Crise global da atenção primária à saúde / Global crisis in primary health care / Crisis global de la atención primaria

Enquanto no Norte Global se discute uma crise na Atenção Primária à Saúde, a maioria dos países nunca chegou a constituir sistemas de saúde baseados propriamente numa atenção primária robusta. Nesse cenário, o Brasil apresenta uma tendência mais favorável, com conquistas importantes para a atenção primária e a medicina de família e comunidade nos últimos dez anos. Restam desafios a serem superados para que o Sistema Único de Saúde alcance níveis satisfatórios de acesso a seus serviços, com profissionais adequadamente formados e valorizados pela população.

While the Global North is discussing a crisis in primary health care, the majority of countries have never managed to establish health systems based on robust primary care. Brazil presents a more favorable trend, with important achievements for primary care and family practice over the last ten years. There are still challenges to be overcome so that the Unified Health System achieves satisfactory levels of access to its services, with professionals who are properly trained and valued by the public.

Mientras que en el Norte Global se habla de una crisis de la atención primaria, la mayoría de los países nunca han creado realmente sistemas sanitarios basados en una atención primaria robusta. Brasil, muestra una tendencia más favorable, con importantes logros para la atención primaria y la medicina familiar y comunitaria en los últimos diez años. Aún quedan retos por superar para que el Sistema Único de Salud alcance niveles satisfactorios de acceso a sus servicios, con profesionales debidamente formados y valorados por la población.

Reimagining the ADR Alert Card: a novel approach to recurrence prevention in low-cost settings for adverse drug reactions.

OBJECTIVES: Adverse drug reactions (ADRs) are among the leading standalone causes of morbidity and hospitalisation and contribute substantially to an increase in healthcare expenditure. Repeat ADR events, although difficult to quantify, are a recognised problem that lead to preventable suffering for the patient. The current approaches for the prevention of ADR recurrence in low/middle-income countries range from inefficient to non-existent. There is very little literature that focuses on the preventability of ADRs in such settings. This study aimed to develop the ADR Alert Card, an economical innovation designed as a stop gap in preventing ADR recurrence, and to evaluate its utility by validating the system through input from medical professionals. METHODS: The ADR Alert Card was validated and registered with the Copyrights Office of the Government of India. To obtain the opinion of healthcare professionals and gauge the status quo in prevention of ADR recurrence, we conducted an online descriptive cross-sectional study over a period of 6 months. RESULTS: The survey received 218 responses. Demographics varied, ranging across different healthcare specialties and years of experience. Our study found that existing practice in ADR recurrence prevention was inadequate, and most healthcare workers were unaware of an alternative approach. Unique solutions were provided by the respondents, with the majority favouring a card format for preventing recurrence. CONCLUSIONS: After being introduced to the ADR Alert Card, there was an overwhelming consensus on the utility and practicality of this card in preventing ADR recurrence.

Using a Quality Management System and Risk-based Approach in Observational Studies to Obtain Robust Real-World Evidence.

The results of observational studies using real-world data, known as real-world evidence, have gradually started to be used in drug development and decision-making by policymakers. A good quality management system-a comprehensive system of process, data, and documentation to ensure quality-is important in obtaining real-world evidence. A risk-based approach is a common quality management system used in interventional studies. We used a quality management system and risk-based approach in an observational study on a designated intractable disease. Our multidisciplinary team assessed the risks of the real-world data study comprehensively and systematically. When using real-world data and evidence to support regulatory decisions, both the quality of the database and the validity of the outcome are important. We followed the seven steps of the risk-based approach for both database selection and research planning. We scored the risk of two candidate databases and chose the Japanese National Database of designated intractable diseases for this study. We also conducted a quantitative assessment of risks associated with research planning. After prioritizing the risks, we revised the research plan and outcomes to reflect the risk-based approach. We concluded that implementing a risk-based approach is feasible for an observational study using real-world data. Evaluating both database selection and research planning is important. A risk-based approach can be essential to obtain robust real-world evidence.

Flavored electronic nicotine delivery system product use among adults in New York State post-statewide restriction implementation.

In May 2020, New York State restricted the sale of flavored e-liquids, excluding tobacco flavor. We conducted a Web-based survey to assess support and changes in use behavior between July and October 2020 (n = 946), with a follow-up between April and June 2021 (n = 542). Most electronic nicotine delivery system (ENDS) users (n = 82/55) continued to use, with 39%/33% reporting continuing to purchase flavored e-liquids, 20%/32% reporting using tobacco flavor, 5%/6% reporting quitting ENDS and smoking cigarettes, and 8%/3% reporting quitting ENDS and not smoking cigarettes. In 2020, 65% of non-users, 53% of cigarette users, 34% of cigarette/ENDS users, and 18% of ENDS users supported this policy restriction on e-liquids. Similar results were observed in 2021. Many ENDS users continued purchasing flavored e-liquids, suggesting that compliance with the policy can be improved. Cigarette smoking did not appear to increase. Continued evaluation of how restrictions on sales of products influence use is critical to understanding the long-term impact on behavior.

Make It or Break It? Injury Impacts More Than Half of Deselected Athletes Who Dropped Out of the High-Performance Pathway System. A 4-Year Retrospective Cohort Study.

To investigate: (1) the injury epidemiology in an Australian academy; (2) how athletes transition through the high-performance sport (HPS) pathway; and (3) why athletes leave this HPS program. This retrospective cohort study was conducted at an Australian HPS academy over a 4-year period. Medical attention injuries were prospectively recorded. Injury incidence rates (IIR) and burden were calculated per 365 athlete-days, according to sport, sex, and pathway level. Athlete pathway levels were mapped to the Foundations, Talent, Elite, and Mastery (FTEM) framework. Reasons for athletes transitioning out were reported. Four hundred and eighty-one injuries were reported across 124 athletes at an IIR of 2.09 injuries per 365 athlete-days (95% CI = 1.91-2.29). Most athletes (103, 83.1%) were injured at least once over the 4-year period. IIRs increased (IRR = 1.17, 95% CI = 1.06-1.29, p = 0.001) as athletes progressed through the pathway. The most common reason for athlete attrition was deselection due to performance (n = 18), with 55.6% of these athletes sustaining an injury in the season prior to deselection. Injury burden was highest at E2 (119.5 days absence per 365 athlete-days (95% CI = 62.18-229.67)) and lowest at T4 (30.47 days absence per 365 athlete-days (95% CI = 21.98-42.24)). Injury occurrence is common across HPS, with IIRs increasing as athletes progressed to higher talent levels. Deselection due to poor performance was the main attrition factor, with more than half the deselected athletes impacted by injury prior to deselection. This study highlights an increased risk of deselection, following injury, and indicates the need for further development of prevention strategies targeting pathway athletes.

Development of Mixed Micelles for Enhancing Fenretinide Apparent Solubility and Anticancer Activity Against Neuroblastoma Cells.

INTRODUCTION/OBJECTIVES: The purpose of the study was to evaluate the suitability of mixed micelles prepared with D-α-tocopheryl polyethylene glycol succinate (TPGS) and 1,2- distearoyl-glycero-3-phosphoethanolamine-N-[methoxy(polyethyleneglycol)-2000] (DSPE-PEG) to encapsulate the poorly soluble anticancer drug fenretinide (4-HPR). METHODS: After assaying the solubilization ability of the surfactants by the equilibrium method, the micelles were prepared using the solvent casting technique starting from different 4-HPR:TPGS: DSPE-PEG w/w ratios. The resulting formulations were investigated for their stability under storage conditions and upon dilution, modelling the reaching of physiological concentrations after intravenous administration. The characterization of micelles included the determination of DL%, EE %, particle size distribution, Z-potential, and thermal analysis by DSC. The cytotoxicity studies were performed on HTLA-230 and SK-N-BE-2C neuroblastoma cells by the MTT essay. RESULTS: The colloidal dispersions showed a mean diameter of 12 nm, negative Zeta potential, and a narrow dimensional distribution. 4-HPR was formulated in the mixed micelles with an encapsulation efficiency of 88% and with an increment of the apparent solubility of 363-fold. The 4-HPR entrapment remained stable up to the surfactants' concentration of 2.97E-05 M. The loaded micelles exhibited a slow-release behaviour, with about 28% of the drug released after 24 h. On the most resistant SK-N-BE-2C cells, the encapsulated 4-HPR was significantly more active than free 4-HPR in reducing cell viability. CONCLUSION: Loaded micelles demonstrated their suitability as a new adjuvant tool potentially useful for the treatment of neuroblastoma.

Oral Patch/Film for Drug Delivery-Current Status and Future Prospects.

In recent years, there has been extensive research into drug delivery systems aimed at enhancing drug utilization while minimizing drug toxicities. Among these systems, oral patches/films have garnered significant attention due to their convenience, noninvasive administration, ability to bypass hepatic first-pass metabolism, thereby enhancing drug bioavailability, and their potential to ensure good compliance, particularly among special patient populations. In this review, from the perspective of the anatomical characteristics of the oral cavity and the advantages and difficulties of oral drug delivery, we illustrate the design ideas, manufacturing techniques, research methodologies, and the essential attributes of an ideal oral patch/film. Furthermore, the applications of oral patches/films in both localized and systemic drug delivery were discussed. Finally, we offer insights into the future prospects of the oral patch/film, aiming to provide valuable reference for the advancement of oral localized drug delivery systems.

[Early classification and recognition algorithm for sudden cardiac arrest based on limited electrocardiogram data trained with a two-stages convolutional neural network].

Sudden cardiac arrest (SCA) is a lethal cardiac arrhythmia that poses a serious threat to human life and health. However, clinical records of sudden cardiac death (SCD) electrocardiogram (ECG) data are extremely limited. This paper proposes an early prediction and classification algorithm for SCA based on deep transfer learning. With limited ECG data, it extracts heart rate variability features before the onset of SCA and utilizes a lightweight convolutional neural network model for pre-training and fine-tuning in two stages of deep transfer learning. This achieves early classification, recognition and prediction of high-risk ECG signals for SCA by neural network models. Based on 16 788 30-second heart rate feature segments from 20 SCA patients and 18 sinus rhythm patients in the international publicly available ECG database, the algorithm performance evaluation through ten-fold cross-validation shows that the average accuracy (Acc), sensitivity (Sen), and specificity (Spe) for predicting the onset of SCA in the 30 minutes prior to the event are 91.79%, 87.00%, and 96.63%, respectively. The average estimation accuracy for different patients reaches 96.58%. Compared to traditional machine learning algorithms reported in existing literatures, the method proposed in this paper helps address the requirement of large training datasets for deep learning models and enables early and accurate detection and identification of high-risk ECG signs before the onset of SCA.

Peanut hulls, an underutilized nutritious culinary ingredient: valorizing food waste for global food, health, and farm economies-a narrative review.

Peanut hulls (PHs) are an edible food waste that is an underutilized food source for human consumption. While edible and palatable, currently they are mainly diverted to livestock feed or building materials. Here, we describe existing literature supporting human food valorization of PHs, and propose methods to optimize recapturing nutrients (protein, fiber, phenols and other phytonutrients) lost by treating PHs as waste. Incorporated into common foods, PHs could be processed into functional ingredients to improve nutrient-density with anticipated corresponding positive health outcomes associated with increases in plant foods. Valorization of PHs addresses multiple priorities of the UN Sustainable Development Goals using a Food Systems Approach (FSA) including reducing food waste, increasing economic opportunities for farmers, and increasing the availability of healthy shelf-stable foodstuffs to address food security. Recent advances in sustainable food processing technologies can be utilized to safely incorporate PHs into human food streams. We propose future applications that could make meaningful impacts for food availability and the nutritional composition of common foods like bread and plant-based meat alternatives. While the limited literature on this topic spans several decades, no commercial operations currently exist to process PHs for human consumption, and most literature on the topic precedes the technological "green revolution." The approaches outlined in this review may help bolster commercialization of this underutilized and nutritious food potentially improving opportunities for multiple global stakeholders.

A Systems Biology Approach to the Pathogenesis of Celiac Disease: Identification of Potential Protective and Promoting Mechanisms.

Background: Celiac disease (CeD) is an autoimmune enteropathy triggered by dietary gluten. Almost 90% of CeD patients have HLA-DQ2 or -DQ8 haplotypes. As a high proportion of first-degree relatives (FDRs) of CeD patients have the same haplotype, it is assumed that they are at a higher risk of disease development than the general population. Nevertheless, the prevalence of CeD among FDRs is considerably low (7.5%). Materials and Methods: In order to figure out this discrepancy, a microarray dataset of intestinal mucosal biopsies of CeD patients, FDRs, and control groups was reanalyzed, and a protein-protein interaction network was constructed. Results: Principal component analysis showed that CeD and FDR groups are far away in terms of gene expression. Comparing differentially expressed genes of both networks demonstrated inverse expression of some genes mainly related to cell cycle mechanisms. Moreover, analysis of the modular structures of up- and downregulated gene networks determined activation of protein degradation mechanisms and inhibition of ribosome-related protein synthesis in celiac patients with an upside-down pattern in FDRs. Conclusions: The top-down systems biology approach determined some regulatory pathways with inverse function in CeD and FDR groups. These genes and molecular mechanisms could be a matter of investigation as potential druggable targets or prognostic markers in CeD.

The evolution of data treatment tools in single-particle and single-cell ICP-MS analytics.

Single-particle inductively coupled plasma-mass spectrometry (sp-ICP-MS) is one of the most powerful tools in the thriving field of nanomaterial analysis. Along the same lines, single-cell ICP-MS (sc-ICP-MS) has become an invaluable tool in the study of the variances of cell populations down to a per-cell basis. Their importance and application fields have been listed numerous times, across various reports and reviews. However, not enough attention has been paid to the immense and ongoing development of the tools that are currently available to the analytical community for the acquisition, and more importantly, the treatment of single-particle and single-cell-related data. Due to the ever-increasing demands of modern research, the efficient and dependable treatment of the data has become more important than ever. In addition, the field of single-particle and single-cell analysis suffers due to a large number of approaches for the generated data-with varying levels of specificity and applicability. As a result, finding the appropriate tool or approach, or even comparing results, can be challenging. This article will attempt to bridge these gaps, by covering the evolution and current state of the tools at the disposal of sp-ICP-MS users.

Assessing the suitability of a one-time sampling event for close-kin mark-recapture: A caribou case study.

Abundance estimation is frequently an objective of conservation and monitoring initiatives for threatened and other managed populations. While abundance estimation via capture-mark-recapture or spatially explicit capture-recapture is now common, such approaches are logistically challenging and expensive for species such as boreal caribou (Rangifer tarandus), which inhabit remote regions, are widely dispersed, and exist at low densities. Fortunately, the recently developed 'close-kin mark-recapture' (CKMR) framework, which uses the number of kin pairs obtained within a sample to generate an abundance estimate, eliminates the need for multiple sampling events. As a result, some caribou managers are interested in using this method to generate an abundance estimate from a single, non-invasive sampling event for caribou populations. We conducted a simulation study using realistic boreal caribou demographic rates and population sizes to assess how population size and the proportion of the population surveyed impact the accuracy and precision of single-survey CKMR-based abundance estimates. Our results indicated that abundance estimates were biased and highly imprecise when very small proportions of the population were sampled, regardless of the population size. However, the larger the population size, the smaller the required proportion of the population surveyed to generate both accurate and reasonably precise estimates. Additionally, we also present a case study in which we used the CKMR framework to generate annual female abundance estimates for a small caribou population in Jasper National Park, Alberta, Canada, from 2006 to 2015 and compared them to existing published capture-mark-recapture-based estimates. Both the accuracy and precision of the annual CKMR-based abundance estimates varied across years and were sensitive to the proportion of pairwise kinship comparisons which yielded a mother-offspring pair. Taken together, our study demonstrates that it is possible to generate CKMR-based abundance estimates from a single sampling event for small caribou populations, so long as a sufficient sampling intensity can be achieved.

Exploring chaos and ergodic behavior of an inductorless circuit driven by stochastic parameters.

There exist extensive studies on periodic and random perturbations of various smooth maps investigating their dynamics. Unlike smooth maps, non-smooth maps are yet to be studied extensively under a stochastic regime. This paper presents a stochastic piecewise-smooth map derived from a simple inductorless switching circuit. The stochasticity is introduced in parameter values. The distribution of the parameter values is bounded and randomly selected from uniform and triangular distributions and ranges between high and low bifurcation parameter values of the deterministic map. Due to this inherent stochasticity in parameter values, the time evolution of the state variable cannot be predicted at a specific time instant. We observe that the state variable exhibits completely ergodic behavior when the minimum value of the parameter is the same as the minimum bifurcation parameter of the deterministic system. However, the ensemble average of the state variable converges to a fixed value. The system demonstrates nonchaotic behavior for a particular range of parameter values but the deterministic map in that bifurcation range shows interplay between chaos and periodic orbits. The values of Lyapunov exponents decrease monotonically with increased asymmetry of the distribution from which the bifurcation parameter values are chosen. We determine the probability density function of the stochastic map and verify its invariance under initial conditions. The most noteworthy result is the disappearance of chaotic behavior when the lower range of the distribution is varied while maintaining a fixed upper threshold for a particular distribution, even though the deterministic map exhibits an array of periodic and chaotic behaviors within the range. As the period-incrementing cascade with chaotic inclusion only occurs in nonsmooth maps, this paper numerically shows the stochasticity of a piecewise-smooth map obtained from a practical system for the first time where randomness is introduced in the parameter space.

Weight management medications for chronic use in 37 veterans affairs medical centers-A medication use evaluation.

Rationale: Controlled trials have demonstrated successful weight loss associated with certain weight management medications (WMMs). However, there are limited real-world data on prescribing patterns and efficacy and safety profiles of WMMs in Veterans Affairs (VA) patients. Objective: To evaluate: utilization patterns of WMMs liraglutide, naltrexone/bupropion, orlistat, phentermine, phentermine/topiramate, and semaglutide; weight loss at three, six, twelve, and more than 12 months; safety; and treatment barriers. Methods: A retrospective, cross-sectional medication use evaluation (MUE) was conducted using electronic health records of outpatient Veterans newly initiated on WMMs at 37 VA Medical Centers between 1 March 2020 and 31 March 2022. Chart review was used to identify WMM utilization and capture rates of clinical response, defined as 5% and 10% or greater weight loss at the final weight, adverse drug events (ADEs), non-adherence, and discontinuations. Site-specific surveys evaluated local practices and barriers. Results: Among 1959 eligible Veterans, semaglutide, phentermine/topiramate, and orlistat were most frequently prescribed. The clinical response was highest among phentermine/topiramate, liraglutide, and semaglutide. Naltrexone/bupropion and phentermine demonstrated the highest and lowest ADE rates, respectively. Potential barriers to WMM utilization and successful treatment by site reports were drug shortages, patient perceptions of therapeutic course, personal preferences, and VA WMM use criteria. Conclusions: Smaller weight loss and higher discontinuation rates were observed relative to clinical trials. The MUE data allow for better assessment of benefits and risks for Veterans prescribed WMMs.

Advancing Pharmacy Practice: The Role of Intelligence-Driven Pharmacy Practice and the Emergence of Pharmacointelligence.

The field of healthcare is experiencing a significant transformation driven by technological advancements, scientific breakthroughs, and a focus on personalized patient care. At the forefront of this evolution is artificial intelligence-driven pharmacy practice (IDPP), which integrates data science and technology to enhance pharmacists' capabilities. This prospective article introduces the concept of "pharmacointelligence", a paradigm shift that synergizes artificial intelligence (AI), data integration, clinical decision support systems (CDSS), and pharmacy informatics to optimize medication-related processes. Through a comprehensive literature review and analysis, this research highlights the potential of pharmacointelligence to revolutionize pharmacy practice by addressing the complexity of pharmaceutical data, changing healthcare demands, and technological advancements. This article identifies the critical need for integrating these technologies to enhance medication management, improve patient outcomes, and streamline pharmacy operations. It also underscores the importance of regulatory and ethical considerations in implementing pharmacointelligence, ensuring patient privacy, data security, and equitable healthcare delivery.

Tobacco and Nicotine Products Adverse Health Events: Findings From the FDA Safety Reporting Portal.

Introduction: The FDA oversees regulatory aspects of all U.S. tobacco products. Understanding the impact of emerging health trends and incidents associated with various tobacco and nicotine products is vital for public health. This study utilizes the FDA's Tobacco Product Problem Reports (TPPRs) to characterize and track adverse health events (AHEs) associated with tobacco and nicotine products over time, considering the impact of EVALI and the COVID-19 pandemic. Methods: FDA TPPRs from 2017-2022 provided information on AHEs related to various tobacco products. After data cleaning, 839 reports were categorized by two independent coders based on affected health category, frequency of AHEs reports, and proportion of AHEs per each health category. Additionally, variations in AHEs over time were assessed, considering major health events like EVALI and the COVID-19 pandemic. Results: Among the 839 reports, electronic cigarettes (e-cigarettes) were the primary product of concern, comprising 90.6% (n = 760) of all reports, surpassing traditional cigarettes (5.1%; n = 43) and other products. Notably, 45.6% of reports (n = 383) identified the neurological system as the most frequently mentioned health category, each reporting at least one AHE. This was followed by the respiratory (39.1%; n = 328) and digestive (10.7%; n = 90) systems. Among all reported AHEs, respiratory system issues were most frequent (25.9%; n = 512), closely followed by neurological (25.2%; n = 499) and digestive (6.6%; n = 131) concerns. Most reports occurred in 2019 (65.7%; n = 551), coinciding with the EVALI outbreak, with a subsequent decline post-Q3 2019, highlighting the potential impact of specific health crises on reporting trends. Conclusion: E-cigarettes dominated adverse health reports, particularly affecting the neurological and respiratory systems, with a peak in 2019. Our findings provide insights to regulatory entities and future research, enhancing understanding of AHEs in lesser-explored bodily systems, such as the neurological and digestive systems. This study emphasizes the need for ongoing and improved surveillance of emerging tobacco products to protect public health.

A step forward in the diagnosis of urinary tract infections: from machine learning to clinical practice.

Objectives: Urinary tract infections (UTIs) are common infections within the Emergency Department (ED), causing increased laboratory workloads and unnecessary antibiotics prescriptions. The aim of this study was to improve UTI diagnostics in clinical practice by application of machine learning (ML) models for real-time UTI prediction. Methods: In a retrospective study, patient information and outcomes from Emergency Department patients, with positive and negative culture results, were used to design models - 'Random Forest' and 'Neural Network' - for the prediction of UTIs. The performance of these predictive models was validated in a cross-sectional study. In a quasi-experimental study, the impact of UTI risk assessment was investigated by evaluating changes in the behaviour of clinicians, measuring changes in antibiotic prescriptions and urine culture requests. Results: First, we trained and tested two different predictive models with 8692 cases. Second, we investigated the performance of the predictive models in clinical practice with 962 cases (Area under the curve was between 0.81 to 0.88). The best performance was the combination of both models. Finally, the assessment of the risk for UTIs was implemented into clinical practice and allowed for the reduction of unnecessary urine cultures and antibiotic prescriptions for patients with a low risk of UTI, as well as targeted diagnostics and treatment for patients with a high risk of UTI. Conclusion: The combination of modern urinalysis diagnostic technologies with digital health solutions can help to further improve UTI diagnostics with positive impact on laboratory workloads and antimicrobial stewardship.

Increasing flexibility in vulnerable power grids using electrochemical storage.

Developing a reliable power grid and investing in non-conventional renewable energy resources pose problems for low- and medium-income countries. Frequently, maintaining a robust power grid infrastructure can present challenges in terms of reliability, resilience, and flexibility. This article presents a methodology for improving power flexibility in susceptible power systems through the utilization of Battery Energy Storage Systems (BESS). The methodology entails the examination of power stability, operating conditions, and security criteria in order to identify suitable locations for storage allocation. A study was conducted utilizing the Electrical Transient and Analysis Program (ETAP®) software to simulate the Central American power transmission grid. The results of the study indicate that including storage systems to offer virtual inertia and backup during emergency situations is a recommended strategy for mitigating potential challenges. The study suggests that applying specific criteria for allocation and sizing at critical points in sensitive systems can enhance power transfer flexibility, eliminating potential constraints. The Central American electrical Power System, which faces power transfer limitations, is well-suited for BESS. In severe contingencies, such as when the system frequency drops to 58.75 Hz and power transfer between Mexico and Central America exceeds 300 MW with voltage levels below 0.97 pu, BESS can help mitigate these issues. The solution involves deploying BESS both centrally and distributively. Results show decreased instability, with power increases not exceeding 300 MW for more than 11 study cycles in all scenarios. The approach includes a BESS with an installed capacity of 1,060 MWh/160 MW and a virtual inertia of H=6s.

Silica 3D printed scaffolds as pH stimuli-responsive drug release platform.

Silica-based scaffolds are promising in Tissue Engineering by enabling personalized scaffolds, boosting exceptional bioactivity and osteogenic characteristics. Moreover, silica materials are highly tunable, allowing for controlled drug release to enhance tissue regeneration. In this study, we developed a 3D printable silica material with controlled mesoporosity, achieved through the sol-gel reaction of tetraethyl orthosilicate (TEOS) at mild temperatures with the addition of different calcium concentrations. The resultant silica inks exhibited high printability and shape fidelity, while maintaining bioactivity and biocompatibility. Notably, the increased mesopore size enhanced the incorporation and release of large molecules, using cytochrome C as a drug model. Due to the varying surface charge of silica depending on the pH, a pH-dependent control release was obtained between pH 2.5 and 7.5, with maximum release in acidic conditions. Therefore, silica with controlled mesoporosity could be 3D printed, acting as a pH stimuli responsive platform with therapeutic potential.

Shear induced remobilization of buried synthetic microfibers.

Microplastics are known to accumulate in sediment beds of aquatic environments where they can be buried. Once buried they can remobilize due to high energetic events, entering the water column again. Here, turbulence induced by an oscillating grid device was used to investigate the remobilization of microfibers (MF) buried into the sediment bed. Four different types of plastic fibers commonly used for several industrial applications (PET, PP, PA and LDPE) and two types of soils (cohesive and non-cohesive) were investigated. Particles were in depth characterized via 3D reconstruction to estimate important parameters like the Corey shape factor and the settling velocity. Experimental runs explored a wide range of shear stresses. Measurements were taken at different time steps (between 15 minutes and 240 minutes from the start of each run). The results have shown that the remobilization of MFs is directly proportional to the value of the shear rate and the duration of the disturbance. Also, buoyant MFs were found more prone to remobilize respect to the denser ones. Drawing from experimental observations of the key parameters affecting MF remobilization, a non-dimensional predictive model was developed. A comparison with previous studies was performed to validate the model in order to predict MF remobilization in aquatic environments.