RESUMEN
The brain's connectome provides the scaffold for canonical neural computations. However, a comparison of connectivity studies in the mouse primary visual cortex (V1) reveals that the average number and strength of connections between specific neuron types can vary. Can variability in V1 connectivity measurements coexist with canonical neural computations? We developed a theory-driven approach to deduce V1 network connectivity from visual responses in mouse V1 and visual thalamus (dLGN). Our method revealed that the same recorded visual responses were captured by multiple connectivity configurations. Remarkably, the magnitude and selectivity of connectivity weights followed a specific order across most of the inferred connectivity configurations. We argue that this order stems from the specific shapes of the recorded contrast response functions and contrast invariance of orientation tuning. Remarkably, despite variability across connectivity studies, connectivity weights computed from individual published connectivity reports followed the order we identified with our method, suggesting that the relations between the weights, rather than their magnitudes, represent a connectivity motif supporting canonical V1 computations.
Asunto(s)
Corteza Visual , Animales , Ratones , Neuronas/fisiología , Estimulación Luminosa/métodos , Tálamo/fisiología , Corteza Visual/fisiología , Vías Visuales/fisiologíaRESUMEN
BACKGROUND: Monitoring social media has been shown to be a useful means to capture patients' opinions and feelings about medical issues, ranging from diseases to treatments. Health-related quality of life (HRQoL) is a useful indicator of overall patients' health, which can be captured online. OBJECTIVE: This study aimed to describe a social media listening algorithm able to detect the impact of diseases or treatments on specific dimensions of HRQoL based on posts written by patients in social media and forums. METHODS: Using a web crawler, 19 forums in France were harvested, and messages related to patients' experience with disease or treatment were specifically collected. The SF-36 (Short Form Health Survey) and EQ-5D (Euro Quality of Life 5 Dimensions) HRQoL surveys were mixed and adapted for a tailored social media listening system. This was carried out to better capture the variety of expression on social media, resulting in 5 dimensions of the HRQoL, which are physical, psychological, activity-based, social, and financial. Models were trained using cross-validation and hyperparameter optimization. Oversampling was used to increase the infrequent dimension: after annotation, SMOTE (synthetic minority oversampling technique) was used to balance the proportions of the dimensions among messages. RESULTS: The training set was composed of 1399 messages, randomly taken from a batch of 20,000 health-related messages coming from forums. The algorithm was able to detect a general impact on HRQoL (sensitivity of 0.83 and specificity of 0.74), a physical impact (0.67 and 0.76), a psychic impact (0.82 and 0.60), an activity-related impact (0.73 and 0.78), a relational impact (0.73 and 0.70), and a financial impact (0.79 and 0.74). CONCLUSIONS: The development of an innovative method to extract health data from social media as real time assessment of patients' HRQoL is useful to a patient-centered medical care. As a source of real-world data, social media provide a complementary point of view to understand patients' concerns and unmet needs, as well as shedding light on how diseases and treatments can be a burden in their daily lives.
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Calidad de Vida , Medios de Comunicación Sociales , Algoritmos , Humanos , Calidad de Vida/psicología , Proyectos de Investigación , Encuestas y CuestionariosRESUMEN
Electron-rich triarylphosphines, namely 4-(methoxyphenyl)diphenylphosphine (MMTPP) and tris(4-trimethoxyphenyl)phosphine (TMTPP), outperform commonly used triphenylphosphine (TPP) in catalyzing oxa-Michael additions. A matrix consisting of three differently strong Michael acceptors and four alcohols of varying acidity was used to assess the activity of the three catalysts. All test reactions were performed with 1 mol % catalyst loading, under solvent-free conditions and at room temperature. The results reveal a decisive superiority of TMTPP for converting poor and intermediate Michael acceptors such as acrylamide and acrylonitrile and for converting less acidic alcohols like isopropanol. With stronger Michael acceptors and more acidic alcohols, the impact of the more electron-rich catalysts is less pronounced. The experimental activity trend was rationalized by calculating the Michael acceptor affinities of all phosphine-Michael acceptor combinations. Besides this parameter, the acidity of the alcohol has a strong impact on the reaction speed. The oxidation stability of the phosphines was also evaluated and the most electron-rich TMTPP was found to be only slightly more sensitive to oxidation than TPP. Finally, the catalysts were employed in the oxa-Michael polymerization of 2-hydroxyethyl acrylate. With TMTPP polymers characterized by number average molar masses of about 1200 g/mol at room temperature are accessible. Polymerizations carried out at 80 °C resulted in macromolecules containing a considerable share of Rauhut-Currier-type repeat units and consequently lower molar masses were obtained.
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BACKGROUND: In 2022, it was estimated that more than 80,000 new cases of bladder cancer (BC) were diagnosed in the United States, 12% of which were locally advanced or metastatic BC (advanced BC). These forms of cancer are aggressive and have a poor prognosis, with a 5-year survival rate of 7.7% for metastatic BC. Despite recent therapeutic advances for advanced BC, little is known about patient and caregiver perceptions of different systemic treatments. To further explore this topic, social media can be used to collect the perceptions of patients and caregivers when they discuss their experiences on forums and online communities. OBJECTIVE: The aim of this study was to assess patient and caregiver perceptions of chemotherapy and immunotherapy for treating advanced BC from social media-posted data. METHODS: Public posts on social media in the United States between January 2015 and April 2021 from patients with advanced BC and their caregivers were collected. The posts included in this analysis were geolocalized to the United States; collected from publicly available domains and sites, including social media sites such as Twitter and forums such as patient association forums; and were written in English. Posts mentioning any line of chemotherapy or immunotherapy were qualitatively analyzed by two researchers to classify perceptions of treatments (positive, negative, mixed, or without perception). RESULTS: A total of 80 posts by 69 patients and 142 posts by 127 caregivers mentioning chemotherapy, and 42 posts by 31 patients and 35 posts by 32 caregivers mentioning immunotherapy were included for analysis. These posts were retrieved from 39 public social media sites. Among patients with advanced BC and their caregivers, treatment perceptions of chemotherapy were more negative (36%) than positive (7%). Most of the patients' posts (71%) mentioned chemotherapy factually without expressing a perception of the treatment. The caregivers' perceptions of treatment were negative in 44%, mixed in 8%, and positive in 7% of posts. In combined patient and caregiver posts, immunotherapy was perceived positively in 47% of posts and negatively in 22% of posts. Caregivers also posted more negative perceptions (37%) of immunotherapy than patients (9%). Negative perceptions of both chemotherapy and immunotherapy were mainly due to side effects and perceived lack of effectiveness. CONCLUSIONS: Despite chemotherapy being standard first-line therapy for advanced BC, negative perceptions were identified on social media, particularly among caregivers. Addressing these negative perceptions of treatment may improve treatment adoption. Strengthening support for patients receiving chemotherapy and their caregivers to help them manage side effects and understand the role of chemotherapy in the treatment of advanced BC would potentially enable a more positive experience.
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Background: Long COVID-a condition with persistent symptoms post COVID-19 infection-is the first illness arising from social media. In France, the French hashtag #ApresJ20 described symptoms persisting longer than 20 days after contracting COVID-19. Faced with a lack of recognition from medical and official entities, patients formed communities on social media and described their symptoms as long-lasting, fluctuating, and multisystemic. While many studies on long COVID relied on traditional research methods with lengthy processes, social media offers a foundation for large-scale studies with a fast-flowing outburst of data. Objective: We aimed to identify and analyze Long Haulers' main reported symptoms, symptom co-occurrences, topics of discussion, difficulties encountered, and patient profiles. Methods: Data were extracted based on a list of pertinent keywords from public sites (eg, Twitter) and health-related forums (eg, Doctissimo). Reported symptoms were identified via the MedDRA dictionary, displayed per the volume of posts mentioning them, and aggregated at the user level. Associations were assessed by computing co-occurrences in users' messages, as pairs of preferred terms. Discussion topics were analyzed using the Biterm Topic Modeling; difficulties and unmet needs were explored manually. To identify patient profiles in relation to their symptoms, each preferred term's total was used to create user-level hierarchal clusters. Results: Between January 1, 2020, and August 10, 2021, overall, 15,364 messages were identified as originating from 6494 patients of long COVID or their caregivers. Our analyses revealed 3 major symptom co-occurrences: asthenia-dyspnea (102/289, 35.3%), asthenia-anxiety (65/289, 22.5%), and asthenia-headaches (50/289, 17.3%). The main reported difficulties were symptom management (150/424, 35.4% of messages), psychological impact (64/424,15.1%), significant pain (51/424, 12.0%), deterioration in general well-being (52/424, 12.3%), and impact on daily and professional life (40/424, 9.4% and 34/424, 8.0% of messages, respectively). We identified 3 profiles of patients in relation to their symptoms: profile A (n=406 patients) reported exclusively an asthenia symptom; profile B (n=129) expressed anxiety (n=129, 100%), asthenia (n=28, 21.7%), dyspnea (n=15, 11.6%), and ageusia (n=3, 2.3%); and profile C (n=141) described dyspnea (n=141, 100%), and asthenia (n=45, 31.9%). Approximately 49.1% of users (79/161) continued expressing symptoms after more than 3 months post infection, and 20.5% (33/161) after 1 year. Conclusions: Long COVID is a lingering condition that affects people worldwide, physically and psychologically. It impacts Long Haulers' quality of life, everyday tasks, and professional activities. Social media played an undeniable role in raising and delivering Long Haulers' voices and can potentially rapidly provide large volumes of valuable patient-reported information. Since long COVID was a self-titled condition by patients themselves via social media, it is imperative to continuously include their perspectives in related research. Our results can help design patient-centric instruments to be further used in clinical practice to better capture meaningful dimensions of long COVID.
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BACKGROUND: Locally advanced or metastatic bladder cancer (BC), which is generally termed advanced BC (aBC), has a very poor prognosis, and in addition to its physical symptoms, it is associated with emotional and social challenges. However, few studies have assessed the unmet needs and burden of aBC from patient and caregiver perspectives. Infodemiology, that is, epidemiology based on internet health-related content, can help obtain more insights on patients' and caregivers' experiences with aBC. OBJECTIVE: The study aimed to identify the main discussion themes and the unmet needs of patients with aBC and their caregivers through a mixed methods analysis of social media posts. METHODS: Social media posts were collected between January 2015 and April 2021 from US geolocalized sites using specific keywords for aBC. Automatic natural language processing (regular expressions and machine learning) methods were used to filter out irrelevant content and identify verbatim posts from patients and caregivers. The verbatim posts were analyzed to identify main discussion themes using biterm topic modeling. Difficulties or unmet needs were further explored using qualitative research methods by 2 independent annotators until saturation of concepts. RESULTS: A total of 688 posts from 262 patients and 1214 posts from 679 caregivers discussing aBC were identified. Analysis of 340 randomly selected patient posts and 423 randomly selected caregiver posts uncovered 33 unique unmet need categories among patients and 36 among caregivers. The main unmet patient needs were related to challenges regarding adverse events (AEs; 28/95, 29%) and the psychological impact of aBC (20/95, 21%). Other patient unmet needs identified were prognosis or diagnosis errors (9/95, 9%) and the need for better management of aBC symptoms (9/95, 9%). The main unmet caregiver needs were related to the psychological impacts of aBC (46/177, 26.0%), the need for support groups and to share experiences between peers (28/177, 15.8%), and the fear and management of patient AEs (22/177, 12.4%). CONCLUSIONS: The combination of manual and automatic methods allowed the extraction and analysis of several hundreds of social media posts from patients with aBC and their caregivers. The results highlighted the emotional burden of cancer for both patients and caregivers. Additional studies on patients with aBC and their caregivers are required to quantitatively explore the impact of this disease on quality of life.