions with electric or magnetic charges, whose metric components are modified from those in the Reissner-Nordström geometry. The electric-magnetic duality of solutions is broken even at the background level by the nonvanishing coupling constantβ. We compute a second-order action of BH perturbations containing both the odd- and even-parity modes and show that there are four dynamical perturbations arising from the gravitational and vector-field sectors. We derive all the linear stability conditions associated with the absence of ghosts and radial/angular Laplacian instabilities for both the electric and magnetic BHs. These conditions exhibit the difference between the electrically and magnetically charged cases by reflecting the breaking of electric-magnetic duality at the level of perturbations. In particular, the four angular propagation speeds in the large-multipole limit are different from each other for both the electric and magnetic BHs. This suggests the breaking of eikonal correspondence between the peak position of at least one of the potentials of dynamical perturbations and the radius of photon sphere. For the electrically and magnetically charged cases, we elucidate parameter spaces of the HVT coupling and the BH charge in which the BHs without naked singularities are linearly stable.
Solar reflection of dark matter with dark-photon mediators
Authors: Emken Timon , Essig Rouven , Xu Hailin
Published: July 2024

We consider the scattering of low-mass halo dark-matter particles in the hot plasma of the
Sun, focusing on dark matter that interact with ordinary matter through a dark-photon mediator.
The resulting “solar-reflected” dark matter (SRDM) component contains high-velocity particles,
which significantly extend the sensitivity of terrestrial direct-detection experiments to sub-MeV
dark-matter masses. We use a detailed Monte Carlo simulation to model the propagation and
scattering of dark-matter particles in the Sun, including thermal effects, with special emphasis
on ultralight dark-photon mediators. We study the properties of the SRDM flux, obtain exclusion
limits from various direct-detection experiments, and provide projections for future experiments,
focusing especially on those with silicon and xenon targets. We find that proposed future
experiments with xenon and silicon targets can probe the entire “freeze-in benchmark”, in which
dark matter is coupled to an ultralight dark photon, including dark-matter masses as low as
 𝒪(keV). Our simulations and SRDM fluxes are publicly available.
Power scaling of intra-cavity Nd:YAG/LBO laser at 532 nm by birefringence compensation
Authors: Li Shuai , Fang Zijun , Peng Majun , Zhu Zhanda , Lei Hong , Li Qiang
Published: July 2024

We report an effective method to reduce the impact of polarization state changes caused by thermal birefringence in intra-cavity frequency-doubled laser. The laser consists of a diode side pumped Nd:YAG module, an acousto-optic modulator Q-switch, and an LBO crystal used for SHG generation in 532 nm laser. The effect of thermal birefringence originated by the Nd:YAG rod with concave-shape end surfaces on SHG efficiency is compensated by the insertion of a λ/8 plate into the cavity. At the repetition frequency of 9 kHz, the 532 nm laser achieves a maximum output power of 23.8 W, a pulse duration of 60 ns (FWHM), and a beam quality factor of Mx
2
× My
2
= 1.52 × 1.43. Compared with the λ/4 plate and without plate, the maximum average power of the laser with the λ/8 plate has increased by 22.7% and 66.4%, respectively, the beam quality factor has also been greatly improved correspondingly. This method provides a new solution for lasers to compensate thermally induced birefringence.
Numerical comprehensive evaluation of the flow control effect on a circular cylinder with a control rod
Authors: Gong Jiarui , Wang Jiansheng , Liu Xueling , Jiang Haoran
Published: July 2024

The drag reduction of the single circular cylinder is achieved by changing the position of an additional control rod in the present work. In order to look for where to place the control rod will help the drag force exerted on the main cylinder surface as little as possible, the additional control rod is arranged at various positions in the downstream region, the upstream region, and the middle region of the single circular cylinder, respectively. The numerical results show that the maximum drag reduction rate of the single circular cylinder can be up to 21.68%. While the additional control rod is located at some specific positions in the flow field, the drag of the single circular cylinder will increase. However, if two bluff bodies (the main circular cylinder and the control rod) are considered as a whole system, due to the extra drag contribution of the control rod, the maximum drag reduction effect of the system is 8.65%. Additionally, the lift exerted on the main cylinder and the control rod has changed a lot due to the interaction between two bluff bodies. Furthermore, the Dynamic Mode Decomposition analysis method is employed to probe the mechanism of drag variation employing the dominant flow modes.
Effect of generalized dimple shape on load-carrying capacity and leakage characteristics of laser surface textured dry gas seal
Authors: Men Ri-Xiu , Liu Chang , Wang Zhen , Wang Shuai , Cao Shu-Qian
Published: July 2024

A new formula is employed to describe the dimple boundaries by considering edge number, superellipse coefficient, long axis radius and inclined angle, which make it possible to describe the boundaries of more typical dimple patterns by a unifiend equation. A mathematical model for obtaining the pressure distribution of dry gas seal with polygon dimple surface is established. The influence of the key geometrical parameters of polygon dimple on opening force and leakage rate is studied. The optimized geometries of generalized polygon dimple for the maximum opening force are obtained. Results show that an inclined quadrilateral dimple with multi rows in the radial direction presents the largest opening force. The opening forces of the two-sided and quadrilateral dimples with micron-scale are significantly better than that of millimeter apertures, while the opening forces of the triangular, pentagonal and hexagonal dimples with millimeter-scale are larger than that of the micron types. The shape profile parameters, directional parameters and radial dimple number of polygon dimples should be properly designed for excellent LCC and leakage characteristics.
Study on dynamic behavior of atomic diffusion at interface between TiAlN coating and WC matrix
Authors: Fan Yihang , Wang Qingyu , Hao Zhaopeng
Published: July 2024

The molecular dynamics method was used to simulate the dynamic behavior change of atomic diffusion at interface between TiAlN coating and WC matrix in the carbide tool with TiAlN coating. It was determined that the one-way diffusion of C atom to TiAlN coating resulted in serious lattice distortion on the surface. Meanwhile, the whole diffusion process was accompanied by the continuous increase of stress, resulting in gradual deformation of the material. The interface bonding performance also decreases. Then, the surface energy and atomic layer convergence are calculated by the first-principles method. The TiAlN crystal surface is stable at 8 atomic layers, and the WC crystal surface is stable at 6 atomic layers, and then a stable microinterface model can be built. The relaxation processing for the established model was performed to determine the diffusion path of C atom. Then, the energy barrier, adhesion work, interface energy and fracture toughness of different transition state structures in the diffusion path of C atom are calculated, and it is determined that with the deepening of the diffusion of C atom in the coating, the binding ability of the interface of the coating base and the performance of the coating tool are more and more serious damage. Finally, the cutting experiment of TiAlN coated tool is designed. According to the surface topography of TiAlN coated tool in different periods, the simulation and theoretical analysis mentioned above are verified, which provides a theoretical basis for the subsequent research on improving the performance of coated tool.
VO2-Based metasurface for dynamically tunable terahertz surface plasmonic waves
Authors: Xu Guanghong , Li Quan , Su Hao , Huang Hai , Wang Shuang
Published: July 2024

Surface plasmonic waves (SPWs), which propagate along metal-dielectric interfaces, play a pivotal role in various photonic applications such as highly integrated photonic devices, super-resolution imaging, high-sensitivity sensing, on-chip integrated systems, etc. The ability to control the excitation direction of the SPWs is of great importance in these applications. In this work, we propose a terahertz on-chip metasurface device whose SPWs propagation direction can be dynamically tuned at the excitation source by exploiting the vanadium dioxide (VO2). Under circularly polarized light incidence, destructive or constructive interference formed in the subwavelength square ring slit resonators (SRSRs) arrays, resulting in the unidirectional propagation of terahertz SPWs. By adjusting the conductivity of VO2, the flexible control over the propagation direction of SPWs is realized. This approach significantly enhances the level of control compared to previous traditional polarization control method which can only be modulated by the polarization state, marking a notable advancement in the development of functional devices that harness the power of SPWs.
AO-SVM: a machine learning model for predicting water quality in the cauvery river
Authors: J Vellingiri , K Kalaivanan , Shanmugaiah Kaliraj , Shobana Bai Femilda Josephin Joseph
Published: July 2024

Water pollution is a significant cause of death globally, resulting in 1.8 million deaths annually due to waterborne diseases. Assessing water quality is a complex process that involves identifying contaminants in water sources and determining whether it is safe for human consumption. In this study, we utilized the Cauvery River dataset to develop a model for evaluating water quality. The aim of our research was to proficiently perform feature selection and classification tasks. We introduced a novel technique called the Aquila Optimization Support Vector Machine (AO-SVM), an advanced and effective machine learning system for predicting water quality. Here SVM is used for the classification, and the Aquila algorithm is used for optimizing SVM. The results show that the proposed method achieved a maximum accuracy rate of 96.3%, an execution time of 0.75 s, a precision of 93.9%, a recall rate of 95.1%, and an F1-Score value of 94.7%. The suggested AO-SVM model outperformed all other existing classification models regarding classification accuracy and other parameters.
Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements
Authors: Gill K , Smith D , Joung S , Geiger B , McKee G , Zimmerman J , Coffee R , Jalalvand A , Kolemen E
Published: July 2024

A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µs and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F
1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.
Optimizing data acquisition: a Bayesian approach for efficient machine learning model training
Authors: Mahani M R , Nechepurenko Igor A , Rahimof Yasmin , Wicht Andreas
Published: July 2024

Acquiring a substantial number of data points for training accurate machine learning (ML) models is a big challenge in scientific fields where data collection is resource-intensive. Here, we propose a novel approach for constructing a minimal yet highly informative database for training ML models in complex multi-dimensional parameter spaces. To achieve this, we mimic the underlying relation between the output and input parameters using Gaussian process regression (GPR). Using a set of known data, GPR provides predictive means and standard deviation for the unknown data. Given the predicted standard deviation by GPR, we select data points using Bayesian optimization to obtain an efficient database for training ML models. We compare the performance of ML models trained on databases obtained through this method, with databases obtained using traditional approaches. Our results demonstrate that the ML models trained on the database obtained using Bayesian optimization approach consistently outperform the other two databases, achieving high accuracy with a significantly smaller number of data points. Our work contributes to the resource-efficient collection of data in high-dimensional complex parameter spaces, to achieve high precision ML predictions.
Pathways to zero emissions in California’s heavy-duty transportation sector
Authors: Hennessy Eleanor M , Singh Madalsa , Saltzer Sarah , Azevedo Inês M L
Published: July 2024

California contributes 0.75% of global greenhouse gas (GHG) emissions and has a target of reaching economy-wide net zero emissions by 2045, requiring all sectors to rapidly reduce emissions. Nearly 8% of California’s GHG emissions are from the heavy-duty transportation sector. In this work, we simulate decarbonization strategies for the heavy-duty vehicle (HDV) fleet using detailed fleet turnover and air quality models to track evolution of the fleet, GHG and criteria air pollutant emissions, and resulting air quality and health impacts across sociodemographic groups. We assess the effectiveness of two types of policies: zero emission vehicle sales mandates, and accelerated retirement policies. For policies including early retirements, we estimate the cost of early retirements and the cost-effectiveness of each policy. We find even a policy mandating all HDV sales to be zero emission vehicles by 2025 would not achieve fleetwide zero emissions by 2045. For California to achieve its goal of carbon neutrality, early retirement policies are needed. We find that a combination of early retirement policies and zero emission vehicle sales mandates could reduce cumulative CO2 emissions by up to 64%. Furthermore, we find that decarbonization policies will significantly reduce air pollution-related mortality, and that Black, Latino, and low-income communities will benefit most. We find that policies targeting long-haul heavy-heavy duty trucks would have the greatest benefits and be most cost-effective.
First site-specific conjugation method for native goat IgG antibodies via glycan remodeling at the conserved Fc region
Authors: Dolan Michael E , Sadiki Amissi , Wang Leo (Lei) , Wang Yan , Barton Christopher , Oppenheim Sheldon F , Zhou Zhaohui Sunny
Published: July 2024

Despite their triumph in treating human diseases, antibody therapies for animals have gained momentum more slowly. However, the first approvals of animal antibodies for osteoarthritic pain in cats and dogs may herald the dawn of a new era. For example, goats are vital to economies around the world for their milk, meat, and hide products. It is therefore imperative to develop therapies to safeguard goats—with antibodies at the forefront. Goat antibodies will be crucial in the development of therapeutic antibodies, for example, as tracers to study antibody distribution in vivo, reagents to develop other therapeutic antibodies, and therapeutic agents themselves (e.g., antibody-drug conjugates). Hamstringing this effort is a still-burgeoning understanding of goat antibodies and their derivatization. Historically, goat antibody conjugates were generated through stochastic chemical modifications, producing numerous attachment sites and modification ratios, thereby deleteriously impacting antigen binding. Site-specific methods exist but often require substantial engineering and have not been demonstrated with goat antibodies. Nevertheless, we present herein a novel method to site-specifically conjugate native goat antibodies: chemo-enzymatic remodeling of the native Fc N-glycan introduces a reactive azide handle, after which click chemistry with strained alkyne partners affords homogeneous conjugates labeled only on the Fc domain. This process is robust, and resulting conjugates retain their antigen binding and specificity. To our knowledge, our report is the first for site-specific conjugation of native goat antibodies. Furthermore, our approach should be applicable to other animal antibodies—even with limited structural information—with similar success.
A semiautomated microfluidic ELISA for the detection of hemophagocytic lymphohistiocytosis biomarkers
Authors: Herskovits Adrianna Zara , Johnson William T , Oved Joseph H , Irwin Spencer , Doddi Sital , John Deronna , Ocasio Angelica , Ramanathan Lakshmi V
Published: July 2024

Objectives

Hemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening condition characterized by a massive overactivation of the immune system. Because the clinical findings are nonspecific, the development of assays to facilitate rapid diagnosis is critical for patient care. The objectives of this study were to evaluate the performance of a microfluidic enzyme-linked immunosorbent assay (ELISA) for HLH biomarkers and investigate the impact of insourcing this testing on workflow, cost, and turnaround time in a tertiary-care cancer hospital.

Methods

Trends in order volume were evaluated for C-X-C motif chemokine ligand 9 (CXCL9) and soluble interleukin 2 receptor ɑ (sIL2R), and a microfluidic ELISA was used to measure these analytes in serum samples. Analyte values, turnaround time, and costs were compared for this assay relative to reference laboratory testing.

Results

Test ordering has increased from 187 to 1030 requests annually over the past 5 years. Insourcing these analytes on a semiautomated ELISA can decrease time to result by approximately 2 days and generate a cost savings of roughly $140,000 annually within our laboratory.

Conclusions

Using a semiautomated ELISA for sIL2R and CXCL9 may help physicians arrive at a diagnosis and monitor therapy for patients with HLH while decreasing turnaround time and costs within the clinical laboratory.
The health implications of cumulative exposure to contextual (dis)advantage: methodological and substantive advances from a unique data linkage
Authors: Xu Wei , Kamis Christina , Agnew Megan , Schultz Amy , Salas Sarah , Malecki Kristen , Engelman Michal
Published: July 2024

Deleterious neighborhood conditions are associated with poor health, yet the health impact of cumulative lifetime exposure to neighborhood disadvantage is understudied. Using up to 5 decades of residential histories for 4177 adult participants in the Survey of the Health of Wisconsin (SHOW) and spatiotemporally linked neighborhood conditions, we developed 4 operational approaches to characterizing cumulative neighborhood (dis)advantage over the life course. We estimated their associations with self-reported general health and compared them with estimates using neighborhood (dis)advantage at the time of study enrollment. When cumulative exposures were assessed with the most granular temporal scale (approach 4), neighborhood transportation constraints (odds ratio [OR] = 1.21; 95% CI, 1.08-1.36), residential turnover (OR = 1.20; 95% CI, 1.07-1.34), education deficit (OR = 1.17; 95% CI, 1.04-1.32), racial segregation (OR = 1.20; 95% CI, 1.04-1.38), and median household income (OR = 0.85; 95% CI, 0.75-0.97) were significantly associated with risk of fair or poor health. For composite neighborhood disadvantage, cumulative exposures had a stronger association (OR = 1.05; 95% CI, 1.02-1.08) than the cross-sectional exposure (OR = 1.03; 95% CI, 1.01-1.06). Single-point-in-time neighborhood measures underestimate the relationship between neighborhood and health, underscoring the importance of a life-course approach to cumulative exposure measurement.
Caregiver burden and risk of epithelial ovarian cancer in the Nurses’ Health Studies
Authors: Barnard Mollie E , Poole Elizabeth M , Huang Tianyi , Sood Anil K , Kubzansky Laura D , Tworoger Shelley S
Published: July 2024

Psychosocial stress may increase ovarian cancer risk and accelerate disease progression. We examined the association between caregiver burden, a common stressor, and risk of epithelial ovarian cancer. We prospectively followed 67 724 women in the Nurses’ Health Study (1992-2012) and 70 720 women in the Nurses’ Health Study II (2001-2009) who answered questions on informal caregiving (ie, caregiving outside of work). Women who reported no informal caregiving were considered noncaregivers, while, among women who provided care outside of work, caregiver burden was categorized by time spent caregiving and perceived stress from caregiving. For the 34% of women who provided informal care for ≥15 hours per week, 42% described caregiving as moderately to extremely stressful. Pooled multivariate analyses indicated no difference in ovarian cancer risk for women providing ≥15 hours of care per week compared to noncaregivers (hazard ratio [HR] = 0.96; 95% confidence interval [CI], 0.79-1.18), and no association was evident for women who reported moderate or extreme stress from caregiving compared to noncaregivers (HR = 0.96; 95% CI, 0.75-1.22). Together with prior work evaluating job strain and ovarian cancer risk, our findings suggest that, when evaluating a stressor’s role in cancer risk, it is critical to consider how the stressor contributes to the overall experience of distress.

This article is part of a Special Collection on Gynecological Cancer.
Safe and Effective Restoration of Jawline Definition With Hyaluronic Acid Injectable Gel VYC-25L: Results From a Randomized Controlled Study
Authors: Rivkin Alexander , Green Jeremy B , Bruce Suzanne , Cox Sue Ellen , Hevia Oscar , Chawla Smita , Sartor Marta
Published: July 2024

Background

A well-defined jawline improves overall facial aesthetics, motivating patients to seek jawline augmentation.

Objectives

In this study we evaluated the safety and effectiveness of the hyaluronic acid injectable gel VYC-25L for restoring jawline definition.

Methods

In a US multicenter, evaluator-blinded study adults with grade 2 (moderate) or 3 (severe) Allergan Loss of Jawline Definition Scale (ALJDS) scores were randomized. Participants were randomized to the VYC-25L treatment group or control group at study onset, with 12-month follow-up. The control group had the option to receive treatment after 6 months (primary endpoint completion). Effectiveness measures included Month 6 ALJDS responders rate (proportion of participants with ≥1-grade improvement from baseline on both sides), FACE-Q Satisfaction With Lower Face and Jawline scores, and Global Aesthetic Improvement Scale (GAIS) responders (improved/much improved) as assessed by the investigator and participants. Injection site responses (ISRs) and adverse events (AEs) were monitored.

Results

At Month 6, ALJDS responder rates were 69.0% vs 38.0% in the VYC-25L treatment (n = 157) and control (n = 49) groups, respectively (P = .0001). In the VYC-25L treatment group, FACE-Q scores improved by a mean of 45.9 points from baseline at Month 6 (P < .0001). Furthermore, 88.4% and 89.0% of participants in the VYC-25L treatment group were GAIS responders at Month 6 by participant and investigator assessment, respectively. Most ISRs were mild or moderate and resolved within 2 weeks. Most treatment-related AEs were mild and resolved within 1 week.

Conclusions

VYC-25L safely and effectively restores jawline definition through 1 year.

Level of Evidence: 1
EGPDI: identifying protein–DNA binding sites based on multi-view graph embedding fusion
Authors: Zheng Mengxin , Sun Guicong , Li Xueping , Fan Yongxian
Published: July 2024

Mechanisms of protein-DNA interactions are involved in a wide range of biological activities and processes. Accurately identifying binding sites between proteins and DNA is crucial for analyzing genetic material, exploring protein functions, and designing novel drugs. In recent years, several computational methods have been proposed as alternatives to time-consuming and expensive traditional experiments. However, accurately predicting protein-DNA binding sites still remains a challenge. Existing computational methods often rely on handcrafted features and a single-model architecture, leaving room for improvement. We propose a novel computational method, called EGPDI, based on multi-view graph embedding fusion. This approach involves the integration of Equivariant Graph Neural Networks (EGNN) and Graph Convolutional Networks II (GCNII), independently configured to profoundly mine the global and local node embedding representations. An advanced gated multi-head attention mechanism is subsequently employed to capture the attention weights of the dual embedding representations, thereby facilitating the integration of node features. Besides, extra node features from protein language models are introduced to provide more structural information. To our knowledge, this is the first time that multi-view graph embedding fusion has been applied to the task of protein–DNA binding site prediction. The results of five-fold cross-validation and independent testing demonstrate that EGPDI outperforms state-of-the-art methods. Further comparative experiments and case studies also verify the superiority and generalization ability of EGPDI.
Gba1 E326K renders motor and non-motor symptoms with pathological α-synuclein, tau and glial activation
Authors: Kweon Sin Ho , Ryu Hye Guk , Kwon Seung-Hwan , Park Hyeonwoo , Lee Saebom , Kim Nam-Shik , Ma Shi-Xun , Jee Hee-Jung , Kim Sangjune , Ko Han Seok
Published: July 2024

Mutations in the GBA1 gene are common genetic risk factors for Parkinson’s disease, disrupting enzymatic activity and causing lysosomal dysfunction, leading to elevated α-synuclein levels. Although the role of GBA1 in synucleinopathy is well established, recent research underscores neuroinflammation as a significant pathogenic mechanism in GBA1 deficiency.

This study investigates neuroinflammation in Gba1 E326K knock-in mice, a model associated with increased risk of Parkinson’s disease and dementia. At 9 and 24 months, we assessed GBA1 protein and activity, α-synuclein pathology, neurodegeneration, motor deficits and gliosis in the ventral midbrain and hippocampus using immunohistochemistry, western blot and glucocerebrosidase assays. Additionally, primary microglia from wild-type and Gba1E326K/E326K mice were treated with α-synuclein preformed fibrils to study microglia activation, pro-inflammatory cytokines, reactive astrocyte formation and neuronal death through quantitative PCR, western blot and immunocytochemistry analyses. We also evaluated the effects of gut inoculation of α-synuclein preformed fibrils in Gba1 E326K mice at 7 months and striatal inoculation at 10 months after injection, assessing motor/non-motor symptoms, α-synuclein pathology, neuroinflammation, gliosis and neurodegeneration via behavioural tests, immunohistochemistry and western blot assays.

At 24 months, Gba1 E326K knock-in mice showed reduced glucocerebrosidase enzymatic activity and glucosylceramide build-up in the ventral midbrain and hippocampus. Increased pro-inflammatory cytokines and reactive astrocytes were observed in microglia and astrocytes from Gba1 E326K mice treated with pathological α-synuclein preformed fibrils. Gut inoculation of α-synuclein preformed fibrils increased Lewy body accumulation in the hippocampal dentate gyrus, with heightened microglia and astrocyte activation and worsened non-motor symptoms. Intrastriatal injection of α-synuclein preformed fibrils induced motor deficits, reactive glial protein accumulation and tauopathy in the prefrontal cortex and hippocampus of Gba1 E326K mice.

GBA1 deficiency attributable to the Gba1 E326K mutation exacerbates neuroinflammation and promotes pathogenic α-synuclein transmission, intensifying disease pathology in Parkinson’s disease models. This study enhances our understanding of how the Gba1 E326K mutation contributes to neuroinflammation and the spread of pathogenic α-synuclein in the brain, suggesting new therapeutic strategies for Parkinson’s disease and related synucleinopathies.
Excitation/Inhibition balance relates to cognitive function and gene expression in temporal lobe epilepsy: a high density EEG assessment with aperiodic exponent
Authors: Duma Gian Marco , Cuozzo Simone , Wilson Luc , Danieli Alberto , Bonanni Paolo , Pellegrino Giovanni
Published: July 2024

Patients with epilepsy are characterized by a dysregulation of excitation/inhibition balance (E/I). The assessment of E/I may inform clinicians during the diagnosis and therapy management, even though it is rarely performed. An accessible measure of the E/I of the brain represents a clinically relevant feature. Here, we exploited the exponent of the aperiodic component of the power spectrum of the electroencephalography (EEG) signal, as a non-invasive and cost-effective proxy of the E/I balance. We recorded resting-state activity with high-density EEG from 67 patients with temporal lobe epilepsy and 35 controls. We extracted the exponent of the aperiodic fit of the power spectrum from source-reconstructed EEG and tested differences between patients with epilepsy and controls. Spearman’s correlation was performed between the exponent and clinical variables (age of onset, epilepsy duration and neuropsychology) and cortical expression of epilepsy-related genes derived from the Allen Human Brain Atlas. Patients with temporal lobe epilepsy showed a significantly larger exponent, corresponding to inhibition-directed E/I balance, in bilateral frontal and temporal regions. Lower E/I in the left entorhinal and bilateral dorsolateral prefrontal cortices corresponded to a lower performance of short-term verbal memory. Limited to patients with temporal lobe epilepsy, we detected a significant correlation between the exponent and the cortical expression of GABRA1, GRIN2A, GABRD, GABRG2, KCNA2 and PDYN genes. EEG aperiodic exponent maps the E/I balance non-invasively in patients with epilepsy and reveals a close relationship between altered E/I patterns, cognition and genetics.
The neutrophil extracellular traps in neurological diseases: an update
Authors: Yu Xiaoping , Chen Zhaoyan , Bao Wei , Jiang Yaqing , Ruan Fei , Wu Di , Le Kai
Published: July 2024

Neutrophil extracellular traps (NETs) released by neutrophils are web-like DNA structures adhered to granulin proteins with bactericidal activity and can be an important mechanism for preventing pathogen dissemination or eliminating microorganisms. However, they also play important roles in diseases of other systems, such as the central nervous system. We tracked the latest advances and performed a review based on published original and review articles related to NETs and neurological diseases. Generally, neutrophils barely penetrate the blood–brain barrier into the brain parenchyma, but when pathological changes such as infection, trauma, or neurodegeneration occur, neutrophils rapidly infiltrate the central nervous system to exert their defensive effects. However, neutrophils may adversely affect the host when they uncontrollably release NETs upon persistent neuroinflammation. This review focused on recent advances in understanding the mechanisms and effects of NETs release in neurological diseases, and we also discuss the role of molecules that regulate NETs release in anticipation of clinical applications in neurological diseases.
Applying Machine Learning Models Derived From Administrative Claims Data to Predict Medication Nonadherence in Patients Self-Administering Biologic Medications for Inflammatory Bowel Disease
Authors: Rhudy Christian , Perry Courtney , Wesley Michael , Fardo David , Bumgardner Cody , Hassan Syed , Barrett Terrence , Talbert Jeffery
Published: July 2024

Background

Adherence to self-administered biologic therapies is important to induce remission and prevent adverse clinical outcomes in Inflammatory bowel disease (IBD). This study aimed to use administrative claims data and machine learning methods to predict nonadherence in an academic medical center test population.

Methods

A model-training dataset of beneficiaries with IBD and the first unique dispense of a self-administered biologic between June 30, 2016 and June 30, 2019 was extracted from the Commercial Claims and Encounters and Medicare Supplemental Administrative Claims Database. Known correlates of medication nonadherence were identified in the dataset. Nonadherence to biologic therapies was defined as a proportion of days covered ratio <80% at 1 year. A similar dataset was obtained from a tertiary academic medical center's electronic medical record data for use in model testing. A total of 48 machine learning models were trained and assessed utilizing the area under the receiver operating characteristic curve as the primary measure of predictive validity.

Results

The training dataset included 6998 beneficiaries (n = 2680 nonadherent, 38.3%) while the testing dataset included 285 patients (n = 134 nonadherent, 47.0%). When applied to test data, the highest performing models had an area under the receiver operating characteristic curve of 0.55, indicating poor predictive performance. The majority of models trained had low sensitivity and high specificity.

Conclusions

Administrative claims-trained models were unable to predict biologic medication nonadherence in patients with IBD. Future research may benefit from datasets with enriched demographic and clinical data in training predictive models.
Latent profiles of global electrical heterogeneity: the Hispanic Community Health Study/Study of Latinos
Authors: Tereshchenko Larisa G , Haq Kazi T , Howell Stacey J , Mitchell Evan C , Martínez Jesús , Hyde Jessica , Briceno Genesis , Pena Jose , Pocius Edvinas , Khan Akram , Soliman Elsayed Z , Lima João A C , Kapadia Samir R , Misra-Hebert Anita D , Kattan Michael W , Kansal Mayank M , Daviglus Martha L , Kaplan Robert
Published: July 2024

Aims

Despite the highest prevalence of stroke, obesity, and diabetes across races/ethnicities, paradoxically, Hispanic/Latino populations have the lowest prevalence of atrial fibrillation and major Minnesota code–defined ECG abnormalities. We aimed to use Latent Profile Analysis in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) population to obtain insight into epidemiological discrepancies.

Methods and results

We conducted a cross-sectional analysis of baseline HCHS/SOL visit. Global electrical heterogeneity (GEH) was measured as spatial QRS-T angle (QRSTa), spatial ventricular gradient azimuth (SVGaz), elevation (SVGel), magnitude (SVGmag), and sum absolute QRST integral (SAIQRST). Statistical analysis accounted for the stratified two-stage area probability sample design. We fitted a multivariate latent profile generalized structural equation model adjusted for age, sex, ethnic background, education, hypertension, diabetes, smoking, dyslipidaemia, obesity, chronic kidney disease, physical activity, diet quality, average RR’ interval, median beat type, and cardiovascular disease (CVD) to gain insight into the GEH profiles. Among 15 684 participants (age 41 years; 53% females; 6% known CVD), 17% had an increased probability of likely abnormal GEH profile (QRSTa 80 ± 27°, SVGaz −4 ± 21°, SVGel 72 ± 12°, SVGmag 45 ± 12 mVms, and SAIQRST 120 ± 23 mVms). There was a 23% probability for a participant of being in Class 1 with a narrow QRSTa (40.0 ± 10.2°) and large SVG (SVGmag 108.3 ± 22.6 mVms; SAIQRST 203.4 ± 39.1 mVms) and a 60% probability of being in intermediate Class 2.

Conclusion

A substantial proportion (17%) in the Hispanic/Latino population had an increased probability of altered, likely abnormal GEH profile, whereas 83% of the population was resilient to harmful risk factors exposures.
Chromosome-Level Assembly and Annotation of the Genome of the Endangered Giant Patagonian Bumble Bee Bombus dahlbomii
Authors: Martínez Lican , Zattara Eduardo E , Arbetman Marina P , Morales Carolina L , Masonbrink Rick E , Severin Andrew J , Aizen Marcelo A , Toth Amy L
Published: July 2024

This article describes a genome assembly and annotation for Bombus dahlbomii, the giant Patagonian bumble bee. DNA from a single, haploid male collected in Argentina was used for PacBio (HiFi) sequencing, and Hi-C technology was then used to map chromatin contacts. Using Juicer and manual curation, the genome was scaffolded into 18 main pseudomolecules, representing a high-quality, near chromosome-level assembly. The sequenced genome size is estimated at 265 Mb. The genome was annotated based on RNA sequencing data of another male from Argentina, and BRAKER3 produced 15,767 annotated genes. The genome and annotation show high completeness, with >95% BUSCO scores for both the genome and annotated genes (based on conserved genes from Hymenoptera). This genome provides a valuable resource for studying the biology of this iconic and endangered species, as well as for understanding the impacts of its decline and designing strategies for its preservation.