Foliar-applied melatonin and titanium nanoparticles modulate cadmium (Cd) toxicity through minimizing Cd accumulation and optimizing physiological and biochemical properties in sage (Salvia officinalis L.).

Notwithstanding the fact that melatonin (MT) and titanium nanoparticles (Ti NPs) alone have been widely used recently to modulate cadmium (Cd) stress in plants, there is a gap in the comparative impacts of these materials on lowering Cd toxicity in sage plants. The objective of this study was to determine how foliar application of MT and Ti NPs affected the growth, Cd accumulation, photosynthesis, water content, lipid peroxidation, and essential oil (EO) quality and quantity of sage plants in Cd-contaminated soils. A factorial experiment was conducted using MT at 100 and 200 µM and Ti NPs at 50 and 100 mg L-1 topically, together with Cd toxicity at 10 and 20 mg Cd kg-1 soil. The results showed that Cd toxicity decreased plant growth and enhanced lipid peroxidation. The Cd stress at 20 mg kg-1 soil resulted in increases in Cd root (693%), Cd shoot (429%), electrolyte leakage (EL, 29%), malondialdehyde (MDA, 72%), shoot weight (31%), root weight (27%), chlorophyll (Chl) a + b (26%), relative water content (RWC, 23%), and EO yield (30%). The application of MT and Ti NPs controlled drought stress by reducing MDA and EL, enhancing plant weight, Chl, RWC, and EO production, and minimizing Cd accumulation in plant tissues. The predominant compounds in the EO were α-thujone, 1,8-cineole, ß-thujone, camphor, and α-humulene. MT and Ti NPs caused α-thujone to rise, whereas Cd stress caused it to fall. Based on heat map analysis, MDA was the trait that was most sensitive to treatments. In summary, the research emphasizes the possibility of MT and Ti NPs, particularly MT at 200 µM, to mitigate Cd toxicity in sage plants and enhance their biochemical reactions.

Breast segmentation in infrared thermography from characteristical inframammary shape.

Infrared thermography is gaining relevance in breast cancer assessment. For this purpose, breast segmentation in thermograms is an important task for performing automatic image analysis and detecting possible temperature changes that indicate the presence of malignancy. However, it is not a simple task since the breast limit borders, especially the top borders, often have low contrast, making it difficult to isolate the breast area. Several algorithms have been proposed for breast segmentation, but these highly depend on the contrast at the lower breast borders and on filtering algorithms to remove false edges. This work focuses on taking advantage of the distinctive inframammary shape to simplify the definition of the lower breast border, regardless of the contrast level, which indeed also provides a strong anatomical reference to support the definition of the poorly marked upper boundary of the breasts, which has been one of the major challenges in the literature. In order to demonstrate viability of the proposed technique for an automatic breast segmentation, we applied it to a database with 180 thermograms and compared their results with those reported by others in the literature. We found that our approach achieved a high performance, in terms of Intersection over Union of 0.934, even higher than that reported by artificial intelligence algorithms. The performance is invariant to breast sizes and thermal contrast of the images.

Multi-scale brain attributes contribute to the distribution of diffuse glioma subtypes.

Gliomas are primary brain tumors and are among the most malignant types. Adult-type diffuse gliomas can be classified based on their histological and molecular signatures as IDH-wildtype glioblastoma, IDH-mutant astrocytoma, and IDH-mutant and 1p/19q-codeleted oligodendroglioma. Recent studies have shown that each subtype of glioma has its own specific distribution pattern. However, the mechanisms underlying the specific distributions of glioma subtypes are not entirely clear despite partial explanations such as cell origin. To investigate the impact of multi-scale brain attributes on glioma distribution, we constructed cumulative frequency maps for diffuse glioma subtypes based on T1w structural images and evaluated the spatial correlation between tumor frequency and diverse brain attributes, including postmortem gene expression, functional connectivity metrics, cerebral perfusion, glucose metabolism, and neurotransmitter signaling. Regression models were constructed to evaluate the contribution of these factors to the anatomic distribution of different glioma subtypes. Our findings revealed that the three different subtypes of gliomas had distinct distribution patterns, showing spatial preferences toward different brain environmental attributes. Glioblastomas were especially likely to occur in regions enriched with synapse-related pathways and diverse neurotransmitter receptors. Astrocytomas and oligodendrogliomas preferentially occurred in areas enriched with genes associated with neutrophil-mediated immune responses. The functional network characteristics and neurotransmitter distribution also contributed to oligodendroglioma distribution. Our results suggest that different brain transcriptomic, neurotransmitter, and connectomic attributes are the factors that determine the specific distributions of glioma subtypes. These findings highlight the importance of bridging diverse scales of biological organization when studying neurological dysfunction.

Considerations for the development of iPSC-derived cell therapies: a review of key challenges by the JSRM-ISCT iPSC Committee.

Since their first production in 2007, human induced pluripotent stem cells (iPSCs) have provided a novel platform for the development of various cell therapies targeting a spectrum of diseases, ranging from rare genetic eye disorders to cancer treatment. However, several challenges must be tackled for iPSC-based cell therapy to enter the market and achieve broader global adoption. This white paper, authored by the Japanese Society for Regenerative Medicine (JSRM) - International Society for Cell Therapy (ISCT) iPSC Committee delves into the hurdles encountered in the pursuit of safe and economically viable iPSC-based therapies, particularly from the standpoint of the cell therapy industry. It discusses differences in global guidelines and regulatory frameworks, outlines a series of quality control tests required to ensure the safety of the cell therapy, and provides details and important considerations around cost of goods (COGs), including the impact of automated advanced manufacturing.

Exploring consumer responses to official endorsement: roles of credibility and attractiveness attributes in live streaming.

Introduction: Official endorsement, distinct from celebrity, expertise, and peer endorsement, introduces a new paradigm where local government officials use online platforms, particularly live streaming, to promote local products and brands. Methods: This study examines the influence of official endorsement on consumer responses using the source credibility and source attractiveness models. We developed a framework that considers official credibility and attractiveness attributes as antecedents, and consumer perceived security and enjoyment as mediators, affecting purchase intention and local brand awareness. The study also incorporates variables such as consumer region and power distance belief. Results: Data from 594 responses obtained through an online survey were analyzed using structural equation modeling. The results indicate that official credibility attributes (expertise, trustworthiness, government credibility) enhances consumer perceived security, while official attractiveness attributes (physical attractiveness, interaction friendliness, and similarity with consumers) increases consumer enjoyment. Both perceived security and enjoyment positively influence purchase intention and local brand awareness. These relationships are partially moderated by consumer region and power distance belief. Discussion: This research pioneers the study of official endorsements, expanding the endorsement literature. It also provides practical insights for marketing professionals and government officials on leveraging official endorsements to enhance the value of local products and brands..

Molecular expression, purification and structural characterization of recombinant L-Glutaminase from Streptomyces roseolus.

The present research reports the anti-cancer potential of recombinant L-Glutaminase from Streptomyces roseolus. L-Glutaminase gene was synthesized by codon-optimization, cloned and successfully expressed in E. coli BL21 (DE3). Affinity purified recombinant L-Glutaminase revealed a molecular mass of 32 kDa. Purified recombinant L-Glutaminase revealed stability at pH 7.0-8.0 with optimum activity at 70 °C further indicating its thermostable nature based on thermodynamic characterization. Recombinant L-Glutaminase exhibited profound stability in the presence of several biochemical parameters and demonstrated its metalloenzyme nature and was also found to be highly specific towards favorable substrate (l-Glutamine) based on kinetics. It demonstrated antioxidant property and pronounced cytotoxic effect against breast cancer (MCF-7 cell lines) in a dose dependent behavior with IC50 of 40.68 µg/mL. Matrix-assisted laser desorption ionization-time of flight-mass spectroscopy (MALDI-TOF-MS) analysis of desired mass peaks ascertained the recombinant L-Glutaminase identity. N-terminal amino acid sequence characterization through Edman degradation revealed highest resemblance for L-glutaminase within the Streptomyces sp. family. The purified protein was characterized structurally and functionally by employing spectroscopic methods like Raman, circular dichroism and nuclear magnetic resonance. The thermostability was assessed by thermogravimetric analysis. The outcomes of the study, suggests the promising application of recombinant L-Glutaminase as targeted therapeutic candidate for breast cancer.

Mitigation of drought stress in chili plants (Capsicum annuum L.) using mango fruit waste biochar, fulvic acid and cobalt.

Drought stress can have negative impacts on crop productivity. It triggers the accumulation of reactive oxygen species, which causes oxidative stress. Limited water and nutrient uptake under drought stress also decreases plant growth. Using cobalt and fulvic acid with biochar in such scenarios can effectively promote plant growth. Cobalt (Co) is a component of various enzymes and co-enzymes. It can increase the concentration of flavonoids, total phenols, antioxidant enzymes (peroxidase, catalase, and polyphenol oxidase) and proline. Fulvic acid (FA), a constituent of soil organic matter, increases the accessibility of nutrients to plants. Biochar (BC) can enhance soil moisture retention, nutrient uptake, and plant productivity during drought stress. That's why the current study explored the influence of Co, FA and BC on chili plants under drought stress. This study involved 8 treatments, i.e., control, 4 g/L fulvic acid (4FA), 20 mg/L cobalt sulfate (20CoSO4), 4FA + 20CoSO4, 0.50%MFWBC (0.50 MFWBC), 4FA + 0.50MFWBC, 20CoSO4 + 0.50MFWBC, 4FA + 20CoSO4 + 0.50MFWBC. Results showed that 4 g/L FA + 20CoSO4 with 0.50MFWBC caused an increase in chili plant height (23.29%), plant dry weight (28.85%), fruit length (20.17%), fruit girth (21.41%) and fruit yield (25.13%) compared to control. The effectiveness of 4 g/L FA + 20CoSO4 with 0.50MFWBC was also confirmed by a significant increase in total chlorophyll contents, as well as nitrogen (N), phosphorus (P), and potassium (K) in leaves over control. In conclusion4g/L, FA + 20CoSO4 with 0.50MFWBC can potentially improve the growth of chili cultivated in drought stress. It is suggested that 4 g/L FA + 20CoSO4 with 0.50MFWBC be used to alleviate drought stress in chili plants.

Contraceptive technology is failing to meet the needs of people in the U.S. because of under-investment in new methods.

This commentary considers if contraceptives currently available in the U.S. are meeting all current or potential user needs and presents the case for the funding of research to enhance contraceptive options. People experience high rates of contraceptive failure, unintended pregnancies, and a non-trivial proportion experience a high level of dissatisfaction with available contraceptive methods. Given increasing restrictions on abortion, additional options that better meet the needs of non-users or dissatisfied users rise in importance. Priorities for improvement include fewer side effects, affordability, and ease of use, all coupled with high effectiveness. Although available products are safe for most users, and those with risks can be identified by screening, additional methods that are safe without screening and address dissatisfactions and contraindications would be desirable. Addressing these gaps through typical market mechanisms is not happening. The level of interest and investment in contraceptive research and development (R&D) is very low in part because extensive use and the apparent diversity of contraceptive options may drive a mistaken perception that contraception is a "solved problem." Even with the incentive of a global contraceptive market of $25 billion annual U.S. contraceptive R&D expenditures in 2021 totaled only $149 million compared to total pharma R&D outlays of $250 billion. An increase in both the priority and funding of contraceptive R&D is needed. Annual outlays of ~$500 million to $1 billion would be needed to address the key challenges holding back the field.

Determining the number of attributes in the GDINA model.

Exploratory cognitive diagnosis models have been widely used in psychology, education and other fields. This paper focuses on determining the number of attributes in a widely used cognitive diagnosis model, the GDINA model. Under some conditions of cognitive diagnosis models, we prove that there exists a special structure for the covariance matrix of observed data. Due to the special structure of the covariance matrix, an estimator based on eigen-decomposition is proposed for the number of attributes for the GDINA model. The performance of the proposed estimator is verified by simulation studies. Finally, the proposed estimator is applied to two real data sets Examination for the Certificate of Proficiency in English (ECPE) and Big Five Personality (BFP).

Research on spatial carving method of glutenite reservoir based on opacity voxel imaging.

The glutenite reservoir in an exploration area in eastern China is well-developed and holds significant exploration potential as an important oil and gas alternative layer. However, due to the influence of sedimentary characteristics, the glutenite reservoir exhibits strong lateral heterogeneity, significant vertical thickness variations, and low accuracy in reservoir space characterization, which affects the reasonable and effective deployment of development wells. Seismic data contains the three-dimensional spatial characteristics of geological bodies, but how to design a suitable transfer function to extract the nonlinear relationship between seismic data and reservoirs is crucial. At present, the transfer functions are concentrated in low-dimensional or high-dimensional fixed mathematical models, which cannot accurately describe the nonlinear relationship between seismic data and complex reservoirs, resulting in low spatial description accuracy of complex reservoirs. In this regard, this paper first utilizes a fusion method based on probability kernel to fuse seismic attributes such as wave impedance, effective bandwidth, and composite envelope difference. This provide a more intuitive reflection of the distribution characteristics of glutenite reservoirs. Moreover, a hybrid nonlinear transfer function is established to transform the fused attribute cube into an opaque attribute cube. Finally, the illumination model and ray casting method are used to perform voxel imaging of the glutenite reservoirs, brighten the detailed characteristics of reservoir space, and then form a set of methods for ' brightening reservoirs and darkening non-reservoirs ', which improves the spatial engraving accuracy of glutenite reservoirs.

Patient Acceptability and Preferences for Solid Oral Dosage Form Drug Product Attributes: A Scoping Review.

Background: There is no consistent framework for patient-centric drug product design, despite the common understanding that drug product acceptability and preferences influence adherence and, therefore, drug product effectiveness. The aim of this review was to assess current understanding of patient acceptability and preferences for solid oral dosage form (SODF) drug product attributes, and the potential impact of these attributes on patient behaviors and outcomes. Patients and Methods: A scoping review was conducted. Embase, Ovid MEDLINE®, and PubMed® were searched for full-text articles published between January 2013 and May 2023. Following screening and assessment against predefined inclusion criteria, data were analyzed thematically. Results: Nineteen studies were included. Four overarching domains of drug product attributes were identified and summarized in a framework: appearance, swallowability, palatability, and handling. Each domain was informed by specific drug product attributes: texture, form, size, shape, color, marking, taste, mouthfeel, and smell. The most frequently studied domains were swallowability and appearance, while the most studied attributes were size, shape, and texture. Smell, marking, and mouthfeel were the least studied attributes. Texture intersected all domains, while form, shape, and size intersected appearance, swallowability, and handling. Swallowability and size appeared to be the key domain and attribute, respectively, to consider when designing drug products. Few studies explored the impact of drug product attributes on behaviors and outcomes. Conclusion: While existing studies of drug product attributes have focused on appearance and swallowability, this review highlighted the importance of two less well-understood domains-palatability and handling-in understanding patients' acceptability and preferences for SODF drug products. The framework provides a tool to facilitate patient-centric design of drug products, organizing and categorizing physical drug product attributes into four overarching domains (appearance, swallowability, palatability, and handling), encouraging researchers to comprehensively assess the impact of drug product attributes on patient acceptability, preferences, and outcomes.

Medicines come in a variety of types and forms. These include tablets and capsules. Factors, such as the size and shape of tablets, can affect how people take medicines. However, patients are rarely involved in designing the medicines that they take. In this study, researchers summarized 19 studies published between 2013 and 2023. They wanted to understand how different factors, like size and shape, affect patients' preferences, ability, and willingness to take medicines. Researchers focused on the "physical" aspects of medicines and found 4 common themes: 1) what they look like (appearance), 2) how easy they are to swallow (swallowability), 3) how they taste and feel in the mouth (palatability), and 4) how easy they are to handle (handling). Eight factors were also found: color, markings, shape, size, smell, taste, texture, and how a medicine feels in the mouth (mouthfeel). Most studies focused on what medicines look like and how easy they are to swallow. The factors that researchers mostly looked at were the size, shape, and texture of medicines. The design of medicines can impact patients of different ages, though there may be specific needs for certain groups of patients, including children, older adults, and people with certain diseases. Patient input should become a part of future medicines design to ensure their acceptability.

A novel scale for assessing the risk of low birthweight: Birthweight questionnaire.

BACKGROUND: The birthweight of a newborn is critical to their health, development, and well-being. Previous studies that used maternal characteristics to predict birthweight did not employ a harmonised scale to assess the risk of low birthweight (LBW). OBJECTIVE: The goal of this study was to develop a new instrument that uses items on a uniform scale to assess the risk of an LBW in a pregnant woman. METHODS: Item response theory was employed to evaluate a similar existing scale, and some weaknesses were identified. RESULTS: Based on the observed weaknesses of the existing scale, a new uniform scale was developed, which is a 3-point Likert scale consisting of seven items. CONCLUSION: The scale, termed birthweight questionnaire, is a valuable tool for collecting data that could assist in assessing the risk of an LBW at every stage of pregnancy.

Predicting Odor Sensory Attributes of Unidentified Chemicals in Water Using Fragmentation Mass Spectra with Machine Learning Models.

Knowing odor sensory attributes of odorants lies at the core of odor tracking when addressing waterborne odor issues. However, experimental determination covering tens of thousands of odorants in authentic water is not pragmatic due to the complexity of odorant identification and odor evaluation. In this study, we propose the first machine learning (ML) model to predict odor perception/threshold aiming at odorants in water, which can use either molecular structure or MS2 spectra as input features. We demonstrate that model performance using MS2 spectra is nearly as good as that using unequivocal structures, both with outstanding accuracy. We particularly show the model's robustness in predicting odor sensory attributes of unidentified chemicals by using the experimentally obtained MS2 spectra from nontarget analysis on authentic water samples. Interpreting the developed models, we identify the intricate interaction of functional groups as the predominant influence factor on odor sensory attributes. We also highlight the important roles of carbon chain length, molecular weight, etc., in the inherent olfactory mechanisms. These findings streamline the odor sensory attribute prediction and are crucial advancements toward credible tracking and efficient control of off-odors in water.

Importance of Terrain and Climate for Predicting Soil Organic Carbon Is Highly Variable across Local to Continental Scales.

Soil organic carbon (SOC) plays a vital role in global carbon cycling and sequestration, underpinning the need for a comprehensive understanding of its distribution and controls. This study explores the importance of various covariates on SOC spatial distribution at both local (up to 1.25 km) and continental (USA) scales using a deep learning approach. Our findings highlight the significant role of terrain attributes in predicting SOC concentration distribution with terrain, contributing approximately one-third of the overall prediction at the local scale. At the continental scale, climate is only 1.2 times more important than terrain in predicting SOC distribution, whereas at the local scale, the structural pattern of terrain is 14 and 2 times more important than climate and vegetation, respectively. We underscore that terrain attributes, while being integral to the SOC distribution at all scales, are stronger predictors at the local scale with explicit spatial arrangement information. While this observational study does not assess causal mechanisms, our analysis nonetheless presents a nuanced perspective about SOC spatial distribution, which suggests disparate predictors of SOC at local and continental scales. The insights gained from this study have implications for improved SOC mapping, decision support tools, and land management strategies, aiding in the development of effective carbon sequestration initiatives and enhancing climate mitigation efforts.

Post-traumatic Stress Disorder in Veterans: A Concept Analysis.

Post-traumatic stress disorder (PTSD) occurs when an individual experiences a traumatic event that exceeds the limits of psychological endurance. Many veterans experience PTSD. PTSD can negatively impact veterans' quality of life, functioning, life satisfaction, and overall well-being. It is important to analyze the concept of PTSD in the veteran population. This concept analysis aimed to investigate the defining attributes, a model case, antecedents, consequences, and empirical referents related to the concept of PTSD among veterans. Walker and Avant's method was used to guide this concept analysis of PTSD. The results showed that three attributes were determined from the analysis: intrusive memories of traumatic events, feelings of isolation and estrangement, and negative cognitions. PTSD is conceptualized as a collection of symptoms that arise from highly traumatic experiences. The military environment predisposes veterans to traumatic events that should be identified or acknowledged. A better understanding of the concept of PTSD can facilitate the development of effective interventions for the veteran population and enhance their mental health.

Dual Functionalization of Hyaluronan Dermal Fillers with Vitamin B3: Efficient Combination of Bio-Stimulation Properties with Hydrogel System Resilience Enhancement.

Hyaluronic acid (HA) hydrogels are commonly used for facial dermal filling and for alternative medical aesthetic purposes. High diversity exists in commercial formulations, notably for the optimization of finished product stability, functionality, and performance. Polyvalent ingredients such as calcium hydroxylapatite (CaHA) or vitamin B3 (niacinamide) are notably used as bio-stimulants to improve skin quality attributes at the administration site. The aim of the present study was to perform multi-parametric characterization of two novel cross-linked dermal filler formulas (HAR-1 "Instant Refine" and HAR-3 "Maxi Lift") for elucidation of the various functional impacts of vitamin B3 incorporation. Therefore, the HAR products were firstly comparatively characterized in terms of in vitro rheology, cohesivity, injectability, and resistance to chemical or enzymatic degradation (exposition to H2O2, AAPH, hyaluronidases, or xanthine oxidase). Then, the HAR products were assessed for cytocompatibility and in vitro bio-stimulation attributes in a primary dermal fibroblast model. The results showed enhanced resilience of the cohesive HAR hydrogels as compared to JUVÉDERM® VOLBELLA® and VOLUMA® reference products in a controlled degradation assay panel. Furthermore, significant induction of total collagen synthesis in primary dermal fibroblast cultures was recorded for HAR-1 and HAR-3, denoting intrinsic bio-stimulatory effects comparable or superior to those of the Radiesse® and Sculptra™ reference products. Original results of high translational relevance were generated herein using robust and orthogonal experimental methodologies (hydrogel degradation, functional benchmarking) and study designs. Overall, the reported results confirmed the dual functionalization role of vitamin B3 in cross-linked HA dermal fillers, with a significant enhancement of hydrogel system stability attributes and the deployment of potent bio-stimulatory capacities.

Sensory characterisation of meatless and nitrite-free cooked ham alternatives in comparison to conventional counterparts: Temporal dominance of sensations and partial napping with ultra-flash profiling.

The cooked ham market is expanding with nitrite-free and meatless alternatives gaining traction as leading trends. An understanding of the attributes that influence the sensory quality of cooked ham is crucial for developing healthier and environmentally sustainable products. The primary aim of this study was to investigate how the removal of nitrites and the use of meatless ingredients affect the sensory characteristics of cooked ham currently available in the Irish market. Sensory evaluation of selected cooked hams (n = 8), including alternatives without nitrites or based on mycoprotein (meatless), was conducted using Temporal Dominance of Sensations (TDS) for in mouth processing and Partial Napping (PN) with Ultra-Flash Profiling (UFP) for the appearance, by a trained sensory panel (n = 9). The nitrite-free cooked ham displayed a similar temporal sensory profile and appearance to the products of the same category, highlighting the opportunity for more nitrite-free products to enter the market. The meatless product was dominated by a "smoky" flavour, which was perceived as "artificial". Meatless ham had a more distinct appearance than the meat-based products and was associated with attributes such as "fake", "artificial colour" and "unappealing". In general, results revealed distinct differences between whole-muscle and sectioned and formed cooked ham products in terms of texture, flavour, and appearance. PN and UFP grouped whole-muscle cooked hams together, which were associated with terms "natural-looking", "better quality" and "healthier", while sectioned and formed cooked hams were perceived as "cheap" and "artificial". The results of this study contribute to a better understanding of the sensory attributes of cooked ham products emphasising the challenges related to novel formulations, and offers valuable insights for the development of healthier and more sustainable meat products within the food industry.

Mechanistic understanding of the improved drying characteristics and quality attributes of lily (Lilium lancifolium Thunb.) by modified microstructure after pulsed electric field (PEF) pretreatment.

The effects of the non-thermal (pulsed electric field, PEF) and thermal pretreatment (vacuum steam pulsed blanching, VSPB) on the drying kinetics, quality attributes, and multi-dimensional microstructure of lily scales were investigated. The results indicate that both PEF and VSPB pretreatments improved the drying rate compared to untreated lily scales. Specifically, PEF pretreatment reduced the drying time by 29.58 % - 43.60 %, while VSPB achieved a 46.91 % reduction in drying time. PEF treatment facilitated the enhanced leaching of phenols and flavonoids compared to VSPB treated samples, thereby increasing antioxidant activity. The rehydration ratio of the dried lilies was improved with PEF and VSPB treatment, which closely related to the microstructure. Weibull distribution and Page model demonstrated excellent fit for the drying and rehydration kinetics of lily scales, respectively (R2 > 0.993). The analysis of multi-dimensional microstructure and ultrastructure confirmed the variations in moisture migration and phytochemical contents among different treatments. Consequently, this study offers insights into the technological support for the potential of non-thermal pretreatment in fruits and vegetables.

Identification and Characterization of Critical Processing Parameters in the Fabrication of Double-Emulsion Poly(lactic-co-glycolic) Acid Microparticles.

In the past several decades, polymeric microparticles (MPs) have emerged as viable solutions to address the limitations of standard pharmaceuticals and their corresponding delivery methods. While there are many preclinical studies that utilize polymeric MPs as a delivery vehicle, there are limited FDA-approved products. One potential barrier to the clinical translation of these technologies is a lack of understanding with regard to the manufacturing process, hindering batch scale-up. To address this knowledge gap, we sought to first identify critical processing parameters in the manufacturing process of blank (no therapeutic drug) and protein-loaded double-emulsion poly(lactic-co-glycolic) acid MPs through a quality by design approach. We then utilized the design of experiments as a tool to systematically investigate the impact of these parameters on critical quality attributes (e.g., size, surface morphology, release kinetics, inner occlusion size, etc.) of blank and protein-loaded MPs. Our results elucidate that some of the most significant CPPs impacting many CQAs of double-emulsion MPs are those within the primary or single-emulsion process (e.g., inner aqueous phase volume, solvent volume, etc.) and their interactions. Furthermore, our results indicate that microparticle internal structure (e.g., inner occlusion size, interconnectivity, etc.) can heavily influence protein release kinetics from double-emulsion MPs, suggesting it is a crucial CQA to understand. Altogether, this study identifies several important considerations in the manufacturing and characterization of double-emulsion MPs, potentially enhancing their translation.

Towards in vitro - In vivo correlation models for in situ forming drug implants.

In vitro-In vivo correlation (IVIVC) is a main focus of the pharmaceutical industry, academia and the regulatory sectors, as this is an effective modelling tool to predict drug product in vivo performance based on in vitro release data and serve as a surrogate for bioequivalence studies, significantly reducing the need for clinical studies. Till now, IVIVCs have not been successfully developed for in situ forming implants due to the significantly different in vitro and in vivo drug release profiles that are typically achieved for these dosage forms. This is not unexpected considering the unique complexity of the drug release mechanisms of these products. Using risperidone in situ forming implants as a model, the current work focuses on: 1) identification of critical attributes of in vitro release testing methods that may contribute to differences in in vitro and in vivo drug release from in situ forming implants; and 2) optimization of the in vitro release method, with the aim of developing Level A IVIVCs for risperidone implants. Dissolution methods based on a novel Teflon shape controlling adapter along with a water non-dissolvable glass fiber membrane (GF/F) instead of a water dissolvable PVA film (named as GF/F-Teflon adapter and PVA-Teflon adapter, respectively), and an in-house fabricated Glass slide adapter were used to investigate the impact of: the surface-to-volume ratio, water uptake ratio, phase separation rate (measured by NMP release in 24 h post injection in vitro or in vivo), and mechanical pressure on the drug release patterns. The surface-to-volume ratio and water uptake were shown to be more critical in vitro release testing method attributes compared to the phase separation rate and mechanical pressure. The Glass slide adapter-based dissolution method, which allowed for the formation of depots with bio-mimicking surface-to-volume ratios and sufficient water uptake, has the ability to generate bio-relevant degradation profiles as well as in vitro release profiles for risperidone implants. For the first time, a Level A IVIVC (rabbit model) has been successfully developed for in situ forming implants. Release data for implant formulations with slightly different PLGA molecular weights (MWs) were used to develop the IVIVC. The predictability of the model passed external validation using the reference listed drug (RLD), Perseris®. IVIVC could not be developed when formulations with different PLGA molar ratios of lactic acid to glycolic acid (L/G) were included. The present work provides a comprehensive understanding of the impact of the testing method attributes on drug release from in situ forming implants, which is a valuable practice for level A IVIVC development.