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Abstract Water years (WY) 2017 and 2023 were anomalously wet for California, each alleviating multiyear drought. In both cases, this was unexpected given La Niña conditions, with most seasonal forecasts favoring drier‐than‐normal winters. We analyze over seven decades of precipitation and snow records along with mid‐tropospheric circulation to identify recurring weather patterns driving California precipitation and Sierra Nevada snowpack. Tropical forcing by ENSO causes subtle but important differences in these wet weather patterns, which largely drives the canonical seasonal ENSO‐precipitation relationship. However, the seasonal frequency of these weather patterns is not strongly modulated by ENSO and remains a primary source of uncertainty for seasonal forecasting. Seasonal frequency of ENSO‐independent weather patterns was a major cause of anomalous precipitation in WY2017, record‐setting snow in WY2023, and differences in precipitation outcome during recent El Niño winters 1983, 1998, and 2016. Improved understanding of recurrent atmospheric weather patterns could help to improve seasonal precipitation forecasts.

Abstract INTRODUCTION We aimed to expand the range of the frontotemporal dementia (FTD) phenotypes assessed by the Clinical Dementia Rating Dementia Staging Instrument plus National Alzheimer's Coordinating Center Behavior and Language Domains (CDR plus NACC FTLD). METHODS Neuropsychiatric and motor domains were added to the standard CDR plus NACC FTLD generating a new CDR plus NACC FTLD‐NM scale. This was assessed in 522 mutation carriers and 310 mutation‐negative controls from the Genetic Frontotemporal dementia Initiative (GENFI). RESULTS The new scale led to higher global severity scores than the CDR plus NACC FTLD: 1.4% of participants were now considered prodromal rather than asymptomatic, while 1.3% were now considered symptomatic rather than asymptomatic or prodromal. No participants with a clinical diagnosis of an FTD spectrum disorder were classified as asymptomatic using the new scales. DISCUSSION Adding new domains to the CDR plus NACC FTLD leads to a scale that encompasses the wider phenotypic spectrum of FTD with further work needed to validate its use more widely. Highlights The new Clinical Dementia Rating Dementia Staging Instrument plus National Alzheimer's Coordinating Center Behavior and Language Domains neuropsychiatric and motor (CDR plus NACC FTLD‐NM) rating scale was significantly positively correlated with the original CDR plus NACC FTLD and negatively correlated with the FTD Rating Scale (FRS). No participants with a clinical diagnosis in the frontotemporal dementia spectrum were classified as asymptomatic with the new CDR plus NACC FTLD‐NM rating scale. Individuals had higher global severity scores with the addition of the neuropsychiatric and motor domains. A receiver operating characteristic analysis of symptomatic diagnosis showed nominally higher areas under the curve for the new scales.

Abstract Atmospheric rivers (ARs) and Santa Ana winds (SAWs) are impactful weather events for California communities. Emergency planning efforts and resource management would benefit from extending lead times of skillful prediction for these and other types of extreme weather patterns. Here we describe a methodology for subseasonal prediction of impactful winter weather in California, including ARs, SAWs and heat extremes. The hybrid approach combines dynamical model and historical information to forecast probabilities of impactful weather outcomes at weeks 1–4 lead. This methodology uses dynamical model information considered most reliable, that is, planetary/synoptic‐scale atmospheric circulation, filters for dynamical model error/uncertainty at longer lead times and increases the sample of likely outcomes by utilizing the full historical record instead of a more limited suite of dynamical forecast model ensemble members. We demonstrate skill above climatology at subseasonal timescales, highlighting potential for use in water, health, land, and fire management decision support.

Abstract Background Neuroinflammation has been shown to be an important pathophysiological disease mechanism in frontotemporal dementia (FTD). This includes activation of microglia, a process that can be measured in life through assaying different glia‐derived biomarkers in cerebrospinal fluid. However, only a few studies so far have taken place in FTD, and even fewer focusing on the genetic forms of FTD. Methods We investigated the cerebrospinal fluid concentrations of TREM2, YKL‐40 and chitotriosidase using immunoassays in 183 participants from the Genetic FTD Initiative (GENFI) study: 49 C9orf72 (36 presymptomatic, 13 symptomatic), 49 GRN (37 presymptomatic, 12 symptomatic) and 23 MAPT (16 presymptomatic, 7 symptomatic) mutation carriers and 62 mutation‐negative controls. Concentrations were compared between groups using a linear regression model adjusting for age and sex, with 95% bias‐corrected bootstrapped confidence intervals. Concentrations in each group were correlated with the Mini‐Mental State Examination (MMSE) score using non‐parametric partial correlations adjusting for age. Age‐adjusted z‐scores were also created for the concentration of markers in each participant, investigating how many had a value above the 95th percentile of controls. Results Only chitotriosidase in symptomatic GRN mutation carriers had a concentration significantly higher than controls. No group had higher TREM2 or YKL‐40 concentrations than controls after adjusting for age and sex. There was a significant negative correlation of chitotriosidase concentration with MMSE in presymptomatic GRN mutation carriers. In the symptomatic groups, for TREM2 31% of C9orf72, 25% of GRN, and 14% of MAPT mutation carriers had a concentration above the 95th percentile of controls. For YKL‐40 this was 8% C9orf72, 8% GRN and 0% MAPT mutation carriers, whilst for chitotriosidase it was 23% C9orf72, 50% GRN, and 29% MAPT mutation carriers. Conclusions Although chitotriosidase concentrations in GRN mutation carriers were the only significantly raised glia‐derived biomarker as a group, a subset of mutation carriers in all three groups, particularly for chitotriosidase and TREM2, had elevated concentrations. Further work is required to understand the variability in concentrations and the extent of neuroinflammation across the genetic forms of FTD. However, the current findings suggest limited utility of these measures in forthcoming trials.

Abstract Low‐level stratiform clouds modulate California's coastal climate during the warm season. Previous work describing the seasonal and daily variability of coastal low cloudiness (CLC) suggests that in July, August, and September southern California's CLC is under the influence of an additional driver, which has less impact in northern California. In this work, we introduce the link in which free‐tropospheric moisture dictated by North American Monsoon (NAM) processes can impact southern California CLC. We use in situ and remote sensing observations, as well as reanalysis and single column model simulations to identify and investigate this previously missing component. We find that monsoonal moisture advected by southeasterly flow from the core NAM region into southern California reduces CLC by diminishing cloud‐top longwave cooling. To add to an already complex brew of known factors influencing coastal cloudiness, another one is hereby introduced and should be accounted for in future work.

Abstract Introduction Behavioural dysfunction is a key feature of genetic frontotemporal dementia (FTD) but validated clinical scales measuring behaviour are lacking at present. Methods We assessed behaviour using the revised version of the Cambridge Behavioural Inventory (CBI‐R) in 733 participants from the Genetic FTD Initiative study: 466 mutation carriers (195 C9orf72, 76 MAPT, 195 GRN) and 267 non‐mutation carriers (controls). All mutation carriers were stratified according to their global CDR plus NACC FTLD score into three groups: asymptomatic (CDR = 0), prodromal (CDR = 0.5) and symptomatic (CDR = 1+). Mixed‐effects models adjusted for age, education, sex and family clustering were used to compare between the groups. Neuroanatomical correlates of the individual domains were assessed within each genetic group. Results CBI‐R total scores were significantly higher in all CDR 1+ mutation carrier groups compared with controls [C9orf72 mean 70.5 (standard deviation 27.8), GRN 56.2 (33.5), MAPT 62.1 (36.9)] as well as their respective CDR 0.5 groups [C9orf72 13.5 (14.4), GRN 13.3 (13.5), MAPT 9.4 (10.4)] and CDR 0 groups [C9orf72 6.0 (7.9), GRN 3.6 (6.0), MAPT 8.5 (13.3)]. The C9orf72 and GRN 0.5 groups scored significantly higher than the controls. The greatest impairment was seen in the Motivation domain for the C9orf72 and GRN symptomatic groups, whilst in the symptomatic MAPTgroup, the highest‐scoring domains were Stereotypic and Motor Behaviours and Memory and Orientation. Neural correlates of each CBI‐R domain largely overlapped across the different mutation carrier groups. Conclusions The CBI‐R detects early behavioural change in genetic FTD, suggesting that it could be a useful measure within future clinical trials.

Abstract Objective This study aims to develop and validate a convolutional neural network (CNN)‐based algorithm for automatic selection of informative frames in flexible laryngoscopic videos. The classifier has the potential to aid in the development of computer‐aided diagnosis systems and reduce data processing time for clinician‐computer scientist teams. Methods A dataset of 22,132 laryngoscopic frames was extracted from 137 flexible laryngostroboscopic videos from 115 patients. 55 videos were from healthy patients with no laryngeal pathology and 82 videos were from patients with vocal fold polyps. The extracted frames were manually labeled as informative or uninformative by two independent reviewers based on vocal fold visibility, lighting, focus, and camera distance, resulting in 18,114 informative frames and 4018 uninformative frames. The dataset was split into training and test sets. A pre‐trained ResNet‐18 model was trained using transfer learning to classify frames as informative or uninformative. Hyperparameters were set using cross‐validation. The primary outcome was precision for the informative class and secondary outcomes were precision, recall, and F1‐score for all classes. The processing rate for frames between the model and a human annotator were compared. Results The automated classifier achieved an informative frame precision, recall, and F1‐score of 94.4%, 90.2%, and 92.3%, respectively, when evaluated on a hold‐out test set of 4438 frames. The model processed frames 16 times faster than a human annotator. Conclusion The CNN‐based classifier demonstrates high precision for classifying informative frames in flexible laryngostroboscopic videos. This model has the potential to aid researchers with dataset creation for computer‐aided diagnosis systems by automatically extracting relevant frames from laryngoscopic videos.

Abstract Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

Abstract Increasing wildfire and declining snowpacks in mountain regions threaten water availability. We combine satellite‐based fire detections with snow seasonality classifications to examine fire activity in California's seasonal and ephemeral snow zones. We find a nearly tenfold increase in fire activity during 2020–2021 versus 2001–2019. Accumulation season broadband snow albedo declined 25%–71% at two burned sites (2021 and 2022) according to in‐situ data relative to un‐burned conditions, with greater declines associated with increased burn severity. By enhancing snowpack susceptibility to melt, both decreased snow albedo and canopy drove midwinter melt during a multi‐week dry spell in 2022. Despite similar meteorological conditions in December–February 2013 and 2022–linked to persistent high pressure weather regimes–minimal melt occurred in 2013. Post‐fire snowpack differences are confirmed with satellite measurements. With growing geographical overlap between wildfire and snow, our findings suggest California's snowpack is increasingly vulnerable to the compounding effects of dry spells and wildfire.

Abstract An increasingly volatile hydroclimate increases California's reliance on precipitation from atmospheric rivers (ARs) for water resources. Here, we simulate the AR that contributed to the Oroville Dam crisis in early February 2017 under global climate conditions representing preindustrial, present‐day, mid‐, and late‐21st century environments. This event consisted of two distinct AR pulses: the first snowy, westerly, and cool followed by a southwesterly and warm pulse resulting in copious rain‐on‐snow. We estimate that climate change to date results in ∼11% and ∼15% increase in precipitation over the Feather River Basin in Northern California for the first and second pulses, respectively, with late‐21st century enhancements upwards of ∼21% and ∼59%, respectively. Although both pulses were enhanced by the imposed climate changes, the thermodynamic response and subsequent precipitation increases were most substantial during the second pulse. The disparate changes demonstrated here highlight that not all ARs will respond similarly in a warmer world.

Abstract Introduction A rapid transition from a clinical‐based classification to a pathology‐based classification of neurodegenerative conditions, largely promoted by the increasing availability of imaging biomarkers, is emerging. The Framework for Innovative Multi‐tracer molecular Brain Imaging, funded by the EU Joint Program ‐ Neurodegenerative Disease Research 2016 “Working Groups for Harmonisation and Alignment in Brain Imaging Methods for Neurodegeneration,” aimed at providing a roadmap for the applications of established and new molecular imaging techniques in dementia. Methods We consider current and future implications of adopting a pathology‐based framework for the use and development of positron emission tomography techniques. Results This approach will enhance efforts to understand the multifactorial etiology of Alzheimer's disease and other dementias. Discussion The availability of pathology biomarkers will soon transform clinical and research practice. Crucially, a comprehensive understanding of strengths and caveats of these techniques will promote an informed use to take full advantage of these tools.

Abstract Recent fire seasons have fueled intense speculation regarding the effect of anthropogenic climate change on wildfire in western North America and especially in California. During 1972–2018, California experienced a fivefold increase in annual burned area, mainly due to more than an eightfold increase in summer forest‐fire extent. Increased summer forest‐fire area very likely occurred due to increased atmospheric aridity caused by warming. Since the early 1970s, warm‐season days warmed by approximately 1.4 °C as part of a centennial warming trend, significantly increasing the atmospheric vapor pressure deficit (VPD). These trends are consistent with anthropogenic trends simulated by climate models. The response of summer forest‐fire area to VPD is exponential, meaning that warming has grown increasingly impactful. Robust interannual relationships between VPD and summer forest‐fire area strongly suggest that nearly all of the increase in summer forest‐fire area during 1972–2018 was driven by increased VPD. Climate change effects on summer wildfire were less evident in nonforested lands. In fall, wind events and delayed onset of winter precipitation are the dominant promoters of wildfire. While these variables did not change much over the past century, background warming and consequent fuel drying is increasingly enhancing the potential for large fall wildfires. Among the many processes important to California's diverse fire regimes, warming‐driven fuel drying is the clearest link between anthropogenic climate change and increased California wildfire activity to date.

Objective Acoustic analysis of voice has the potential to expedite detection and diagnosis of voice disorders. Applying an image‐based, neural‐network approach to analyzing the acoustic signal may be an effective means for detecting and differentially diagnosing voice disorders. The purpose of this study is to provide a proof‐of‐concept that embedded data within human phonation can be accurately and efficiently decoded with deep learning neural network analysis to differentiate between normal and disordered voices. Methods Acoustic recordings from 10 vocally‐healthy speakers, as well as 70 patients with one of seven voice disorders (n = 10 per diagnosis), were acquired from a clinical database. Acoustic signals were converted into spectrograms and used to train a convolutional neural network developed with the Keras library. The network architecture was trained separately for each of the seven diagnostic categories. Binary classification tasks (ie, to classify normal vs. disordered) were performed for each of the seven diagnostic categories. All models were validated using the 10‐fold cross‐validation technique. Results Binary classification averaged accuracies ranged from 58% to 90%. Models were most accurate in their classification of adductor spasmodic dysphonia, unilateral vocal fold paralysis, vocal fold polyp, polypoid corditis, and recurrent respiratory papillomatosis. Despite a small sample size, these findings are consistent with previously published data utilizing deep neural networks for classification of voice disorders. Conclusion Promising preliminary results support further study of deep neural networks for clinical detection and diagnosis of human voice disorders. Current models should be optimized with a larger sample size. Levels of Evidence Level III

While total white matter hyperintensity (WMH) volume on magnetic resonance imaging (MRI) has been associated with hippocampal atrophy, less is known about how the regional distribution of WMH volume may differentially affect the hippocampus in healthy aging. Additionally, apolipoprotein E (APOE) ε4 carriers may be at an increased risk for greater WMH volumes and hippocampal atrophy in aging. The present study sought to investigate whether regional WMH volume mediates the relationship between age and hippocampal volume and if this association is moderated by APOE ε4 status in a group of 190 cognitively healthy adults (APOE ε4 status [carrier/non-carrier] = 59/131), ages 50-89. Analyses revealed that temporal lobe WMH volume significantly mediated the relationship between age and average bilateral hippocampal volume, and this effect was moderated by APOE ε4 status (-0.020 (SE = 0.009), 95% CI, [-0.039, -0.003]). APOE ε4 carriers, but not non-carriers, showed negative indirect effects of age on hippocampal volume through temporal lobe WMH volume (APOE ε4 carriers: -0.016 (SE = 0.007), 95% CI, [-0.030, -0.003]; APOE ε4 non-carriers: .005 (SE = 0.006), 95% CI, [-0.006, 0.017]). These findings remained significant after additionally adjusting for sex, years of education, hypertension status and duration, cholesterol status, diabetes status, Body Mass Index, history of smoking, and the Wechsler Adult Intelligence Scale-IV Full Scale IQ. There were no significant moderated mediation effects for frontal, parietal, and occipital lobe WMH volumes, with or without covariates. Our findings indicate that in cognitively healthy older adults, elevated WMH volume regionally localized to the temporal lobes in APOE ε4 carriers is associated with reduced hippocampal volume, suggesting greater vulnerability to brain aging and the risk for Alzheimer's disease., (© 2021 Wiley Periodicals LLC.)

Purpose: Magnetic resonance imaging (MRI) is widely used in human brain research to evaluate the effects of healthy aging and development, as well as neurological disorders. Although standardized methods for quality assurance of human MRI instruments have been established, such approaches have typically not been translated to small animal imaging. We present a method for the generation and analysis of customized phantoms for small animal MRI systems that allows rapid and accurate system stability monitoring., Methods: Computer-aided design software was used to produce a customized phantom using a rapid prototyping printer. Automated registration algorithms were used on three-dimensional images of the phantom to allow system stability to be easily monitored over time., Results: The design of the custom phantom allowed reliable placement relative to the imaging coil. Automated registration showed superior ability to detect gradient changes reflected in the images than with manual measurements. Registering images acquired over time allowed monitoring of gradient drifts of less than one percent., Conclusion: A low cost, MRI compatible phantom was successfully designed using computer-aided design software and a three-dimensional printer. Registering phantom images acquired over time allows monitoring of gradient stability of the MRI system., (Copyright © 2013 Wiley Periodicals, Inc.)

Previous lesion studies have shown compromised complex object discrimination in rats, monkeys, and human patients with damage to the perirhinal cortical region (PRC) of the medial temporal lobe. These findings support the notion that the PRC is involved in object discrimination when pairs of objects have a high degree of overlapping features but not when object discrimination can be resolved on the basis of a single feature (e.g., size or color). Recent studies have demonstrated age-related functional changes to the PRC in animals (rats and monkeys) resulting in impaired complex object discrimination and object recognition. To date, no studies have compared younger and older humans using paradigms previously shown to engage the PRC. To investigate the influence of age on complex object discrimination in humans, the present study used an object matching paradigm for blob-like objects that have previously been shown to recruit the PRC. Difficulty was manipulated by varying the number of overlapping features between objects. Functional MRI data was acquired to determine the involvement of the PRC in the two groups during complex object discrimination. Results indicated that while young and older adults performed similarly on the easy version of the task, most older adults were impaired relative to young participants when the number of overlapping features increased. fMRI results suggest that older adults do not engage bilateral anterior PRC to the same extent as young adults. Specifically, complex object matching performance in older adults was predicted by the degree to which they engage left anterior PRC. These results provide evidence for human age-related changes in PRC function that impact complex object discrimination., (Copyright © 2012 Wiley Periodicals, Inc.)

A key question in designing MRI-based clinical trials is how the main magnetic field strength of the scanner affects the power to detect disease effects. In 110 subjects scanned longitudinally at both 3.0 and 1.5 T, including 24 patients with Alzheimer's Disease (AD) [74.8 +/- 9.2 years, MMSE: 22.6 +/- 2.0 at baseline], 51 individuals with mild cognitive impairment (MCI) [74.1 +/- 8.0 years, MMSE: 26.6 +/- 2.0], and 35 controls [75.9 +/- 4.6 years, MMSE: 29.3 +/- 0.8], we assessed whether higher-field MR imaging offers higher or lower power to detect longitudinal changes in the brain, using tensor-based morphometry (TBM) to reveal the location of progressive atrophy. As expected, at both field strengths, progressive atrophy was widespread in AD and more spatially restricted in MCI. Power analysis revealed that, to detect a 25% slowing of atrophy (with 80% power), 37 AD and 108 MCI subjects would be needed at 1.5 T versus 49 AD and 166 MCI subjects at 3 T; however, the increased power at 1.5 T was not statistically significant (alpha = 0.05) either for TBM, or for SIENA, a related method for computing volume loss rates. Analysis of cumulative distribution functions and false discovery rates showed that, at both field strengths, temporal lobe atrophy rates were correlated with interval decline in Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog), mini-mental status exam (MMSE), and Clinical Dementia Rating sum-of-boxes (CDR-SB) scores. Overall, 1.5 and 3 T scans did not significantly differ in their power to detect neurodegenerative changes over a year. Hum Brain Mapp, 2010. (c) 2009 Wiley-Liss, Inc.

Studies of single-cell discharge in the basal ganglia of behaving primates have revealed: characteristic patterns of spontaneous discharge in the striatum, external (GPe) and internal (GPi) globus pallidus, pars reticulata and pars compacta of the substantia nigra, and the subthalamic nucleus (STN); phasic changes in neural discharge in relation to movements of specific body parts (e.g. leg, arm, neck, face); short-latency (sensory) neural responses to passive joint rotation; a somatotopic organization of movement-related neurons in GPe, GPi, and STN; a clustering of functionally similar neurons in the putamen and globus pallidus; greater representation of the proximal than of the distal portion of the limb; changes in neural activity in reaction-time tasks, suggesting a greater role of the basal ganglia in the execution than in the initiation of movement in this paradigm; a clear relation of neuronal activity to direction, amplitude (?velocity) of movement, and force; a preferential relation of neural activity to the direction of movement, rather than to the pattern of muscular activity. Some of these findings suggest that the basal ganglia may play a role in the control of movement parameters rather than (or independent of) the pattern of muscular activity. Loss of basal ganglia output related to amplitude may account for the bradykinesia in Parkinson's disease. The presence of somatotopic organization in the putamen and globus pallidus, together with known topographic striopallidal connections, suggests that segregated, parallel cortico-subcortical loops subserve 'motor' and 'complex' functions.