Effectiveness of a gamified digital intervention based on lifestyle modification (iGAME) in secondary prevention: a protocol for a randomised controlled trial.

INTRODUCTION: Combating physical inactivity and reducing sitting time are one of the principal challenges proposed by public health systems. Gamification has been seen as an innovative, functional and motivating strategy to encourage patients to increase their physical activity (PA) and reduce sedentary lifestyles through behaviour change techniques (BCT). However, the effectiveness of these interventions is not usually studied before their use. The main objective of this study will be to analyse the effectiveness of a gamified mobile application (iGAME) developed in the context of promoting PA and reducing sitting time with the BCT approach, as an intervention of secondary prevention in sedentary patients. METHODS AND ANALYSIS: A randomised clinical trial will be conducted among sedentary patients with one of these conditions: non-specific low back pain, cancer survivors and mild depression. The experimental group will receive a 12-week intervention based on a gamified mobile health application using BCT to promote PA and reduce sedentarism. Participants in the control group will be educated about the benefits of PA. The International Physical Activity Questionnaire will be considered the primary outcome. International Sedentary Assessment Tool, EuroQoL-5D, MEDRISK Instruments and consumption of Health System resources will be evaluated as secondary outcomes. Specific questionnaires will be administered depending on the clinical population. Outcomes will be assessed at baseline, at 6 weeks, at the end of the intervention (12 weeks), at 26 weeks and at 52 weeks. ETHICS AND DISSEMINATION: The study has been approved by the Portal de Ética de la Investigación Biomédica de Andalucía Ethics Committee (RCT-iGAME 24092020). All participants will be informed about the purpose and content of the study and written informed consent will be completed. The results of this study will be published in a peer-reviewed journal and disseminated electronically and in print. TRIAL REGISTRATION NUMBER: NCT04019119.

Machine Learning on Prediction of Relative Physical Activity Intensity Using Medical Radar Sensor and 3D Accelerometer.

BACKGROUND: One of the most critical topics in sports safety today is the reduction in injury risks through controlled fatigue using non-invasive athlete monitoring. Due to the risk of injuries, it is prohibited to use accelerometer-based smart trackers, activity measurement bracelets, and smart watches for recording health parameters during performance sports activities. This study analyzes the synergy feasibility of medical radar sensors and tri-axial acceleration sensor data to predict physical activity key performance indexes in performance sports by using machine learning (ML). The novelty of this method is that it uses a 24 GHz Doppler radar sensor to detect vital signs such as the heartbeat and breathing without touching the person and to predict the intensity of physical activity, combined with the acceleration data from 3D accelerometers. METHODS: This study is based on the data collected from professional athletes and freely available datasets created for research purposes. A combination of sensor data management was used: a medical radar sensor with no-contact remote sensing to measure the heart rate (HR) and 3D acceleration to measure the velocity of the activity. Various advanced ML methods and models were employed on the top of sensors to analyze the vital parameters and predict the health activity key performance indexes. three-axial acceleration, heart rate data, age, as well as activity level variances. RESULTS: The ML models recognized the physical activity intensity and estimated the energy expenditure on a realistic level. Leave-one-out (LOO) cross-validation (CV), as well as out-of-sample testing (OST) methods, have been used to evaluate the level of accuracy in activity intensity prediction. The energy expenditure prediction with three-axial accelerometer sensors by using linear regression provided 97-99% accuracy on selected sports (cycling, running, and soccer). The ML-based RPE results using medical radar sensors on a time-series heart rate (HR) dataset varied between 90 and 96% accuracy. The expected level of accuracy was examined with different models. The average accuracy for all the models (RPE and METs) and setups was higher than 90%. CONCLUSIONS: The ML models that classify the rating of the perceived exertion and the metabolic equivalent of tasks perform consistently.

HPLC Analysis of Polyphenols Derived from Hungarian Aszú from Tokaj Wine Region and Its Effect on Inflammation in an In Vitro Model System of Endothelial Cells.

Many studies have been published in recent years regarding the fact that moderate wine consumption, as a part of a balanced diet can have a beneficial effect on human health. The biologically active components of wine continue to be the subject of intense research today. In this study, the bioactive molecules of Hungarian aszú from the Tokaj wine region were analyzed using high-performance liquid chromatography (HPLC) and investigated in an in vitro model system of endothelial cells induced by bacterial-derived lipopolysaccharide. The HPLC measurements were performed on a reversed phased column with gradient elution. The non-cytotoxic concentration of the active substance was determined based on 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyltetrazolium bromide (MTT)-, apoptosis, and necrosis assays. The antioxidant effect of the extract was determined by evaluating its ability to eliminate ROS. The expressions of the interleukin-(IL)1α, IL1-ß, IL-6, and IL-8 pro-inflammatory cytokines and nitric oxide synthase (eNOS) at the mRNA level were evaluated using a quantitative polymerase chain reaction (qPCR). We found that the lipopolysaccharides (LPS)-induced increases in the expressions of the investigated cytokines were significantly suppressed by Hungarian aszú extract, excluding IL-6. In our experimental setup, our treatment had a positive effect on the eNOS expression, which was impaired as a result of the inflammatory manipulation. In our experimental model, the Hungarian aszú extract decreased the LPS-induced increases in the expression of the investigated cytokines and eNOS at the mRNA level, which presumably had a positive effect on the endothelial dysfunction caused by inflammation due to its strong antioxidant and anti-inflammatory effects. Collectively, this research contributes to a more thorough understanding of the bioactive molecules of aszú from the Tokaj wine region.

AI-Assisted Fatigue and Stamina Control for Performance Sports on IMU-Generated Multivariate Times Series Datasets.

BACKGROUND: Optimal sports performance requires a balance between intensive training and adequate rest. IMUs provide objective, quantifiable data to analyze performance dynamics, despite the challenges in quantifying athlete training loads. The ability of AI to analyze complex datasets brings innovation to the monitoring and optimization of athlete training cycles. Traditional techniques rely on subjective assessments to prevent overtraining, which can lead to injury and underperformance. IMUs provide objective, quantitative data on athletes' physical status during action. AI and machine learning can turn these data into useful insights, enabling data-driven athlete performance management. With IMU-generated multivariate time series data, this paper uses AI to construct a robust model for predicting fatigue and stamina. MATERIALS AND METHODS: IMUs linked to 19 athletes recorded triaxial acceleration, angular velocity, and magnetic orientation throughout repeated sessions. Standardized training included steady-pace runs and fatigue-inducing techniques. The raw time series data were used to train a supervised ML model based on frequency and time-domain characteristics. The performances of Random Forest, Gradient Boosting Machines, and LSTM networks were compared. A feedback loop adjusted the model in real time based on prediction error and bias estimation. RESULTS: The AI model demonstrated high predictive accuracy for fatigue, showing significant correlations between predicted fatigue levels and observed declines in performance. Stamina predictions enabled individualized training adjustments that were in sync with athletes' physiological thresholds. Bias correction mechanisms proved effective in minimizing systematic prediction errors. Moreover, real-time adaptations of the model led to enhanced training periodization strategies, reducing the risk of overtraining and improving overall athletic performance. CONCLUSIONS: In sports performance analytics, the AI-assisted model using IMU multivariate time series data is effective. Training can be tailored and constantly altered because the model accurately predicts fatigue and stamina. AI models can effectively forecast the beginning of weariness before any physical symptoms appear. This allows for timely interventions to prevent overtraining and potential accidents. The model shows an exceptional ability to customize training programs according to the physiological reactions of each athlete and enhance the overall training effectiveness. In addition, the study demonstrated the model's efficacy in real-time monitoring performance, improving the decision-making abilities of both coaches and athletes. The approach enables ongoing and thorough data analysis, supporting strategic planning for training and competition, resulting in optimized performance outcomes. These findings highlight the revolutionary capability of AI in sports science, offering a future where data-driven methods greatly enhance athlete training and performance management.

Monitoring and recovery of hyperglycaemia-induced endothelial dysfunction with rheopheresis in diabetic lower extremity ulceration with hyperviscosity.

AIMS: Rheopheresis is an extracorporeal haematotherapy that improves haemorheological status by filtering proteins that enhance blood viscosity. It also has anti-inflammatory effects by removing inflammatory cytokines. Our study aims to examine the effects of rheopheresis on the endothelial status in diabetic lower extremity ulceration. METHODS: In vitro experiments were performed in a HUVEC model to mimic hyperglycaemic stress. We determined the changes in gene expression levels of IL-6, IL-8, TNF-alpha, endothelin convertase enzyme, ET-1, and NO synthase, as well as the ROS and intracellular GSH levels upon hyperglycaemia. In in vivo studies, two rheopheresis procedures were performed on seven patients with diabetic lower extremity ulceration with hyperviscosity, and we measured the changes in plasma concentrations of ET-1, TXB2, SOD enzyme activity, and extracellular components of the glutathione pool depending on treatments. RESULTS: Our results showed that hyperglycaemia increases endothelial expression of inflammatory cytokines, ET-1, and endothelin convertase enzyme, while NO synthase was decreased. As a result of rheopheresis, we observed decreased ET-1 and TXB2 concentrations in the plasma and beneficial changes in the parameters of the glutathione pool. CONCLUSION: To summarize our results, hyperglycaemia-induced oxidative stress and endothelial inflammation can be moderated by rheopheresis in diabetic lower extremity ulceration with hyperviscosity.

Comparison of the Modulating Effect of Anthocyanin-Rich Sour Cherry Extract on Occludin and ZO-1 on Caco-2 and HUVEC Cultures.

Increased permeability of the epithelial and endothelial cell layers results in the onset of pathogenic mechanisms. In both cell types, cell-cell connections play a regulatory role in altering membrane permeability. The aim of this study was to investigate the modulating effect of anthocyanin-rich extract (AC) on TJ proteins in inflammatory Caco-2 and HUVEC monolayers. Distribution of Occludin and zonula occludens-1 (ZO-1) were investigated by immunohistochemical staining and the protein levels were measured by flow cytometry. The mRNA expression was determined by quantitative real-time PCR. The transepithelial electrical resistance (TEER) values were measured during a permeability assay on HUVEC cell culture. As a result of inflammatory induction by TNF-α, redistribution of proteins was observed in Caco-2 cell culture, which was reduced by AC treatment. In HUVEC cell culture, the decrease in protein and mRNA expression was more dominant during inflammatory induction, which was compensated for by the AC treatment. Overall, AC positively affected the expression of the examined cell-binding structures forming the membrane on both cell types.

Reliability Study of Inertial Sensors LIS2DH12 Compared to ActiGraph GT9X: Based on Free Code.

The study's purpose was to assess the reliability of the LIS2DH12 in two different positions, using the commercial sensor Actigraph GT9X as a reference instrument. Five participants completed two gait tests on a treadmill. Firstly, both sensors were worn on the wrist and around the thigh. Each test consisted of a 1 min walk for participants to become accustomed to the treadmill, followed by a 2 min trial at ten pre-set speeds. Data from both sensors were collected in real-time. Intraclass correlation coefficient (ICC) was used to evaluate the equality of characteristics obtained by both sensors: maximum peaks, minimum peaks, and the mean of the complete signal (sequence of acceleration values along the time) by each axis and speed were extracted to evaluate the equality of characteristics obtained with LIS2DH12 compared to Actigraph. Intraclass correlation coefficient (ICC) was extracted, and a standard deviation of the mean was obtained from the data. Our results show that LIS2DH12 measurements present more reliability than Actigraph GT9X, ICC > 0.8 at three axes. This study concludes that LIS2DH12 is as reliable and accurate as Actigraph GT9X Link and, therefore, would be a suitable tool for future kinematic studies.

The Validity of the Energy Expenditure Criteria Based on Open Source Code through two Inertial Sensors.

Through this study, we developed and validated a system for energy expenditure calculation, which only requires low-cost inertial sensors and open source R software. Five healthy subjects ran at ten different speeds while their kinematic variables were recorded on the thigh and wrist. Two ActiGraph wireless inertial sensors and a low-cost Bluetooth-based inertial sensor (Lis2DH12), assembled by SensorID, were used. Ten energy expenditure equations were automatically calculated in a developed open source R software (our own creation). A correlation analysis was used to compare the results of the energy expenditure equations. A high interclass correlation coefficient of estimated energy expenditure on the thigh and wrist was observed with an Actigraph and Sensor ID accelerometer; the corrected Freedson equation showed the highest values, and the Santos-Lozano vector magnitude equation and Sasaki equation demonstrated the lowest one. Energy expenditure was compared between the wrist and thigh and showed low correlation values. Despite the positive results obtained, it was necessary to design specific equations for the estimation of energy expenditure measured with inertial sensors on the thigh. The use of the same formula equation in two different placements did not report a positive interclass correlation coefficient.

Tools for Evaluating the Content, Efficacy, and Usability of Mobile Health Apps According to the Consensus-Based Standards for the Selection of Health Measurement Instruments: Systematic Review.

BACKGROUND: There are several mobile health (mHealth) apps in mobile app stores. These apps enter the business-to-customer market with limited controls. Both, apps that users use autonomously and those designed to be recommended by practitioners require an end-user validation to minimize the risk of using apps that are ineffective or harmful. Prior studies have reviewed the most relevant aspects in a tool designed for assessing mHealth app quality, and different options have been developed for this purpose. However, the psychometric properties of the mHealth quality measurement tools, that is, the validity and reliability of the tools for their purpose, also need to be studied. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) initiative has developed tools for selecting the most suitable measurement instrument for health outcomes, and one of the main fields of study was their psychometric properties. OBJECTIVE: This study aims to address and psychometrically analyze, following the COSMIN guideline, the quality of the tools that are used to measure the quality of mHealth apps. METHODS: From February 1, 2019, to December 31, 2019, 2 reviewers searched PubMed and Embase databases, identifying mHealth app quality measurement tools and all the validation studies associated with each of them. For inclusion, the studies had to be meant to validate a tool designed to assess mHealth apps. Studies that used these tools for the assessment of mHealth apps but did not include any psychometric validation were excluded. The measurement tools were analyzed according to the 10 psychometric properties described in the COSMIN guideline. The dimensions and items analyzed in each tool were also analyzed. RESULTS: The initial search showed 3372 articles. Only 10 finally met the inclusion criteria and were chosen for analysis in this review, analyzing 8 measurement tools. Of these tools, 4 validated ≥5 psychometric properties defined in the COSMIN guideline. Although some of the tools only measure the usability dimension, other tools provide information such as engagement, esthetics, or functionality. Furthermore, 2 measurement tools, Mobile App Rating Scale and mHealth Apps Usability Questionnaire, have a user version, as well as a professional version. CONCLUSIONS: The Health Information Technology Usability Evaluation Scale and the Measurement Scales for Perceived Usefulness and Perceived Ease of Use were the most validated tools, but they were very focused on usability. The Mobile App Rating Scale showed a moderate number of validated psychometric properties, measures a significant number of quality dimensions, and has been validated in a large number of mHealth apps, and its use is widespread. It is suggested that the continuation of the validation of this tool in other psychometric properties could provide an appropriate option for evaluating the quality of mHealth apps.

Evaluation of Android and Apple Store Depression Applications Based on Mobile Application Rating Scale.

There are a large number of mobile applications that allow the monitoring of health status. The quality of the applications is only evaluated by users and not by standard criteria. This study aimed to examine depression-related applications in major mobile application stores and to analyze them using the rating scale tool Mobile Application Rating Scale (MARS). A search of digital applications for the control of symptoms and behavioral changes in depression was carried out in the two reference mobile operating systems, Apple (App Store) and Android (Play Store), by means of two reviewers with a blind methodology between September and October 2019 in stores from Spain and the United Kingdom. Eighteen applications from the Android Play Store and twelve from the App Store were included in this study. The quality of the applications was evaluated using the MARS scale from 1 (inadequate) to 5 (excellent). The average score of the applications based on the MARS was 3.67 ± 0.53. The sections with the highest scores were "Functionality" (4.51) and "Esthetics" (3.98) and the lowest "Application Subjective quality" (2.86) and "Information" (3.08). Mobile Health applications for the treatment of depression have great potential to influence the health status of users; however, applications come to the digital market without health control.

Behavior Change Techniques and the Effects Associated With Digital Behavior Change Interventions in Sedentary Behavior in the Clinical Population: A Systematic Review.

Background: Sedentary behavior (SB) negatively impact health and is highly prevalent in the population. Digital behavior change interventions (DBCIs) have been developed to modify behaviors such as SB by technologies. However, it is unknown which behavior change techniques (BCTs) are most frequently employed in SB as well as the effect associated with DBCIs in this field. The aim of this systematic review was: (a) to evaluate the BCT most frequently employed in digital health including all technologies available and interventions aimed at increasing physical activity (PA), reducing sedentary time, and improving adherence to exercise in the clinical population, and (b) to review the effect associated with DBCIs in this field. Methods: The database used was Medline, as well as Scopus, Scielo, and Google Scholar. For the search strategy, we considered versions of behavior/behavioral, mHealth/eHealth/telemedicine/serious game/gamification. The terms related to PA and SB were included, the criteria for inclusion were randomized clinical trials (RCTs), adults, intervention based on digital media, and outcome variable lifestyle modification; a last 5 years filter was included. Michie's Taxonomy was used to identify BCTs. The study was registered under the number PROSPERO CRD42019138681. Results: Eighteen RCTs were included in the present systematic review, 5 of them healthy adults, and 13 of them with some illness. Studies included 2298 sedentary individuals who were followed up for 5 weeks-3 years. The most used BCTs were goal setting, problem solving, review outcomes/goals, feedback on behavior and outcomes of behavior, self-monitoring of behavior, social support, information about health consequences, and behavior practice/rehearsal. The effect associated with DBCIs showed improvements, among several related to PA and physiologic self-reported and anthropometric outcomes. Conclusion: The BCTs most used in digital health to change outcomes related to SB were goals and planning, feedback and monitoring, social support, natural consequences, repetition, and substitution. Besides these findings, DBCIs are influenced by several factors like the type of intervention, patients' preferences and values, or the number of BCTs employed. More research is needed to determine with precision which DBCIs or BCTs are the most effective to reduce SB in the clinical population.

Assessment of the Quality of Mobile Applications (Apps) for Management of Low Back Pain Using the Mobile App Rating Scale (MARS).

Digital health interventions may improve different behaviours. However, the rapid proliferation of technological solutions often does not allow for a correct assessment of the quality of the tools. This study aims to review and assess the quality of the available mobile applications (apps) related to interventions for low back pain. Two reviewers search the official stores of Android (Play Store) and iOS (App Store) for localisation in Spain and the United Kingdom, in September 2019, searching for apps related to interventions for low back pain. Seventeen apps finally are included. The quality of the apps is measured using the Mobile App Rating Scale (MARS). The scores of each section and the final score of the apps are retrieved and the mean and standard deviation obtained. The average quality ranges between 2.83 and 4.57 (mean 3.82) on a scale from 1 (inadequate) to 5 (excellent). The best scores are found in functionality (4.7), followed by aesthetic content (mean 4.1). Information (2.93) and engagement (3.58) are the worst rated items. Apps generally have good overall quality, especially in terms of functionality and aesthetics. Engagement and information should be improved in most of the apps. Moreover, scientific evidence is necessary to support the use of applied health tools.

Effect of Anthocyanin-Rich Extract of Sour Cherry for Hyperglycemia-Induced Inflammatory Response and Impaired Endothelium-Dependent Vasodilation.

Diabetes mellitus (DM)-related morbidity and mortality are steadily rising worldwide, affecting about half a billion people worldwide. A significant proportion of diabetic cases are in the elderly, which is concerning given the increasing aging population. Proper nutrition is an important component in the effective management of diabetes in the elderly. A plethora of active substances of plant origin exhibit potency to target the pathogenesis of diabetes mellitus. The nutraceutical and pharmaceutical effects of anthocyanins have been extensively studied. In this study, the effect of Hungarian sour cherry, which is rich in anthocyanins, on hyperglycemia-induced endothelial dysfunction was tested using human umbilical cord vein endothelial cells (HUVECs). HUVECs were maintained under both normoglycemic (5 mM) and hyperglycemic (30 mM) conditions with or without two concentrations (1.50 ng/µL) of anthocyanin-rich sour cherry extract. Hyperglycemia-induced oxidative stress and inflammatory response and damaged vasorelaxation processes were investigated by evaluating the level of reactive oxygen species (ROS) and gene expression of four proinflammatory cytokines, namely, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-8 (IL-8), and interleukin-1α (IL-1α), as well as the gene expression of nitric oxide synthase (NOS) endothelin-1 (ET-1) and endothelin-converting enzyme-1 (ECE-1). It was found that hyperglycemia-induced oxidative stress was significantly suppressed by anthocyanin-rich sour cherry extract in a concentration-dependent manner. The gene expression of the tested proinflammatory cytokines increased under hyperglycemic conditions but was significantly reduced by both 1 and 50 ng/µL anthocyanin-rich sour cherry extract. Further, although increased ET-1 and ECE-1 expression due to hyperglycemia was reduced by anthocyanin-rich sour cherry extract, NOS expression was increased by the extract. Collectively, these data suggest that anthocyanin-rich sour cherry extract could alleviate hyperglycemia-induced endothelial dysfunction due to its antioxidant, anti-inflammatory, and vasorelaxant effects.

Allithiamine Alleviates Hyperglycaemia-Induced Endothelial Dysfunction.

Diabetes mellitus-related morbidity and mortality is a rapidly growing healthcare problem, globally. Several nutraceuticals exhibit potency to target the pathogenesis of diabetes mellitus. The antidiabetic effects of compounds of garlic have been extensively studied, however, limited data are available on the biological effects of a certain garlic component, allithiamine. In this study, allithiamine was tested using human umbilical cord vein endothelial cells (HUVECs) as a hyperglycaemic model. HUVECs were isolated by enzymatic digestion and characterized by flow cytometric analysis using antibodies against specific marker proteins including CD31, CD45, CD54, and CD106. The non-cytotoxic concentration of allithiamine was determined based on MTT, apoptosis, and necrosis assays. Subsequently, cells were divided into three groups: incubating with M199 medium as the control; or with 30 mMol/L glucose; or with 30 mMol/L glucose plus allithiamine. The effect of allithiamine on the levels of advanced glycation end-products (AGEs), activation of NF-κB, release of pro-inflammatory cytokines including IL-6, IL-8, and TNF-α, and H2O2-induced oxidative stress was investigated. We found that in the hyperglycaemia-induced increase in the level of AGEs, pro-inflammatory changes were significantly suppressed by allithiamine. However, allithiamine could not enhance the activity of transketolase, but it exerts a potent antioxidant effect. Collectively, our data suggest that allithiamine could alleviate the hyperglycaemia-induced endothelial dysfunction due to its potent antioxidant and anti-inflammatory effect by a mechanism unrelated to the transketolase activity.

Anthocyanin-Rich Sour Cherry Extract Attenuates the Lipopolysaccharide-Induced Endothelial Inflammatory Response.

The anthocyanin content of Hungarian sour cherry is remarkable based on our preliminary investigations. Nutraceutical and pharmaceutical effects of anthocyanins have been extensively studied. The objective of this work was to investigate the the effect of purified sour cherry extract using human umbilical cord vein endothelial cells (HUVECs) as the inflammatory model. HUVECs were isolated by enzymatic digestion and characterized by flow cytometry. The optimal concentration range of sour cherry extract was selected based on MTT, apoptosis, and necrosis assays. Cells were divided into three groups, incubating with M199 medium as control, or with lipopolysaccharide (LPS) or with LPS plus anthocyanin extract (ACE). The effect of sour cherry extract on oxidative stress, pro-inflammatory factors, and arachidonic pathway was investigated. An amount of 50 µg/mL ACE (ACE50) was able to increase the level of glutathione and decrease the ROS, thereby improving the unbalanced redox status in inflammation. ACE50 lowered pro-inflammatory cytokine levels including Interleukin-6 (IL-6), regulated on activation, normal T cell expressed and secreted (RANTES), granulocyte-macrophage colony-stimulating factor (GM-CSF), and tumor necrosis factor alpha (TNF-α). ACE50 affected the arachidonic acid pathway by reducing the LPS-induced enzyme expression (cyclooxygenase-1, cyclooxygenase-2, and prostacyclin synthase). The extract under investigation seems to have a pleiotropic effect including anti-oxidative, anti-inflammatory, hemostatic, and vasoactive effects. Our results indicate that purified sour cherry extract could reduce the LPS-induced inflammatory response, thereby improving endothelial dysfunction.

Evaluation of Objective Signs and Subjective Symptoms of Dry Eye Disease in Patients with Inflammatory Bowel Disease.

AIM: To evaluate tear film parameters and relationship of objective clinical signs and subjective symptoms of dry eye disease (DED) in inflammatory bowel disease (IBD) subgroups. METHODS: 39 patients with Crohn's disease (CD), 26 patients with ulcerative colitis (UC), and 39 control persons with no ocular symptoms or surface disorders were included in this prospective, case-control, and cross-sectional study. The ocular surface disease index (OSDI) questionnaire was applied to evaluate dry eye symptoms, and objective tests of DED were performed on both eyes of each subject. RESULTS: The average of OSDI scores was 30.59 (±16.68) in CD patients, 24.67 (±23.48) in UC patients, and 11.19 (±5.8) in controls. Except for tear film breakup time (tBUT) and Schirmer-I values other objective parameters were better in UC patients, than in CD patients. CD patients rather than UC patients tend to develop DED. This was associated with immunosuppressant and TNF-α inhibitor use. CONCLUSIONS: Clinicians must be aware of the spectrum of DED involvement in IBD and suggest using artificial tears in order to decrease severity of ocular complications.

Isolation of allithiamine from Hungarian red sweet pepper seed (Capsicum annuum L.).

A natural fat-soluble thiamine derivative, namely N-[(4-amino-2-methylpyrimidin-5-yl)methyl]-N-[(2E)-5-hydroxy-3-(prop-2-en-1-yldisulfanyl)pent-2-en-2-yl]formamide (allithiamine) has been identified only in garlic (Allium sativum) until now. Hungarian red sweet pepper (Capsicum annuum) was found as a new source of allithiamine. Extraction procedure and analytical method were developed for the isolation of allithiamine and a chemical synthesis of the compound was also developed. First solid-liquid extraction was performed with 96 % ethanol to isolate allithiamine from pepper seeds. Thereafter, solid phase extraction was applied from ethanolic extract using C18 cartridge to concentrate and purify samples for further analysis. The structure of the synthesized and the isolated compounds was verified by reverse phase HPLC, HPLC-MS, MALD-TOF MS and NMR. Furthermore, effect of allithiamine was investigated on streptozotocin-induced diabetic mice with neuropathy. The results show that neuropathic pain sensation is improved by allithiamine treatment similarly to benfothiamine.

Determination of Flavonoid and Proanthocyanidin Profile of Hungarian Sour Cherry.

Hungarian sour cherries (SC) are excellent source of anthocyanin (concentrations (100⁻300 mg in 100 g fresh fruit) and melatonin (0.15 mg in 100 g fresh fruit), but other flavonoid derivatives also can be isolated by aqueous alcoholic extraction. We have developed a new process for extracting non-extractable procyanidines bound to the membrane, proteins, and fibers. These compounds were seperated with UHPLC-MS methods, and the structure of individual components were identified on the basis of their mass fragmentation spectra. The antioxidant capacity of soluble and non-soluble antioxidants were measured with ferric reducing antioxidant power (FRAP), 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity (DPPH), trolox equivalent antioxidant capacity (TEAC) assays, and compared to the new measurement methods of water-soluble antioxidant capacity (ACW), lipid-soluble antioxidant capacity (ACL). Furthermore, total phenolic content (TPC) and total procyanidin content (PAC) were determinated. As a result of our investigation, we found that the solvent combination, where in the first step is water⁻ethanol (1:1), then 100% ethanol were suitable for the extraction of the extractable antioxidants. However, the chemiluminescence method that is based on the elimination of the superoxide radical is more accurate than other colorimetric methods which measure antioxidant capacity.

Selective targeted delivery of TNFalpha to tumor blood vessels.

We sought to enhance the selective toxicity of tumor necrosis factor alpha (TNFalpha) to permit its systemic use in cancer therapy. Because ligand-targeted therapeutics have proven successful in improving the selective toxicity of drugs, we prepared a fusion protein (L19mTNFalpha) composed of mouse TNFalpha and a high-affinity antibody fragment (L19 scFv) to the extradomain B (ED-B) domain of fibronectin, a marker of angiogenesis. L19mTNFalpha was expressed in mammalian cells, purified, and characterized. L19mTNFalpha was an immunoreactive and biologically active homotrimer. Radiolabeled L19mTNFalpha selectively targeted tumor neovasculature in tumor-bearing mice, where it accumulated selectively and persistently (tumor-to-blood ratio of the percentage of injected dose per gram [%ID/g] of 700, 48 hours from injection). L19mTNFalpha showed a greater anticancer therapeutic activity than both mTNFalpha and TN11mTNFalpha, a control fusion protein in which an antibody fragment, irrelevant in the tumor model used, substituted for L19. This activity was further dramatically enhanced by its combination with melphalan or the recently reported fusion protein L19-IL2. In conclusion, L19mTNFalpha allows concentrating therapeutically active doses of TNFalpha at the tumor level, thus opening new possibilities for the systemic use of TNFalpha in cancer therapy.

Expression of extradomain-B-containing fibronectin in subretinal choroidal neovascular membranes.

PURPOSE: To investigate the presence of the fibronectin isoform containing the extradomain B (B-FN), a marker-protein of angiogenesis, in surgically excised human choroidal neovascular membranes (CNVM) to evaluate whether B-FN could be used as a therapeutic target for specific antibody-photosensitizer immunoconjugates. DESIGN: Laboratory investigation. METHODS: The setting was an institutional practice. The study population consisted of 15 eyes (15 patients) with CNVM undergoing membrane excision (four eyes with age-related macular degeneration, seven with pathologic myopia and four with multifocal choroiditis). The control group consisted of eight eye bank eyes (four subjects) without choroidal neovascularization. Light microscopic immunohistochemistry on cryostat sections of tissues was obtained. B-FN was detected by a human recombinant antibody, CGS-1, and compared with immunostaining for endothelial cells with factor VIII-related antigen. The main outcome measure was the presence of CGS-1 positively stained cells or areas of the extracellular matrix. Staining of CGS-1 was scored on a scale from 0 to 3. RESULTS: Fourteen of 15 neovascular membranes stained strongly with CGS-1 (score 2 or 3). One membrane from a patient with pathologic myopia was negatively stained (score 0). CGS-1 positive staining was detected around endothelial cells and in the extracellular matrix of CNVMs. The retina of eyes without choroidal neovascularization was negative with CGS-1 in all eight donor eyes, while the choroid contained some weakly CGS-1 positive cells (score 0 and 1, respectively). CONCLUSIONS: The extradomain B is abundantly expressed in CNVMs, but its expression is more restricted in eyes harboring no apparent choroidal neovascularization. In the future, B-FN might serve as a target for the delivery of antibody-photosensitizer immunoconjugates to newly developed vessels to enhance the selectivity of photodynamic therapy.