Structure and functionality of surface-active amylose-fatty amine salt inclusion complexes.

Novel value-added starch-based materials can be produced by forming amylose inclusion complexes (AIC) with hydrophobic compounds. There is currently little research on AIC use as polymeric emulsifiers, particularly for AIC with fatty amine salt ligands. This work evaluated AIC emulsifiers by studying the structure and functionality of AIC composed of high amylose corn starch and fatty amine salts (10-18 carbons, including a mixture simulating vegetable oil composition) produced via steam jet cooking. X-ray scattering verified successful AIC formation, with peaks located near 7.0°, 12.8° and 19.9° 2θ. AIC were easily dispersed in water (80-85 °C) and remained in suspension at room temperature for weeks, unlike the uncomplexed ligands or starch. AIC were highly effective emulsifying agents, with emulsifying activity indexes of 213-229 m2g-1 at pH 5, and zeta potentials, a measure of electrostatic repulsion, as high as 43.4 mV. AIC dispersions had surface tension ranging from 24 to 41 mN/m and displayed surface-active properties superior to amylose complexes formed from fatty acid salts and competitive with common starch-based emulsifiers. These findings demonstrate that fatty amine salt AIC are effective emulsifiers that can be made from low-cost sources of fatty amine salts, such as vegetable oil derivatives.

Work Productivity and General Health Through 2 Years of Guselkumab Treatment in a Phase 3 Randomized Trial of Patients With Active Psoriatic Arthritis.

INTRODUCTION: To evaluate the effect of guselkumab on work productivity and nonwork daily activity impairment and general health status through 2 years in patients who were biologic-naïve with active psoriatic arthritis (PsA) in the phase 3 DISCOVER-2 clinical trial. METHODS: Adult patients with PsA were randomized to subcutaneous injections of guselkumab 100 mg every 4 weeks (Q4W); at weeks 0, 4, then every 8 weeks (Q8W); or placebo (through week 24 with crossover to guselkumab Q4W). Work productivity and nonwork daily activity impairment were assessed using the Work Productivity and Activity Impairment Questionnaire for PsA (WPAI-PsA) and patient-reported general health status using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) Index and EQ-Visual Analog Scale (EQ-VAS). Least-squares (LS) mean changes from baseline in WPAI-PsA domains and EQ-5D-5L/EQ-VAS were assessed through week 100. Changes in employment status were utilized to estimate potential indirect savings from improved work productivity. RESULTS: Of 739 randomized patients, 738 had available baseline data for the analyses (Q4W 245; Q8W 248; placebo 245). At week 24, greater improvements in work productivity, nonwork daily activity, and EQ-5D-5L/EQ-VAS were observed in the Q4W and Q8W groups versus the placebo group. At week 100, LS mean reductions in work productivity impairment (- 23.8% to - 28.0%) and nonwork daily activity impairment (- 26.6% to - 29.2%) and improvements in EQ-5D-5L/EQ-VAS (0.14 to 0.15/21.2 to 25.0) were maintained in patients receiving guselkumab. Among patients employed at baseline, 12.1-16.4% were not employed at week 100, and 20.0-25.3% shifted from not employed at baseline to employed at week 100. Potential yearly indirect cost savings (USD) from improved work productivity at week 100 ranged from $16,529 to $19,409. CONCLUSION: Patients with active PsA treated with guselkumab demonstrated reduced impairment in work productivity and nonwork daily activity, together with improvement in general health status and substantial potential cost savings, over a 2-year period. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT03158285.

Assessment of the Environmental Impacts of a Localized Food System and Food Waste Reduction in a Water-Scarce Region Using Diet Optimization Models.

Despite growing interest in fresh local produce across the United States, scaling up local agricultural development might impose new environmental pressures on increasingly scarce water and land resources in specific localities. Drawing upon the case of the Palouse of the US Inland Northwest, this study evaluates land and water footprints of local foods along with food waste reduction in a water-scarce region. We used both non-robust and robust diet-optimization techniques to estimate the minimum amounts of irrigation water necessary to grow foods locally and to satisfy the local population's caloric or nutrition needs. Our modeling results indicate that, on an annual basis, an increase of less than 5% of the current freshwater withdrawal on the Palouse could satisfy 10% of the local population's aspirational demand for locally grown food products, while more than 35% of local foods (by mass) may be wasted. Furthermore, reducing food waste by 50% could simultaneously reduce water use by up to 24%, cropland use by 13%, and pastureland use by 20%. Our findings not only provide intriguing information for access to local food but could also be used to stimulate new efforts to increase consumers' and retailers' awareness of environmental benefits associated with food waste reduction.

Impact of key manifestations of psoriatic arthritis on patient quality of life, functional status, and work productivity: Findings from a real-world study in the United States and Europe.

OBJECTIVES: To determine the individual impact of key manifestations of psoriatic arthritis (PsA) on quality of life (QoL), physical function, and work disability. METHODS: Data from the Adelphi 2018 PsA Disease-Specific Programme, a multinational, cross-sectional study of PsA patients, were used. PsA manifestations included peripheral arthritis (number of joints affected), psoriasis (body surface area [BSA]), axial involvement (inflammatory back pain [IBP] and sacroiliitis) enthesitis, and dactylitis. General, and disease-specific QoL, physical function, and work disability were measured with EQ-5D-5L, PsAID-12, HAQ-DI, and WPAI, respectively. Multivariate regression adjusting for potential confounders evaluated the independent effect of PsA manifestations on each outcome. RESULTS: Among the 2222 PsA patients analysed, 77.0% had active psoriasis and 64.4% had peripheral arthritis; 5.9%, 6.8%, 10.2%, and 3.6% had enthesitis, dactylitis, IBP, or sacroiliitis, respectively. Mean EQ VAS scores were significantly poorer in patients with vs. without enthesitis (59.9 vs. 75.6), dactylitis (63.6 vs. 75.4), and with greater peripheral joint involvement (none: 82.5; 1-2 affected joints: 74.1; 3-6 joints: 74.2; >6 joints: 65.0). Significantly worse mean PsAID-12 scores were associated with vs. without enthesitis (4.39 vs. 2.34) or dactylitis (4.30 vs. 2.32), and with greater peripheral joint involvement (none: 1.21; 1-2 joints: 2.36; 3-6 joints: 2.74; >6 joints: 3.92), and BSA (none: 1.49; >3-10%: 2.96; >10%: 3.43). Similar patterns were observed with HAQ-DI and WPAI scores. CONCLUSION: Most PsA manifestations were independently associated with worse general, and PsA-specific QoL, physical function, and work disability, highlighting the need for treatments targeting the full spectrum of PsA symptoms to lower the burden of disease.

Preoperative A1c and Postoperative Infection in Elective Hand Surgery.

Diabetes mellitus affects 10.5% of the US population. Numerous studies have documented increased risk of complications for patients with diabetes after different types of surgery, including hand surgery. By aiming for a preoperative target hemoglobin A1c (A1c), the risk of surgical complications following elective hand surgery may be reduced for patients with diabetes. This literature review was conducted to evaluate the association between diabetes mellitus and surgical site infections and, more specifically, to determine whether there is any association between preoperative A1c level and postoperative infections in hand surgery. The risk for surgical site infections and wound complications appears to be higher for patients with insulin-dependent diabetes mellitus, but not necessarily for patients with noninsulin-dependent diabetes mellitus, when compared with patients without diabetes. The role of prophylactic antibiotics for patients with diabetes undergoing elective hand surgery was also considered. Prophylactic antibiotics have not been shown to be beneficial for healthy patients undergoing clean, elective hand surgery. However, preoperative antibiotics may have a protective role for some patients with poorly controlled hyperglycemia.

Characterization and properties of starch-dicarboxylic acid inclusion complexes prepared by excess steam jet cooking.

A series of dicarboxylic-amylose inclusion complexes (AIC) were prepared by excess steam jet-cooking high amylose corn starch with linear C10, C12, C14, and C16 dicarboxylic acids to examine the influence of two polar head groups on complex formation. The C12, C14, and C16 dicarboxylic acid AIC were prepared in 48-63 % yields and contained 8.9-11.8 % diacid while the C10 AIC gave 30 % and contained 2.6 % diacid. These AIC had V6 helical amylose structures by XRD and complexation was further confirmed by DSC, FTIR, and TGA. SEM of the C12-C16 AIC revealed micron-sized toroidal spherulites while the C10 AIC was predominantly amorphous. DSC showed two AIC related transitions. This work provides a better understanding of the formation and physicochemical properties of these diacid AIC. Preparation by excess steam jet cooking demonstrates practical and commercial utility to prepare AIC as off-the-shelf materials for food and nonfood applications.

The Effect of Guselkumab on General Health State in Biologic-Naïve Patients with Active Psoriatic Arthritis Through Week 52 of the Phase 3, Randomized, Placebo-Controlled DISCOVER-2 Trial.

INTRODUCTION: In DISCOVER-2, guselkumab, an interleukin-23 p19 subunit inhibitor, was efficacious in biologic-naïve psoriatic arthritis (PsA) patients. We report the effect of guselkumab on health-related quality of life (HRQoL) using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) Index and Visual Analog Scale (EQ-VAS) through Week 52. METHODS: Adults with active PsA were randomized to guselkumab 100 mg every 4 weeks (Q4W) or Weeks 0, 4, then every 8 weeks (Q8W), or placebo (crossover to guselkumab Q4W at Week 24). Least squares (LS) mean changes in EQ-5D-5L Index (0-1, US-based value set) and EQ-VAS (0-100) from baseline through Week 52 were assessed. Proportions of patients achieving minimally important differences (MIDs) were assessed through Week 52. Associations between patient clinical features and EQ-5D-5L Index and EQ-VAS scores were examined cross-sectionally with pooled data through Week 24. RESULTS: The analysis included 738 patients (Q4W n = 245; Q8W n = 248; placebo n = 245). At Week 24, LS mean changes from baseline in the Q4W, Q8W, and placebo groups were 0.12, 0.12, and 0.05, respectively, for EQ-5D-5L Index, and 18.2, 18.4, and 6.8, respectively, for EQ-VAS. At Week 52, improvement was maintained in the guselkumab groups and increased in the placebo crossover group. EQ-5D-5L Index MID was achieved by 56.0% in each guselkumab group at Week 24 and 66.2% in Q4W, 68.5% in Q8W, and 66.1% in placebo crossover group at Week 52. Higher C-reactive protein level, Psoriasis Area and Severity Index score, fatigue, and pain were correlated with worse EQ-5D-5L Index and EQ-VAS, based on pooled data through Week 24. Higher tender joint count was correlated with worse EQ-5D-5L, while higher swollen joint count was correlated with worse EQ-VAS. CONCLUSIONS: Guselkumab improved HRQoL through 52 weeks in patients with active PsA. Impairment in HRQoL was correlated with increased inflammation, fatigue, pain, and measures of skin and joint symptom severity. CLINICALTRIALS: GOV: NCT03158285.

The Effect of Guselkumab on Work Productivity in Biologic-Naïve Patients with Active Psoriatic Arthritis Through Week 52 of the Phase 3, Randomized, Placebo-Controlled DISCOVER-2 Trial.

INTRODUCTION: The phase 3 DISCOVER-2 trial evaluated the effect of guselkumab on impaired work productivity and nonwork activity in biologic-naïve patients with psoriatic arthritis (PsA). METHODS: Adults with active PsA were randomized (1:1:1) to guselkumab 100 mg every 4 weeks (Q4W), guselkumab 100 mg at weeks 0 and 4 and then every 8 weeks (Q8W), or placebo (with crossover to guselkumab Q4W at week 24). Least squares mean change from baseline in Work Productivity and Activity Impairment Questionnaire for PsA (WPAI-PsA) domains and employment were assessed by treatment group. Multivariate analysis of data from weeks 0 through 24 assessed independent associations between PsA clinical features and WPAI-PsA domains. RESULTS: In total, 738 patients were evaluated (guselkumab Q4W n = 245; guselkumab Q8W n = 248; placebo n = 245). At week 24, improvements (reduced impairment) in presenteeism (Q4W -20.1%, Q8W -19.6%, placebo -10.5%), work productivity (Q4W -20.1%, Q8W -19.2%, placebo -10.6%), and nonwork activity (Q4W -20.5%, Q8W -21.2%, placebo -9.9%) were greater in guselkumab-treated versus placebo-treated patients. At week 52, following placebo crossover at week 24, improvements were similar among groups. Baseline absenteeism was minimal and did not change in any group. By week 52, 23.1-25.9% of guselkumab-treated patients who were unemployed at baseline were employed. All WPAI-PsA domains were positively associated with C-reactive protein level, fatigue, and pain. All domains except absenteeism were positively associated with enthesitis and Psoriasis Area and Severity Index score. Age was negatively associated with presenteeism and work productivity loss, female sex and tender joint count were positively associated with nonwork activity impairment, and dactylitis was positively associated with presenteeism. CONCLUSION: Both guselkumab regimens reduced work productivity loss and nonwork activity impairment in patients with active PsA. Association of work productivity loss and nonwork activity impairment with PsA joint and skin features suggests that improvement in both features is beneficial for optimizing improved work productivity loss and nonwork activity impairment. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT03158285.

Learning neural decoders without labels using multiple data streams.

Objective.Recent advances in neural decoding have accelerated the development of brain-computer interfaces aimed at assisting users with everyday tasks such as speaking, walking, and manipulating objects. However, current approaches for training neural decoders commonly require large quantities of labeled data, which can be laborious or infeasible to obtain in real-world settings. Alternatively, self-supervised models that share self-generated pseudo-labels between two data streams have shown exceptional performance on unlabeled audio and video data, but it remains unclear how well they extend to neural decoding.Approach.We learn neural decoders without labels by leveraging multiple simultaneously recorded data streams, including neural, kinematic, and physiological signals. Specifically, we apply cross-modal, self-supervised deep clustering to train decoders that can classify movements from brain recordings. After training, we then isolate the decoders for each input data stream and compare the accuracy of decoders trained using cross-modal deep clustering against supervised and unimodal, self-supervised models.Main results.We find that sharing pseudo-labels between two data streams during training substantially increases decoding performance compared to unimodal, self-supervised models, with accuracies approaching those of supervised decoders trained on labeled data. Next, we extend cross-modal decoder training to three or more modalities, achieving state-of-the-art neural decoding accuracy that matches or slightly exceeds the performance of supervised models.Significance.We demonstrate that cross-modal, self-supervised decoding can be applied to train neural decoders when few or no labels are available and extend the cross-modal framework to share information among three or more data streams, further improving self-supervised training.

AJILE12: Long-term naturalistic human intracranial neural recordings and pose.

Understanding the neural basis of human movement in naturalistic scenarios is critical for expanding neuroscience research beyond constrained laboratory paradigms. Here, we describe our Annotated Joints in Long-term Electrocorticography for 12 human participants (AJILE12) dataset, the largest human neurobehavioral dataset that is publicly available; the dataset was recorded opportunistically during passive clinical epilepsy monitoring. AJILE12 includes synchronized intracranial neural recordings and upper body pose trajectories across 55 semi-continuous days of naturalistic movements, along with relevant metadata, including thousands of wrist movement events and annotated behavioral states. Neural recordings are available at 500 Hz from at least 64 electrodes per participant, for a total of 1280 hours. Pose trajectories at 9 upper-body keypoints were estimated from 118 million video frames. To facilitate data exploration and reuse, we have shared AJILE12 on The DANDI Archive in the Neurodata Without Borders (NWB) data standard and developed a browser-based dashboard.

Antimony(+5) ion induced tunable intramolecular charge transfer in hypervalent antimony(V) porphyrins.

The +5 oxidation state of antimony induced push-pull style intramolecular charge transfer in an elegantly designed axial dimethoxyantimony(V) porphyrin series: SbP(OMe)2·PF6, SbMP(OMe)2·PF6, SbDMP(OMe)2·PF6, SbTMP(OMe)2·PF6 with phenyl (P), 4-methoxyphenyl (MP), 3,5-dimethoxyphenyl (DMP), and 3,4,5-trimethoxyphenyl (TMP) units, respectively, in its meso positions. The Sb(+5) made the porphyrin ring electron-poor, whereas the methoxy groups on the phenyl unit produced electron-rich sites within the molecule. The presence of electron-poor and electron-rich parts in the same molecule resulted in a push-pull type intramolecular charge transfer (ICT). However, the ICT is strongly dependent on the position of the methoxy groups on the phenyl ring. The charge transfer character is more pronounced in meta-methoxy substituted antimony(V) derivatives (SbDMP(OMe)2·PF6, SbTMP(OMe)2·PF6) than the para-methoxy or no-methoxy substituted antimony(V) derivatives (SbP(OMe)2·PF6, SbMP(OMe)2·PF6). Steady-state and transient spectroscopic techniques, as well as solvatochromism techniques, were employed to establish the tunable ICT. Additionally, time-dependant density functional theory (TD-DFT) calculations were used to complement the experimental results. The systematic study of antimony(V) porphyrins, especially the tunable push-pull nature could play an important role in instigating high yield charge-separated states in multi-modular donor-acceptor systems for solar energy conversion and molecular electronic and photonic applications.

Decoding Happiness from Neural and Video Recordings for Better Insight Into Emotional Processing in the Brain.

Gaining a better understanding of which brain regions are responsible for emotional processing is crucial for the development of novel treatments for neuropsychiatric disorders. Current approaches rely on sparse assessments of subjects' emotional states, rarely reaching more than a hundred per patient. Additionally, data are usually obtained in a task solving scenario, possibly influencing their emotions by study design. Here, we utilize several days worth of near-continuous neural and video recordings of subjects in a naturalistic environment to predict the emotional state of happiness from neural data. We are able to obtain high-frequency and high-volume happiness labels for this task by first predicting happiness from video data in an intermediary step, achieving good results (F1 = .75) and providing us with more than 6 million happiness assessments per patient, on average. We then utilize these labels for a classifier on neural data (F1 = .71). Our findings provide a potential pathway for future work on emotional processing that circumvents the mentioned restrictions.

Diagnosing Systemic Amyloidosis Presenting as Carpal Tunnel Syndrome: A Risk Nomogram to Guide Biopsy at Time of Carpal Tunnel Release.

BACKGROUND: As carpal tunnel syndrome often precedes other signs of systemic amyloidosis, tenosynovial biopsy at the time of carpal tunnel release may facilitate early diagnosis and treatment. However, evidence-based guidelines for amyloidosis screening during carpal tunnel release have not been established. We sought to develop a predictive model for amyloidosis after carpal tunnel release to inform screening efforts. METHODS: We performed a retrospective cohort study of adults without known amyloidosis undergoing at least 1 carpal tunnel release from 2000 to 2019 with use of the national Veterans Health Administration database. After estimating the cumulative incidence of amyloidosis after carpal tunnel release, we identified risk factors, constructed a predictive nomogram based on a multivariable subdistribution-hazard competing-risks model, and performed cross-validation. RESULTS: Among 89,981 patients undergoing at least 1 carpal tunnel release, 310 were subsequently diagnosed with amyloidosis at a median interval of 4.5 years, corresponding to a cumulative incidence of 0.55% (95% confidence interval [CI]: 0.47% to 0.63%) at 10 years. Amyloidosis diagnosis following carpal tunnel release was associated with an increased hazard of heart failure (hazard ratio [HR], 4.68; 95% CI: 4.26 to 5.55) and death (HR, 1.27; 95% CI: 1.07 to 1.51) after adjustment for potential confounders. Age, male sex, Black race, monoclonal gammopathy of undetermined significance or multiple myeloma, rheumatoid arthritis, atrial fibrillation, spinal stenosis, and bilateral carpal tunnel syndrome were independently associated with increased risk of amyloidosis diagnosis and were included in the risk nomogram. CONCLUSIONS: Amyloidosis diagnosis after carpal tunnel release is rare but is associated with poor outcomes. We present an amyloidosis-risk nomogram to help guide tenosynovial biopsy at time of carpal tunnel release. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Behavioral and Neural Variability of Naturalistic Arm Movements.

Motor behaviors are central to many functions and dysfunctions of the brain, and understanding their neural basis has consequently been a major focus in neuroscience. However, most studies of motor behaviors have been restricted to artificial, repetitive paradigms, far removed from natural movements performed "in the wild." Here, we leveraged recent advances in machine learning and computer vision to analyze intracranial recordings from 12 human subjects during thousands of spontaneous, unstructured arm reach movements, observed over several days for each subject. These naturalistic movements elicited cortical spectral power patterns consistent with findings from controlled paradigms, but with considerable neural variability across subjects and events. We modeled interevent variability using 10 behavioral and environmental features; the most important features explaining this variability were reach angle and day of recording. Our work is among the first studies connecting behavioral and neural variability across cortex in humans during unstructured movements and contributes to our understanding of long-term naturalistic behavior.

Mining naturalistic human behaviors in long-term video and neural recordings.

BACKGROUND: Recent technological advances in brain recording and machine learning algorithms are enabling the study of neural activity underlying spontaneous human behaviors, beyond the confines of cued, repeated trials. However, analyzing such unstructured data lacking a priori experimental design remains a significant challenge, especially when the data is multi-modal and long-term. NEW METHOD: Here we describe an automated, behavior-first approach for analyzing simultaneously recorded long-term, naturalistic electrocorticography (ECoG) and behavior video data. We identify and characterize spontaneous human upper-limb movements by combining computer vision, discrete latent-variable modeling, and string pattern-matching on the video. RESULTS: Our pipeline discovers and annotates over 40,000 instances of naturalistic arm movements in long term (7-9 day) behavioral videos, across 12 subjects. Analysis of the simultaneously recorded brain data reveals neural signatures of movement that corroborate previous findings. Our pipeline produces large training datasets for brain-computer interfacing applications, and we show decoding results from a movement initiation detection task. COMPARISON WITH EXISTING METHODS: Spontaneous movements capture real-world neural and behavior variability that is missing from traditional cued tasks. Building beyond window-based movement detection metrics, our unsupervised discretization scheme produces a queryable pose representation, allowing localization of movements with finer temporal resolution. CONCLUSIONS: Our work addresses the unique analytic challenges of studying naturalistic human behaviors and contributes methods that may generalize to other neural recording modalities beyond ECoG. We publish our curated dataset and believe that it will be a valuable resource for future studies of naturalistic movements.

The effect of intravenous golimumab on health-related quality of life and work productivity in patients with active psoriatic arthritis: results of the Phase 3 GO-VIBRANT trial.

INTRODUCTION/OBJECTIVES: To evaluate changes in health-related quality of life (HRQoL) and productivity following treatment with intravenous (IV) golimumab in patients with psoriatic arthritis (PsA). METHODS: Patients were randomized to IV golimumab 2 mg/kg (n=241) at Weeks 0, 4, then every 8 weeks (q8w) through Week 52 or placebo (n=239) at Weeks 0, 4, then q8w, with crossover to IV golimumab 2 mg/kg at Weeks 24, 28, then q8w through Week 52. Change from baseline in EuroQol-5 dimension-5 level (EQ-5D-5L) index and visual analog scale (EQ-VAS), daily productivity VAS, and the Work Limitations Questionnaire (WLQ) was assessed. Relationships between these outcomes and disease activity and patient functional capability were evaluated post hoc. RESULTS: At Week 8, change from baseline in EQ-5D-5L index (0.14 vs 0.04), EQ-VAS (17.16 vs 3.69), daily productivity VAS (-2.91 vs -0.71), and WLQ productivity loss score (-2.92 vs -0.78) was greater in the golimumab group versus the placebo group, respectively. At Week 52, change from baseline was similar in the golimumab and placebo-crossover groups (EQ-5D-5L index: 0.17 and 0.15; EQ-VAS: 21.61 and 20.84; daily productivity VAS: -2.89 and -3.31; WLQ productivity loss: -4.49 and -3.28, respectively). HRQoL and productivity were generally associated with disease activity and functional capability, with continued association from Week 8 through Week 52. CONCLUSION: IV golimumab resulted in early and sustained improvements in HRQoL and productivity from Week 8 through 1 year in patients with PsA. HRQoL and productivity improvements were associated with improvements in disease activity and patient functional capability. Key Points • In patients with active psoriatic arthritis (PsA), intravenous (IV) golimumab improved health-related quality of life (HRQoL) and productivity as early as 8 weeks and maintained improvement through 1 year • Improvements in HRQoL and productivity outcomes in patients with PsA treated with IV golimumab were associated with improvements in disease activity and patient functional capability outcomes • IV golimumab is an effective treatment option for PsA that can mitigate the negative effects of the disease on HRQoL and productivity.

Generalized neural decoders for transfer learning across participants and recording modalities.

Objective. Advances in neural decoding have enabled brain-computer interfaces to perform increasingly complex and clinically-relevant tasks. However, such decoders are often tailored to specific participants, days, and recording sites, limiting their practical long-term usage. Therefore, a fundamental challenge is to develop neural decoders that can robustly train on pooled, multi-participant data and generalize to new participants.Approach. We introduce a new decoder, HTNet, which uses a convolutional neural network with two innovations: (a) a Hilbert transform that computes spectral power at data-driven frequencies and (b) a layer that projects electrode-level data onto predefined brain regions. The projection layer critically enables applications with intracranial electrocorticography (ECoG), where electrode locations are not standardized and vary widely across participants. We trained HTNet to decode arm movements using pooled ECoG data from 11 of 12 participants and tested performance on unseen ECoG or electroencephalography (EEG) participants; these pretrained models were also subsequently fine-tuned to each test participant.Main results. HTNet outperformed state-of-the-art decoders when tested on unseen participants, even when a different recording modality was used. By fine-tuning these generalized HTNet decoders, we achieved performance approaching the best tailored decoders with as few as 50 ECoG or 20 EEG events. We were also able to interpret HTNet's trained weights and demonstrate its ability to extract physiologically-relevant features.Significance. By generalizing to new participants and recording modalities, robustly handling variations in electrode placement, and allowing participant-specific fine-tuning with minimal data, HTNet is applicable across a broader range of neural decoding applications compared to current state-of-the-art decoders.

Human electrocortical, electromyographical, ocular, and kinematic data during perturbed walking and standing.

Active balance control is critical for performing many of our everyday activities. Our nervous systems rely on multiple sensory inputs to inform cortical processing, leading to coordinated muscle actions that maintain balance. However, such cortical processing can be challenging to record during mobile balance tasks due to limitations in noninvasive neuroimaging and motion artifact contamination. Here, we present a synchronized, multi-modal dataset from 30 healthy, young human participants during standing and walking while undergoing brief sensorimotor perturbations. Our dataset includes 20 total hours of high-density electroencephalography (EEG) recorded from 128 scalp electrodes, along with surface electromyography (EMG) from 10 neck and leg electrodes, electrooculography (EOG) recorded from 3 electrodes, and 3D body position from 2 sensors. In addition, we include ∼ 18000 total balance perturbation events across participants. To facilitate data reuse, we share this dataset in the Brain Imaging Data Structure (BIDS) data standard and publicly release code that replicates our previous event-related findings.

The effect of intravenous golimumab on health-related quality of life and work productivity in adult patients with active ankylosing spondylitis: results of the phase 3 GO-ALIVE trial.

INTRODUCTION/OBJECTIVES: The effect of intravenous (IV) golimumab on health-related quality of life (HRQoL) and productivity in patients with ankylosing spondylitis (AS) was evaluated. METHOD: Patients were randomized to IV golimumab 2 mg/kg (n = 105) at weeks 0, 4, then every 8 weeks (q8w) through week 52 or placebo (n = 103) at weeks 0, 4, 12, with crossover to golimumab 2 mg/kg at weeks 16, 20, then q8w through week 52. Changes from baseline in EuroQol-5 dimension-5 level (EQ-5D-5L) index and visual analog scale (EQ-VAS), daily productivity VAS, Work Limitations Questionnaire (WLQ), and Ankylosing Spondylitis Quality of Life (ASQoL) were assessed. Correlations between these outcomes and disease activity and patient functioning outcomes were evaluated post hoc. RESULTS: At week 16, changes from baseline (mean ± standard deviation) in EQ-5D-5L index (0.17 ± 0.16 vs 0.05 ± 0.14), EQ-VAS (20.3 ± 24.6 vs 4.8 ± 23.5), daily productivity VAS (- 2.9 ± - 2.9 vs - 1.1 ± - 2.5), WLQ productivity loss score (- 3.5 ± - 5.3 vs - 1.9 ± - 4.0), and ASQoL (- 5.4 ± - 5.0 vs - 1.8 ± - 4.5) were greater in the IV golimumab versus placebo group, respectively. At week 28, changes from baseline were similar between the IV golimumab and placebo-crossover groups (EQ-5D-5L index: 0.18 ± 0.17 and 0.16 ± 0.16, EQ-VAS: 20.5 ± 27.9 and 22.5 ± 23.1, daily productivity VAS: - 3.1 ± - 3.0 and - 3.1 ± - 2.8, WLQ productivity loss: - 3.9 ± - 5.5 and - 4.5 ± - 4.5, and ASQoL: - 5.3 ± - 5.2 and - 5.3 ± - 4.8, respectively); improvements were maintained through week 52. HRQoL and productivity outcomes were generally moderately correlated with disease activity and functioning outcomes. CONCLUSIONS: In patients with AS, IV golimumab produced sustained improvements in HRQoL and productivity through 1 year, which correlated with improvements in disease activity and functioning. ClinicalTrials.gov registry number is NCT02186873. Key Points • Intravenous (IV) golimumab resulted in clinically important improvement in general and ankylosing spondylitis-specific health-related quality of life (HRQoL) and productivity outcomes in patients with ankylosing spondylitis (AS) as early as week 8 and maintained improvement through 1 year • Improvements in HRQoL and productivity outcomes in these patients with AS were correlated with improvements in measures of disease activity and patient functional capability • IV golimumab is an effective treatment option for AS that can help mitigate the negative effects of the disease on HRQoL and productivity.

Unsupervised Sleep and Wake State Identification in Long-Term Electrocorticography Recordings.

Studying the neural correlates of sleep can lead to revelations in our understanding of sleep and its interplay with different neurological disorders. Sleep research relies on manual annotation of sleep stages based on rules developed for healthy adults. Automating sleep stage annotation can expedite sleep research and enable us to better understand atypical sleep patterns. Our goal was to create a fully unsupervised approach to label sleep and wake states in human electro-corticography (ECoG) data from epilepsy patients. Here, we demonstrate that with continuous data from a single ECoG electrode, hidden semi-Markov models (HSMM) perform best in classifying sleep/wake states without excessive transitions, with a mean accuracy (n=4) of 85.2% compared to using K-means clustering (72.2%) and hidden Markov models (81.5%). Our results confirm that HSMMs produce meaningful labels for ECoG data and establish the groundwork to apply this model to cluster sleep stages and potentially other behavioral states.