μSim: A goal-driven framework for elucidating the neural control of movement through musculoskeletal modeling

How does the motor cortex (MC) produce purposeful and generalizable movements from the complex musculoskeletal system in a dynamic environment? To elucidate the underlying neural dynamics, we use a goal-driven approach to model MC by considering its goal as a controller driving the musculoskeletal system through desired states to achieve movement. Specifically, we formulate the MC as a recurrent neural network (RNN) controller producing muscle commands while receiving sensory feedback from biologically accurate musculoskeletal models. Given this real-time simulated feedback implemented in advanced physics simulation engines, we use deep reinforcement learning to train the RNN to achieve desired movements under specified neural and musculoskeletal constraints. Activity of the trained model can accurately decode experimentally recorded neural population dynamics and single-unit MC activity, while generalizing well to testing conditions significantly different from training. Simultaneous goal- and data- driven modeling in which we use the recorded neural activity as observed states of the MC further enhances direct and generalizable single-unit decoding. Finally, we show that this framework elucidates computational principles of how neural dynamics enable flexible control of movement and make this framework easy-to-use for future experiments.

Impact of pregnancy vaccine uptake and socio-demographic determinants on subsequent childhood Measles, Mumps and Rubella vaccine uptake: A UK birth cohort study

BACKGROUND

We examined the association between socio-demographic determinants and uptake of childhood Measles, Mumps & Rubella (MMR) vaccines and the association between pregnant women's pertussis vaccine uptake and their children's MMR vaccine uptake.

METHODS

We used nationally-representative linked mother-baby electronic records from the United Kingdom's Clinical-Practice-Research-Datalink. We created a birth cohort of children born between 01.01.2000 and 12.12.2020. We estimated the proportion vaccinated with first MMR vaccine by age 2 years and first and second MMR vaccines by age 5 years. We used survival-analysis and Cox proportional hazard models to examine the association between deprivation, ethnicity and maternal age and pertussis vaccination in pregnancy and children's MMR uptake.

RESULTS

Overall, 89.4 % (710,797/795,497) of children had first MMR by age 2 years and 92.6 % (736,495/795,497) by age 5 years. Among children still in the cohort when second MMR was due, 85.9 % (478,480/557,050) had two MMRs by age 5 years. Children from the most-deprived areas, children of Black ethnicity and children of mothers aged < 20 years had increased risk of being unvaccinated compared with children from the least-deprived areas, White children and children of mothers aged 31-40 years: first MMR by 5 years, adjusted Hazard Ratios (HR):0.86 (CI:0.85-0.87), HR:0.87 (CI:0.85-0.88) & HR:0.89 (CI:0.88-0.90) respectively. Deprivation was the determinant associated with the greatest risk of missed second MMR: adjusted HR:0.82 (CI:0.81-0.83). Children of mothers vaccinated in pregnancy were more likely than children of unvaccinated mothers to have MMR vaccines after adjusting for ethnicity, deprivation, and maternal age (First and Second MMRs adjusted HRs:1.43 (CI:1.41-1.45), 1.49 (CI:1.45-1.53).

CONCLUSION

Children from most-deprived areas are less likely to have MMR vaccines compared with children from least-deprived areas. Mothers who take up pregnancy vaccines are more likely to have their children vaccinated with MMR. Healthcare services should promote and facilitate access to both maternal and childhood vaccines during pregnancy.

Diagnostic performance of saliva RT-PCR test as a diagnostic tool and its utility in the detection of SARS-CoV-2 shedding with different patient characteristics: Prospective observational study

BACKGROUND

Salivary shedding of SARS-CoV-2 is a known entity and its role has been established in transmission of the disease. The present study was performed to evaluate the duration of viral shedding in saliva in COVID-19 patients and its variation among symptomatic and asymptomatic patients with or without co-morbidities.

METHODS

The present prospective observational study was conducted at the COVID-19 care hospital associated with primary to tertiary care in New Delhi, India. A total of 124 COVID-19 confirmed cases enrolled in two phases (January-March 2021; April-June 2021) who consented for 48hrly saliva and nasopharyngeal swab (NPS) specimens till discharge from the hospital for SARS-CoV-2 detection were included. The specimens obtained were tested for SARS-CoV-2 by Real-Time PCR.

RESULTS

The sensitivity and the specificity of RT-PCR on saliva were 81.7 ​% and 85.0 ​%, respectively. The sensitivity of saliva-based PCR was comparable in symptomatic and asymptomatic patients (81.6 ​% vs 82.1 ​%). The sensitivity of saliva-based PCR markedly increased in the second phase of enrollment as compared to the first phase (92.6 ​% vs 78.5 ​%) indicating higher level of salivary shedding by the delta variant of SARS-CoV-2. The sensitivity of PCR on saliva was the highest up to day seven of illness. The median duration of RNA shedding in saliva was comparable among the symptomatic and asymptomatic patients. The severity of the disease was not associated with the duration of SARS-CoV-2 shedding in saliva.

CONCLUSIONS

SARS-CoV-2 shedding in saliva continued till seven days in large number of patients including asymptomatic patients. Saliva is non-inferior to NPS specimen in the diagnosis of SARS-CoV-2. Saliva specimen is recommended as a good alternate to NPS for SARS-CoV-2 testing.

Combination of EGFR-Directed Tyrosine Kinase Inhibitors (EGFR-TKI) with Radiotherapy in Brain Metastases from Non-Small Cell Lung Cancer: A 2010-2019 Retrospective Cohort Study

INTRODUCTION

Traditionally, brain metastases have been treated with stereotactic radiosurgery (SRS), whole-brain radiation (WBRT), and/or surgical resection. Non-small cell lung cancers (NSCLC), over half of which carry EGFR mutations, are the leading cause of brain metastases. EGFR-directed tyrosine kinase inhibitors (TKI) have shown promise in NSCLC; but their utility in NSCLC brain metastases (NSCLCBM) remains unclear. This work sought to investigate whether combining EGFR-TKI with WBRT and/or SRS improves overall survival (OS) in NSCLCBM.

METHODS

A retrospective review of NSCLCBM patients diagnosed during 2010-2019 at a tertiary-care US center was performed and reported following the 'strengthening the reporting of observational studies in epidemiology' (STROBE) guidelines. Data regarding socio-demographic and histopathological characteristics, molecular attributes, treatment strategies, and clinical outcomes were collected. Concurrent therapy was defined as the combination of EGFR-TKI and radiotherapy given within 28 days of each other.

RESULTS

A total of 239 patients with EGFR mutations were included. Of these, 32 patients had been treated with WBRT only, 51 patients received SRS only, 36 patients received SRS and WBRT only, 18 were given EGFR-TKI and SRS, and 29 were given EGFR-TKI and WBRT. Median OS for the WBRT-only group was 3.23 months, for SRS + WBRT it was 3.17 months, for EGFR-TKI + WBRT 15.50 months, for SRS only 21.73 months, and for EGFR-TKI + SRS 23.63 months. Multivariable analysis demonstrated significantly higher OS in the SRS-only group (HR = 0.38, 95% CI 0.17-0.84, p = 0.017) compared to the WBRT reference group. There were no significant differences in overall survival for the SRS + WBRT combination cohort (HR = 1.30, 95% CI = 0.60, 2.82, p = 0.50), EGFR-TKIs and WBRT combination cohort (HR = 0.93, 95% CI = 0.41, 2.08, p = 0.85), or the EGFR-TKI + SRS cohort (HR = 0.46, 95% CI = 0.20, 1.09, p = 0.07).

CONCLUSIONS

NSCLCBM patients treated with SRS had a significantly higher OS compared to patients treated with WBRT-only. While sample-size limitations and investigator-associated selection bias may limit the generalizability of these results, phase II/III clinicals trials are warranted to investigate synergistic efficacy of EGFR-TKI and SRS.

Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks

Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in devising corrective neural stimulation before the onset of behavior. Recurrent Neural Networks (RNNs) are common models for sequence data. However, standard RNNs are not able to handle data with temporal distributional shifts to guarantee robust classification across time. To enable the network to utilize all temporal features of the neural input data, and to enhance the memory of an RNN, we propose a novel approach: RNNs with time-varying weights, here termed Time-Varying RNNs (TV-RNNs). These models are able to not only predict the class of the time-sequence correctly but also lead to accurate classification earlier in the sequence than standard RNNs. In this work, we focus on early sequential classification of brain-wide neural activity across time using TV-RNNs applied to a variety of neural data from mice and humans, as subjects perform motor tasks. Finally, we explore the contribution of different brain regions on behavior classification using SHapley Additive exPlanation (SHAP) value, and find that the somatosensory and premotor regions play a large role in behavioral classification.

First- versus Third-Generation EGFR Tyrosine Kinase Inhibitors in EGFR-Mutated Non-Small Cell Lung Cancer Patients with Brain Metastases

Introduction: Up to 50% of non-small cell lung cancer (NSCLC) harbor EGFR alterations, the most common etiology behind brain metastases (BMs). First-generation EGFR-directed tyrosine kinase inhibitors (EGFR-TKI) are limited by blood-brain barrier penetration and T790M tumor mutations, wherein third-generation EGFR-TKIs, like Osimertinib, have shown greater activity. However, their efficacy has not been well-studied in later therapy lines in NSCLC patients with BMs (NSCLC-BM). We sought to compare outcomes of NSCLC-BM treated with either first- or third-generation EGFR-TKIs in first-line and 2nd-to-5th-line settings. Methods: A retrospective review of NSCLC-BM patients diagnosed during 2010-2019 at Cleveland Clinic, Ohio, US, a quaternary-care center, was performed and reported following 'strengthening the reporting of observational studies in epidemiology' (STROBE) guidelines. Data regarding socio-demographic, histopathological, molecular characteristics, and clinical outcomes were collected. Primary outcomes were median overall survival (mOS) and progression-free survival (mPFS). Multivariable Cox proportional hazards modeling and propensity score matching were utilized to adjust for confounders. Results: 239 NSCLC-BM patients with EGFR alterations were identified, of which 107 received EGFR-TKIs after diagnosis of BMs. 77.6% (83/107) received it as first-line treatment, and 30.8% (33/107) received it in later (2nd-5th) lines of therapy, with nine patients receiving it in both settings. 64 of 107 patients received first-generation (erlotinib/gefitinib) TKIs, with 53 receiving them in the first line setting and 13 receiving it in the 2nd-5th lines of therapy. 50 patients received Osimertinib as third-generation EGFR-TKI, 30 in first-line, and 20 in the 2nd-5th lines of therapy. Univariable analysis in first-line therapy demonstrated mOS of first- and third-generation EGFR-TKIs as 18.2 and 19.4 months, respectively (p = 0.57), while unadjusted mPFS of first- and third-generation EGFR-TKIs was 9.3 and 13.8 months, respectively (p = 0.14). In 2nd-5th line therapy, for first- and third-generation EGFR-TKIs, mOS was 17.3 and 11.9 months, (p = 0.19), while mPFS was 10.4 and 6.08 months, respectively (p = 0.41). After adjusting for age, performance status, presence of extracranial metastases, whole-brain radiotherapy, and presence of leptomeningeal metastases, hazard ratio (HR) for OS was 1.25 (95% CI 0.63-2.49, p = 0.52) for first-line therapy. Adjusted HR for mOS in 2nd-to-5th line therapy was 1.60 (95% CI 0.55-4.69, p = 0.39). Conclusions: No difference in survival was detected between first- and third-generation EGFR-TKIs in either first or 2nd-to-5th lines of therapy. Larger prospective studies are warranted reporting intracranial lesion size, EGFR alteration and expression levels in primary tumor and brain metastases, and response rates.

Motor deficit and lack of overt dystonia in Dlx conditional Dyt1 knockout mice

DYT1 or DYT-TOR1A dystonia is early-onset generalized dystonia caused by a trinucleotide deletion of GAG in the TOR1A or DYT1 gene leads to the loss of a glutamic acid residue in the resulting torsinA protein. A mouse model with overt dystonia is of unique importance to better understand the DYT1 pathophysiology and evaluate preclinical drug efficacy. DYT1 dystonia is likely a network disorder involving multiple brain regions, particularly the basal ganglia. Tor1a conditional knockout in the striatum or cerebral cortex leads to motor deficits, suggesting the importance of corticostriatal connection in the pathogenesis of dystonia. Indeed, corticostriatal long-term depression impairment has been demonstrated in multiple targeted DYT1 mouse models. Pappas and colleagues developed a conditional knockout line (Dlx-CKO) that inactivated Tor1a in the forebrain and surprisingly displayed overt dystonia. We set out to validate whether conditional knockout affecting both cortex and striatum would lead to overt dystonia and whether machine learning-based video behavioral analysis could be used to facilitate high throughput preclinical drug screening. We generated Dlx-CKO mice and found no overt dystonia or motor deficits at 4 months. At 8 months, retesting revealed motor deficits in rotarod, beam walking, grip strength, and hyperactivity in the open field; however, no overt dystonia was visually discernible or through the machine learning-based video analysis. Consistent with other targeted DYT1 mouse models, we observed age-dependent deficits in the beam walking test, which is likely a better motor behavioral test for preclinical drug testing but more labor-intensive when overt dystonia is absent.

Artificial neural network-based rapid predictor of biological nerve fiber activation for DBS applications

Objective.Computational models are powerful tools that can enable the optimization of deep brain stimulation (DBS). To enhance the clinical practicality of these models, their computational expense and required technical expertise must be minimized. An important aspect of DBS models is the prediction of neural activation in response to electrical stimulation. Existing rapid predictors of activation simplify implementation and reduce prediction runtime, but at the expense of accuracy. We sought to address this issue by leveraging the speed and generalization abilities of artificial neural networks (ANNs) to create a novel predictor of neural fiber activation in response to DBS.Approach.We developed six variations of an ANN-based predictor to predict the response of individual, myelinated axons to extracellular electrical stimulation. ANNs were trained using datasets generated from a finite-element model of an implanted DBS system together with multi-compartment cable models of axons. We evaluated the ANN-based predictors using three white matter pathways derived from group-averaged connectome data within a patient-specific tissue conductivity field, comparing both predicted stimulus activation thresholds and pathway recruitment across a clinically relevant range of stimulus amplitudes and pulse widths.Main results.The top-performing ANN could predict the thresholds of axons with a mean absolute error (MAE) of 0.037 V, and pathway recruitment with an MAE of 0.079%, across all parameters. The ANNs reduced the time required to predict the thresholds of 288 axons by four to five orders of magnitude when compared to multi-compartment cable models.Significance.We demonstrated that ANNs can be fast, accurate, and robust predictors of neural activation in response to DBS.

Next-generation brain observatories

We propose centralized brain observatories for large-scale recordings of neural activity in mice and non-human primates coupled with cloud-based data analysis and sharing. Such observatories will advance reproducible systems neuroscience and democratize access to the most advanced tools and data.

Mesoscale cortex-wide neural dynamics predict goal-directed, but not random actions in mice several seconds prior to movement

Volition – the sense of control or agency over one’s voluntary actions – is widely recognized as the basis of both human subjective experience and natural behavior in nonhuman animals. Several human studies have found peaks in neural activity preceding voluntary actions, for example the readiness potential (RP), and some have shown upcoming actions could be decoded even before awareness. Others propose that random processes underlie and explain pre-movement neural activity. Here, we seek to address these issues by evaluating whether pre-movement neural activity in mice contains structure beyond that present in random neural activity. Implementing a self-initiated water-rewarded lever-pull paradigm in mice while recording widefield [Ca++] neural activity we find that cortical activity changes in variance seconds prior to movement and that upcoming lever pulls could be predicted between 3 and 5 s (or more in some cases) prior to movement. We found inhibition of motor cortex starting at approximately 5 s prior to lever pulls and activation of motor cortex starting at approximately 2 s prior to a random unrewarded left limb movement. We show that mice, like humans, are biased toward commencing self-initiated actions during specific phases of neural activity but that the pre-movement neural code changes over time in some mice and is widely distributed as behavior prediction improved when using all vs. single cortical areas. These findings support the presence of structured multi-second neural dynamics preceding self-initiated action beyond that expected from random processes. Our results also suggest that neural mechanisms underlying self-initiated action could be preserved between mice and humans.

How did the covid-19 pandemic affect lower respiratory tract infections in young children in England?

Background

Social distancing policies to reduce transmission of covid-19 also reduced children's exposures to endemic respiratory viruses. We aimed to examine the impact of the covid-19 pandemic on lower respiratory tract infections in under 5s presenting to primary care in England.

Methods

Longitudinal trends analysis using electronic health records from a nationally representative primary care database. Our target population was children aged &lt;5 years registered with a primary care practice from January 2015 to March 2021.

Our main outcome was total weekly contacts with primary care for a lower respiratory tract infection (LRTI). We defined three pandemic phases from March 2020 - March 2021: i) first national lockdown (late March to early June 2020), ii) childcare settings reopened and second national lockdown with schools open (mid-June to mid-December 2020) and iii) third national lockdown with schools closed (late December 2020 to end of March 2021). We compared outcomes during each of the three phases with corresponding calendar weeks during pre-pandemic years 2015 to 2019.

Results

Our study population included 843 020 children &lt;5 years who had 1 076 181 contacts with primary care for LRTIs. During the first phase (first lockdown) there were falls of 79.3% (95% CI: 73.6 to 84.5) from an average of 28 547 primary care contacts for LRTI in 2015 - 2019 to 5915 in 2020; there was a 78.9% (95% CI: 73.7 to 83.9) fall in phase two (childcare settings reopened and second lockdown) from 107 873 to 22 792 contacts; and a 77.7% (95% CI: 73.5 to 81.4) fall in phase three (third lockdown) from 57 200 to 12 764 contacts.

Conclusions

Children under 5 in England had fewer contacts with primary care for LRTIs during the covid-19 pandemic. This change likely reflects lower prevalence of respiratory illness due to fewer social contacts. This may impact on future health service use as these children have had less exposure, and therefore may have less immunity, to respiratory diseases.

Key messages

• Children under 5 had fewer contacts with primary care for lower respiratory tract infections during the covid-19 pandemic in England likely due to the restrictions in place to reduce social contacts.

• The falls in lower respiratory tract infections during the covid-19 pandemic in under 5s may mean they have less immunity to respiratory viruses which may impact upon their future health service use.

The use of EPR spectroscopy to study transcription mechanisms

Electron paramagnetic resonance (EPR) spectroscopy has become a promising structural biology tool to resolve complex and dynamic biological mechanisms in-vitro and in-cell. Here, we focus on the advantages of continuous wave (CW) and pulsed EPR distance measurements to resolve transcription processes and protein-DNA interaction. The wide range of spin-labeling approaches that can be used to follow structural changes in both protein and DNA render EPR a powerful method to study protein-DNA interactions and structure-function relationships in other macromolecular complexes. EPR-derived data goes well beyond static structural information and thus serves as the method of choice if dynamic insight is needed. Herein, we describe the conceptual details of the theory and the methodology and illustrate the use of EPR to study the protein-DNA interaction of the copper-sensitive transcription factor, CueR.

Update on the Management of Brain Metastasis

Brain metastases occur in almost one-third of adult patients with solid tumor malignancies and lead to considerable patient morbidity and mortality. The rising incidence of brain metastases has been ascribed to the development of better imaging and screening techniques and the formulation of better systemic therapies. Until recently, the multimodal management of brain metastases focused primarily on the utilization of neurosurgical techniques, with varying combinations of whole-brain radiation therapy and stereotactic radio-surgical procedures. Over the past 2 decades, in particular, the increment in knowledge pertaining to molecular genetics and the pathogenesis of brain metastases has led to significant developments in targeted therapies and immunotherapies. This review article highlights the recent updates in the management of brain metastases with an emphasis on novel systemic therapies.

Motor cortical influence relies on task-specific activity covariation

During limb movement, spinal circuits facilitate the alternating activation of antagonistic flexor and extensor muscles. Yet antagonist cocontraction is often required to stabilize joints, like when loads are handled. Previous results suggest that these different muscle activation patterns are mediated by separate flexion- and extension-related motor cortical output populations, while others suggest recruitment of task-specific populations. To distinguish between hypotheses, we developed a paradigm in which mice toggle between forelimb tasks requiring antagonist alternation or cocontraction and measured activity in motor cortical layer 5b. Our results conform to neither hypothesis: consistent flexion- and extension-related activity is not observed across tasks, and no task-specific populations are observed. Instead, activity covariation among motor cortical neurons dramatically changes between tasks, thereby altering the relation between neural and muscle activity. This is also observed specifically for corticospinal neurons. Collectively, our findings indicate that motor cortex drives different muscle activation patterns via task-specific activity covariation.

P302 Disseminated histoplasmosis: Rare entity in immunocompromised individuals in India

 

Poster session 2, September 22, 2022, 12:30 PM - 1:30 PM

Invasive mycoses kill more than one million people every year. The disease burden of mycoses has increased over the last 20 years and the importance of fungal disease is expected to keep increasing in the years to come. One of these mycoses, histoplasmosis, a disease caused by species of dimorphic genera, Histoplasma and is endemic in the USA, Asia, and Africa with sporadic cases reported from India. In the United States alone, 3.4 cases/100 000 people occur yearly. In India, prevalence of histoplasmosis is seen in the eastern part of the country and few cases are reported from north India. Here, we present four cases of classic progressive disseminated histoplasmosis from non-endemic central and northern parts of India.

Cases I and II: Two cases, firstly a 51-year-old male resident of Delhi, came with complaints of fever, generalized weakness and weight loss for the past 6 months, and another a 55-year-old in an apparently immunocompetent female from a non-endemic state in central India. The disease was diagnosed by bone marrow aspirate incidentally.

Cases III and IV: A 25-year-old female and a 29-year-old HIV-infected female, with chief complaints of multiple skins colored swellings on her face, neck, chest, and back and also on both limbs. Physical examination revealed multiple skin-colored papules and nodules coalescing to form large plaques on the face, neck, upper back, and chest which had overlying yellowish-brown crusting (Fig.1). Her entire face was involved with depression of the nasal bridge and madarosis. Multiple discrete 0.1-0.5 mm papules and nodules on bilateral upper and lower limbs. Patient was started on the treatment of cutaneous histoplasmosis with injection of liposomal amphotericin-B 100 mg intravenous (around 3 mg/kg/day) after pre-medication for 10 days. For both cases, capsule itraconazole 200 mg BD started for 4 days. Patient responded well to the treatment and follow-up showed improvement in the condition of the patient.

Results

In all the cases, fine needle aspirate cytology of the lesions showed plenty of inflammatory cells and macrophages in pathological microscopic examination. Microscopic examination of skin tissue revealed that macrophages comprising of yeast forms of Histoplasma have pericellular halo around them. Moreover, on long incubation of biopsy sample on SDA media plate at 27˚C, white/buff colonies with yellow-tan on the back were observed. Furthermore, microscopic examination of grown fungal culture showed mycelial septate hyphae bearing round to pear-shaped, smooth-walled broadly elliptical microconidia, or tuberculate macroconidia. In all the cases, clinical suspicion, histopathological and mycological findings (microscopy, culture and post-culture sequencing) led to a confirmatory diagnosis of progressive disseminated Histoplasmosis by H. capsulatum var. capsulatum was made.

Conclusion

In all, 3 of these cases are of progressive disseminated histoplasmosis in apparently immunocompetent patients from the non-endemic states of north India. On the contrary, one of the cases was HIV positive with mucocutaneous lesions. Disseminated histoplasmosis in immunocompetent individuals is not a rare entity, in India. High clinical suspicion and awareness regarding the pathogen are required. From the point of good patient care, an accurate diagnosis, and timely management in cases of histoplasmosis are warranted.

Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis

A key aspect of neuroscience research is the development of powerful, general-purpose data analyses that process large datasets. Unfortunately, modern data analyses have a hidden dependence upon complex computing infrastructure (e.g., software and hardware), which acts as an unaddressed deterrent to analysis users. Although existing analyses are increasingly shared as open-source software, the infrastructure and knowledge needed to deploy these analyses efficiently still pose significant barriers to use. In this work, we develop Neuroscience Cloud Analysis As a Service (NeuroCAAS): a fully automated open-source analysis platform offering automatic infrastructure reproducibility for any data analysis. We show how NeuroCAAS supports the design of simpler, more powerful data analyses and that many popular data analysis tools offered through NeuroCAAS outperform counterparts on typical infrastructure. Pairing rigorous infrastructure management with cloud resources, NeuroCAAS dramatically accelerates the dissemination and use of new data analyses for neuroscientific discovery.

Extrapulmonary tuberculosis presentation in the form of a chest wall abscess with no pulmonary involvement in the UK: a case report

The presentation of an extrapulmonary manifestation of tuberculous (TB) infection to a tertiary care facility in the UK is a rare event given its low prevalence. This case report focuses on an atypical presentation of an extrapulmonary tuberculosis (EPTB) infection in the form of a chest wall abscess. This was recognized and managed appropriately. This case however elucidates vital learning as migration from around the globe would contribute to an increasing number of TB/EPTB infections. The wide array and indolent nature of their presentation creates diagnostic and treatment challenges. Appreciation for the epidemiology, risk factors, effective and prompt treatment with follow up protocols would help develop pathways for better care. Within the UK, despite it being a low-risk country for TB, there is need for increased awareness, education with established management pathways and governance for TB and EPTB infections.

Recurrent neural networks controlling musculoskeletal models predict motor cortex activity during novel limb movements

Goal-driven networks trained to perform a task analogous to that performed by biological neural populations are being increasingly utilized as insightful computational models of motor control. The resulting dynamics of the trained networks are then analyzed to uncover the neural strategies employed by the motor cortex to produce movements. However, these networks do not take into account the role of sensory feedback in producing movement, nor do they consider the complex biophysical underpinnings of the underlying musculoskeletal system. Moreover, these models can not be used in context of predictive neuromechanical simulations for hypothesis generation and prediction of neural strategies during novel movements. In this research, we adapt state-of-the-art deep reinforcement learning (DRL) algorithms to train a controller to drive a developed anatomically accurate monkey arm model to track experimentally recorded kinematics. We validate that the trained controller mimics biologically observed neural strategies to produce movement. The trained controller generalizes well to unobserved conditions as well as to perturbation analyses. The recorded firing rates of motor cortex neurons can be predicted from the controller activity with high accuracy even on unseen conditions. Finally, we validate that the trained controller outperforms existing goal-driven and representational models of motor cortex in single neuron decoding accuracy, thus showing the utility of the complex underpinnings of anatomically accurate models in shaping motor cortex neural activity during limb movements. The learned controller can be used for hypothesis generation and prediction of neural strategies during novel movements and unobserved conditions.

Alien genome mobilization and fixation utilizing an apomixis mediated genome addition (AMGA) strategy in Pennisetum to improve domestication traits of P. squamulatum

An approach to release 'frozen' variability in apomictic species using sexuality of another species, eventually its utilization in crop improvement and de-novo domestication of crop wild relatives is presented. Pennisetum squamulatum, a secondary gene pool species of pearl millet (P. glaucum), harbours many desirable traits. However, it was neither utilized to improve pearl millet fodder traits nor improvement of its own domestication traits was attempted, due to the complexities of genomes and apomictic reproduction. To overcome this, we followed an Apomixis Mediated Genome Addition (AMGA) strategy and utilized the contrasting reproductive capacities (sexuality and apomixis) of both the species to access the otherwise un-available variability embedded in P. squamulatum. Segregating population of interspecific hybrids exhibited significant variability and heterosis for desired morphological, agronomical, and nutritional traits. Elite apomictic and perennial hybrids were evaluated in breeding trials, and eventually a novel grass cultivar was released for commercial cultivation in India. The performance of newly developed cultivar was superior to other adapted perennial grasses of arid and semi-arid rangelands. Through AMGA, the sexuality of one species was successfully utilized to 'release' the 'frozen' variability embedded in another species. Subsequently, the hybrids representing desirable trait combinations were again 'fixed' utilizing the apomixis alleles from the male parent in a back-and-forth apomixis-sexual-apomixis selection cycle. This study also demonstrated the potential of AMGA to improve crop relatives through genomes introgression as well as de novo domestication of new crops from wild species.

Modeling the behavior of multiple subjects using a Cauchy-Schwarz regularized Partitioned Subspace Variational AutoEncoder (CS-PS-VAE)

Effectively modeling and quantifying behavior is essential for our understanding of the brain. Modeling behavior across different subjects in a unified manner remains a significant challenge in the field of behavioral quantification, which necessitates partitioning the behavioral data into features that are common across subjects, and others that are distinct to each subject. We build on a semi-supervised approach to partition the subspace adequately known as a Partitioned Subspace Variational AutoEncoder (PS-VAE), and propose a novel regularization based on the Cauchy-Schwarz divergence to model the distinct features across subjects. Our model, called the Cauchy-Schwarz regularized Partitioned Subspace Variational AutoEncoder (CS-PS-VAE), successfully models continuously varying differences in behavior, and models distinct features of the behavioral videos across subjects in an unsupervised manner. This method is also successful at uncovering the relationships between recorded neural data and the ensuing behavior.

Motor cortex activity across movement speeds is predicted by network-level strategies for generating muscle activity

Learned movements can be skillfully performed at different paces. What neural strategies produce this flexibility? Can they be predicted and understood by network modeling? We trained monkeys to perform a cycling task at different speeds, and trained artificial recurrent networks to generate the empirical muscle-activity patterns. Network solutions reflected the principle that smooth well-behaved dynamics require low trajectory tangling. Network solutions had a consistent form, which yielded quantitative and qualitative predictions. To evaluate predictions, we analyzed motor cortex activity recorded during the same task. Responses supported the hypothesis that the dominant neural signals reflect not muscle activity, but network-level strategies for generating muscle activity. Single-neuron responses were better accounted for by network activity than by muscle activity. Similarly, neural population trajectories shared their organization not with muscle trajectories, but with network solutions. Thus, cortical activity could be understood based on the need to generate muscle activity via dynamics that allow smooth, robust control over movement speed.

Uncovering the effect of different brain regions on behavioral classification using recurrent neural networks

As our ability to record neural activity from a larger number of brain areas increases, we need to develop tools to understand how this activity is related to ongoing behavior. Recurrent neural networks (RNNs) have been shown to perform successful classification for sequence data. However, they are black box models: once trained, it is difficult to uncover the mechanisms that they are using to classify. In this study, we analyze the effect of RNNs on classifying behavior using a simulated dataset and a widefield neural activity dataset as mice perform a self-initiated behavior. We show that RNNs are comparable to, or outperform, traditional classification methods such as Support Vector Machine (SVM), and can also lead to accurate prediction of behavior. Using dimensionality reduction, we visualize the activity of the RNNs to better understand the classification mechanisms of the RNNs. Finally, we are able to accurately pinpoint the effect of different regions on behavioral classification. This study highlights the utility and interpretability of RNNs while classifying behavior using neural activity from different regions.

Are children at schools registered to The Daily Mile™ more physically active?

Background

The Daily Mile (TDM) is among the most popular school-based running programmes recommended globally by governments and the WHO to meet the shortfalls in children's physical activity. In England, it has been adopted by 1 in 5 primary schools. However, its impact on children's physical activity has not been assessed at scale. We aimed to compare a)minutes (mins) of moderate to vigorous physical activity (MVPA) in and outside school hours and b)meeting physical activity guidelines in primary school children in England, comparing those in schools registered with TDM with those that were not.

Methods

This was a cross-sectional study. We used self-reported data of 49,561 English primary school children(5-11 years) from the Active Lives Children and Young People Survey and TDM registration data of their school. We compared mins of MVPA in and outside school hours between children in TDM-registered and non-registered schools using a multilevel zero-inflated negative binomial model; and the differences in the likelihood of meeting physical activity guidelines based on TDM registration with a multilevel logistic regression model. All models included a random effect for school and adjusted for potential confounders.

Results

Children attending TDM-registered schools reported an extra 36 mins of MVPA a week overall, including 10 additional mins (95%CI:3,16) MVPA/week during school hours and 26 additional (95%CI:4,44) mins MVPA/week outside school hours. Children in TDM-registered schools were 6% more likely to meet physical activity guidelines compared to those who were not(RR:1.06 (95%CI:1.02,1.11)).

Conclusions

Children in primary schools registered to TDM report more physical activity that is not compensated for outside school hours. However, the absolute differences fall considerably short of international guidelines across the whole child population. Therefore, a whole school and systems-based approach is required, embedding school-based running programmes.

Key messages

Children in schools registered to TDM report more MVPA overall, inside, and outside school hours; suggesting no compensation of activity in those who are registered. TDM is a potential solution to increase children’s physical activity during the school day.

Internalized weight bias in the relationship between mental health and obesity in UK adolescents

Background

It is crucial to promote mental and physical health during adolescence to protect against lifetime risks of mental health problems and obesity. Internalized weight bias (self-directed stigmatizing attitudes about perceived weight status) and bullying are implicated as potential mechanisms in the relationship between mental health and obesity in adolescence. We examined internalized weight bias and bullying as potential mediators of the relationship between mental health and weight status across adolescence in the United Kingdom (UK).

Methods

We analysed data on 8,688 adolescents from the UK Millennium Cohort Study. Weight status was defined using sex and age specific International Obesity Taskforce cut points for body-mass index (not overweight/obese; overweight; obese) at 11 and 17 years. Mental health was defined using parental reported emotional (anxiety and depression), and externalizing (aggression and impulsivity) symptoms at 11 and 17 years (low; moderate; high). Self-reported measures of internalized weight bias captured via body-dissatisfaction and self-esteem and bullying at 14 years were tested as mediators. We used Generalized Structural Equation Models to examine longitudinal pathways between weight status and mental health across 11 and 17 years, whilst accounting for concurrent associations and potential confounders.

Results

Adolescents with high emotional (relative risk (RR) 1.98, 95% CI 1.28 to 3.07) or externalizing symptoms (RR 2.07, 95% CI 1.23 to 3.48) at 11 years were twice as likely to be obese at 17 years compared with those who had low symptoms. The impact of emotional and externalizing symptoms on weight status was found to be partially attributable to internalized weight bias, but not bullying, with significant mediation for body-dissatisfaction and low self-esteem.

Conclusions

Internalized weight bias partially explains the relationship between mental health and weight status across adolescence.

Key messages

There is a need for a holistic, early prevention strategy to focus on reducing weight stigma to encourage healthy mental and physical development of children. The relationship between mental health and weight status across adolescence is partly attributable to internalized weight bias.

A core outcome set for school-based physical activity interventions: an international consensus

Background

Studies of school-based physical activity interventions vary in the outcomes they measure. This prevents comparisons of results to establish impacts. We aimed to develop a core outcome set agreed by key stakeholders for future studies of school-based physical activity interventions.

Methods

We used a modified-Delphi consensus method. First, we conducted a systematic review to identify outcomes measured in relevant studies and listed these in a Delphi survey. Next, we recruited key stakeholders to complete 2 survey rounds: Round 1 was to rate each outcome from ‘not important' to ‘critical', and Round 2 was to re-rate the outcomes based on feedback from Round 1. Outcomes rated ‘critical' by 70% of stakeholders (i.e., reaching consensus) were highlighted. Then, using the full list of outcomes, we conducted a children's workshop to include their views. Finally, we held a stakeholder meeting to discuss results and agree consensus.

Results

We identified 50 outcomes from the systematic review. Sixty-five stakeholders (16 educators, 13 health professionals, 12 parents, 24 researchers) representing 9 countries completed both survey rounds; 13/50 outcomes reached consensus. Children (n = 16) identified 8 outcomes of importance; 3 were consistent with the survey results. Stakeholders attending the meeting (n = 13) reached consensus on 14 outcomes to be included in the core outcome set: fitness, physical activity intensity, energy, sleep, diet, happiness, stress, depression, anxiety, wellbeing, self-esteem, enjoyment, concentration, and focus. These core outcomes were reviewed and agreed by all 65 stakeholders.

Conclusions

Our core outcome set agreed by international stakeholders includes physical and mental health, and cognitive function. We recommend its use in future studies of school-based physical activity interventions. Findings from future studies can be compared and combined which will be relevant to public health policy makers and educators.

Key messages

School-based physical activity interventions should measure physical and mental health, and cognitive function. Wide use of this core outcome set will enable findings to be compared and combined.

Implementation of The Daily Mile™: survey of primary schools in Greater London

Background

The Daily Mile™ is a free school-based active mile intervention. Its main features include that children run or jog for 15 minutes at least 3 times a week (3x/wk) during school hours. The Daily Mile Foundation recommends 10 principles for successful implementation. These are it is (1) quick (15 minutes), (2) fun, (3) whole school participates, (4) it takes place in all weathers, (5) 3x/wk in addition to curricular lessons (not during PE, breaks, before/after school), (6) ideally in the school playground, (7) safe, (8) simple (no equipment), (9) children go at their own pace and (10) no change of clothes or shoes is needed. The aim of this study was to identify how many Greater London primary schools adopting The Daily Mile implement its 10 principles.

Methods

In September 2020, we sent all state-funded primary schools (n = 1721) in every Greater London borough (n = 32) a survey to find out if and how they implemented The Daily Mile.

Results

By June 2021, 368 (21%) schools responded to our survey (at least one from every London borough). Of these, 195 (53%) schools adopted The Daily Mile of which only 7 (4%) reported implementing all 10 principles; a median 7 (IQR: 6,8) principles were reported implemented. Whole school participation was reported by 93 (48%) Daily Mile schools, 104 (53%) reported implementing The Daily Mile for 15 minutes, 127 (65%) implemented it at least 3x/wk, and 149 (76%) schools reported that the children ran or jogged during The Daily Mile. A large proportion of schools reported implementing The Daily Mile in the school playground and that it was done simply (both n = 171, 88%), but only 85 (44%) schools reported implementing it during lessons.

Conclusions

Daily Mile schools in Greater London implement 7/10 principles on average. Whether implementing all the principles limits the success of its desired effect is unclear. Studies assessing effects of The Daily Mile should consider its implementation when reporting results.

Key messages

Of The Daily Mile’s 10 principles, an average of 7 are implemented in London schools. Studies examining The Daily Mile should consider implementation which may impact its desired effect.

Chronic, cortex-wide imaging of specific cell populations during behavior

Measurements of neuronal activity across brain areas are important for understanding the neural correlates of cognitive and motor processes such as attention, decision-making and action selection. However, techniques that allow cellular resolution measurements are expensive and require a high degree of technical expertise, which limits their broad use. Wide-field imaging of genetically encoded indicators is a high-throughput, cost-effective and flexible approach to measure activity of specific cell populations with high temporal resolution and a cortex-wide field of view. Here we outline our protocol for assembling a wide-field macroscope setup, performing surgery to prepare the intact skull and imaging neural activity chronically in behaving, transgenic mice. Further, we highlight a processing pipeline that leverages novel, cloud-based methods to analyze large-scale imaging datasets. The protocol targets laboratories that are seeking to build macroscopes, optimize surgical procedures for long-term chronic imaging and/or analyze cortex-wide neuronal recordings. The entire protocol, including steps for assembly and calibration of the macroscope, surgical preparation, imaging and data analysis, requires a total of 8 h. It is designed to be accessible to laboratories with limited expertise in imaging methods or interest in high-throughput imaging during behavior.

Efficacy and tolerability of eslicarbazepine acetate as monotherapy in patients of newly diagnosed focal epilepsy

Introduction

Eslicarbazepine Acetate, a novel anti-epileptic drug has been approved as monotherapy in focal onset seizures, with/without secondary generalization in adults. Eslicarbazepine has many advantages over older anti-epileptic drugs and is useful in patients of new onset focal epilepsy.

Objectives

Aim of our study was to determine the efficacy and safety of Eslicarbazepine Acetate, observe its well-tolerated use and monitor adverse effects in newly diagnosed patients of focal epilepsy.

Methods

Study was done at Department of Psychiatry, Teerthanker Mahaveer University, Moradabad. A total of 30 newly diagnosed cases of focal epilepsy between 18-60 years of age were studied for 6 months, using a Semi-structured Interview and Liverpool Adverse Events Profile.

Results

Majority of patients were males (58%), between 21-30 years. Patients with partial/focal seizures (63%) were more common than those of generalized seizures (37%). Majority of the participants had 1-2 episodes of focal seizures weekly(48%), while some had almost daily(32%). Majority were on Eslicarbazepine Acetate 800 mg in two divided doses daily (64%), while the others received 1200 mg in three divided doses(32%). The mean Liverpool Adverse Events Profile score initially was 28.34 ± 6.28 which significantly improved after 4 weeks treatment to 22.80 ± 4.35 (p < 0.05). The improvement in newly diagnosed focal seizures patients was significantly more than other patients (p < 0.05). No major side effects were observed.

Conclusions

Eslicarbazepine Acetate as a monotherapy is effective in treating focal epilepsy. Better results of this drug are found in newly diagnosed focal epilepsy patients.

Disclosure

No significant relationships.

Dynamics of noise-induced wave-number selection in the stabilized Kuramoto-Sivashinsky equation

We revisit the question of wave-number selection in pattern-forming systems by studying the one-dimensional stabilized Kuramoto-Sivashinsky equation with additive noise. In earlier work, we found that a particular periodic state is more probable than all others at very long times, establishing the critical role of noise in the selection process. However, the detailed mechanism by which the noise picked out the selected wave number was not understood. Here, we address this issue by analyzing the noise-averaged time evolution of each unstable mode from the spatially homogeneous state, with and without noise. We find drastic differences between the nonlinear dynamics in the two cases. In particular, we find that noise opposes the growth of Eckhaus modes close to the critical wave number and boosts the growth of Eckhaus modes with wave numbers smaller than the critical wave number. We then hypothesize that the main factor responsible for this behavior is the excitation of long-wavelength (q→0) modes by the noise. This hypothesis is confirmed by extensive numerical simulations. We also examine the significance of the magnitude of the noise.

Ten-year fracture risk predicted by proximal femur Hounsfield units

Colon cancer screening occurs at younger ages than osteoporosis screening. Bone density measurements using virtual colonoscopy performed for colon cancer screening can provide an early warning sign of patients at potential risk for osteoporosis-related fractures. Earlier identification may improve treatment and potentially fracture prevention.

INTRODUCTION

Opportunistic osteoporosis screening with computed tomography colonography (CTC) offers an opportunity to capitalize on earlier colorectal cancer screening to identify patients at risk of future fractures. The purpose of this study is to evaluate 10-year fracture and specifically hip fracture risk based on Hounsfield units (HU) obtained from CTC.

METHODS

We identified all CTC scans between 2004 and 2007 of patients 40 years and older with 10 years minimum follow-up. Hounsfield units were measured within the proximal femur and fractures identified via worldwide military records. Patients were stratified into two cohorts based on the presence or lack of a fracture in the wrist, spine, hip, or proximal humerus. Hounsfield unit measurements were compared between groups using Student's t test and the HU threshold was calculated that best approximated an 80% sensitivity to optimally screen patients for fracture risk. The odds ratio, negative predictive value, 10-year incidence of fracture, and survival curves were calculated.

RESULTS

We identified 3711 patients with 183 fractures over 10 years. The HU threshold that corresponded with an 80% sensitivity to identify fractures was 112 HU. The negative predictive value (NPV) for overall fractures and hip fractures was over 97%. The 10-year fracture incidence was higher in patients below 112 HU compared to those above for both overall fractures (6.3% vs 1.7%) and hip fractures (2.7% vs 0.07%). The 112 HU threshold corresponds with an odds ratio for overall fracture and hip fractures of 2.5 (95% confidence interval (CI), 1.7-3.6) and 24.5 (95% CI, 3.3-175.5), respectively.

CONCLUSION

In the 10 years following CTC, patients who experienced a fracture had lower hip HU. Decreasing HU on CTC may be an early warning sign of fracture potential.

Impact of school-based physical activity interventions in primary schools: measuring what matters

Background

A growing number of small studies suggest that school-based physical activity initiatives can help children achieve the recommended 60 minutes of physical activity per day. However, the heterogeneity of outcomes and measures used in small studies prevents pooling of results to demonstrate whether short-term health benefits are sustained. Qualitative studies suggest many benefits that are not represented by outcomes in trials to date. The aim of this study was to generate a list of outcomes that have been studied to develop a core outcome set (COS) acceptable to key stakeholders for future studies evaluating school-based physical activity initiatives.

Methods

We searched six databases (MEDLINE, EMBASE, PsycINFO, CINAHL, CENTRAL and Cochrane Database of Systematic Reviews) systematically for reviews of school-based physical activity interventions, and extracted relevant studies to identify the outcomes and measures used in each paper. A long list was generated from the literature and a previous workshop with stakeholders. This study is registered with COMET (#1322), and with PROSPERO (CRD42019146621).

Results

75/121 cited studies drawn from 53/2409 reviews met our inclusion criteria. We grouped 65 outcomes into 3 domains: (i) physical activity and health (ii) social and emotional health, and (iii) educational attainment. We will conduct two Delphi survey rounds with four stakeholder groups (health professionals, researchers, educators and parents) to rate the importance of each outcome. A core outcome set will be generated from a consensus process.

Conclusions

There is currently a large variation of outcomes and measures studied that precludes evidence synthesis of the impact of school-based physical activity interventions. Consensus methods are needed to focus research on the outcomes that matter the most to key stakeholders and to provide tools for future studies to assess long-term impact.

Key messages

Variations in outcomes studied precludes evidence synthesis of SBPA intervention impacts. A core outcome set is needed to ensure future SBPA interventions measure outcomes that matter the most.

Early years pathways to inequalities in childhood asthma? A causal mediation analysis

Background

Asthma affects one in five children in the United Kingdom (UK). Children in deprived areas have twice as many unplanned admissions for wheeze but mediating pathways between socioeconomic circumstances and asthma remain unclear. We aimed to quantify which early years pathways explain inequalities in childhood asthma in the UK.

Methods

We analysed data on 10650 children from the Millennium Cohort Study (MCS), a nationally representative sample of the UK population. Early life socioeconomic circumstance (SEC) was measured by maternal education at birth. Our outcome was parent-reported asthma at 5 years of age categorised as none, diagnosed asthma and diagnosed asthma with wheeze symptoms in the preceding year. Mediators were grouped into perinatal characteristics (maternal BMI, breastfeeding duration, birthweight, gestation, maternal smoking and alcohol use during pregnancy), neighbourhood features (pollution, grime and environment issues, traffic volume, housing quality) and the home environment (damp/condensation, tenure, pets, tobacco smoke). We used multinomial regression to examine the total effect of SEC on childhood asthma, then adjusted for all potential mediators. Using causal mediation analysis, we will estimate the proportion mediated by blocks of mediators and the natural indirect effect (NIE) via each block of mediators.

Results

Children whose mothers had no qualifications were more than twice as likely to have asthma by the age of 5 years with a wheeze episode in the preceding year compared with those whose mothers had degree-level qualifications (relative risk (RR) 2.21, 95% CI 1.44 to 3.40). After adjustment for all mediators, there was a 69% reduction to aRR 1.38 (95% CI 0.89 to 2.14).

Conclusions

Perinatal characteristics and early years neighbourhood features and measures of the home environment partially contribute to inequalities in childhood asthma.

Key messages

The antenatal period and early years of development are important for targeting interventions to reduce inequalities in asthma. About two-thirds of the social inequality in childhood asthma was explained by perinatal characteristics, early years neighbourhood features and the home environment.

Impact of financial incentives for primary care to give long acting reversible contraceptive advice

Background

Long acting reversible contraceptives (LARC) are cost-effective but uptake remains poor even in high income settings. In 2009/10, a pay-for-performance (P4P) scheme in the United Kingdom was introduced for primary care physicians to offer advice about LARC to women attending for contraceptive care. We examined the equity and impact of this scheme on LARC uptake and abortions

Methods

We examined records of women aged 13 to 54 years registered with a primary care practice in the UK Clinical Practice Research Datalink from 2004/05 to 2013/14. We used interrupted time series analysis to examine trends in annual LARC and non-LARC hormonal contraception (NLHC) uptake and abortion rates, stratified by age, region and deprivation groups, before and after P4P was introduced in 2009/10.

Results

LARC uptake among women of all ages increased immediately after P4P with step change of 5.36 per 1,000 women (95% CI 5.26 to 5.45). Largest increase was in women aged 20 to 24 years (8.40, 8.34 to 8.47). NLHC uptake fell in all women with a step change of -22.9 (-24.5 to -21.2). Among LARC methods, contraceptive injection and implant had the greatest increase after P4P; step changes were 1.68 (1.67 to 1.70) and 1.64 (1.63 to 1.65) respectively. Abortion rates fell across all 12 regions in UK and in all women immediately after P4P with a step change of -2.28 (-2.99 to -1.57). The largest falls occurred in women aged 13 to 19 years (step change -5.04, -7.56 to -2.51) and women from the most deprived group (step change -4.40, -6.89 to -1.91).

Conclusions

Pay-for-performance scheme for primary care physicians to give LARC advice to women attending for contraception was associated with desirable impact and equity of LARC prescriptions and abortion.

LARC uptake increased in women of all ages, especially 13-19 and 20-24 years. Abortion rates fell in all UK regions and age groups, particularly 13-19 and 20-24 years and those from deprived quintile.

Key messages

Pay-for-performance scheme for primary care practitioners to give LARC advice to women attending for contraception was associated with desirable impact and equity of LARC prescriptions and abortion. LARC uptake increased in women of all ages, especially 13-19 and 20-24 years. Abortion rates fell in all UK regions and age groups, particularly 13-19 and 20-24 years and those from deprived quintile.

Prevalence and duration of gastrointestinal symptoms before diagnosis of Inflammatory Bowel Disease and predictors of timely specialist review: a population-based study

BACKGROUND AND AIMS

Lack of timely referral and significant waits for specialist review amongst individuals with unresolved gastrointestinal (GI) symptoms can result in delayed diagnosis of Inflammatory Bowel Disease (IBD).

AIMS

To determine the frequency and duration of GI symptoms and predictors of timely specialist review before the diagnosis of both Crohn's Disease (CD) and ulcerative colitis (UC).

METHODS

Case-control study of IBD matched 1:4 for age and sex to controls without IBD using the Clinical Practice Research Datalink from 1998-2016.

RESULTS

We identified 19,555 cases of IBD, and 78,114 controls. 1 in 4 cases of IBD reported gastrointestinal symptoms to their primary care physician more than 6 months before receiving a diagnosis. There is a significant excess prevalence of GI symptoms in each of the 10 years before IBD diagnosis. GI symptoms were reported by 9.6% and 10.4% at 5 years before CD and UC diagnosis respectively compared to 5.8% of controls. Amongst patients later diagnosed with IBD, <50% received specialist review within 18 months from presenting with chronic GI symptoms. Patients with a previous diagnosis of irritable bowel syndrome or depression were less likely to receive timely specialist review (IBS: HR=0.77, 95%CI 0.60-0.99, depression: HR=0.77, 95%CI 0.60-0.98).

CONCLUSIONS

There is an excess of GI symptoms 5 years before diagnosis of IBD compared to the background population which are likely attributable to undiagnosed disease. Previous diagnoses of IBS and depression are associated with delays in specialist review. Enhanced pathways are needed to accelerate specialist referral and timely IBD diagnosis.

Performance Limitations in Sensorimotor Control: Trade-Offs Between Neural Computation and Accuracy in Tracking Fast Movements

The ability to move fast and accurately track moving objects is fundamentally constrained by the biophysics of neurons and dynamics of the muscles involved. Yet the corresponding trade-offs between these factors and tracking motor commands have not been rigorously quantified. We use feedback control principles to quantify performance limitations of the sensorimotor control system (SCS) to track fast periodic movements. We show that (1) linear models of the SCS fail to predict known undesirable phenomena, including skipped cycles, overshoot and undershoot, produced when tracking signals in the "fast regime," while nonlinear pulsatile control models can predict such undesirable phenomena, and (2) tools from nonlinear control theory allow us to characterize fundamental limitations in this fast regime. Using a validated and tractable nonlinear model of the SCS, we derive an analytical upper bound on frequencies that the SCS model can reliably track before producing such undesirable phenomena as a function of the neurons' biophysical constraints and muscle dynamics. The performance limitations derived here have important implications in sensorimotor control. For example, if the primary motor cortex is compromised due to disease or damage, the theory suggests ways to manipulate muscle dynamics by adding the necessary compensatory forces using an assistive neuroprosthetic device to restore motor performance and, more important, fast and agile movements. Just how one should compensate can be informed by our SCS model and the theory developed here.

Localized semi-nonnegative matrix factorization (LocaNMF) of widefield calcium imaging data

Widefield calcium imaging enables recording of large-scale neural activity across the mouse dorsal cortex. In order to examine the relationship of these neural signals to the resulting behavior, it is critical to demix the recordings into meaningful spatial and temporal components that can be mapped onto well-defined brain regions. However, no current tools satisfactorily extract the activity of the different brain regions in individual mice in a data-driven manner, while taking into account mouse-specific and preparation-specific differences. Here, we introduce Localized semi-Nonnegative Matrix Factorization (LocaNMF), a method that efficiently decomposes widefield video data and allows us to directly compare activity across multiple mice by outputting mouse-specific localized functional regions that are significantly more interpretable than more traditional decomposition techniques. Moreover, it provides a natural subspace to directly compare correlation maps and neural dynamics across different behaviors, mice, and experimental conditions, and enables identification of task- and movement-related brain regions.

Reconstructing Neural Activity and Kinematics Using a Systems-Level Model of Sensorimotor Control

There are two popular and largely independent approaches to study the sensorimotor control system (SCS). One is to construct systems-level models of the SCS that characterize dynamics of motor regions in the brain, alpha motor neurons, and the musculoskeletal system to reconstruct motor behavior. These models view the brain as a feedforward and feedback controller that actuates the musculoskeletal system, and have been useful in understanding how the SCS generates movements. Another approach is to measure neural activity and movements simultaneously in primate and human subjects,and the nanalyze the data tounder standhow the brain encodes and controls movement. In this paper, we combine these two approaches by fitting parameters of a systems-level model of the SCS to neural activity and behavior measured from a nonhuman primate executing four types of reach-tograsp tasks. We applied a nonlinear least squares estimation to fit parameters of the model components that characterize cerebrocerebellar processing of movement error and muscles that are actuated by alpha motor neurons receiving commands from primary motor cortex (M1). Our fitted SCS model accurately reconstructs firing rate activity of six populations of M1 neurons and associated reaching trajectories. This study paves the way for the validation of systems-level models of the SCS using experimental data.

Wave-number selection in pattern-forming systems

Wave-number selection in pattern-forming systems remains a long-standing puzzle in physics. Previous studies have shown that external noise is a possible mechanism for wave-number selection. We conduct an extensive numerical study of the noisy stabilized Kuramoto-Sivashinsky equation. We use a fast spectral method of integration, which enables us to investigate long-time behavior for large system sizes that could not be investigated by earlier work. We find that a state with a unique wave number has the highest probability of occurring at very long times. We also find that this state is independent of the strength of the noise and initial conditions, thus making a convincing case for the role of noise as a mechanism of state selection.

Neuroinflammation is a putative target for the prevention and treatment of perioperative neurocognitive disorders

INTRODUCTION

The demographics of aging of the surgical population has increased the risk for perioperative neurocognitive disorders in which trauma-induced neuroinflammation plays a pivotal role.

SOURCES OF DATA

After determining the scope of the review, the authors used PubMed with select phrases encompassing the words in the scope. Both preclinical and clinical reports were considered.

AREAS OF AGREEMENT

Neuroinflammation is a sine qua non for development of perioperative neurocognitive disorders.

AREAS OF CONTROVERSY

What is the best method for ameliorating trauma-induced neuroinflammation while preserving inflammation-based wound healing.

GROWING POINTS

This review considers how to prepare for and manage the vulnerable elderly surgical patient through the entire spectrum, from preoperative assessment to postoperative period.

AREAS TIMELY FOR DEVELOPING RESEARCH

What are the most effective and safest interventions for preventing and/or reversing Perioperative Neurocognitive Disorders.

CXCR1/2 Chemokine Network Regulates Melanoma Resistance to Chemotherapies Mediated by NF-κB

BACKGROUND

Cancer-related inflammation is recognized as a driver for tumor progression and chemokines are important players in both inflammation and the progression of many cancer types. CXC chemokines, especially CXCL8, have been implicated in melanoma growth and metastasis, while less is known for their roles in drug resistance.

METHODS

We generated drug-resistant cells by continuous exposure to chemotherapeutic drugs and analyzed the mechanism(s) of therapy resistance in malignant melanoma.

RESULTS

We report chemotherapies induced upregulation of a variety of chemokines in the CXCR1/CXCR2 network by an NF-κB-dependent mechanism. Notably, analysis of the drug-resistant melanoma cell line selected after prolonged exposure to chemotherapeutic drug dacarbazine revealed higher levels of CXCL8 and CXCR2 compared with parent cells as a signature of drug resistance. CXCR2 neutralization markedly improved sensitivity to dacarbazine in melanoma cells.

CONCLUSION

These data provide insights into what drives melanoma cells to survive after chemotherapy treatment, thus pointing to strategies for developing combined drug therapies for combating the problem of chemotherapy resistance in melanoma.

Ophthalmological manifestation in patients of tuberculous meningitis

BACKGROUND

Vision impairment, blindness in particular is a devastating complication in patients with tuberculous meningitis. However, information regarding ophthalmological manifestation and its impact on vision is sparse in the literature. This study evaluated the spectrum of ophthalmological manifestations in tuberculous meningitis, including retinal nerve fiber layer thickness assessment by optic coherence tomography and its correlation with visual and clinical outcome.

METHODS

This was a prospective observational study done from October 2015 to March 2017. Consecutive patients of tuberculous meningitis, diagnosed as per consensus case definition were included in the study. The patients were divided into two categories: uncomplicated and complicated tuberculous meningitis. Clinical evaluation, cerebrospinal fluid examination and contrast enhanced MRI of brain was done. Detailed ophthalmological evaluation including optic coherence tomography was done in all patients. All the patients were followed for 6 months. The primary outcome was blindness or low vision after 6 months. The secondary outcome was death or severe disability after 6 months. It was defined as modified Barthel index (MBI) ≤ 12 at 6 months (including disability plus death). Appropriate statistical analysis was done.

RESULTS

Out of 101 patients of tuberculous meningitis, 47 patients of TBM belonged to uncomplicated category, while 54 patients were of complicated group. The visual impairment was present in 24 out of 101 (23.76%) patients out of which 20 (19.8%) patients had low vision while 4 (3.96%) had blindness. The visual impairment was more evident in complicated group, low vision 0.03 (1.2-31.5). The most common abnormality on fundus examination was papilledema (22.8%). The complicated group had more incidence <0.0001 (19.6-48). Optic atrophy was found in three patients while choroid tubercles were found in eight patients (all complicated TBM group). RNFL thinning was noted in 10 patients in both the eyes. On univariate analysis, presence of diplopia at baseline, impairment of color vision at baseline, visual impairment at baseline, cranial nerve VIth involvement, optic atrophy and papilledema at baseline, RNFL thinning, abnormal VEP and baseline MBI were associated with poor visual outcome. On multivariate analysis, none of the factors were found to be independently associated with poor visual outcome. On univariate analysis, many factors including baseline MRC staging, altered sensorium, seizure, hemiparesis, basal exudates, infarcts, optochiasmaticarachnoiditis, visual impairment at baseline were found to be associated with poor clinical outcome at 6 months. On multivariate analysis, presence of seizure (P = 0.047, odds ratio = 78.59, 95% confidence interval (1.07-578.72)) was the only factor found to be independently associated with poor outcome.

CONCLUSION

Wide spectrum of ophthalmological manifestation was observed in patients of tuberculous meningitis. The visual impairment was more evident in complicated tuberculous meningitis. Ophthalmological findings like optic atrophy, papilledema and RNFL thinning were associated with poor visual outcome on univariate but not multivariate analysis. Visual impairment at baseline, among other factors was associated with poor clinical outcome on univariate analysis, whereas seizure was the only factor independently associated with poor outcome on multivariate analysis.