Artificial intelligence application for rapid fabrication of size-tunable PLGA microparticles in microfluidics

In this study, synthetic polymeric particles were effectively fabricated by combining modern technologies of artificial intelligence (AI) and microfluidics. Because size uniformity is a key factor that significantly influences the stability of polymeric particles, therefore, this work aimed to establish a new AI application using machine learning technology for prediction of the size of poly(d,l-lactide-co-glycolide) (PLGA) microparticles produced by diverse microfluidic systems either in the form of single or multiple particles. Experimentally, the most effective factors for tuning droplet/particle sizes are PLGA concentrations and the flow rates of dispersed and aqueous phases in microfluidics. These factors were utilized to develop five different and simple in structure artificial neural network (ANN) models that are capable of predicting PLGA particle sizes produced by different microfluidic systems either individually or jointly merged. The systematic development of ANN models allowed ultimate construction of a single in silico model which consists of data for three different microfluidic systems. This ANN model eventually allowed rapid prediction of particle sizes produced using various microfluidic systems. This AI application offers a new platform for further rapid and economical exploration of polymer particles production in defined sizes for various applications including biomimetic studies, biomedicine, and pharmaceutics

Antibacterial surface modification of titanium implants in orthopaedics

The use of biomaterials in orthopaedics for joint replacement, fracture healing and bone regeneration is a rapidly expanding field. Infection of these biomaterials is a major healthcare burden, leading to significant morbidity and mortality. Furthermore, the cost to healthcare systems is increasing dramatically. With advances in implant design and production, research has predominately focussed on osseointegration; however, modification of implant material, surface topography and chemistry can also provide antibacterial activity. With the increasing burden of infection, it is vitally important that we consider the bacterial interaction with the biomaterial and the host when designing and manufacturing future implants. During this review, we will elucidate the interaction between patient, biomaterial surface and bacteria. We aim to review current and developing surface modifications with a view towards antibacterial orthopaedic implants for clinical applications

Thermal comfort survey in office buildings in Bandung, Indonesia

The comfort state of office building’s occupants is crucial since its related to the worker’s productivity. This comfort temperature of people from tropical climate might be different from temperate climate area. This study aimed to investigate thermal comfort and adaptive behaviour of occupants in office buildings with different ventilation modes: air-conditioned, mixed-mode, and free running. On February and March 2015, approximately 400 responses has been obtained through field surveys in three office buildings Bandung, Indonesia. The results has shown quite different comfort range between occupants in three ventilation modes: 24.7 oC, 26.3 oC, and 27.5 oC operative comfort temperature for FR, CL, and MM accordingly

Sensitivity Comparison of Macro- and Micro-Electrochemical Biosensors for Human Chorionic Gonadotropin (hCG) Biomarker Detection

Selectivity and sensitivity are important figures of merit in the design and optimization of electrochemical biosensors. The efficiency of a fabricated immunosensing surface can easily be influenced by several factors, such as the detection limit, non-specific binding, and type of sensing platform. Here, we demonstrate the effects of macro- and micro-sized planner working electrodes (4 mm and 400 μm diameter, respectively) on electrochemical behavior and the ability of the developed biosensor to detect human chorionic gonadotropin (hCG), which is a biomarker of several tumors. The fabricated screen-printed sensor was constructed by modifying the carbon macroand micro-electrodes with a linker, 1-pyrenebutyric acid-N-hydroxy-succinimide ester (PANHS), and immobilization of anti-hCG antibodies to specifically detect the hCG protein. The characterization of the developed electrodes was performed by cyclic voltammetry (CV) and square wave voltammetry (SWV). Each immunosensing system showed unique electrochemical behavior, which might be attributed to the arrangement of particles on the surface. However, a smaller microelectrode surface area was found to show higher sensitivity (1 pg/mL) compared to the macro-electrode sensor with a lower detection limit of 100 pg/mL. Further, Raman spectroscopy analysis confirmed that the micro-electrode had a relatively low density of defects and disorder compared to the macro-electrode. The proposed assay represents a promising approach that is highly effective for specific detection of an analyte and can be exploited to target biomarkers for a variety of point-of-care diagnostic applications

NFKB1 regulates human NK cell maturation and effector functions

12siopenopenLougaris, Vassilios; Patrizi, Ornella; Baronio, Manuela; Tabellini, Giovanna; Tampella, Giacomo; Damiati, Eufemia; Frede, Natalie; van der Meer, Jos W.M.; Fliegauf, Manfred; Grimbacher, Bodo; Parolini, Silvia; Plebani, AlessandroLougaris, Vassilios; Patrizi, Ornella; Baronio, Manuela; Tabellini, Giovanna; Tampella, Giacomo; Damiati, Eufemia; Frede, Natalie; van der Meer, Jos W. M.; Fliegauf, Manfred; Grimbacher, Bodo; Parolini, Silvia; Plebani, Alessandr

Graphene FET Sensors for Alzheimer’s Disease Protein Biomarker Clusterin Detection

We report on the fabrication and characterisation of graphene field-effect transistor (GFET) biosensors for the detection of Clusterin, a prominent protein biomarker of Alzheimer’s disease (AD). The GFET sensors were fabricated on Si/SiO2 substrate using photolithographic patterning and metal lift-off techniques with evaporated chromium and sputtered gold contacts. Raman Spectroscopy was performed on the devices to determine the quality of the graphene. The GFETs were annealed to improve their performance before the channels were functionalized by immobilising the graphene surface with linker molecules and anti-Clusterin antibodies. Concentration of linker molecules was also independently verified by absorption spectroscopy using the highly collimated micro-beam light of Diamond B23 beamline. The detection was achieved through the binding reaction between the antibody and varying concentrations of Clusterin antigen from 1 to 100 pg/mL, as well as specificity tests using human chorionic gonadotropin (hCG), a glycoprotein risk biomarker of certain cancers. The GFETs were characterized using direct current (DC) 4-probe electrical resistance (4-PER) measurements, which demonstrated a limit of detection of the biosensors to be ∼ 300 fg/mL (4 fM). Comparison with back-gated Dirac voltage shifts with varying concentration of Clusterin show 4-PER measurements to be more accurate, at present, and point to a requirement for further optimisation of the fabrication processes for our next generation of GFET sensors. Thus, we have successfully fabricated a promising set of GFET biosensors for the detection of Clusterin protein biomarker. The developed GFET biosensors are entirely generic and also have the potential to be applied to a variety of other disease detection applications such as Parkinson’s, cancer, and cardiovascular.</jats:p

Evaluating assumptions of scales for subjective assessment of thermal environments – Do laypersons perceive them the way, we researchers believe?

People's subjective response to any thermal environment is commonly investigated by using rating scales describing the degree of thermal sensation, comfort, and acceptability. Subsequent analyses of results collected in this way rely on the assumption that specific distances between verbal anchors placed on the scale exist and that relationships between verbal anchors from different dimensions that are assessed (e.g. thermal sensation and comfort) do not change. Another inherent assumption is that such scales are independent of the context in which they are used (climate zone, season, etc.). Despite their use worldwide, there is indication that contextual differences influence the way the scales are perceived and therefore question the reliability of the scales’ interpretation. To address this issue, a large international collaborative questionnaire study was conducted in 26 countries, using 21 different languages, which led to a dataset of 8225 questionnaires. Results, analysed by means of robust statistical techniques, revealed that only a subset of the responses are in accordance with the mentioned assumptions. Significant differences appeared between groups of participants in their perception of the scales, both in relation to distances of the anchors and relationships between scales. It was also found that respondents’ interpretations of scales changed with contextual factors, such as climate, season, and language. These findings highlight the need to carefully consider context-dependent factors in interpreting and reporting results from thermal comfort studies or post-occupancy evaluations, as well as to revisit the use of rating scales and the analysis methods used in thermal comfort studies to improve their reliability

The Scales Project, a cross-national dataset on the interpretation of thermal perception scales

Thermal discomfort is one of the main triggers for occupants’ interactions with components of the built environment such as adjustments of thermostats and/or opening windows and strongly related to the energy use in buildings. Understanding causes for thermal (dis-)comfort is crucial for design and operation of any type of building. The assessment of human thermal perception through rating scales, for example in post-occupancy studies, has been applied for several decades; however, long-existing assumptions related to these rating scales had been questioned by several researchers. The aim of this study was to gain deeper knowledge on contextual influences on the interpretation of thermal perception scales and their verbal anchors by survey participants. A questionnaire was designed and consequently applied in 21 language versions. These surveys were conducted in 57 cities in 30 countries resulting in a dataset containing responses from 8225 participants. The database offers potential for further analysis in the areas of building design and operation, psycho-physical relationships between human perception and the built environment, and linguistic analyses

The Scales Project, a cross-national dataset on the interpretation of thermal perception scales

Thermal discomfort is one of the main triggers for occupants' interactions with components of the built environment such as adjustments of thermostats and/or opening windows and strongly related to the energy use in buildings. Understanding causes for thermal (dis-)comfort is crucial for design and operation of any type of building. The assessment of human thermal perception through rating scales, for example in post-occupancy studies, has been applied for several decades; however, long-existing assumptions related to these rating scales had been questioned by several researchers. The aim of this study was to gain deeper knowledge on contextual influences on the interpretation of thermal perception scales and their verbal anchors by survey participants. A questionnaire was designed and consequently applied in 21 language versions. These surveys were conducted in 57 cities in 30 countries resulting in a dataset containing responses from 8225 participants. The database offers potential for further analysis in the areas of building design and operation, psycho-physical relationships between human perception and the built environment, and linguistic analyses