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2- or 4-Pyridyl benzylic amines represent a privileged motif in drug discovery. However, the formation of heterocyclic benzylic amines with fully substituted α-carbons can require the execution of lengthy synthetic routes, which limit their application. Addition of various nucleophilic agents to Ellman's imines has been well established; however, there is no precedented literature reported for pyridyl-type nucleophiles, which are very important for medicinal chemistry. In this letter, we disclose the development of a one-step synthesis of heterocyclic benzylic amines with fully substituted α-carbons from heteroaryl halides and sulfinyl imines. Starting from 2,4-dibromopyridine, regioselective synthesis of 2- or 4-pyridyl benzylic amines could be achieved by choosing toluene or MTBE as a solvent.
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BACKGROUND: Affective states influence the sympathetic nervous system, inducing variations in electrodermal activity (EDA), however, EDA association with bipolar disorder (BD) remains uncertain in real-world settings due to confounders like physical activity and temperature. We analysed EDA separately during sleep and wakefulness due to varying confounders and potential differences in mood state discrimination capacities. METHODS: We monitored EDA from 102 participants with BD including 35 manic, 29 depressive, 38 euthymic patients, and 38 healthy controls (HC), for 48 h. Fifteen EDA features were inferred by mixed-effect models for repeated measures considering sleep state, group and covariates. RESULTS: Thirteen EDA feature models were significantly influenced by sleep state, notably including phasic peaks (p < 0.001). During wakefulness, phasic peaks showed different values for mania (M [SD] = 6.49 [5.74, 7.23]), euthymia (5.89 [4.83, 6.94]), HC (3.04 [1.65, 4.42]), and depression (3.00 [2.07, 3.92]). Four phasic features during wakefulness better discriminated between HC and mania or euthymia, and between depression and euthymia or mania, compared to sleep. Mixed symptoms, average skin temperature, and anticholinergic medication affected the models, while sex and age did not. CONCLUSION: EDA measured from awake recordings better distinguished between BD states than sleep recordings, when controlled by confounders.
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Deep brain stimulation targeting the subcallosal cingulate area, a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While subcallosal cingulate deep brain stimulation drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0â T functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of 12 patients with fully implanted deep brain stimulation devices targeting the subcallosal cingulate area. Four additional subcallosal cingulate deep brain stimulation patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n = 78 acquisitions overall) during (i) inactive deep brain stimulation; (ii) clinically optimal active deep brain stimulation; and (iii) suboptimal active deep brain stimulation. All scans were acquired within a single MRI session, each separated by a 5-min washout period. Analysis of the amplitude of low-frequency fluctuations in each sequence indicated that clinically optimal deep brain stimulation reduced spontaneous brain activity in several areas, including the bilateral dorsal anterior cingulate cortex, the bilateral posterior cingulate cortex, the bilateral precuneus and the left inferior parietal lobule (PBonferroni < 0.0001). Stimulation-induced dorsal anterior cingulate cortex signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings and was related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dorsal anterior cingulate cortex, posterior cingulate cortex and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated amplitude of low-frequency fluctuations changes in these three areas (along with preoperative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally, all three brain areas exhibited significant changes in functional connectivity between active and inactive deep brain stimulation states (PBonferroni < 0.01). These results provide insight into the network-level mechanisms of subcallosal cingulate deep brain stimulation and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.
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Estimulação Encefálica Profunda , Substância Branca , Encéfalo/diagnóstico por imagem , Estimulação Encefálica Profunda/métodos , Giro do Cíngulo , Humanos , Imageamento por Ressonância MagnéticaRESUMO
BACKGROUND: Subcutaneous (SC) trastuzumab is similar to intravenous trastuzumab in terms of pharmacokinetics, efficacy and tolerability. The use of dual anti-HER2 agents trastuzumab and pertuzumab has become the new standard for node-positive HER2-positive breast cancers at adjuvant setting, but the safety and tolerability of combining SC trastuzumab and intravenous pertuzumab is not well studied. METHODS: This was a prospective single-arm pilot study with locally advanced HER2-positive breast cancer who received adjuvant SC trastuzumab and intravenous pertuzumab after standard anti-HER2 treatment with chemotherapy. Primary outcomes included adverse events (AEs), severe AEs and cardiac AEs. Secondary outcome was invasive disease-free survival (iDFS). RESULTS: With a median follow-up of 21.7 months, 20 patients were enrolled. One patient (5%) developed asymptomatic drop in left ventricular ejection fraction from 69% to 53%. Two patients (10%) developed grade 1 injection site reaction related to SC trastuzumab. There were no grade 2 or above AEs. All AEs were transient. No new AEs were observed. The 1-year iDFS was 90% (95% CI 0.656 to 0.974). CONCLUSIONS: Combination of SC trastuzumab and intravenous pertuzumab for HER2-positive breast cancer is a safe and well-tolerated option in adjuvant setting.
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Neoplasias da Mama , Humanos , Feminino , Trastuzumab/efeitos adversos , Neoplasias da Mama/tratamento farmacológico , Projetos Piloto , Volume Sistólico , Estudos Prospectivos , Receptor ErbB-2/uso terapêutico , Protocolos de Quimioterapia Combinada Antineoplásica/efeitos adversos , Função Ventricular EsquerdaRESUMO
Recent genomic studies have shed light on the biology and inter-tumoral heterogeneity underlying pineal parenchymal tumors, in particular pineoblastomas (PBs) and pineal parenchymal tumors of intermediate differentiation (PPTIDs). Previous reports, however, had modest sample sizes and lacked the power to integrate molecular and clinical findings. The different proposed molecular group structures also highlighted a need to reach consensus on a robust and relevant classification system. We performed a meta-analysis on 221 patients with molecularly characterized PBs and PPTIDs. DNA methylation profiles were analyzed through complementary bioinformatic approaches and molecular subgrouping was harmonized. Demographic, clinical, and genomic features of patients and samples from these pineal tumor groups were annotated. Four clinically and biologically relevant consensus PB groups were defined: PB-miRNA1 (n = 96), PB-miRNA2 (n = 23), PB-MYC/FOXR2 (n = 34), and PB-RB1 (n = 25). A final molecularly distinct group, designated PPTID (n = 43), comprised histological PPTID and PBs. Genomic and transcriptomic profiling allowed the characterization of oncogenic drivers for individual tumor groups, specifically, alterations in the microRNA processing pathway in PB-miRNA1/2, MYC amplification and FOXR2 overexpression in PB-MYC/FOXR2, RB1 alteration in PB-RB1, and KBTBD4 insertion in PPTID. Age at diagnosis, sex predilection, and metastatic status varied significantly among tumor groups. While patients with PB-miRNA2 and PPTID had superior outcome, survival was intermediate for patients with PB-miRNA1, and dismal for those with PB-MYC/FOXR2 or PB-RB1. Reduced-dose CSI was adequate for patients with average-risk, PB-miRNA1/2 disease. We systematically interrogated the clinical and molecular heterogeneity within pineal parenchymal tumors and proposed a consensus nomenclature for disease groups, laying the groundwork for future studies as well as routine use in tumor diagnostic classification and clinical trial stratification.
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Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patologia , Glândula Pineal/patologia , Pinealoma/genética , Pinealoma/patologia , Adolescente , Adulto , Criança , Pré-Escolar , Estudos de Coortes , Metilação de DNA , Feminino , Estudo de Associação Genômica Ampla , Humanos , Lactente , Recém-Nascido , Masculino , Pessoa de Meia-Idade , Transcriptoma , Adulto JovemRESUMO
OBJECTIVE: Thyroid immune-related adverse events (irAEs) have been reported to have prognostic significance among patients with cancer treated with anti-programmed cell death-1 (PD1) and anti-programmed death-ligand 1 monotherapies. We evaluated the clinical course and predictors of thyroid irAEs in relation to outcomes of patients with advanced cancer treated with combination anti-PD1/anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA4). METHODS: We conducted a regional study and identified patients with advanced cancer who received ≥1 cycle of combination anti-PD1/anti-CTLA4 between 2015 and 2019 in Hong Kong. Thyroid function tests (TFTs) were monitored every 3 weeks. Thyroid irAE was defined by ≥2 abnormal TFTs after initiation of combination anti-PD1/anti-CTLA4 in the absence of other causes. RESULTS: One hundred and three patients were included (median age: 59 years; 71.8% men). About 45% had prior anti-PD1 exposure. Upon median follow-up of 6.8 months, 17 patients (16.5%) developed thyroid irAEs, where 6 initially presented with thyrotoxicosis (overt, n = 4; subclinical, n = 2) and 11 with hypothyroidism (overt, n = 2; subclinical, n = 9). Eventually, 10 patients (58.8%) required continuous thyroxine replacement. Systemic steroid was not required in all cases. Prior anti-PD1 exposure (odds ratio, 3.67; 95% CI, 1.19-11.4; P = .024) independently predicted thyroid irAEs. Multivariable Cox regression analysis revealed that occurrence of thyroid irAEs was independently associated with better overall survival (adjusted hazard ratio, 0.34; 95% CI, 0.17-0.71; P = .004). CONCLUSION: Thyroid irAEs are common in routine clinical practice among patients with advanced cancer treated with anti-PD1/anti-CTLA4 combination and might have potential prognostic significance. Regular TFT monitoring is advised for timely treatment of thyroid irAEs to prevent potential morbidities.
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Inibidores de Checkpoint Imunológico , Neoplasias , Doenças da Glândula Tireoide/induzido quimicamente , Antígeno CTLA-4/antagonistas & inibidores , Feminino , Humanos , Inibidores de Checkpoint Imunológico/efeitos adversos , Inibidores de Checkpoint Imunológico/uso terapêutico , Masculino , Pessoa de Meia-Idade , Neoplasias/tratamento farmacológico , Receptor de Morte Celular Programada 1/antagonistas & inibidores , Estudos Retrospectivos , Glândula TireoideRESUMO
Pineoblastomas (PBs) are rare, aggressive pediatric brain tumors of the pineal gland with modest overall survival despite intensive therapy. We sought to define the clinical and molecular spectra of PB to inform new treatment approaches for this orphan cancer. Tumor, blood, and clinical data from 91 patients with PB or supratentorial primitive neuroectodermal tumor (sPNETs/CNS-PNETs), and 2 pineal parenchymal tumors of intermediate differentiation (PPTIDs) were collected from 29 centres in the Rare Brain Tumor Consortium. We used global DNA methylation profiling to define a core group of PB from 72/93 cases, which were delineated into five molecular sub-groups. Copy number, whole exome and targeted sequencing, and miRNA expression analyses were used to evaluate the clinico-pathologic significance of each sub-group. Tumors designated as group 1 and 2 almost exclusively exhibited deleterious homozygous loss-of-function alterations in miRNA biogenesis genes (DICER1, DROSHA, and DGCR8) in 62 and 100% of group 1 and 2 tumors, respectively. Recurrent alterations of the oncogenic MYC-miR-17/92-RB1 pathway were observed in the RB and MYC sub-group, respectively, characterized by RB1 loss with gain of miR-17/92, and recurrent gain or amplification of MYC. PB sub-groups exhibited distinct clinical features: group 1-3 arose in older children (median ages 5.2-14.0 years) and had intermediate to excellent survival (5-year OS of 68.0-100%), while Group RB and MYC PB patients were much younger (median age 1.3-1.4 years) with dismal survival (5-year OS 37.5% and 28.6%, respectively). We identified age < 3 years at diagnosis, metastatic disease, omission of upfront radiation, and chr 16q loss as significant negative prognostic factors across all PBs. Our findings demonstrate that PB exhibits substantial molecular heterogeneity with sub-group-associated clinical phenotypes and survival. In addition to revealing novel biology and therapeutics, molecular sub-grouping of PB can be exploited to reduce treatment intensity for patients with favorable biology tumors.
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Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patologia , Glândula Pineal , Pinealoma/genética , Pinealoma/patologia , Adolescente , Adulto , Fatores Etários , Neoplasias Encefálicas/mortalidade , Criança , Pré-Escolar , Estudos de Coortes , Feminino , Humanos , Lactente , Masculino , MicroRNAs/metabolismo , Mutação/genética , Pinealoma/mortalidade , Sistema de Registros , Taxa de Sobrevida , Adulto JovemRESUMO
BackgroundWith growing numbers of patients receiving deep brain stimulation (DBS), radiologists are encountering these neuromodulation devices at an increasing rate. Current MRI safety guidelines, however, limit MRI access in these patients.PurposeTo describe an MRI (1.5 T and 3 T) experience and safety profile in a large cohort of participants with active DBS systems and characterize the hardware-related artifacts on images from functional MRI.Materials and MethodsIn this prospective study, study participants receiving active DBS underwent 1.5- or 3-T MRI (T1-weighted imaging and gradient-recalled echo [GRE]-echo-planar imaging [EPI]) between June 2017 and October 2018. Short- and long-term adverse events were tracked. The authors quantified DBS hardware-related artifacts on images from GRE-EPI (functional MRI) at the cranial coil wire and electrode contacts. Segmented artifacts were then transformed into standard space to define the brain areas affected by signal loss. Two-sample t tests were used to assess the difference in artifact size between 1.5- and 3-T MRI.ResultsA total of 102 participants (mean age ± standard deviation, 60 years ± 11; 65 men) were evaluated. No MRI-related short- and long-term adverse events or acute changes were observed. DBS artifacts were most prominent near the electrode contacts and over the frontoparietal cortical area where the redundancy of the extension wire is placed subcutaneously. The mean electrode contact artifact diameter was 9.3 mm ± 1.6, and 1.9% ± 0.8 of the brain was obscured by the coil artifact. The coil artifacts were larger at 3 T than at 1.5 T, obscuring 2.1% ± 0.7 and 1.4% ± 0.7 of intracranial volume, respectively (P < .001). The superficial frontoparietal cortex and deep structures neighboring the electrode contacts were most commonly obscured.ConclusionWith a priori local safety testing, patients receiving deep brain stimulation may safely undergo 1.5- and 3-T MRI. Deep brain stimulation hardware-related artifacts only affect a small proportion of the brain.© RSNA, 2019Online supplemental material is available for this article.See also the editorial by Martin in this issue.
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Artefatos , Encéfalo/diagnóstico por imagem , Estimulação Encefálica Profunda/instrumentação , Eletrodos Implantados , Imageamento por Ressonância Magnética/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Imagem Ecoplanar , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos ProspectivosRESUMO
The scope of thermolytic, N-Boc deprotection was studied on 26 compounds from the Pfizer compound library, representing a diverse set of structural moieties. Among these compounds, 12 substrates resulted in clean (≥95% product) deprotection, and an additional three compounds gave ≥90% product. The thermal de-Boc conditions were found to be compatible with a large number of functional groups. A combination of computational modeling, statistical analysis, and kinetic model fitting was used to support an initial, slow, and concerted proton transfer with release of isobutylene, followed by a rapid decarboxylation. A strong correlation was found to exist between the electrophilicity of the N-Boc carbonyl group and the reaction rate.
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PURPOSE OF REVIEW: Malignant embryonal brain tumors (EBTs) of childhood span a wide clinical spectrum but can share remarkably similar morphologic features. This overlap presents significant diagnostic challenges, particularly for tumor entities that are rarely encountered in clinical practice and for which diagnostic criteria were poorly defined. This review will provide an update on the evolving characterization and treatment of rare EBTs. RECENT FINDINGS: Rapid advances in genomic tools have led to the discovery of robust molecular markers, and identification of novel tumor types and subtypes for almost all major categories of pediatric brain tumors. These developments have had significant impact on improving the diagnostic classification of the rare EBTs, particularly for tumors with newly recognized C19MC alterations, central nervous system primitive neuroectodermal tumors (CNS-PNET), and pineoblastoma (PB). These important developments in the clinical and molecular understanding of rare EBTs are paving the way for novel therapeutic strategies and improved clinical management.
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Neoplasias Encefálicas/classificação , Neoplasias Encefálicas/terapia , Neoplasias Embrionárias de Células Germinativas/terapia , Doenças Raras/terapia , Gerenciamento Clínico , Humanos , PrognósticoRESUMO
BACKGROUND: More than half of children with high-risk neuroblastoma (NB) will experience recurrence. Radiologic imaging is used for initial staging and during therapy to assess response. However, the role of surveillance imaging in the detection of relapse has not been well studied. Surveillance potentially results in high cumulative exposure to ionizing radiation, which may be associated with an increased risk of developing second malignancies. PROCEDURE: We reviewed NB cases at our institution between 2000 and 2011. We calculated radiation exposure due to imaging (during diagnosis, treatment, and posttherapy surveillance) using cumulative effective dose (CED) estimates and determined whether cross-sectional imaging identified recurrences. RESULTS: Fifty of 183 patients with NB experienced a recurrence. The median time from diagnosis to relapse was 1.20 years (range: 0.18-6.66 years). Most patients had evidence of metastases and only 4 of 50 patients presented with isolated primary tumor site recurrences. The mean CED prior to relapse was 125.2 mSv (range: 24.5-259.7), 64% of which was from computed tomography (CT) scans. Thirty-seven of 50 patients had clinically evident or measurable disease detected by X-ray (XR), ultrasound (US), or urinary catecholamines (UCats), and the addition of metaiodobenzylguanidine (MIBG) scans identified eight additional recurrences. Thus, cross-sectional imaging (CT/MRI, where MRI is magnetic resonance imaging) was only required to identify 10% (5/50) of cases. CONCLUSION: Relapsed disease was detected in most patients by symptoms/exam, MIBG scan, UCats, and/or XR/US, supporting reduced use of CT imaging in posttherapy surveillance, thereby decreasing cumulative radiation dose. Refinement of surveillance imaging may be further guided by risk stratification, disease sites, and potentially biomolecular markers.
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Recidiva Local de Neoplasia/diagnóstico por imagem , Neuroblastoma/diagnóstico por imagem , Exposição à Radiação , Criança , Pré-Escolar , Humanos , Lactente , Imageamento por Ressonância Magnética , Tomografia Computadorizada por Raios XAssuntos
Neoplasias Encefálicas/patologia , Neoplasias Embrionárias de Células Germinativas/patologia , Glândula Pineal/patologia , Pinealoma/patologia , Adolescente , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/metabolismo , Neoplasias Cerebelares/genética , Neoplasias Cerebelares/metabolismo , Neoplasias Cerebelares/patologia , Feminino , Humanos , Masculino , Meduloblastoma/genética , Meduloblastoma/metabolismo , Meduloblastoma/patologia , Mutação de Sentido Incorreto/genética , Neoplasias Embrionárias de Células Germinativas/genética , Neoplasias Embrionárias de Células Germinativas/metabolismo , Pinealoma/genética , Pinealoma/metabolismo , Proteínas Wnt/metabolismo , beta Catenina/genéticaRESUMO
Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited specialized care availability remains a major bottleneck thus hindering pre-emptive interventions. MDs manifest with changes in mood, sleep, and motor activity, observable in ecological physiological recordings thanks to recent advances in wearable technology. Therefore, near-continuous and passive collection of physiological data from wearables in daily life, analyzable with machine learning (ML), could mitigate this problem, bringing MDs monitoring outside the clinician's office. Previous works predict a single label, either the disease state or a psychometric scale total score. However, clinical practice suggests that the same label may underlie different symptom profiles, requiring specific treatments. Here we bridge this gap by proposing a new task: inferring all items in HDRS and YMRS, the two most widely used standardized scales for assessing MDs symptoms, using physiological data from wearables. To that end, we develop a deep learning pipeline to score the symptoms of a large cohort of MD patients and show that agreement between predictions and assessments by an expert clinician is clinically significant (quadratic Cohen's κ and macro-average F1 score both of 0.609). While doing so, we investigate several solutions to the ML challenges associated with this task, including multi-task learning, class imbalance, ordinal target variables, and subject-invariant representations. Lastly, we illustrate the importance of testing on out-of-distribution samples.
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Afeto , Transtornos do Humor , Humanos , Transtornos do Humor/diagnóstico , Aprendizado de Máquina , SonoRESUMO
BACKGROUND: Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide disease burden. However, collecting and annotating wearable data is resource intensive. Studies of this kind can thus typically afford to recruit only a few dozen patients. This constitutes one of the major obstacles to applying modern supervised machine learning techniques to MD detection. OBJECTIVE: In this paper, we overcame this data bottleneck and advanced the detection of acute MD episodes from wearables' data on the back of recent advances in self-supervised learning (SSL). This approach leverages unlabeled data to learn representations during pretraining, subsequently exploited for a supervised task. METHODS: We collected open access data sets recording with the Empatica E4 wristband spanning different, unrelated to MD monitoring, personal sensing tasks-from emotion recognition in Super Mario players to stress detection in undergraduates-and devised a preprocessing pipeline performing on-/off-body detection, sleep/wake detection, segmentation, and (optionally) feature extraction. With 161 E4-recorded subjects, we introduced E4SelfLearning, the largest-to-date open access collection, and its preprocessing pipeline. We developed a novel E4-tailored transformer (E4mer) architecture, serving as the blueprint for both SSL and fully supervised learning; we assessed whether and under which conditions self-supervised pretraining led to an improvement over fully supervised baselines (ie, the fully supervised E4mer and pre-deep learning algorithms) in detecting acute MD episodes from recording segments taken in 64 (n=32, 50%, acute, n=32, 50%, stable) patients. RESULTS: SSL significantly outperformed fully supervised pipelines using either our novel E4mer or extreme gradient boosting (XGBoost): n=3353 (81.23%) against n=3110 (75.35%; E4mer) and n=2973 (72.02%; XGBoost) correctly classified recording segments from a total of 4128 segments. SSL performance was strongly associated with the specific surrogate task used for pretraining, as well as with unlabeled data availability. CONCLUSIONS: We showed that SSL, a paradigm where a model is pretrained on unlabeled data with no need for human annotations before deployment on the supervised target task of interest, helps overcome the annotation bottleneck; the choice of the pretraining surrogate task and the size of unlabeled data for pretraining are key determinants of SSL success. We introduced E4mer, which can be used for SSL, and shared the E4SelfLearning collection, along with its preprocessing pipeline, which can foster and expedite future research into SSL for personal sensing.
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Transtornos do Humor , Aprendizado de Máquina Supervisionado , Dispositivos Eletrônicos Vestíveis , Humanos , Estudos Prospectivos , Dispositivos Eletrônicos Vestíveis/estatística & dados numéricos , Dispositivos Eletrônicos Vestíveis/normas , Masculino , Feminino , Transtornos do Humor/diagnóstico , Transtornos do Humor/psicologia , Adulto , Exercício Físico/psicologia , Exercício Físico/fisiologia , Universidades/estatística & dados numéricos , Universidades/organização & administraçãoRESUMO
Pineal parenchymal tumors are rare neoplasms for which evidence-based treatment recommendations are lacking. These tumors vary in biology, clinical characteristics, and prognosis, requiring treatment that ranges from surgical resection alone to intensive multimodal antineoplastic therapy. Recently, international collaborative studies have shed light on the genomic landscape of these tumors, leading to refinement in molecular-based disease classification in the 5th edition of the World Health Organization (WHO) classification of tumors of the central nervous system. In this review, we summarize the literature on diagnostic and therapeutic approaches, and suggest pragmatic recommendations for the clinical management of patients presenting with intrinsic pineal region masses including parenchymal tumors (pineocytoma, pineal parenchymal tumor of intermediate differentiation, and pineoblastoma), pineal cyst, and papillary tumors of the pineal region.
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Understanding how biological visual systems process information is challenging because of the nonlinear relationship between visual input and neuronal responses. Artificial neural networks allow computational neuroscientists to create predictive models that connect biological and machine vision. Machine learning has benefited tremendously from benchmarks that compare different model on the same task under standardized conditions. However, there was no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system. To address this gap, we established the SENSORIUM 2023 Benchmark Competition with dynamic input, featuring a new large-scale dataset from the primary visual cortex of ten mice. This dataset includes responses from 78,853 neurons to 2 hours of dynamic stimuli per neuron, together with the behavioral measurements such as running speed, pupil dilation, and eye movements. The competition ranked models in two tracks based on predictive performance for neuronal responses on a held-out test set: one focusing on predicting in-domain natural stimuli and another on out-of-distribution (OOD) stimuli to assess model generalization. As part of the NeurIPS 2023 competition track, we received more than 160 model submissions from 22 teams. Several new architectures for predictive models were proposed, and the winning teams improved the previous state-of-the-art model by 50%. Access to the dataset as well as the benchmarking infrastructure will remain online at www.sensorium-competition.net.
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BACKGROUND: Bipolar disorder is highly prevalent and consists of biphasic recurrent mood episodes of mania and depression, which translate into altered mood, sleep and activity alongside their physiological expressions. AIMS: The IdenTifying dIgital bioMarkers of illnEss activity and treatment response in BipolAr diSordEr with a novel wearable device (TIMEBASE) project aims to identify digital biomarkers of illness activity and treatment response in bipolar disorder. METHOD: We designed a longitudinal observational study including 84 individuals. Group A comprises people with acute episode of mania (n = 12), depression (n = 12 with bipolar disorder and n = 12 with major depressive disorder (MDD)) and bipolar disorder with mixed features (n = 12). Physiological data will be recorded during 48 h with a research-grade wearable (Empatica E4) across four consecutive time points (acute, response, remission and episode recovery). Group B comprises 12 people with euthymic bipolar disorder and 12 with MDD, and group C comprises 12 healthy controls who will be recorded cross-sectionally. Psychopathological symptoms, disease severity, functioning and physical activity will be assessed with standardised psychometric scales. Physiological data will include acceleration, temperature, blood volume pulse, heart rate and electrodermal activity. Machine learning models will be developed to link physiological data to illness activity and treatment response. Generalisation performance will be tested in data from unseen patients. RESULTS: Recruitment is ongoing. CONCLUSIONS: This project should contribute to understanding the pathophysiology of affective disorders. The potential digital biomarkers of illness activity and treatment response in bipolar disorder could be implemented in a real-world clinical setting for clinical monitoring and identification of prodromal symptoms. This would allow early intervention and prevention of affective relapses, as well as personalisation of treatment.
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Pyrido[4,3-d]pyrimidin-4(3H)-one (1) was prepared by reacting 2-trifluoromethyl-4-iodo-nicotinic acid (2) with amidine 9a catalyzed by Pd(2)(dba)(3) and Xantphos, followed by cyclization effected with HBTU and subsequent demethylation using PhBCl(2). The amidine arylation method was found applicable for the syntheses of quinazolin-4(3H)-ones. Thus, reaction of 2-bromo or 2-iodo benzoate esters with amdidines afforded substituted quinazolin-4(3H)-ones in 44-89% yields.
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Amidinas/química , Hidrocarbonetos Halogenados/química , Ácidos Nicotínicos/química , Pirimidinonas/síntese química , Quinazolinonas/síntese química , Catálise , Ciclização , Estrutura Molecular , Pirimidinonas/química , Quinazolinonas/químicaRESUMO
Fusions involving CRAF (RAF1) are infrequent oncogenic drivers in pediatric low-grade gliomas, rarely identified in tumors bearing features of pilocytic astrocytoma, and involving a limited number of known fusion partners. We describe recurrent TRAK1::RAF1 fusions, previously unreported in brain tumors, in three pediatric patients with low-grade glial-glioneuronal tumors. We present the associated clinical, histopathologic and molecular features. Patients were all female, aged 8 years, 15 months, and 10 months at diagnosis. All tumors were located in the cerebral hemispheres and predominantly cortical, with leptomeningeal involvement in 2/3 patients. Similar to previously described activating RAF1 fusions, the breakpoints in RAF1 all occurred 5' of the kinase domain, while the breakpoints in the 3' partner preserved the N-terminal kinesin-interacting domain and coiled-coil motifs of TRAK1. Two of the three cases demonstrated methylation profiles (v12.5) compatible with desmoplastic infantile ganglioglioma (DIG)/desmoplastic infantile astrocytoma (DIA) and have remained clinically stable and without disease progression/recurrence after resection. The remaining tumor was non-classifiable; with focal recurrence 14 months after initial resection; the patient remains symptom free and without further recurrence/progression (5 months post re-resection and 19 months from initial diagnosis). Our report expands the landscape of oncogenic RAF1 fusions in pediatric gliomas, which will help to further refine tumor classification and guide management of patients with these alterations.
Assuntos
Astrocitoma , Neoplasias Encefálicas , Ganglioglioma , Glioma , Criança , Feminino , Humanos , Proteínas Adaptadoras de Transporte Vesicular , Astrocitoma/genética , Astrocitoma/patologia , Neoplasias Encefálicas/patologia , Ganglioglioma/patologia , Glioma/genética , Glioma/patologia , Fusão OncogênicaRESUMO
BACKGROUND: Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity, alongside physiological alterations wearables can capture. OBJECTIVE: Firstly, we explored whether physiological wearable data could predict (aim 1) the severity of an acute affective episode at the intra-individual level and (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to prior predictions, generalization across patients, and associations between affective symptoms and physiological data. METHODS: We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded using a research-grade wearable (Empatica E4) across 3 consecutive time points (acute, response, and remission of episode). Euthymic patients and healthy controls were recorded during a single session (approximately 48 h). Manic and depressive symptoms were assessed using standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), skin temperature, blood volume pulse, heart rate (HR), and electrodermal activity (EDA). Invalid physiological data were removed using a rule-based filter, and channels were time aligned at 1-second time units and segmented at window lengths of 32 seconds, as best-performing parameters. We developed deep learning predictive models, assessed the channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel, fully automated method for the preprocessing and analysis of physiological data from a research-grade wearable device, including a viable supervised learning pipeline for time-series analyses. RESULTS: Overall, 35 sessions (1512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 healthy controls (mean age 39.7, SD 12.6 years; 6/19, 32% female) were analyzed. The severity of mood episodes was predicted with moderate (62%-85%) accuracies (aim 1), and their polarity with moderate (70%) accuracy (aim 2). The most relevant features for the former tasks were ACC, EDA, and HR. There was a fair agreement in feature importance across classification tasks (Kendall W=0.383). Generalization of the former models on unseen patients was of overall low accuracy, except for the intra-individual models. ACC was associated with "increased motor activity" (NMI>0.55), "insomnia" (NMI=0.6), and "motor inhibition" (NMI=0.75). EDA was associated with "aggressive behavior" (NMI=1.0) and "psychic anxiety" (NMI=0.52). CONCLUSIONS: Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression, respectively. These findings represent a promising pathway toward personalized psychiatry, in which physiological wearable data could allow the early identification and intervention of mood episodes.