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BioRxiv : the Preprint Server For... May 2024Major Depressive Disorder (MDD) presents a significant public health challenge. Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) shows promise...
Major Depressive Disorder (MDD) presents a significant public health challenge. Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) shows promise as a treatment for this disorder, although its mechanisms of action remain unclear. This study investigated whole-brain response patterns during rtfMRI-NF training to explain interindividual variability in clinical efficacy in MDD. We analyzed data from 95 participants (67 active, 28 control) with MDD from previous rtfMRI-NF studies designed to increase left amygdala activation through positive autobiographical memory recall. We focused on whole-brain activation patterns during two critical epochs of the neurofeedback procedure: activation during the self-regulation period and transient responses to feedback signal presentation. Through a systematic process involving feature selection, manifold extraction, and clustering with cross-validation, we identified subtypes within these patterns. Significant symptom reduction was observed in the active group ( =-4.404, =-0.704, <0.001) but not in the control group ( = -1.609, =-0.430, =0.111); however, left amygdala activation did not account for the variability in clinical efficacy. Subtyping analysis revealed two subtypes in regulation activation and three subtypes in brain responses to feedback signals (regulation: =8.735, =0.005; feedback response: =5.326, =0.008; interaction: =3.471, =0.039). Subtypes associated with significant symptom reduction were characterized by selective increases in control regions, including lateral prefrontal areas, and decreases in regions associated with self-referential thinking, such as default mode areas. These findings suggest that large-scale brain activity is more critical for clinical efficacy than the level of activation in the neurofeedback target region during training. Tailoring neurofeedback training to incorporate these patterns could significantly enhance its therapeutic efficacy.
PubMed: 38746338
DOI: 10.1101/2024.05.01.592108 -
Journal of the Intensive Care Society May 2024Despite high rates of cardiovascular disease in Scotland, the prevalence and outcomes of patients with cardiogenic shock are unknown.
EPidemiology Of Cardiogenic sHock in Scotland (EPOCHS): A multicentre, prospective observational study of the prevalence, management and outcomes of cardiogenic shock in Scotland.
BACKGROUND
Despite high rates of cardiovascular disease in Scotland, the prevalence and outcomes of patients with cardiogenic shock are unknown.
METHODS
We undertook a prospective observational cohort study of consecutive patients with cardiogenic shock admitted to the intensive care unit (ICU) or coronary care unit at 13 hospitals in Scotland for a 6-month period. Denominator data from the Scottish Intensive Care Society Audit Group were used to estimate ICU prevalence; data for coronary care units were unavailable. We undertook multivariable logistic regression to identify factors associated with in-hospital mortality.
RESULTS
In total, 247 patients with cardiogenic shock were included. After exclusion of coronary care unit admissions, this comprised 3.0% of all ICU admissions during the study period (95% confidence interval [CI] 2.6%-3.5%). Aetiology was acute myocardial infarction (AMI) in 48%. The commonest vasoactive treatment was noradrenaline (56%) followed by adrenaline (46%) and dobutamine (40%). Mechanical circulatory support was used in 30%. Overall in-hospital mortality was 55%. After multivariable logistic regression, age (odds ratio [OR] 1.04, 95% CI 1.02-1.06), admission lactate (OR 1.10, 95% CI 1.05-1.19), Society for Cardiovascular Angiographic Intervention stage D or E at presentation (OR 2.16, 95% CI 1.10-4.29) and use of adrenaline (OR 2.73, 95% CI 1.40-5.40) were associated with mortality.
CONCLUSIONS
In Scotland the prevalence of cardiogenic shock was 3% of all ICU admissions; more than half died prior to discharge. There was significant variation in treatment approaches, particularly with respect to vasoactive support strategy.
PubMed: 38737313
DOI: 10.1177/17511437231217877 -
Frontiers in Public Health 2024Social media platforms serve as a valuable resource for users to share health-related information, aiding in the monitoring of adverse events linked to medications and...
INTRODUCTION
Social media platforms serve as a valuable resource for users to share health-related information, aiding in the monitoring of adverse events linked to medications and treatments in drug safety surveillance. However, extracting drug-related adverse events accurately and efficiently from social media poses challenges in both natural language processing research and the pharmacovigilance domain.
METHOD
Recognizing the lack of detailed implementation and evaluation of Bidirectional Encoder Representations from Transformers (BERT)-based models for drug adverse event extraction on social media, we developed a BERT-based language model tailored to identifying drug adverse events in this context. Our model utilized publicly available labeled adverse event data from the ADE-Corpus-V2. Constructing the BERT-based model involved optimizing key hyperparameters, such as the number of training epochs, batch size, and learning rate. Through ten hold-out evaluations on ADE-Corpus-V2 data and external social media datasets, our model consistently demonstrated high accuracy in drug adverse event detection.
RESULT
The hold-out evaluations resulted in average F1 scores of 0.8575, 0.9049, and 0.9813 for detecting words of adverse events, words in adverse events, and words not in adverse events, respectively. External validation using human-labeled adverse event tweets data from SMM4H further substantiated the effectiveness of our model, yielding F1 scores 0.8127, 0.8068, and 0.9790 for detecting words of adverse events, words in adverse events, and words not in adverse events, respectively.
DISCUSSION
This study not only showcases the effectiveness of BERT-based language models in accurately identifying drug-related adverse events in the dynamic landscape of social media data, but also addresses the need for the implementation of a comprehensive study design and evaluation. By doing so, we contribute to the advancement of pharmacovigilance practices and methodologies in the context of emerging information sources like social media.
Topics: Social Media; Pharmacovigilance; Humans; Natural Language Processing; Drug-Related Side Effects and Adverse Reactions; Adverse Drug Reaction Reporting Systems
PubMed: 38716250
DOI: 10.3389/fpubh.2024.1392180 -
Nanoscale Advances Apr 2024The nexus of advanced technology and medical therapeutics has ushered in a transformative epoch in contemporary medicine. Within this arena, Magnetic Resonance Imaging... (Review)
Review
The nexus of advanced technology and medical therapeutics has ushered in a transformative epoch in contemporary medicine. Within this arena, Magnetic Resonance Imaging (MRI) emerges as a paramount tool, intertwining the advancements of technology with the art of healing. MRI's pivotal role is evident in its broad applicability, spanning from neurological diseases, soft-tissue and tumour characterization, to many more applications. Though already foundational, aspirations remain to further enhance MRI's capabilities. A significant avenue under exploration is the incorporation of innovative nanotechnological contrast agents. Forefront among these are Superparamagnetic Iron Oxide Nanoparticles (SPIONs), recognized for their adaptability and safety profile. SPION's intrinsic malleability allows them to be tailored for improved biocompatibility, while their functionality is further broadened when equipped with specific targeting molecules. Yet, the path to optimization is not devoid of challenges, from renal clearance concerns to potential side effects stemming from iron overload. This review endeavors to map the intricate journey of SPIONs as MRI contrast agents, offering a chronological perspective of their evolution and deployment. We provide an in-depth current outline of the most representative and impactful pre-clinical and clinical studies centered on the integration of SPIONs in MRI, tracing their trajectory from foundational research to contemporary applications.
PubMed: 38694462
DOI: 10.1039/d3na01064c -
Frontiers in Chemistry 2024The epoch of Nano-biomaterials and their application in the field of medicine and dentistry has been long-lived. The application of nanotechnology is extensively used in... (Review)
Review
The epoch of Nano-biomaterials and their application in the field of medicine and dentistry has been long-lived. The application of nanotechnology is extensively used in diagnosis and treatment aspects of oral diseases. The nanomaterials and its structures are being widely involved in the production of medicines and drugs used for the treatment of oral diseases like periodontitis, oral carcinoma, etc. and helps in maintaining the longevity of oral health. Chitosan is a naturally occurring biopolymer derived from chitin which is seen commonly in arthropods. Chitosan nanoparticles are the latest in the trend of nanoparticles used in dentistry and are becoming the most wanted biopolymer for use toward therapeutic interventions. Literature search has also shown that chitosan nanoparticles have anti-tumor effects. This review highlights the various aspects of chitosan nanoparticles and their implications in dentistry.
PubMed: 38660569
DOI: 10.3389/fchem.2024.1362482 -
Frontiers in Artificial Intelligence 2024We proposed an artificial neural network model to predict radiobiological parameters for the head and neck squamous cell carcinoma patients treated with radiation...
BACKGROUND AND PURPOSE
We proposed an artificial neural network model to predict radiobiological parameters for the head and neck squamous cell carcinoma patients treated with radiation therapy. The model uses the tumor specification, demographics, and radiation dose distribution to predict the tumor control probability and the normal tissue complications probability. These indices are crucial for the assessment and clinical management of cancer patients during treatment planning.
METHODS
Two publicly available datasets of 31 and 215 head and neck squamous cell carcinoma patients treated with conformal radiation therapy were selected. The demographics, tumor specifications, and radiation therapy treatment parameters were extracted from the datasets used as inputs for the training of perceptron. Radiobiological indices are calculated by open-source software using dosevolume histograms from radiation therapy treatment plans. Those indices were used as output in the training of a single-layer neural network. The distribution of data used for training, validation, and testing purposes was 70, 15, and 15%, respectively.
RESULTS
The best performance of the neural network was noted at epoch number 32 with the mean squared error of 0.0465. The accuracy of the prediction of radiobiological indices by the artificial neural network in training, validation, and test phases were determined to be 0.89, 0.87, and 0.82, respectively. We also found that the percentage volume of parotid inside the planning target volume is the significant parameter for the prediction of normal tissue complications probability.
CONCLUSION
We believe that the model has significant potential to predict radiobiological indices and help clinicians in treatment plan evaluation and treatment management of head and neck squamous cell carcinoma patients.
PubMed: 38646416
DOI: 10.3389/frai.2024.1329737 -
Journal of Korean Medical Science Apr 2024The advent of the omicron variant and the formulation of diverse therapeutic strategies marked a new epoch in the realm of coronavirus disease 2019 (COVID-19). Studies...
BACKGROUND
The advent of the omicron variant and the formulation of diverse therapeutic strategies marked a new epoch in the realm of coronavirus disease 2019 (COVID-19). Studies have compared the clinical outcomes between COVID-19 and seasonal influenza, but such studies were conducted during the early stages of the pandemic when effective treatment strategies had not yet been developed, which limits the generalizability of the findings. Therefore, an updated evaluation of the comparative analysis of clinical outcomes between COVID-19 and seasonal influenza is requisite.
METHODS
This study used data from the severe acute respiratory infection surveillance system of South Korea. We extracted data for influenza patients who were infected between 2018 and 2019 and COVID-19 patients who were infected in 2021 (pre-omicron period) and 2022 (omicron period). Comparisons of outcomes were conducted among the pre-omicron, omicron, and influenza cohorts utilizing propensity score matching. The adjusted covariates in the propensity score matching included age, sex, smoking, and comorbidities.
RESULTS
The study incorporated 1,227 patients in the pre-omicron cohort, 1,948 patients in the omicron cohort, and 920 patients in the influenza cohort. Following propensity score matching, 491 patients were included in each respective group. Clinical presentations exhibited similarities between the pre-omicron and omicron cohorts; however, COVID-19 patients demonstrated a higher prevalence of dyspnea and pulmonary infiltrates compared to their influenza counterparts. Both COVID-19 groups exhibited higher in-hospital mortality and longer hospital length of stay than the influenza group. The omicron group showed no significant improvement in clinical outcomes compared to the pre-omicron group.
CONCLUSION
The omicron group did not demonstrate better clinical outcomes than the pre-omicron group, and exhibited significant disease severity compared to the influenza group. Considering the likely persistence of COVID-19 infections, it is imperative to sustain comprehensive studies and ongoing policy support for the virus to enhance the prognosis for individuals affected by COVID-19.
Topics: Humans; Influenza, Human; COVID-19; Propensity Score; Seasons; SARS-CoV-2; Republic of Korea
PubMed: 38622937
DOI: 10.3346/jkms.2024.39.e128 -
The Journal of Maternal-fetal &... Dec 2024To evaluate the effectiveness of using hospital-based 40% dextrose gel (DG) in preventing and treating asymptomatic hypoglycemia in infants of diabetic mothers (IDM),...
OBJECTIVE
To evaluate the effectiveness of using hospital-based 40% dextrose gel (DG) in preventing and treating asymptomatic hypoglycemia in infants of diabetic mothers (IDM), large for gestational age (LGA), and macrosomic neonates.
METHODS
A medical chart review was conducted to compare data between before (April 2018 to March 2019, epoch 1) and after (September 2020 to November 2021, epoch 2) 40% DG implementation. DG, prepared by the hospital pharmaceutical unit, was applied within 30-45 min after birth, and three additional doses could be repeated during the first 6 h of life in combination with early feeding. The primary outcome was the rate of intravenous dextrose administration. Secondary outcomes were the incidence of hypoglycemia, first capillary blood glucose concentrations, and the length of hospital stay.
RESULTS
Six hundred forty-three at-risk newborns were included (320 before and 323 after implementation of DG). Maternal and neonatal baseline characteristics were not different between the two epochs. The incidence of hypoglycemia was not different (17.8% in before versus 14.6% in after implementation, = 0.26). The rate of intravenous dextrose administration after DG implementation was significantly lower than that before DG implementation (3.4% versus 10.3%, < 0.001, risk reduction ratio = 0.33, 95% CI = 0.17-0.64). The length of hospital stay was not different between the two epochs.
CONCLUSIONS
Implementing a protocol for administration of hospital-based 40% DG can reduce the need of intravenous dextrose administration among IDM, LGA and macrosomic neonates.
Topics: Infant, Newborn; Infant; Female; Humans; Administration, Intravenous; Gels; Hospitals; Hypoglycemia; Pregnancy in Diabetics; Weight Gain; Glucose
PubMed: 38616182
DOI: 10.1080/14767058.2024.2341310 -
Frontiers in Molecular Neuroscience 2024A patient with the E280A mutation and homozygous for Christchurch () displayed extreme resistance to Alzheimer's disease (AD) cognitive decline and tauopathy, despite...
A patient with the E280A mutation and homozygous for Christchurch () displayed extreme resistance to Alzheimer's disease (AD) cognitive decline and tauopathy, despite having a high amyloid burden. To further investigate the differences in biological processes attributed to , we generated induced pluripotent stem (iPS) cell-derived cerebral organoids from this resistant case and a non-protected control, using CRISPR/Cas9 gene editing to modulate expression. In the cerebral organoids, we observed a protective pattern from early tau phosphorylation. ScRNA sequencing revealed regulation of Cadherin and Wnt signaling pathways by , with immunostaining indicating elevated β-catenin protein levels. Further reporter assays unexpectedly demonstrated that ApoE3Ch functions as a Wnt3a signaling enhancer. This work uncovered a neomorphic molecular mechanism of protection of ApoE3 Christchurch, which may serve as the foundation for the future development of protected case-inspired therapeutics targeting AD and tauopathies.
PubMed: 38571814
DOI: 10.3389/fnmol.2024.1373568 -
Biology of Sport Mar 2024The purpose of this study was three-fold: (i) to compare total distance, high-speed running (HSR) distance, and sprint distance covered per 5-minute epoch by players...
Testing variations between starters and substitute players in terms of total distance, high-speed running, and sprinting distance: a descriptive study on professional male soccer players.
The purpose of this study was three-fold: (i) to compare total distance, high-speed running (HSR) distance, and sprint distance covered per 5-minute epoch by players acting as both starters and substitutes; (ii) to compare the locomotor demands between the moments the players entered the match (45-60, 60-75 and 75-90 minutes); and (iii) to compare the locomotor demands of the players between the variations of the within- and between-playing positions. Twenty-one male professional soccer players competing in the Professional Premier League of one of the European countries were observed over sixteen official matches. The players were monitored during all matches using a Global Navigation Satellite System. The measures collected were total distance (TD; m), distance in HSR, sprint distance, HSR, and sprint counts. Considering the comparisons between the splits over the second half of match play, a significant difference between the starters and the substitutes was observed only for sprint distance in the 90-95 minute split (Z = -2.023; p = 0.043). Moreover, no substantial differences were found between the moment the substitute player entered the match regarding total distance (H = 2.650; p = 0.266), HSR distance (H = 1.738; p = 0.419), and sprint distance (H = 0.048; p = 0.976). However, the comparison of between-playing positions revealed considerable differences in total distance (H = 29.246; p < 0.001), and HSR distance (H = 12.153; p = 0.002) covered by the players acting as starters. In contrast, for substitute players, such differences were reported in HSR distance (H = 27.892; p < 0.001) and sprint distance (H = 15.879; p < 0.001). In conclusion, this study suggests that acting as a starter or a substitute does not significantly affect the intensity of effort except during the last periods of match play. However, the contextual factor of performing in a specific playing position plays a significant role both for starters and substitutes.
PubMed: 38524810
DOI: 10.5114/biolsport.2024.131817