From R&D to production: Scale-out of continuous spin-freeze-drying for a PEGylated peptide formulation.

Scalable purification platforms have been developed for adeno-associated virus (AAV) processing to support large-scale vector manufacturing. The ability of column chromatography to recover packaged vectors and remove empty capsids has been well-established, but knowledge gaps remain for understanding process parameter impacts on impurity retention. In this work, we examine the impacts of two key process parameters-the harvest method and affinity resin selection-on residual host cell protein (HCP) retention. Sequential window acquisition of all theoretical fragment ion mass spectra (SWATH-MS) proteomics is applied to comprehensively profile residual HCPs in affinity chromatography (AC) elution pools from four AAV serotypes (AAV2, -5, -8, and -9) produced by suspension HEK293 cells. Vectors were purified from cell culture lysates and from supernatants using POROS™ CaptureSelect™ AAVX (AAVX) and one additional serotype-specific affinity resin-Capto™ AVB (AVB), POROS CaptureSelect AAV8 (PAAV8), or POROS CaptureSelect AAV9 (PAAV9). Significant divergence in residual HCP profiles was observed with the use of different affinity resins, with AVB and PAAV9 showing reduced residual HCP content in elution pools compared with AAVX and PAAV8. Processing of null culture lysates with fresh resins and resins with digested single-domain antibody fragments (sdAbs) shows that differences in resin performance are driven by variable nonspecific sdAb association with cellular impurities. Proteomic analysis of vector preparations from lysates compared with supernatants demonstrates product quality advantages of designing a media-only harvest process, specifically for AAV8, which was measured to contain an average of 66% of total vector genome content in the cell culture media. This work highlights the importance of serotype-specific tailoring of AAV downstream process design for improved product quality attributes to support clinical manufacture and small-scale analytics workflows.

Mutation in BrCLF resulted in leaf curling phenotype in Chinese cabbage.

Metabolic engineering of microbial pathways for 5-aminolevulinic acid biosynthesis: Recent advances and biotechnological applications.

This study investigates pricing dynamics in illicit cocaine and heroin markets across 17 European countries over the period 2002-2022. Using a panel dataset constructed from United Nations drug market data, we analyse wholesale and retail price trends and compute dealer margins to examine how economic pressures shape the structure of illegal drug distribution. Employing correlation analysis and Dumitrescu-Hurlin panel Granger causality tests, we explore the dynamic interrelationships among wholesale prices, retail prices and margins. The results reveal strong negative correlations between wholesale prices and margins for both substances, suggesting that increases in upstream costs are not fully passed through to retail prices, leading to margin compression. In contrast, retail prices are strongly positively associated with margins, indicating that margin variation is more closely linked to downstream pricing dynamics. Retail and wholesale prices are only weakly correlated, pointing to a partial decoupling between upstream and downstream price formation. The findings also indicate the presence of predictive relationships between wholesale prices and margins, particularly in the cocaine market, consistent with feedback mechanisms within the supply chain. These patterns may reflect a combination of factors, including incomplete cost pass-through, market structure, enforcement pressures and potential changes in product quality. However, in the absence of direct purity data, such interpretations should be made with caution. Overall, the analysis provides new evidence on the temporal dynamics of pricing in illicit drug markets and highlights the potential value of price and margin indicators as indirect signals of changing market conditions relevant to public health and policy.

Decoding skatole: A comprehensive review on biosynthesis, metabolism, and mitigation in livestock production.

Cold atmospheric plasma (CAP) and light-based technologies, including ultraviolet (UV), pulsed light, and visible light, are increasingly investigated as nonthermal interventions for food safety due to their broad-spectrum antimicrobial activity and minimal impact on product quality. However, when applied individually, both approaches are constrained by limited penetration depth, matrix-dependent efficacy, and reduced effectiveness against resistant microbial structures such as biofilms and spores. Accumulating evidence indicates that integrating CAP with light-based treatments can produce synergistic effects that exceed additive outcomes, resulting in enhanced microbial inactivation and accelerated degradation of recalcitrant chemical contaminants at reduced treatment intensities. This review critically synthesizes current literature on CAP-light integration, with a focus on the mechanistic basis of synergy, including CAP-induced barrier weakening, suppression of cellular repair and antioxidant systems, and photolytic amplification of CAP-generated reactive species. The efficacy of combined treatments across diverse microorganisms, food matrices, and processing environments is evaluated, alongside implications for food safety. However, quality assessments and long-term stability studies following combined CAP-light treatments remain scarce and warrant systematic investigation. Overall, CAP-light integration represents a promising multihurdle strategy for next-generation nonthermal food safety applications, though industrial adoption will require addressing scalability challenges, regulatory approval pathways, and cost-effectiveness relative to conventional sanitation technologies.

Physicochemical quality detection of wheat during hot air drying based on hyperspectral imaging combined with machine learning.

Developer Experience (Dev-X) has emerged as a critical driver of software quality, developer productivity, and project success. However, the empirical literature remains fragmented, with limited understanding of how specific Dev-X interventions affect downstream software and business outcomes. This study aims to synthesize and map the current empirical evidence on Dev-X interventions, identifying how they influence software outcomes (e.g., code readability, collaboration) and propagate to organizational key performance indicators (KPIs) such as product quality and process efficiency. We conducted a systematic mapping study of 160 empirical articles published between 2006 and 2024. We identified 146 unique interventions that impacts software outcomes such as role match may impact on developers’ workload, likewise managing burnout in developer feedback may impact organizational culture. Using grounded coding, we also classified such mappings to 8 KPIs and 5 Dev-X dimensions based on the strength of empirical relationships (correlational, causal, classification-based) reported in the literature. Our analysis reveal that quality-related KPIs are more frequently impacted than productivity metrics, challenging traditional emphasis. Emotional state and values-oriented interventions dominate current practices, while cognitive load and motivation-focused strategies remain underexplored. Only a minority of studies (39 out of 160) explicitly trace full chains of intervention–outcome–KPI, highlighting persistent fragmentation; in other cases, we reconstructed these chains using cross-sectional synthesis of study data. Notably, recent years show an emergence of AI-assisted and value-centered intervention designs. This study consolidates the fragmented Dev-X landscape by offering an evidence-based, open-access Ready-Reckoner tool for navigating interventions and their effects. While not prescriptive, it enables structured, context-aware exploration of empirical findings and lays the foundation for future causal, longitudinal, and multi-channel Dev-X research. • We systematically map 160 empirical studies to trace how Developer Experience (Dev-X) interventions influence software outcomes and business-critical KPIs. • The study identifies 146 unique interventions and categorizes them by their targeted Dev-X facets, intermediate outcomes, and relationship strength (causal, correlational, qualitative). • Our results highlight a gap in empirical traceability between Dev-X practices and long-term organizational success, emphasizing the need for integrated evaluation frameworks. • The study identifies underexplored connections across Dev-X dimensions and advocates for research into their combined influence on developer performance and project outcomes. • We deliver an open-access, practitioner-oriented Dev-X Ready-Reckoner Tool that supports evidence-based selection of interventions aligned with organizational goals.

Engineering the subcutaneous delivery of antibody-drug conjugates.

The global prevalence of iron (Fe) deficiency anemia (IDA) continues to pose major public health challenges, necessitating the development of effective fortification strategies. Dairy-based systems are promising vehicles for Fe fortification and delivery due to their widespread consumption and nutritional value, although their complex matrix presents significant challenges for maintaining Fe bioavailability and product quality. This review critically evaluates current knowledge on Fe fortification in dairy systems, integrating evidence on Fe forms, physicochemical interactions between Fe and the matrix, and their consequent effects on Fe bioavailability and physical functionality. Emerging fortification strategies are highlighted. Conventional Fe salts, including ferrous sulfate, ferrous fumarate, and ferric pyrophosphate, have varying degrees of solubility and absorption but are often associated with adverse sensory changes, lipid oxidation, and reduced product stability. Fe-ligand complexes, including protein-, carbohydrate-, and Maillard reaction product (MRP)-based systems, can impart improved stability to the fortified product and bioavailability by minimizing interactions with inhibitors of Fe absorption. The incorporation of Fe into dairy matrices influences product pH and structural and functional properties while also accelerating lipid oxidation and sensory deterioration when inorganic salts are used. Strategies such as Fe chelation, microencapsulation, and co-fortification with enhancers have shown potential to mitigate these limitations. In addition, the role of prebiotics, probiotics, and MRPs in modulating Fe absorption remains complex and context dependent. Despite promising advancements, gaps remain in understanding interactions between Fe, proteins, carbohydrates and MRP and their implications for Fe fortification of dairy systems. Future research should focus on developing integrated fortification approaches enabling the design of next-generation functional dairy foods to effectively combat global Fe deficiency.

People who use anabolic-androgenic steroids (AAS) face health risks from illicit markets and limited tailored harm reduction services. This study aimed to examine whether laboratory testing results from submitted AAS products (ie, compound presence and purity) influence AAS consumers' future behaviours. As part of Wave 3 of a Steroid Testing Trial (2024), community members in Queensland, Australia, submitted AAS samples for laboratory analysis. Using advanced forensic techniques, we tested these samples for compound presence and dosage accuracy. Participants who accessed their results completed a follow-up survey on demographics, AAS use, healthcare access, and response to results. Behaviour change was measured by self-reported modifications to use. Logistic regression examined predictors including perceived helpfulness, confidence to change, quality concerns, prior health effects, and healthcare access barriers. Of 105 AAS samples analysed, 22% were mislabelled and 50% were underdosed. Most participants who engaged with testing results (N = 117) were men (97.4%), with a mean age of 32, and about half resided in Australia. Nearly all (95.7%) found results helpful, and 45.3% reported behaviour changes, including adjusting dosage, source, or testing compounds before use. Although the logistic regression model was not significant overall, concern about AAS quality predicted behaviour change (odds ratio [OR] = 1.57, P = .026), while perceived helpfulness, confidence, prior health effects, and healthcare barriers were not significant. Concern about product quality appears to drive harm reduction behaviours more than perceived helpfulness or confidence. These findings support the value of AAS in drug testing data dissemination that highlights product quality issues.

Strategy for balancing quality and moderate sodium reduction in beef patties through Maillard reaction modulation by banana peel extract.

Agronomic biofortification of durum wheat with selenium (Se) and zinc (Zn) represents a promising strategy to combat micronutrient deficiencies in human populations relying on cereal-based diets. This study evaluated the effectiveness of soil Zn application (S0Zn: no application; S50Zn: 50 kg of ZnSO4·7H2O ha− 1) and foliar applications of Se and Zn (0 F: no application; ZnF: two applications of 4 kg ZnSO4·7H2O ha− 1; SeF: 10 g Na2SeO4 ha− 1; ZnF + SeF: combined ZnF and SeF) on nutrient accumulation and yield in durum wheat semolina and pasta under Mediterranean rainfed conditions over two growing seasons. Semolina and pasta were analyzed for nutrient concentrations, phytic acid content, and indices of Zn bioavailability, including phytic acid–Zn molar ratios and modelled fractional and total absorbed Zn (FAZ and TAZ). Foliar treatments significantly increased Zn and Se concentrations in both semolina and pasta, with the combined Zn + Se treatment reaching 36.7 mg Zn kg⁻¹ and 43.1 µg Se kg⁻¹ in semolina and 32.7 mg Zn kg⁻¹ and 41.6 µg Se kg⁻¹ in pasta. These treatments also reduced PA: Zn ratios and increased estimated Zn absorption, while improving semolina yield by up to 4%. Processing from grain to semolina and pasta resulted in moderate but consistent micronutrient losses, with retention rates ranging from 66 to 74%. Overall, combined foliar application of Zn and Se proved to be an effective strategy to improve the nutritional quality of durum wheat-derived products under Mediterranean conditions.

This study investigated the potential of Cucurbita moschata and Cucurbita maxima as functional ingredients in cookie formulations. Pumpkin powders were incorporated as partial wheat flour substitutes to evaluate their effects on the physicochemical, nutritional profile, and functional properties of cookies. The results showed that pumpkin incorporation improved moisture retention and water absorption capacity, contributing to enhanced technological performance of the dough and baked products. Nutritional analysis revealed significant increases in protein, dietary fiber, fat, ash, and carotenoid contents in enriched cookies compared with the control formulation.Texture profile analysis demonstrated variety-dependent effects. Cookies enriched with C. moschata showed increased hardness at lower substitution levels but a softening effect at higher concentrations, whereas C. maxima maintained relatively stable firmness across formulations. Thermal analysis indicated improved thermal stability in enriched cookies, while mineral analysis confirmed better retention of essential elements. Confocal laser scanning microscopy further revealed a more homogeneous ingredient distribution and stronger matrix integration in cookies containing C. maxima powder.Furthermore, the incorporation of pumpkin powders significantly enhanced the bioactive profile of cookies, as reflected by higher total polyphenol content and increased DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging activity. These results highlight the potential of pumpkin powders as valuable functional ingredients for improving both the nutritional quality and functional properties of bakery products. The study supports the development of nutritionally enriched cookies with enhanced health benefits and technological performance.

HPLC-DAD method development and validation for the quantification of CBD, CBDA, Δ9-THC AND Δ9-THCA in Cannabis-based products.

The control of microbial contamination in flour represents a significant challenge for food safety. Traditional thermal methods often compromise product safety and quality as they cause undesirable changes. In addition, many existing technologies suffer from limitations such as uneven treatment, safety issues, and mainly superficial effects. To overcome these problems, a prototype system integrating atmospheric dielectric barrier discharges (DBD) cold plasma with mechanical fluidization was developed and applied to naturally contaminated maize flour for 5, 10, 20 and 30 min. Bacterial and fungal inactivation, physico-chemical properties, particle size distribution and microstructural properties were evaluated. A gradual reduction in mesophilic aerobic bacteria (MAB) was observed, with complete inactivation achieved after 30 min; however, bacterial regrowth was detected after 16 days of storage. Filamentous fungi were completely inactivated after 10 min and although partial recovery occurred during storage, fungal loads remained below those of the control. Fungal diversity was also altered, with Aspergillus flavus being more sensitive than Aspergillus oryzae. A notable reduction in water content and activity was observed for longer treatments. Modification of particle size and morphology likely occurred in the process with plasma associated to mechanical fluidization of flour. Overall, the effectiveness of ACP was influenced by treatment duration and fungal species, highlighting both its potential and limitations in flour decontamination, without detrimental effects on the selected physical quality attributes of the product. • Mechanical fluidization-assisted ACP was applied to maize flour. • Cold plasma significantly reduced the naturally contaminated microbiota by 3.3 Log. • Microbial inactivation and surface morphology depended on plasma exposure time. • Post-treatment storage showed no full regrowth of fungi over 16 days. • SEM analysis revealed progressive granule deformation and surface roughening.

Decoding and reconstructing yeast protein flavor based on an integrated sensory-omics approach.

High performance of ethanol colorimetric biosensor using core-shell biocomposite.

Temperature-sensitive medicines require controlled storage and transport conditions because unsuitable temperature and humidity exposure can compromise product quality and drug-delivery reliability. This study presents a low-cost Internet of Things (IoT)-assisted and lightweight machine learning framework for cold-chain risk assessment in temperature-sensitive drug delivery. A realistic cold-chain monitoring dataset was prepared to represent normal refrigerated storage, door-opening disturbance, transport exposure, freezing-risk events, humidity variation, and high-temperature excursions. Temperature, humidity, deviation-based variables, and exposure-duration features were used to classify storage conditions into Safe, Warning, and Unsafe states. Since unsafe excursions were naturally less frequent, bounded sensor-level augmentation was applied to construct an ML-ready dataset while preserving the raw monitoring profile for descriptive analysis. Four lightweight classifiers, namely Logistic Regression, Decision Tree, Random Forest, and support vector machine, were evaluated. Random Forest achieved the highest baseline performance with 0.9659 accuracy and 0.9636 macro F1-score. In feature-set ablation, the derived feature configuration without the direct risk score achieved 0.9636 accuracy and 0.9616 macro F1-score using seven features. The findings indicate that low-cost IoT monitoring combined with lightweight learning can support early warning and decision assistance in resource-constrained temperature-sensitive drug-delivery environments.