Local spatiotemporal dynamics of particulate matter and oak pollen measured by machine learning aided optical particle counters.

Conventional techniques for monitoring pollen currently have significant limitations in terms of labour, cost and the spatiotemporal resolution that can be achieved. Pollen monitoring networks across the world are generally sparse and are not able to fully represent the detailed characteristics of airborne pollen. There are few studies that observe concentrations on a local scale, and even fewer that do so in ecologically rich rural areas and close to emitting sources. Better understanding of these would be relevant to occupational risk assessments for public health, as well as ecology, biodiversity, and climate. We present a study using low-cost optical particle counters (OPCs) and the application of machine learning models to monitor particulate matter and pollen within a mature oak forest in the UK. We characterise the observed oak pollen concentrations, first during an OPC colocation period (6 days) for calibration purposes, then for a period (36 days) when the OPCs were distributed on an observational tower at different heights through the canopy. We assess the efficacy and usefulness of this method and discuss directions for future development, including the requirements for training data. The results show promise, with the derived pollen concentrations following the expected diurnal trends and interactions with meteorological variables. Quercus pollen concentrations appeared greatest when measured at the canopy height of the forest (20-30 m). Quercus pollen concentrations were lowest at the greatest measurement height that is above the canopy (40 m), which is congruent with previous studies of background pollen in urban environments. The attenuation of pollen concentrations as sources are depleted is also observed across the season and at different heights, with some evidence that the pollen concentrations persist later at the lowest level beneath the canopy (10 m) where catkins mature latest in the season compared to higher catkins.

Machine learning methods for low-cost pollen monitoring - Model optimisation and interpretability.

Pollen is a major issue globally, causing as much as 40 % of the population to suffer from hay fever and other allergic conditions. Current techniques for monitoring pollen are either laborious and slow, or expensive, thus alternative methods are needed to provide timely and more localised information on airborne pollen concentrations. We have demonstrated previously that low-cost Optical Particle Counter (OPC) sensors can be used to estimate pollen concentrations when machine learning methods are used to process the data and learn the relationships between OPC output data and conventionally measured pollen concentrations. This study demonstrates how methodical hyperparameter tuning can be employed to significantly improve model performance. We present the results of a range of models based on tuned hyperparameter configurations trained to predict Poaceae (Barnhart), Quercus (L.), Betula (L.), Pinus (L.) and total pollen concentrations. The results achieved here are a significant improvement on results we previously reported: the average R2 scores for the total pollen models have at least doubled compared to using previous parameter settings. Furthermore, we employ the explainable Artificial Intelligence (XAI) technique, SHAP, to interpret the models and understand how each of the input features (i.e. particle sizes) affect the estimated output concentration for each pollen type. In particular, we found that Quercus pollen has a strong positive correlation with particles of optical diameter 1.7-2.3 µm, which distinguishes it from other pollen types such as Poaceae and may suggest that type-specific subpollen particles are present in this size range. There is much further work to be done, especially in training and testing models on data obtained across different environments to evaluate the extent of generalisability. Nevertheless, this work demonstrates the potential this method can offer for low-cost monitoring of pollen and the valuable insight we can gain from what the model has learned.

Delayed diagnosis of oral lymphoma: a case series.

Lymphomas are the second most common neoplasm in the head and neck. The clinical and radiographic presentation of non-Hodgkin lymphoma in the oral cavity is non-specific and can be hard to differentiate from other common infectious or inflammatory conditions. We report four cases of lymphoma of the head and neck, which presented as odontogenic infection, osteomyelitis, or cutaneous infection, and subsequently led to a delay in provision of appropriate treatment. Correlation between clinical, radiographic and histological findings is essential in reaching an accurate diagnosis. It is important for clinicians to consider malignant lesions, such as lymphoma, in the differential diagnosis of pain, swelling, tooth mobility or radiographic radiolucencies. Clinicians should maintain a high level of suspicion for malignancy when inflammatory lesions fail to respond to normal modes of treatment.

Constructing a pollen proxy from low-cost Optical Particle Counter (OPC) data processed with Neural Networks and Random Forests.

Pollen allergies affect a significant proportion of the global population, and this is expected to worsen in years to come. There is demand for the development of automated pollen monitoring systems. Low-cost Optical Particle Counters (OPCs) measure particulate matter and have attractive advantages of real-time high time resolution data and affordable costs. This study asks whether low-cost OPC sensors can be used for meaningful monitoring of airborne pollen. We employ a variety of methods, including supervised machine learning techniques, to construct pollen proxies from hourly-average OPC data and evaluate their performance, holding out 40 % of observations to test the proxies. The most successful methods are supervised machine learning Neural Network (NN) and Random Forest (RF) methods, trained from pollen concentrations collected from a Hirst-type sampler. These perform significantly better than using a simple particle size-filtered proxy or a Positive Matrix Factorisation (PMF) source apportionment pollen proxy. Twelve NN and RF models were developed to construct a pollen proxy, each varying by model type, input features and target variable. The results show that such models can construct useful information on pollen from OPC data. The best metrics achieved (Spearman correlation coefficient = 0.85, coefficient of determination = 0.67) were for the NN model constructing a Poaceae (grass) pollen proxy, based on particle size information, temperature, and relative humidity. Ability to distinguish high pollen events was evaluated using F1 Scores, a score reflecting the fraction of true positives with respect to false positives and false negatives, with promising results (F1 ≤ 0.83). Model-constructed proxies demonstrated the ability to follow monthly and diurnal trends in pollen. We discuss the suitability of OPCs for monitoring pollen and offer advice for future progress. We demonstrate an attractive alternative for automated pollen monitoring that could provide valuable and timely information to the benefit of pollen allergy sufferers.

Towards European automatic bioaerosol monitoring: Comparison of 9 automatic pollen observational instruments with classic Hirst-type traps.

To benefit allergy patients and the medical practitioners, pollen information should be available in both a reliable and timely manner; the latter is only recently possible due to automatic monitoring. To evaluate the performance of all currently available automatic instruments, an international intercomparison campaign was jointly organised by the EUMETNET AutoPollen Programme and the ADOPT COST Action in Munich, Germany (March-July 2021). The automatic systems (hardware plus identification algorithms) were compared with manual Hirst-type traps. Measurements were aggregated into 3-hourly or daily values to allow comparison across all devices. We report results for total pollen as well as for Betula, Fraxinus, Poaceae, and Quercus, for all instruments that provided these data. The results for daily averages compared better with Hirst observations than the 3-hourly values. For total pollen, there was a considerable spread among systems, with some reaching R2 > 0.6 (3 h) and R2 > 0.75 (daily) compared with Hirst-type traps, whilst other systems were not suitable to sample total pollen efficiently (R2 < 0.3). For individual pollen types, results similar to the Hirst were frequently shown by a small group of systems. For Betula, almost all systems performed well (R2 > 0.75 for 9 systems for 3-hourly data). Results for Fraxinus and Quercus were not as good for most systems, while for Poaceae (with some exceptions), the performance was weakest. For all pollen types and for most measurement systems, false positive classifications were observed outside of the main pollen season. Different algorithms applied to the same device also showed different results, highlighting the importance of this aspect of the measurement system. Overall, given the 30 % error on daily concentrations that is currently accepted for Hirst-type traps, several automatic systems are currently capable of being used operationally to provide real-time observations at high temporal resolutions. They provide distinct advantages compared to the manual Hirst-type measurements.

How effective is toluidine blue for screening and diagnosis of oral cancer and premalignant lesions?

Design A systematic review and bivariate meta-analysis was designed to determine the efficacy of toluidine blue (TB) in the screening and diagnosis of oral cancer and premalignant lesions. Six databases were reviewed independently by two authors to identify relevant studies.Case selection Inclusion criteria comprised prospective or retrospective studies comparing TB with chemiluminescence or clinical examination, which incorporated sensitivity and specificity analyses. Studies regarding diagnosis of non-oral tumours were excluded, as well as case reports and review articles.Data analysis Diagnostic accuracy was analysed using diagnostic odds ratio (DOR) with 95% confidence intervals (CI). Summary receiver operating characteristic (SROC) curves and the inter-rater agreement were also analysed. Cohen's kappa coefficient and Fisher z-values were used to estimate reliability and stabilise variance. Homogeneity analyses were performed using the Q statistic. Forest plots were drawn for the sensitivity, specificity, negative predictive values, and SROC curves.Results Twenty-nine studies comprising 1,921 participants were included in the meta-analysis. The DOR of TB was 7.017 (95% CI, 4.544; 10.836). Nine studies compared TB with chemiluminescence; TB had a lower sensitivity but a higher specificity. Compared with clinical examination in four studies, TB had a higher sensitivity and specificity. TB has a sensitivity of 73% and specificity of 69%, and was found to be more sensitive in severe dysplasia but more specific in benign lesions.Conclusions The diagnostic accuracy of TB for oral cancer or premalignant lesions is greater than clinical examination alone; however, it is not reliable enough for TB to be used as a screening method in isolation. TB is a diagnostic aid that can be recommended in adjunct with chemiluminescence or other techniques.

How successful are maxillary implant-retained overdentures on two or four implants?

Design A randomised crossover clinical trial was designed to determine survival and success of four-implant overdentures in the edentulous maxilla, in participants with mandibular two-implant overdentures. Participants received four implants in the maxilla, two anteriorly and two posteriorly, then were randomly allocated into two treatment groups. The prosthetic phase included alternate loading of anterior and posterior implants for three months each, followed by loading of all four implants for another three months. Participants were then followed up in the recall phase for a mean period of 2.2 years.Case selection Four participants were taken from the authors' previous clinical study, meeting the inclusion criteria for a two-implant overdenture in the mandible. Another 21 participants were recruited from study calls after a widening of inclusion criteria. These patients were all pre-treated in accordance with the previous study protocol, so there was standardisation before maxillary implant placement.Data analysis A sample size calculation was performed and a Kaplan-Meier curve was used to demonstrate implant survival over time.Results Twenty-four patients were included in the study. Three implants were lost during the prosthetic phase and two during the recall phase; all were anterior implants. Implant survival after loading was 93.8% after a mean period of 3.1 years. There were 27 maxillary prosthetic complications overall. Denture success was 95.8% after a mean period of 2.2 years.Conclusions Implant survival of four asynchronously loaded implants in implant-supported overdentures in the edentulous maxilla was good and is a recommendable treatment option for patients with two-implant mandibular overdentures. Implant and prosthetic complications are common but mostly straightforward to manage. Two posterior implants are not superior to two anterior implants, but the majority of patients prefer the four-implant maxillary overdenture.

"Look At It Carefully Now": Athenian Tragedy And The "Talking Cure".

It is often suggested that the Greek tragedians present clinically credible pictures of mental disturbance. For instance, some modern interpreters have compared the process by which Cadmus brings Agave back to sanity in Euripides' Bacchae with modern psychotherapy. But a reading of medical writers' views on the psychological dimension of medicine offers little evidence for believing that these scenes reflect the practices of late fifth-century Athenian doctors, for whom verbal cures are associated with older traditions of non-rational thought, and thus are scorned in favor of more "scientific cures" based on diet or medication. This paper will argue that Athenian tragedians, working from older traditions that advocated verbal cures for some mental ailments, do understand the potential psychological effects that their work can have on audiences, since tragedy requires psychological interaction with its audience in order to be effective. From a close reading of select scenes in Euripidean tragedy, this paper suggests that the experiences of the characters who experience suffering in Euripides' Heracles and Bacchae are analogues of the experiences undergone by the spectators of tragedy at large. Parallels are made between the way that Agave and Heracles are both talked back to sanity by looking upon what has happened, and the way that tragedians make their audiences observe lamentations and meditations that follow the central tragic act, to help them return from the intense emotion provoked, perhaps, by the violence they have seen.

Client characteristics, organizational variables and burnout in care staff: the mediating role of fear of assault.

A broad range of factors have been identified as having an impact on burnout and performance. To improve our understanding of how these factors interact, a model of carer stress is tested. Staff were surveyed in residential units, assessments included burnout, organizational factors, staff cognitions and ratings of resident challenging behavior. The relationship between challenging behavior and emotional exhaustion was fully mediated by fear of assault. The relationship between emotional exhaustion and experienced safety (an organizational variable) was also fully mediated by fear of assault. The use of the model with staff is supported and it suggests that staff burnout can be reduced by influencing either staff cognitions, organizational factors or challenging behavior or a combination of these factors.

No evidence of association between Catechol-O-Methyltransferase (COMT) Val158Met genotype and performance on neuropsychological tasks in children with ADHD: a case-control study.

BACKGROUND: Several studies have suggested an association between the functional Val158Met polymorphism in the Catechol-O-Methyltransferase (COMT) gene and neurocognitive performance. Two studies showed that subjects with the low activity Met allele performed better on the Wisconsin Card Sorting Test (WCST) and another study found an effect on processing speed and attention. METHODS: We set out to examine the association between the Val158Met polymorphism and performance on neurocognitive tasks including those tapping working memory, attention and speed, impulsiveness and response inhibition in a sample of 124 children with ADHD. Task performance for each genotypic group was compared using analysis of variance. RESULTS: There was no evidence of association with performance on any of the neurocognitive tasks. CONCLUSIONS: We conclude that Val158Met COMT genotype is not associated with neurocognitive performance in our sample.

No evidence of association between HLA-DRB1 and attention deficit hyperactivity disorder.

OBJECTIVES: There has been a recent resurgence in interest in the role of autoimmunity in childhood neuropsychiatric disorders. Significant association between HLA-DRB1 and attention deficit hyperactivity disorder (ADHD) in a case-control study of 31 subjects has been reported but there have been no other published studies following up these results. We attempted to replicate these findings. METHODS: In a well-characterized sample of 173 children with ADHD, using a fully automated sequence-specific oligonucleotide method for HLA genotyping, association between ADHD and HLA-DRB1 was tested for using the Transmission Disequilibrium Test and case-control analysis. RESULTS: Transmission Disequilibrium Test analysis yielded a chi-square of 10.694 with a simulated global P value of 0.1641 for the full sample, and a chi-square value of 11.307 with a simulated global P value of 0.1323 for the complete trios only. CONCLUSION: There was no evidence of association of HLA-DRB1 and ADHD.