DLK1/DIO3 locus upregulation by a ß-catenin-dependent enhancer drives cell proliferation and liver tumorigenesis.

The CTNNB1 gene, encoding ß-catenin, is frequently mutated in hepatocellular carcinoma (HCC, ∼30%) and in hepatoblastoma (HB, >80%), in which DLK1/DIO3 locus induction is correlated with CTNNB1 mutations. Here, we aim to decipher how sustained ß-catenin activation regulates DLK1/DIO3 locus expression and the role this locus plays in HB and HCC development in mouse models deleted for Apc (ApcΔhep) or Ctnnb1-exon 3 (ß-cateninΔExon3) and in human CTNNB1-mutated hepatic cancer cells. We identified an enhancer site bound by TCF-4/ß-catenin complexes in an open conformation upon sustained ß-catenin activation (DLK1-Wnt responsive element [WRE]) and increasing DLK1/DIO3 locus transcription in ß-catenin-mutated human HB and mouse models. DLK1-WRE editing by CRISPR-Cas9 approach impaired DLK1/DIO3 locus expression and slowed tumor growth in subcutaneous CTNNB1-mutated tumor cell grafts, ApcΔhep HB and ß-cateninΔExon3 HCC. Tumor growth inhibition resulted either from increased FADD expression and subsequent caspase-3 cleavage in the first case or from decreased expression of cell cycle actors regulated by FoxM1 in the others. Therefore, the DLK1/DIO3 locus is an essential determinant of FoxM1-dependent cell proliferation during ß-catenin-driven liver tumorigenesis. Targeting the DLK1-WRE enhancer to silence the DLK1/DIO3 locus might thus represent an interesting therapeutic strategy to restrict tumor growth in primary liver cancers with CTNNB1 mutations.

Tonic dopamine and biases in value learning linked through a biologically inspired reinforcement learning model.

A hallmark of various psychiatric disorders is biased future predictions. Here we examined the mechanisms for biased value learning using reinforcement learning models incorporating recent findings on synaptic plasticity and opponent circuit mechanisms in the basal ganglia. We show that variations in tonic dopamine can alter the balance between learning from positive and negative reward prediction errors, leading to biased value predictions. This bias arises from the sigmoidal shapes of the dose-occupancy curves and distinct affinities of D1- and D2-type dopamine receptors: changes in tonic dopamine differentially alters the slope of the dose-occupancy curves of these receptors, thus sensitivities, at baseline dopamine concentrations. We show that this mechanism can explain biased value learning in both mice and humans and may also contribute to symptoms observed in psychiatric disorders. Our model provides a foundation for understanding the basal ganglia circuit and underscores the significance of tonic dopamine in modulating learning processes.

Pharmacological Modulation of the Ca2+/cAMP/Adenosine Signaling in Cardiac Cells as a New Cardioprotective Strategy to Reduce Severe Arrhythmias in Myocardial Infarction.

Acute myocardial infarction (AMI) is the main cause of morbidity and mortality worldwide and is characterized by severe and fatal arrhythmias induced by cardiac ischemia/reperfusion (CIR). However, the molecular mechanisms involved in these arrhythmias are still little understood. To investigate the cardioprotective role of the cardiac Ca2+/cAMP/adenosine signaling pathway in AMI, L-type Ca2+ channels (LTCC) were blocked with either nifedipine (NIF) or verapamil (VER), with or without A1-adenosine (ADO), receptors (A1R), antagonist (DPCPX), or cAMP efflux blocker probenecid (PROB), and the incidence of ventricular arrhythmias (VA), atrioventricular block (AVB), and lethality (LET) induced by CIR in rats was evaluated. VA, AVB and LET incidences were evaluated by ECG analysis and compared between control (CIR group) and intravenously treated 5 min before CIR with NIF 1, 10, and 30 mg/kg and VER 1 mg/kg in the presence or absence of PROB 100 mg/kg or DPCPX 100 µg/kg. The serum levels of cardiac injury biomarkers total creatine kinase (CK) and CK-MB were quantified. Both NIF and VER treatment were able to attenuate cardiac arrhythmias caused by CIR; however, these antiarrhythmic effects were abolished by pretreatment with PROB and DPCPX. The total serum CK and CK-MB were similar in all groups. These results indicate that the pharmacological modulation of Ca2+/cAMP/ADO in cardiac cells by means of attenuation of Ca2+ influx via LTCC and the activation of A1R by endogenous ADO could be a promising therapeutic strategy to reduce the incidence of severe and fatal arrhythmias caused by AMI in humans.

Antifungal activity of Co(II) and Cu(II) complexes containing 1,3-bis(benzotriazol-1-yl)-propan-2-ol on the growth and virulence traits of fluconazole-resistant Candida species: synthesis, DFT calculations, and biological activity.

Relevant virulence traits in Candida spp. are associated with dimorphic change and biofilm formation, which became an important target to reduce antifungal resistance. In this work, Co(II) complexes containing a benzotriazole derivative ligand showed a promising capacity of reducing these virulence traits. These complexes exhibited higher antifungal activities than the free ligands against all the Candida albicans and non-albicans strains tested, where compounds 2 and 4 showed minimum inhibitory concentration values between 15.62 and 125 µg mL-1. Moreover, four complexes (2-5) of Co(II) and Cu(II) with benzotriazole ligand were synthesized. These compounds were obtained as air-stable solids and characterized by melting point, thermogravimetric analysis, infrared, Raman and ultraviolet/visible spectroscopy. The analysis of the characterization data allowed us to identify that all the complexes had 1:1 (M:L) stoichiometries. Additionally, Density Functional Theory calculations were carried out for 2 and 3 to propose a probable geometry of both compounds. The conformer Da of 2 was the most stable conformer according to the Energy Decomposition Analysis; while the conformers of 3 have a fluxional behavior in this analysis that did not allow us to determine the most probable conformer. These results provide an important platform for the design of new compounds with antifungal activities and the capacity to attack other target of relevance to reduce antimicrobial resistance.

Quantitative Imaging of the Action of vCPP2319, an Antimicrobial Peptide from a Viral Scaffold, against Staphylococcus aureus Biofilms of a Clinical Isolate.

The formation of biofilms is a common virulence factor that makes bacterial infections difficult to treat and a major human health problem. Biofilms are bacterial communities embedded in a self-produced matrix of extracellular polymeric substances (EPS). In this work, we show that vCPP2319, a polycationic peptide derived from the capsid protein of Torque teno douroucouli virus, is active against preformed Staphylococcus aureus biofilms produced by both a reference strain and a clinical strain isolated from a diabetic foot infection, mainly by the killing of biofilm-embedded bacteria. The direct effect of vCPP2319 on bacterial cells was imaged using atomic force and confocal laser scanning microscopy, showing that the peptide induces morphological changes in bacterial cells and membrane disruption. Importantly, vCPP2319 exhibits low toxicity toward human cells and high stability in human serum. Since vCPP2319 has a limited effect on the biofilm EPS matrix itself, we explored a combined effect with α-amylase (EC 3.2.1.1), an EPS matrix-degrading enzyme. In fact, α-amylase decreases the density of S. aureus biofilms by 2.5-fold. Nonetheless, quantitative analysis of bioimaging data shows that vCPP2319 partially restores biofilm compactness after digestion of the polysaccharides, probably due to electrostatic cross-bridging of the matrix nucleic acids, which explains why α-amylase fails to improve the antibacterial action of the peptide.

Emergence of belief-like representations through reinforcement learning.

To behave adaptively, animals must learn to predict future reward, or value. To do this, animals are thought to learn reward predictions using reinforcement learning. However, in contrast to classical models, animals must learn to estimate value using only incomplete state information. Previous work suggests that animals estimate value in partially observable tasks by first forming "beliefs"-optimal Bayesian estimates of the hidden states in the task. Although this is one way to solve the problem of partial observability, it is not the only way, nor is it the most computationally scalable solution in complex, real-world environments. Here we show that a recurrent neural network (RNN) can learn to estimate value directly from observations, generating reward prediction errors that resemble those observed experimentally, without any explicit objective of estimating beliefs. We integrate statistical, functional, and dynamical systems perspectives on beliefs to show that the RNN's learned representation encodes belief information, but only when the RNN's capacity is sufficiently large. These results illustrate how animals can estimate value in tasks without explicitly estimating beliefs, yielding a representation useful for systems with limited capacity.

The ribonuclease PNPase is a key regulator of biofilm formation in Listeria monocytogenes and affects invasion of host cells.

Biofilms provide an environment that protects microorganisms from external stresses such as nutrient deprivation, antibiotic treatments, and immune defences, thereby creating favorable conditions for bacterial survival and pathogenesis. Here we show that the RNA-binding protein and ribonuclease polynucleotide phosphorylase (PNPase) is a positive regulator of biofilm formation in the human pathogen Listeria monocytogenes, a major responsible for food contamination in food-processing environments. The PNPase mutant strain produces less biofilm biomass and exhibits an altered biofilm morphology that is more susceptible to antibiotic treatment. Through biochemical assays and microscopical analysis, we demonstrate that PNPase is a previously unrecognized regulator of the composition of the biofilm extracellular matrix, greatly affecting the levels of proteins, extracellular DNA, and sugars. Noteworthy, we have adapted the use of the fluorescent complex ruthenium red-phenanthroline for the detection of polysaccharides in Listeria biofilms. Transcriptomic analysis of wild-type and PNPase mutant biofilms reveals that PNPase impacts many regulatory pathways associated with biofilm formation, particularly by affecting the expression of genes involved in the metabolism of carbohydrates (e.g., lmo0096 and lmo0783, encoding PTS components), of amino acids (e.g., lmo1984 and lmo2006, encoding biosynthetic enzymes) and in the Agr quorum sensing-like system (lmo0048-49). Moreover, we show that PNPase affects mRNA levels of the master regulator of virulence PrfA and PrfA-regulated genes, and these results could help to explain the reduced bacterial internalization in human cells of the ΔpnpA mutant. Overall, this work demonstrates that PNPase is an important post-transcriptional regulator for virulence and adaptation to the biofilm lifestyle of Gram-positive bacteria and highlights the expanding role of ribonucleases as critical players in pathogenicity.

Extracellular Vesicles and Infection: From Hijacked Machinery to Therapeutic Tools.

Extracellular vesicles (EVs) comprise a broad range of secreted cell-derived membrane vesicles. Beyond their more well-characterized role in cell communication, in recent years, EVs have also been shown to play important roles during infection. Viruses can hijack the biogenesis of exosomes (which are small EVs) to promote viral spreading. Additionally, these exosomes are also important mediators in inflammation and immune responses during both bacterial and viral infections. This review summarizes these mechanisms while also describing the impact of bacterial EVs in regulating immune responses. Finally, the review also focuses on the potential and challenges of using EVs, in particular, to tackle infectious diseases.

Acetate modulates the inhibitory effect of Lactobacillus gasseri against the pathogenic yeasts Candida albicans and Candida glabrata.

The exploration of the interference prompted by commensal bacteria over fungal pathogens is an interesting alternative to develop new therapies. In this work we scrutinized how the presence of the poorly studied vaginal species Lactobacillus gasseri affects relevant pathophysiological traits of Candida albicans and Candida glabrata. L. gasseri was found to form mixed biofilms with C. albicans and C. glabrata resulting in pronounced death of the yeast cells, while bacterial viability was not affected. Reduced viability of the two yeasts was also observed upon co-cultivation with L. gasseri under planktonic conditions. Either in planktonic cultures or in biofilms, the anti-Candida effect of L. gasseri was augmented by acetate in a concentration-dependent manner. During planktonic co-cultivation the two Candida species counteracted the acidification prompted by L. gasseri thus impacting the balance between dissociated and undissociated organic acids. This feature couldn't be phenocopied in single-cultures of L. gasseri resulting in a broth enriched in acetic acid, while in the co-culture the non-toxic acetate prevailed. Altogether the results herein described advance the design of new anti-Candida therapies based on probiotics, in particular, those based on vaginal lactobacilli species, helping to reduce the significant burden that infections caused by Candida have today in human health.

Emergence of belief-like representations through reinforcement learning.

To behave adaptively, animals must learn to predict future reward, or value. To do this, animals are thought to learn reward predictions using reinforcement learning. However, in contrast to classical models, animals must learn to estimate value using only incomplete state information. Previous work suggests that animals estimate value in partially observable tasks by first forming "beliefs"-optimal Bayesian estimates of the hidden states in the task. Although this is one way to solve the problem of partial observability, it is not the only way, nor is it the most computationally scalable solution in complex, real-world environments. Here we show that a recurrent neural network (RNN) can learn to estimate value directly from observations, generating reward prediction errors that resemble those observed experimentally, without any explicit objective of estimating beliefs. We integrate statistical, functional, and dynamical systems perspectives on beliefs to show that the RNN's learned representation encodes belief information, but only when the RNN's capacity is sufficiently large. These results illustrate how animals can estimate value in tasks without explicitly estimating beliefs, yielding a representation useful for systems with limited capacity. Author Summary: Natural environments are full of uncertainty. For example, just because my fridge had food in it yesterday does not mean it will have food today. Despite such uncertainty, animals can estimate which states and actions are the most valuable. Previous work suggests that animals estimate value using a brain area called the basal ganglia, using a process resembling a reinforcement learning algorithm called TD learning. However, traditional reinforcement learning algorithms cannot accurately estimate value in environments with state uncertainty (e.g., when my fridge's contents are unknown). One way around this problem is if agents form "beliefs," a probabilistic estimate of how likely each state is, given any observations so far. However, estimating beliefs is a demanding process that may not be possible for animals in more complex environments. Here we show that an artificial recurrent neural network (RNN) trained with TD learning can estimate value from observations, without explicitly estimating beliefs. The trained RNN's error signals resembled the neural activity of dopamine neurons measured during the same task. Importantly, the RNN's activity resembled beliefs, but only when the RNN had enough capacity. This work illustrates how animals could estimate value in uncertain environments without needing to first form beliefs, which may be useful in environments where computing the true beliefs is too costly.

A Glimpse into Dendrimers Integration in Cancer Imaging and Theranostics.

Cancer is a result of abnormal cell proliferation. This pathology is a serious health problem since it is a leading cause of death worldwide. Current anti-cancer therapies rely on surgery, radiation, and chemotherapy. However, these treatments still present major associated problems, namely the absence of specificity. Thus, it is urgent to develop novel therapeutic strategies. Nanoparticles, particularly dendrimers, have been paving their way to the front line of cancer treatment, mostly for drug and gene delivery, diagnosis, and disease monitoring. This is mainly derived from their high versatility, which results from their ability to undergo distinct surface functionalization, leading to improved performance. In recent years, the anticancer and antimetastatic capacities of dendrimers have been discovered, opening new frontiers to dendrimer-based chemotherapeutics. In the present review, we summarize the intrinsic anticancer activity of different dendrimers as well as their use as nanocarriers in cancer diagnostics and treatment.

Exploring the potential of eco-friendly silver nanoparticles to inhibit azole-resistant clinical isolates of Candida spp.

The antimicrobial activity and biological efficiency of silver nanoparticles (AgNps) have been widely described and can be modeled through stabilizing and reducing agents, especially if they exhibit biocidal properties, which can enhance bioactivity against pathogens. The selective action of AgNps remains a major concern. In this regard, the use of plant extracts for the green synthesis of nanoparticles offers advantages because it improves the toxicity of Nps for microorganisms and is harmless to normal cells. However, biological evaluations of the activity of AgNps synthesized using different reducing agents are determined independently, and comparisons are frequently overlooked. Thus, we investigated and compared the antifungal and cytotoxic effects of two ecological AgNps synthesized from Moringa oleifera aqueous leaf extract (AgNp-M) and glucose (AgNp-G) against azole-resistant clinical isolates of Candida spp. and nontumor mammalian cells. Synthesized AgNps exhibited an antifungal effect on planktonic cells of drug-resistant C. albicans and C. tropicalis (MIC 0.21-52.6 µg/mL). The toxicity was influenced by size. However, the use of M. oleifera extracts allows us to obtain AgNps that are highly selective and nongenotoxic to Vero cells due to modifications of the shape and surface. Therefore, these results suggest that AgNp-M has antimicrobial potential and deserves further investigation for biomedical applications.

Spontaneous behaviour is structured by reinforcement without explicit reward.

Spontaneous animal behaviour is built from action modules that are concatenated by the brain into sequences1,2. However, the neural mechanisms that guide the composition of naturalistic, self-motivated behaviour remain unknown. Here we show that dopamine systematically fluctuates in the dorsolateral striatum (DLS) as mice spontaneously express sub-second behavioural modules, despite the absence of task structure, sensory cues or exogenous reward. Photometric recordings and calibrated closed-loop optogenetic manipulations during open field behaviour demonstrate that DLS dopamine fluctuations increase sequence variation over seconds, reinforce the use of associated behavioural modules over minutes, and modulate the vigour with which modules are expressed, without directly influencing movement initiation or moment-to-moment kinematics. Although the reinforcing effects of optogenetic DLS dopamine manipulations vary across behavioural modules and individual mice, these differences are well predicted by observed variation in the relationships between endogenous dopamine and module use. Consistent with the possibility that DLS dopamine fluctuations act as a teaching signal, mice build sequences during exploration as if to maximize dopamine. Together, these findings suggest a model in which the same circuits and computations that govern action choices in structured tasks have a key role in sculpting the content of unconstrained, high-dimensional, spontaneous behaviour.

The role of RNA regulators, quorum sensing and c-di-GMP in bacterial biofilm formation.

Biofilms provide an ecological advantage against many environmental stressors, such as pH and temperature, making it the most common life-cycle stage for many bacteria. These protective characteristics make eradication of bacterial biofilms challenging. This is especially true in the health sector where biofilm formation on hospital or patient equipment, such as respirators, or catheters, can quickly become a source of anti-microbial resistant strains. Biofilms are complex structures encased in a self-produced polymeric matrix containing numerous components such as polysaccharides, proteins, signalling molecules, extracellular DNA and extracellular RNA. Biofilm formation is tightly controlled by several regulators, including quorum sensing (QS), cyclic diguanylate (c-di-GMP) and small non-coding RNAs (sRNAs). These three regulators in particular are fundamental in all stages of biofilm formation; in addition, their pathways overlap, and the significance of their role is strain-dependent. Currently, ribonucleases are also of interest for their potential role as biofilm regulators, and their relationships with QS, c-di-GMP and sRNAs have been investigated. This review article will focus on these four biofilm regulators (ribonucleases, QS, c-di-GMP and sRNAs) and the relationships between them.

Efeitos de intervenções lúdicas digitais em pacientes oncológicos na pandemia da covid-19: estudo quase-experimental / Efectos de las intervenciones digitales en pacientes oncológicos en la pandemia de covid-19: estudio cuasi-experimental / Effects of digital playful interventions in patients with cancer during the covid-19 pandemic: a quasi-experimental study

RESUMO Objetivo: avaliar o efeito de intervenções lúdicas digitais na qualidade de vida, depressão, ansiedade, estresse e apoio social em pacientes oncológicosna pandemia da Covid-19. Método: estudo quase-experimental, com 15 pacientes de uma organização não governamental brasileira, de agosto de 2020 a outubro de 2021.As intervenções digitais consistiram emcontar histórias, jogos, culinária, expressão artística e corporal. Foram utilizados: questionário sociodemográfico e clínico,questionário de qualidade de vida,escalas de depressão, ansiedade e estresseeapoio social, todos validados em versão brasileira. Os participantesforam avaliados nos tempos: pré-,pós-intervenção1 (após 4 meses) e pós-intervenção2 (após 10 meses).A análise inferencial verificou diferenças entre os tempos utilizando modelos lineares generalizados e testes não paramétricos de Friedman e Nemenyi, considerando-se p≤0,05. Resultados: a percepção da qualidade de vida melhorouna função emocional pós-intervenção2 em relação ao tempo pré-intervenção,com significância estatística (p=0,0020); depressão (p= 0,0106), ansiedade (p=0,0002), estresse (p=0,0032) e apoio emocional, interação social positiva (p<0,0001)melhoraram com significância estatística pós-intervenção1 e pós-intervenção2relacionadas ao tempo pré-intervenção. Conclusão: as intervenções contribuíram para melhorar a qualidade de vida emocional, depressão, ansiedade, estresse, apoio emocional einteração social positiva em pacientes oncológicosna pandemia, podendo ser estimuladasentre esta população.

RESUMEN Objetivo: evaluar el efecto de intervenciones lúdicas digitales en la calidad de vida, depresión, ansiedad, estrés y apoyo social en pacientes oncológicos en la pandemia de Covid-19. Método: estudio cuasi-experimental, con 15 pacientes de una organización no gubernamental brasileña, de agosto de 2020 a octubre de 2021. Las intervenciones digitales consistieron en contar historias, juegos, culinaria, expresión artística y corporal. Fueron utilizados: cuestionario sociodemográfico y clínico, cuestionario de calidad de vida, escalas de depresión, ansiedad y estrés y apoyo social, todos validados en versión brasileña. Los participantes fueron evaluados en los tiempos: pre, posintervención1 (tras 4 meses) y posintervención2 (tras 10 meses). El análisis inferencial encontró diferencias entre los tiempos, utilizando modelos lineales generalizados y prueba no paramétricas de Friedman y Nemenyi, considerándose p≤0,05. Resultados: la percepción de la calidad de vida mejoró en la función emocional posintervención2 en relación al tiempo preintervención, con significación estadística (p=0,0020); depresión (p=0,0106), ansiedad (p=0,0002), estrés (p=0,0032) y apoyo emocional, interacción social positiva (p<0,0001) mejoraron con significación estadística posintervención1 y posintervención2 relacionadas al tiempo preintervención. Conclusión: las intervenciones contribuyeron a mejorar la calidad de vida emocional, depresión, ansiedad, estrés, apoyo emocional e interacción social positiva en pacientes oncológicos en la pandemia, pudiendo ser fomentadas entre esta población.

ABSTRACT Objective: to assess the effect of digital playful interventions on quality of life, depression, anxiety, stress and social support in patients with cancer during the COVID-19 pandemic. Method: a quasi-experimental study, with 15 patients from a Brazilian non-governmental organization, from August 2020 to October 2021.Digital interventions consisted of storytelling, games, cooking, artistic and body expression. Sociodemographic and clinical questionnaire, quality of life questionnaire, depression, anxiety and stress scales and social support were used, all validated in the Brazilian version. Participants were assessed pre-intervention, post-intervention 1 (after 4 months) and post-intervention 2 (after 10 months).Inferential analysis verified differences between times using generalized linear models and Friedman and Nemenyi non-parametric tests, considering p≤0.05. Results: improved perceived quality of life in post-intervention 2 emotional function compared to pre-intervention time, with statistical significance (p=0.0020).Depression (p=0.0106), anxiety (p=0.0002), stress (p=0.0032) and emotional support, positive social interaction (p<0.0001) improved with statistical significance post-intervention 1 and post-intervention 2 related to pre-intervention time. Conclusion: the interventions contributed to improving emotional quality of life, depression, anxiety, stress, emotional support and positive social interaction in patients with cancer during the pandemic, and can be encouraged among this population.

Xeno-Free Integrated Platform for Robust Production of Cardiomyocyte Sheets from hiPSCs.

Human induced pluripotent stem cells (hiPSCs) can be efficiently differentiated into cardiomyocytes (CMs), which can be used for cardiac disease modeling, for drug screening, and to regenerate damaged myocardium. Implementation of xeno-free culture systems is essential to fully explore the potential of these cells. However, differentiation using xeno-free adhesion matrices often results in low CM yields and lack of functional CM sheets, capable of enduring additional maturation stages. Here, we established a xeno-free CM differentiation platform using TeSR/Synthemax, including a replating step and integrated with two versatile purification/enrichment metabolic approaches. Results showed that the replating step was essential to reestablish a fully integrated, closely-knit CM sheet. In addition, replating contributed to increase the cTnT expression from 65% to 75% and the output from 2.2 to 3.1 CM per hiPSC, comparable with the efficiency observed when using TeSR/Matrigel. In addition, supplementation with PluriSin1 and Glu-Lac+ medium allowed increasing the CM content over 80% without compromising CM sheet integrity or functionality. Thus, this xeno-free differentiation platform is a reliable and robust method to produce hiPSC-derived CMs, increasing the possibility of using these cells safely for a wide range of applications.

Cost-Effective Mechanical Aggregation of Cardiac Progenitors and Encapsulation in Matrigel Support Self-Organization in a Dynamic Culture Environment.

Human iPSC-derived self-organized cardiac tissues can be valuable for the development of platforms for disease modeling and drug screening, enhancing test accuracy and reducing pharmaceutical industry financial burden. However, current differentiation systems still rely on static culture conditions and specialized commercial microwells for aggregation, which hinders the full potential of hiPSC-derived cardiac tissues. Herein, we integrate cost-effective and reproducible manual aggregation of hiPSC-derived cardiac progenitors with Matrigel encapsulation and a dynamic culture to support hiPSC cardiac differentiation and self-organization. Manual aggregation at day 7 of cardiac differentiation resulted in 97% of beating aggregates with 78% of cTnT-positive cells. Matrigel encapsulation conjugated with a dynamic culture promoted cell migration and the creation of organized structures, with observed cell polarization and the creation of lumens. In addition, encapsulation increased buoyancy and decreased coalescence of the hiPSC-derived cardiac aggregates. Moreover, VEGF supplementation increased over two-fold the percentage of CD31-positive cells resulting in the emergence of microvessel-like structures. Thus, this study shows that the explored culture parameters support the self-organization of hiPSC-derived cardiac microtissues containing multiple cardiac cell types. Additional stimuli (e.g., BMP) in long-term scalable and fully automatized cultures can further potentiate highly structured and mature hiPSC-derived cardiac models, contributing to the development of reliable platforms for high-throughput drug screening and disease modeling.

A designed cyclic analogue of gomesin has potent activity against Staphylococcus aureus biofilms.

BACKGROUND: Infections caused by bacterial biofilms are very difficult to treat. The use of currently approved antibiotics even at high dosages often fails, making the treatment of these infections very challenging. Novel antimicrobial agents that use distinct mechanisms of action are urgently needed. OBJECTIVES: To explore the use of [G1K,K8R]cGm, a designed cyclic analogue of the antimicrobial peptide gomesin, as an alternative approach to treat biofilm infections. METHODS: We studied the activity of [G1K,K8R]cGm against biofilms of Staphylococcus aureus, a pathogen associated with several biofilm-related infections. A combination of atomic force and real-time confocal laser scanning microscopies was used to study the mechanism of action of the peptide. RESULTS: The peptide demonstrated potent activity against 24 h-preformed biofilms through a concentration-dependent ability to kill biofilm-embedded cells. Mechanistic studies showed that [G1K,K8R]cGm causes morphological changes on bacterial cells and permeabilizes their membranes across the biofilm with a half-time of 65 min. We also tested an analogue of [G1K,K8R]cGm without disulphide bonds, and a linear unfolded analogue, and found both to be inactive. CONCLUSIONS: The results suggest that the 3D structure of [G1K,K8R]cGm and its stabilization by disulphide bonds are essential for its antibacterial and antibiofilm activities. Moreover, our findings support the potential application of this stable cyclic antimicrobial peptide to fight bacterial biofilms.

Optically traceable PLGA-silica nanoparticles for cell-triggered doxorubicin delivery.

Fluorescent silica nanoparticles with a polymer shell of poly (D, L-lactide-co-glycolide) (PLGA) can provide traceable cell-triggered delivery of the anticancer drug doxorubicin (DOX), protecting the cargo while in transit and releasing it only intracellularly. PLGA with 50:50 lactide:glycolide ratio was grown by surface-initiated ring-opening polymerization (ROP) from silica nanoparticles of ca. 50 nm diameter, doped with a perylenediimide (PDI) fluorescent dye anchored to the silica structure. After loading DOX, release from the core-shell particles was evaluated in solution at physiological pH (7.4), and in human breast cancer cells (MCF-7) after internalization. The hybrid silica-PLGA nanoparticles can accommodate a large cargo of DOX, and the release in solution (PBS) due to PLGA hydrolysis is negligible for at least 72 h. However, once internalized in MCF-7 cells, the nanoparticles release the DOX cargo by degradation of the PLGA. Accumulation of DOX in the nucleus causes cell apoptosis, with the drug-loaded nanoparticles found to be as potent as free DOX. Our fluorescently traceable hybrid silica-PLGA nanoparticles with cell-triggered cargo release offer excellent prospects for the controlled delivery of anticancer drugs, protecting the cargo while in transit and efficiently releasing the drug once inside the cell.

Core-shell polycationic polyurea pharmadendrimers: new-generation of sustainable broad-spectrum antibiotics and antifungals.

The efficacy of conventional antimicrobials is falling to critical levels and raising alarming concerns around the globe. In this scenery, engineered nanoparticles emerged as a solid strategy to fight growing deadly infections. Here, we show the in vitro and in vivo performance of pharmadendrimers, a novel class of engineered polyurea dendrimers that are synthetic mimics of antibacterial peptides, against a collection of both Gram-positive and Gram-negative bacteria and fungi. These nanobiomaterials are stable solids prepared by low-cost and green processes, display a dense positively charged core-shell, and are biocompatible and hemocompatible drugs. Mechanistic data, corroborated by coarse-grained molecular dynamics simulations, points towards a fast-killing mechanism via membrane disruption, triggered by electrostatic interactions. Altogether this study provides strong evidence and support for the future use of polyurea pharmadendrimers in antibacterial and antifungal nanotherapeutics.