TGFBR1, TGFBR2, SMAD3, TGFB2, TGFB3, or SMAD2 in children with suggestive findings. These genes distinguish LDS into six classes . Delay in diagnosis of Loeys–Dietz syndrome may be associated with an adverse prognosis due to a very high augmented risk of early complications such as aortic or vascular rupture. The present report describes a case of an early diagnosis of LDS in a neonate with cleft soft palate and aortic root dilatation.Loeys–Dietz syndrome (LDS) is a rare autosomal-dominant disorder of the connective tissue with some typical vascular findings, skeletal manifestations, craniofacial features, and cutaneous findings with a wide phenotypic spectrum. Six different genes are involved in LDS and the diagnosis is based on the identification of a heterozygous pathogenic variant in  TGFBR1 and TGFBR2 genes in 2005 in 10 patients who showed novel aortic aneurysm syndrome and a clinical triad of hypertelorism, bifid uvula/cleft palate and aortic/arterial aneurysms, and tortuosity [TGFβ) pathway [Bart Loeys and Harry Dietz first described the Loeys–Dietz syndrome due to mutations in the  pathway .TGFBR1, TGFBR2, SMAD3, TGFB2, TGFB3, or SMAD2 encoding for components cooperating within the TGFbeta receptor signaling cascade to regulate cell differentiation and the development of many tissues, including bone, cartilage, blood vessels, and the heart. Loss-of-function heterozygous variants in TGFBR1 and TGFBR2 are the most frequent in LDS patients. Each gene is associated with different clinical characteristics that define a particular genotype–phenotype model. The clinical picture defined by mutations in the TGFBR1–TGFBR2 genes is largely overlapping in the majority of LDS cases. Patients with this mutation frequently have an ascending aortic root aneurysm and severe arterial involvement. Valve anomalies, in particular, prolapse and insufficiency of the mitral valve, are rarer. Craniofacial malformations are significant especially in patients with the TGFBR1 (LDS1) mutation including dolichocephaly, hypertelorism, malar hypoplasia, and a strongly arched palate, while abnormal palate and uvula bifida are not as frequent. LDS3 is instead defined by mutations in the SMAD3 gene, and what distinguishes it from other classes of LDS is the finding of arthrosis in the patient with this mutation and less cardiovascular involvement [TGFB2 gene mutation defined as LDS class 4 is characterized by mild cardiovascular anomalies and a more important skeletal involvement with joint hypermobility, pectoral deformity, and scoliosis. Recently this genetic subtype has also shown instability of the cervical spine and ectopia lentis. At the moment, there is still little information in the literature about TGFB3 and SMAD2 mutations. Research on these genotype–phenotype models is still open, but we can confirm that patients with these mutations share much of the cardiovascular and connective tissue characteristics common to LDS.The diagnosis of LDS is established on characteristic clinical findings in the proband and family members and/or by the identification of a heterozygous pathogenic variant in olvement . More raLDS is an autosomal-dominant disorder with both non-penetrance and mosaicism reported. Approximately 25% of individuals diagnosed with LDS have an affected parent; the remainder of probands have LDS due to a de novo pathogenic variant. In general, the more severe cases with marked craniofacial and skeletal findings result from a de novo mutation, whereas the milder cases tend to be familial. Prenatal diagnosis for pregnancies at increased risk for LDS is possible if the pathogenic variant in the family is known. Ultrasound examination in the first two trimesters has a low sensitivity in detecting manifestations of LDS, but prenatal occurrence of aortic dilatation can be detected in the more striking cases. LDS has become a focus of researchers worldwide, leading to an improved understanding of the disease; however, LDS remains insufficiently studied. Currently, no standard treatment or guidelines for LDS patients exist, and few studies have been conducted. What is known is derived from other connective tissue diseases, including Marfan syndrome. Various medical approaches have been studied to slow down the development of vascular abnormalities in these genetic conditions, including beta blockers, ACE inhibitors, and angiotensin receptor blockers (ARBs), especially losartan. This report presents the findings of a genetically confirmed LDS case during the neonatal age.Our proband was the second child of healthy and non-consanguineous parents. The mother, a 33-year-old smoker of about ten cigarettes a day, had another healthy 4-year-old child and had a spontaneous abortion. No remarkable disease was recorded in the family history. Neither the prenatal blood exams nor ultrasonography evaluation showed any problem. The proband was delivered by vaginal birth at our hospital at 39 weeks and 5 days of gestation after an uneventful pregnancy. He had normal adaptation to the post-natal life; the Apgar score was 8 and 9, respectively, at the 1st and 5th minute after birth. During the first inspection of the oral cavity in the neonatal resuscitation unit, the neonatologist found a cleft soft palate , so the The more striking results were obtained at the bedside echocardiography, which showed an aneurysm of the aortic root  with a mild regurgitation of the aortic valve, a normal ascending aorta  and a tortuous aortic arch with patent ductus arteriosus. A chest x-ray was performed to rule out other cardiopulmonary anomalies, but it documented just a slight augmented cardiac diameter. During a pediatric cardiology specialist consult, the echocardiogram confirmed the aortic ectasia , which wThe brain MR demonstrated a signal impairment in the para- and periventricular white matter, reduced thickness of the corpus callosum, and a slight bulge of the lateral ventricles. Lastly, a mild expansion of the periventricular spaces was found in association with a subarachnoid cyst .The plastic surgery and otolaryngology consult were scheduled at two months to plan the corrective surgery for the cleft palate, and manipulations for the contractures of feet joints were started after the physiatrist evaluation. The ophthalmologist did not find any ocular features of the connective tissue disorders.TGFBR2. The mutation was not detected in the parental DNA blood samples and confirmed the diagnosis of Loeys–Dietz syndrome in our proband.Chromosomal analysis on peripheral blood lymphocytes revealed a normal karyotype  so a molecular genetic analysis through next-generation sequencing (NGS) for aortic anomalies was requested on the peripheral blood cells. This test revealed a c.1658C>A pathogenetic mutation of exon 8 of The patient started a neurologic follow-up that documented a delay in gaining sitting position, a fix to follow moving objects, and reduced muscle tone at the inferior limbs. A mild improvement was achieved with psychomotricity. To prevent aortic dissection, the baby was initiated to medical therapy with beta-adrenergic blockers in addition to strict ultrasound monitoring of aortic and large vessel diseases. As of the writing of this report, the patient was 9 months old and no cardiovascular events had been recorded. On follow-up echocardiography, there was no increase in the aortic root at a dilation of 17 mm (z-score +8.65), while the aortic valve regurgitation was reduced. Correction surgery has not proved necessary for the time being. The child had optimal weight gain for his age with a BMI between the 50th and 75th percentile.TGFBR2 gene associated with a cleft palate and aortic dilatation. The first mutations identified in the TGF-beta cascade concern the subunits of the TGF-beta receptor . These mutations are associated with a phenotype with a prevalence of craniofacial alterations and identify as the clinical variant LDS type 1 [TGFBR2 were described [TGFBR2 are referred to as LDS type 4 [We report a case of Loeys–Dietz syndrome type 2 due to a pathogenic variant in the S type 1 . With thescribed . These pS type 4 .TGFBR2 [TGFBR1 [TGFBR2 gene. However, the same group identified a second case of LDS in a female born at 41 + 3 weeks of gestation. Unlike the previous case, the newborn presented a cleft palate and minor dysmorphisms but no alteration on the echocardiographic examination, although the genetic test confirmed the presence of a pathogenetic variant of TGFB3 [TGFBR2 [TGFBR2 [Although LDS presents with great phenotypic variability, a categorization on LDS genes is critical for the diagnosis and subsequent management of LDS patients. Cleft lip with or without cleft palate is one of the most common congenital malformations, occurring in about 1 in 600 to 700 births in the USA. A cleft palate alone is less common (1 in 1000 to 1500 births in the USA) but is more often associated with syndromes and not prone to prenatal diagnosis due to technological limitations . In our TGFBR2 . Complex [TGFBR1 . In thisof TGFB3 . Yetman of TGFB3 . Muramat [TGFBR2 . Individ [TGFBR2 ,15. Rece [TGFBR2 . In our  [TGFBR2 . In our  [TGFBR2 . Finally [TGFBR2  and seemThe pleiotropic effect of genetic mutations associated with LDS makes the diagnosis more subtle. As has been widely reported, the characteristics of LDS may not be known from the fetal time or first days of life, so a careful family investigation can lead us to perform genetic investigations to determine a diagnosis of LDS.Our case confirms the benefit of performing a careful examination of the patient in the neonatal resuscitation unit and in newborns with signs of connective disease to evaluate a possible association with a rare syndrome. Both specialistic consulting and molecular genetic diagnosis are imperative to confirm the primitive findings and begin a planned and tailored follow up and treatment program for LDS. Prenatal diagnosis for pregnancies at increased risk for LDS is possible if the disease-causing mutation in the family is known. In newborns with vascular anomalies, an early diagnosis is essential to ensure medical or surgical treatment that avoids lethal consequences. The possible benefits of beta-blockers or ARBs reported in the literature should encourage their immediate use when vascular anomalies are detected. The cardiovascular surgical approach should only be used in cases of nonresponsiveness to drug treatment.Based on our clinical case, echocardiographic screening should be proposed at birth in all newborns with cleft palate to exclude aortic dilatation and possibly prevent short- and long-term consequences. We, ourselves, would not have arrived at the diagnosis so quickly without a screening echocardiogram.We hope that new clinical trials will be conducted that identify genes and molecules useful in the medical therapy of LDS and limiting the progression of vascular abnormalities.


This study proposes to identify and validate weighted sensor stream signatures that predict near-term risk of a major depressive episode and future mood among healthcare workers in Kenya.The study will deploy a mobile app platform and use novel data science analytic approaches  to identifying predictors of mental health disorders among 500 randomly sampled healthcare workers from five healthcare facilities in Nairobi, Kenya.This study will lay the basis for creating agile and scalable systems for rapid diagnostics that could inform precise interventions for mitigating depression and ensure a healthy, resilient healthcare workforce to develop sustainable economic growth in Kenya, East Africa, and ultimately neighboring countries in sub-Saharan Africa. This protocol paper provides an opportunity to share the planned study implementation methods and approaches.A mobile technology platform that is scalable and can be used to understand and improve mental health outcomes is of critical importance. According to the World Health Organization, mental disorders account for the largest burden of illness among all types of health problems . Major d based prediction models of depression and mood among Kenyan healthcare workersTo collect and evaluate individual active and passive data that may predict depression and mood among Kenyan healthcare workersThe objective of the proposed study is to demonstrate the feasibility of a novel methodology in developing predictive models for mood and depression among Kenyan healthcare workers. The specific objectives of the research are:This will be a longitudinal cohort study.The setting will be in five urban healthcare facilities in the Kenyan capital city, Nairobi, where healthcare workers are directly involved with the patient’s care.Facility 1:  This is a private facility with a bed capacity of 254 with 14 different departments.Facility 2:  This is a public maternity facility with 396 healthcare staff spread across 13 different cadres  and 25 different departments [Facility 3:  This is a public facility with 700 healthcare workers who attend to more than 800 outpatients daily and has an ever-growing bed capacity.Facility 4: This is public facility which has a bed capacity of 1800 and a staff population of 6000 [ of 6000 . These sFacility 5:  This is a public facility which has an over 650 bed capacity and there are around 665 hospital staff [al staff .n is the sample size, Z is the statistic corresponding to 95% level of confidence, P is expected proportion, and d is precision (corresponding to effect size). Thus, we will recruit 500 participants, which will translate to 100 participants from each of the five healthcare facilities.The Cochran formula to estimate a representative sample for proportions is utilized . Using aA socio-demographic questionnaire in the App incorporates elements such as age, gender and education background. Each participant will complete the following standardized instruments:1) Neuroticism - NEO-Five Factor Inventory  is a 60-2) Positive and Negative Suicide Inventory (PANSI)  will mea3) Patient Health Questionnaire (PHQ-9) . It cons4) Pittsburgh Sleep Quality Index  will ass5) Risky Families Questionnaire  will be 6) Generalized Anxiety Disorder – 7 (GAD-7)  will mea7) MyDataHelps App – Online Survey developed by CareEvolution which provides step-by-step instructions for collecting data from participants via their smartphones [MyDataHelps is an application rtphones . The app8) Mobile Monitoring™(www.fitbit.com) which is a wearable fitness tracker wristband to track daily activity levels, daily mood rating and sleep. The device automatically connects via Bluetooth and transfers data to a mobile platform via a dedicated App. Fitbit Inspire 2™ allows tracking of sleep stages  in addition to sleep/wake states. During set-up, the participants will be prompted to allow MyDataHelps to send them notifications. A notification will be automatically generated on their phone daily and will appear as follows: “On a scale of 1 to 10 what was your average mood today?” They will then respond in the App. We will ask them to complete this daily rating for a period of one year. After completing the consenting process and initial survey via the study App, participants will be given Fitbit Inspire 2. They will be asked to sync the fitness tracker with their phone and wear it daily through to the end of their study year for the purpose of collecting objective data on their daily activity. On the App activities page, participants will be able to track their recent activity data  (see “MyDataHelps App – Dashboard-Activities Screen’). Healthcare workers will also be able to view graphs of their mood, sleep, and step data at any time on the App dashboard.  and own a smart phone. Exclusion criteria will be: decline consent to participate in study; has a non-smartphone and HCW’s on locum. This sampling technique is preferred due to the large number of healthcare workers who rotate in these sites. Potential participants will be randomly selected from a list with staff names and contacts. They will then be contacted via email or smartphone.We will administer surveys and collect active and passive mobile data on mood and affect over a 12-month period in a Kenyan cohort of 500 healthcare workers, recruited from five health facilities. The frequency of the data collection will vary i.e., daily, monthly and quarterly. The initial data collection day will be the same as the consenting day. Right after the participants give consent through the App (MyDataHelps), a unique identifier will be generated. All consented healthcare workers will then be encouraged to complete the baseline survey. In addition to demographic and baseline psychological information (Neuroticism using the NEO-FFI and Early Family Environment using the Risk Family Questionnaire), the baseline survey will assess anxiety symptoms using GAD-7, suicidal symptoms using PANSI and depressive symptoms using PHQ-9 –18. Part. At 3-month intervals (quarterly) they will also be assessed via the App using a shorter questionnaire designed to assess: 1) current depressive symptoms measured by the PHQ-9, 2) current suicidal symptoms measured by the PANSI, 3) current anxiety symptoms measured by the GAD-7, 4) non-work life stress, 5) COVID-19 experiences, 6) work hours, and 7) perceived medical errors . If partSee. The heaData will be collected, stored in the cloud database, and checked for completeness daily. Whenever we come across missing data, a reminder will be sent to the respondents after three consecutive days of missed entries, urging them to complete the data entry process. When they opt out of the study, reminders will no longer be sent. Once the study is over, the data will be stored in accordance with guidelines from Kenya’s Data Protection Act 2019 , NationaThe framework for this model was built in 1999 , 29, andWe will use our modeling framework to estimate circadian phase and sleep drive in individual subjects. We will compare the Fitbit estimates of individuals both asleep and awake with our predicted sleep drive with the hypothesis typically used in the field. The predicted relationship between these variables by our mathematical models will be compared with these datasets, aggregated over the population to refine parameters for the mathematical model, which will represent the behavior of a typical individual. These estimates of circadian and sleep drive have the potential to inform shift work.Granger cause. Consider the two regression models: (a) j-th element is the lag-j effect upon and B is a vector with j-th element representing the effect of j-th lag of X upon Y. Then X is said to be Granger-causal for Y only if model (a) results in significant improvement over model (b). We will use the multivariate extension of the notion of Granger causality between two variables to p variables, referred to as graphical Granger models (GGM) [We will make inferences about which behavioral phenotypes are most predictive and evaluate their time-delayed impact upon mood at different time lags. Granger causality  is a quals (GGM) . GGM uncWe will estimate the strength of association among the mobile phenotypes and their respective associations with the daily mood scores. For example, we will construct the sequence of sleep hours averaged over the past 1, 2 or 7 days and study their respective association with self-reported mood scores. These estimates will directly address two questions: 1) “Which phenotypes and their temporal features predict the daily mood scores?”, and 2) “If a phenotype is predictive of daily mood scores, at what time lags do we observe the strongest predictive strength?” We address these questions via Lasso-type estimates in the context of Granger causality to estimate the effects of variables on each other in a sparse graphical model framework . ImportaWe will also likely observe nonlinear relationships between the mobile phenotypes and the daily mood scores. We will use kernel-based regression methods to explicitly relax the linear dependence of the outcome upon predictors .In addition to the daily mood scores, we will also use PHQ-9 scores to assess the study participants’ depressive symptoms. We will use dynamic latent variable models  to addreAs with in any longitudinal study, missing data may be a problem. We will perform a secondary analysis after accounting for missing data to ensure the absence of missing data biases and to maximize power .We cannot diagnose major depressive disorders (MDD) using self-reported assessments. However, our self-reporting assessment has several advantages. For instance, the PHQ-9 instrument that we will utilize to measure depressive symptoms has a sensitivity of 88% and a specificity of 88% for a MDD diagnosis with a cut-off of 10 points or higher , 45. FurThe smartphone and wearable devices utilized in this study rely on emerging technology and do not measure parameters of sleep and activity as accurately as gold-standard laboratory tests , 48. Whi


Mixed Reality technology may provide many advantages over traditional teaching methods. Despite its potential, the technology has yet to be used for the formal assessment of clinical competency. This study sought to collect validity evidence and assess the feasibility of using the HoloLens 2 mixed reality headset for the conduct and augmentation of Objective Structured Clinical Examinations (OSCEs).A prospective cohort study was conducted to compare the assessment of undergraduate medical students undertaking OSCEs via HoloLens 2 live (HLL) and recorded (HLR), and gold-standard in-person (IP) methods. An augmented mixed reality scenario was also assessed.p = 0.01), 0.98 (p = 0.01) and 0.82 (p = 0.01) for IP vs. HLL, HLL vs. HLR and IP vs. HLR respectively. Skill based correlations for IP vs. HLR were assessed for history taking , clinical examination , procedural  and clinical skills , and assessment of a virtual mixed reality patient . The HoloLens device was deemed to be usable and practical  score = 51.5), and the technology was thought to deliver greater flexibility and convenience, and have the potential to expand and enhance assessment opportunities.Thirteen undergraduate participants completed a total of 65 OSCE stations. Overall inter-modality correlation was 0.81 (HoloLens 2 is comparable to traditional in-person examination of undergraduate medical students for both live and recorded assessments, and therefore is a valid and robust method for objectively assessing performance. The technology is in its infancy, and users need to develop confidence in its usability and reliability as an assessment tool. However, the potential to integrate additional functionality including holographic content, automated tracking and data analysis, and to facilitate remote assessment may allow the technology to enhance, expand and standardise examinations across a range of educational contexts.The online version contains supplementary material available at 10.1186/s12909-022-03701-3. Innovative mixed reality (MR) technologies have the potential to transform the delivery of medical education , and mayThe HoloLens 2 (HL2) is a commercially available MR headset produced by Microsoft  that allows for remote first-person visualisation, multi-directional audio and visual communication, and the integration and manipulation of interactive 3-dimensional (3D) holographic content into real-world scenarios . The devThe HL2 device may facilitate remote assessment both in real-time and via recorded content. This approach may not only reduce cost and improve access to qualified assessors, but may also facilitate assessments to be taken out of the abstract structured environment of formal examinations and into real-life opportunistic clinical interactions. In addition, the use of interactive MR content provides opportunities to augment the assessment process through the use of holographic assets, or the use of interactive instructional material and clinical information , 16. DesThe study sought to examine the feasibility and validity of using the HL2 MR headset for objective assessment and augmentation of Objective Structured Clinical Examinations (OSCEs) across a range of core undergraduate clinical competencies.Thirteen undergraduate medical student participants were recruited. All were at, or above the level of proficiency required to complete the study, and none had prior experience of using a HL2 device. The study received institutional educational ethical approval (EERP2021-055) and written informed consent was obtained from all participants.This prospective cohort study was conducted to collect validity evidence for the use of MR technology as a tool for the objective assessment of undergraduate clinical competencies by comparing it to the current gold-standard in-person method of examination. Study accrual was based on convenience sampling comparable to similar studies as no power calculation was practicable due to the novel data being assessed. Participants undertook an OSCE examination consisting of five stations representative of their assessed curriculum. Each station examined a different domain of mandatory core clinical competencies encompassing clinical examination, history, and procedural and skills-based assessment, and utilised actors and synthetic benchtop models. A final station introduced a virtual simulated COVID-19 patient provided publicly for free by GigXR  that created an immersive learning environment simulating a deteriorating patient  to examiParticipants undertook all five stations on rotation. Ten minutes were provided to complete each station with one-minute intervals between, mimicking the local standardised clinical OSCE examination format. A HL2 device was worn by each student whilst completing the study following a period of standardised training on how to wear and operate the device. Each station was assessed via three modalities: the current gold-standard in person assessment by a trained examiner in the room (IP), virtually in real-time using the HL2 device linked to a trained examiner (HLL), via the Microsoft Remote Assist software platform  and finally via a recording of the scenario obtained from the HL2 device (HLR). All examiners were qualified doctors with proficiency to assess the core competencies examined as part of the study. Examiners rated all three arms of the study and intra-modality variability was assessed to ensure consistency of performance. Indicative mark schemes for each station are provided in Additional file Standard descriptive statistics were employed. Normality of data were assessed via Shapiro–Wilk tests and two Tailed Pearson’s and Spearman Rank Correlation Coefficients were calculated. Inter-modality variability was examined by Cronbach Alpha Intra Class Coefficient. Correlations were classified according to the correlation coefficient . All datp =  < 0.01), 0.98 (p =  < 0.01) and 0.82 (p =  < 0.01) for IP vs. HLL, HLL vs. HLR and IP vs. HLR respectively , 0.89 (p =  < 0.01), 0.94 (p =  < 0.01) and 0.95 (p =  < 0.01) for clinical examination, history, procedural and skills-based assessments respectively , and once again correlations across all three assessment modalities with the holographic patient were strong: IP vs. HLL , HLL vs. HLR  and IP vs. HLR .Utilising MR content to augment traditional approaches to assessment also has promise. Participants demonstrated comparable overall performance in the holographic patient scenario compared to real patient scenarios with mean scores of 28.4 and 29.8 respectively . 12/13 (92.3%) of student participants and 5/8 (62.5%) of assessors stated that the first-person view allowed for better visualisation of student performance compared to in-person assessment. 11/13 (85.6%) of students and 8/8 (100%) of assessors agreed or strongly agreed that they would like to see the technology incorporated into future assessments. 12/13 (92.3%) students agreed or strongly that recording their performance could be useful for self-directed learning and future development. 8/8 (100%) of assessors agreed or strongly agreed that scoring a recording of a students’ performance instead of in person allows for greater flexibility, convenience and accessibility. “HoloLens 2 allowed greater flexibility both in real-time and also for re-watching recordings at a later date.” (Assessor).100%  agreed or strongly agreed that the integration of MR technology has the potential to enhance the assessment experience. “HoloLens 2 looks to be overall a very promising and novel method of teaching and assessing, one that certainly has a few early teething problems with implementation, but I am confident once over the learning curve and made more widely accessible, will prove to be a very useful tool piloted in medical education but with possible widespread applications across multiple industries.” (Assessor).Feedback on the technology was not universally positive, however. 6/13 (46.2%) of participants reported general discomfort or difficulty concentrating with the HL2 device, although none reported symptoms of headache, fatigue, nausea or eye strain. 12/13 (92.3%) of students and 2/8 (25.0%) of assessors reported that the device potentially interfered with their ability to carry out the required task. This was principally due to unfamiliarity with the technology and software usability despite a period of standardised training, rather than the physical impact of the device; issues which will likely dimmish as familiarity with the technology grows. Overall, the HL2 technology was reported to be moderately usable, with an SUS score of 51.5 . The higHoloLens 2 appears to be comparable to in-person examination of undergraduate medical students for both live and recorded assessment, and therefore is a valid and robust method for objectively assessing performance across a full range of core competencies including clinical examination, history taking, and clinical and procedural skills. The use of MR content, in this case a virtual patient, has been shown to have the potential to augment the assessment process with students and assessors performing comparably to clinical interactions with real simulated patients.MR technology has the potential to unlock a wide range of novel assessment techniques and opportunities. It may facilitate the summative appraisal of tasks conducted in representative real-life contexts through the assessment of opportunistic clinical interactions and skills. The ability to facilitate the assessment of infrequent, or challenging competencies such as breaking bad news, or rare clinical presentations and procedures provides opportunities for increasing the scope of formal assessment. The use of virtual logbooks may also facilitate the provision of greater, and higher quality supervision and mentoring from educators who cannot be present to undertake assessment or feedback in real-time. In addition, it may support a more robust approach to quality assurance, and allow for greater transparency in decision making, particularly when there may be disputes regarding performance or ability. Given that most medical students are dissatisfied with the feedback they receive, introducing new technologies that support more robust, transparent, and engaging assessment processes should be championed . The potMR technology such as the HL2 device provides seamless integration with cloud services, and the ability to deploy intuitive software platforms that can integrate holographic content and additional functionality that are supported by a range of sensors and hardware on the device. Whilst in its infancy, the use of holographic content to augment the assessment process has been shown to be robust and valid, and broadly comparable to the use of live patients. Despite showing potential, the use of holographic material only supports the assessment of specific parts of clinical interactions. It remains to be demonstrated that a holographic patient, or other MR content can fully replicate more complex and nuanced aspects such as non-verbal cues or subtleties of language, communication and inter-personal interaction. In addition, the substantial gap in the technology is its inability to replicate key multi-sensory parts of basic physical examination such as palpation or auscultation. Given these limitations, whilst there may be a role for MR content to augment the assessment process, the technology is too immature currently to completely replace real or actor patients.Despite showing promise there remain several barriers to its widespread adoption and successful scaling of the technology. Key to this are inherent limitations found with current generation of hardware and software. The battery life of the device limits the time it can be used, with often only around 60 min of continuous use achieved, potentially limiting its applicability to longer forms of assessment. In addition, there are limitations to the number of applications that can be run at any point in time without the device crashing, which may restrict the ability to augment the assessment process to the technologies full potential due to limitations with current off-the-shelf software applications. The significant financial resources required—$3,500 per device, with individual software licences in addition—may act as a barrier to widespread adoption but may conversely also be seen as an effective way to minimise the cost of exams by negating the need to bring together examiners, students, and patients in traditional structured formats. Finally, there is a learning curve to the technology. For example, the HL2 device is principally controlled by hand gestures, with supination and tapping of the wrist returning to user to the home screen; a movement which closely mimics the action of putting on gloves during a clinical scenario. If the device it to be used more widely, then solutions or mitigations to these issues must be developed.One out of the five assessors reported concerns that the HL2 interfered with their ability to assess the student compared to being present in the room, and most students were also concerned that the device my hinder their performance. These concerns were not however borne out, with students and assessors displaying consistent performance across all modalities. It has been demonstrated that MR headsets have no impact on cognitive function , and thiThe additional limitations of this study, primarily that of convenience sampling from a single institution and a small study size leave the risk of type II error and bias impacting the results. Any new technology, and the assessment of it, will also be influenced by technology bias. There is a need to minimise these potential confounders and to evaluate the technology at scale across a range of contexts, and not just in a digitally advanced and engaged institution as in this study to determine its wider applicability. Much of the study utilised the basic core functions of the HL2 device, namely the head-mounted camera and microphone. An important additional evaluation that was not undertaken would be to compare performance of students and assessors when using the HL2 device compared to fixed cameras within the examination room. This would not only deliver further evidence for the potential impact of a head-mounted device on performance but would also provide further context to demonstrate the added value of holographic content and the other additional HL2 device functionality.HL2 has previously been integrated into medical school curricula , 9 of suHoloLens 2 is comparable to traditional in-person examination and appears to be a valid and robust method for objectively assessing performance across a variety of core clinical competencies. The technology is in its infancy and still requires considerable development, and users need to gain confidence in its usability and reliability as an assessment tool. However, the potential to integrate additional functionality and to facilitate remote or ad-hoc assessments may allow the technology to enhance, expand and standardise examinations across a range of educational settings.Additional file 1:Table S1. History Station (Leg Pain) Mark Scheme. Table S2. Examination Station (Lower Limb) Mark Scheme. Table S3. Procedure Station  Mark Scheme. Table S4. Skills Station (Simple Suturing) Mark Scheme. Table S5. History and Assessment (Simulated Patient) Mark Scheme.


Cancer survivors are vulnerable to experiencing symptoms of anxiety and depression and may benefit from accessible interventions focused on improving emotion regulation. CanCope Mind (CM) was developed as an internet-delivered intervention adapted from the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders to improve emotion regulation and support the mental health of cancer survivors.This protocol aims to provide an outline of the CanCope Study, a trial comparing the efficacy of a Unified Protocol–adapted internet-delivered intervention (CM) designed for cancer survivors compared with an active control condition—an internet-delivered healthy lifestyle intervention, CanCope Lifestyle (CL). The primary aim is to assess and compare the efficacy of both interventions in improving emotion regulation, anxiety and depressive symptoms, and quality of life. The secondary aims involve assessing the mechanisms of the CM intervention.0), between each module , immediately after the intervention (T4), and at 3-month follow-up (T5). The study aims to recruit 110 participants who have completed T4.This trial is a 2-arm randomized controlled trial that allocates cancer survivors to either CM or CL. Both interventions comprise 4 web-based modules and are expected to take participants at least 8 weeks to complete. Participants’ mental and physical health will be assessed via self-reported surveys at baseline  and CL  groups.The CanCope study began recruitment in September 2020. A total of 224 participants have been randomized to the CM (nThis is one of the first trials to develop and investigate the efficacy of a web-based intervention for cancer survivors that specifically targets emotion regulation.Australian Clinical Trials ACTRN12620000943943; https://tinyurl.com/b3z9cjspDERR1-10.2196/36658 The end of cancer treatment is a challenging transition for many cancer survivors. Individuals can continue to experience cancer-related distress long after primary treatment has ended. Specifically, 42% and 29% of cancer survivors experience at least subclinical symptoms of anxiety and depression, respectively, and worse mental health compared with the general population -3. Even Emotion regulation can be defined as the ability to adapt to one’s affective experience, such as maintain, increase, or decrease feelings, behaviors, or physiological responses that comprise an emotional experience . DifficuOne cognitive-behavioral intervention designed to target approach-oriented emotion regulation is the Unified Protocol (UP) . The UP why and how interventions achieve their desired effects. For instance, meta-analytic findings reveal that even though the UP may be effective in improving symptom outcomes, there is a lack of evidence to suggest that these effects are mediated through changes in emotion regulation [Although many psychological interventions target the mental health of patients with cancer and cancer survivors -27, few gulation .specific intervention components, information critical for understanding the causal mechanisms that drive improvements in mental health [Similarly, little is known about the effectiveness of l health . Uncoverl health ,31. The l health . The autl health . For exaIn addition, evidence suggests that the UP may improve broader health outcomes and overall quality of life (QoL) ,33-35. CTo address these limitations, a 2-arm randomized controlled trial was designed to assess the efficacy of an internet-delivered, multimodular UP-based intervention package with all modules combined, titled CanCope Mind (CM). CM was compared with a healthy lifestyle active control intervention, CanCope Lifestyle (CL).4), cancer survivors randomized to CM will experience fewer difficulties regulating emotions as well as lower symptoms of anxiety and depression. Both CM and CL are expected to improve QoL, as CL includes components that target diet, physical activity, relaxation, and sleep. Given that these 4 lifestyle factors are associated with improved QoL, it is unclear whether CM or CL will be more effective in improving QoL.Aim 1 is to assess the efficacy of CM versus CL in reducing emotion dysregulation (primary outcome) and in improving anxiety and depressive symptoms and QoL (secondary outcomes) in cancer survivors. Hypothesis 1 states that, compared with CL, after treatment ≤2 years since finishing primary cancer treatment Regular access to the internet and emailRegular access to a computer, laptop, or smartphone device.Exclusion criteriaCurrently undergoing or planning to undergo further primary cancer treatment Cancer is not in remission or is progressing in severityEndorses current suicidality and considered high risk for self-harmCurrent episode of psychosisAttending regular sessions with a mental health professional Started or changed psychotropic medication or dose within the previous 2 weeks, or plans to start or change psychotropic medication or dose throughout the 8-week trialPreviously participated in the CanCope pilot trialsNo minimum criterion was included for the primary outcomes of emotion dysregulation, as it is not certain that this UP-adaption is only effective in highly dysregulated cancer survivors. By excluding participants based on a minimum cut-off, we would not be able to assess the intervention effects on cancer survivors experiencing high and low difficulties.Participants are recruited using multiple methods, including social media platforms , web-based community forums , and via organizers of cancer support groups. Embedded within each of these advertisements, participants can access a link to the study’s written explanatory statement and consent form hosted on the Research Electronic Data Capture (REDCap) tool ,44. InfoConsenting participants are automatically redirected to a web-based screening survey to assess eligibility. Subsequently, eligible participants complete the baseline survey and are telephoned to administer the Mini International Neuropsychiatric Interview (MINI)  and condRandomization to CM or CL is conducted using a stratified, block randomization scheme generated in advance and uploaded to REDCap. Variable block sizes  are used to ensure allocation concealment and prior guessing of the allocation sequence at the end of each block. Randomization is stratified by baseline depressive and anxiety symptoms as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Anxiety and Depression scales  and the Difficulties in Emotion Regulation Scale–Short Form (2 strata: <45 and ≥45). The randomization scheme is generated and set up in REDCap by a member of the research staff who is not involved in the recruitment or delivery of the intervention nor in the subsequent statistical analysis. The participants are aware of their intervention allocation ; thus, they are not blinded. However, participants remain unaware of the study hypotheses regarding which group will improve more on outcomes, and both treatments are presented as potentially effective.5, all participants receive the alternative group’s intervention material via an email link .Both the CM and CL intervention conditions are internet-delivered programs comprising 4 modules (2 weeks of content per module), which may take participants as few as 8 weeks to complete. Both interventions comprise educational readings and videos followed by activities on the web. The activities include textboxes for participants to provide written responses to encourage active reflections. All intervention materials and activities are delivered on the web via REDCap. every daily activity, although they must complete at least 1 to 2 core activities per module before they could move on to the subsequent module. This format aims to mirror a more real-life, clinician-led intervention, where clients would not prematurely progress to a subsequent and more advanced module without first being exposed to fundamental skills from the previous modules . As a result, participants who reach the end of the entire intervention have been exposed to all core skills. Each module is outlined in subsequent sections, and a summary overview is provided in CM is a web-based version of the UP’s Transdiagnostic Treatment for Emotional Disorders . The ovePart 1 explains that emotions are neither good nor bad, and it outlines the various adaptive functions of common emotions. For instance, anxiety elicits fight-or-flight responses, which is important in times of threat. During the daily activities, participants are encouraged to reflect on their own emotions and their adaptive functions in their lives. Part 2 describes common unhelpful beliefs or misconceptions around emotions . The daily activities encourage participants to explore their own unhelpful beliefs about their emotions. Part 3 describes the three interrelated components that constitute an emotional experience: (1) thoughts, (2) feelings or bodily sensations, and (3) behaviors. During the daily activities, participants are encouraged to bring awareness to these 3 components in their lives.Module 1 aims to build an awareness and understanding of emotions through 3 psychoeducational readings, 2 summary videos, and 14 daily activities. part 1, participants are encouraged to adopt an accepting and nonjudgmental stance toward primary emotions, as critical judgment of primary emotional responses can perpetuate negative affective states. Participants are provided with 2 emotion-focused guided mindfulness audios and are encouraged to listen to one of them every day for 7 days. Part 2 teaches a four-step mindful anchoring exercise: (1) paying attention to a cue, such as the breath; (2) identifying their thoughts, feelings, and behaviors; (3) considering whether their response is consistent with the present moment; and (4) shifting their response to align with the demands of the present moment. For 7 days, participants are encouraged to practice anchoring in real time, when experiencing uncomfortable emotions.Module 2 aims to increase mindful awareness of emotions through 2 psychoeducational readings, 2 summary videos, and 14 activities. In flexible thinking . Flexible thinking involves the ability to (1) identify automatic and unhelpful thoughts and interpretations and subsequently (2) identify an alternative, more balanced appraisal of the given situation. The module comprises 1 reading, 1 summary video, and 14 activities that outline the bidirectional relationship between thoughts and emotions. Participants are taught about common and unhelpful thinking traps , including catastrophizing, jumping to conclusions, tunnel vision, “should” statements, and all-or-nothing thinking. The daily activities on the web encourage participants to (1) identify their thinking traps, (2) answer multiple questions to challenge the thinking trap , and (3) generate an alternative and more balanced appraisal of the situation.Module 3 aims to increase skills in Part 1 focuses on overt and covert avoidance-oriented EDBs  and their paradoxical effect in increasing negative emotions, such as anxiety. Two other broad categories of EDBs are discussed: reassurance-seeking behaviors  and defensive behaviors . In activities on the web, participants are encouraged to identify and reflect on these EDBs throughout their lives. Part 2 teaches participants about alternative actions, value-consistent and healthier behaviors that can replace unhelpful EDBs . In daily activities on the web, participants are encouraged to practice replacing their EDBs with alternative actions.The final module aims to build skills in identifying and altering unhelpful emotion-driven behaviors (EDBs) through 2 psychoeducational readings, 2 summary videos, and 14 activities. Unhelpful EDBs are defined as maladaptive ways to try to manage one’s emotions, often with the purpose of eliminating an emotion or preventing oneself from feeling an emotion in the first place. Rationale for Choice of Control GroupTo assess the effects of CM on an appropriate comparator, we consulted the National Institute of Health’s Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials . AccordiCurrently, patients with cancer and cancer survivors have access to a host of resources that aim to promote general QoL, often with a focus on diet, physical exercise, relaxation, and sleep. These resources are often disseminated freely on the web by cancer-specific  and noncancer-specific  community and government organizations. Therefore, two possible comparator options were considered: (1) a wait-list control condition versus (2) a basic lifestyle and well-being intervention targeting diet, exercise, sleep, and relaxation using free and highly accessible web-based resources.Both options were evaluated against 7 key characteristics identified in the National Institute of Health model , which adescribe how you applied the module material to your lifeover the past week and describe how you plan to apply the module material to your life over the next week). Participants may take 3 to 10 minutes to complete each reflective activity on the web. Although the CL participants are sent fewer application activities on the web than the CM participants, they are still encouraged to apply the module material to their daily lives over the 2-week module duration. The content included in CL is publicly available, except for sleep hygiene information, which was developed by the Monash University sleep research group. The content of each module is outlined in the subsequent sections.In parallel to the CM modules, the CL group receives four internet-delivered modules that focus on different lifestyle domains: (1) diet, (2) physical activity, (3) relaxation, and (4) sleep. Throughout each 2-week module, participants are sent 2 activity links via email, whereby they are asked to apply what they have learned from the module  and outlines 8 tips to improve well-being through healthy diet habits . All the 3 readings were developed by the Cancer Council. The readings promote eating a healthy diet rich in fruits, vegetables, and whole grains to maintain well-being and reduce cancer risk and provide healthy recipes. Participants are encouraged to apply the healthy eating habits across the 2-week module.Module 1 comprises 1 video and 3 readings. The video was developed by the organization Mind and outlines tips to encourage physical activity . Participants are directed to the Cancer Council’s reading; “Exercise for people living with cancer,” which provides various exercises related to strength training, aerobic exercise, flexibility, and strengthening the pelvic floor. Participants are encouraged to choose 2 exercises listed in the reading  to apply throughout the module.Module 2 comprises 1 video and 1 reading. The video was developed by the organization Mind and outlines 8 tips to aid relaxation . The reading, titled “Learning to relax,” was developed by the Cancer Council and discusses healthy ways to manage emotional stress and aid relaxation . Finally, participants are sent a link to access Beyond Blue’s guided relaxation audio clips. Participants could choose from (1) breathing exercises, (2) muscle relaxation, and (3) guided visualizations. Participants are encouraged to listen to any of these audio clips as many times as they would like across the 2-week module.Module 3 comprises educational material (1 video and 1 reading) and a link to various guided relaxation audios. The 5-minute YouTube video was developed by the organization The final module comprises 2 readings focused on sleep and fatigue. The first reading was developed by the Cancer Council and explains fatigue in the context of cancer and ways to manage fatigue. The second reading provides education on sleep  and various sleep hygiene tips . This informational sheet was developed by researchers at Monash University. Participants are encouraged to apply the sleep hygiene tips across the 2-week module.0, approximately 25 minutes), after module 1 , after module 2 , after module 3 , after module 4 , and at the 3-month follow-up . Participants in the CL are automatically emailed a link to complete each postmodule survey approximately 14 days after starting a given module. For CM participants, the postmodule surveys are automatically scheduled to be sent only once the core activities are completed   will be T score . Higher scores indicate greater depressive or anxiety symptoms .The PROMIS QoL Health Utility Score  will be All the module-specific target outcomes and their respective modules are listed in The Credibility Expectancy Questionnaire  will be The Depression Risk Questionnaire-7  is a bri1 and T2) are provided with an e-gift card worth equivalent to Aus $40 (US $30) in their local currency as a token of appreciation. This compensation is provided at the end of their participation.All eligible participants who complete the baseline assessment as well as at least 2 modules and their respective postintervention assessments . As all primary and secondary outcomes are continuous, the primary analyses will be linear regressions with group as a predictor and outcome scores at baseline included as a covariate. We set the type 1 error at Cronbach α=.05 (2-tailed). A Monte Carlo simulation study was conducted to determine the power analysis and required sample size. In the simulation, we varied (1) the correlation between baseline and postintervention outcome scores (r) across four values  selected from the literature and our pilot research [4 will provide more than 80% power to detect a medium (SMD=0.5) group difference—after the intervention, even with only a moderate correlation (r=0.3) between baseline and postintervention outcome scores with Cronbach α=.05.The primary end point for the trial is the immediate postintervention assessment (Tresearch  and (2) research  where weresearch . ResultsAnalyses will be conducted in R on an intention-to-treat basis with statistical significance set at Cronbach α=.05 for type 1 error. The tests for primary and secondary outcomes will be 2-sided. The data will be assessed for outliers. If outliers are present, we will use quantile regression to calculate a median estimate or evaluate removing or winsorizing outliers.4). Anxiety and depression symptoms as well as overall QoL are secondary outcomes. All outcomes are continuous measures.Missing data are ubiquitous in research, and dropout and incomplete data  are particularly common in web-only trials . For aim4) will be included as the outcome variable in a linear regression, with group as the main predictor and the outcome variable at baseline (T0) and stratification factors included as covariates. Adjusted means in each group, as well as the adjusted mean difference, will be calculated. In the event of outliers, quantile regression will be used in place of linear regression and adjusted median differences at the primary end point (T4), and as exploratory analyses, the other time points will be estimated. Following recent research suggestions [P values [The primary analyses will consist of linear regressions on multiple imputed data. Each outcome variable at the primary end point . For the linear regression assessment of depression and anxiety symptoms, only the DERS-SF stratification factor will be included. For the linear regression assessing QoL, both stratification factors will be included.4), we will explore group differences at T1, T2, T3, and T5 on the primary and secondary outcomes. The overall sample mean at T0 will be presented for comparison.In addition to testing for group differences at the primary end point  divided by the residual SD estimated from the model. In the case of outliers, standardized median difference will be calculated. By using the residual adjusted for baseline outcome scores, this is effectively an effect size on the difference scores or for repeated measures .4) adjusted for the score before completing the module.The same analyses, significance tests, sharp null hypothesis, and result reporting described for the primary aim will be used to assess aim 2, the effect of CM versus CL on module-specific target outcomes. The model-specific target outcomes are presented in If intervention effects are observed on the DERS-SF, aim 3 will involve conducting mediation analyses to assess whether greater improvements on the DERS-SF (primary outcome), in the CM versus CL condition, mediate the effects of CM versus CL on anxiety and depression symptoms (secondary outcomes).P values and CIs, (2) generalized additive models to examine whether results differ when allowing nonlinear associations between baseline and postintervention symptoms, (3) per-protocol analyses based only on participants who completed all core intervention components, and (4) assessing group differences in intervention duration and the impact of intervention completion time on outcomes.Planned sensitivity analyses will include (1) calculating parametric and asymptotic 2 and T4 to assess the side effects due to the intervention and negative experiences, such as inappropriateness or unhelpfulness of the intervention; and (3) monitoring for any unsolicited reports of adverse events or serious adverse events . In the consent form, participants are informed that the survey questions, including PROMIS anxiety and depressive symptom surveys, ask sensitive information and may be confronting, triggering temporary elevations in distress for some individuals. If this occurs, all participants are provided with relevant mental health support numbers to contact, and they could report this to the researchers.This study received ethics approval from the Human Research Ethics Committee at Monash University (ethics ID number: 25825). Any protocol modifications will be communicated to the Human Research Ethics Committee and participants. The primary investigator will make safety and progress reports to the ethics committee at least annually and within 3 months of study completion. Adverse events will be tracked in the following ways: (1) a >10-point worsening (at any time point compared with the previous time points) in PROMIS T scores on the anxiety or depressive symptom outcomes; (2) two questions administered at both T=110, 49.1%) and CL  groups. In total, 61 CM participants and 75 CL participants have completed the intervention and postintervention assessment surveys.Recruitment for this trial began in September 2020 and all follow-up data were collected in April 2022. A total of 224 patients were randomized to the CM  compared with an active comparator intervention (CL) in improving emotion regulation, symptoms of anxiety and depression, and QoL in cancer survivors. The findings from this trial will extend previous pilot results, which suggested that each CM module may be independently effective in improving cancer survivors’ mental health and emotion regulation .The results of this trial will be interpreted in the context of its limitations. For instance, as the treatment group’s effects will not be compared against the absence of any intervention , we will not be able to assess whether improvements in either group are due to the actual interventions or a result of naturalistic tendencies . In addition, the intervention intensity and thus the potential duration of CM and CL differ. Unlike in CL, CM includes mandatory core activities in each module, which must be completed before participants can progress to the subsequent modules. This means that CM participants are likely to take longer to complete the intervention, which could impact the outcomes and attrition rates. Finally, CM and CL are English language–based interventions, and the trial excludes those who cannot read or write in English, which may limit the generalizability of findings to English-speaking populations only.Despite these limitations, this is the first randomized controlled trial to evaluate an emotion-focused, UP-adapted, and internet-delivered intervention designed for cancer survivors to improve their mental health and QoL. Considering 1) that most of those diagnosed with cancer survive their diagnosis , (2) tha that mosAnother strength of this study relates to its unique study design. The trial will allow not only an assessment of symptom improvement but also an evaluation of factors that account for symptom changes. Specifically, by concurrently measuring emotion regulation and psychopathological symptoms at all time points, the design will enable the assessment of more nuanced relationship patterns between these closely linked variables. Thus far, few studies assessing applications of the UP have been able to clearly decipher whether improvements in emotion dysregulation are truly mediating symptom improvements.Furthermore, the study will allow a detailed assessment and comparison of each module’s effects in the treatment versus control conditions. This mechanistic analysis allows for greater treatment optimization. For example, if the target outcome of one module is found to contribute minimally compared with the other modules, then theoretically, the less effective module may be removed or decreased in intensity to reduce intervention duration and improve treatment efficiency.In addition, the CL intervention material may prove to be a rather formidable control comparator. This is because lifestyle factors, such as diet , exercis


The procedure was validated by a soil reference material (NIST 2710), and no external or cross-contamination was observed for the 27 trace elements studied. The results demonstrate the suitability of this protocol for ultra-trace analysis when the utilization of HF is mandatory.The complete dissolution of silicate-containing materials, often necessary for elemental determination, is generally performed by microwave-assisted digestion involving the forced use of hydrofluoric acid (HF). Although highly efficient in dissolving silicates, this acid exhibits many detrimental effects  that make its removal after digestion essential. The displacement of HF is normally achieved by evaporation in open-vessel systems: atmospheric contamination or loss of analytes can occur when fuming-off HF owing to the non-ultraclean conditions necessarily adopted for safety reasons. This aspect strongly hinders determination at the ultra-trace level. To overcome this issue, we propose a clean and safe microwave-assisted procedure to induce the evaporative migration of HF inside a sealed “vessel-inside-vessel” system: up to 99.9% of HF can be removed by performing two additional microwave cycles after sample dissolution. HF migrates from the digestion solution to a scavenger (ultrapure H Microwave-assisted sample digestion is an important routine technique for the effective and safe dissolution of solid samples and subsequent elemental composition or isotope ratio analyses of a wide variety of matrices such as soils ,2,3, sedGenerally, the solid samples are digested using a mixture of pure acids inside a sealed polymeric container  and Polytetrafluoroethylene (PTFE)) under microwave (MW) irradiation, to reach elevated temperature and pressure which favor matrix dissolution. The choice of the acid mixture is key for fast and effective digestion and strictly depends on the nature of the materials to be dissolved and the analytes to be determined. For instance, silicate-containing samples normally require the presence of hydrofluoric acid (HF) for quantitative MW digestion, as it is able to efficiently dissolve silicates ,4,6,11. 3BO3) is also widely used to mask HF after MW-assisted digestion. However, the addition of H3BO3 may induce spectral interferences [The other strategy to solve this problem implies the removal of HF by evaporation. This method is normally preferred, as the addition of other concentrated acids (necessary to displace HF) allows to redissolve insoluble fluorides improving the overall elements recovery ,16,17. Hferences ,19 and aferences . Finallyferences . Furtherferences  and of tferences ,24 durinConsidering the drawbacks evidenced by existing methods, the development of a new fluoride removal protocol may be favorable if safer, cleaner and more controlled conditions are achieved, maintaining the same HF displacement efficiency.3BO3) are tested as scavengers for the outer solution. A careful evaluation of the eventual cross-contamination effects is also presented. Finally, a certified soil reference material is digested to validate the proposed method.Based on these considerations, herein, we propose a protocol to cleanly and efficiently remove HF from digestion solutions. The proposed procedure is executed using a sealed “vessel-inside-vessel” system  by perfo3  were used for sample digestion. Hydrogen Peroxide  was used for soil moistening and organic matter decomposition. Ultrapure water was used for the preparation of each solution used and was produced with a Sartorius Arium mini plus UV Lab Water System. Saturated H3BO3 solutions were obtained by dissolving the solid  in ultrapure water. Standard fluoride solutions  for IC analysis were obtained by dilution from a 1000 mg L−1 standard solution . A multi-elemental standard solution  was used for ICP-MS standard preparation and for samples preparation in cross-contamination tests. A certified soil from the National Institute of Standard & Technology  was used as the Standard Reference Material (SRM) for protocol validation.Ultrapure hydrofluoric acid  and ultrapure nitric acid produced by sub-boiling distillation  from com3BO3 solution as scavenging agents. Six samples were always loaded into the six-position carousel for all the reported experiments  to guarantee the same conditions inside the reactor for all batches. The uniform power feeding distribution was ensured by keeping the carousel under constant rotation and filling all vessels with solutions possessing an analogous composition, thus having the same absorption behavior as microwaves. All quantitative results in this work  are expressed as mean value ± two times the standard deviation determined over five replicated samples according to this batch configuration.An ETHOS One  MW digestion system equipped with 6 PTFE vessels  was used for all MW-assisted acid digestion reported in this work. A loosely tightened PFA vessel  with a round-shaped bottom interior  containing the digestion solution was placed inside each PTFE vessel. A scavenger solution was eventually added outside the PFA container . Three dFirst cycle (sample digestion): 2 mL of HF were placed inside the PFA container, eventually together with the solid sample to be digested. The scavenging solution (2 mL) was placed in the external PTFE vessel. The application of both MW power programs shown in 3 was added into the PFA vessel to favor HF evaporation, and the scavenging solution was replaced with a fresh one. The MW power program depicted in Second cycle (first HF evaporation step): 1 mL of HNOThird cycle (second HF evaporation step): an identical repetition of the second cycle which aimed to completely remove residual HF.The optimized sample digestion and HF displacement tests were conducted as follows:As mentioned above, two different MW power programs were developed in the present work. The control of the MW process by temperature measurement was intentionally avoided as the temperature probe in vessel-inside-vessel systems cannot monitor the condition of the digestion solution but only that of the external scavenging solution. This constraint may lead to inaccurate or non-reproducible conditions if a temperature program is applied.After each MW cycle, the solutions from both the inside and outside vessels were collected for fluoride determination by Ion Chromatography (IC) analysis using a Metrohm ECO IC equipped with a Metrohm 813 compact autosampler .2O2; the mixture was heated up on a hot plate at 50 °C for 30 min, under a laminar flow hood, to decompose most of the organic material. After the moistening procedure, 1 mL of HF and 1 mL of HNO3 were added to the PFA vessel, and the digestion program  and then with a 2% wt. HNO3 solution  bottles and diluted to 30 g with ultrapure water and then again, a dilution of 1:100 was performed before instrumental analysis. Prior to their use, the LDPE bottles were thoroughly cleaned and decontaminated by a 3-stage procedure involving prolonged washing with a detergent solution (4 mL Ltails in ).A Thermo Scientific ICAP Q inductive coupled plasma mass spectrometer  was used to determine the concentration of 10 trace elements . Measurements were performed using a He-collision cell in kinetic energy discrimination (KED) mode.Cross-contamination tests were performed to evaluate the migration of trace elements from the sample solution to the scavenging one and vice versa. Both tests were performed by adding an aliquot of the multi-elemental standard solution used for ICP-MS analysis in the digestion solution and scavenger, alternatively. A total of 27 elements were analyzed .−1 for the selected elements  in case of complete recovery. The obtained samples were then analyzed by ICP-MS.Inside-to-Outside  migration: 100 µL of the multi-elemental standard solution were added to the hydrofluoric acid contained in the inner PFA vessel. Once the digestion/evaporation protocol was completed, the digestion solution was transferred to LDPE bottles and diluted to 20 g with ultrapure water to obtain a final concentration of 50 µg LOutside-to-Inside  migration: 100 µL of the multi-elemental standard solution were added to ultrapure water in the outside vessel. Once the digestion/evaporation protocol was completed, the digestion solution was transferred to LDPE containers, diluted to 20 g with ultrapure water and analyzed by ICP-MS.Tests were conducted as follows:3 is added to the sample solution). Thus, the potential overall benefit of this proposed strategy is that it paves the way to perform determinations at the ultra-trace level even when the utilization of HF is mandatory.The idea behind the proposed hydrofluoric acid removal method is to induce its evaporation directly inside a sealed PTFE vessel rather than using an open-vessel system . To achieve this goal, a vessel-inside-vessel system was conceived : a small3BO3 solution as scavenging agents. The latter is expected to act as an actual scavenger: the reaction with HF that leads to the formation of HBF4 species may possibly shift the evaporation equilibrium and accelerate the migration process. Each experiment was conducted as reported in Preliminary tests were conducted to achieve the proof of concept of the expected process and evaluate its effectiveness. Different experimental conditions were tested by varying the content of the outer PTFE vessel. Three different conditions were tested: (i) the absence of a scavenging solution, (ii) 2 mL of ultrapure water and (iii) 2 mL of saturated H3BO3 saturated solution. In both cases, slightly lower removal was observed (98.6 ± 0.6%).The obtained results are summarized in All these findings suggest that the mechanism behind hydrofluoric acid migration is merely physical: the temperature reached inside the inner vessel allows HF evaporation which then tends to occupy all the accessible volume, i.e., it significantly migrates to the outer vessel. Such a mechanism fits very well with the observation that the variation of the chemistry outside the digestion vessel has no positive or negative effects on the migrated amounts. The slightly higher migration efficiency observed when using no scavenging solutions could be explained considering that microwaves can only be captured by the HF inner solution, which is then consistently overheated.In preliminary digestion experiments carried out on quartz powders, it was noticed that, in the absence of any outer scavenging solution, incomplete dissolutions were observed. This evidence could be ascribed to too rapid HF evaporation in the first cycle. For this reason, all further experiments were always conducted using 2 mL of ultrapure water in the outer vessel: the use of boric acid was discarded because it does not improve the removal efficiency, and, therefore, it is possible to avoid the use of unnecessary chemicals that could induce unwanted contaminations. Such choice also allowed for the handling of diluted HF solutions as wastes after digestion, which can be more safely dismissed or recycled for other analytical or non-analytical purposes  from the digestion solution to the scavenger and (ii) from the scavenger to the digestion solution at the end of entire digestion/evaporation protocol .3 are probably not suitable for the complete digestion of the organic fraction.The MW program depicted in 2O2 was conducted at around 50 °C on a hot plate under a laminar flow hood to decompose organic matter. Secondly, 2 mL of a 1:1 mixture of HF and HNO3 was added to the moistened soil, and the MW-assisted digestion procedure was carried out by revising the MW power program. A low power step (150 W for 30 min) was introduced to retard HF evaporation  for HF evaporation was proposed and proved effective for the fast, safe and especially clean removal of hydrofluoric acid. This last issue represents the major advantage of the proposed protocol, as HF removal is performed in sealed vessels, thus ruling out any possible contamination in this crucial step. This protocol is therefore compliant with elemental determination at ultra-trace levels when the utilization of HF is mandatory.It was determined that the mechanism behind hydrofluoric acid removal is purely physical: HF evaporation in the digestion vessel migrates into the large volume of the outer PTFE vessel and, after cooling down, condenses into the scavenging solution. The presence of ultrapure water as a scavenging solution in the PTFE vessel allows for better control of the evaporation process and the handling of diluted hydrofluoric acid solutions, which can be safely dismissed or collected and recycled for other applications at the end of each MW cycle. This side feature is perfectly in line with the principles of green analytical chemistry, making the proposed method even more attractive.Finally, the effectiveness of the MW-assisted digestion/evaporation protocol was validated on the NIST 2710 certified soil.


Existing research on mycelium-based materials recognizes the binding capacity of fungal hyphae. Fungal hyphae digest and bond to the surface of the substrate, form entangled networks, and enhance the mechanical strength of mycelium-based composites. This investigation was driven by the results of an ongoing project, where we attempt to provide basic concepts for a broad application of a mycelium and chipped wood composite for building components. Simultaneously, we further explore the binding capacity of mycelium and chipped wood composites with a series of experiments involving different mechanical interlocking patterns. Although the matrix material was analyzed on a micro-scale, the samples were developed on a meso-scale to enhance the bonding surface. The meso-scale allows exploring the potential of the bio-based material for use in novel construction systems. The outcome of this study provides a better understanding of the material and geometrical features of mycelium-based building elements. Looking for alternative renewable materials, recent research has suggested that fast-growing organisms such as Fungal mycelium can be engineered to produce novel construction materials [Although using renewable raw materials, e.g., wood, presents itself as a logical strategy to withstand COaterials ,4,5,6. MOur team has been conducting research experiments by developing methods for influencing hyphal growth with the primary objective to provide a mycelium-based composite with particular stability and increased strength ,9,10,11.Ganoderma lucidum (GL) and Pycnoporus sanguineus (PS), and the substrate is beechwood. Fungi belonging to the genus Basidiomycetes, such as GL, Ganoderma applanatum, Trametes hirsuta, Trametes versicolor, or Fomes fomentarius, are mostly found in forests and fulfill, among other things, the task of decomposing deadwood. Consequently, we chose timber as the lignocellulosic substrate. Wood consists of approx. 25–30 wt% lignin, 25–30 wt% pentosans (hemicellulose), 40–50 wt% cellulose, and other components such as resinous substances, terpenes fats, fatty acids, proteins, and minerals. Fungi can decompose lignin, hemicellulose, and cellulose into their subunits by releasing enzymes such as cellulases, laccases, amylases, proteases, or lipases into the immediate environment to degrade the substrate. Subsequently, the degradation products are absorbed by the hyphae and used to grow the fungus [The findings of this study concern a specific fungal–substrate composition: the fungal mycelium is derived from e fungus . The sele fungus . Althoug(1)Selecting the lignocellulosic substrate.(2)Inoculating the substrate with fungal spores and fungal mycelium.(3)Mixing the inoculated substrate so that a homogeneous growth of the mycelium can be achieved.(4)Incubating the obtained mixture from Step (3) in a first incubation phase for a time between 5 and 7 days, at a temperature ranging from 20 °C to 28 °C, and at humidity ranging from 80% to 95% to achieve the cross-linked growth of the mycelium around the substrate.(5)Placing the obtained incubated mixture from Step (4) in shaping containers defining the shape of the base unit of the composite material, and incubating the mixture in a second incubation phase for a time between 3 and 10 days, at a temperature ranging from 20 °C to 30 °C, and at humidity ranging from 80% to 95% in order to obtain the cross-linked growth of the mycelium around the substrate.(6)Obtaining at least two base units of the composite with at least one bonding interface.(7)Joining at least two basic units through the binding interface and incubating for a time between 10 and 30 days, at a temperature in the range of 15 °C to 30 °C, and at a humidity in the range of 80% to 95% to promote the formation of search hyphae and skeletal hyphae between said basic units and to obtain mycelium and wood-based composite specimens (3rd incubation phase) .As mentioned before, we seek to provide a mycelium-based composite with a particularly stable and increased strength for use in construction. The manufacturing method proposed consists of the following steps:(8)Denaturizing the specimen at a temperature range of 65 °C to 90 °C and obtaining a mycelium-based lignocellulosic composite with a residual moisture content of 10% to 12% by weight based on the total weight of the composite.Steps (1)–(4) of the manufacturing process are similar to those described in the previous publications of this research team . It is iA proper joining configuration is achieved by placing at least two basic units against each other, even though more basic units are able to be attached to form the compound units. Subsequently, the joined basic units are incubated in a third incubation phase (Step (7)). The fungal mycelium grows within the binding interface and couples the two basic units of the composite material.Finally, the composite material obtained in Step (8) is denaturized to bulk consistency. A mycelium and wood-based lignocellulose composite material is obtained with 10% to 15% residual moisture content.All manufacturing process steps described above result in the fungal mycelium forming predominantly skeletal hyphae at the joint interface of the composite material, which, due to its morphology, leads to the increased strength of the material in the binding interface.The present research developed a method wherein the binding interface of at least two basic units has a non-planar surface and wherein a factor between 1.2 and 5 enlarges the binding interface compared to that of a planar surface. Whether the surface area of the bonding interfaces is increased by non-planar joint means that the surface of the connection interface has teeth-like interlocking. It could be arranged symmetrically or asymmetrically, which can be connected by the interface of at least two basic units with teeth-like interlocking in the longitudinal section.The surface of the connecting interface of the base units is enlarged with teeth-like interlocking with jagged (see test specimens Sch2 and Sch3) or rounded protrusions (see test specimens Sch4 and Sch5). These protrusions may be continuous or have at least one short planar section between each jag or curve.Six different shaping containers were developed to compare, on the one hand, a single test specimen as a single solid unit (Sch0), without binding interface, with at least two base units test samples (Sch1–5). On the other hand, different geometries of the binding interface were developed to compare the influence of the planar and non-planar binding interfaces.3 capacity. Each container had a 134.4 cm3 in a cube-like container (a × a × h). Due to the exploratory character of the testing, two different substrate–fungus combinations were tested: beechwood–GL and beechwood–PS. This variation led to a total amount of 24 Sch test specimens. The shear tests were conducted under laboratory conditions with the corresponding setup, using a Zwick Zmart.Pro testing machine with a testing speed of 3 mm/min. The tests were documented with the help of photographs, and the force deformation curve was digitally recorded with ZickRoell software. The recorded data were subsequently edited and graphically represented in strength diagrams.Test methods determined the shear strength of the test specimens according to DIN-EN 12090:2013 test standards as illustrated in The obtained material was examined to determine its shear strength. As mentioned before, the tests were carried out on Sch0 to Sch5 test specimens under DIN-EN 12090:2013. The force–displacement curve was recorded for each test, and the shear strength was derived from it .The first set of analyses presented an apparent variation in fracture behavior. As shown in Non-homogeneous growth on the test specimens may have contributed to the increased variation in the curves in both My8 and My9. The growth variety may result from non-proper environmental conditions in one or more of the cultivation stages during manufacturing.From the observation of the red curve (Sch1 = planar binding interface) in contrast to the rest of them , an influence on the geometry of the inner binding interfaces can be deduced. Consequently, different interface geometries influence the material’s behavior in terms of failure mode, stiffness, and shear strength. The force–displacement curve of specimen Sch1 (red curves) with a planar connection interface, for example, demonstrates an early start of material fracture, which is indicated by a sharp drop in the curve. However, due to the significant curve variation, it has not been possible to determine whether the surface area increase or geometry variation in the binding interface has increased the resistance. Additionally, it would be necessary to repeat the tests with a more significant number of test specimens to determine if the variation between jagged and rounded geometry plays a role in the binding capacity.The results show that by using the binding ability of the mycelium, it is possible to influence the material properties of composites through the targeted arrangement of joining surfaces with higher stiffness. In this way, direction-dependent material behavior can also be generated. It is also interesting to note that the study of shear strengths reveals that both the interface arrangement and the shear strength are essentially derived from the interface configuration.2 footprint compared to the vast majority of standard building materials. A wide variety of mycelium-based products have been developed, such as packaging [2). Although non-planar binding interfaces present higher shear strength (up to 83%), the results obtained by planar binding interfaces have significant implications for mycelium-based materials. This process could allow the production of multi-laminar elements and could replace oil-based glue materials. Binding-specific manufacturing will doubtless be much scrutinized, but due to the increase in the shear strength, we can conclude that the production process presents advantageous conditions for conglomerates and laminar mycelium and wood-based materials.The attractiveness of mycelium as a matrix material lies on the one hand in its biological origin, which due to its chemically untreated state, can be easily integrated into the biological material cycle for the circular economy . Due to ackaging  or insulackaging . In geneWith the investigations presented in this paper, it could be assumed that several basic units’ laminar composition can positively influence the load-bearing behavior of mycelium-based materials. However, multiple basic unit composition is not the only factor to consider to achieve building standard requirements. Other factors that positively influence the strength and stiffness properties of mycelium-based materials are mycelium–substrate combinations which could lead to optimal growth or optimal mechanical qualities, and the increase in the material’s density by compression . FurtherOne of the most important findings of this research is that the geometry of the interfaces can influence fracture behavior. The work reported in this manuscript resulted in the Patent Application No. (DRN) 2021122113010200DE.


Furthermore, we estimate UHI in Chicago with 10-min temporal frequency and 1-km spatial resolution on the hottest day in 2018. It is demonstrated that the RFR model can accurately predict UHI at fine spatiotemporal scales with high-frequency urban sensor network data integrated with satellite remote sensing data.Due to climate change and rapid urbanization, Urban Heat Island (UHI), featuring significantly higher temperature in metropolitan areas than surrounding areas, has caused negative impacts on urban communities. Temporal granularity is often limited in UHI studies based on satellite remote sensing data that typically has multi-day frequency coverage of a particular urban area. This low temporal frequency has restricted the development of models for predicting UHI. To resolve this limitation, this study has developed a cyber-based geographic information science and systems (cyberGIS) framework encompassing multiple machine learning models for predicting UHI with high-frequency urban sensor network data combined with remote sensing data focused on Chicago, Illinois, from 2018 to 2020. Enabled by rapid advances in urban sensor network technologies and high-performance computing, this framework is designed to predict UHI in Chicago with fine spatiotemporal granularity based on environmental data collected with the Array of Things (AoT) urban sensor network and Landsat-8 remote sensing imagery. Our computational experiments revealed that a random forest regression (RFR) model outperforms other models with the prediction accuracy of 0.45 degree Celsius in 2020 and 0.8 degree Celsius in 2018 and 2019 with mean absolute error as the evaluation metric. Humidity, distance to geographic center, and PM The city has diverse land cover types, from dense urban canyons to residential. Adjacent to Lake Michigan, the second largest of the Great Lakes at 58,030 km2, the city manages nearly 9,000 acres (36 km2) of green space—the largest municipal park system in the USA. The city anchors Cook County, which manages some 70,000 acres (283 km2) of forest preserves and parks. Particularly within the city, the diversity of land cover also reflects significant challenges with under-resourced communities resulting from over a century of social and racial segregation issues  concentration), humidity, light intensity, and land surface characteristics.As the extensive body of prior UHI studies were conducted using thermal remote sensing data from satellites like Landsat and Aster that record measurements for the same location weekly or bi-weekly, data availability is inadequate to take advantage of machine learning models for fine-scale characterization of UHI. The temporal aspect of UHI was often not adequately addressed due to the data limitation. The cyberGIS framework aims to fill this gap by predicting UHI within Chicago at fine spatial and temporal scales. The framework also is designed to gain better understanding about the relationships between UHI and multiple environmental factors such as air quality indicators  from 2018 to 2020. Due to an insufficient number of AoT nodes deployed in the first phase of the AoT project, 2016 and 2017 are excluded from this study. Another data source used in this study is satellite remote sensing data. In particular, Landsat 8 Collection-2 Level-2 data covering the city of Chicago during the summer of 2018 to 2020 are used to provide important information regarding the surrounding physical microenvironment of each AoT node. Landsat-8 Collection-2 Level-2 data provides high-quality images that have gone through geometric-related preprocessing including Terrain Precision Correction, Systematic Terrain Correction, and Geometric Systematic Correction as well as atmospheric correction using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) and Land Surface Reflectance Code (LaSRC) surface reflectance algorithms , and 10 μm particles are hypothesized to have a positive correlation with UHI effects; 3) physical environmental variables including Band1 to Band7 values collected from Landsat 8 Collection-2 Level-2 and the Euclidean distance between each AoT node to the geographic center of the city of Chicago  tempOur method is centered on a cyberGIS framework for integrating multiple machine learning models into a multi-step workflow encompassing five major components – data preparation, data preprocessing, modeling, validation, and prediction. As shown in Fig. , where Q1 is the first quantile, Q3 is the third quantile, and IQR is the difference between Q3 and Q1  method is used to fill in the missing values Wilson, . MICE isDue to computational intensity of handling the large dataset, machine learning model training was conducted using Bridges-2 – a high-performance computer at the Pittsburgh Supercomputing Center. Graphics processing unit (GPU) Tesla v100 is equipped within Bridges-2 for model training. After normalizing the independent variables  and Mean Absolute Error (MAE) are adopted as evaluation metrics:where Fine spatiotemporal granularity prediction of temperature and spatiotemporal clusters of UHI in Chicago is conducted with the best-performing machine learning method. 1 km and 10 min are selected as spatial and temporal resolution respectively. For each spatiotemporal point, the urban sensor-related independent variables are estimated using inverse-distance weighing (IDW) spatial interpolation based on the values of nearby AoT nodes. Remote sensing imagery-related independent variables are estimated daily using linear interpolation based on the two most recent remote sensing imageries covering Chicago at the location we are interested in.First in Sect. The testing metrics of polynomial regression and machine learning models are shown in Table r-square from 2018 to 2020 are 0.335, 0.384 and 0.696 respectively. Both the r-square and the evaluating metrics, including MSE and MAE, show that polynomial regression cannot be used effectively in predicting UHI with the current data we have.For 2018 and 2019, both ANN and SVM models outperform the polynomial regression model. However, in 2020, the result with the polynomial regression model is better than the results from ANN and SVM. As the most straightforward model, the polynomial regression model did not perform well in predicting UHI as expected. The R-square value for polynomial regression in 2018, 2019 and 2020 are 0.335, 0.385 and 0.697 and the adjusted To compare between two machine learning models ANN and SVM, the MSE evaluation result from ANN is generally more significant, especially in 2020. High MSE and relatively low MAE indicate some extreme values predicted by ANN, showing the model can be unstable in the prediction of temperature. Even though the SVM model outperforms ANN with MSE used as the evaluation metric, the ANN outperforms SVM in 2019 and 2020 with MAE as the evaluation metric. The effectiveness of ANN and SVM are considered similar in predicting temperature with the existing dataset. However, these two models are not appropriate to be used in real-world scenarios because their prediction results are mediocre and the RFR model outperforms both models by a large margin. Because human activities could play a significant role in the generation of UHI effects  to 78 degrees Fahrenheit (25.6 degrees Celsius) based on the weather report from the National Oceanic and Atmospheric Administration (NOAA) and AccuWeather. On that day, there were in total 46 functioning AoT nodes available in Chicago.To demonstrate how the RFR model predicts spatial patterns of UHI, we create heatmaps to visualize UHI on the hottest day in Chicago in 2018 and 2019 as shown in Figs. th, 2018, a heatmap of UHI is generated using the average observed temperature from those AoT nodes based on bilinear interpolation. Similarly, the UHI distribution heatmaps are generated with the temperature predicted with the RFR model and ANN model respectively. Figure For all the active AoT nodes in Chicago, based on the highest temperature recorded by each node on August 27th with the highest temperature of 96 degrees Fahrenheit (35.6 degrees Celsius) and the lowest temperature on that day being 76 degrees Fahrenheit (24.4 degrees Celsius). On July 20th, 2019, there were 39 functioning AoT nodes recording the surrounding environmental attributes including temperature, humidity, PM2.5, etc. As we can see from Fig. The same process is applied to the hottest day in 2019 to generate heatmaps for comparison. Based on the weather report from NOAA and AccuWeather, the hottest day in Chicago in 2019 is July 20Figure We apply the RFR model with 1 km as spatial resolution and 10 min as temporal granularity to delineate spatiotemporal clusters of UHI within Chicago on the hottest day in 2018. Spatiotemporal points with extreme high temperature are clustered for visual interpretation. As shown in Fig. 2.5 concentration are found to be important factors contributing to the model performance of RFR model. Second, the RFR model is stable as the performance of the model is consistent during all four months in the summers of 2018, 2019, and 2020. We constructed heatmaps to compare the observed UHI and predicted UHI on the hottest day in 2018 and 2019. The heatmaps show that the predicted spatial patterns are similar to the corresponding patterns from the observed UHI based on the urban sensor network data. Last, the framework is applied to delineate fine-scale spatiotemporal patterns of UHI with 1-km spatial resolution and 10-min temporal resolution using the RFR model on the hottest day in 2018. Our framework has demonstrated that the RFR model can be used effectively to predict spatiotemporal distributions of UHI.This study has developed a framework to integrate cyberGIS and machine learning for fine spatiotemporal granularity prediction of UHI with satellite remote sensing data and high-frequency urban sensor network data. This framework is designed to assess the performance of the polynomial regression model, SVM, ANN, and RFR model in predicting spatial and temporal patterns of UHI in Chicago for the years of 2018, 2019, and 2020. First, the RFR model is found to achieve the best performance among all the machine learning models with MAE being 0.45 degrees Celsius in 2020 and around 0.8 in 2018 and 2019. Humidity, distance to geographic center and PM2.5, temperature, relative humidity, and multiple air pollutant gases (Daepp et al., We plan to conduct future work in three aspects. First, human activities are not fully addressed in our study, especially for the travel activities involving vehicles, as they emit not only heat but also exhaust gas, which is believed to cause UHI. Also, manufacturing activities and even the use of electric appliance such air conditioners by city residents may result in temperature increases in some places. As different human activities may contribute to the formation of UHI, the framework could be improved by integrating human activities data. Second, as machine learning models perform better with more high-quality data, the framework could be improved with more sensors and nodes deployed in urban environments. Finally, two AoT follow-on projects are under way that are providing new, near real-time urban sensing data. First, nodes with more powerful edge processors that can be customized with project-specific sensor packages are being deployed to replace AoT nodes in Chicago as part of a National Science Foundation Mid-Scale Research Infrastructure development project called SAGE (Beckman et al.,