Light Levels Research Articles

Translation of paclitaxel-induced peripheral neurotoxicity from mice to patients: the importance of model selection.

Paclitaxel-induced peripheral neurotoxicity (PIPN) is a potentially dose-limiting side effect in anticancer chemotherapy. Several animal models of PIPN exist, but their results are sometimes difficult to be translated into the clinical setting. We compared 2 widely used PIPN models characterized by marked differences in their methodologies. Female C57BL/6JOlaHsd mice were used, and they received only paclitaxel vehicle (n = 38) or paclitaxel via intravenous injection (n = 19, 70 mg/kg) once a week for 4 weeks (Study 1) or intraperitoneally (n = 19, 10 mg/kg) every 2 days for 7 times (Study 2). At the end of treatment and in the follow-up, mice underwent behavioral and neurophysiological assessments of PIPN. At the same time points, some mice were killed and dorsal root ganglia, skin, and sciatic and caudal nerve samples underwent pathological examination. Serum neurofilament light levels were also measured. The differences in the neurotoxicity parameters were analyzed using a nonparametric Mann-Whitney test, with significance level set at P < 0.05. Study 1 showed significant and consistent behavioral, neurophysiological, pathological, and serological changes induced by paclitaxel administration at the end of treatment, and most of these changes were still evident in the follow-up period. By contrast, study 2 evidenced only a transient small fiber neuropathy, associated with neuropathic pain. Our comparative study clearly distinguished a PIPN model recapitulating all the clinical features of the human condition and a model showing only small fiber neuropathy with neuropathic pain induced by paclitaxel.

Augmented dataset for multidimensional ballast segmentation and evaluation

Ballast plays an important role as a railway track supporting structure against repeated loading. Ballast degradation results in poor drainage, lateral instability, excessive settlement, service interruptions, and safety concerns. Therefore, utilizing efficient methods for evaluating ballast fouling is important to ensure safe railroad operations. Emerging computer vision approaches have been effectively incorporated into the ballast inspection processes to enhance their accuracy and robustness. Owing to the inherent data-driven nature of deep learning approaches, the efficacy of the developed model heavily depends on the quality of the training dataset, revealing an urgent need for a comprehensive and high-quality annotated ballast aggregate dataset. In this study, a multidimensional ballast aggregate dataset has been established which contains realistic data collected from field and laboratory setups, augmented by data produced by a synthetic ballast particle generator. In the dataset, the 2D data comprised ballast images with 2D annotations (masks) for localizing the particles in the images. The 3D data comprises height maps, point clouds, and 3D annotations for particle localization. The collected data included various environmental lighting levels and fouling conditions to ensure adequate coverage and diversity in the training dataset. A 2D ballast particle segmentation model previously developed by the authors was trained using an augmented dataset and demonstrated reliable and accurate results in field ballast inspections. The proposed dataset will be utilized in future studies, including 3D ballast particle segmentation and shape completion, to aid in the inspection and investigative methods for effective ballast maintenance.

Light competition drives species replacement during secondary tropical forest succession

Light competition is thought to drive successional shifts in species dominance in closed vegetations, but few studies have assessed this for species-rich and vertically structured tropical forests. We analyzed how light competition drives species replacement during succession, and how cross-species variation in light competition strategies is determined by underlying species traits. To do so, we used chronosequence approach in which we compared 14 Mexican tropical secondary rainforest stands that differ in age (8–32 year-old). For each tree, height and stem diameter were monitored for 2 years to calculate relative biomass growth rate (RGR, the aboveground biomass gain per unit aboveground tree biomass per year). For each stand, 3D light profiles were measured to estimate individuals’ light interception to calculate light interception efficiency (LIE, intercepted light per unit biomass per year) and light use efficiency (LUE, biomass growth per intercepted light). Throughout succession, species with higher RGR attained higher changes in species dominance and thus increased their dominance over time. Both light competition strategies (LIE and LUE) increased RGR. In early succession, a high LIE and its associated traits (large crown leaf mass and low wood density) are more important for RGR. During succession, forest structure builds up, leading to lower understory light levels. In later succession, a high LUE and its associated traits (high wood density and leaf mass per area) become more important for RGR. Therefore, successional changes in relative importance of light competition strategies drive shifts in species dominance during tropical rainforest succession.

Adaptive display white point under various ambient conditions

AbstractDisplay technologies have been developed to adjust the display brightness and color under different viewing conditions, providing better viewing experiences to users. Solutions have been proposed to adjust the display white point according to the ambient light condition, which roots into the underlying chromatic adaptation mechanism in the human visual system. This study was carefully designed to reveal the necessity to consider the ambient light level and display luminance together, which affects the viewing mode, when adjusting the adaptive display white point. The results clearly suggested that when the display luminance was greater than the ambient light diffuse white luminance, the display was viewed in the self‐luminous mode and the display white point was not significantly affected by the ambient light chromaticities. In contrast, when the display luminance was lower than the ambient light diffuse white luminance, the display was viewed in the surface mode and the ambient light chromaticities had a significant effect on the display white point, especially when the surround ratio was high.

The Efficacy of Horizontal Adjustable Bent Louver Shading for Enhancing Daylighting Performance in Walk-Up Apartment Buildings

This paper addressed the challenges posed by the limited windows and restricted areas in walk-up flats in Indonesia, resulting in improper indoor daylight performance. The study proposes using outdoor horizontally bent, adjustable louver screens as daylight reflectors to overcome this issue and improve daylighting performance in apartment buildings. The quasi-experimental technique implemented the Radiance Desktop Plug-in Version 1.02 and Ecotect 2011 lighting software. Variables, such as slat shading geometry, i.e., flat, one-bent, two-bent slats, and rotation opening angles, i.e., 30°, 45°, 60°, and 90°, were examined for interior daylight performance regarding daylight intensity and distribution. The findings indicate that although shading can reduce the average lighting level in a room, shading types with bents can improve daylight performance in another important aspect, namely achieving a more even distribution. The most effective shading technique for harvesting and distributing daylight evenly in tropical walk-up apartments was a two-bent slat type, particularly with opening angles of 90°. The results also demonstrate that louvers with multiple bent slat geometry are particularly effective in reflecting high altitudes of incident light often encountered in tropical regions and scattering the incoming light evenly into the innermost area of the room.

Neither Corpus Nor Edition: Building a Pipeline to Make Data Analysis Possible on Medieval Arabic Commentary Traditions

We have built a suite of tools in Python to proficiently analyze text reuse and intertextuality for a specific kind of set of medieval Arabic texts (commentaries) available in print. We take these printed editions, scan them, pre-process the images, give it to an OCR engine, clean the results, and store it in a data structure that mimics the explicit intertextual relation the texts have, and continue to perform data analysis on it. Digital approaches to medieval Arabic texts have either been at the micro-level in what has become known as a ‘digital edition’, i.e. the digital representation of one text, densely annotated, most commonly in TEI-XML, or it has been done at the macro-level in what is called a ‘digital corpus’, consisting of thousands of loosely encoded and sparsely annotated plain text files, accompanied by an entire infrastructure and high-performing software to perform broadly scoped queries. The micro-level generally is at the level of tens of thousands of words while the macro-level can be at the level of over a billion words. The micro-level is explicitly designed to be human readable first, while the macro-level is built to be machine readable first. At the micro-level, every little detail needs to be correct and in order, while at the macro-level a fairly large margin of error is still negligible as a mere rounding error. Amidst these levels we have been seeking a meso-level of digital analysis: neither edition nor corpus, but rather a group of texts at the level of hundreds of thousands to millions of words, with a small but perceptible margin of error, and a light but noticeable level of annotations, principally geared towards machine readability, but with ample opportunity for visual inspection and manual correction. In this paper we explain the rationale for our approach, the technical achievements it has led us to, and the results we so far obtained.

YOLOv5s-CEDB: A robust and efficiency Camellia oleifera fruit detection algorithm in complex natural scenes

To solve the problem of poor recognition accuracy caused by various colors, uneven distribution, and occlusion by branches and leaves of Camellia oleifera fruits under natural growth conditions, this study proposes an improved deep learning network, YOLOv5s-CEDB, for Camellia oleifera fruit detection based on YOLOv5s. Coordinate Attention Mechanism (CoordAtt), Deformable Convolution (DConv), and Explicit Visual Center (EVC) are introduced to enhance the network’s local and global feature extraction performance. To improve the detection performance for small and dense targets, the feature fusion module of the network was replaced with the designed light-bidirectional feature pyramid (light-BiFPN) structure. GhostConv was used to reduce the parameters and inference speed of the structure. A dataset with different light conditions, colors, and density levels of Camellia oleifera fruits was established, and performance evaluation experiments were conducted. Experimental results showed that the mean Average Precision (mAP) and F1-score of the designed YOLOv5s-CEDB network reached 91.4 % and 89.6 %, respectively, which were 2.6 % and 3.6 % higher than those of the original YOLOv5s model, respectively, and the influencing frame rate arrived at 37.6 FPS. Under different colors, distribution densities, occlusion scenarios, and light intensities, the detection accuracy of the YOLOv5s-CEDB network model was significantly better than those of the YOLOv5s, YOLOv8s and Faster-RCNN networks. It was verified that the proposed YOLOv5s-CEDB network could significantly improve the accuracy and stability of Camellia oleifera fruit detection, satisfying the requirements of yield estimation and intelligent harvesting.

Spectroscopic Observations of the Solar Corona during the 2017 August 21 Total Solar Eclipse: Comparison of Spectral Line Widths and Doppler Shifts between Open and Closed Magnetic Structures

The spectroscopic observations presented here were acquired during the 2017 August 21 total solar eclipse (TSE) with a three-channel partially multiplexed imaging spectrometer operating at extremely high orders (>50). The 4 R ⊙ extent of the slit in the north–south direction scanned the corona starting from the central meridian out to approximately 1.0 R ⊙ off the east limb throughout totality. The line widths and Doppler shifts of the Fe x (637.4 nm) and Fe xiv (530.3 nm) emission lines, characteristic of 1.1 × 106 K and 1.8 × 106 K electron temperatures, respectively, varied across the different coronal structures intercepted by the slit. Fe xiv was the dominant emission in the closed fields of an active region and the base of a streamer, with relatively constant 20–30 km s−1 line widths independent of the height. In contrast, Fe x emission exhibited broader (>40 km s−1) line widths in open fields, which increased with height, in particular in the polar coronal hole. Inferences of line widths and Doppler shifts were consistent with extreme ultraviolet (EUV) observations from the Hinode/EUV Imaging Spectrograph, as well as with the near-infrared Fe xiii 1074 nm line observed by Coronal Multichannel Polarimeter. The differences in the spectral line widths between distinct coronal structures are interpreted as an indication of the predominance of wave heating in open structures versus localized heating in closed structures. This study underscores the unparalleled advantages and the enormous potential of TSE spectroscopy in measuring line widths simultaneously in open and closed fields at high altitudes, with minimal exposure times, stray light levels, and instrumental widths.

Smart Streetlight Energy Saving System Based on mmWave Radar

Streetlights serve as fundamental infrastructure to meet the lighting needs of people on every road. However, their extensive deployment often results in unnecessary energy waste, with many streetlights maintaining high brightness despite minimal usage during the night. This study aims to develop a smart energy-efficient streetlight system that automatically adjusts lighting levels based on the absence of vehicles and pedestrians, detected after a 3-minute countdown. Specifically, the study utilizes mmWave radar to collect point cloud data, which undergoes denoising through Doppler, DBSCAN, and XYZ techniques. Additionally, the mmWave radar assists in training an LSTM model to identify pedestrian pathways. The implementation of the proposed system significantly reduces energy consumption and annual costs by automatically dimming or turning off streetlights in areas with minimal pedestrian activity during nighttime.

Leakage Current Harmonic Index as A Diagnostic Technique for Tool to Assess the Surface Condition Assessment of Aged Insulator Surface Under Varying Humidity

Leakage current has been widely utilized as an effective means to monitor the pollution severity of outdoor insulators. The indices of the odd harmonic components of the leakage current have proven to be reliable indicators of insulator performance, particularly in the third to fifth harmonic orders. However, significant challenges exist in using these indices to monitor and classify the leakage current of aged insulators under varying harmonic and pollution conditions. This paper introduces the harmonic index K((3/(5+7) ) which employs third up to seventh odd harmonic component of the leakage current as a diagnostic tool to determine the pollution severity of aged insulators under light, medium and heavy contamination levels. The experiments were conducted using 12 different sets of 11kV insulators with varying degrees of aging. The results indicate that the harmonic index Ki for new and moderately aged insulators decreases with an increase in contamination and is lower than that of heavily aged insulators.

Mechanical properties and microstructure of lime-treated shield tunnel muck improved with carbide slag and soda residue

Shield tunnel muck are usually discarded due to high water content and poor engineering properties, resulting in occupation of land sources and waste of soil sources. Meanwhile, large amounts of industrial waste such as carbide slag (CS) and soda residue (SR) are landfilled with a low reuse rate, which poses a threat to the natural environment. This study aims to improve waste shield tunnel muck using CS and SR and traditional lime, and the improved tunnel muck is expected to be used in subgrade filling to provide a new approach to solve this dilemma. A series of physical, mechanical, subgrade property, and microcosmic tests were conducted on shield tunnel muck improved by CS, SR and lime. The effects of different mixing proportions on the properties of improved tunnel muck were examined. The micro-improvement mechanisms of CS and SR on tunnel muck were explored. Results indicate that the addition of CS or SR can effectively improve the physical and mechanical properties of shield tunnel muck. CS plays a significantly role than SR in improving physical and mechanical properties of tunnel muck. A synergistic enhancement is observed as the combined CS and SR are added, and the optimal mixing proportion of tunnel muck to CS to SR is found to be 100:6:2 with a fixed lime content of 4 %. The alkaline environment created by the synergistic action of CS and SR promotes the dissolution of the active ions in soils, and the generated crystals and gelling products of hydration significant contribute to soil improvement. The tunnel muck improved with appropriate CS or SR content could meet the requirements for light or medium traffic load levels and can be effectively utilized as subgrade filling.

Association of serum glial fibrillary acidic protein with progression independent of relapse activity in multiple sclerosis

ObjectiveInsidious disability worsening is a common feature in relapsing–remitting multiple sclerosis (RRMS). Many patients experience progression independent of relapse activity (PIRA) despite being treated with high efficacy disease-modifying therapies. We prospectively investigated associations of body-fluid and imaging biomarkers with PIRA.MethodsPatients with early RRMS (n = 104) were prospectively included and followed up for 60 months. All patients were newly diagnosed and previously untreated. PIRA was defined using a composite score including the expanded disability status scale, 9-hole peg test, timed 25 foot walk test, and the symbol digit modalities test. Eleven body fluid and imaging biomarkers were determined at baseline and levels of serum neurofilament light (sNfL) and glial fibrillary acidic protein (sGFAP) were also measured annually thereafter. Association of baseline biomarkers with PIRA was investigated in multivariable logistic regression models adjusting for clinical and demographic confounding factors. Longitudinal serum biomarker dynamics were investigated in mixed effects models.ResultsOnly sGFAP was significantly higher in PIRA at baseline (median [IQR] 73.9 [60.9–110.1] vs. 60.3 [45.2–79.9], p = 0.01). A cut-off of sGFAP > 65 pg/mL resulted in a sensitivity of 68% and specificity of 61%, to detect patients at higher risk of PIRA. In a multivariable logistic regression, sGFAP > 65 pg/mL was associated with higher odds of developing PIRA (odds ratio 4.3, 95% CI 1.44–12.86, p = 0.009). Repeated measures of sGFAP levels showed that patients with PIRA during follow-up had higher levels of sGFAP along the whole follow-up compared to stable patients (p < 0.001).ConclusionDetermination of sGFAP at baseline and follow-up may be useful in capturing disability accrual independent of relapse activity in early RRMS.

Blue light regulated lignin and cellulose content of soybean petioles and stems under low light intensity.

To improve light harvest and plant structural support under low light intensity, it is useful to investigate the effects of different ratios of blue light on petiole and stem growth. Two true leaves of soybean seedlings were exposed to a total light intensity of 200μmolm-2 s-1 , presented as either white light or three levels of blue light (40μmolm-2 s-1 , 67μmolm-2 s-1 and 100μmolm-2 s-1 ) for 15days. Soybean petioles under the low blue light treatment upregulated expression of genes relating to lignin metabolism, enhancing lignin content compared with the white light treatment. The low blue light treatment had high petiole length, increased plant height and improved petiole strength arising from high lignin content, thus significantly increasing leaf dry weight relative to the white light treatment. Compared with white light, the treatment with the highest blue light ratio reduced plant height and enhanced plant support through increased cellulose and hemicellulose content in the stem. Under low light intensity, 20% blue light enhanced petiole length and strength to improve photosynthate biomass; whereas 50% blue light lowered plants' centre of gravity, preventing lodging and conserving carbohydrate allocation.

Multilevel sensor for monitoring external and internal environment of eggs

Although it is well known that incubation environment has a great influence on embryogenesis and post-hatching performance of birds, not much is known about how external thermal, sound and light stimuli are isolated by eggshells and perceived by embryos. In this context, this study aimed to develop, calibrate and evaluate a multilevel sensor for integrated monitoring of the external (incubator) and internal environment of eggs. The variables of interest for the external environment were air temperature and relative humidity. For the internal environment, shell temperature, internal temperature, luminosity and sound pressure level were considered. The sensor was developed with an ATmega328 microcontroller, in open-source prototyping, using electronic components which are compatible with the egg's physical structure. Calibrations were carried out in a controlled environment, comparing the multilevel sensor with commercial equipment, obtaining coefficients of determination of R 2 > 0.90 for all variables studied. The multilevel sensor was also validated, simulating a commercial incubation situation and comparing eggs with 2 shell colors (white and brown) and internal volume (intact and empty). Validation results showed that white-shelled eggs insulate less external light (P < 0.001) and full eggs presented higher internal temperatures, greater light and lower sound pressure levels compared to empty eggs (P < 0.001). The multilevel sensor developed here is an innovative proposal for monitoring, simultaneously and in real time, different variables of interest in the commercial incubation environment.

Too Warm and Too Dry—Decline and Threat of the Subarctic-Subalpine Liverwort Hygrobiella laxifolia in a Low Mountain Range in Central Europe under the Conditions of Climate Change

Using the liverwort Hygrobiella laxiflora as an example, this study aims to investigate the impact of climate change on montane species and their ecosystems. The study area is the Elbe Sandstone Mountains in Germany and the Czech Republic, where Hygrobiella laxifolia has an isolated occurrence in deeply carved gorges characterized by a specific microclimate (cellar climate). The focus is on determining the rate at which populations are affected. After little change in the population over a long period, a sudden sharp decline has been observed in recent years. The decline correlates with the mass proliferation of the European spruce bark beetle (Ips typographus) observed since 2017, which has led to a strong thinning of the forests in the area. In many areas of occurrence, the forests now have a much sparser tree layer or none at all. Competition from other, more competitive species also plays an important role as a cause of decline, as these have spread more widely on the sites due to the now higher light levels. The severe bark beetle infestation and the large-scale forest fire of 2022 both represent events that led to the almost complete deforestation of large parts of the study area, which was previously unknown on this scale. Since both the bark beetle infestation and the forest fire are strongly intensified by climate change, we assume that climate change is the main reason for the decline of Hygrobiella laxifolia in the area. The populations of Hygrobiella laxifolia of the Elbe Sandstone Mountains show some morphological peculiarities. As two new species have recently been described within Hygrobiella, we have integrated a sample from the area into a molecular phylogeny of Hygrobiella based on the plastid sequences of trnL-trnF intergenic spacer and matK to clarify the relationships. The sample from Elbe Sandstone Mountains fits well into the clade of Hygrobiella laxifolia.

Testing the influence of light on nitrite cycling in the eastern tropical North Pacific

Abstract. Light is considered a strong controlling factor of nitrification rates in the surface ocean. Previous work has shown that ammonia oxidation and nitrite oxidation may be inhibited by high light levels, yet active nitrification has been measured in the sunlit surface ocean. While it is known that photosynthetically active radiation (PAR) influences microbial nitrite production and consumption, the level of inhibition of nitrification is variable across datasets. Additionally, phytoplankton have light-dependent mechanisms for nitrite production and consumption that co-occur with nitrification around the depths of the primary nitrite maximum (PNM). In this work, we experimentally determined the direct influence of light level on net nitrite production, including all major nitrite cycling processes (ammonia oxidation, nitrite oxidation, nitrate reduction and nitrite uptake) in microbial communities collected from the base of the euphotic zone. We found that although ammonia oxidation was inhibited at the depth of the PNM and was further inhibited by increasing light at all stations, it remained the dominant nitrite production process at most stations and treatments, even up to 25 % surface PAR. Nitrate addition did not enhance ammonia oxidation in our experiments but may have increased nitrate and nitrite uptake at a coastal station. In contrast to ammonia oxidation, nitrite oxidation was not clearly inhibited by light and sometimes even increased at higher light levels. Thus, accumulation of nitrite at the PNM may be modulated by changes in light, but light perturbations did not exclude nitrification from the surface ocean. Nitrite uptake and nitrate reduction were both enhanced in high-light treatments relative to low light and in some cases showed high rates in the dark. Overall, net nitrite production rates of PNM communities were highest in the dark treatments.

Here comes the sun: Thermoregulatory behavior in ectotherms illuminated by light‐level geolocators

AbstractDaily activity patterns of free‐ranging wildlife affect a wide range of ecological and physiological processes and, in turn are affected by anthropogenic disturbances to the environment. However, obtaining a continuous record of activity without disturbing wild animals is logistically challenging. We used commercially available, multi‐purpose light‐level geolocator dataloggers to continuously record light environment and time spent out of water during 5‐months (1 May to 9 September 2021) in an ectothermic freshwater turtle species, the northern map turtle (Graptemys geographica). We used these data to compare time of year and sex differences in thermoregulatory behavior in an ectothermic species in its natural habitat. We recorded &gt;500 000 data points from 17 individual turtles (nine males and eight females). We found no differences in the mean light levels, or proportion of time spent out of the water, between males and females. However, there was a significant effect of both time of year and sex by time of year interaction in both light level, proportion of time spent dry, and number of state changes (i.e., shuttling behavior, wet to dry or dry to wet), suggesting that turtles alter their aerial basking behavior over the course of the season and that the changes in patterns of aerial basking behavior differ between the sexes throughout the year. In general, the proportion of time spent dry decreased over the active season, with an increase during the last week of June and the first week of July, while the number of state changes increased in females during late May/early June before decreasing, while males remained relatively constant. These changes may reflect the different energetic demands associated with reproduction between the two sexes. The overall downward trend in aerial basking likely reflects the role of increasing environmental temperatures, particularly water temperature, in the maintenance of body temperature in this largely aquatic species.

Longitudinal cognitive decline characterizes the profile of non-PD-manifest GBA1 mutation carriers

With disease-modifying treatment for Parkinson’s disease (PD) associated with variants in the glucocerebrosidase gene (GBA1) under way, the challenge to design clinical trials with non-PD-manifest GBA mutation carriers (GBA1NMC) comes within close reach. To delineate trajectories of motor and non-motor markers as well as serum neurofilament light (sNfL) levels and to evaluate clinical endpoints as outcomes for clinical trials in GBA1NMC, longitudinal data of 56 GBA1NMC carriers and 112 age- and sex-matched GBA1 wildtype participants (GBA1wildtype) with up to 9 years of follow-up was analyzed using linear mixed-effects models (LMEM) and Kaplan–Meier survival analysis of clinical endpoints for motor and cognitive function. GBA1NMC showed worse performance in Pegboard, 20 m fast walking, global cognition as well as in executive and memory function at baseline. Longitudinally, LMEM revealed a higher annual increase of the MDS-UPDRS III bradykinesia subscore in GBA1NMC compared to GBA1wildtype, but comparable trajectories of all other motor and non-motor markers as well as sNfL. Kaplan–Meier survival analysis showed a significantly earlier progression to clinical endpoints of cognitive decline in GBA1NMC. Incidence of PD was significantly higher in GBA1NMC. In conclusion, our study extends data on GBA1NMC indicating early cognitive decline as a potentially characteristic feature. Comprehensive longitudinal assessments of cognitive function are crucial to delineate the evolution of early changes in GBA1NMC enabling a more accurate stratification and allow for a more precise definition of trial design and sample size.

Motor band sign is specific for amyotrophic lateral sclerosis and corresponds to motor symptoms.

Magnetic resonance imaging can detect neurodegenerative iron accumulation in the motor cortex, called the motor band sign. This study aims to evaluate its sensitivity/specificity and correlations to symptomatology, biomarkers, and clinical outcome in amyotrophic lateral sclerosis. This prospective study consecutively enrolled 114 persons with amyotrophic lateral sclerosis and 79 mimics referred to Karolinska University Hospital, and also 31 healthy controls. All underwent 3-Tesla brain susceptibility-weighted imaging. Three raters independently assessed motor cortex susceptibility with total and regional motor band scores. Survival was evaluated at a median of 34.2 months after the imaging. The motor band sign identified amyotrophic lateral sclerosis with a sensitivity of 59.6% and a specificity of 91.1% versus mimics and 96.8% versus controls. Higher motor band scores were more common with genetic risk factors (p = 0.032), especially with C9orf72 mutation, and were associated with higher neurofilament light levels (std. β 0.22, p = 0.019). Regional scores correlated strongly with focal symptoms (medial region vs. gross motor dysfunction, std. β -0.64, p = 0.001; intermediate region vs. fine motor dysfunction, std. β -0.51, p = 0.031; lateral region vs. bulbar symptoms std. β -0.71, p < 0.001). There were no associations with cognition, progression rate, or survival. In a real-life clinical setting, the motor band sign has high specificity but relatively low sensitivity for identifying amyotrophic lateral sclerosis. Associations with genetic risk factors, neurofilament levels and somatotopic correspondence to focal motor weakness suggest that the motor band sign could be a suitable biomarker for diagnostics and clinical trials in amyotrophic lateral sclerosis.

An autoantibody signature predictive for multiple sclerosis.

Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. In this study, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster in approximately 10% of PwMS who share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active preclinical period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically or radiologically isolated neuroinflammatory syndromes.