British Gynaecological Cancer Society and British Menopause Society guidelines: Management of menopausal symptoms following treatment of gynaecological cancer.

These guidelines have been developed jointly by the British Gynaecological Cancer Society and British Menopause Society to provide information for all healthcare professionals managing women treated for gynaecological cancer. Menopausal symptoms can have a significant impact on quality of life for women. Cancer therapies, including surgery, pelvic radiotherapy, chemotherapy and endocrine therapy, can all affect ovarian function. The benefits and risks of using hormone replacement therapy are considered by cancer type with guidance on the type of HRT and optimal time of commencement after cancer treatment. Vaginal estrogens can be very effective for improving urogenital symptoms and are safe for the majority of women, including those for whom systemic HRT is contraindicated with rare exceptions. Alternative options to HRT are reviewed including pharmacological and non-pharmacological approaches.

Targeting ZNF638 activates antiviral immune responses and potentiates immune checkpoint inhibition in glioblastoma.

Viral mimicry refers to the activation of innate anti-viral immune responses due to the induction of endogenous retroelement (RE) expression. Viral mimicry has been previously described to augment anti-tumor immune responses and sensitize solid tumors to immunotherapy including colorectal cancer, melanoma, and clear renal cell carcinoma. Here, we found that targeting a novel, master epigenetic regulator, Zinc Finger Protein 638 (ZNF638), induces viral mimicry in glioblastoma (GBM) preclinical models and potentiates immune checkpoint inhibition (ICI). ZNF638 recruits the HUSH complex, which precipitates repressive H3K9me3 marks on endogenous REs. In GBM, ZNF638 is associated with marked locoregional immunosuppressive transcriptional signatures, reduced endogenous RE expression and poor immune cell infiltration (CD8 + T-cells, dendritic cells). ZNF638 knockdown decreased H3K9-trimethylation, increased cytosolic dsRNA and activated intracellular dsRNA-signaling cascades (RIG-I, MDA5 and IRF3). Furthermore, ZNF638 knockdown upregulated antiviral immune programs and significantly increased PD-L1 immune checkpoint expression in patient-derived GBM neurospheres and diverse murine models. Importantly, targeting ZNF638 sensitized mice to ICI in syngeneic murine orthotopic models through innate interferon signaling. This response was recapitulated in recurrent GBM (rGBM) samples with radiographic responses to checkpoint inhibition with widely increased expression of dsRNA, PD-L1 and perivascular CD8 cell infiltration, suggesting dsRNA-signaling may mediate response to immunotherapy. Finally, we showed that low ZNF638 expression was a biomarker of clinical response to ICI and improved survival in rGBM patients and melanoma patients. Our findings suggest that ZNF638 could serve as a target to potentiate immunotherapy in gliomas.

Cycle-frequency content EEG analysis improves the assessment of respiratory-related cortical activity.

Objective. Time-frequency (T-F) analysis of electroencephalographic (EEG) is a common technique to characterise spectral changes in neural activity. This study explores the limitations of utilizing conventional spectral techniques in examining cyclic event-related cortical activities due to challenges, including high inter-trial variability.Approach. Introducing the cycle-frequency (C-F) analysis, we aim to enhance the evaluation of cycle-locked respiratory events. For synthetic EEG that mimicked cycle-locked pre-motor activity, C-F had more accurate frequency and time localization compared to conventional T-F analysis, even for a significantly reduced number of trials and a variability of breathing rhythm.Main results. Preliminary validations using real EEG data during both unloaded breathing and loaded breathing (that evokes pre-motor activity) suggest potential benefits of using the C-F method, particularly in normalizing time units to cyclic activity phases and refining baseline placement and duration.Significance. The proposed approach could provide new insights for the study of rhythmic neural activities, complementing T-F analysis.

Antiretroviral Drug Repositioning for Glioblastoma.

Outcomes for glioblastoma (GBM) remain poor despite standard-of-care treatments including surgical resection, radiation, and chemotherapy. Intratumoral heterogeneity contributes to treatment resistance and poor prognosis, thus demanding novel therapeutic approaches. Drug repositioning studies on antiretroviral therapy (ART) have shown promising potent antineoplastic effects in multiple cancers; however, its efficacy in GBM remains unclear. To better understand the pleiotropic anticancer effects of ART on GBM, we conducted a comprehensive drug repurposing analysis of ART in GBM to highlight its utility in translational neuro-oncology. To uncover the anticancer role of ART in GBM, we conducted a comprehensive bioinformatic and in vitro screen of antiretrovirals against glioblastoma. Using the DepMap repository and reversal of gene expression score, we conducted an unbiased screen of 16 antiretrovirals in 40 glioma cell lines to identify promising candidates for GBM drug repositioning. We utilized patient-derived neurospheres and glioma cell lines to assess neurosphere viability, proliferation, and stemness. Our in silico screen revealed that several ART drugs including reverse transcriptase inhibitors (RTIs) and protease inhibitors (PIs) demonstrated marked anti-glioma activity with the capability of reversing the GBM disease signature. RTIs effectively decreased cell viability, GBM stem cell markers, and proliferation. Our study provides mechanistic and functional insight into the utility of ART repurposing for malignant gliomas, which supports the current literature. Given their safety profile, preclinical efficacy, and neuropenetrance, ARTs may be a promising adjuvant treatment for GBM.

Graded onset of parasternal intercostal inspiratory activity detected with surface electromyography in healthy young females and males.

Intramuscular recordings of single motor unit activity from parasternal intercostal muscles show a rostrocaudal gradient in timing and amplitude of inspiratory activity. This study determined the feasibility of surface electromyographic activity (EMG) to measure graded parasternal intercostal activity in young females and males during quiet breathing and breathing with inspiratory resistive loads. Surface EMGs were recorded from the 1st-to-5th parasternal intercostal muscles during 10 min of breathing. EMGs were processed to remove 50 Hz and electrocardiogram artifacts and integrated. Amplitude and onset time of inspiratory activity were measured from waveform averages triggered at the onset of inspiratory flow. Onset times were measured independently by two assessors, blinded to interspace and EMG scale, with excellent agreement (ICC3,k = 0.86). The onset of inspiratory activity in the 1st-to-3rd interspaces was at or within ∼400 ms of the start of inspiratory airflow, but activity in the caudal (4th and 5th) spaces was delayed by up to ∼1,000 ms (P < 0.001). There was no main effect of sex on onset time (P = 0.07), but an interaction with interspace (P < 0.001) revealed that inspiratory activity in the caudal interspaces was delayed by 15% of inspiratory time in female participants compared with 30% of inspiratory time in male participants. Inspiratory loads did not affect EMG onset time (P = 0.31). Thus, surface EMG is feasible to assess the onset time of inspiratory activity as a marker of inspiratory neural drive and pattern of activation across spaces, in both females and males.NEW & NOTEWORTHY We demonstrated that surface EMG is a valid method to measure graded inspiratory EMG in the parasternal intercostal muscles in healthy young male and female participants during quiet breathing and loaded breathing. Across the 1st-to-5th interspaces, there was more homogenous activation in women and more graded activity in men across parasternal intercostal muscles during breathing. By recording surface EMG from both male and female participants, we have revealed sex differences in inspiratory activity across intercostal muscles.

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup.

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p-FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

Are we getting enough sleep? Frequent irregular sleep found in an analysis of over 11 million nights of objective in-home sleep data.

OBJECTIVES: Evidence-based guidelines recommend that adults should sleep 7-9 h/night for optimal health and function. This study used noninvasive, multinight, objective sleep monitoring to determine average sleep duration and sleep duration variability in a large global community sample, and how often participants met the recommended sleep duration range. METHODS: Data were analyzed from registered users of the Withings under-mattress Sleep Analyzer (predominantly located in Europe and North America) who had ≥28 nights of sleep recordings, averaging ≥4 per week. Sleep durations (the average and standard deviation) were assessed across a ∼9-month period. Associations between age groups, sex, and sleep duration were assessed using linear and logistic regressions, and proportions of participants within (7-9 hours) or outside (<7 hours or >9 hours) the recommended sleep duration range were calculated. RESULTS: The sample consisted of 67,254 adults (52,523 males, 14,731 females; aged mean ± SD 50 ± 12 years). About 30% of adults demonstrated an average sleep duration outside the recommended 7-9 h/night. Even in participants with an average sleep duration within 7-9 hours, about 40% of nights were outside this range. Only 15% of participants slept between 7 and 9 hours for at least 5 nights per week. Female participants had significantly longer sleep durations than male participants, and middle-aged participants had shorter sleep durations than younger or older participants. CONCLUSIONS: These findings indicate that a considerable proportion of adults are not regularly sleeping the recommended 7-9 h/night. Even among those who do, irregular sleep is prevalent. These novel data raise several important questions regarding sleep requirements and the need for improved sleep health policy and advocacy.

Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods.

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Thinking versus feeling: How interoception and cognition influence emotion recognition in behavioural-variant frontotemporal dementia, Alzheimer's disease, and Parkinson's disease.

Disease-specific mechanisms underlying emotion recognition difficulties in behavioural-variant frontotemporal dementia (bvFTD), Alzheimer's disease (AD), and Parkinson's disease (PD) are unknown. Interoceptive accuracy, accurately detecting internal cues (e.g., one's heart beating), and cognitive abilities are candidate mechanisms underlying emotion recognition. One hundred and sixty-eight participants (52 bvFTD; 41 AD; 24 PD; 51 controls) were recruited. Emotion recognition was measured via the Facial Affect Selection Task or the Mini-Social and Emotional Assessment Emotion Recognition Task. Interoception was assessed with a heartbeat detection task. Participants pressed a button each time they: 1) felt their heartbeat (Interoception); or 2) heard a recorded heartbeat (Exteroception-control). Cognition was measured via the Addenbrooke's Cognitive Examination-III or the Montreal Cognitive Assessment. Voxel-based morphometry analyses identified neural correlates associated with emotion recognition and interoceptive accuracy. All patient groups showed worse emotion recognition and cognition than controls (all P's ≤ .008). Only the bvFTD showed worse interoceptive accuracy than controls (P < .001). Regression analyses revealed that in bvFTD worse interoceptive accuracy predicted worse emotion recognition (P = .008). Whereas worse cognition predicted worse emotion recognition overall (P < .001). Neuroimaging analyses revealed that the insula, orbitofrontal cortex, and amygdala were involved in emotion recognition and interoceptive accuracy in bvFTD. Here, we provide evidence for disease-specific mechanisms for emotion recognition difficulties. In bvFTD, emotion recognition impairment is driven by inaccurate perception of the internal milieu. Whereas, in AD and PD, cognitive impairment likely underlies emotion recognition deficits. The current study furthers our theoretical understanding of emotion and highlights the need for targeted interventions.

Neurocognitive and psychiatric symptoms following infection with COVID-19: Evidence from laboratory and population studies.

Objective: The objective of the current investigation was to examine associations between symptomatic COVID-19 history, neurocognitive function, and psychiatric symptoms using cognitive task performance, functional brain imaging, and a prospective population survey. Methods: Study 1 was a laboratory study conducted between 3 May 2022 and 16 Nov 2022 involving 120 fully vaccinated community dwelling adults between 18 and 84 years of age (Mage = 31.96 (SD = 20.71), 63.3% female). In this cross-sectional study we examined the association between symptomatic COVID-19 infection history and performance on three computer tasks assessing cognitive function (Flanker interference, delay discounting and simple reaction time) and measured oxygen saturation within the prefrontal cortex using functional near infrared spectroscopy (fNIRS). Study 2 was a 2-wave population survey undertaken between 28 September 2021 and 21 March 2022, examining the prospective relationship between symptomatic COVID-19 and self-reported symptoms of cognitive dysfunction, depressive symptoms, anxiety symptoms, and agitation at 6-month follow up. The sample (N = 2,002, M age = 37.0, SD = 10.4; 60.8% female) was collected using a quota process to ensure equal numbers of vaccinated and unvaccinated individuals. Structural equation modelling with latent variables was performed on the population-level data, evaluating the fit of the proposed mediational model of symptomatic COVID-19 to psychiatric symptoms through cognitive dysfunction. Results: Findings from Study 1 revealed significant effects of symptomatic COVID-19 history on Flanker interference and delay discounting. Effects on flanker performance were significantly stronger among older adult women (effect: 9.603, SE = 4.452, t = 2.157, p = .033), and were accompanied by task-related changes cerebral oxygenation at the right superior frontal gyrus (F (1, 143.1) = 4.729, p = .031). Additionally, those with a symptomatic COVID-19 infection history showed evidence of amplified delay discounting (coefficient = 0.4554, SE = 0.2208, t = 2.0629, p = .041). In Study 2, baseline symptomatic COVID-19 history was associated with self-reported cognitive dysfunction and a latent variable reflecting psychiatric symptoms of anxiety, depression and agitation at follow-up. Mediational analyses revealed evidence of cognitive mediation of clinically significant psychiatric outcomes: depression (indirect effect = 0.077, SE = 0.026, p = .003) and generalized anxiety (indirect effect = 0.060, SE = 0.021, p = .004). Conclusions: Converging findings from laboratory and population survey data support the conclusion that symptomatic COVID-19 infection is associated with task-related, functional imaging and self-reported indices of cognitive dysfunction as well as psychiatric symptoms. In some cases, these findings appear to be more amplified among women than men, and among older women than younger.

Questions arising from the application of the ICD-11 diagnoses of complex post traumatic stress disorder and personality disorder.

There is an overlap between the International Classification of Diseases for Mortality and Morbidity Statistics- 11th Revision (ICD-11) diagnoses of complex post-traumatic stress disorder (CPTSD) and personality disorder. When the latter is comorbid with post-traumatic stress disorder (PTSD), this may allow for a false positive CPTSD diagnosis. This fact has both clinical implications and throws into relief theoretical questions about the ontology of trauma and personality disorder-related pathology. These questions are presented as a call for further research.

The ICD 11 introduces a new CPTSD diagnosis, and a new conceptualisation of personality disorder.Despite the advances of the ICD 11, the arrangement of these constructs allows for issues which may pose difficulties for clinicians working in this area.There remain a variety of epistemological and ontological questions concerning trauma and the type of difficulties captured by the diagnosis of personality disorder. These will require future research to clarify.

Social cognitive predictors of vaccination status, uptake and mitigation behaviors in the Canadian COVID-19 Experiences survey.

Emerging infectious diseases like COVID-19 will remain a concern for the foreseeable future, and determinants of vaccination and other mitigation behaviors are therefore critical to understand. Using data from the first two waves of the Canadian COVID-19 Experiences Survey (CCES; N = 1,958; 66.56 % female), we examined social cognitive predictors of vaccination status, transition to acceptance and mitigation behaviors in a population-representative sample. Findings indicated that all social cognitive variables were strong predictors of mitigation behavior performance at each wave, particularly among unvaccinated individuals. Among those who were vaccine hesitant at baseline, most social cognitive variables predicted transition to fully vaccinated status at follow-up. After controlling for demographic factors and geographic region, greater odds of transitioning from unvaccinated at CCES Wave 1 to fully vaccinated at CCES Wave 2 was predicted most strongly by a perception that one's valued peers were taking up the vaccine (e.g., dynamic norms (OR = 2.13 (CI: 1.54,2.93)), perceived effectiveness of the vaccine (OR = 3.71 (CI: 2.43,5.66)), favorable attitudes toward the vaccine (OR = 2.80 (CI: 1.99,3.95)), greater perceived severity of COVID-19 (OR = 2.02 (CI: 1.42,2.86)), and stronger behavioral intention to become vaccinated (OR = 2.99 (CI: 2.16,4.14)). As a group, social cognitive variables improved prediction of COVID-19 mitigation behaviors (masking, distancing, hand hygiene) by a factor of 5 compared to demographic factors, and improved prediction of vaccination status by a factor of nearly 20. Social cognitive processes appear to be important leverage points for health communications to encourage COVID-19 vaccination and other mitigation behaviors, particularly among initially hesitant members of the general population.

Cognitive predictors of COVID-19 mitigation behaviors in vaccinated and unvaccinated general population members.

BACKGROUND: Given the long-term threat posed by COVID-19, predictors of mitigation behaviors are critical to identify. Prior studies have found that cognitive factors are associated with some COVID-19 mitigation behaviors, but few studies employ representative samples and no prior studies have examined cognitive predictors of vaccination status. The purpose of the present study was to examine associations between cognitive variables (executive function, delay discounting, and future orientation) and COVID-19 mitigation behaviors (mask wearing, social distancing, hand hygiene and vaccination) in a population representative sample. METHODS: A population representative sample of 2,002 adults completed validated measures of delay discounting, future orientation, and executive function. Participants also reported frequency of mitigation behaviors, vaccination status, and demographics. RESULTS: Future orientation was associated with more mask wearing (ß = 0.160, 95 % CI [0.090, 0.220], p < 0.001), social distancing (ß = 0.150, 95 % CI [0.070, 0.240], p < 0.001), hand hygiene behaviors (ß = 0.090, 95 % CI [0.000, 0.190], p = 0.054), and a higher likelihood of being fully vaccinated (OR = 0.80, 95 % CI [0.670, 0.970], p = 0.020). Lower delay discounting predicted more consistent mask wearing (ß = -0.060, 95 % CI[-0.120, -0.010], p = 0.032) and being fully vaccinated (OR = 1.28, 95 % CI [1.13, 1.44], p < 0.001), while more symptoms of executive dysfunction predicted less mask wearing (ß = -0.240, 95 % CI [-0.320, -0.150] p < 0.001) and hand hygiene (ß = -0.220, 95 % CI [-0.320, -0.130], p < 0.001), but not vaccination status (OR = 0.96, 95 % CI [0.80, 1.16], p = 0.690) or social distancing behaviors (ß = -0.080, 95 % CI [-0.180, 0.020], p = 0.097). Overall, social distancing was the least well-predicted outcome from cognitive factors, while mask wearing was most well-predicted. Vaccination status was not a significant moderator of these effects of cognitive predictors on mitigation behaviors. CONCLUSIONS: Cognitive variables predict significant variability in mitigation behaviors. regardless of vaccination status. In particular, thinking about the future and discounting it less may encourage more consistent implementation of mitigating behaviors.

Respiratory-related evoked potentials in chronic obstructive pulmonary disease and healthy aging.

Altered neural processing and increased respiratory sensations have been reported in chronic obstructive pulmonary disease (COPD) as larger respiratory-related evoked potentials (RREPs), but the effect of healthy-aging has not been considered adequately. We tested RREPs evoked by brief airway occlusions in 10 participants with moderate-to-severe COPD, 11 age-matched controls (AMC) and 14 young controls (YC), with similar airway occlusion pressure stimuli across groups. Mean age was 76 years for COPD and AMC groups, and 30 years for the YC group. Occlusion intensity and unpleasantness was rated using the modified Borg scale, and anxiety rated using the Hospital Anxiety and Depression Scale. There was no difference in RREP peak amplitudes across groups, except for the N1 peak, which was significantly greater in the YC group than the COPD and AMC groups (p = 0.011). The latencies of P1, P2 and P3 occurred later in COPD versus YC (p < 0.05). P3 latency occurred later in AMC than YC (p = 0.024). COPD and AMC groups had similar Borg ratings for occlusion intensity (3.0 (0.5, 3.5) [Median (IQR)] and 3.0 (3.0, 3.0), respectively; p = 0.476) and occlusion unpleasantness (1.3 (0.1, 3.4) and 1.0 (0.75, 2.0), respectively; p = 0.702). The COPD group had a higher anxiety score than AMC group (p = 0.013). A higher N1 amplitude suggests the YC group had higher cognitive processing of respiratory inputs than the COPD and AMC groups. Both COPD and AMC groups showed delayed neural responses to the airway occlusion, which may indicate impaired processing of respiratory sensory inputs in COPD and healthy aging.

Inspiratory muscle reflex control after incomplete cervical spinal cord injury.

In healthy individuals, loading inspiratory muscles by brief inspiratory occlusion produces a short-latency inhibitory reflex (IR) in the electromyographic (EMG) activity of scalene and diaphragm muscles. This IR may play a protective role to prevent aspiration and airway collapse during sleep. In people with motor and sensory complete cervical spinal cord injury (cSCI), who were able to breathe independently, this IR was predominantly absent. Here, we investigated the reflex response to brief airway occlusion in 16 participants with sensory incomplete cSCI [American spinal injury association impairment scale (AIS) score B or C]. Surface EMG was recorded from scalene muscles and the lateral chest wall (overlying diaphragm). The airway occlusion evoked a small change in mouth pressure resembling a physiological occlusion. The short-latency IR was present in 10 (63%) sensory incomplete cSCI participants; significantly higher than the IR incidence observed in complete cSCI participants in our previous study (14%; P = 0.003). When present, mean IR latency across all muscles was 58 ms (range 29-79 ms), and mean rectified EMG amplitude decreased to 37% preocclusion levels. Participants without an IR had untreated severe obstructive sleep apnea (OSA), in contrast to those with an IR, who had either had no, mild, or treated OSA (P = 0.002). Insufficient power did not allow statistical comparison between IR presence or absence and participant clinical characteristics. In conclusion, spared sensory connections or intersegmental connections may be necessary to generate the IR. Future studies to establish whether IR presence is related to respiratory morbidity in the tetraplegic population are required.NEW & NOTEWORTHY Individuals with incomplete cSCI were tested for the presence of a short latency reflex inhibition of inspiratory muscles, by brief airway occlusion. The reflex was 4.5 times more prevalent in this group compared with those with complete cSCI and is similar to the incidence in able-bodied people. Participants without this reflex all had untreated severe OSA, in contrast to those with an IR, who either had no, mild, or treated OSA. This work reveals novel differences in the reflex control of inspiratory muscles across the cSCI population.

Systematic Comparison of Pancreatic Ductal Adenocarcinoma Models Identifies a Conserved Highly Plastic Basal Cell State.

Intratumoral heterogeneity and cellular plasticity have emerged as hallmarks of cancer, including pancreatic ductal adenocarcinoma (PDAC). As PDAC portends a dire prognosis, a better understanding of the mechanisms underpinning cellular diversity in PDAC is crucial. Here, we investigated the cellular heterogeneity of PDAC cancer cells across a range of in vitro and in vivo growth conditions using single-cell genomics. Heterogeneity contracted significantly in two-dimensional and three-dimensional cell culture models but was restored upon orthotopic transplantation. Orthotopic transplants reproducibly acquired cell states identified in autochthonous PDAC tumors, including a basal state exhibiting coexpression and coaccessibility of epithelial and mesenchymal genes. Lineage tracing combined with single-cell transcriptomics revealed that basal cells display high plasticity in situ. This work defines the impact of cellular growth conditions on phenotypic diversity and uncovers a highly plastic cell state with the capacity to facilitate state transitions and promote intratumoral heterogeneity in PDAC. SIGNIFICANCE: This work provides important insights into how different model systems of pancreatic ductal adenocarcinoma mold the phenotypic space of cancer cells, highlighting the power of in vivo models.

A comparison of methods to harmonize cortical thickness measurements across scanners and sites.

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants' demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.

Combined head accelerometry and EEG improves the detection of respiratory-related cortical activity during inspiratory loading in healthy participants.

Mechanical ventilation is a highly utilized life-saving tool, particularly in the current era. The use of EEG in a brain-ventilator interface (BVI) to detect respiratory discomfort (due to sub-optimal ventilator settings) would improve treatment in mechanically ventilated patients. This concept has been realized via development of an EEG covariance-based classifier that detects respiratory-related cortical activity associated with respiratory discomfort. The aim of this study was to determine if head movement, detected by an accelerometer, can detect and/or improve the detection of respiratory-related cortical activity compared to EEG alone. In 25 healthy participants, EEG and acceleration of the head were recorded during loaded and quiet breathing in the seated and lying postures. Detection of respiratory-related cortical activity using an EEG covariance-based classifier was improved by inclusion of data from an Accelerometer-based classifier, i.e. classifier 'Fusion'. In addition, 'smoothed' data over 50s, rather than one 5 s window of EEG/Accelerometer signals, improved detection. Waveform averages of EEG and head acceleration showed the incidence of pre-inspiratory potentials did not differ between loaded and quiet breathing, but head movement was greater in loaded breathing. This study confirms that compared to event-related analysis with >5 min of signal acquisition, an EEG-based classifier is a clinically valuable tool with rapid processing, detection times, and accuracy. Data smoothing would introduce a small delay (<1 min) but improves detection results. As head acceleration improved detection compared to EEG alone, the number of EEG signals required to detect respiratory discomfort with future BVIs could be reduced if head acceleration is included.