Application of FTIR two-dimensional correlation spectroscopy (2D-COS) analysis in characterizing environmental behaviors of microplastics: A systematic review.

Microplastics (MPs) are ubiquitous in the environment, continuously undergo aging processes and release toxic chemical substances. Understanding the environmental behaviors of MPs is critical to accurately evaluate their long-term ecological risk. Generalized two-dimensional correlation spectroscopy (2D-COS) is a powerful tool for MPs studies, which can dig more comprehensive information hiding in the conventional one-dimensional spectra, such as infrared (IR) and Raman spectra. The recent applications of 2D-COS in analyzing the behaviors and fates of MPs in the environment, including their aging processes, and interactions with natural organic matter (NOM) or other chemical substances, were summarized systematically. The main requirements and limitations of current approaches for exploring these processes are discussed, and the corresponding strategies to address these limitations and drawbacks are proposed as well. Finally, new trends of 2D-COS are prospected for analyzing the properties and behaviors of MPs in both natural and artificial environmental processes.

The Application of Organoids in the Study of Antiviral Innate Immunity.

Antiviral innate immunity plays a critical role in the defense against viral infections, yet its complex interactions with viruses have been challenging to study using traditional models. Organoids, three-dimensional (3D) tissue-like structures derived from stem cells, have emerged as powerful tools for modeling human tissues and studying the complex interactions between viruses and the host innate immune system. This chapter summarizes relevant applications of organoids in antiviral innate immunity studies and provides detailed information and experimental procedures for using organoids to study antiviral innate immunity.

Regulation of mechanical properties of microcapsules and their applications.

Microcapsules encapsulating payloads are one of the most promising delivery methods. The mechanical properties of microcapsules often determine their application scenarios. For example, microcapsules with low mechanical strength are more widely used in biomedical applications due to their superior biocompatibility, softness, and deformability. In contrast, microcapsules with high mechanical strength are often mixed into the matrix to enhance the material. Therefore, characterizing and regulating the mechanical properties of microcapsules is essential for their design optimization. This paper first outlines four methods for the mechanical characterization of microcapsules: nanoindentation technology, parallel plate compression technology, microcapillary technology, and deformation in flow. Subsequently, the mechanisms of regulating the mechanical properties of microcapsules and the progress of applying microcapsules with different degrees of softness and hardness in food, textile, and pharmaceutical formulations are discussed. These regulation mechanisms primarily include altering size and morphology, introducing sacrificial bonds, and construction of hybrid shells. Finally, we envision the future applications and research directions for microcapsules with tunable mechanical properties.

A detailed methodology for estimating health-related hazards of workplace exposure to indoor formaldehyde vapours.

A comprehensive risk assessment method was applied to examine the risks associated with airborne formaldehyde occupational exposure among hospital laboratory staff. The method assessed exposure levels and health impacts by integrating area and personal air sampling, biological monitoring, and self-reported health data. Samples were collected from 74 workplaces across various departments using NIOSH method 3500 and were analyzed via UV-vis spectrophotometry. The data showed significant differences in exposure levels between departments (p≤0.05) and confirmed the efficacy of the method in identifying risk differences. Despite average personal exposure levels being measured lower than occupational limits, individual assessments indicated that some participants surpassed these limits, emphasizing the necessity of personal monitoring for workers with higher risks. The high prevalence of respiratory symptoms, such as cough and wheezing among staff, indicated the need for further investigation and targeted interventions. Although estimated cancer and non-cancer risks were within safe thresholds, the study emphasized the importance of continuous exposure monitoring and the implementation of effective control measures in hospital laboratory departments with formaldehyde emission. This integrated method improved the reliability and generalizability of formaldehyde exposure risk assessments and aided in the development of safe occupational health practices.•The method integrated personal and area sampling with advanced calibration for precise occupational exposure evaluation in laboratories.•The method used of biomarkers to assess formaldehyde absorption in the body estimating both cancerous and non-cancerous health risks associated with occupational exposure.•Addressed traditional method limitations and integrated risk components to improve data reliability for workplace safety and health risk management.

Development model based on visual image big data applied to art management.

This paper aims to explore the application of visual image big data (BD) in art management, and proposes and develops a new art management model. First of all, this study conducted extensive research on the overview and application of big data, focusing on analyzing the characteristics of big data and its characteristics and application methods in art management. By introducing image processing (IP) technology, this paper expounds on the application of visual image technology in art management in detail and discusses the classification of computer vision images to determine its application direction. On this basis, this paper proposes the application of visual images and big data in art management from three aspects: the accurate acquisition of visual images, the development model of art management, and the development of visual image technology in art resource management and teaching, and strengthens the development model of art management based on IP algorithm. Experiments and surveys show that the art management model development system built by the newly introduced visual image technology, big data technology, and IP algorithm can increase user satisfaction by 24 %. This result shows that the new model has a significant effect in improving the efficiency and quality of art management, providing strong technical support for the field of art management, while also providing designers with a more accurate tool for assessing market trends, helping to adhere to and promote good design concepts.

The Effect of Numeric Versus Pass/Fail USMLE Step 1 Scores in the Integrated Plastic Surgery 2023-2024 Match Cycle: A Single Institution Study.

OBJECTIVE: The USMLE Step 1 exam, an important metric in the integrated plastic surgery match, transitioned to pass/fail scoring in January 2022. No previous studies have investigated the impact of this new scoring system on the process of ranking applicants in the integrated plastic surgery match. DESIGN: 330 Plastic Surgery Common Applications (PSCAs) were submitted to a single academic center in the 2023-2024 match cycle. Applicants were sorted into tiers via a holistic review process, and quantifiable data, including USMLE Step 1 scores, were then compared between tiers. SETTING: Our Institution's Integrated Plastic Surgery Residency Program. PARTICIPANTS: Integrated Plastic Surgery applicants in the 2023-2024 match cycle. RESULTS: 317 of 330 PSCAs were analyzed in this study, excluding applicants who did an elective rotation at our institution. Applicants were sorted into 3 tiers: high (n = 100), middle (n = 118) and low (n = 99), with a significant difference in match rate per tier, respectively (88.0%, 58.5%, 30.3%, p < 0.0001). The majority of USMLE Step 1 scores were reported as pass/fail (186/317, 58.7%). There was a significant difference (p < 0.0001) between the average USMLE Step 1 score between the high (mean 250.5, SD 10.4), middle (mean 241, SD 14.6), and low tiers (mean 235.5, SD 16.5). More applicants in the low tier (50%) and high tier (40%) reported numeric USMLE Step 1 scores than those in the middle tier (35%, p = 0.0734). Stepwise logistic regression revealed USMLE Step 1 score to be an independent predictor of tier placement between the high and middle tier (p = 0.0030) and high and low tier (p = 0.0001). Lastly, 3 applicants reported their USMLE Step 1 score as 'pass' instead of their given numeric score. CONCLUSIONS: Comparing applicants with numeric USMLE Step 1 scores to those with pass/fail scores can have a significant impact on the ranking of those applicants and should be carefully considered during the plastic surgery match process.

Mobile mental health application use, and app feature preferences among individuals with mental disorders in Ethiopia: A cross-sectional survey.

BACKGROUND: Mobile health applications have been shown to assist in the treatment of mental illnesses, yet their potential remains underutilized. As supportive care, mental health applications use may be useful tools in improving mental health literacy and treatment outcomes, but patients' use of and interest in using these apps have not been studied in low-income countries like Ethiopia. This study explores the determinants of patients' mental health app use interests and app feature preferences. METHODS: A cross-sectional study was conducted with 419 outpatient individuals with mental health disorders at Amanuel Mental Specialized Hospital, Ethiopia, between October and November 2023, using a convenience sampling method. Patients' self-reported mental health app use, interests, attitudes, and app feature preferences were collected. A multivariate logistic regression model was used to identify the associated factors. RESULTS: Overall prevalence of not interested, somewhat interested, interested, and extremely interested in mental health app use was 5.3 %, 16.9 %, 27.7 %, and 50.1 % respectively. The proportion of current mental health apps use was low (21.2 %). Current mental health app use is associated with living in an urban area (AOR = 6.69, CI: 3.19-14) and having a higher education level (4.12 (2.02-8.04). Furthermore, app features such as psychoeducation, symptom tracking, and self-management techniques ranked as the most preferred app features. CONCLUSIONS: Most study participants were interested in using mental health apps, but only about one in four were using mental health apps. This suggests promise for their utility in the Ethiopian context. App developers and policymakers should consider rural residents', lower educational levels, and patient app preferences when developing these applications.

Neural Conversational Agent for Weight Loss Counseling: Protocol for an Implementation and Feasibility Study.

BACKGROUND: Obesity is a common, serious and costly chronic disease. Current clinical practice guidelines recommend that providers augment the longitudinal care of people living with obesity with consistent support for the development of self-efficacy and motivation to modify their lifestyle behaviors. Lifestyle behavior change aligns with the goals of motivational interviewing (MI), a client-centered yet directive counseling modality. However, training health care providers to be proficient in MI is expensive and time-consuming, resulting in a lack of trained counselors and limiting the widespread adoption of MI in clinical practice. Artificial intelligence (AI) counselors accessible via the internet can help circumvent these barriers. OBJECTIVE: The primary objective is to explore the feasibility of conducting unscripted MI-consistent counseling using Neural Agent for Obesity Motivational Interviewing (NAOMI), a large language model (LLM)-based web app for weight loss counseling. The secondary objectives are to test the acceptability and usability of NAOMI's counseling and examine its ability to shift motivational precursors in a sample of patients with overweight and obesity recruited from primary care clinics. METHODS: NAOMI will be developed based on recent advances in deep learning in four stages. In stages 1 and 2, NAOMI will be implemented using an open-source foundation LLM and (1) few-shot learning based on a prompt with task-specific instructions and (2) domain adaptation strategy based on fine-tuning LLM using a large corpus of general psychotherapy and MI treatment transcripts. In stages 3 and 4, we will refine the best of these 2 approaches. Each NAOMI version will be evaluated using a mixed methods approach in which 10 adults (18-65 years) meeting the criteria for overweight or obesity (25.0≥BMI≤39.9) interact with NAOMI and provide feedback. NAOMI's fidelity to the MI framework will be assessed using the Motivational Interviewing Treatment Integrity scale. Participants' general perceptions of AI conversational agents and NAOMI specifically will be assessed via Pre- and Post-Interaction Questionnaires. Motivational precursors, such as participants' confidence, importance, and readiness for changing lifestyle behaviors (eg, diet and activity), will be measured before and after the interaction, and 1 week later. A qualitative analysis of changes in the measures of perceptions of AI agents and counselors and motivational precursors will be performed. Participants will rate NAOMI's usability and empathic skills post interaction via questionnaire-based assessments along with providing feedback about their experience with NAOMI via a qualitative interview. RESULTS: NAOMI (version 1.0) has been developed. Participant recruitment will commence in September 2024. Data collection activities are expected to conclude in May 2025. CONCLUSIONS: If proven effective, LLM-based counseling agents can become a cost-effective approach for addressing the obesity epidemic at a public health level. They can also have a broad, transformative impact on the delivery of MI and other psychotherapeutic treatment modalities extending their reach and broadening access. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/60361.

Value of Engagement in Digital Health Technology Research: Evidence Across 6 Unique Cohort Studies.

BACKGROUND: Wearable digital health technologies and mobile apps (personal digital health technologies [DHTs]) hold great promise for transforming health research and care. However, engagement in personal DHT research is poor. OBJECTIVE: The objective of this paper is to describe how participant engagement techniques and different study designs affect participant adherence, retention, and overall engagement in research involving personal DHTs. METHODS: Quantitative and qualitative analysis of engagement factors are reported across 6 unique personal DHT research studies that adopted aspects of a participant-centric design. Study populations included (1) frontline health care workers; (2) a conception, pregnant, and postpartum population; (3) individuals with Crohn disease; (4) individuals with pancreatic cancer; (5) individuals with central nervous system tumors; and (6) families with a Li-Fraumeni syndrome affected member. All included studies involved the use of a study smartphone app that collected both daily and intermittent passive and active tasks, as well as using multiple wearable devices including smartwatches, smart rings, and smart scales. All studies included a variety of participant-centric engagement strategies centered on working with participants as co-designers and regular check-in phone calls to provide support over study participation. Overall retention, probability of staying in the study, and median adherence to study activities are reported. RESULTS: The median proportion of participants retained in the study across the 6 studies was 77.2% (IQR 72.6%-88%). The probability of staying in the study stayed above 80% for all studies during the first month of study participation and stayed above 50% for the entire active study period across all studies. Median adherence to study activities varied by study population. Severely ill cancer populations and postpartum mothers showed the lowest adherence to personal DHT research tasks, largely the result of physical, mental, and situational barriers. Except for the cancer and postpartum populations, median adherences for the Oura smart ring, Garmin, and Apple smartwatches were over 80% and 90%, respectively. Median adherence to the scheduled check-in calls was high across all but one cohort (50%, IQR 20%-75%: low-engagement cohort). Median adherence to study-related activities in this low-engagement cohort was lower than in all other included studies. CONCLUSIONS: Participant-centric engagement strategies aid in participant retention and maintain good adherence in some populations. Primary barriers to engagement were participant burden (task fatigue and inconvenience), physical, mental, and situational barriers (unable to complete tasks), and low perceived benefit (lack of understanding of the value of personal DHTs). More population-specific tailoring of personal DHT designs is needed so that these new tools can be perceived as personally valuable to the end user.

Trial Factors Associated With Completion of Clinical Trials Evaluating AI: Retrospective Case-Control Study.

BACKGROUND: Evaluation of artificial intelligence (AI) tools in clinical trials remains the gold standard for translation into clinical settings. However, design factors associated with successful trial completion and the common reasons for trial failure are unknown. OBJECTIVE: This study aims to compare trial design factors of complete and incomplete clinical trials testing AI tools. We conducted a case-control study of complete (n=485) and incomplete (n=51) clinical trials that evaluated AI as an intervention of ClinicalTrials.gov. METHODS: Trial design factors, including area of clinical application, intended use population, and intended role of AI, were extracted. Trials that did not evaluate AI as an intervention and active trials were excluded. The assessed trial design factors related to AI interventions included the domain of clinical application related to organ systems; intended use population for patients or health care providers; and the role of AI for different applications in patient-facing clinical workflows, such as diagnosis, screening, and treatment. In addition, we also assessed general trial design factors including study type, allocation, intervention model, masking, age, sex, funder, continent, length of time, sample size, number of enrollment sites, and study start year. The main outcome was the completion of the clinical trial. Odds ratio (OR) and 95% CI values were calculated for all trial design factors using propensity-matched, multivariable logistic regression. RESULTS: We queried ClinicalTrials.gov on December 23, 2023, using AI keywords to identify complete and incomplete trials testing AI technologies as a primary intervention, yielding 485 complete and 51 incomplete trials for inclusion in this study. Our nested propensity-matched, case-control results suggest that trials conducted in Europe were significantly associated with trial completion when compared with North American trials (OR 2.85, 95% CI 1.14-7.10; P=.03), and the trial sample size was positively associated with trial completion (OR 1.00, 95% CI 1.00-1.00; P=.02). CONCLUSIONS: Our case-control study is one of the first to identify trial design factors associated with completion of AI trials and catalog study-reported reasons for AI trial failure. We observed that trial design factors positively associated with trial completion include trials conducted in Europe and sample size. Given the promising clinical use of AI tools in health care, our results suggest that future translational research should prioritize addressing the design factors of AI clinical trials associated with trial incompletion and common reasons for study failure.

Identification of a thermostable L-asparaginase from Pyrococcus yayanosii CH1 and its application in the reduction of acrylamide.

L-asparaginase (ASNase, E.C. 3.5.1.1) catalyzes the deamination of L-asparagine to L-aspartic acid and ammonia and is widely used in medicine to treat acute lymphocytic leukemia. It also has significant applications in the food industry by inhibiting acrylamide formation. In this study, we characterized a thermostable ASNase from the hyper thermophilic strain, Pyrococcus yayanosii CH1. The recombinant enzyme (PyASNase) exhibited maximal activity at pH 8.0 and 85 °C. Moreover, PyASNase demonstrated promising thermostability across temperatures ranging from 70 to 95 °C. The kinetic parameters of PyASNase for L-asparagine were a Km of 6.3 mM, a kcat of 1989s-1, and a kcat/Km of 315.7 mM-1 s-1. Treating potato samples with 10 U/mL of PyASNase at 85 °C for merely 10 min reduced the acrylamide content in the final product by 82.5%, demonstrating a high efficiency and significant advantage of PyASNase in acrylamide inhibition.

Design requirements for a digital storytelling application for people with mild cognitive impairment (MCI).

Background: The current digital storytelling applications present advantages for individuals with Mild Cognitive Impairment (MCI); however, there exists a notable oversight regarding their potential to facilitate group-based storytelling activities with this population. This study endeavors to identify design requirements for a more inclusive and accessible digital storytelling tool for people with MCI. Method: The methodological framework encompasses distinct stages, commencing with focus groups and interviews (Stage 1), followed by prototyping workshops (Stage 2) and qualitative prototype testing (Stage 3). The comprehensive three-stage research involved participants residing in Beijing, China, including 43 people with MCI aged 65-95 years (M = 79.09, SD = 8.99), with a mean Montreal Cognitive Assessment score of 21.91 (range = 18-26, SD = 2.40). Additionally, 17 care partners and 10 occupational or clinical therapists actively participated. Result: The culmination of the three-stage research process has yielded 12 discernible key design requirements. Preferred storytelling themes center around narratives designed to elicit positive emotions. The narrative material generation process involves a systematic approach, unlocking memories through carefully formulated questions. In memory retrieval, users are provided with hints, bolstering confidence and perpetuating a semblance of face-to-face interaction. The focus in story sharing lies in transcending mere narration and extending it to a wider audience. Conclusion: This case study centers on crafting a digital storytelling application to enhance social connections for people with MCI. It delves into crucial design requirements addressing memory challenges, emphasizing individual preparation and group sharing. The developed digital storytelling application demonstrates potential to offer valuable memory support and foster personal and collective connections. Future research will focus on formal testing to evaluate these outcomes.

Clinical value and risk factors of compression supporting screwsin patients with femoral neck fractures.

BACKGROUND: This study was performed with attempt to explore the clinical value and risk factors of compression supporting screws for the treatment of femoral neck fractures. METHODS: This retrospective analysis enrolled 102 patients with femoral neck fractures who admitted to our hospital from June 2020 to June 2022. Based on different screws during the operation, the participants were allocated into hollow screw group (52 cases, conventional fixation of parallel partial-thread hollow screw) and compression screw group (50 cases, compression screw fixation). RESULT: The incidence of complications (including internal fixation failure, nonunion, a vascular necrosis of the femoral head, shortening of the femoral neck by less than 10 mm, and lateral screw withdrawal, of the affected limb) in the compression screw group were significantly lower than those in the hollow screw group (P < 0.05). Patients enrolled in this study were followed up for 9 to 14 months, with an average follow-up time of (12.09 ± 1.87) months.The pain degree at 3 days, 10 days, and the last follow-up after operation in the compression screw group was evidently lower than that in the hollow screw group (P < 0.05). At the last follow-up, the improvment in hip joint function was more significant in the compression screw group than in the hollow screw group (P < 0.05). Univariate logistic regression analysis showed that the risk factors for complications in the treatment of femoral neck fractures with compression supporting screws were age, Pauwels type III fracture (modified Pauwels classification), and hip joint (≥ 90 points). In addition, the result of multivariate logistic regression analysis showed that the risk factors for complications in the treatment of femoral neck fractures with compression supporting screws were age, Pauwels type III fracture (modified Pauwels classification). CONCLUSION: Our findings demonstrated beneficial outcomes obtained by using compression supporting screw, in terms of effectively enhancing the recovery of patients with femoral neck fracture and reducing the associated complications.

Ni-Based Materials for Industrial Alkaline Hydrogen Production.

Hydrogen has been recognized as a green energy carrier, which can relieve energy shortage and environmental pollution. Currently, alkaline water electrolysis (AWE) driven by renewable energy to produce large-scale green hydrogen is a mainstream technology. However, tardy cathodic hydrogen evolution reaction (HER) and stability issue of catalysts make it challenging to meet the industrial requirements. Ni-based materials have attracted wide attention, thanks to their low cost and rich tuning possibilities, and many efforts have focused on their activity and stability. However, due to the significant discrepancy between laboratory and industrial conditions, these catalysts have not been widely deployed in industrial AWE. In this review, we first introduce the differences between laboratory and industrial stage, especially concerning equipment, protocols and evaluation metrics. To shorten these gaps, some strategies are proposed to improve the activity and stability of the Ni-based catalysts. Besides, some key issues related to the catalysts in industrial AWE device are also emphasized, including reverse-current and foreign ions in the electrolyte. Finally, the challenges and outlooks on the industrial alkaline AWE are discussed.

Microstructure Design and Dimensional Engineering of Nanomaterials for Electromagnetic Wave Absorption and Thermal Insulation.

Multifunctional materials integrated with electromagnetic wave absorption (EWA), thermal insulation, and lightweight properties are urgently indispensable for the flourishing advancement of space technology, which can simultaneously prevent electromagnetic detection and resist aerodynamic heating. To achieve excellent synergistic EWA and thermal insulation performance, the elaborate regulate the microstructure and dimension of nanomaterials has emerged as a captivating research direction. However, comprehending the structure-property relationships between microstructure, electromagnetic response, and thermal insulation mechanisms remains a significant challenge. Herein, a comprehensive perspective focuses on the microstructure design encompassing various dimensions of nanomaterials, providing a comprehensive understanding of correlations among structure, EWA, and thermal insulation. First, the cutting-edge mechanisms of EWA and thermal insulation are elaborated, followed by the relationship between the dimensions of nanomaterials. Moreover, the synergistic design methods of EWA and thermal insulation are explored. Lastly, this review summarizes the corresponding shortcomings and issues of current EWA-integrated thermal insulation materials and proposes breakthrough directions for the creation of materials with superior performance.

Preventive effects of transcutaneous CO2 application on disuse osteoporosis and muscle atrophy in a rat hindlimb suspension model.

We previously demonstrated that transcutaneous CO2 application promotes muscle fiber-type switching, fracture healing, and osteogenesis by increasing blood flow and angiogenesis. Here, we aimed to investigate the preventive effects of transcutaneous CO2 application on disuse osteoporosis and muscle atrophy in a rat hindlimb suspension model. Eleven-week-old male Sprague-Dawley rats were divided into hindlimb suspension (HS), HS with transcutaneous CO2 application (HSCO2), and control groups. HSCO2 rats were administered transcutaneous 100 % CO2 gas in their bilateral hindlimbs, five times a week for 20 min. After 3 weeks, we harvested the gastrocnemius, femur, and tibia for assessment. Histological analysis revealed a significant decrease in the gastrocnemius myofiber cross-sectional area in HS rats compared to the control rats, whereas HSCO2 rats exhibited a significant increase compared to HS rats. Micro-computed tomography showed significant bone atrophy in the trabecular and cortical bones of the femur in HS rats compared to those of the control rats, whereas significant improvement was noted in HSCO2 rats. Histological analysis of the proximal tibia revealed more marrow adipose tissue in the HS rats than in the control rats. However, in the HSCO2 rats, fewer marrow adipose tissue and osteoclasts were observed. Moreover, HSCO2 rats had more osteoblasts and higher expression of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) and vascular endothelial growth factor (VEGF) than the HS rats. The gastrocnemius and distal femur of HSCO2 rats also exhibited elevated PGC-1α and VEGF expression and upregulation of the myogenesis markers and osteogenesis markers compared to those of HS rats. This treatment effectively prevented disuse osteoporosis and muscle atrophy by promoting local angiogenesis and blood flow. PGC-1α is crucial for promoting this angiogenic pathway. Transcutaneous CO2 application may be a novel preventive procedure for disuse osteoporosis and muscle atrophy, complementing medication and rehabilitation.

Paeonia genus: a systematic review of active ingredients, pharmacological effects and mechanisms, and clinical applications for the treatment of cancer.

The main active constituents of plants of the Paeonia genus are known to have antitumor activity. Hundreds of compounds with a wide range of pharmacological activities, including monoterpene glycosides, flavonoids, tannins, stilbenes, triterpenoids, steroids, and phenolic compounds have been isolated. Among them, monoterpenes and their glycosides, flavonoids, phenolic acids, and other constituents have been shown to have good therapeutic effects on various cancers, with the main mechanisms including the induction of apoptosis; the inhibition of tumor cell proliferation, migration, and invasion; and the modulation of immunity. In this study, many citations related to the traditional uses, phytochemical constituents, antitumor effects, and clinical applications of the Paeonia genus were retrieved from popular and widely used databases such as Web of Science, Science Direct, Google Scholar, and PubMed using different search strings. A systematic review of the antitumor constituents of the Paeonia genus and their therapeutic effects on various cancers was conducted and the mechanisms of action and pathways of these phytochemicals were summarised to provide a further basis for antitumor research.

Developing the First Digital Occupational Therapy Dictionary Worldwide: A Promising Mobile Application Model for Occupational Therapy Service Providers and Recipients.

The purpose of this study was to develop the first English-Arabic occupational therapy dictionary mobile application that could be used by occupational therapy service providers and recipients and help fill the gap in understanding and communicating occupational therapy services. Google Play Store and App Store application stores were searched first to identify any current electronic occupational therapy dictionary. While developing the dictionary concept and structure, end users' needs, language, and culture were taken into consideration applying a user-friendly design, functionalities, and an easy-to-understand language with illustrative visual representations. Our search for currently available electronic occupational therapy dictionaries did not identify any mobile application on the official application stores for iPhone and Android. As a result, a conceptual model was created to develop a mobile application aiming to develop a comprehensive and user-friendly mobile electronic dictionary with over 2400 scientific terms translated and annotated from English to Arabic, more than 350 illustrative pictures, and special features to assist occupational therapy professionals and occupational therapy services recipients in looking up and understanding terminology used in rehabilitation and occupational therapy in the most convenient, fastest, and easiest way possible. The occupational therapy dictionary mobile application has helped create a unified terminology and a common language of shared understanding, proved to be a helpful tool of communicating important messages between Arab occupational therapy professionals and community members through providing an easy access to up-to-date comprehensive English-Arabic lexicography in occupational therapy. It has become the first digital occupational therapy dictionary worldwide and has been made available for everyone to download from Google Play and App Store on their smartphones, computers, or tablets free of charge. Further research is urgently needed for quality improvement and to further enrich Arabic content in occupational therapy through developing evidence-based mobile tools to be used in occupational therapy practice by Arabic-speaking population.

Establishment and clinical application of a droplet digital PCR method for the detection of Edwardsiella tarda.

Edwardsiella tarda (E. tarda) can infect humans and a variety of animals, including fish, amphibians, reptiles, birds, and mammals. However, a more highly sensitive, specific, and repeatable test for its detection is lacking. The objective of this study was to develop a highly sensitive, specific, and repeatable droplet digital polymerase chain reaction (ddPCR)-based method for the quantitative detection of E. tarda. The gyrB gene was selected as the target gene, and primers and probe were designed and synthesized. Using E. tarda genomic DNA as templates, the reaction method was optimized to establish a linear relationship with real-time PCR detection methods. The sensitivity, specificity, and repeatability of the method were analyzed, and clinical samples were tested. When the primer and probe concentrations were 900 and 300 nM, respectively, and the annealing temperature was 57°C, the efficiency of the ddPCR amplification reaction was highest and the boundary between positive and negative droplet distribution was clearest. The sensitivity was high, with detection limit being as low as 0.56 copies·µL-1; additionally, and a good linear relationship (R 2 = 0.9962) between ddPCR and real-time PCR detection, within the range of 1-25,000 copies·µL-1, was evident. The repeatability was good, with a detection coefficient of variation of 2.74%. There was no cross-reactivity with 15 other common pathogenic microorganisms in aquatic animals (Streptococcus agalactiae, Streptococcus iniae, Streptococcus suis type 2, Nocardia seriolae, Vibrio parahaemolyticus, Aeromonas sobria, red sea bream iridovirus, decapod iridescent virus 1, enterocytozoon hepatopenaei, carp edema virus, Koi herpesvirus, goldfish hematopoietic necrosis virus, tilapia lake virus, viral nervous necrosis virus, or grass carp reovirus) in positive samples. Among the 48 clinical samples, including Bahaba taipingensis and its live food fish, pond water samples, and routine monitoring samples (Koi), 21 were positive for E. tarda, consistent with the bacterial isolation and identification results. The E. tarda ddPCR detection method has high specificity, sensitivity, and repeatability, can more accurately quantify E. tarda, and provides a useful reference for research related to this bacterium.

Applications of plant-derived extracellular vesicles in medicine.

Plant-derived extracellular vesicles (EVs) are promising therapeutic agents owing to their natural abundance, accessibility, and unique biological properties. This review provides a comprehensive exploration of the therapeutic potential of plant-derived EVs and emphasizes their anti-inflammatory, antimicrobial, and tumor-inhibitory effects. Here, we discussed the advancements in isolation and purification techniques, such as ultracentrifugation and size-exclusion chromatography, which are critical for maintaining the functional integrity of these nanovesicles. Next, we investigated the diverse administration routes of EVs and carefully weighed their respective advantages and challenges related to bioavailability and patient compliance. Moreover, we elucidated the multifaceted mechanisms of action of plant-derived EVs, including their roles in anti-inflammation, antioxidation, antitumor activity, and modulation of gut microbiota. We also discussed the impact of EVs on specific diseases such as cancer and inflammatory bowel disease, highlighting the importance of addressing current challenges related to production scalability, regulatory compliance, and immunogenicity. Finally, we proposed future research directions for optimizing EV extraction and developing targeted delivery systems. Through these efforts, we envision the seamless integration of plant-derived EVs into mainstream medicine, offering safe and potent therapeutic alternatives across various medical disciplines.