In vivo rescue of genetic dilated cardiomyopathy by systemic delivery of nexilin.

BACKGROUND: Dilated cardiomyopathy (DCM) is one of the most common causes of heart failure. Multiple identified mutations in nexilin (NEXN) have been suggested to be linked with severe DCM. However, the exact association between multiple mutations of Nexn and DCM remains unclear. Moreover, it is critical for the development of precise and effective therapeutics in treatments of DCM. RESULTS: In our study, Nexn global knockout mice and mice carrying human equivalent G645del mutation are studied using functional gene rescue assays. AAV-mediated gene delivery is conducted through systemic intravenous injections at the neonatal stage. Heart tissues are analyzed by immunoblots, and functions are assessed by echocardiography. Here, we identify functional components of Nexilin and demonstrate that exogenous introduction could rescue the cardiac function and extend the lifespan of Nexn knockout mouse models. Similar therapeutic effects are also obtained in G645del mice, providing a promising intervention for future clinical therapeutics. CONCLUSIONS: In summary, we demonstrated that a single injection of AAV-Nexn was capable to restore the functions of cardiomyocytes and extended the lifespan of Nexn knockout and G645del mice. Our study represented a long-term gene replacement therapy for DCM that potentially covers all forms of loss-of-function mutations in NEXN.

Patient listening on social media for patient-focused drug development: a synthesis of considerations from patients, industry and regulators.

Patients, life science industry and regulatory authorities are united in their goal to reduce the disease burden of patients by closing remaining unmet needs. Patients have, however, not always been systematically and consistently involved in the drug development process. Recognizing this gap, regulatory bodies worldwide have initiated patient-focused drug development (PFDD) initiatives to foster a more systematic involvement of patients in the drug development process and to ensure that outcomes measured in clinical trials are truly relevant to patients and represent significant improvements to their quality of life. As a source of real-world evidence (RWE), social media has been consistently shown to capture the first-hand, spontaneous and unfiltered disease and treatment experience of patients and is acknowledged as a valid method for generating patient experience data by the Food and Drug Administration (FDA). While social media listening (SML) methods are increasingly applied to many diseases and use cases, a significant piece of uncertainty remains on how evidence derived from social media can be used in the drug development process and how it can impact regulatory decision making, including legal and ethical aspects. In this policy paper, we review the perspectives of three key stakeholder groups on the role of SML in drug development, namely patients, life science companies and regulators. We also carry out a systematic review of current practices and use cases for SML and, in particular, highlight benefits and drawbacks for the use of SML as a way to identify unmet needs of patients. While we find that the stakeholders are strongly aligned regarding the potential of social media for PFDD, we identify key areas in which regulatory guidance is needed to reduce uncertainty regarding the impact of SML as a source of patient experience data that has impact on regulatory decision making.

Intervention with metabolites emulating endogenous cell transitions accelerates muscle regeneration in young and aged mice.

Tissue regeneration following an injury requires dynamic cell-state transitions that allow for establishing the cell identities required for the restoration of tissue homeostasis and function. Here, we present a biochemical intervention that induces an intermediate cell state mirroring a transition identified during normal differentiation of myoblasts and other multipotent and pluripotent cells to mature cells. When applied in somatic differentiated cells, the intervention, composed of one-carbon metabolites, reduces some dedifferentiation markers without losing the lineage identity, thus inducing limited reprogramming into a more flexible cell state. Moreover, the intervention enabled accelerated repair after muscle injury in young and aged mice. Overall, our study uncovers a conserved biochemical transitional phase that enhances cellular plasticity in vivo and hints at potential and scalable biochemical interventions of use in regenerative medicine and rejuvenation interventions that may be more tractable than genetic ones.

Mitochondrial and ribosomal markers in the identification of nematodes of clinical and veterinary importance.

BACKGROUND: Nematodes of the Ascarididae, Ancylostomatidae and Onchocercidae families are parasites of human and veterinary importance causing infections with high prevalence worldwide. Molecular tools have significantly improved the diagnosis of these helminthiases, but the selection of genetic markers for PCR or metabarcoding purposes is often challenging because of the resolution these may show. METHODS: Nuclear 18S rRNA, internal transcribed spacers 1 (ITS-1) and 2 (ITS-2), mitochondrial gene cytochrome oxidase 1 (cox1) and mitochondrial rRNA genes 12S and 16S loci were studied for 30 species of the mentioned families. Accordingly, their phylogenetic interspecies resolution, pairwise nucleotide p-distances and sequence availability in GenBank were analyzed. RESULTS: The 18S rRNA showed the least interspecies resolution since separate species of the Ascaris, Mansonella, Toxocara or Ancylostoma genus were intermixed in phylogenetic trees as opposed to the ITS-1, ITS-2, cox1, 12S and 16S loci. Moreover, pairwise nucleotide p-distances were significantly different in the 18S compared to the other loci, with an average of 99.1 ± 0.1%, 99.8 ± 0.1% and 98.8 ± 0.9% for the Ascarididae, Ancylostomatidae and Onchocercidae families, respectively. However, ITS-1 and ITS-2 average pairwise nucleotide p-distances in the three families ranged from 72.7% to 87.3%, and the cox1, 12S and 16S ranged from 86.4% to 90.4%. Additionally, 2491 cox1 sequences were retrieved from the 30 analyzed species in GenBank, whereas 212, 1082, 994, 428 and 143 sequences could be obtained from the 18S, ITS-1, ITS-2, 12S and 16S markers, respectively. CONCLUSIONS: The use of the cox1 gene is recommended because of the high interspecies resolution and the large number of sequences available in databases. Importantly, confirmation of the identity of an unknown specimen should always be complemented with the careful morphological examination of worms and the analysis of other markers used for specific parasitic groups.

Overview of the 8th Social Media Mining for Health Applications (#SMM4H) shared tasks at the AMIA 2023 Annual Symposium.

OBJECTIVE: The aim of the Social Media Mining for Health Applications (#SMM4H) shared tasks is to take a community-driven approach to address the natural language processing and machine learning challenges inherent to utilizing social media data for health informatics. In this paper, we present the annotated corpora, a technical summary of participants' systems, and the performance results. METHODS: The eighth iteration of the #SMM4H shared tasks was hosted at the AMIA 2023 Annual Symposium and consisted of 5 tasks that represented various social media platforms (Twitter and Reddit), languages (English and Spanish), methods (binary classification, multi-class classification, extraction, and normalization), and topics (COVID-19, therapies, social anxiety disorder, and adverse drug events). RESULTS: In total, 29 teams registered, representing 17 countries. In general, the top-performing systems used deep neural network architectures based on pre-trained transformer models. In particular, the top-performing systems for the classification tasks were based on single models that were pre-trained on social media corpora. CONCLUSION: To facilitate future work, the datasets-a total of 61 353 posts-will remain available by request, and the CodaLab sites will remain active for a post-evaluation phase.

What happens to the inhibitory control functions of the right inferior frontal cortex when this area is dominant for language?

A low number of individuals show an atypical brain control of language functions that differs from the typical lateralization in the left cerebral hemisphere. In these cases, the neural distribution of other cognitive functions is not fully understood. Although there is a bias towards a mirrored brain organization consistent with the Causal hypothesis, some individuals are found to be exceptions to this rule. However, no study has focused on what happens to the homologous language areas in the right frontal inferior cortex. Using an fMRI-adapted stop-signal task in a healthy non right-handed sample (50 typically lateralized and 36 atypically lateralized for language production), our results show that atypical lateralization is associated with a mirrored brain organization of the inhibitory control network in the left hemisphere: inferior frontal cortex, presupplementary motor area, and subthalamic nucleus. However, the individual analyses revealed a large number of cases with a noteworthy overlap in the inferior frontal gyrus, which shared both inhibitory and language functions. Further analyses showed that atypical lateralization was associated with stronger functional interhemispheric connectivity and larger corpus callosum. Importantly, we did not find task performance differences as a function of lateralization, but there was an association between atypical dominance in the inferior frontal cortex and higher scores on schizotypy and autistic spectrum traits, as well as worse performance on a reading accuracy test. Together, these results partially support the Causal hypothesis of hemispheric specialization and provide further evidence of the link between atypical hemispheric lateralization and increased interhemispheric transfer through the corpus callosum.

Raising awareness of the important role of engineering in sustainable development.

STEAM (Science, Technology, Engineering, Arts and Mathematics) professions play a crucial role in transforming 21st-century society, as they contribute to developing new technologies that support the achievement of the Sustainable Development Goals (SDGs). Aligning engineering education with sustainable development requires raising awareness among students, fostering commitment among future generations of engineers, and promoting technical vocations. In this paper, an educational experience designed with these objectives is presented, in which more than 130 students from five undergraduate degrees in engineering and architecture at the Higher Polytechnic School of Zamora (HPSZ) of the University of Salamanca actively participated. To carry out the project, an online course was designed to train all participating students on general aspects of the 2030 Agenda, and research works were proposed in the ten involved degree subjects. The assessment of students' prior knowledge and learning regarding the 2030 Agenda was conducted through an objective multiple-choice pre-test and post-test. Additionally, their satisfaction with this educational experience was assessed through a questionnaire. The results revealed a considerable improvement in the students' knowledge of the general contents of sustainable development, especially after participating in classroom debate sessions. The initial objective test showed a low average score, indicating the lack of knowledge about the 2030 Agenda and the SDGs among engineering students. However, the final objective test revealed a significant improvement of 3 points out of 10. Regarding the research works, out of a total of 91 students, 53 papers addressing complex issues related to sustainable development and current engineering solutions were presented. This approach facilitated collaborative learning and the celebration of World Engineering Day at the HPSZ. The results of the satisfaction survey demonstrated that the experience was positive for both students and faculty Furthermore, its media impact was essential for increasing engineering vocations' visibility and social recognition.

A description of risk associated with use of antipsychotics among community dwelling older adults: A descriptive cross-sectional study.

The objective of this research was to analyze the risk of adverse effects in patients older than 65 years with dementia and in concomitant treatment with antidementia and antipsychotic drugs and who are cared for by community nurses. A retrospective cross-sectional descriptive study was carried out. A total of 332 patients who were cared for by primary care teams participated. Most of the patients were women, totally dependent for the basic activities of daily living and residing in the family home. They were polymedicated and there was poor therapeutic adherence. The risk of adverse effects was higher in polymedicated patients who had been taking antipsychotics for longer periods and in those who had a main caregiver. However, those patients who had been assessed by the community nurse were protected from suffering adverse effects. This study demonstrates how integrated and continuous nursing care can reduce adverse effects in this type of patient.

Kidney organoid models reveal cilium-autophagy metabolic axis as a therapeutic target for PKD both in vitro and in vivo.

Human pluripotent stem cell-derived kidney organoids offer unprecedented opportunities for studying polycystic kidney disease (PKD), which still has no effective cure. Here, we developed both in vitro and in vivo organoid models of PKD that manifested tubular injury and aberrant upregulation of renin-angiotensin aldosterone system. Single-cell analysis revealed that a myriad of metabolic changes occurred during cystogenesis, including defective autophagy. Experimental activation of autophagy via ATG5 overexpression or primary cilia ablation significantly inhibited cystogenesis in PKD kidney organoids. Employing the organoid xenograft model of PKD, which spontaneously developed tubular cysts, we demonstrate that minoxidil, a potent autophagy activator and an FDA-approved drug, effectively attenuated cyst formation in vivo. This in vivo organoid model of PKD will enhance our capability to discover novel disease mechanisms and validate candidate drugs for clinical translation.

Generative artificial intelligence empowers digital twins in drug discovery and clinical trials.

INTRODUCTION: The concept of Digital Twins (DTs) translated to drug development and clinical trials describes virtual representations of systems of various complexities, ranging from individual cells to entire humans, and enables in silico simulations and experiments. DTs increase the efficiency of drug discovery and development by digitalizing processes associated with high economic, ethical, or social burden. The impact is multifaceted: DT models sharpen disease understanding, support biomarker discovery and accelerate drug development, thus advancing precision medicine. One way to realize DTs is by generative artificial intelligence (AI), a cutting-edge technology that enables the creation of novel, realistic and complex data with desired properties. AREAS COVERED: The authors provide a brief introduction to generative AI and describe how it facilitates the modeling of DTs. In addition, they compare existing implementations of generative AI for DTs in drug discovery and clinical trials. Finally, they discuss technical and regulatory challenges that should be addressed before DTs can transform drug discovery and clinical trials. EXPERT OPINION: The current state of DTs in drug discovery and clinical trials does not exploit the entire power of generative AI yet and is limited to simulation of a small number of characteristics. Nonetheless, generative AI has the potential to transform the field by leveraging recent developments in deep learning and customizing models for the needs of scientists, physicians and patients.

Physico-Chemical comparison of four commercially available mineral trioxide aggregates / Comparación fisicoquímica de cuatro mineral trióxido agregados disponibles comercialmente

Abstract To compare the physicochemical composition of 4 MTAs commercially available in Latin America. ProRoot MTA (Dentsply, USA), MTA Angelus (Angelus, Brazil), MTA Flow (Ultradent, USA), and MTA Viarden (Viarden, Mexico) were physically and chemically compared. Scanning electron microscopy (SEM) images were obtained from the MTA powder and the prepared presentations. Energy Dispersive X-Ray Spectroscopy (EDS) analyses were performed by triplicate, to calculate the mass proportion of calcium (Ca), silicon (Si), the Ca/Si proportion among the 4 brands. Thermogravimetric analyses (TGA) were conducted (50ºC-1000ºC), and mass loss and inflection points were calculated for each material. Statistical differences for Ca and Si content were determined by ANOVA (p<0.05). SEM images showed evident differences in the appearance of both the powder and the prepared MTAs among brands. Angelus MTA showed cubic prisms not observed in the other 3 brands. ProRoot MTA and MTA Flow showed similar homogeneous structures. MTA Viarden was the less homogeneous, with random structures (>15um). When comparing the mass proportions of Ca and Si between the 4 powder samples, MTA Viarden showed a significantly lower proportions of both elements when compared with the other brands (p<0.005). TGA análisis showed a similar behavior for ProRoot MTA, MTA Angelus and MTA Flow, with less than 2% mass loss when the 1000C temperature was reached. MTA Viarden showed a mass loss of 9,94% before the 700C, indicating the presence of different content sensible to temperature degradation. The analyzed MTAs demonstrated to vary significantly in their chemical composition and physical characteristics. Clinicians must be aware of the differences between different brands of a same material, and future research should focus on the clinical implications of these differences.

Resumen Comparar la composición fisicoquímica de 4 MTA disponibles comercialmente en América Latina. Se compararon física y químicamente ProRoot MTA (Dentsply, EE. UU.), MTA Angelus (Angelus, Brasil), MTA Flow (Ultradent, EE. UU.) y MTA Viarden (Viarden, México). Se obtuvieron imágenes de microscopía electrónica de barrido (SEM) del polvo de MTA y de las presentaciones preparadas. Los análisis de espectroscopía de dispersión de energía de rayos X (EDS) se realizaron por triplicado para calcular la proporción de masa de calcio (Ca), silicio (Si), la proporción Ca/Si entre las 4 marcas. Se realizaron análisis termogravimétricos (TGA) (50ºC-1000ºC), y se calcularon las pérdidas de masa y los puntos de inflexión para cada material. Las diferencias estadísticas para el contenido de Ca y Si se determinaron mediante ANOVA (p<0,05). Los análisis SEM mostraron diferencias evidentes en la apariencia tanto del polvo como las preparaciones de los MTA, entre las diferentes marcas. MTA Angelus mostró prismas cúbicos no observados en las otras 3 marcas. ProRoot MTA y MTA Flow mostraron estructuras homogéneas similares. MTA Viarden fue el menos homogéneo, con estructuras aleatorias (>15um). Al comparar las proporciones de masa de Ca y Si entre las 4 muestras de polvo, MTA Viarden mostró proporciones significativamente más bajas de ambos elementos en comparación con las otras marcas (p<0,005). El análisis TGA mostró un comportamiento similar para ProRoot MTA, MTA Angelus y MTA Flow, con menos del 2 % de pérdida de masa al alcanzar los 1000 °C de temperatura. El MTA Viarden mostró una pérdida de masa de 9,94% antes de los 700 °C, indicando la presencia de diferentes contenidos sensibles a la degradación por temperatura. Los MTA analizados demostraron diferencias significativas en su composición química y características físicas. Los clínicos deben ser conscientes de las diferencias entre las diferentes marcas de un mismo material, y futuras investigaciones deben enfocarse en las implicaciones clínicas de estas diferencias.

Trastornos psicóticos en Paraguay: ¿existen diferencias significativas entre zonas urbanas y rurales? / Psychotic disorders in Paraguay: Are there any significant differences between urban and rural areas?

Actualmente existe una tendencia mundial de desplazamiento de la población rural hacia áreas cada vez más urbanizadas. Existe evidencia que informa que el desarrollo de las enfermedades mentales tiene relación importante con factores tanto internos (por ejemplo, genéticos) y externos (el ambiente, entre otros). Con respecto a esto último, la manera en la que el entorno afecta a la salud mental es un objeto de estudio de interés global y se ha reportado que las áreas urbanas presentan mayores tasas de trastornos mentales comunes en comparación con las rurales. En el caso de la psicosis, por más de que el factor genético sea el más demostrado (y estudiado en los últimos años), el factor ambiental representando por el ambiente urbano ya ha sido analizado por investigadores a inicios del siglo 20. Desde allí, a lo largo de los años se obtuvo evidencia repetida que lo respalda como un factor de riesgo. Se ha encontrado que, además, existe relación con el grado de exposición, lo que hace pensar que la causa no solamente se limita a la transición del área rural al área urbana, sino que están involucrados factores sociales, económicos y medioambientales más profundos como la disparidad social, inseguridad, contaminación, entre otros 1. Ya en las últimas décadas del siglo 20, investigadores informaron de un aumento de la incidencia de esquizofrenia de 1,65 en hombres que vivían ciudades sobre sus contrapartes de origen rural. Años después, otros estudios han reportado esta variación en la incidencia de primeros episodios psicóticos a través del gradiente social urbano-rural, así como una relación entre el aumento de hospitalización por esquizofrenia con el grado de urbanización.

Overview of the 8th Social Media Mining for Health Applications (#SMM4H) Shared Tasks at the AMIA 2023 Annual Symposium.

The aim of the Social Media Mining for Health Applications (#SMM4H) shared tasks is to take a community-driven approach to address the natural language processing and machine learning challenges inherent to utilizing social media data for health informatics. The eighth iteration of the #SMM4H shared tasks was hosted at the AMIA 2023 Annual Symposium and consisted of five tasks that represented various social media platforms (Twitter and Reddit), languages (English and Spanish), methods (binary classification, multi-class classification, extraction, and normalization), and topics (COVID-19, therapies, social anxiety disorder, and adverse drug events). In total, 29 teams registered, representing 18 countries. In this paper, we present the annotated corpora, a technical summary of the systems, and the performance results. In general, the top-performing systems used deep neural network architectures based on pre-trained transformer models. In particular, the top-performing systems for the classification tasks were based on single models that were pre-trained on social media corpora. To facilitate future work, the datasets-a total of 61,353 posts-will remain available by request, and the CodaLab sites will remain active for a post-evaluation phase.

Optimized vaccine candidate MVA-S(3P) fully protects against SARS-CoV-2 infection in hamsters.

The development of novel optimized vaccines against coronavirus disease 2019 (COVID-19) that are capable of controlling the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and the appearance of different variants of concern (VoC) is needed to fully prevent the transmission of the virus. In the present study, we describe the enhanced immunogenicity and efficacy elicited in hamsters by a modified vaccinia virus Ankara (MVA) vector expressing a full-length prefusion-stabilized SARS-CoV-2 spike (S) protein [termed MVA-S(3P)]. Hamsters vaccinated with one or two doses of MVA-S(3P) developed high titers of S-binding IgG antibodies and neutralizing antibodies against the ancestral Wuhan SARS-CoV-2 virus and VoC beta, gamma, and delta, as well as against omicron, although with a somewhat lower neutralization activity. After SARS-CoV-2 challenge, vaccinated hamsters did not lose body weight as compared to matched placebo (MVA-WT) controls. Consistently, vaccinated hamsters exhibited significantly reduced viral RNA in the lungs and nasal washes, and no infectious virus was detected in the lungs in comparison to controls. Furthermore, almost no lung histopathology was detected in MVA-S(3P)-vaccinated hamsters, which also showed significantly reduced levels of proinflammatory cytokines in the lungs compared to unvaccinated hamsters. These results reinforce the use of MVA-S(3P) as a vaccine candidate against COVID-19 in clinical trials.

Non-nosocomial Healthcare-Associated Infective Endocarditis: A Distinct Entity? Data From the GAMES Series (2008-2021).

Background: Patients who acquire infective endocarditis (IE) following contact with the healthcare system, but outside the hospital, are classified as having non-nosocomial healthcare-associated IE (HCIE). Our aim was to characterize HCIE and establish whether its etiology, diagnosis, and therapeutic approach suggest it should be considered a distinct entity. Methods: This study retrospectively analyzes data from a nationwide, multicenter, prospective cohort including consecutive cases of IE at 45 hospitals across Spain from 2008 to 2021. HCIE was defined as IE detected in patients in close contact with the healthcare system (eg, patients receiving intravenous treatment, hemodialysis, or institutionalized). The prevalence and main characteristics of HCIE were examined and compared with those of community-acquired IE (CIE) and nosocomial IE (NIE) and with literature data. Results: IE was diagnosed in 4520 cases, of which 2854 (63%) were classified as CIE, 1209 (27%) as NIE, and 457 (10%) as HCIE. Patients with HCIE showed a high burden of comorbidities, a high presence of intravascular catheters, and a predominant staphylococcal etiology, Staphylococcus aureus being identified as the most frequent causative agent (35%). They also experienced more persistent bacteremia, underwent fewer surgeries, and showed a higher mortality rate than those with CIE (32.4% vs 22.6%). However, mortality in this group was similar to that recorded for NIE (32.4% vs 34.9%, respectively, P = .40). Conclusions: Our data do not support considering HCIE as a distinct entity. HCIE affects a substantial number of patients, is associated with a high mortality, and shares many characteristics with NIE.

Design of a new mortality indicator in acute coronary syndrome on admission to the Intensive Care Unit.

OBJECTIVE: To design a mortality indicator in acute coronary syndrome (ACS) in the intensive care unit (ICU). DESIGN: A multicenter, observational descriptive study was carried out. PARTICIPANTS: Patients with ACS admitted to the ICUs included in the ARIAM-SEMICYUC registry between January 2013 and April 2019. INTERVENTIONS: None. MAIN VARIABLES OF INTEREST: Demographic parameters, time of access to the healthcare system, and clinical condition. Revascularization therapy, drugs and mortality were analyzed. Cox regression analysis was performed, followed by the design of a neural network. A receiver operating characteristic curve (ROC) was plotted to calculate the power of the new score. Lastly, the clinical utility or relevance of the ARIAM indicator (ARIAM's) was assessed using a Fagan test. RESULTS: A total of 17,258 patients were included in the study, with a mortality rate of 3.5% (n = 605) at discharge from the ICU. The variables showing statistical significance (P < .001) were entered into the supervised predictive model, an artificial neural network. The new ARIAM's yielded a mean of 0.0257 (95%CI: 0.0245-0.0267) in patients discharged from the ICU versus 0.27085 (95%CI: 0.2533-0.2886) in those who died (P < .001). The area under the ROC curve of the model was 0.918 (95%CI: 0.907-0.930). Based on the Fagan test, the ARIAM's showed the mortality risk to be 19% (95%CI: 18%-20%) when positive and 0.9% (95%CI: 0.8%-1.01%) when negative. CONCLUSIONS: A new mortality indicator for ACS in the ICU can be established that is more accurate and reproducible, and periodically updated.

Automatic Extraction of Medication Mentions from Tweets-Overview of the BioCreative VII Shared Task 3 Competition.

This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter user's publicly available tweets (the user's 'timeline'). In general, detecting health-related tweets is notoriously challenging for natural language processing tools. The main challenge, aside from the informality of the language used, is that people tweet about any and all topics, and most of their tweets are not related to health. Thus, finding those tweets in a user's timeline that mention specific health-related concepts such as medications requires addressing extreme imbalance. Task 3 called for detecting tweets in a user's timeline that mentions a medication name and, for each detected mention, extracting its span. The organizers made available a corpus consisting of 182 049 tweets publicly posted by 212 Twitter users with all medication mentions manually annotated. The corpus exhibits the natural distribution of positive tweets, with only 442 tweets (0.2%) mentioning a medication. This task was an opportunity for participants to evaluate methods that are robust to class imbalance beyond the simple lexical match. A total of 65 teams registered, and 16 teams submitted a system run. This study summarizes the corpus created by the organizers and the approaches taken by the participating teams for this challenge. The corpus is freely available at https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-3/. The methods and the results of the competing systems are analyzed with a focus on the approaches taken for learning from class-imbalanced data.

Two different brain networks underlying picture naming with familiar pre-existing native words and new vocabulary.

The present research used fMRI to longitudinally investigate the impact of learning new vocabulary on the activation pattern of the language control network by measuring BOLD signal changes during picture naming tasks with familiar pre-existing native words (old words) and new vocabulary. Nineteen healthy participants successfully learned new synonyms for already known Spanish words, and they performed a picture naming task using the old words and the new words immediately after learning and two weeks after learning. The results showed that naming with old words, compared to naming with newly learned words, produced activations in a cortical network involving frontal and parietal regions, whereas the opposite contrast showed activation in a broader cortical/subcortical network, including the SMA/ACC, the hippocampus, and the midbrain. These two networks are maintained two weeks after learning. These results suggest that the language control network can be separated into two functional circuits for diverse cognitive purposes.

BCG-activation of leukocytes is sufficient for the generation of donor-independent innate anti-tumor NK and γδ T-cells that can be further expanded in vitro.

Bacillus Calmette-Guérin (BCG), the nonpathogenic Mycobacterium bovis strain used as tuberculosis vaccine, has been successfully used as treatment for non-muscle invasive bladder cancer for decades, and suggested to potentiate cellular and humoral immune responses. However, the exact mechanism of action is not fully understood. We previously described that BCG mainly activated anti-tumor cytotoxic NK cells with upregulation of CD56 and a CD16+ phenotype. Now, we show that stimulation of human peripheral blood mononuclear cells with iBCG, a preparation based on BCG-Moreau, expands oligoclonal γδ T-cells, with a cytotoxic phenotype, together with anti-tumor CD56high CD16+ NK cells. We have used scRNA-seq, flow cytometry, and functional assays to characterize these BCG-activated γδ T-cells in detail. They had a high IFNγ secretion signature with expression of CD27+ and formed conjugates with bladder cancer cells. BCG-activated γδ T-cells proliferated strongly in response to minimal doses of cytokines and had anti-tumor functions, although not fully based on degranulation. BCG was sufficient to stimulate proliferation of γδ T-cells when cultured with other PBMC; however, BCG alone did not stimulate expansion of purified γδ T-cells. The characterization of these non-donor restricted lymphocyte populations, which can be expanded in vitro, could provide a new approach to prepare cell-based immunotherapy tools.

KHz-rate volumetric voltage imaging of the whole Zebrafish heart.

Fast volumetric imaging is essential for understanding the function of excitable tissues such as those found in the brain and heart. Measuring cardiac voltage transients in tissue volumes is challenging, especially at the high spatial and temporal resolutions needed to give insight to cardiac function. We introduce a new imaging modality based on simultaneous illumination of multiple planes in the tissue and parallel detection with multiple cameras, avoiding compromises inherent in any scanning approach. The system enables imaging of voltage transients in situ, allowing us, for the first time to our knowledge, to map voltage activity in the whole heart volume at KHz rates. The high spatiotemporal resolution of our method enabled the observation of novel dynamics of electrical propagation through the zebrafish atrioventricular canal.