Full Spectrum Research Articles

Effects of OnabotulinumtoxinA on Allodynia and Interictal Burden of Patients with Chronic Migraine.

We primarily aimed to ascertain whether treatment with OnabotulinumtoxinA (BoNTA) might influence the extent of the interictal burden and cutaneous allodynia in patients with chronic migraine (CM). Seventy CM patients, who received three consecutive cycles of BoNTA, were studied. The interictal burden was assessed with the Migraine Interictal Burden Scale (MIBS-4), while cutaneous allodynia was examined with the Allodynia Symptom Checklist (ASC-12) together with PI-NRS VAS to obtain hair brushing scores, and then these were compared from baseline (T0) to the last efficacy evaluation follow-up (T1). Efficacy outcomes, mostly mean headache days (MHD) and "Headache Impact Test" scores, were also assessed between T0 and T1. BONTA improved the interictal burden, with a decrease in MIBS-4 scoring by an average of -7 at T1, compared to baseline (p < 0.001). The percentage of patients with a moderate/severe interictal burden was substantially decreased. Likewise, BoNTA reduced the extent of cutaneous allodynia, with a significant reduction in both the ASC-12 (1 vs. 6; p < 0.001) and PI-NRS VAS (1 vs. 5; p < 0.001) to hair brushing median scores at T1, compared to baseline. Reduced MHD rates were significantly associated with a smaller interictal burden at T1. The efficacy of BoNTA, with a significant reduction in MHD and HIT-6 scores at T1 compared to T0, was re-confirmed. BoNTA resulted in a statistically significant reduction in the interictal burden and also improved cutaneous allodynia. The reduction in ictal burden was associated with the down-scaling of the interictal burden. Hence, BoNTA improved the full spectrum of migraine impairment by diminishing the clinical expression of central sensitization.

Genome sequencing as a generic diagnostic strategy for rare disease

BackgroundTo diagnose the full spectrum of hereditary and congenital diseases, genetic laboratories use many different workflows, ranging from karyotyping to exome sequencing. A single generic high-throughput workflow would greatly increase efficiency. We assessed whether genome sequencing (GS) can replace these existing workflows aimed at germline genetic diagnosis for rare disease.MethodsWe performed short-read GS (NovaSeq™6000; 150 bp paired-end reads, 37 × mean coverage) on 1000 cases with 1271 known clinically relevant variants, identified across different workflows, representative of our tertiary diagnostic centers. Variants were categorized into small variants (single nucleotide variants and indels < 50 bp), large variants (copy number variants and short tandem repeats) and other variants (structural variants and aneuploidies). Variant calling format files were queried per variant, from which workflow-specific true positive rates (TPRs) for detection were determined. A TPR of ≥ 98% was considered the threshold for transition to GS. A GS-first scenario was generated for our laboratory, using diagnostic efficacy and predicted false negative as primary outcome measures. As input, we modeled the diagnostic path for all 24,570 individuals referred in 2022, combining the clinical referral, the transition of the underlying workflow(s) to GS, and the variant type(s) to be detected.ResultsOverall, 95% (1206/1271) of variants were detected. Detection rates differed per variant category: small variants in 96% (826/860), large variants in 93% (341/366), and other variants in 87% (39/45). TPRs varied between workflows (79–100%), with 7/10 being replaceable by GS. Models for our laboratory indicate that a GS-first strategy would be feasible for 84.9% of clinical referrals (750/883), translating to 71% of all individuals (17,444/24,570) receiving GS as their primary test. An estimated false negative rate of 0.3% could be expected.ConclusionsGS can capture clinically relevant germline variants in a ‘GS-first strategy’ for the majority of clinical indications in a genetics diagnostic lab.

Stellar populations of massive early-type galaxies observed by MUSE

ABSTRACT Stellar population studies of massive early-type galaxies (ETGs) suggest that the stellar initial mass function may not be universal. In particular, the centres of ETGs seem to contain an excess of low-mass dwarf stars compared to our own Galaxy. Through high-resolution data from MUSE (Multi Unit Spectroscopic Explorer), we carry out a detailed study of the stellar populations of eight massive ETGs. We use full spectrum fitting to determine ages, element abundances, and initial mass function (IMF) slopes for spatially binned spectra. We measure flat gradients in age and [Mg/Fe] ratio, as well as negative gradients in metallicity and [Na/Fe]. We detect IMF gradients in some galaxies, with the centres hosting bottom-heavy IMFs and mass excess factors between 1.5 and 2.5 compared to a Kroupa IMF. The IMF slope below 0.5 M$_\odot$varies for our galaxy sample between 1 and 2.8, with negative radial gradients, while the IMF slope between 0.5 and 1M$_\odot$ has a steep value of $\sim$3 with mildly positive gradients for most galaxies. For M87, we find excellent agreement with the dynamical mass-to-light ratio (M/L) as a function of radius. For the other galaxies, we find systematically higher M/L from stellar populations compared to orbit-based dynamical analysis of the same data. This discrepancy increases with NaI strength, suggesting a combination of calibration issues of this line and correlated uncertainties.

Patient With Parkinson Disease and Care Partner Perceptions of Key Domains Affecting Health-Related Quality of Life: Systematic Review

To effectively customize Parkinson disease (PD) programs, it is important to incorporate the "individual's voice" and have a thorough understanding of the symptom priorities of people with PD (PwP) and care partners (CP). In this convergent integrated mixed-method systematic review, we aimed to analyze qualitative and quantitative evidence of PD motor and nonmotor symptoms affecting health-related quality of life (HRQOL) in PwP and CP, comparing priorities across different levels of disease severity. We searched MEDLINE, PsycINFO, Web of Science, Embase, and Scopus; ProQuest Dissertations and Theses Global; and the Michael J. Fox Foundation Data Resources for studies published up to June 29, 2022. We included qualitative, quantitative, and mixed-method studies investigating PD symptom priorities among PwP and CP. We critically appraised eligible studies for methodological quality using the Mixed-Methods Appraisal Tool. Derived terms were mapped and coded according to thematic attribution. Independent syntheses of qualitative and quantitative evidence and transformation of quantitative data into qualitative formats were performed. Of the 7,716 identified studies, we included 70 that provided qualitative (n = 13), quantitative (n = 53), and mixed (n = 4) evidence. We included 604 mapped terms representing 11 PwP-identified and CP-identified motor and nonmotor symptom categories. Across all PD stages, both PwP and CP considered 5 domains more affecting their HRQOL, namely: "motor functionality," "mood," "cognition," "gait, balance, posture, and falls," and "nighttime sleep disorders." In early disease, PwP and CP considered "mood" the domain that most affected their HRQOL. In advanced PD, PwP considered "pain" the domain that most affects their HRQOL, while CP considered "psychiatric symptoms." The domain "gait, balance, posture, and falls" was equally considered by both PwP and CP as the second domain that most affects their HRQOL in the advanced stage of PD. The ranking of the priority of symptoms is largely shared by PwP and CP, and motor symptom priorities dominate the full disease spectrum. However, the nonmotor symptom priorities shift according to the disease severity stage. Tailored care and research require that providers consider these shifting priorities and incorporate the "individual's voice" into treatment decisions.

Impact of image registration errors on the quality of hyperspectral images in imaging static Fourier transform spectrometry

Imaging static Fourier transform spectrometry (isFTS) is used for pushbroom airborne or spaceborne hyperspectral remote sensing. In isFTS, a static two-wave interferometer imprints linear interference fringes over the image of the scene, so that the spectral information is multiplexed over several instantaneous images, and numerical reconstruction is needed to recover the full spectrum for each pixel. The image registration step is crucial since insufficient accuracy leads to artefacts on the images and the estimated spectra. In order to investigate these artifacts, we performed a theoretical study and designed a simulation program. We established that registration errors create crenellated spatial patterns, the magnitude of which depends on the radiance gradient of the scene, the amplitude of the registration error, and the wavelength. In the case of sinusoidal perturbations, which may correspond for instance to mechanical vibrations of the carrier, we established that spurious peaks appear on the spectrum, similarly to what happens in dynamic FTS, but with spatial patterns specific to static interferometers.

Effects of protection and temperature variation on temporal stability in a marine reserve network.

Understanding the drivers of ecosystem stability has been a key focus of modern ecology as the impacts of the Anthropocene become more prevalent and extreme. Marine protected areas (MPAs) are tools used globally to promote biodiversity and mediate anthropogenic impacts. However, assessing the stability of natural ecosystems and responses to management actions is inherently challenging due to the complex dynamics of communities with many interdependent taxa. Using a 12-year time series of subtidal community structure in an MPA network in the Channel Islands (United States), we estimated species interaction strength (competition and predation), prey species synchrony, and temporal stability in trophic networks, as well as temporal variation in sea surface temperature to explore the causal drivers of temporal stability at community and metacommunity scales. At the community scale, only trophic networks in MPAs at Santa Rosa Island showed greater temporal stability than reference sites, likely driven by reduced prey synchrony. Across islands, competition was sometimes greater and predation always greater in MPAs compared with reference sites. Increases in interaction strength resulted in lower temporal stability of trophic networks. Although MPAs reduced prey synchrony at the metacommunity scale, reductions were insufficient to stabilize trophic networks. In contrast, temporal variation in sea surface temperature had strong positive direct effects on stability at the regional scale and indirect effects at the local scale through reductions in species interaction strength. Although MPAs can be effective management strategies for protecting certain species or locations, our findings for this MPA network suggest that temperature variation has a stronger influence on metacommunity temporal stability by mediating species interactions and promoting a mosaic of spatiotemporal variation in community structure of trophic networks. By capturing the full spectrum of environmental variation in network planning, MPAs will have the greatest capacity to promote ecosystem stability in response to climate change.

CBD products: Labeling accuracy of an obscure niche market

In recent years, there has been an increased availability of cannabis products in Europe, despite strict regulations. Numerous manufacturers of niche products promote cannabidiol (CBD) and Cannabis sativa (C. sativa) as ingredients, often in ambiguous ways leading to consumer confusion. The aim of this study was to analyze a diverse range of foods, food supplements, health related products and other consumer products (e.g. vapes) associated with C. sativa/CBD in order to determine whether the declared and promised ingredients are present in the products and how these comply to current legal regulations. We have established a HPLC-UV method to quantify the most important cannabinoids, namely the legally important THC and THCA, and the CBD/CBDA. All of the 35 analyzed products met the legally required limit for THC/THCA. A total of 27 of the samples explicitly listed CBD contents. In 33% of the samples, the analyzed value matched the content given on the label, 26% exceeded the declared CBD content, while 41% contained lower amounts. CBD products with an unclear or not defined CBD content, were mostly below the limit of detection (LoD). Products promising “full spectrum C. sativa extracts” were further screened by GC-MS method to detect additional naturally-occurring cannabinoids, to verify the use of C. sativa plant material/extracts as the source of CBD. No further cannabinoids could be detected in one out of eight products claiming the use of C. sativa extracts.This study shows, that this niche market is still a constantly evolving product sector, depending on the type and origin of the products, there may be significant discrepancies between the marketing and the actual ingredients contained, making the market less transparent for consumers.

Preparation of solid-solid phase change composites and their solar-interfacial water evaporation performance

Solar powered interfacial evaporation materials are widely used in seawater desalination. But solar energy is intermittent. To solve this problem, researchers combined phase change materials (PCMs) with interfacial evaporation materials. Many PCMs are loaded into the interface evaporation matrix material through physical blending, which may cause leakage problems during long-term use, leading to secondary water pollution. We have developed a novel interfacial evaporation material that continuously and efficiently vaporizes clean water under intermittent sunlight to address these issues. The solid-solid PCMs (BC/PVA/GO-g-LA-SSPCMs) were obtained by chemical grafting of PCMs lauric acid (LA) and graphene oxide (GO), and the substrate material bacterial fibrin (BC) was modified by polyvinyl alcohol (PVA). The material achieved light absorption of 88.8% in the full spectrum range. Under 1 kW m−2 light, the evaporation rate reaches 3.4 kg m−2h−1, and the solar-thermal conversion efficiency is 94.2%. In the dark, the evaporation rate is 1.05 kg m−2h−1, and the solar-thermal conversion efficiency is 49.5%. 15 light-dark cycle experiments and harsh environments (high concentration brine, acidic solution, alkaline solution, dye wastewater) showed high efficiency and stable evaporation performance. The material cost of the evaporator is about 0.98 USD·m−2, and the solar-thermal quality factor is 4.64, which is higher than that of most reported materials. In short, BC/PVA/GO-g-LA-SSPCMs provides a new idea for the future design and development of solar-thermal conversion materials to achieve efficient and continuous saltwater desalination and wastewater purification under intermittent solar-irradiation.

Multielement simultaneous quantitative analysis of trace elements in stainless steel via full spectrum laser-induced breakdown spectroscopy

Laser-Induced Breakdown Spectroscopy (LIBS) instruments are increasingly recognized as valuable tools for detecting trace metal elements due to their simplicity, rapid detection, and ability to perform simultaneous multi-element analysis. Traditional LIBS modeling often relies on empirical or machine learning-based feature band selection to establish quantitative models. In this study, we introduce a novel approach—simultaneous multi-element quantitative analysis based on the entire spectrum, which enhances model establishment efficiency and leverages the advantages of LIBS. By logarithmically processing the spectra and quantifying the cognitive uncertainty of the model, we achieved remarkable predictive performance (R2) for trace elements Mn, Mo, Cr, and Cu (0.9876, 0.9879, 0.9891, and 0.9841, respectively) in stainless steel. Our multi-element model shares features and parameters during the learning process, effectively mitigating the impact of matrix effects and self-absorption. Additionally, we introduce a cognitive error term to quantify the cognitive uncertainty of the model. The results suggest that our approach has significant potential in the quantitative analysis of trace elements, providing a reliable data processing method for efficient and accurate multi-task analysis in LIBS. This methodology holds promising applications in the field of LIBS quantitative analysis.

Retinomorphic Photonic Synapses for Mimicking Ultraviolet Radiation Sensing and Damage Imaging

AbstractPhotonic synapses integrate sensing and processing within a single device, making them promising candidates for emulating the visual perception of a biological retina. Most retinomorphic photonic synapses achieve image pre‐processing by differentially responding to red, green, and blue (RGB). However, the impact of invisible ultraviolet (UV) light on the retina remains insufficiently explored, hindering the perception of the full spectrum by retinomorphic devices. Herein, a photonic synapse is constructed with strong UV absorption of Poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐co‐(4,4′‐(N‐(4‐sec‐butylphenyl) diphenylamine)] (TFB) as photosensitive layer. The device exhibits synaptic properties of long‐term memory (LTM) and short‐term memory (STM) at different UV radiation stages. Extracting the electrical conductance of the device under UV radiation generates patterns of different resolutions, facilitating the simulation of retinal damage's impact on object perception. Moreover, an electronic eye system, incorporating the photonic synapse under UV radiation, successfully replicates pupil constriction and eye‐closing behaviors akin to those observed in a real biological eye. This result underscores the authenticity of retinomorphic devices, expending a novel concept for the future development of visuomorphic computing.

Design of Multifunctional Color Routers with Kerker Switching Using Generative Adversarial Networks

AbstractTo achieve optoelectronic devices with high resolution and efficiency, there is a pressing need for optical structural units that possess an ultrasmall footprint yet exhibit strong controllability in both the frequency and spatial domains. For dielectric nanoparticles, the overlap of electric and magnetic dipole moments can scatter light completely forward or backward, which is called Kerker theory. This effect can expand to any multipoles and any directions, re‐named as generalized Kerker effect, and realize controllable light manipulation at full space and full spectrum using well‐designed dielectric structures. However, the complex situations of multipole couplings make it difficult to achieve structural design. Here, generative artificial intelligence (AI) is utilized to facilitate multi‐objective‐oriented structural design, wherein the study leverages the concept of “combined spectra” that consider both spectra and direction ratios as labels. The proposed generative adversarial network (GAN) is named as DDGAN (double‐discriminator GAN) that discriminates both images and spectral labels. Using trained networks, the simultaneous design for scattering color and directivities, RGB color routers, as well as narrowband light routers is achieved. Notably, all generated structures possess a footprint &lt;600 × 600 nm indicating their potential applications in optoelectronic devices with ultrahigh resolution.

Establishment and comparison of in situ detection models for foodborne pathogen contamination on mutton based on SWIR-HSI.

Rapid and accurate detection of food-borne pathogens on mutton is of great significance to ensure the safety of mutton and its products and the health of consumers. The feasibility of short-wave infrared hyperspectral imaging (SWIR-HSI) in detecting the contamination status and species of Escherichia coli (EC), Staphylococcus aureus (SA) and Salmonella typhimurium (ST) contaminated on mutton was explored. The hyperspectral images of uncontaminated and contaminated mutton samples with different concentrations (108, 107, 106, 105, 104, 103 and 102 CFU/mL) of EC, SA and ST were acquired. The one dimensional convolutional neural network (1D-CNN) model was constructed and the influence of structure hyperparameters on the model was explored. The effects of different spectral preprocessing methods on partial least squares-discriminant analysis (PLS-DA), support vector machine (SVM) and 1D-CNN models were discussed. In addition, the feasibility of using the characteristic wavelength to establish simplified models was explored. The best full band model was the 1D-CNN model with the convolution kernels number of (64, 16) and the activation function of tanh established by the original spectra, and its accuracy of training set, test set and external validation set were 100.00, 92.86 and 97.62%, respectively. The optimal simplified model was genetic algorithm optimization support vector machine (GA-SVM). For discriminating the pathogen species, the accuracies of SVM models established by full band spectra preprocessed by 2D and all 1D-CNN models with the convolution kernel number of (32, 16) and the activation function of tanh were 100.00%. In addition, the accuracies of all simplified models were 100.00% except for the 1D-CNN models. Considering the complexity of features and model calculation, the 1D-CNN models established by original spectra were the optimal models for pathogenic bacteria contamination status and species. The simplified models provide basis for developing multispectral detection instruments. The results proved that SWIR-HSI combined with machine learning and deep learning could accurately detect the foodborne pathogen contamination on mutton, and the performance of deep learning models were better than that of machine learning. This study can promote the application of HSI technology in the detection of foodborne pathogens on meat.

Deep Learning for Polarization Optical System Automated Design

Aiming at the problem that traditional design methods make it difficult to control the polarization aberration distribution of optical systems quickly and accurately, this study proposes an automatic optimization design method for polarization optical systems based on deep learning. The unsupervised training model based on ray tracing and polarized ray tracing was constructed by learning the reference lens structural feature data from the optical lens library, and the generalization ability of the deep neural network model was improved to achieve the automatic optimization design of the polarized optical system. The design results show that the optical system structure optimized by the network model is close to the reference lens in the full field of view and the full spectrum and that the optical system structure can be designed for different focal length requirements. The success rate of 1 million groups of initial structures designed is better than 96.403%, and the polarization effect of the optical system is effectively controlled. The proposed deep learning approach to optical design provides a new solution for future complex optical systems and also provides an effective way to improve the design accuracy of special optical systems such as polarization optical systems.

Proposing the "Continuum of UTI" for a Nuanced Approach to Diagnosis and Management of Urinary Tract Infections.

Patients with suspected UTIs are categorized into 3 clinical phenotypes based on current guidelines: no UTI, asymptomatic bacteriuria (ASB), or UTI. However, all patients may not fit neatly into these groups. Our objective was to characterize clinical presentations of patients who receive urine tests using the "continuum of UTI" approach. This was a retrospective cohort study of a random sample of adult noncatheterized inpatient and emergency department encounters with paired urinalysis and urine cultures from 5 hospitals in 3 states between January 01, 2017, and December 31, 2019. Trained abstractors collected clinical (eg, symptom) and demographic data. A focus group discussion with multidisciplinary experts was conducted to define the continuum of UTI, a 5-level classification scheme that includes 2 new categories: lower urinary tract symptoms/other urologic symptoms and bacteriuria of unclear significance. The newly defined continuum of UTI categories were compared to the current UTI classification scheme. Of 220,531 encounters, 3392 randomly selected encounters were reviewed. Based on the current classification scheme, 32.1% (n = 704) had ASB and 53% (n = 1614) did not have a UTI. When applying the continuum of UTI categories, 68% of patients (n = 478) with ASB were reclassified as bacteriuria of unclear significance and 29% of patients (n = 467) with "no UTI" were reclassified to lower urinary tract symptoms/other urologic symptoms. Our data suggest the need to reframe our conceptual model of UTI vs ASB to reflect the full spectrum of clinical presentations, acknowledge the diagnostic uncertainty faced by frontline clinicians, and promote a nuanced approach to diagnosis and management of UTIs.

Navigating the Cyber Kill Chain: A modern approach to pentesting

The Cyber Kill Chain is a strategic model that outlines the stages of a cyberattack, from initial reconnaissance to achieving the final objective. This framework is often mirrored in penetration testing (pentest), a legal and authorized simulated attack on a computer system performed to evaluate its security. By understanding the steps in the Cyber Kill Chain, penetration testers can mimic the strategies of malicious attackers, exploring vulnerabilities at each stage of the chain. This approach allows organizations to evaluate their defensive measures across the full spectrum of an attack, identifying weaknesses and enhancing their security protocols accordingly. In essence, the Cyber Kill Chain provides a roadmap for pen-testers to systematically evaluate an organization's cyber defences. The research method of this article involves a systematic analysis of the Cyber Kill Chain model, examining how penetration testers can employ this strategic framework to emulate the tactics of malicious attackers and identify methodology at each stage of the chain.

A Full-Spectrum ZnS Photocatalyst with Gradient Distribution of Atomic Copper Dopants and Concomitant Sulfur Vacancies for Highly Efficient Hydrogen Evolution.

A rarely discussed phenomenon in the realm of photocatalytic materials involves the presence of gradient distributed dopants and defects from the interior to the surface. This intriguing characteristic has been successfully achieved in the case of ZnS through the incorporation of atomic monovalent copper ions (Cu+) and concurrent sulfur vacancies (Vs), resulting in a photocatalyst denoted as G-CZS1-x. Through the cooperative action of these atomic Cu dopants and Vs, G-CZS1-x significantly extends its photoabsorption range to encompass the full spectrum (200-2100 nm), which improves the solar utilization ability. This alteration enhances the efficiency of charge separation and optimizes Δ(H*) (free energy of hydrogen adsorption) to approach 0 eV for the hydrogen evolution reaction (HER). It is noteworthy that both surface-exposed atomic Cu and Vs act as active sites for photocatalysis. G-CZS1-x exhibits a significant H2 evolution rate of 1.01 mmol h-1 in the absence of a cocatalyst. This performance exceeds the majority of previously reported photocatalysts, exhibiting approximately 25-fold as ZnS, and 5-fold as H-CZS1-x with homogeneous distribution of equal content Cu dopants and Vs. In contrast to G-CZS1-x, the H adsorption on Cu sites for H-CZS1-x (ΔG(H*) = -1.22 eV) is excessively strong to inhibit the H2 release, and the charge separation efficiency for H-CZS1-x is relatively sluggish, revealing the positive role of a gradient distribution model of dopants and defects on activity enhancement. This work highlights the synergy of atomic dopants and defects in advancing photoactivity, as well as the significant benefit of the controllable distribution model of dopants and defects for photocatalysis.

Single-photon counting detectors for diffraction-limited light sources

When first introduced, single-photon counting detectors reshaped crystallography at synchrotrons. Their fast readout speed enabled, for example, shutter-less data collection and fine slicing of the rotation angle and boosted the development of new experimental techniques like ptychography. Under optimal conditions, single-photon counting detectors provide an unlimited dynamic range with image noise only limited by the Poisson statistics of the incoming photons. Counting the pulses from individual photons, essentially what made the detectors so successful, also causes the main drawback, which is the loss of efficiency at high photon fluxes due to pulse pileup in the analog front end. To fully take advantage of diffraction-limited light sources, the next-generation single-photon counters need to improve their count rate capabilities in the same order of magnitude as the increased flux. Moreover, fast frame rates (a few kHz) are required to cope with the shorter dwell time achievable, thanks to the higher flux. Detector architecture with multiple comparators and counters can open new possibilities for energy-resolved imaging, while interpixel communication can overcome the issues arising from charge sharing and reduce the loss of efficiency at the pixel corners. Coupling single-photon counting detectors to high-Z sensors for hard X-ray detection (&gt;20 keV) and to low-gain avalanche diodes (LGADs) for soft X-rays is also necessary to make use of the increased coherence of the new light sources over the full radiation spectrum. In this paper, we present possible strategies to improve the performance of single-photon counting detectors at the fourth-generation synchrotron sources and compare them to charge integrating detectors.

(026) Ten Years of Authorship by Women in Sexual Medicine Journals: Are We Making Progress?

Abstract Introduction Women are historically underrepresented in Urology, but the demographics are slowly changing. As of 2023, only 10.9% of urology attendings are women; however, women represent 37% of the accepted residency class of 2028. With increasing representation of women in urology, we hypothesized this would reflect in women’s authorship patterns in published manuscripts. Objective We sought to identify if the increasing representation of women in urology is reflected in first or last authorship in sexual medicine journals. Methods All manuscripts published in the Journal of Sexual Medicine and Sexual Medicine from 2013 to 2023 were reviewed. Original research manuscripts were included; manuscripts submitted under Psychology subsections, Paraphilia subsections, as well as systematic reviews, meta-analyses, communications, commentaries, replies, and those involving psychometrics were excluded. Single author manuscripts were classified under first author for the analysis. First and last authors were identified and internet search was performed to best determine gender, relying on, in order of preference: listed pronouns, picture, or traditionally masculine versus feminine name. We recognize this method of determining gender identity based on conventional gender presentations is imperfect and may not represent the full spectrum of gender diversity of the included authors. Institutional information was also collected. Chi-square analyses and odds ratio were performed to compare authorship patterns. Results 2156 manuscripts met criteria, 1717 from Journal of Sexual Medicine and 439 from Sexual Medicine. From 2013-2023, women composed 44.1% (951/2156) of first authors and 32.5% (691/2156) of last authors. Overall, first authorship by women increased from 2013 (110/271, 41%) to 2023 (59/104, 57%) (p&amp;lt;0.005) [Figure 1]. In 2022 and 2023, women were the majority of first authors (50.3% and 56.7%, respectively). Manuscripts with women as first authors were more likely to have women as last authors (OR: 1.64, CI: 1.45-1.86, p&amp;lt;0.0001). In the US and Canada, the majority of first (61.1%, 214/350) and last (61.6%, 157/254) authors who are women came from public rather than private institutions, but this was non-significant. First authors who are women predominantly came from North America (38.6%), Europe (36.3%), Asia (17.7%), South America (3.9%), Australia/New Zealand (2.6%), followed by Africa (0.9%); last authors who are women had a similar breakdown by continent. The greatest percentage of authorship by women came from Australia/New Zealand with 50.8% (32/63) of first authors and 45% (27/60) of last authors. The largest disparity was seen in Africa with 22.2% (10/45) of first authors and a mere 16.3% (7/43) of last authors being women. Conclusions Authorship by women in sexual medicine journals is increasing over time, with positive trends observed in both first and last authorship. The effect is more pronounced in first authorship as compared to last, possibly reflecting the increasing numbers of trainees who are women. Manuscripts with women as first authors are correlated with last authors who are women, supporting a positive relationship in gender concordant mentorship. Disclosure No.

A hyperspectral deep learning attention model for predicting lettuce chlorophyll content

BackgroundThe phenotypic traits of leaves are the direct reflection of the agronomic traits in the growth process of leafy vegetables, which plays a vital role in the selection of high-quality leafy vegetable varieties. The current image-based phenotypic traits extraction research mainly focuses on the morphological and structural traits of plants or leaves, and there are few studies on the phenotypes of physiological traits of leaves. The current research has developed a deep learning model aimed at predicting the total chlorophyll of greenhouse lettuce directly from the full spectrum of hyperspectral images.ResultsA CNN-based one-dimensional deep learning model with spectral attention module was utilized for the estimate of the total chlorophyll of greenhouse lettuce from the full spectrum of hyperspectral images. Experimental results demonstrate that the deep neural network with spectral attention module outperformed the existing standard approaches, including partial least squares regression (PLSR) and random forest (RF), with an average R2 of 0.746 and an average RMSE of 2.018.ConclusionsThis study unveils the capability of leveraging deep attention networks and hyperspectral imaging for estimating lettuce chlorophyll levels. This approach offers a convenient, non-destructive, and effective estimation method for the automatic monitoring and production management of leafy vegetables.

Conservative Treatment and Secondary Prevention of PAD (Peripheral Artery Disease)

The immediate and long-term success of endovascular and surgical revascularization crucially depends on the conservative treatment of the PAD. The "gentle, preserving" treatment should be understood as he absolutely basic therapy for every PAD patient, because conservative treatment adresses the "big five" of atherosclerotic risk factors. This article presents both the full spectrum of pharmacological and non-pharmacological strategies.