Quality Control Measures Research Articles

Breast Cancer Polygenic Risk Score Validation and Effects of Variable Imputation.

Breast cancer (BC) is a complex disease affecting one in eight women in the USA. Advances in population genomics have led to the development of polygenic risk scores (PRSs) with the potential to augment current risk models, but replication is often limited. We evaluated 2 robust PRSs with 313 and 3820 SNPs and the effects of multiple genotype imputation replications in BC cases and control populations. Biological samples from BC cases and cancer-free controls were drawn from three European ancestry cohorts. Genotyping on the Illumina Global Screening Array was followed by stringent quality control measures and 20 genotype imputation replications. A total of 468 unrelated cases and 4337 controls were scored, revealing significant differences in mean PRS percentiles between cases and controls (p < 0.001) for both SNP sets (313-SNP PRS: 52.81 and 48.07; 3820-SNP PRS: 55.45 and 49.81), with receiver operating characteristic curve analysis showing area under the curve values of 0.596 and 0.603 for the 313-SNP and 3820-SNP PRS, respectively. PRS fluctuations (from ~2-3% up to 9%) emerged across imputation iterations. Our study robustly reaffirms the predictive capacity of PRSs for BC by replicating their performance in an independent BC population and showcases the need to average imputed scores for reliable outcomes.

Comprehensive Elemental Profiling of Romanian Honey: Exploring Regional Variance, Honey Types, and Analyzed Metals for Sustainable Apicultural and Environmental Practices.

We investigated the mineral concentrations of 61 honey samples from eight Romanian regions, employing advanced techniques to assess 30 chemical elements. Potassium emerged as the dominant element, showcasing significant variations across geographical locations. Essential minerals like calcium, magnesium, sodium, and manganese maintained consistent levels, while zinc, copper, and chromium were present in smaller proportions. Critically, lead and cadmium levels exceeded established safety limits in some samples, suggesting potential environmental contamination. Additionally, elevated levels of lithium, strontium, nickel, and aluminum were detected, hinting at possible atmospheric pollution. These findings highlight the importance of regional analysis, as mineral content varied significantly between locations. Furthermore, correlation analysis revealed interdependencies among elements, suggesting shared environmental influences. Advanced statistical techniques like hierarchical clustering and principal component analysis effectively captured the impact of geographical origin on honey composition. These insights contribute valuable information for future efforts in honey quality control, traceability systems, and regulatory measures. By providing valuable insights into environmental influences on honey composition, this study informs future research endeavors and paves the way for the development of robust regulatory measures to ensure honey safety for consumers.

Synthesis Product for Ocean Time Series (SPOTS) – a ship-based biogeochemical pilot

Abstract. The presented pilot for the Synthesis Product for Ocean Time Series (SPOTS) includes data from 12 fixed ship-based time-series programs. The related stations represent unique open-ocean and coastal marine environments within the Atlantic Ocean, Pacific Ocean, Mediterranean Sea, Nordic Seas, and Caribbean Sea. The focus of the pilot has been placed on biogeochemical essential ocean variables: dissolved oxygen, dissolved inorganic nutrients, inorganic carbon (pH, total alkalinity, dissolved inorganic carbon, and partial pressure of CO2), particulate matter, and dissolved organic carbon. The time series used include a variety of temporal resolutions (monthly, seasonal, or irregular), time ranges (10–36 years), and bottom depths (80–6000 m), with the oldest samples dating back to 1983 and the most recent one corresponding to 2021. Besides having been harmonized into the same format (semantics, ancillary data, units), the data were subjected to a qualitative assessment in which the applied methods were evaluated and categorized. The most recently applied methods of the time-series programs usually follow the recommendations outlined by the Bermuda Time Series Workshop report (Lorenzoni and Benway, 2013), which is used as the main reference for “method recommendations by prevalent initiatives in the field”. However, measurements of dissolved oxygen and pH, in particular, still show room for improvement. Additional data quality descriptors include precision and accuracy estimates, indicators for data variability, and offsets compared to a reference and widely recognized data product for the global ocean: the GLobal Ocean Data Analysis Project (GLODAP). Generally, these descriptors indicate a high level of continuity in measurement quality within time-series programs and a good consistency with the GLODAP data product, even though robust comparisons to the latter are limited. The data are available as (i) a merged comma-separated file that is compliant with the World Ocean Circulation Experiment (WOCE) exchange format and (ii) a format dependent on user queries via the Environmental Research Division's Data Access Program (ERDDAP) server of the Global Ocean Observing System (GOOS). The pilot increases the data utility, findability, accessibility, interoperability, and reusability following the FAIR philosophy, enhancing the readiness of biogeochemical time series. It facilitates a variety of applications that benefit from the collective value of biogeochemical time-series observations and forms the basis for a sustained time-series living data product, SPOTS, complementing relevant products for the global interior ocean carbon data (GLobal Ocean Data Analysis Project), global surface ocean carbon data (Surface Ocean CO2 Atlas; SOCAT), and global interior and surface methane and nitrous oxide data (MarinE MethanE and NiTrous Oxide product). Aside from the actual data compilation, the pilot project produced suggestions for reporting metadata, implementing quality control measures, and making estimations about uncertainty. These recommendations aim to encourage the community to adopt more consistent and uniform practices for analysis and reporting and to update these practices regularly. The detailed recommendations, links to the original time-series programs, the original data, their documentation, and related efforts are available on the SPOTS website. This site also provides access to the data product (DOI: https://doi.org/10.26008/1912/bco-dmo.896862.2, Lange et al., 2024) and ancillary data.

XAI-empowered IoT multi-sensor system for real-time milk adulteration detection

In response to the critical issue of milk adulteration jeopardizing both the nutritional integrity of milk and the health of consumers, this paper presents an innovative Artificial Intelligence (AI) enabled Internet of Things (IoT) based multi-sensor system. The escalating consumption of milk as a pivotal nutritional source necessitates robust measures to ensure its safety and quality. Traditional methods of detecting adulteration have shown limitations, prompting the development of an automated and advanced approach. The proposed system integrates various sensors capable of real-time measurement, including pH, electrical conductivity (EC), temperature, gas parameters, and Volatile Organic Compounds (VOC) parameters. This comprehensive approach extends to measuring key constituents of milk samples like Fat, Protein, Solids Not Fat (SNF), Lactose, and Gravity values. To address specific adulterants—Urea, Starch, Sodium Bicarbonate, Maltodextrin, and Formaldehyde—a machine learning-based ensemble technique is employed for classification. This ensemble method outperforms conventional algorithms like RF, Light GBM, and Extra Trees Classifiers, achieving an impressive 96% accuracy rate in detecting adulterants within the milk dataset. The pivotal contribution of this study lies in the development of an IoT-based data acquisition device that seamlessly integrates with the sensor system, enabling efficient and precise measurements. Additionally, XAI is used to analyse the results obtained by the proposed model. For this, a framework called SHAP (SHapley Additive exPlanations) analysis is employed to elucidate the decision-making process of the ensemble model, enhancing the interpretability of results. By virtue of its real-time monitoring capabilities and accurate classification, the AI-enabled IoT-based multi-sensor system emerges as a promising solution for addressing milk adulteration. This innovation holds the potential to bolster milk quality control measures in the dairy industry. The system's ability to swiftly detect and categorize adulterants underscores its significance in combating the pervasive issue of compromised milk quality, thereby ensuring consumer safety and fostering industry integrity.

Seasonal dynamics of the microbial community in a strong-flavor baijiu fermentation.

The microbial community plays a crucial role in Chinese strong-flavor baijiu (SFB) fermentation. However, the seasonal dynamics of the microbial community in the SFB fermentation system and its contribution to the unique flavor of SFB have not been fully elucidated. In this study, we investigated the seasonal dynamics of the microbial community through 16S rRNA and ITS gene sequencing. The results revealed significant temporal dynamics of microbial communities and environmental variables throughout the four seasons. The influence of seasons on fungal communities was found to be more significant than on bacterial communities. The diversity of bacteria was higher during the winter and summer, whereas fungal diversity was more prominent in summer and autumn. Stochastic processes maintained their dominance in microbial assembly throughout all four seasons but the significance of heterogeneous selection increased during summer for both bacteria and fungi, whereas homogeneous selection became more pronounced during winter for fungi. The pH and environmental temperature were important drivers of microbial community assembly across different seasons, primarily impacting the core genera responsible for the production of major volatile flavor compounds (VFCs), especially ethyl caproate. These findings provide new insights into the impact of seasons on microbial communities and hold promise for improving the quality-control measures for SFB brewed in different seasons. © 2024 Society of Chemical Industry.

FT-IR Characterization and Determination of Mycotoxins (Aflatoxins) (AF’s) from Branded &amp; Unbranded Mixed Spice Samples

Background: The global spice market is essential to food industry and public health due to the widespread use of spices as flavor enhancers, preservatives, and medicinal components. However, the quality of spices can be compromised by the presence of mycotoxins, specifically aflatoxins, which pose significant health risks. Ensuring the quality and safety of spices, both branded and unbranded, is of paramount concern, especially in regions with high humidity and temperature that can facilitate fungal growth and mycotoxin production. Objective: This study aimed to assess the quality of branded and unbranded spice samples from Sindh, Pakistan, by determining their ash content, moisture level, oil composition, and mycotoxin (aflatoxin) content to ensure their suitability for consumption and adherence to food safety standards. Methods: A total of ten spice samples (five branded and five unbranded) were collected from different cities in Sindh province, Pakistan. Ash content was measured by high-temperature oxidation, while moisture content was quantified through oven drying. Oil was extracted using a Soxhlet apparatus, and its quality parameters, including free fatty acid (FFA), peroxide, iodine, and saponification values, were determined using standard AOCS methods. Aflatoxins were quantified by employing an official AOAC method. Additionally, FT-IR spectroscopy was utilized for qualitative analysis of the spice oils. Results: The ash content varied widely, with the highest in unbranded samples at 18.33% and the lowest in branded at 5.67%. Moisture content across all samples was within the safe limit of 5-10%, with the highest at 4.46% and the lowest at 2.22%. The oil content ranged from 5.96% to 14.56%, with unbranded samples showing higher values. FFA values exceeded the standard 0.1% in all samples, indicating a potential quality concern. Peroxide values were higher than the standard 2 meq/mol in most samples, raising concerns about oxidative stability. Aflatoxin levels were within the EU regulatory limits, suggesting acceptable levels for consumption. FT-IR analysis corroborated these findings, revealing no significant differences in the spectral profiles between branded and unbranded samples. Conclusion: The study concluded that while moisture content and aflatoxin levels in the spice samples complied with safety standards, there were notable concerns regarding the ash content, oil quality, and peroxide values. These findings highlight the necessity for regular quality control measures and adherence to food safety regulations to ensure the safety of spice consumption.

Renural networks applied to self-purification models of a river in West Parana

Among the parameters that allow evaluating the degree of pollution of a river, one of the most efficient is dissolved oxygen concentration (DO), as it reflects the balance between the production and consumption of oxygen in aquatic ecosystems. Due to the dynamic characteristic of DO concentration, especially in rivers and wetlands, it is highly recommended to generate DO models periodically for aquatic ecosystems so that quality control measures can be optimized over a time horizon. To this end, implementation of different artificial intelligence (AI) techniques have been suggested in the relevant literature and among these techniques, neural networks (ANNs) have been successfully applied to water quality estimates. In this context, the present work describes the development of a model in Convolutional Neural Networks – CNN (Convolutional Neural Networks) with the objective of simulating the self-cleaning potential of the Rio Alegria, located in the municipality of Medianeira in the State of Paraná . The data used was the same as that collected by Schütz in 2014, so that it was possible to compare the performance of the CNN network with the performance of the Feed Forward Network (FFN), developed with the same set of data collected in 2014. The models were developed based on data on the quality of the river's water and the effluent that is incorporated into the watercourse throughout the studied interval. The model was named, CNN5. Tests and validations were carried out by varying the network architecture with cross-validation to estimate dissolved oxygen. Considering the results referring to the simulations carried out with the CNN5 model, where the simulated OD values are compared (from the combination of the weights that the network assigns to each input), with the results collected in the field and it can be concluded that a CNN network can be used to predict dissolved oxygen in the waters of a stretch of river, with an overall accuracy of 0.90, while FFN5 managed to achieve an accuracy of 77% for the same group of data. processing, a reduction from 12 hours to two minutes can be observed.

Assessment of heavy metals and fungi contamination of spices available in Saudi Arabian food cuisines

The study investigates the elemental composition and fungal contamination of commonly utilized spices and herbs, namely Turmeric, Cloves, Black pepper, Latency/cumin, Ring/legume, Cinnamon, Coriander, Ginger, Indian saffron, Fenugreek, Fennel flower, Aniseed, and Cayenne pepper. The presence of minerals and poisons elements, including zinc (Zn), iron (Fe), chromium (Cr), manganese (Mn), copper (Cu), nickel (Ni), cadmium (Cd), and lead (Pb), was examined. The concentration of the poisonous elements ranged from 44.1 ± 1.3 to 231±41 µgg−1 for Fe, 3.8 ± 5.9 to 17.3 ± 3.1 µgg−1 for Zn, 1.3 ± 0.2 to 9.3 ± 0.4 µgg−1 for Cu, 10.4 ± 1.1 µgg−1 for Mn, and 219±2.1 µgg−1 for Pb; Cd was below the level of detection. The study also assessed fungal contamination, revealing black pepper as the most contaminated sample (87.6 %), followed by saffron (76.2 %), Cayenne pepper (72.1 %), Coriander (65.0 %), and cumin (64.4 %). Conversely, fenugreek (52.5 %) and cinnamon (51.6 %) exhibited lower contamination rates. Aspergillus flavus was predominant in white pepper (70.0 %) and black pepper (34.0 %), while ginger showed a diverse range of fungal species, including A. niger, A. flavus, and Rhizopus stolonifera (50 %). Notably, cinnamon was found highly contaminated with Aspergillus flavus (40 %), Aspergillus niger (40 %), and Rhizopus stolonifera (40 %), while legumes were contaminated with Aspergillus niger (40 %), Penicillium arenicola (40 %), and Penicillium oxalicum (40 %). This study highlights potential health risks associated with spice consumption, particularly in large quantities, due to mycotoxin contamination. The findings emphasize the importance of monitoring and implementing stringent quality control measures in the spice industry to ensure food safety and mitigate health hazards associated with elemental and fungal contamination. By combining scientific rigor with a focus on local context, this research strives to make a meaningful impact on public health, culinary traditions, and the broader global conversation on food safety.

From Farm to Fork: Transforming Egg Quality and Boosting Export Potential using Artificial Intelligence on Poultry Farming

Nothing can spoil fresh eggs that were laid by chickens, like dirty vent feathers, blood strains and minor cracks. Eggs play an important role in the context of human health due to its cheap cost and accessibility across the globe. But egg damage paves the way for a significant size of a shortage of nutritions, and creates demand which leads to an increase in price. The brand name of the company that supplies the eggs loses its reputation when damaged eggs reach the market along with good eggs and this can also lead to business loss. India is considered to be one of the worst farm poultry industries across the world, because of poor maintenance of farm, lack of cleanliness and non-compliance to the safety standards. Just because of this, the Indian market loses its power of negotiation on price and loses the opportunity to export the eggs to foreign countries even though India's egg production is close to the egg production margin of other countries. Not only from the perspective of commerce but also from the view of health this can lead to adverse consequences when the unclean eggs are consumed by the public or people who have less immunity. Every year a significant number of people are suffering from diseases when the eggs, which are poorly handled in the process of quality control, are consumed. This could also lead to a fixation of mindset to the consumer that these are usual eggs in india. The consequence of this mindset could result in more severe effects in consumerism over the period of time. This might also prevent people from purchasing the eggs for consumption. The major reason for this is unhygienic rearing practice and improper quality control measures. These are open invitations for egg contamination although India is the third largest country in the world in the production of eggs. There are more than forty seven million egg producers who do not meet safety standards, most of the produce are rejected for export due to chemicals used during the rearing process. Consumption of these eggs had led to a serious issue in india. A sizable number of people are resistant to antibiotics just because of the consumption of eggs that were produced using chemicals and eggs in which chemicals were intact on the shell of that egg. An article that was published by a renowned newspaper states that consumption of such contaminated eggs, which had heavy metal, has led to poisoning in children, paving the way for mental development problems, sometimes mental retardation. This study has attempted to reduce the severe consequences which are a result of consuming eggs with dirt or damaged eggs. A huge effort has been made to ensure that this scenario changes over the period of time, by incorporating AI in the field of Poultry industry in order to enhance the quality of egg production. The study we conducted clearly shows that most of the poor rearing practice happens due to human error. This can be changed by replacing the human efforts by machine, we could replace the entire quality control process especially removing the spoiled eggs from the the batch that is to be sent to the market. The model that we tried to build has given marvelous results in separating the spoiled from the good eggs. The algorithm will not only identify the spoiled eggs but also stores the final output in the database where the Organisations can access it at any point of time. The AI Object detection model will detect the cracked eggs, the eggs with dirt, the eggs with blood stain and many more. In nutshell our object detection model will detect all abnormal eggs which will help us prevent the abnormal eggs from reaching the consumer.

Multi-element analysis of unfiltered samples in river water monitoring—digestion and single-run analyses of 67 elements

Routine analysis of inorganic analytes in whole water samples from rivers (unfiltered river water) is rarely reported in scientific publications. However, this sample type is valuable and often used in long-term monitoring, regulation, and catchment element budgets, as it includes the dissolved, colloidal, and particulate fraction in one sample type. Preservation measures are not needed and solid–liquid partitioning can be disregarded, which simplifies automated sampling and storage procedures. In this study, we provide several digestion protocols for whole water samples from rivers and the subsequent multi-element analysis of 67 major, minor, and trace elements: Li, Be, B, Na, Mg, Al, Si, P, S, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Ge, As, Se, Br, Rb, Sr, Y, Zr, Nb, Mo, Ru, Ag, Cd, In, Sn, Sb, Te, Cs, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Hf, Ta, W, Ir, Pt, Au, Hg, Tl, Pb, Bi, Th, U. In the absence of whole water reference materials for inorganic analytes, we introduce simulated whole water samples by suspending sediment reference materials as quality control measures. The applicability for improved routine water quality monitoring was successfully tested on samples from different rivers revealing variations of the element fingerprints over time.Graphical abstract

A Panoramic Review on the Management of Rheumatoid Arthritis through Herbalism.

Arthritis is a chronic inflammatory condition that affects millions of individuals worldwide. The conventional treatment options for arthritis often come with limitations and potential side effects, leading to increased interest in herbal plants as alternative therapies. This article provides a comprehensive overview of the use of herbal plants in arthritis treatment, focusing on their traditional remedies, active components, mechanisms of action, and pharmaceutical approaches for enhancing their delivery. Various herbal plants, including turmeric, ginger, Boswellia, and willow bark, have shown anti-inflammatory and analgesic properties, making them valuable options for managing arthritis symptoms. The active components of these herbal plants, such as curcumin, gingerols, and boswellic acids, contribute to their therapeutic effects. To enhance the delivery of herbal medicines, pharmaceutical approaches like nanoparticle-based drug delivery systems, liposomes, polymeric nanoparticles, nanoemulsions, microneedles, and inhalation systems have been explored. These approaches aim to improve bioavailability, targeted delivery, and controlled release of herbal compounds. Safety considerations, including potential interactions with medications and the risk of allergic reactions, are also discussed. Future perspectives for this field involve conducting well-designed clinical studies, enhancing standardization and quality control measures, exploring novel drug delivery systems, and fostering collaborations between traditional medicine practitioners and healthcare professionals. Continued research and development in these areas will help unlock the full potential of herbal plants in arthritis treatment, offering personalized and effective care for affected individuals.

IMPATIENT-qPCR: monitoring SELEX success during in vitro aptamer evolution

SELEX (Systematic Evolution of Ligands by Exponential enrichment) processes aim on the evolution of high-affinity aptamers as binding entities in diagnostics and biosensing. Aptamers can represent game-changers as constituents of diagnostic assays for the management of instantly occurring infectious diseases or other health threats. Without in-process quality control measures SELEX suffers from low overall success rates. We present a quantitative PCR method for fast and easy quantification of aptamers bound to their targets. Simultaneous determination of melting temperatures (Tm) of each SELEX round delivers information on the evolutionary success via the correlation of increasing GC content and Tm alone with a round-wise increase of aptamer affinity to the respective target. Based on nine successful and published previous SELEX processes, in which the evolution/selection of aptamer affinity/specificity was demonstrated, we here show the functionality of the IMPATIENT-qPCR for polyclonal aptamer libraries and resulting individual aptamers. Based on the ease of this new evolution quality control, we hope to introduce it as a valuable tool to accelerate SELEX processes in general.IMPATIENT-qPCR SELEX success monitoring. Selection and evolution of high-affinity aptamers using SELEX technology with direct aptamer evolution monitoring using melting curve shifting analyses to higher Tm by quantitative PCR with fluorescence dye SYBR Green I.Key points• Fast and easy analysis.• Universal applicability shown for a series of real successful projects.Graphical

Modulation of Protein Disulfide Isomerase Functions by Localization: The Example of the Anterior Gradient Family.

Significance: Oxidative folding within the endoplasmic reticulum (ER) introduces disulfide bonds into nascent polypeptides, ensuring proteins' stability and proper functioning. Consequently, this process is critical for maintaining proteome integrity and overall health. The productive folding of thousands of secretory proteins requires stringent quality control measures, such as the unfolded protein response (UPR) and ER-Associated Degradation (ERAD), which contribute significantly to maintaining ER homeostasis. ER-localized protein disulfide isomerases (PDIs) play an essential role in each of these processes, thereby contributing to various aspects of ER homeostasis, including maintaining redox balance, proper protein folding, and signaling from the ER to the nucleus. Recent Advances: Over the years, there have been increasing reports of the (re)localization of PDI family members and other ER-localized proteins to various compartments. A prime example is the anterior gradient (AGR) family of PDI proteins, which have been reported to relocate to the cytosol or the extracellular environment, acquiring gain of functions that intersect with various cellular signaling pathways. Critical Issues: Here, we summarize the functions of PDIs and their gain or loss of functions in non-ER locations. We will focus on the activity, localization, and function of the AGR proteins: AGR1, AGR2, and AGR3. Future Directions: Targeting PDIs in general and AGRs in particular is a promising strategy in different human diseases. Thus, there is a need for innovative strategies and tools aimed at targeting PDIs; those strategies should integrate the specific localization and newly acquired functions of these PDIs rather than solely focusing on their canonical roles.

Road and Bridge Construction Technology and Quality Control Measures and Analysis

With the rapid development of China's social economy, urban construction has undergone qualitative changes, and road construction and bridge engineering construction have become increasingly perfect, playing an important role in urban development and construction. Municipal road construction projects cover a wide range, with urban bridge construction running through them, effectively improving environmental and traffic issues, but there are still many areas that need improvement. This article proposes corresponding solutions for monitoring the construction quality of municipal roads and bridges, as well as the problems that arise, based on the development status of the city and the actual situation.

Addressing air quality challenges: Comparative analysis of Barcelona, Venezuela, and Guayaquil, Ecuador

This study presents a willingness-to-pay (WtP) questionnaire that was designed, validated, and applied to assess perceptions of air quality and self-reported health in two middle-income South American cities: Barcelona and its neighboring cities (Venezuela) and Guayaquil (Ecuador). These cities lack air quality monitoring and control measures. The questionnaire is a reliable tool to assess air quality based on citizens' perceptions, and the results reveal that both populations perceive low air quality and accurately identify emission sources and air pollutants (industrial emissions and particulate matter in Barcelona and vehicular emissions and carbon monoxide in Guayaquil).The study also evaluated the efforts made by both cities to improve air quality using the United Nations Environment Programme to strengthen air quality in South America. Based on this evaluation, strengths were identified for enhancing air quality in both cities. The study finds that in Barcelona and its surroundings, investment is needed to improve urban transport, waste management, and update the environmental legislation regarding air quality at the national level. In contrast, Guayaquil has already taken some measures to improve air quality, but more investment in public transport and measures to lower vehicle emissions are needed.

Everything falls apart: How solids degrade and release nanomaterials, composite fragments, and microplastics

To ensure the safe use of materials, one must assess the identity and quantity of exposure. Solid materials, such as plastics, metals, coatings and cements, degrade to some extent during their life cycle, and releases can occur during manufacturing, use and end-of-life. Releases (e.g., what is released, how does release happen, and how much material is released) depend on the composition and internal (nano)structures of the material as well as the applied stresses during the lifecycle. We consider, in some depth, releases from mechanical, weathering and thermal stresses and specifically address the use cases of fused-filament 3D printing, dermal contact, food contact and textile washing. Solid materials can release embedded nanomaterials, composite fragments, or micro- and nanoplastics, as well as volatile organics, ions and dissolved organics. The identity of the release is often a heterogenous mixture and requires adapted strategies for sampling and analysis, with suitable quality control measures. Control materials enhance robustness by enabling comparative testing, but reference materials are not always available as yet. The quantity of releases is typically described by time-dependent rates that are modulated by the nature and intensity of the applied stress, the chemical identity of the polymer or other solid matrix, and the chemical identity and compatibility of embedded engineered nanomaterials (ENMs) or other additives. Standardization of methods and the documentation of metadata, including all the above descriptors of the tested material, applied stresses, sampling and analytics, are identified as important needs to advance the field and to generate robust, comparable assessments. In this regard, there are strong methodological synergies between the study of all solid materials, including the study of micro- and nanoplastics. From an outlook perspective, we review the hazard of the released entities, and show how this informs risk assessment. We also address the transfer of methods to related issues such as tyre wear, advanced materials and advanced manufacturing, biodegradable polymers, and non-solid matrices. As the consideration of released entities will become more routine in industry via lifecycle assessment in Safe-and-Sustainable-by-Design practices, release assessments will require careful design of the study with quality controls, the use of agreed-on test materials and standardized methods where these exist and the adoption of clearly defined data reporting practices that enable data reuse, meta-analyses, and comparative studies.

Enhancing Quality in Hematology Laboratory Testing: A Comprehensive Review of Preanalytical Phase Errors and Prevention Strategies

Abstract: This comprehensive review explores the critical importance of the preanalytical phase in hematology laboratory testing and its significant impact on the overall quality of results. The preanalytical phase encompasses all the processes from sample collection to sample preparation, and any errors during this stage can lead to inaccurate and unreliable hematological data. By systematically examining the various sources of preanalytical errors, including specimen collection, transportation, and handling, this review provides insights into the potential challenges faced in the hematology laboratory. Furthermore, the article discusses a range of effective prevention strategies to mitigate preanalytical phase errors and enhance the reliability of hematological test results. These strategies encompass improvements in staff training, standardization of collection procedures, implementation of quality control measures, and advancements in technology and automation. The review emphasizes the importance of fostering a culture of awareness and adherence to best practices in the laboratory setting. Preanalytical errors remain a major concern in every laboratory because the majority of the stages leading up to these errors are not within the direct control of the laboratory. Even though they cannot be eliminated, they can definitely be minimized. The preanalytical errors of a hematology laboratory can be reduced with the help of quality management systems, personnel training, regular audits, and automation in the preanalytical stage, thus increasing the accuracy of the results and providing better patient care.

A novel approach to generate enzyme-free single cell suspensions from archived tissues for miRNA sequencing

Obtaining high-quality omics data at the single-cell level from archived human tissue samples is crucial for gaining insights into cellular heterogeneity and pushing the field of personalized medicine forward. In this technical brief we present a comprehensive methodological framework for the efficient enzyme-free preparation of tissue-derived single cell suspensions and their conversion into single-cell miRNA sequencing libraries. The resulting data from this study have the potential to deepen our understanding of miRNA expression at the single-cell level and its relevance in the context of the examined tissues. The workflow encompasses tissue collection, RNALater immersion, storage, thawing, TissueGrinder-mediated dissociation, miRNA lysis, library preparation, sequencing, and data analysis. Quality control measures ensure reliable miRNA data, with specific attention to sample quality. The UMAP analysis reveals tissue-specific cell clustering, while miRNA diversity reflects tissue variations. The presented workflow effectively processes preserved tissues, extending opportunities for retrospective analysis and biobank utilization.

Effects of structured protocolized physical therapy on the duration of mechanical ventilation in patients with prolonged weaning

Purpose20% of patients with mechanical ventilation (MV) have a prolonged, complex weaning process, often experiencing a condition of ICU-acquired weakness (ICUAW), with a severe decrease in muscle function and restricted long-term prognosis. We aimed to analyze a protocolized, systematic approach of physiotherapy in prolonged weaning patients and hypothesized that the duration of weaning from MV would be shortened. MethodsICU patients with prolonged weaning were included before (group 1) and after (group 2) introduction of a quality control measure of a structured and protocolized physiotherapy program. Primary endpoint was the tested dynamometric handgrip strength and the Surgical Intensive Care Unit Optimal Mobilization Score (SOMS). Secondary endpoints were weaning success rate, ventilator-free days, hospital mortality, the prevalence of ICUAW, infections and delirium. Results106 patients were included. Both the SOMS and the handgrip test were significantly improved after introducing the program. Despite no differences in weaning success rates at discharge, the total length of MV was significantly shorter in group 2, which also had lower prevalence of infection and higher probability of survival. ConclusionsProtocolized, systematic physiotherapy resulted in an improvement of the clinical outcome in patients with prolonged weaning. Results were objectifiable with the SOMS and the handgrip test.

Contemporary Utilization and Outcomes of Resuscitative Endovascular Balloon Occlusion of the Aorta for Traumatic Noncompressible Torso Hemorrhage in Korea: A Retrospective Multi-Center Study

Purpose: This study aimed to evaluate the utilization and outcomes of resuscitative endovascular balloon occlusion of the aorta (REBOA) in managing noncompressible torso hemorrhage (NCTH) among trauma patients in Korea. The evolution of REBOA and its impact on patient survival was investigated as well as predictors of mortality.Methods: This retrospective study included 234 post-REBOA patients from 5 leading regional trauma centers across Korea between 2016 and 2021. Primary outcomes were in-hospital mortality, and secondary outcomes were various clinical parameters regarding REBOA, overall treatment flow, and complications. For comparative analyses, patients were dichotomized into in-hospital non-survivors or survivors. Then, generalized additive and linear regression models were used to evaluate the trend of in-hospital mortality.Results: The overall in-hospital mortality was 65.4%. The survivors had a higher proportion of responders following REBOA (87.7% vs 62.7%, &lt;i&gt;p&lt;/i&gt; &lt; 0.001). Key variables influencing outcomes included total occlusion time, red blood cell transfusion volume within the first 24 hours, revised trauma score, and systolic blood pressure gap. These factors significantly correlated with mortality rates in multivariate logistic regression.Conclusion: Over 6 years, survival rates for NCTH patients undergoing REBOA in Korea have shown improvement. Despite diverse REBOA protocols across institutions, the results underscore the need for continued research, standardized practices, and national quality control measures to further optimize patient outcome and establish more effective treatment protocols for NCTH.