A systematic review of physiological signals based driver drowsiness detection systems

Driving a vehicle is a complex, multidimensional, and potentially risky activity demanding full mobilization and utilization of physiological and cognitive abilities. Drowsiness, often caused by stress, fatigue, and illness declines cognitive capabilities that affect drivers' capability and cause many accidents. Drowsiness-related road accidents are associated with trauma, physical injuries, and fatalities, and often accompany economic loss. Drowsy-related crashes are most common in young people and night shift workers. Real-time and accurate driver drowsiness detection is necessary to bring down the drowsy driving accident rate. Many researchers endeavored for systems to detect drowsiness using different features related to vehicles, and drivers' behavior, as well as, physiological measures. Keeping in view the rising trend in the use of physiological measures, this study presents a comprehensive and systematic review of the recent techniques to detect driver drowsiness using physiological signals. Different sensors augmented with machine learning are utilized which subsequently yield better results. These techniques are analyzed with respect to several aspects such as data collection sensor, environment consideration like controlled or dynamic, experimental set up like real traffic or driving simulators, etc. Similarly, by investigating the type of sensors involved in experiments, this study discusses the advantages and disadvantages of existing studies and points out the research gaps. Perceptions and conceptions are made to provide future research directions for drowsiness detection techniques based on physiological signals.

Empowering Lower Limb Disorder Identification through PoseNet and Artificial Intelligence

A novel approach is presented in this study for the classification of lower limb disorders, with a specific emphasis on the knee, hip, and ankle. The research employs gait analysis and the extraction of PoseNet features from video data in order to effectively identify and categorize these disorders. The PoseNet algorithm facilitates the extraction of key body joint movements and positions from videos in a non-invasive and user-friendly manner, thereby offering a comprehensive representation of lower limb movements. The features that are extracted are subsequently standardized and employed as inputs for a range of machine learning algorithms, such as Random Forest, Extra Tree Classifier, Multilayer Perceptron, Artificial Neural Networks, and Convolutional Neural Networks. The models undergo training and testing processes using a dataset consisting of 174 real patients and normal individuals collected at the Tehsil Headquarter Hospital Sadiq Abad. The evaluation of their performance is conducted through the utilization of K-fold cross-validation. The findings exhibit a notable level of accuracy and precision in the classification of various lower limb disorders. Notably, the Artificial Neural Networks model achieves the highest accuracy rate of 98.84%. The proposed methodology exhibits potential in enhancing the diagnosis and treatment planning of lower limb disorders. It presents a non-invasive and efficient method of analyzing gait patterns and identifying particular conditions.

Enhancing Cricket Performance Analysis with Human Pose Estimation and Machine Learning

Cricket has a massive global following and is ranked as the second most popular sport globally, with an estimated 2.5 billion fans. Batting requires quick decisions based on ball speed, trajectory, fielder positions, etc. Recently, computer vision and machine learning techniques have gained attention as potential tools to predict cricket strokes played by batters. This study presents a cutting-edge approach to predicting batsman strokes using computer vision and machine learning. The study analyzes eight strokes: pull, cut, cover drive, straight drive, backfoot punch, on drive, flick, and sweep. The study uses the MediaPipe library to extract features from videos and several machine learning and deep learning algorithms, including random forest (RF), support vector machine, k-nearest neighbors, decision tree, linear regression, and long short-term memory to predict the strokes. The study achieves an outstanding accuracy of 99.77% using the RF algorithm, outperforming the other algorithms used in the study. The k-fold validation of the RF model is 95.0% with a standard deviation of 0.07, highlighting the potential of computer vision and machine learning techniques for predicting batsman strokes in cricket. The study's results could help improve coaching techniques and enhance batsmen's performance in cricket, ultimately improving the game's overall quality.

An Approach to Detect Chronic Obstructive Pulmonary Disease Using UWB Radar-Based Temporal and Spectral Features

Chronic obstructive pulmonary disease (COPD) is a severe and chronic ailment that is currently ranked as the third most common cause of mortality across the globe. COPD patients often experience debilitating symptoms such as chronic coughing, shortness of breath, and fatigue. Sadly, the disease frequently goes undiagnosed until it is too late, leaving patients without the care they desperately need. So, COPD detection at an early stage is crucial to prevent further damage to the lungs and improve quality of life. Traditional COPD detection methods often rely on physical examinations and tests such as spirometry, chest radiography, blood gas tests, and genetic tests. However, these methods may not always be accurate or accessible. One of the key vital signs for detecting COPD is the patient’s respiration rate. However, it is crucial to consider a patient’s medical and demographic characteristics simultaneously for better detection results. To address this issue, this study aims to detect COPD patients using artificial intelligence techniques. To achieve this goal, a novel framework is proposed that utilizes ultra-wideband (UWB) radar-based temporal and spectral features to build machine learning and deep learning models. This new set of temporal and spectral features is extracted from respiration data collected non-invasively from 1.5 m distance using UWB radar. Different machine learning and deep learning models are trained and tested on the collected dataset. The findings are promising, with a high accuracy score of 100% for COPD detection. This means that the proposed framework could potentially save lives by identifying COPD patients at an early stage. The k-fold cross-validation technique and performance comparison with the state-of-the-art studies are applied to validate its performance, ensuring that the results are robust and reliable. The high accuracy score achieved in the study implies that the proposed framework has the potential for the efficient detection of COPD at an early stage.

Automatic User Preferences Selection of Smart Hearing Aid Using BioAid

Noisy environments, changes and variations in the volume of speech, and non-face-to-face conversations impair the user experience with hearing aids. Generally, a hearing aid amplifies sounds so that a hearing-impaired person can listen, converse, and actively engage in daily activities. Presently, there are some sophisticated hearing aid algorithms available that operate on numerous frequency bands to not only amplify but also provide tuning and noise filtering to minimize background distractions. One of those is the BioAid assistive hearing system, which is an open-source, freely available downloadable app with twenty-four tuning settings. Critically, with this device, a person suffering with hearing loss must manually alter the settings/tuning of their hearing device when their surroundings and scene changes in order to attain a comfortable level of hearing. However, this manual switching among multiple tuning settings is inconvenient and cumbersome since the user is forced to switch to the state that best matches the scene every time the auditory environment changes. The goal of this study is to eliminate this manual switching and automate the BioAid with a scene classification algorithm so that the system automatically identifies the user-selected preferences based on adequate training. The aim of acoustic scene classification is to recognize the audio signature of one of the predefined scene classes that best represent the environment in which it was recorded. BioAid, an open-source biological inspired hearing aid algorithm, is used after conversion to Python. The proposed method consists of two main parts: classification of auditory scenes and selection of hearing aid tuning settings based on user experiences. The DCASE2017 dataset is utilized for scene classification. Among the many classifiers that were trained and tested, random forests have the highest accuracy of 99.7%. In the second part, clean speech audios from the LJ speech dataset are combined with scenes, and the user is asked to listen to the resulting audios and adjust the presets and subsets. A CSV file stores the selection of presets and subsets at which the user can hear clearly against the scenes. Various classifiers are trained on the dataset of user preferences. After training, clean speech audio was convolved with the scene and fed as input to the scene classifier that predicts the scene. The predicted scene was then fed as input to the preset classifier that predicts the user's choice for preset and subset. The BioAid is automatically tuned to the predicted selection. The accuracy of random forest in the prediction of presets and subsets was 100%. This proposed approach has great potential to eliminate the tedious manual switching of hearing assistive device parameters by allowing hearing-impaired individuals to actively participate in daily life by automatically adjusting hearing aid settings based on the acoustic scene.

Biochemical and behavioural profile of NTBC treated Tyrosinemie type 1 mice

BACKGROUND

Tyrosinemia type 1 (HT1) is a rare metabolic disorder caused by a defect in the tyrosine catabolic pathway. Since HT1 patients are treated with NTBC, outcome improved and life expectancy greatly increased. However extensive neurocognitive and behavioural problems have been described, which might be related to treatment with NTBC, the biochemical changes induced by NTBC, or metabolites accumulating due to the enzymatic defect characterizing the disease.

OBJECTIVE

To study the possible pathophysiological mechanisms of brain dysfunction in HT1, we assessed blood and brain LNAA, and brain monoamine neurotransmitter metabolite levels in relation to behavioural and cognitive performance of HT1 mice.

DESIGN

C57BL/6 littermates were divided in three different experimental groups: HT1, heterozygous and wild-type mice (n = 10; 5 male). All groups were treated with NTBC and underwent cognitive and behavioural testing. One week after behavioural testing, blood and brain material were collected to measure amino acid profiles and brain monoaminergic neurotransmitter levels.

RESULTS

Irrespective of the genetic background, NTBC treatment resulted in a clear increase in brain tyrosine levels, whereas all other brain LNAA levels tended to be lower than their reference values. Despite these changes in blood and brain biochemistry, no significant differences in brain monoamine neurotransmitter (metabolites) were found and all mice showed normal behaviour and learning and memory.

CONCLUSION

Despite the biochemical changes, NTBC and genotype of the mice were not associated with poorer behavioural and cognitive function of the mice. Further research involving dietary treatment of FAH-/- are warranted to investigate whether this reveals the cognitive impairments that have been seen in treated HT1 patients.

Automated breast lesion localisation in microwave imaging employing simplified pulse coupled neural network

MammoWave is a microwave imaging device for breast lesion detection, employing two antennas which rotate azimuthally (horizontally) around the breast. The antennas operate in the 1-9 GHz band and are set in free space, i.e., pivotally, no matching liquid is required. Microwave images, subsequently obtained through the application of Huygens Principle, are intensity maps, representing the homogeneity of the dielectric properties of the breast tissues under test. In this paper, MammoWave is used to realise tissues dielectric differences and localise lesions by segmenting microwave images adaptively employing pulse coupled neural network (PCNN). Subsequently, a non-parametric thresholding technique is modelled to differentiate between breasts having no radiological finding (NF) or benign (BF) and breasts with malignant finding (MF). Resultant findings verify that automated breast lesion localization with microwave imaging matches the gold standard achieving 81.82% sensitivity in MF detection. The proposed method is tested on microwave images acquired from a feasibility study performed in Foligno Hospital, Italy. This study is based on 61 breasts from 35 patients; performance may vary with larger number of datasets and will be subsequently investigated.

Modeling the cognitive effects of diet discontinuation in adults with phenylketonuria (PKU) using pegvaliase therapy in PAH-deficient mice

Existing phenylalanine hydroxylase (PAH)-deficient mice strains are useful models of untreated or late-treated human phenylketonuria (PKU), as most contemporary therapies can only be initiated after weaning and the pups have already suffered irreversible consequences of chronic hyperphenylalaninemia (HPA) during early brain development. Therefore, we sought to evaluate whether enzyme substitution therapy with pegvaliase initiated near birth and administered repetitively to C57Bl/6-Pah^enu2/enu2 mice would prevent HPA-related behavioral and cognitive deficits and form a model for early-treated PKU. The main results of three reported experiments are: 1) lifelong weekly pegvaliase treatment prevented the cognitive deficits associated with HPA in contrast to persisting deficits in mice treated with pegvaliase only as adults. 2) Cognitive deficits reappear in mice treated with weekly pegvaliase from birth but in which pegvaliase is discontinued at 3 months age. 3) Twice weekly pegvaliase injection also prevented cognitive deficits but again cognitive deficits emerged in early-treated animals following discontinuation of pegvaliase treatment during adulthood, particularly in females. In all studies, pegvaliase treatment was associated with complete correction of brain monoamine neurotransmitter content and with improved overall growth of the mice as measured by body weight. Mean total brain weight however remained low in all PAH deficient mice regardless of treatment. Application of enzyme substitution therapy with pegvaliase, initiated near birth and continued into adulthood, to PAH-deficient Pah^enu2/enu2 mice models contemporary early-treated human PKU. This model will be useful for exploring the differential pathophysiologic effects of HPA at different developmental stages of the murine brain.

Respiration Based Non-Invasive Approach for Emotion Recognition Using Impulse Radio Ultra Wide Band Radar and Machine Learning

Emotion recognition gained increasingly prominent attraction from a multitude of fields recently due to their wide use in human-computer interaction interface, therapy, and advanced robotics, etc. Human speech, gestures, facial expressions, and physiological signals can be used to recognize different emotions. Despite the discriminating properties to recognize emotions, the first three methods have been regarded as ineffective as the probability of human's voluntary and involuntary concealing the real emotions can not be ignored. Physiological signals, on the other hand, are capable of providing more objective, and reliable emotion recognition. Based on physiological signals, several methods have been introduced for emotion recognition, yet, predominantly such approaches are invasive involving the placement of on-body sensors. The efficacy and accuracy of these approaches are hindered by the sensor malfunctioning and erroneous data due to human limbs movement. This study presents a non-invasive approach where machine learning complements the impulse radio ultra-wideband (IR-UWB) signals for emotion recognition. First, the feasibility of using IR-UWB for emotion recognition is analyzed followed by determining the state of emotions into happiness, disgust, and fear. These emotions are triggered using carefully selected video clips to human subjects involving both males and females. The convincing evidence that different breathing patterns are linked with different emotions has been leveraged to discriminate between different emotions. Chest movement of thirty-five subjects is obtained using IR-UWB radar while watching the video clips in solitude. Extensive signal processing is applied to the obtained chest movement signals to estimate respiration rate per minute (RPM). The RPM estimated by the algorithm is validated by repeated measurements by a commercially available Pulse Oximeter. A dataset is maintained comprising gender, RPM, age, and associated emotions which are further used with several machine learning algorithms for automatic recognition of human emotions. Experiments reveal that IR-UWB possesses the potential to differentiate between different human emotions with a decent accuracy of 76% without placing any on-body sensors. Separate analysis for male and female participants reveals that males experience high arousal for happiness while females experience intense fear emotions. For disgust emotion, no large difference is found for male and female participants. To the best of the authors' knowledge, this study presents the first non-invasive approach using the IR-UWB radar for emotion recognition.

A Novel Approach to Railway Track Faults Detection Using Acoustic Analysis

Regular inspection of railway track health is crucial for maintaining safe and reliable train operations. Factors, such as cracks, ballast issues, rail discontinuity, loose nuts and bolts, burnt wheels, superelevation, and misalignment developed on the rails due to non-maintenance, pre-emptive investigations and delayed detection, pose a grave danger and threats to the safe operation of rail transport. The traditional procedure of manually inspecting the rail track using a railway cart is both inefficient and prone to human error and biases. In a country like Pakistan where train accidents have taken many lives, it is not unusual to automate such approaches to avoid such accidents and save countless lives. This study aims at enhancing the traditional railway cart system to address these issues by introducing an automatic railway track fault detection system using acoustic analysis. In this regard, this study makes two important contributions: data collection on Pakistan railway tracks using acoustic signals and the application of various classification techniques to the collected data. Initially, three types of tracks are considered, including normal track, wheel burnt and superelevation, due to their common occurrence. Several well-known machine learning algorithms are applied such as support vector machines, logistic regression, random forest and decision tree classifier, in addition to deep learning models like multilayer perceptron and convolutional neural networks. Results suggest that acoustic data can help determine the track faults successfully. Results indicate that the best results are obtained by RF and DT with an accuracy of 97%.

Use of Crotalidae equine immune F(ab')2 antivenom for treatment of an Agkistrodon envenomation

INTRODUCTION

Anavip (F(ab')₂AV) is a lyophilized F(ab')₂ immunoglobulin fragment derived from horses immunized with venom from Bothrops asper and Crotalus durissus. It was approved by the FDA in 2015 for treatment of North American rattlesnake envenomation but not for Agkistrodon envenomation. Published data regarding the efficacy and safety of Anavip in treating Agkistrodon envenomations is limited. We present a case of a patient treated with Anavip after confirmed Agkistrodon laticinctus envenomation.

CASE DETAILS

A 77 year-old man was bitten on his fifth finger by a captive A. laticinctus. He was taken to a local emergency department where he received a 10 vial initial dose of F(ab')₂AV for pain and swelling and was transferred. At the receiving facility, his pain had improved and his swelling had not progressed. Over the next 30 h, his platelets declined to 132,000/mm³ and he received an additional 4 vials of F(ab')₂AV. The remainder of his course was unremarkable with complete recovery by 3 months.

DISCUSSION

This case provides an additional published datapoint on the use of this F(ab')₂AV in the treatment of envenomation by Agkistrodon.

A novel Pah-exon1 deleted murine model of phenylalanine hydroxylase (PAH) deficiency

Phenylalanine hydroxylase (PAH) deficiency, colloquially known as phenylketonuria (PKU), is among the most common inborn errors of metabolism and in the past decade has become a target for the development of novel therapeutics such as gene therapy. PAH deficient mouse models have been key to new treatment development, but all prior existing models natively express liver PAH polypeptide as inactive or partially active PAH monomers, which complicates the experimental assessment of protein expression following therapeutic gene, mRNA, protein, or cell transfer. The mutant PAH monomers are able to form hetero-tetramers with and inhibit the overall holoenzyme activity of wild type PAH monomers produced from a therapeutic vector. Preclinical therapeutic studies would benefit from a PKU model that completely lacks both PAH activity and protein expression in liver. In this study, we employed CRISPR/Cas9-mediated gene editing in fertilized mouse embryos to generate a novel mouse model that lacks exon 1 of the Pah gene. Mice that are homozygous for the Pah exon 1 deletion are viable, severely hyperphenylalaninemic, accurately replicate phenotypic features of untreated human classical PKU and lack any detectable liver PAH activity or protein. This model of classical PKU is ideal for further development of gene and cell biologics to treat PKU.

Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection

In this paper, we present an investigation of different artefact removal methods for ultra-wideband Microwave Imaging (MWI) to evaluate and quantify current methods in a real environment through measurements using an MWI device. The MWI device measures the scattered signals in a multi-bistatic fashion and employs an imaging procedure based on Huygens principle. A simple two-layered phantom mimicking human head tissue is realised, applying a cylindrically shaped inclusion to emulate brain haemorrhage. Detection has been successfully achieved using the superimposition of five transmitter triplet positions, after applying different artefact removal methods, with the inclusion positioned at 0°, 90°, 180°, and 270°. The different artifact removal methods have been proposed for comparison to improve the stroke detection process. To provide a valid comparison between these methods, image quantification metrics are presented. An "ideal/reference" image is used to compare the artefact removal methods. Moreover, the quantification of artefact removal procedures through measurements using MWI device is performed.

ITERATOR: A 3D Gait Identification from IR-UWB Technology

A more locally cared for and self-managing aging population along with better attention to self health-care, has resulted in increasing need for non-intrusive monitoring. Wearable, wireless physiological sensors, and cameras can pose user privacy, security and discomfort issues which may have a negative impact on consumer confidence and uptake. Thus, for the first time a non-contact, non-intrusive 3D human motion model is proposed for gait disorder identification from impulse radio ultra-wide band (ITERATOR) with the understanding of spherical trigonometry and vector field. Simultaneously, the Kinect Xbox One is used to compare the outcomes of the proposed IR-UWB model. The experiment comprises twenty-four human participants, where twenty people have normal walking pattern and four persons have spasticity. The height of different body sections from the ground have been recorded for each individual and employed later to distinguish lower and upper human body from the outcomes. The proposed work has transformed the radars backscattered responses through trigonometry and vector algebra where, only vector algebra has been implemented to transform the skeletal data obtained from Kinect. Angles between two thighs have been determined from the proposed UWB algorithm and validated against angles obtained from the Kinect skeletal data using root mean square error (RMSE), where less than 0.5 RMSE has been found.

AAV-Mediated CRISPR/Cas9 Gene Editing in Murine Phenylketonuria

Phenylketonuria (PKU) due to recessively inherited phenylalanine hydroxylase (PAH) deficiency results in hyperphenylalaninemia, which is toxic to the central nervous system. Restriction of dietary phenylalanine intake remains the standard of PKU care and prevents the major neurologic manifestations of the disease, yet shortcomings of dietary therapy remain, including poor adherence to a difficult and unpalatable diet, an increased incidence of neuropsychiatric illness, and imperfect neurocognitive outcomes. Gene therapy for PKU is a promising novel approach to promote lifelong neurological protection while allowing unrestricted dietary phenylalanine intake. In this study, liver-tropic recombinant AAV2/8 vectors were used to deliver CRISPR/Cas9 machinery and facilitate correction of the Pah ^enu2 allele by homologous recombination. Additionally, a non-homologous end joining (NHEJ) inhibitor, vanillin, was co-administered with the viral drug to promote homology-directed repair (HDR) with the AAV-provided repair template. This combinatorial drug administration allowed for lifelong, permanent correction of the Pah ^enu2 allele in a portion of treated hepatocytes of mice with PKU, yielding partial restoration of liver PAH activity, substantial reduction of blood phenylalanine, and prevention of maternal PKU effects during breeding. This work reveals that CRISPR/Cas9 gene editing is a promising tool for permanent PKU gene editing.

Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging Clinical Data

Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for breast lesion detection is used to accumulate clinical data from subjects undergoing breast examinations at the Department of Diagnostic Imaging, Perugia Hospital, Perugia, Italy. This paper presents the first ever clinical demonstration and comparison of a microwave ultra-wideband (UWB) device augmented by machine learning with subjects who are simultaneously undergoing conventional breast examinations. Non-ionizing microwave signals are transmitted through the breast tissue and the scattering parameters (S-parameter) are received via a dedicated moving transmitting and receiving antenna set-up. The output of a parallel radiologist study for the same subjects, performed using conventional techniques, is taken to pre-process microwave data and create suitable data for the machine intelligence system. These data are used to train and investigate several suitable supervised machine learning algorithms nearest neighbour (NN), multi-layer perceptron (MLP) neural network, and support vector machine (SVM) to create an intelligent classification system towards supporting clinicians to recognise breasts with lesions. The results are rigorously analysed, validated through statistical measurements, and found the quadratic kernel of SVM can classify the breast data with 98% accuracy.

A Self Regulating and Crowdsourced Indoor Positioning System through Wi-Fi Fingerprinting for Multi Storey Building

Unobtrusive indoor location systems must rely on methods that avoid the deployment of large hardware infrastructures or require information owned by network administrators. Fingerprinting methods can work under these circumstances by comparing the real-time received RSSI values of a smartphone coming from existing Wi-Fi access points with a previous database of stored values with known locations. Under the fingerprinting approach, conventional methods suffer from large indoor scenarios since the number of fingerprints grows with the localization area. To that aim, fingerprinting-based localization systems require fast machine learning algorithms that reduce the computational complexity when comparing real-time and stored values. In this paper, popular machine learning (ML) algorithms have been implemented for the classification of real time RSSI values to predict the user location and propose an intelligent indoor positioning system (I-IPS). The proposed I-IPS has been integrated with multi-agent framework for betterment of context-aware service (CAS). The obtained results have been analyzed and validated through established statistical measurements and superior performance achieved.

Automated Peripheral Neuropathy Assessment Using Optical Imaging and Foot Anthropometry

A large proportion of individuals who live with type-2 diabetes suffer from plantar sensory neuropathy. Regular testing and assessment for the condition is required to avoid ulceration or other damage to patient's feet. Currently accepted practice involves a trained clinician testing a patient's feet manually with a hand-held nylon monofilament probe. The procedure is time consuming, labor intensive, requires special training, is prone to error, and repeatability is difficult. With the vast increase in type-2 diabetes, the number of plantar sensory neuropathy sufferers has already grown to such an extent as to make a traditional manual test problematic. This paper presents the first investigation of a novel approach to automatically identify the pressure points on a given patient's foot for the examination of sensory neuropathy via optical image processing incorporating plantar anthropometry. The method automatically selects suitable test points on the plantar surface that correspond to those repeatedly chosen by a trained podiatrist. The proposed system automatically identifies the specific pressure points at different locations, namely the toe (hallux), metatarsal heads and heel (Calcaneum) areas. The approach is generic and has shown 100% reliability on the available database used. The database consists of Chinese, Asian, African, and Caucasian foot images.

480 Mbit/s UWB bi-directional radio over fiber CWDM PON using ultra-low cost and power VCSELs

Radio-over-fiber (RoF) schemes offer the possibility of permitting direct access to native format services for the domestic user. A low power requirement and cost effectiveness are crucial to both the service provider and the end user. Here, we present an ultra-low cost and power RoF scheme using direct modulation of commercially-available 1344 nm and 1547 nm VCSELs by band-group 1 UWB wireless signals (ECMA-368) at near broadcast power levels. As a result, greatly simplified electrical-optical-electrical conversion is accomplished. A successful demonstration over a transmission distance of 20.1 km is described using a SSMF, CWDM optical network. EVMs of better than -18.3 dB were achieved.

Conservation of functional asymmetry in the mammalian MutLα ATPase

The DNA mismatch repair (MMR) protein dimer MutLα is comprised of the MutL homologues MLH1 and PMS2, which each belong to the family of GHL ATPases. These ATPases undergo functionally important conformational changes, including dimerization of the NH₂-termini associated with ATP binding and hydrolysis. Previous studies in yeast and biochemical studies with the mammalian proteins established the importance of the MutLα ATPase for overall MMR function. Additionally, the studies in yeast demonstrated a functional asymmetry between the contributions of the Mlh1 and Pms1 ATPase domains to MMR that was not reflected in the biochemical studies. We investigated the effect of mutating the highly conserved ATP hydrolysis and Mg²(+) binding residues of MLH1 and PMS2 in mammalian cell lines. Amino acid substitutions in MLH1 intended to impact either ATP binding or hydrolysis disabled MMR, as measured by instability at microsatellite sequences, to an extent similar to MLH1-null mutation. Furthermore, cells expressing these MLH1 mutations exhibited resistance to the MMR-dependent cytotoxic effect of 6-thioguanine (6-TG). In contrast, ATP hydrolysis and binding mutants of PMS2 displayed no measurable increase in microsatellite instability or resistance to 6-TG. Our findings suggest that, in vivo, the integrity of the MLH1 ATPase domain is more critical than the PMS2 ATPase domain for normal MMR functions. These in vivo results are in contrast to results obtained previously in vitro that showed no functional asymmetry within the MutLα ATPase, highlighting the differences between in vivo and in vitro systems.

Do TETRA (Airwave) base station signals have a short-term impact on health and well-being? A randomized double-blind provocation study

BACKGROUND

"Airwave" is the new communication system currently being rolled out across the United Kingdom for the police and emergency services, based on the Terrestrial Trunked Radio Telecommunications System (TETRA). Some police officers have complained about skin rashes, nausea, headaches, and depression as a consequence of using their Airwave handsets. In addition, a small subgroup in the population self-report being sensitive to electromagnetic fields (EMFs) in general.

OBJECTIVES

We conducted a randomized double-blind provocation study to establish whether short-term exposure to a TETRA base station signal has an impact on the health and well-being of individuals with self-reported "electrosensitivity" and of participants who served as controls.

METHODS

Fifty-one individuals with self-reported electrosensitivity and 132 age- and sex-matched controls participated in an open provocation test; 48 sensitive and 132 control participants went on to complete double-blind tests in a fully screened semianechoic chamber. Heart rate, skin conductance, and blood pressure readings provided objective indices of short-term physiological response. Visual analog scales and symptom scales provided subjective indices of well-being.

RESULTS

We found no differences on any measure between TETRA and sham (no signal) under double-blind conditions for either controls or electrosensitive participants, and neither group could detect the presence of a TETRA signal at rates greater than chance (50%). When conditions were not double blind, however, the self-reported electrosensitive individuals did report feeling worse and experienced more severe symptoms during TETRA compared with sham.

CONCLUSIONS

Our findings suggest that the adverse symptoms experienced by electrosensitive individuals are due to the belief of harm from TETRA base stations rather than to the low-level EMF exposure itself.

Efficacy of follow-up and contact tracing of women who test positive for genital tract chlamydia trachomatis prior to pregnancy termination

We examined the efficacy of follow-up, contact tracing and the need for retreatment in women who were screen-positive for genital tract Chlamydia trachomatis prior to termination of pregnancy. Eighty-six of 1363 (6.3%) women screened positive. These women were significantly younger than those who screened negative (P < 0.0001). The genitourinary medicine (GUM) clinic was notified of 73 (84.9%) screen-positive women and 41 (47.7%) attended for follow-up. Contact tracing was undertaken in 38 (92.7%) women who attended and 29 (70.7%) women who attended required retreatment for Chlamydia. The median duration between pregnancy termination and GUM clinic attendance was significantly longer in women who required retreatment compared to those who did not require retreatment (P = 0.003). In conclusion, follow-up and contact-tracing of women who screen positive for genital tract C. trachomatis was incomplete. This may substantially compromise the cost-effectiveness of a screen-and-treat programme.

16S ribosomal RNA tools identify an unexpected predominance of Paenibacillus-like bacteria in an industrial activated sludge system suffering from poor biosolids separation

Molecular biology tools targeting 16S ribosomal RNA (16S rRNA) were used to identify a predominant bacterial population in a full-scale dairy wastewater activated sludge system suffering from poor biosolids separation. Gram and acridine orange staining indicated that viable, Gram-positive microorganisms were present in samples removed from the influent waste stream and represented approximately 50% of total cell counts in samples removed from the mixed liquor. Subsequently, the "full-cycle 16S rRNA approach" showed that phylogenetic relatives of Paenibacillus spp., a low guanine-plus-cytosine percent DNA-content, Gram-positive microorganism, represented up to 30% of total 4,6-diamidino-2-phenylindole (DAPI)-stained cell counts in samples of mixed liquor. Although fluorescent in situ hybridizations with 16S rRNA-targeted oligonucleotide hybridization probes identified Paenibacillus-like spp. in samples removed from the influent waste stream, their abundance was less than 10% of total stained cell counts. Results of this study suggest that Paenibacillus-like spp. were present in low abundance in the influent waste stream, increased in relative abundance within the treatment system, and should be examined further as a candidate bacterial population responsible for poor biosolids separation. This study demonstrates that the full-cycle 16S rRNA approach can be used to identify candidate bacterial populations that may be responsible for operational upsets in full-scale activated sludge systems without prior information from cultivation or microscopic analyses.

Novel PMS1 alleles preferentially affect the repair of primer strand loops during DNA replication

Null mutations in DNA mismatch repair (MMR) genes elevate both base substitutions and insertions/deletions in simple sequence repeats. Data suggest that during replication of simple repeat sequences, polymerase slippage can generate single-strand loops on either the primer or template strand that are subsequently processed by the MMR machinery to prevent insertions and deletions, respectively. In the budding yeast Saccharomyces cerevisiae and mammalian cells, MMR appears to be more efficient at repairing mispairs comprised of loops on the template strand compared to loops on the primer strand. We identified two novel yeast pms1 alleles, pms1-G882E and pms1-H888R, which confer a strong defect in the repair of "primer strand" loops, while maintaining efficient repair of "template strand" loops. Furthermore, these alleles appear to affect equally the repair of 1-nucleotide primer strand loops during both leading- and lagging-strand replication. Interestingly, both pms1 mutants are proficient in the repair of 1-nucleotide loop mispairs in heteroduplex DNA generated during meiotic recombination. Our results suggest that the inherent inefficiency of primer strand loop repair is not simply a mismatch recognition problem but also involves Pms1 and other proteins that are presumed to function downstream of mismatch recognition, such as Mlh1. In addition, the findings reinforce the current view that during mutation avoidance, MMR is associated with the replication apparatus.

Contributions by MutL homologues Mlh3 and Pms2 to DNA mismatch repair and tumor suppression in the mouse

Germ line DNA mismatch repair mutations in MLH1 and MSH2 underlie the vast majority of hereditary non-polyposis colon cancer. Four mammalian homologues of Escherichia coli MutL heterodimerize to form three distinct complexes: MLH1/PMS2, MLH1/MLH3, and MLH1/PMS1. Although MLH1/PMS2 is generally thought to have the major MutL activity, the precise contributions of each MutL heterodimer to mismatch repair functions are poorly understood. Here, we show that Mlh3 contributes to mechanisms of tumor suppression in the mouse. Mlh3 deficiency alone causes microsatellite instability, impaired DNA-damage response, and increased gastrointestinal tumor susceptibility. Furthermore, Mlh3;Pms2 double-deficient mice have tumor susceptibility, shorter life span, microsatellite instability, and DNA-damage response phenotypes that are indistinguishable from Mlh1-deficient mice. Our data support previous results from budding yeast that show partial functional redundancy between MLH3 and PMS2 orthologues for mutation avoidance and show a role for Mlh3 in gastrointestinal and extragastrointestinal tumor suppression. The data also suggest a mechanistic basis for the more severe mismatch repair-related phenotypes and cancer susceptibility in Mlh1- versus Mlh3- or Pms2-deficient mice. Contributions by both MLH1/MLH3 and MLH1/PMS2 complexes to mechanisms of mismatch repair-mediated tumor suppression, therefore, provide an explanation why, among MutL homologues, only germ line mutations in MLH1 are common in hereditary non-polyposis colon cancer.

Apoptosis and mutation in the murine small intestine: loss of Mlh1- and Pms2-dependent apoptosis leads to increased mutation in vivo

The mismatch repair (MMR) protein Msh2 has been shown to function in the apoptotic response to alkylating agents in vivo. Here, we extend these studies to the MutL homologues (MLH) Mlh1 and Pms2 by analysing the apoptotic response within the small intestine of gene targeted strains. We demonstrate significant differences between Msh2, Mlh1 and Pms2 mutations in influencing apoptotic signalling following 50mg/kg N-methyl-nitrosourea (NMNU), with no obvious reliance upon either Mlh1 or Pms2. However, following exposure to 100mg/kg temozolomide or lower levels of NMNU (10mg/kg) both Mlh1- and Pms2-dependent apoptosis was observed, indicating that the apoptotic response at these levels of DNA damage is dependent on the MutL homologues. Given our ability to observe a MutLalpha dependence of the apoptotic response, we tested whether perturbations of this response directly translate into increases in mutation frequency in vivo. We show that treatment with temozolomide or 10mg/kg NMNU significantly increases mutation in both the Mlh1 and Pms2 mutant mice. At higher levels of NMNU, where the apoptotic response is independent of Mlh1 and Pms2, no gene dependent increase in mutation frequency was observed. These results argue that the MutSalpha and MutLalpha are not equally important in their ability to signal apoptosis. However, when MMR does mediate apoptosis, perturbation of this response leads to long-term persistence of mutant cells in vivo.

Mlh1 deficiency accelerates myeloid leukemogenesis in neurofibromatosis 1 (Nf1) heterozygous mice

Defects in DNA mismatch repair (MMR) have been implicated in the genesis of a diverse set of human cancers. Recent studies have suggested that one of the targets of MMR is the neurofibromatosis 1 (NF1) gene. To evaluate the contribution of Mlh1 MMR deficiency to Nf1 tumorigenesis, Mlh1-/-;Nf1+/- mice were generated. All Mlh1-/-;Nf1+/- mice (n=21) were dead by 260 days compared to none of the Nf1+/- mice. In all, 50% of the Mlh1-/-;Nf1+/- mice were dead at 150 days compared to 252 days for Mlh1-/- mice. Nine of the Mlh1-/-;Nf1+/- mice were found to harbor intrathoracic NOS2-immunoreactive myeloid leukemias similar to the hematopoietic malignancies observed in older Nf1+/- mice. As expected, significant microsatellite instability was observed in six of six tumors and neurofibromin expression was lost in all tumors analysed. These results suggest that MMR deficiency can accelerate myeloid leukemogenesis in Nf1+/- mice, presumably by inactivating Nf1 gene expression.

Neurofibromatosis type 1 gene as a mutational target in a mismatch repair-deficient cell type

DNA mismatch repair (MMR) is the process by which incorrectly paired DNA nucleotides are recognized and repaired. A germline mutation in one of the genes involved in the process may be responsible for a dominantly inherited cancer syndrome, hereditary nonpolyposis colon cancer. Cancer progression in predisposed individuals results from the somatic inactivation of the normal copy of the MMR gene, leading to a mutator phenotype affecting preferentially repeat sequences (microsatellite instability, MSI). Recently, we identified children with a constitutional deficiency of MMR activity attributable to a mutation in the h MLH1 gene. These children exhibited a constitutional genetic instability associated with clinical features of de novo neurofibromatosis type 1 (NF1) and early onset of extracolonic cancer. Based on these observations, we hypothesized that somatic NF1 gene mutation was a frequent and possibly early event in MMR-deficient cells. To test this hypothesis, we screened for NF1 mutations in cancer cells. Genetic alterations were identified in five out of ten tumor cell lines with MSI, whereas five MMR-proficient tumor cell lines expressed a wild-type NF1 gene. Somatic NF1 mutations were also detected in two primary tumors exhibiting an MSI phenotype. Finally, a 35-bp deletion in the murine Nf1 coding region was identified in mlh1-/- mouse embryonic fibroblasts. These observations demonstrate that the NF1 gene is a mutational target of MMR deficiency and suggest that its inactivation is an important step of the malignant progression of MMR-deficient cells.

Tuneable optoelectronic bandpass filtering using a simple self-pulsating two-section laser

We demonstrate tuneable optoelectronic bandpass filtering of an ASK modulated subcarrier data stream, using a two-section laser. Gain enhancement of 15dB is measured when the laser is locked to a 697MHz and 1100MHz carrier frequency.

Characterization of nuclease-dependent functions of Exo1p in Saccharomyces cerevisiae

Exo1p is a member of the Rad2p family of structure-specific nucleases that contain conserved N and I nuclease domains. Exo1p has been implicated in numerous DNA metabolic processes, such as recombination, double-strand break repair and DNA mismatch repair (MMR). In this report, we describe in vitro and in vivo characterization of full-length wild-type and mutant forms of Exo1p. Herein, we demonstrate that full-length yeast Exo1p possesses an intrinsic 5'-3' exonuclease activity as reported previously, but also possesses a flap-endonuclease activity. Our study indicates that Exo1p shares similar, but not identical structure-function relationships to other characterized members of the Rad2p family in the N and I nuclease domains. The two exo1p mutants we examined, showed deficiencies for both double-stranded DNA (dsDNA) 5'-3' exonuclease and flap-endonuclease activities. Examining the genetic interaction of these two exo1 mutations with rad27Delta suggest that the Exo1p flap-endonuclease activity and not the dsDNA 5'-3' exonuclease is redundant to Rad27p for viability. In addition, our in vivo results also indicate that many exo1Delta phenotypes are dependent on the complete catalytic activities of Exo1p. Finally, our findings plus those of other investigators suggest that Exo1p functions both in a catalytic and a structural capacity during DNA MMR.

Diet, cancer and aging in DNA mismatch repair deficient mice

Diet is an important risk factor for many cancers. High fat/low calcium (HFLC) diets are associated with increased tumorigenesis, whereas caloric restriction (CR) reproducibly increases lifespan and decreases tumors. Mutations are involved in aging and cancer, and different diets may alter mutagenesis. However, a number of repair pathways normally counteract mutations by correcting errors before they can be fixed in the genome. To further understand interactions between diet, aging and cancer, mice deficient in a major repair pathway called DNA mismatch repair (MMR) were fed HFLC, CR or control diets. Mlh1 deficient mice are prone to lymphomas and intestinal adenomas and carcinomas. No significant changes in adenocarcinoma or lymphoma incidence were observed with HFLC or CR diets. Significantly more (2.2-fold) adenomas occurred with HFLC diets although adenoma numbers were unchanged with CR. Only a small increase in lifespan (116% of control) was achieved with CR. In addition, levels of microsatellite mutations in the small and large intestines were unchanged with the different diets. Our studies indicate that MMR deficiency may be epistatic to certain otherwise strong environmental influences on carcinogenesis or aging.

Bacterial pathogens of otitis media and sinusitis: detection in the nasopharynx with selective agar media

Carriage rates for the bacterial pathogens associated with otitis media (Streptococcus pneumoniae [SP], Hemophilus influenzae [HI], and Moraxella catarrhalis [MC]) are of interest. Culture on three selective agars was compared with culture on two standard agars to determine the more accurate method for detection of these species in the nasopharynx of healthy children. Weekly samples were obtained in winter from 18 healthy children (ages 1 through 9 years) as part of a longitudinal study. A 0.1-mL sample of 116 nasopharyngeal aspirate/washes was inoculated onto each of five agars. Two were standard (sheep blood and chocolate), and three were selective (blood with gentamicin for SP; chocolate with vancomycin, bacitracin, and clindamycin for HI; blood with amphotericin B, vancomycin, trimethoprim, and acetazolamide for MC). One technician read the standard plates and another the selective; both were blinded to the results of the other. SP was found in 44% of samples with selective agar versus 25% with standard agar; HI was found in 31% with selective versus 9% with standard; MC was found in 56% with selective versus 37% with standard. Overall, 80% of samples had one or more pathogens detected with selective agars as compared with 58% with standard agars (P =.0004). Selective agars were more accurate than standard agars for detecting otitis pathogens in the nasopharynx, where they are a common part of normal flora in healthy children.

Abortion training in U.S. obstetrics and gynecology residency programs, 1998

CONTEXT

Since the late 1970s, the number of obstetrics and gynecology residency programs providing abortion training in the United States has steadily decreased. Given the documented shortage of abortion providers, assessing and ensuring the availability of abortion training in graduate medical education is critical.

METHODS

In 1998, the National Abortion Federation surveyed the 261 accredited U.S. residency programs in obstetrics and gynecology, and analyzed the availability of first- and second-trimester abortion training.

RESULTS

Of the 179 programs that responded to the survey, 81% reported that they offer first-trimester abortion training--46% routinely and 34% as an elective. Seventy-four percent of programs offer second-trimester training--44% routinely and 29% as an elective. Some programs that do not offer training give residents the option of obtaining it elsewhere. While 26% of programs indicated that all residents in their programs receive abortion training, 40% said that fewer than half are trained, including 14% that train no residents. The operating room is the most common training site: Fifty-nine percent of programs reported that abortion training takes place in the operating room.

CONCLUSIONS

After a decades-long decline in the availability of abortion training, opportunities for abortion training have increased. However, there is reason to be cautious in interpreting these results, including possible response bias and pressure to report the availability of abortion training because of new guidelines from the Accreditation Council for Graduate Medical Education.

Mlh1 deficiency enhances several phenotypes of Apc(Min)/+ mice

Defects in APC and DNA mismatch repair genes are associated with a strong predisposition to colon cancer in humans, and numerous mouse strains with mutations in these genes have been generated. In this report we describe the phenotype of Min/+ Mlh1-/- mice. We find that these doubly mutant mice develop more than three times the number of intestinal adenomas compared to Min/+ Mlh1+/+ or +/- mice but that these tumors do not show advanced progression in terms of tumor size or histological appearance. Full length Apc protein was not detected in the tumor cells from Min/+ Mlh1-/- mice. Molecular analyses indicated that in many tumors from Min/+ Mlh1-/- mice, Apc was inactivated by intragenic mutation. Mlh1 deficiency in Min/+ mice also led to an increase in cystic intestinal crypt multiplicity as well as enhancing desmoid tumorigenesis and epidermoid cyst development. Thus, Mlh1 deficiency influences the somatic events involved in the development of most of the phenotypes associated with the Min mutation. Oncogene (2000).

Predominant interactions between mu-conotoxin Arg-13 and the skeletal muscle Na+ channel localized by mutant cycle analysis

High-affinity mu-conotoxin block of skeletal muscle Na+ channels depends on an arginine at position 13 (Arg-13). To understand both the mechanism of toxin interaction and the general structure of its binding site in the channel mouth, we examined by thermodynamic mutant cycle analysis the interaction between the critical Arg-13 and amino acid residues known to be in the channel's outer vestibule. Arg-13 interacts specifically with domain II Glu-758 with energy of about -3.0 kcal/mol, including both electrostatic and nonelectrostatic components, and with Glu-403 with energy of about -2.0 kcal/mol. Interactions with the other charged residues in the outer vestibule were shown to be almost entirely electrostatic, because these interactions were maintained when Arg-13 was replaced by lysine. These results place the bound Arg-13 at the channel mouth adjacent to the P (pore) loops of domains I and II. Distance estimates based on interaction energies suggest that the charged vestibule residues are in relative positions similar to those of the Lipkind-Fozzard vestibule model [Lipkind, G. M., and Fozzard, H. A. (1994) Biophys. J. 66, 1-13]. Kinetic analysis suggests that Arg-13 interactions are partially formed in the ligand-channel transition state.

Hospital-acquired urinary tract infections in the pediatric patient: a prospective study

To determine through a prospective study the characteristics of hospital-acquired urinary tract infections (HAUTI) in children, 525 children subjected to bladder catheterization during a hospital admission were identified through surveillance of 12,316 admissions during a 24-month period. Urine culture results were available for 296 (56.4%) of the catheterized patients. In addition 12 noncatheterized children with a documented HAUTI were identified. The clinical courses of all patients with a HAUTI were followed for at least 6 months after their last HAUTI during the study period. Forty-four patients, 1 week to 17 years of age, with 1 or more HAUTI during a hospital unit admission were identified. A total of 51 HAUTI occurred. Thirty-nine (76.5%) of the infections occurred in patients subjected to catheterization. Thirty-two (10.8%) of 296 catheterized patients developed a HAUTI. Forty-three (84.3%) of the 51 infections were single organism infections. One HAUTI was associated with a wound infection with the same organism and one with a concurrent bacteremia with the same organism. Relapses were seen after 4 HAUTI. One reinfection was identified. There were no deaths directly associated with a HAUTI. Hospitalized children subjected to urinary tract catheterization are at significant risk for HAUTI. Complications are infrequent and not life-threatening.

Carbon-isotope discrimination by leaves of Flaveria species exhibiting different amounts of C3-and C 4-cycle co-function

Carbon-isotope ratios were examined as δ(13)C values in several C3, C4, and C3-C4 Flaveria species, and compared to predicted δ(13)C, values generated from theoretical models. The measured δ(13)C values were within 4‰ of those predicted from the models. The models were used to identify factors that contribute to C3-like δ(13)C values in C3-C4 species that exhibit considerable C4-cycle activity. Two of the factors contributing to C3-like δ(13)C values are high CO2 leakiness from the C4 pathway and pi/pa values that were higher than C4 congeners. A marked break occurred in the relationship between the percentage of atmospheric CO2 assimilated through the C4 cycle and the δ(13)C value. Below 50% C4-cycle assimialtion there was no significant relationship between the variables, but above 50% the δ(13)C values became less negative. These results demonstrate that the level of C4-cycle expression can increase from, 0 to 50% with little integration of carbon transfer from the C4 to the C3 cycle. As expression increaces above 50%, however, increased integration of C3- and C4-cycle co-function occurs.

Use of an anaerobic culture jar in processing pediatric throat cultures

Two hundred consecutive throat cultures from a Pediatric Walk-in Clinic were processed, using both aerobic and anaerobic culture techniques. The 35 aerobic isolates of group A beta-hemolytic streptococci (BHS) were all confirmed anaerobically as well, and there were two additional isolates detected only by the anaerobic technique. Of these 37 bacitracin-sensitive isolates, only 24 (65%) could be identified at 24 hours using the aerobic technique, compared to 29 (78%) using the anaerobic technique. In contrast to this relatively small effect upon the isolation of group A BHS, the yield of BHS from groups B, C, F, and G was more than doubled by the anaerobic technique. The confusion engendered by the improved detection of these bacitracin-resistant BHS using the anaerobic technique offset the small advantage in thoroughness and speed of detection of group A organisms. On this account, until more is known about the possible significance of isolating nongroup A BHS in the pharynx, the advisability of using an anaerobic culture jar to process pediatric throat cultures remains uncertain.