Rectal cancer survivorship : work loss and long-term morbidity

In the last few decades, due to early detection and advances in treatments, rectal cancer survival has been improved significantly. Meanwhile, rectal cancer survivors and health practitioners are facing more challenges arising from the disease, in terms of survivors’ longterm morbidity and work ability. The general aims of the register-based doctoral projects therefore include: 1). to evaluate the short- and long-term work loss in incident relapse-free rectal cancer survivors, together with the underlying association between work loss and survivors’ clinical characteristics; 2). to investigate the long-term cardiotoxicity in irradiated relapse-free rectal cancer survivors; 3). to systematically estimate the long-term drug use as a proxy for morbidity in relapse-free rectal cancer survivors. In Study I, we included 2815 curatively treated working-age rectal cancer patients without previous disability pension and their matched general comparators. After a median follow-up of 6 years (range 0-10 years), we found nearly one fourth relapse-free survivors and one tenth of their comparators were on disability pension listing, making the disability pension risk significantly doubled in the relapse-free survivors. Abdominoperineal resection was associated with higher disability pension risk than anterior resection. Surgical complications and reoperation also yielded more risk in survivors’ disability pension. In Study II, using the same study design as the previous study, we found the median work loss days during the 1st after treatment was 147 days and 336 days among relapse-free rectal cancer survivors without (n=2,529) and with (n=909) prediagnostic work loss history, respectively. Among those who had prediagnostic work loss, the post-treatment work loss varied very little by clinical characteristics; whereas among those without any prediagnostic work loss, advanced stage at diagnosis, operated with Abdominoperineal resection, neoadjuvant (chemo)radiotherapy treatment and surgical complications were all associated with higher work loss risk in survivors. In Study III, we included 14901 register-based (9227 received preoperative radiotherapy (RT) and surgery and 5674 were treated only with surgery) and 2675 trial-based (randomized into preoperative RT or not followed by surgery) relapse-free rectal cancer patients during a maximum follow-up of 18 and 33 years, respectively. We found no significant overall or subtypes of cardiovascular risk associated with preoperative RT. Although a slightly elevated risk of venous thromboembolism was noted in both cohorts during the first 6 months following treatment, the absolute number of patients affected was rather low, hence the safety of RT was further assured. In Study IV, we evaluated the detailed prescribed drug dispensing using defined daily doses (DDDs) by the Anatomical Therapeutic Chemical (ATC) classification among relapse-free rectal cancer patients across a maximum follow-up of 10 years. In comparison to the general population, rectal cancer survivors had a slight increase in overall drug use. While the survivors did acquire more drugs in digestive system, this could be due to both the long-term disease complications and potential prophylactic treatment

Molecular Electrochemical Catalysis of the CO 2 -to-CO Conversion with a Co Complex: A Cyclic Voltammetry Mechanistic Investigation

International audienceThe electrochemical catalytic reduction of CO2 into CO could be achieved with excellent selectivity and rate in acetonitrile in the presence of phenol with cobalt 2,2′:6′,2″:6″,2‴-quaterpyridine complex [CoII(qpy)(H2O)2]2+ (Co) acting as a molecular catalyst. Upon using cyclic voltammetry at low and high scan rate (up to 500 V/s) two catalytic pathways have been identified. At a low concentration of phenol (<1 M), catalysis mainly occurs after the reduction of Co with three electrons. In that case, the selectivity for CO production is ca. 80% with 20% of H2 as by product, along with a turnover frequency of 1.2 × 104 s−1 for COproduction at an overpotential η of ca. 0.6 V. The triply reduced active species binds to CO2 and the C−O bond is cleaved thanks to the acid. At very large concentration of phenol (3 M), another pathway becomes predominant: the doubly reduced species binds to CO2, while its reductive protonation leads to CO formation. As already shown, this later process is endowed with fast rate at low overpotential (turnover frequency of 3 × 104 s−1 at η = 0.3 V) and 95% selectivity for CO production. By varying the phenol concentration and the scan rate in voltammetry experiments, it was thus possible to identify, activate, and characterize several pathways for the CO2-to-CO conversion and to decipher Co electrochemical reactivity toward CO2

Retroform Cervical Dystonia: Target Muscle Selection and Efficacy of Botulinum Toxin Injection

IntroductionRetroform cervical dystonia (RCD), which includes retrocaput and retrocollis, is a rare form of cervical dystonia. Few reports have been published on RCD. The present study aimed to characterize the target muscles involved in RCD and the efficacy of botulinum toxin type A (BTX-A) injection.MethodsPatients with consecutive cervical dystonia with RCD as the most problematic feature were retrospectively analyzed over a 10-year period. Target muscles were screened and confirmed based on clinical evaluation, single-photon emission computed tomography, and electromyography. In addition, efficacy and adverse events following BTX-A injection in patients with RCD were evaluated.ResultsA total of 34 patients with RCD were included, 18 of whom presented with retrocaput and 16 with retrocollis. The most frequently injected muscles in RCD were splenius capitis (SPCa, 97.1%) and semispinalis capitis (SSCa, 97.1%), followed by levator scapulae (LS, 50.0%), rectus capitis posterior major (RCPM, 47.1%), trapezius (TPZ, 41.2%), and sternocleidomastoid muscle (SCM, 41.2%). Besides cervical muscles, the erector spinae was also injected in 17.6% of patients. Most muscles were predominantly bilaterally injected. The injection schemes of retrocaput and retrocollis were similar, possibly because in patients with retrocollis, retrocaput was often combined. BTX-A injection achieved a satisfactory therapeutic effect in RCD, with an average symptom relief rate of 69.0 ± 16.7%. Mild dysphagia (17.6%) and posterior cervical muscle weakness (17.6%) were the most common adverse events.ConclusionSPCa, SSCa, LS, RCPM, LS, and SCM were commonly and often bilaterally injected in RCD. Patients with RCD could achieve satisfactory symptom relief after BTX-A injection

A sequential learning model with GNN for EEG-EMG-based stroke rehabilitation BCI

IntroductionBrain-computer interfaces (BCIs) have the potential in providing neurofeedback for stroke patients to improve motor rehabilitation. However, current BCIs often only detect general motor intentions and lack the precise information needed for complex movement execution, mainly due to insufficient movement execution features in EEG signals.MethodsThis paper presents a sequential learning model incorporating a Graph Isomorphic Network (GIN) that processes a sequence of graph-structured data derived from EEG and EMG signals. Movement data are divided into sub-actions and predicted separately by the model, generating a sequential motor encoding that reflects the sequential features of the movements. Through time-based ensemble learning, the proposed method achieves more accurate prediction results and execution quality scores for each movement.ResultsA classification accuracy of 88.89% is achieved on an EEG-EMG synchronized dataset for push and pull movements, significantly outperforming the benchmark method's performance of 73.23%.DiscussionThis approach can be used to develop a hybrid EEG-EMG brain-computer interface to provide patients with more accurate neural feedback to aid their recovery

Subject-independent EEG classification based on a hybrid neural network

A brain-computer interface (BCI) based on the electroencephalograph (EEG) signal is a novel technology that provides a direct pathway between human brain and outside world. For a traditional subject-dependent BCI system, a calibration procedure is required to collect sufficient data to build a subject-specific adaptation model, which can be a huge challenge for stroke patients. In contrast, subject-independent BCI which can shorten or even eliminate the pre-calibration is more time-saving and meets the requirements of new users for quick access to the BCI. In this paper, we design a novel fusion neural network EEG classification framework that uses a specially designed generative adversarial network (GAN), called a filter bank GAN (FBGAN), to acquire high-quality EEG data for augmentation and a proposed discriminative feature network for motor imagery (MI) task recognition. Specifically, multiple sub-bands of MI EEG are first filtered using a filter bank approach, then sparse common spatial pattern (CSP) features are extracted from multiple bands of filtered EEG data, which constrains the GAN to maintain more spatial features of the EEG signal, and finally we design a convolutional recurrent network classification method with discriminative features (CRNN-DF) to recognize MI tasks based on the idea of feature enhancement. The hybrid neural network proposed in this study achieves an average classification accuracy of 72.74 ± 10.44% (mean ± std) in four-class tasks of BCI IV-2a, which is 4.77% higher than the state-of-the-art subject-independent classification method. A promising approach is provided to facilitate the practical application of BCI

American Gut: An Open Platform For Citizen Science Microbiome Research

Copyright © 2018 McDonald et al. Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples