ABSTRACT
La metodología de Planificación Centrada en la Persona (PCP) cada vez tiene mayor impacto en España. Comenzando desde las distintas legislaciones que regulan la atención a este colectivo en las diferentes autonomías y terminando en los centros que proveen este servicio. No obstante, existe escasa literatura internacional de estudios empíricos a grandes escalas que sitúen este enfoque metodológico en una posición relevante que garantice la eficacia de la PCP. El objetivo principal de este estudio es conocer el estado del uso de la metodología de PCP a través de estudios avalados empíricamente que sostengan tanto beneficios como limitaciones durante los últimos 10 años (2012-2022). Para ello, se ha realizado una revisión sistemática desde las directrices de PRISMA (2020), que incluye un total de 31 artículos. Como conclusión, se han descubierto más beneficios que limitaciones entre las que destacan las ventajas en su uso para las personas con discapacidad intelectual y del desarrollo y las mejoras de aspectos relacionados con la autodeterminación. No obstante, las limitaciones prevalecen por la falta de apoyos y recursos adecuados de las organizaciones para responder a una planificación centrada en la persona y la necesidad de formación de las personas implicadas en la elaboración de la PCP, lo que genera la incógnita de si se están realizando buenas prácticas en el uso de dicha metodología. (AU)
The methodology of Person Centered Planning (PCP) is having an increasing impact in Spain. Starting from the different legislations that regulate the attention to this group in the different autonomous regions and ending in the centers that provide this service. However, there is little international literature on large-scale empirical studies that place this methodological approach in a relevant position to guarantee the efficacy of PCP. The main objective of this study is to know the status of the use of PCP methodology through empirically supported studies that sustain both benefits and limitations during the last 10 years (2012-2022). For this purpose, a systematic review has been conducted since the PRISMA guidelines (2020), including a total of 31 articles. As a conclusion, more benefits than limitations have been found, among which the advantages in its use for people with intellectual and developmental disabilities and improvements in aspects related to self-determination stand out. However, limitations prevail due to the lack of adequate support and resources from organizations to respond to person-centered planning and the need for training of the people involved in the development of the PCP, which raises the question of whether good practices are being carried out in the use of this methodology. (AU)
Subject(s)
Developmental Disabilities , Intellectual Disability , Disabled Persons , SpainABSTRACT
La metodología de Planificación Centrada en la Persona (PCP) cada vez tiene mayor impacto en España. Comenzando desde las distintas legislaciones que regulan la atención a este colectivo en las diferentes autonomías y terminando en los centros que proveen este servicio. No obstante, existe escasa literatura internacional de estudios empíricos a grandes escalas que sitúen este enfoque metodológico en una posición relevante que garantice la eficacia de la PCP. El objetivo principal de este estudio es conocer el estado del uso de la metodología de PCP a través de estudios avalados empíricamente que sostengan tanto beneficios como limitaciones durante los últimos 10 años (2012-2022). Para ello, se ha realizado una revisión sistemática desde las directrices de PRISMA (2020), que incluye un total de 31 artículos. Como conclusión, se han descubierto más beneficios que limitaciones entre las que destacan las ventajas en su uso para las personas con discapacidad intelectual y del desarrollo y las mejoras de aspectos relacionados con la autodeterminación. No obstante, las limitaciones prevalecen por la falta de apoyos y recursos adecuados de las organizaciones para responder a una planificación centrada en la persona y la necesidad de formación de las personas implicadas en la elaboración de la PCP, lo que genera la incógnita de si se están realizando buenas prácticas en el uso de dicha metodología. (AU)
The methodology of Person Centered Planning (PCP) is having an increasing impact in Spain. Starting from the different legislations that regulate the attention to this group in the different autonomous regions and ending in the centers that provide this service. However, there is little international literature on large-scale empirical studies that place this methodological approach in a relevant position to guarantee the efficacy of PCP. The main objective of this study is to know the status of the use of PCP methodology through empirically supported studies that sustain both benefits and limitations during the last 10 years (2012-2022). For this purpose, a systematic review has been conducted since the PRISMA guidelines (2020), including a total of 31 articles. As a conclusion, more benefits than limitations have been found, among which the advantages in its use for people with intellectual and developmental disabilities and improvements in aspects related to self-determination stand out. However, limitations prevail due to the lack of adequate support and resources from organizations to respond to person-centered planning and the need for training of the people involved in the development of the PCP, which raises the question of whether good practices are being carried out in the use of this methodology. (AU)
Subject(s)
Developmental Disabilities , Intellectual Disability , Disabled Persons , SpainABSTRACT
This study aimed to enhance the extracellular polymeric substances (EPS) production of Virgibacillus dokdonensis VITP14 and explore its antioxidant potential. EPS and biomass production by VITP14 strain were studied under different culture parameters and media compositions using one factor at a time method. Among different nutrient sources, glucose and peptone were identified as suitable carbon and nitrogen sources. Furthermore, the maximum EPS production was observed at 5% of inoculum size, 5 g/L of NaCl, and 96 h of fermentation. Response surface methodology was employed to augment EPS production and investigate the optimal levels of nutrient sources with their interaction. The strain was observed to produce actual maximum EPS of about 26.4 g/L for finalized optimum medium containing glucose 20 g/L, peptone 10 g/L, and NaCl 50 g/L while the predicted maximum EPS was 26.5 g/L. There was a nine fold increase in EPS production after optimization study. Additionally, EPS has exhibited significant scavenging, reducing, and chelating potential (>85%) at their higher concentration. This study imparts valuable insights into optimizing moderately halophilic bacterial EPS production and evaluating its natural antioxidant properties. According to findings, V. dokdonensis VITP14 was a promising isolate that will provide significant benefits to biopolymer producing industries.
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This study aimed to evaluate the sous-vide cooking and ficin treatment effects on the tenderness of beef steak and optimize it for the elderly using response surface methodology (RSM). The M. semitendinosus (ST) from Chikso cattle was shaped into 5 × 5 × 2.54 cm pieces. Ficin solution was injected into the ST steak at 10% of the meat weight, and sous-vide cooked in a water bath at 65 °C for 6 or 12 h. As ficin concentration increased, L*- and a*-value, shear force, and hardness decreased, while soluble peptides increased (P < 0.05). As cooking time increased, cooking loss and collagen solubility of the steak increased (P < 0.05). An interaction effect between ficin and sous-vide cooking was found in L*- and a*-value, shear force, hardness, and soluble peptides (P < 0.05). A model to optimize the hardness for elderly people was established (R2 = 0.7991). Optimization conditions by RSM were 0.86 U/L with 8.87 h (23 N/cm3) for tooth intake (grade 1), 16.31 U/L with 13.24 h (3 N/cm3) for gums intake (grade 2), according to KS H 4897 and Universal Design Foods concept for the elderly. These optimized conditions enable the production of customized products tailored to the oral conditions of elderly people.
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Behavior analysts in research and clinical practice are interested in an ever-expanding array of topics. They are compelled to explore the social validity of the interventions they propose and the findings they generate. As the field moves in these important directions, qualitative methods are becoming increasingly relevant. Representing a departure from small-n design favored by behavior analysts, qualitative approaches provide analysts a unique set of tools to answer questions that prioritize voice, experience, and understandings in context. Despite recognition of the value of qualitative approaches in other disciplines, application of qualitative methods in behavior analysis remains limited. One likely explanation is that behavior analysts are not yet fluent in applying qualitative approaches within their clinical and research investigations. To address this issue, exploration of qualitative research approaches in behavior analytic literature is needed, alongside practical advice for analysts who are interested in using qualitative methods. This article briefly outlines qualitative literature which pertains to behavior analysts wanting to incorporate qualitative methods into their inquiries. Attention is primarily drawn to the need for coherence in designing and implementing a robust qualitative study that aligns with the behavior analyst's aims and perspective on knowing. A set of guiding questions are provided to orient behavior analysts to considerations in qualitative research and outline how analysts can conceptualize a strong qualitative study. This article aims to support increased application of qualitative methods by behavior analysts, where these methods best address the function of the behavior analytic investigation.
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In this present study, a three-factor Box-Behnken, response surface methodology (RSM) design was employed to optimize the skimmed milk powder (SMP)/whey protein concentrate (WPC) ratio (0.25-0.75%w/v) as a source of milk protein, inulin (1-2%w/v), and honey (4-6%w/v) for production of high-quality goat milk yoghurt (GMY). The resulting ANOVA and response surface equations revealed the significant effect (p < 0.05) of these variables on the various attributes such as total solid (%), pH, titratable acidity [(LA) % by weight], syneresis (%), DPPH (% inhibition), viscosity (m.Paâ s), whiteness index (WI), and overall acceptability (OA). The coefficient of determination (R2) for all response variables ranged from 0.88 to 0.99. Lack-of-fit tests resulted in non-significant F-values. The optimal conditions were determined as SMP/WPC at 0.36%w/v, inulin at 1.00%w/v, and honey at 6.00%w/v. The optimum values for total solid, pH, titratable acidity, syneresis, DPPH, viscosity, WI, and OA were 22.03, 4.46, 0.77, 6.34, 25.20, 182.30, 76.29 and 8.37, respectively with desirability value of 0.95.
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Wastewater textile dye treatment is a challenge that requires the development of eco-friendly technology to avoid the alarming problems associated with water scarcity and health-environment. This study investigated the potential of phengite clay as naturally low-cost abundant clay from Tamgroute, Morocco (TMG) that was activated with a 0.1M NaOH base (TMGB) after calcination at 850°C for 3 hours (TMGC) before its application in the Congo red (CR) anionic dye from the aqueous solution. The effect of various key operational parameters: adsorbent dose, contact time, dye concentration, pH, temperature, and the effect of salts, was studied by a series of adsorption experiments in a batch system, which affected the adsorption performance of TMG, TMGC, and TMGB for CR dye removal. In addition, the properties of adsorption kinetics, isotherms, and thermodynamics were also studied. Experimental results showed that optimal adsorption occurred at an acidic pH. At a CR concentration of 100 mg L-1, equilibrium elimination rates were 68%, 38%, and 92% for TMG, TMGC, and TMGB, respectively. The adsorption process is rapid, follows pseudo-second-order kinetics, and is best described by a Temkin and Langmuir isotherm. The thermodynamic parameters indicated that the adsorption of CR onto TMGB is endothermic and spontaneous. The experimental values of CR adsorption on TMGB are consistent with the predictions of the response surface methodology. These led to a maximum removal rate of 99.97% under the following conditions: pH =2, TMGB dose of 7g L-1, and CR concentration of 50 mg L-1. The adsorbent TMGB's relatively low preparation cost of around $2.629 g-1 and its ability to regenerate in more than 6 thermal calcination cycles with a CR removal rate of around 56.98%, stimulate its use for textile effluent treatment on a pilot industrial scale.
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Despite significant advancements in ichthyoplankton collection and data processing, challenges persist in the taxonomic identification of these organisms, particularly their eggs. To overcome these challenges, a novel technique has been developed to facilitate the identification of live eggs collected directly in wild. This user-friendly technique includes the collection, processing of the material, and field incubation. Sampling must be conducted using a pelagic net towed at low speed, preferably during early evening. The material processing involves pre-sorting and sorting to remove eggs and larvae. The separated eggs, kept in an aerated bowl, can be identified based on their morphological and meristic characteristics. Unidentified eggs can be placed in plastic bags with oxygen and incubated directly in the aquatic environment for 48-72 h. After this incubation period, the hatched larvae at the yolk-sac or preflexion stage, are identified to the lowest possible taxonomic level. Depending on the study's purpose, hatched larvae and field-collected larvae can be transported to research centers for further development, released back into the natural environment, or fixed to complete the collection. The application of this technique supports management and monitoring programs by identifying spawning areas through egg identification, forming broodstock, and replenishing threatened species, thereby enhancing scientific collections of ichthyoplankton. Additionally, it reduces mortality in ichthyoplankton techniques, including endangered species. Therefore, we believe that this novel taxonomic technique for identifying live ichthyoplankton represents a paradigm shift in the monitoring, management, and conservation of fish, as well as in ecological stewardship and advances in this area of research.
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The dyeing process of textile materials is inherently intricate, influenced by a myriad of factors, including dye concentration, dyeing time, pH level, temperature, type of dye, fiber composition, mechanical agitation, salt concentration, mordants, fixatives, water quality, dyeing method, and pre-treatment processes. The intricacy of achieving optimal settings during dyeing poses a significant challenge. In response, this study introduces a novel algorithmic approach that integrates response surface methodology (RSM), artificial neural network (ANN), and genetic algorithm (GA) techniques for the precise fine-tuning of concentration, time, pH, and temperature. The primary focus is on quantifying color strength, represented as K/S, as the response variable in the dyeing process of polyamide 6 and woolen fabric, utilizing plum-tree leaves as a sustainable dye source. Results indicate that ANN (R2 ~ 1) performs much better than RSM (R2 > 0.92). The optimization results, employing ANN-GA integration, indicate that a concentration of 100 wt.%, time of 86.06 min, pH level of 8.28, and a temperature of 100 °C yield a K/S value of 10.21 for polyamide 6 fabric. Similarly, a concentration of 55.85 wt.%, time of 120 min, pH level of 5, and temperature of 100 °C yield a K/S value of 7.65 for woolen fabric. This proposed methodology not only paves the way for sustainable textile dyeing but also facilitates the optimization of diverse dyeing processes for textile materials.
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An increasing number of psychological experiments with children are being conducted using online platforms, in part due to the COVID-19 pandemic. Individual replications have compared the findings of particular experiments online and in-person, but the general effect of data collection method on data collected from children is still unknown. Therefore, the goal of the current meta-analysis is to estimate the average difference in effect size for developmental studies conducted online compared to the same studies conducted in-person. Our pre-registered analysis includes 211 effect sizes calculated from 30 papers with 3282 children, ranging in age from four months to six years. The estimated effect size for studies conducted online was slightly smaller than for their counterparts conducted in-person, a difference of d = -.05, but this difference was not significant, 95% CI = [-.17, .07]. We examined several potential moderators of the effect of online testing, including the role of dependent measure (looking vs verbal), online study method (moderated vs unmoderated), and age, but none of these were significant. The literature to date thus suggests-on average-small differences in results between in-person and online experimentation.
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This study tackles the Garden of Forking Paths, as a challenge for replicability and reproducibility of ERP studies. Here, we applied a multiverse analysis to a sample ERP N400 dataset, donated by an independent research team. We analyzed this dataset using 14 pipelines selected to showcase the full range of methodological variability found in the N400 literature using systematic review approach. The selected pipelines were compared in depth by looking into statistical test outcomes, descriptive statistics, effect size, data quality, and statistical power. In this way we provide a worked example of how analytic flexibility can impact results in research fields with high dimensionality such as ERP, when analyzed using standard null-hypothesis significance testing. Out of the methodological decisions that were varied, high-pass filter cut-off, artifact removal method, baseline duration, reference, measurement latency and locations, and amplitude measure (peak vs. mean) were all shown to affect at least some of the study outcome measures. Low-pass filtering was the only step which did not notably influence any of these measures. This study shows that even some of the seemingly minor procedural deviations can influence the conclusions of an ERP study. We demonstrate the power of multiverse analysis in both identifying the most reliable effects in a given study, and for providing insights into consequences of methodological decisions.
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BACKGROUND: The COVID-19 pandemic placed an additional mental health burden on individuals and families, resulting in widespread service access problems. Digital mental health interventions suggest promise for improved accessibility. Recent reviews have shown emerging evidence for individual use and early evidence for multiusers. However, attrition rates remain high for digital mental health interventions, and additional complexities exist when engaging multiple family members together. OBJECTIVE: As such, this scoping review aims to detail the reported evidence for digital mental health interventions designed for family use with a focus on the build and design characteristics that promote accessibility and engagement and enable cocompletion by families. METHODS: A systematic literature search of MEDLINE, Embase, PsycINFO, Web of Science, and CINAHL databases was conducted for articles published in the English language from January 2002 to March 2024. Eligible records included empirical studies of digital platforms containing some elements designed for cocompletion by related people as well as some components intended to be completed without therapist engagement. Platforms were included in cases in which clinical evidence had been documented. RESULTS: Of the 9527 papers reviewed, 85 (0.89%) met the eligibility criteria. A total of 24 unique platforms designed for co-use by related parties were identified. Relationships between participants included couples, parent-child dyads, family caregiver-care recipient dyads, and families. Common platform features included the delivery of content via structured interventions with no to minimal tailoring or personalization offered. Some interventions provided live contact with therapists. User engagement indicators and findings varied and included user experience, satisfaction, completion rates, and feasibility. Our findings are more remarkable for what was absent in the literature than what was present. Contrary to expectations, few studies reported any design and build characteristics that enabled coparticipation. No studies reported on platform features for enabling cocompletion or considerations for ensuring individual privacy and safety. None examined platform build or design characteristics as moderators of intervention effect, and none offered a formative evaluation of the platform itself. CONCLUSIONS: In this early era of digital mental health platform design, this novel review demonstrates a striking absence of information about design elements associated with the successful engagement of multiple related users in any aspect of a therapeutic process. There remains a large gap in the literature detailing and evaluating platform design, highlighting a significant opportunity for future cross-disciplinary research. This review details the incentive for undertaking such research; suggests design considerations when building digital mental health platforms for use by families; and offers recommendations for future development, including platform co-design and formative evaluation.
Subject(s)
COVID-19 , Family , Humans , Family/psychology , Mental Health Services , Telemedicine , Mental Health , SARS-CoV-2 , PandemicsABSTRACT
The development of geopolymer concrete offers promising prospects for sustainable construction practices due to its reduced environmental impact compared to conventional Portland cement concrete. However, the complexity involved in geopolymer concrete mix design often poses challenges for engineers and practitioners. In response, this study proposes a simplified approach for designing geopolymer concrete mixtures, drawing upon principles from Portland cement concrete mix design standards and recommended molar ratios of oxides involved in geopolymer synthesis. The proposed methodology aims to streamline the mix design process while optimizing key factors such as chemical composition, alkali activation solution, water content, and curing conditions to achieve desired compressive strength and workability. By leveraging commonalities between Portland cement concrete and geopolymer concrete, this approach seeks to facilitate the adoption of geopolymer concrete in practical construction applications. The proposed mix design guidelines have been validated through examples for concrete cured under different conditions, including outdoor and oven curing. Future research should focus on validating the proposed methodology through experimental studies and exploring cost-effective alternatives for alkali activation solutions to enhance the feasibility and scalability of geopolymer concrete production. Overall, the proposed simplified approach holds promise for advancing the utilization of geopolymer concrete as a sustainable alternative in the construction industry.
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BACKGROUND: In-depth interviews are a common method of qualitative data collection, providing rich data on individuals' perceptions and behaviors that would be challenging to collect with quantitative methods. Researchers typically need to decide on sample size a priori. Although studies have assessed when saturation has been achieved, there is no agreement on the minimum number of interviews needed to achieve saturation. To date, most research on saturation has been based on in-person data collection. During the COVID-19 pandemic, web-based data collection became increasingly common, as traditional in-person data collection was possible. Researchers continue to use web-based data collection methods post the COVID-19 emergency, making it important to assess whether findings around saturation differ for in-person versus web-based interviews. OBJECTIVE: We aimed to identify the number of web-based interviews needed to achieve true code saturation or near code saturation. METHODS: The analyses for this study were based on data from 5 Food and Drug Administration-funded studies conducted through web-based platforms with patients with underlying medical conditions or with health care providers who provide primary or specialty care to patients. We extracted code- and interview-specific data and examined the data summaries to determine when true saturation or near saturation was reached. RESULTS: The sample size used in the 5 studies ranged from 30 to 70 interviews. True saturation was reached after 91% to 100% (n=30-67) of planned interviews, whereas near saturation was reached after 33% to 60% (n=15-23) of planned interviews. Studies that relied heavily on deductive coding and studies that had a more structured interview guide reached both true saturation and near saturation sooner. We also examined the types of codes applied after near saturation had been reached. In 4 of the 5 studies, most of these codes represented previously established core concepts or themes. Codes representing newly identified concepts, other or miscellaneous responses (eg, "in general"), uncertainty or confusion (eg, "don't know"), or categorization for analysis (eg, correct as compared with incorrect) were less commonly applied after near saturation had been reached. CONCLUSIONS: This study provides support that near saturation may be a sufficient measure to target and that conducting additional interviews after that point may result in diminishing returns. Factors to consider in determining how many interviews to conduct include the structure and type of questions included in the interview guide, the coding structure, and the population under study. Studies with less structured interview guides, studies that rely heavily on inductive coding and analytic techniques, and studies that include populations that may be less knowledgeable about the topics discussed may require a larger sample size to reach an acceptable level of saturation. Our findings also build on previous studies looking at saturation for in-person data collection conducted at a small number of sites.
Subject(s)
COVID-19 , Interviews as Topic , Humans , Sample Size , Interviews as Topic/methods , Qualitative Research , SARS-CoV-2 , Pandemics , Data Collection/methods , InternetABSTRACT
Considering comprehensive utilization of natural products, isolation and activity determination processes of bioactive compounds are essential. In this study, a combined high-speed countercurrent chromatography (HSCCC) with preparative HPLC method was developed to isolate the five antioxidant polyphenols from 75% ethanol extract of Malus pumila Mill. leaves. The HSCCC conditions were optimized by response surface methodology (RSM) considering two response indexes including retention of stationary phase and analysis time. The optimal HSCCC conditions were flow rate of 2.11 mL/min, revolution speed of 717 rpm, and temperature of 25â, with a solvent system of ethyl acetate/methanol/water (10:1:10, v/v/v). The unseparated fractions obtained from HSCCC were subjected to preparative HPLC for further isolation. As a result, phloridzin (15.3 mg), isoquercitrin (2.1 mg), quercetin 3-O-xyloside (1.9 mg), quercetin-3-O-arabinoside (4.0 mg), and quercitrin (2.0 mg) were isolated from 200.0 mg extracts. The purities of these compounds were all above 92%. Their chemical structures were identified by mass spectrometer and nuclear magnetic resonance. The five isolated compounds were further investigated for their rat hippocampal neuroprotective effects against hydrogen peroxide-induced oxidative stress. No cytotoxicity was observed in all tested concentrations. While all five compounds except phloridzin showed significantly neurogenic activities and neuroprotective effects, especially at the concentration of 0.5 mg/L. These results demonstrate that RSM is a suitable technique for optimisation of HSCCC and the isolated polyphenols can be used as antioxidants in pharmaceutical and food products.
ABSTRACT
Sorption enhanced steam gasification of biomass (SESGB) presents a promising approach for producing high-purity H2 with potential for zero or negative carbon emissions. This study investigated the effects of gasification temperature, CaO to carbon in biomass molar ratio [CaO/C], and steam flow on the SESGB process, employing carbide slag (CS) and its modifications, CSSi2 (mass ratio of CS to SiO2 is 98:2) and CSCG5 (mass ratio of CS to coal gangue (CG) is 95:5), as CaO-based sorbents. The investigation included non-isothermal and isothermal gasification experiments and kinetic analyses using corn cob (CC) in a macro-weight thermogravimetric setup, alongside a fixed-bed pyrolysis-gasification system to assess operational parameter effects on gas product. The results suggested that CO2 capture by CaO reduced the mass loss during the main gasification as the [CaO/C] increased. The appropriate temperature for SESGB process should be selected between 550 and 700 °C at atmospheric pressure. The appropriate amount of sorbent or steam could facilitate the gasification reaction, but excessive addition led to adverse effects. Operational parameters influenced the apparent activation energy (Ea) by affecting various gasification reactions. For each test, Ea at the char gasification stage was significantly higher than that at the rapid pyrolysis stage. The addition of CS notably increased H2 concentration and yield, while sharply reducing CO2 levels. H2 concentration initially rose and then fell with greater steam flow, peaking at 76.11 vol% for a steam flow of 1.0 g/min. H2 yield peaked at 298 mL/g biomass with a steam flow of 1.5 g/min, a gasification temperature of 600 °C and a [CaO/C] of 1.0. Increasing gasification temperature remarkably boosted the H2 and CO2 yields. Optimal conditions for the SESGB using CS as a sorbent, determined via response surface methodology (RSM), include a gasification temperature of 666 °C, a [CaO/C] of 1.99, and a steam flow of 0.5 g/min, under which H2 and CO2 yields were 464 and 48 mL/g biomass, respectively. CSSi2 and CSCG5 demonstrated excellent cyclic H2 production stability, maintaining H2 yields around 440 mL/g biomass and low CO2 yields (â¼60 mL/g biomass) across five cycles. The study results offer new insights for the high-value utilization of agroforestry biomass and the reduction and resource utilization of industrial waste.
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Capillary electrophoresis (CE) is a powerful separation technique offering quick and efficient analyses in various fields of bioanalytical chemistry. It is characterized by many well-known advantages, but one, which is perhaps the most important for this application field, is somewhat overlooked. It is the possibility to perform chemical and biochemical reactions at the nL scale inside the separation capillary. There are two basic formats applicable for this purpose, heterogeneous and homogeneous. In the former, one reactant is immobilized onto a particle or monolithic support or directly on the capillary wall, and the other is injected. In the latter, the reactant mixing inside a capillary is based on electromigration or diffusion. One of the diffusion-based methodologies, termed Transverse Diffusion of Laminar Flow Profiles, is the subject of this review. Since most studies utilizing in-capillary reactions in CE focus on enzymes, which are being continuously and exhaustively reviewed, this review covers the atypical applications of this methodology, but still in the bioanalytical field. As can be seen from the demonstrated applications, they are not limited to reactions, but can also be utilized for other biochemical systems.
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OBJECTIVE: Combining clinical investigations with usability studies provides valuable information for medical devices evaluation. But both types of study are very different in terms of objectives and methodologies. How are usability studies integrated into clinical investigations in practice? METHODS: We searched the ClinicalTrials.gov database for clinical investigation protocols that included usability outcome(s) and analyzed them. RESULTS: 77 study protocols were identified for the analysis, including 102 outcomes related to usability in total. The most frequently assessed outcomes were satisfaction (53/102) and ease of use (33/102). The questionnaire was the most frequently planned technique (85/102) followed by interviews (24/102). Other methods were used, such as observation (9/102), mostly when the end users was a healthcare professional, and diary (6/102), mostly with patients. CONCLUSION: Our study results showed that the collection of usability data can be included in a clinical investigation, with various levels of investment. Resource-light, rapid integration via a questionnaire will enable the collection of subjective data on the users' perceptions. When more resources are available, observation in accessible environments can be set up (especially during use by healthcare professionals in hospital) or interviews and/or diaries for home-based environments (especially by patients).
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Inductive generalization is adaptive in novel contexts for both biological and artificial intelligence. Spontaneous generalization in inexperienced animals raises questions on whether predispositions (evolutionarily acquired biases, or priors) enable generalization from sparse data, without reinforcement. We exposed neonate chicks to an artificial social partner of a specific color, and then looked at generalization on the red-yellow or blue-green ranges. Generalization was inconsistent with an unbiased model. Biases included asymmetrical generalization gradients, some preferences for unfamiliar stimuli, different speed of learning, faster learning for colors infrequent in the natural spectrum. Generalization was consistent with a Bayesian model that incorporates predispositions as initial preferences and treats the learning process as an update of predispositions. Newborn chicks are evolutionarily prepared for generalization, via biases independent from experience, reinforcement, or supervision. To solve the problem of induction, biological and artificial intelligence can use biases tuned to infrequent stimuli, such as the red and blue colors.
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Current studies in early cancer detection based on liquid biopsy data often rely on off-the-shelf models and face challenges with heterogeneous data, as well as manually designed data preprocessing pipelines with different parameter settings. To address those challenges, we present AutoCancer, an automated, multimodal, and interpretable transformer-based framework. This framework integrates feature selection, neural architecture search, and hyperparameter optimization into a unified optimization problem with Bayesian optimization. Comprehensive experiments demonstrate that AutoCancer achieves accurate performance in specific cancer types and pan-cancer analysis, outperforming existing methods across three cohorts. We further demonstrated the interpretability of AutoCancer by identifying key gene mutations associated with non-small cell lung cancer to pinpoint crucial factors at different stages and subtypes. The robustness of AutoCancer, coupled with its strong interpretability, underscores its potential for clinical applications in early cancer detection.
