Greater Resolution Research Articles

Printed electronics-based biosensors

Printed electronics have attracted enormous interest owing to their large production capability, low cost, and environmentally friendly properties. Printed electronics-based biosensors have also achieved increasing attention in different domains that range from laboratory to home for many applications. They will be necessary for the implementation of next-generation platforms due to printing simplifies the fabrication of platforms on several thin, rigid, and/or flexible substrates. Moreover, the printed electronics-based biosensors show an excellent chance to facilitate fast, sensitive, and real-time screening of several molecules to exploit their features. Printing technology has strong impacts to assemble more customizable and simpler production of biosensors with great resolution and combination with microfluidic and electronics systems. This review is a summary of recent progress in printed electronics-based biosensors to produce various electronic devices and circuits and also supplies a review of the properties of printed electronics-based biosensors in different applications. In the end, up-to-date experiments of the latest studies of the printed electronics-based biosensors for various target molecules is reported.

Preparation of Borrelia-Infected Mammalian Cells for Helium Ion Microscopy.

Preparation of mammalian cells for a Borrelia burgdorferi infection can be cumbersome especially if investigating possible cell entry processes. The initial steps of infection or entry into cells by a pathogen often involve attachment to the cell surface and plasma membrane changes. To topologically investigate with great resolution and detail these interactions of the pathogen and the mammalian cell, helium ion microscopy (HIM) can be employed. Here we describe a protocol used to define a specific multiplicity of infection (MOI) of Borrelia burgdorferi on a human chondrosarcoma cell line (SW1353) so that fine detail structures on the mammalian cell can be observed and quantified by HIM.

Holistic Approach Uses Electromagnetic Tools, LWD Data To Improve Reservoir Understanding

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215519, “A Holistic Approach to Data Interpretation Combines the Strengths of Ultradeep Electromagnetic Tools With Shallow Logging-While-Drilling Data To Improve Reservoir Understanding,” by Karol Riofrio, SPE, and Nigel Clegg, Halliburton, and Luke Rawsthorne, Aker BP, et al. The paper has not been peer reviewed. _ During drilling operations, logging-while-drilling (LWD) tools, which have greater resolution than seismic, are deployed to aid in decision-making and optimize well placement. Focusing on the data sources in isolation can lead to successful wells, but placing this data in a geological context allows for more-sophisticated decision-making and leads to greater reservoir understanding. Key to linking the near-wellbore measurements with the geological models derived from seismic interpretation are ultradeep electromagnetic tools. The authors describe an approach in which all available technologies are combined to improve reservoir understanding of different depositional environments. Geological Background Deep marine turbidite deposits are recognized as an important hydrocarbon reservoir type; many recent major hydrocarbon discoveries and field developments worldwide occur in sediments deposited by turbidite currents. Turbidite deposits are characterized by a variety of elements such as large-scale erosive features, channels and channel deposits, overbank deposits, lobes, and channel/ lobe transition zones. Each of these elements contains distinctive characteristics. In this complex setting, better definition of the elements present in the reservoir significantly decreases uncertainty while drilling and can improve the completion design, lengthening well life. Applying different well-acquisition technologies such as ultradeep resistivity (UDAR) inversion and anisotropic inversion and interpretation methodologies such as petrophysical analysis, correlation with spectral decomposition volumes, and 4D seismic can help initially for well placement and subsequently for well-completion design and future development of analogous fields. Methodology The complete paper provides the background, characteristics, and advantages of the following methodologies that the authors used in the study: - 1D UDAR inversion - 3D electromagnetic UDAR inversion - 3D electromagnetic UDAR inversion for anisotropy - Spectral decomposition - 4D Seismic Case Study The strength of combining these tools can be demonstrated in the approach to understanding the results of a single well. In the target well, the main goal was to drain the remaining oil identified by 4D seismic in the target structure. Among the complexities acknowledged predrilling was an undulating oil/water contact (OWC) identified as a result of production from previously drilled wells in the area, the lithological complexity of the reservoir resulting from the turbiditic depositional environment, and the filling history of the field. Identification of these complexities highlighted that the chance of exiting the hydrocarbon-bearing zone was high because of the potential for structural uncertainty and a complex, undulating OWC.

Human burials during the hunter‐gathering/farming transition in Ojo de Agua, Northern Patagonia, Argentina

AbstractThis paper explores the implications of the conformation of formal burial areas in the southernmost limit of agricultural dispersion in South America. Previous research proposed the development of cemeteries or formal burial areas due to specialization in using specific habitats and the development of territorial ownership. From a paleoecological background, we hypothesize that hunter‐gatherers intensified resource exploitation and develop territoriality in population growth and pressure over resources. The expectation is that formal burial areas emerged in this context to legitimize the ties with the territory and ensure exclusive access to the land and its resources. To evaluate this hypothesis, we analyzed a mortuary context from southern Mendoza (Central Western Argentina), named Ojo de Agua, by describing the site's characteristics, burial modality, presence of grave goods, age at death profile, and evidence of violence. This site has two main conditions for handling our hypothesis: (1) the chronology and spatial localization coincide with the temporal and geographic dispersion of pre‐Hispanic cultigens; (2) systematic procedures during fieldwork led us to access a significant amount of information not available in other mortuary contexts of the area. Our results point to Ojo de Agua as a cemetery that emerged in the frame of increasing territoriality and conflict with neighboring groups and permitted us to improve our knowledge about the dynamic relationship between human population, environment, and cultural responses in the context of intensification and contact with food production. These results deepen recent studies in the same line but with a greater resolution.

A New Interrogation System for FBG Sensors based on Midband Filter with Correction

In this paper, a midband interrogation system for Fiber Bragg Grating (FBG) sensors is presented and its numerical demonstration is reported. The midband interrogation system is based on a finite reflection filter with automatic correction. The filter is used to interrogate the FBG sensors. The strain FBG sensors were used to demonstrate the effectiveness of the proposed systems. The results demonstrate that the proposed system of interrogation has a great resolution (±1 pm) with good stability.

Targeted NGS Panel Guides Risk-Adapted Treatment Intention in Newly Diagnosed Myeloma Patients

Introduction While overall survival has improved, patients with high-risk multiple myeloma (MM) have poor outcomes. Fluorescent in situ hybridisation (FISH) is widely used to identify high-risk genomic features at diagnosis, but a significant minority of patients classified with standard-risk disease progress rapidly and in retrospect may have warranted more intense frontline therapy. Recently, we implemented the Myeloma Genome Project Panel (MGPP) into clinical workflows - a myeloma-specific targeted sequencing panel capturing 228 genes, 6 translocation regions and 56 copy number abnormalities (CNAs) in a single assay [PMID: 35522533]. Given that MGPP captures many prognostic regions beyond the limited number assessed by FISH, there is potential to better identify high-risk patients. However, the utility of MGPP in supporting clinical risk designation and therapy choice when compared with FISH in newly diagnosed MM is unknown. Methods A prospective cohort study was conducted to compare the impact of MGPP vs. FISH on baseline risk stratification and treatment intention, in 55 unselected newly diagnosed MM patients. For MGPP, libraries were generated from 100ng DNA from bone marrow (BM) derived CD138 + MM cells and matched germline peripheral blood (Roche KAPA HyperCap Target Enrichment/Hyperplus kit). Reads were aligned to hg38, and somatic mutations, CNAs and translocations called with a custom pipeline. ISO-accredited FISH analysis was performed in NHS laboratories. In a multicentre multidisciplinary team (MDT) meeting, four blinded haematologists independently reviewed each clinical case presented twice with either FISH or MGPP, in a random order. Clinicians designated risk status and treatment intentions using a structured proforma. Therapeutically actionable variants could be selected as per the MyDRUG trial [ClinicalTrials.gov: NCT03732703]. A consensus MDT outcome for high-risk or more intensive therapy required at least 3 out of 4 concordant decisions. Results Data is presented here for 23 of 55 patients. The mean age was 68.9 years, 57% were transplant eligible, with R-ISS-1 (35%), R-ISS-2 (26%) and R-ISS-3 (39%). Firstly, MGPP had greater technical success than FISH, reporting successfully in 100% vs. 83% cases from the same diagnostic BM samples respectively (n=4 assay failures with FISH). Secondly, MGPP reported more genomic features than FISH, detecting 231 vs. 18 somatic variants at 127 vs. 7 regions, respectively. Thirdly, MGPP captured equivalent loci at greater resolution, detecting subclonal CNAs missed by FISH (Figure 1). In a head-to-head comparison with FISH, these additional genomic insights from MGPP influenced clinical treatment decisions. A clinician-led MDT reclassified 9 (39%) patients designated as standard-risk by FISH to high-risk status when presented with MGPP (Table 1). Reclassified patients were enriched for prognostically significant MYC translocations (17%) and subclonal 17p loss (22%), 1p loss (17%) and 1q gain (13%) CNAs that were missed by FISH. Altered risk designation influenced frontline treatment intention; clinicians opted for intensification of induction therapy in 13% (FISH) vs. 48% (MGPP) high-risk patients, and considered tandem autologous transplant as an option in 0% (FISH) vs. 23% (MGPP) transplant-eligible patients. FISH identified a therapeutically actionable variant in 3 (13%) patients [venetoclax, n=3]. MGPP identified 13 (57%) additional patients with opportunity for targeted therapy [MEK inhibitor, n=11; BRAF V600E inhibitor, n=2], which the MDT considered as a treatment option in all cases if available in trial. The full dataset and analysis will be presented at time of the conference. Conclusions We demonstrate that MGPP impacts clinical risk designation and treatment intention in newly diagnosed MM. MGPP had greater technical assay success than FISH and captured a greater range and depth of somatic variants. Importantly, these additional insights led a clinical MDT to reclassify 39% patients as high-risk, consider intensification regimen in 39% cases and potential for actionable targeted therapy in 57% patients. Our results support MGPP as a robust alternative to FISH in supporting risk-adapted treatment decisions. We will implement MGPP in additional large prospective cohorts over the next year, to better understand its prognostic utility and feasibility in routine clinical workflows.

An Open Operative Readiness Standard for Surgical Trainees

IntroductionThe American Board of Surgery is transitioning from a volume-based to a competency-based assessment of residents using Entrustable Professional Activities. This form of feedback and evaluation should also apply to operative procedures to help residents track their own progress. We describe an operative readiness tool that measures perceived competency in trainees across several operative, procedural, and clinical activities. MethodsWe distributed a survey to General Surgery trainees at our institution. Participants were asked to rate their level of comfort in 28 operative, procedural, or clinical activities using the standard Entrustable Professional Activity scale: (1) Observation Only, (2) Direct Supervision, (3) Indirect Supervision, (4) Unsupervised Practice, or (5) Supervising Others. Results43 of 46 residents (93%) responded to the survey. Median perceived comfort level generally increased with post graduate year level across all competencies. Residents reached a median perceived level of “Unsupervised Practice” by post graduate year 5 in 17 of 28 competencies of various complexity levels. ConclusionsWhile residents are not expected to achieve an “Unsupervised Practice” comfort level in all competencies, creating a transparent platform for reporting this information provides programs a tool to guide educational quality improvement efforts. In addition, it allows for program directors to have greater resolution into the operative advancement of residents outside of their own specialty. In the future, this tool may be instrumental in the development of national competency standards.

Evaluation of Fourier transform-infrared spectroscopy (FT-IR) as a control measure for nosocomial outbreak investigations.

Whole-genome sequencing (WGS) provides greater resolution than other molecular epidemiology strategies and is emerging as a new gold standard approach for microbial strain typing. The Bruker IR Biotyper is designed as a screening tool to identify bacterial isolates that require WGS to establish accurate relationships, but its performance and utility in nosocomial outbreak investigations have not been thoroughly investigated. Here, we evaluated the IR Biotyper by retrospectively examining isolates tested by WGS during investigations of potential nosocomial transmission events or outbreaks. Ninety-eight clinical isolates from 14 different outbreak investigations were examined: three collections of Acinetobacter baumannii (n = 2, n = 9, n = 5 isolates in each collection), one of Escherichia coli (n = 16), two of Pseudomonas aeruginosa (n = 2 and n = 5), two of Serratia marcescens (n = 9 and n = 7), five of Staphylococcus aureus (n = 8, n = 4, n = 3, n = 3, n = 17), and one of Stenotrophomonas maltophilia (n = 8). Linear regression demonstrated a weak, positive correlation between the number of pairwise genome-wide single-nucleotide polymorphisms (SNPs) and IR Biotyper spectral distance values for Gram-positive (r = 0.43, P ≤ 0.0001), Gram-negative (r = 0.1554, P = 0.0639), and all organisms combined (r = 0.342, P ≤ 0.0001). Overall, the IR Biotyper had a positive predictive value (PPV) of 55.81% for identifying strains that were closely related by genomic identity, but a negative predictive value (NPV) of 86.79% for identifying unrelated isolates. When experimentally adjusted cut-offs were applied to A. baumannii, P. aeruginosa, and E. coli, the PPV was 62% for identifying strains that were closely related and the NPV was 100% for identifying unrelated isolates. Implementation of the IR Biotyper as a screening tool in this cohort would have reduced the number of Gram-negative isolates requiring further WGS analysis by 50% and would reduce the number of S. aureus isolates needing WGS resolution by 48%.

Unraveling the role of non-coding rare variants in epilepsy.

The discovery of new variants has leveled off in recent years in epilepsy studies, despite the use of very large cohorts. Consequently, most of the heritability is still unexplained. Rare non-coding variants have been largely ignored in studies on epilepsy, although non-coding single nucleotide variants can have a significant impact on gene expression. We had access to whole genome sequencing (WGS) from 247 epilepsy patients and 377 controls. To assess the functional impact of non-coding variants, ExPecto, a deep learning algorithm was used to predict expression change in brain tissues. We compared the burden of rare non-coding deleterious variants between cases and controls. Rare non-coding highly deleterious variants were significantly enriched in Genetic Generalized Epilepsy (GGE), but not in Non-Acquired Focal Epilepsy (NAFE) or all epilepsy cases when compared with controls. In this study we showed that rare non-coding deleterious variants are associated with epilepsy, specifically with GGE. Larger WGS epilepsy cohort will be needed to investigate those effects at a greater resolution. Nevertheless, we demonstrated the importance of studying non-coding regions in epilepsy, a disease where new discoveries are scarce.

A hybrid CZT-LaBr3:Ce Compton camera system for improving proton therapy imaging

This work aims to combine the Polaris-J cadmium zinc telluride semi-conductor detector with a LaBr3:Ce scintillation detector as a hybrid Compton camera that can produce high-quality prompt γ ray images. The LaBr3:Ce detectors (Saint-Gobain Crystals) have outstanding timing resolution (< 350 ps), great energy resolution (< 2.5 % at 1332 keV), and a higher maximum energy range. The goal is to use the strengths of the LaBr3:Ce detectors to offset some of the limitations of the Polaris-J detector.

Towards affordable 3D physics-based river flow rating: application over the Luangwa River basin

Abstract. Uncrewed aerial vehicles (UAVs), affordable precise global navigation satellite system hardware, multi-beam echo sounders, open-source 3D hydrodynamic modelling software, and freely available satellite data have opened up opportunities for a robust, affordable, physics-based approach to monitoring river flows. Traditional methods of river discharge estimation are based on point measurements, and heterogeneity of the river geometry is not contemplated. In contrast, a UAV-based system which makes use of geotagged images captured and merged through photogrammetry in order to generate a high-resolution digital elevation model (DEM) provides an alternative. This UAV system can capture the spatial variability in the channel shape for the purposes of input to a hydraulic model and hence probably a more accurate flow discharge. In short, the system can be used to produce the river geometry at greater resolution so as to improve the accuracy in discharge estimations. Three-dimensional hydrodynamic modelling offers a framework to establish relationships between river flow and state variables such as width and depth, while satellite images with surface water detection methods or altimetry records can be used to operationally monitor flows through the established rating curve. Uncertainties in the data acquisition may propagate into uncertainties in the relationships found between discharge and state variables. Variations in acquired geometry emanate from the different ground control point (GCP) densities and distributions used during photogrammetry-based terrain reconstruction. In this study, we develop a rating curve using affordable data collection methods and basic principles of physics. The basic principal involves merging a photogrammetry-based dry bathymetry and wet bathymetry measured using an acoustic Doppler current profiler (ADCP). The output is a seamless bathymetry which is fed into the hydraulic model so as to estimate discharge. The impact of uncertainties in the geometry on discharge estimation is investigated. The impact of uncertainties in satellite observation of depth and width is also analysed. The study shows comparable results between the 3D and traditional river rating discharge estimations. The rating curve derived on the basis of 3D hydraulic modelling was within a 95 % confidence interval of the traditional gauging-based rating curve. The 3D-hydraulic-model-based estimation requires determination of the roughness coefficient within the stable bed and the floodplain using field observation at the end of both the dry and wet season. Furthermore, the study demonstrates that variations in the density of GCPs beyond an optimal number have no significant influence on the resultant rating relationships. Finally, the study observes that which state variable approximation (water level and river width) is more accurate depends on the magnitude of the flow. Combining stage-appropriate proxies (water level when the floodplain is entirely filled and width when the floodplain is filling) in data-limited environments yields more accurate discharge estimations. The study was able to successfully apply advanced UAV and real-time kinematic positioning (RTK) technologies for accurate river monitoring through hydraulic modelling. This system may not be cheaper than in situ monitoring; however, it is notably more affordable than other systems such as crewed aircraft with lidar. In this study the calibration of the hydraulic model is based on surface velocity and the water depth. The validation is based on visual inspection of an RTK-based waterline. In future studies, a larger number of in situ gauge readings may be considered so as to optimize the validation process.

5.7 ps Resolution Time-to-Digital Converter Implementation Using Routing Path Delays

A tapped delay line (TDL)-based time-to-digital converter (TDC) implemented on an FPGA (Field Programmable Gate Array) is sensitive to nonlinearities because of significant variations in the delay of the delay elements. Most of the nonlinearity of FPGA-based TDCs comes from the routing of the design. It is promising to realize TDCs using internal routing resources available in FPGAs, as these devices contain a lot of routing resources and are resistant to voltage and temperature changes. This work implements and tests a TDC based on a series of counters driven by a variable delay line that exploits the internal routing resources available in the FPGA as delay elements. A manual placement and routing technique that results in greater resolution and linearity is proposed. The time-interleaving concept is used to improve the resolution of the TDC. A measurement matrix with 512 and 1024 parallel counters is implemented on a Zynq Evaluation and Development (ZED) board. The result of the 1024-unit TDC showed that a dynamic range of 93.6 ns can be measured using a 4-bit coarse gray code counter running at a reference frequency of 171 MHz, and a resolution of 5.7 ps is achieved. The implemented TDC is low-cost, has a fast time to market, and it benefits from the abundant routing resources in the FPGA.

Puke or poop? Comparison of regurgitate and faecal samples to infer alpine grasshopper (Paprides nitidus Hutton) diet in experimental plant communities.

Characterising plant-herbivore interactions is important to understanding the processes that influence community structure and ecosystem functioning. Traditional methods used to identify plant-herbivore interactions are being superseded by non-destructive molecular approaches that can infer interactions with greater resolution and accuracy from environmental DNA (e.g. faeces and regurgitate). However, few studies have compared the success of using different sample types and whether they provide similar or contrasting information about species' diet. Here we compared the success of DNA amplification and host plant species identification using restriction fragment length polymorphism (RFLP) applied to faecal and regurgitate samples collected from alpine grasshoppers Paprides nitidus Hutton during a grassland community mesocosm experiment. We found that DNA amplification success was 23% and 86% higher for faecal than regurgitate samples from female and male grasshoppers, respectively. In contrast, successful host plant identification using RFLP was 9% higher for regurgitate than faecal samples. The mean number of host plant species identified per sample (1.40) did not differ between sample types or grasshopper sexes. Of the 136 paired faecal-regurgitate samples, just 41% and 74% produced exactly or partially matching host plant identifications, respectively, indicating that different sample types provided complementary information about herbivore diet. Some plant species were more likely to be identified from faecal samples than expected by chance, and we found that this identification bias skewed towards plant species with higher investment in leaf tissue. We conclude that multiple sample types may be required to fully characterise an invertebrate herbivore species' diet.

Breast Thermograms Analysis using Deep Neural Network

Breast cancer is one of the leading causes of mortality among women globally. Early identification of this kind of cancer is important for a successful treatment outcome. A variety of screening techniques can be used to identify breast cancer. Thermography is possible for early diagnosis that uses thermal cameras with great resolution and sensitivity. The goal is to develop a system that automatically captures and classifies thermographic imaging of the breast as normal or abnormal. In this method,the detection and classification of breast cancer from thermography images usingadeeplearning-based convolution neural network using the VGG-19 algorithm. Breast cancer detection is performed using CNN with the help of Google collaboratory (Google Colab). Finally, as the result of experimental studies, the major focus is on the performance accuracy of the train and test dataset, and the graph is plotted between the training and validation accuracy.The VGG-19 network achieved the highesttestperformanceof 99.80% in breast cancer detection and to classify cancer using the DMR Mastology Research dataset.

Identifikasi Sebaran Asap Kebakaran Hutan di Wilayah Jambi dengan Menggunakan Radar C-BAND

Forest and land fires along with the distribution of smoke are one of the disasters threats in the Jambi region which has tropical forests. By knowing the lowest level of visibility from observations, this study was conducted on September 23, 2015. Weather and satellite radar have ability to detect particles and the distribution of smoke from forest and land fires with great spatial and temporal resolution, supported by HIMAWARI-8 satellite data as comparison. C-Band Doppler radar and default strategy scanning are used to identify smoke in Jambi. Wind layer analysis uses CAPPI V products to display smoke distribution and CMAX dBZ with palette changes to identify smoke particles, which then will be carried out vertical cross section to see smoke reflectivity values, identify smoke vertical profiles, and patterns of smoke distribution of forest and land fires. The smoke reflectivity index value can be seen from the dBZ value. The results of the identification show that the smoke material reaches a maximum reflectivity value of 30 dBZ at the centre of the fire point and the minimum value of very fine smoke particles reaches -24.4 dBZ which scattered with the dominant velocity distribution direction to the northwest.

Settings and Indications of Ultrasound in Imaging of Shoulder, Foot, and Ankle

Ultrasonography is a well-established musculoskeletal imaging technique with a multitude of advantages when compared to other modalities. It provides great spatial resolution in the evaluation of superficial articular and peri-articular structures including tendons, ligaments, bursae, and nerves. Given that it is the only modality which allows dynamic assessment, it also plays a crucial role in diagnosing impingement, subluxation/dislocation, and instability. The purpose of this article is to review the settings and indications of US in the imaging of shoulder, foot, and ankle in particular. Relevant literature, predominantly in the form of peer-reviewed journal articles was obtained from the electronic databases such as PubMed and MEDLINE and reviewed in a structured manner. This was combined with background knowledge and expertise in this field.

LESSONS LEARNT FROM THE HIGH RESOLUTION UAS PHOTOGRAMMETRIC SURVEY OF A HISTORIC URBAN AREA: UNESCO SITE OF SABBIONETA

Abstract. In view of the increasing development of the smart city concept and the generation of 3d city models, it becomes essential to have an up-to-date, high-detail 3D survey of urban areas. There are several technologies that enable the development of a geometric survey of urban areas, including the use of aerial laser scanning, remote sensing, mobile mapping systems, and Unmanned Aerial Sistems (UAS) photogrammetry. Of these, the last mentioned, when developed with high-resolution cameras and flight plans with appropriate elevations, allows point clouds to be obtained at a high level of detail and orthophotos with great resolution. This technique may be the preferable choice when the object of the survey is a historic urban area, which has some special features, which might make surveying difficult with other surveying techniques. This paper presents the survey with UAS photogrammetry of a historic urban area: the city of Sabbioneta, in northern Italy. The UAS flight planning is discussed in details, specifically referring to european UAS flight regulations. The survey was developed with DJI Matrice 300 RTK, equipped with a flight terminator and parachute, and coupled with a high precision GNSS Mobile Station DJI D-RTK 2. Ground control points and check points were measured with GNSS receiver Leica GS18. Images were processed with Agisoft Metashape following a photogrammetric workflow. The resulting orthophoto has a pixel size of 1 cm. The obtained dense point cloud is suitable for future use for its segmentation by testing existing machine learning and deep learning methods and for future urban analysis.

Diagnostic efficacy of cone beam computed tomography in tmj disorders – A narrative review

Temporomandibular joint disorders (TMDs) diagnosis requires routine clinical evaluation and radiographic evaluation of patients with temporomandibular joint disorders (TMDs). Various imaging techniques have been described in the literature to evaluate TMJ in both symptomatic and asymptomatic patients. Cone beam computed tomography (CBCT), a fast developing method, is currently used often in dento-maxillofacial imaging. Due to its great resolution and relatively low dosage, it has an advantage. When looking through the data on TMJ imaging, it appears that the ongoing CBCT revolution has had a significant influence. The goal of this narrative review is to discuss the current situation regarding the diagnostic use of CBCT in TMDs.

A convolutional neural network to characterize mouse hindlimb foot strikes during voluntary wheel running.

Voluntary wheel running (VWR) is widely used to study how exercise impacts a variety of physiologies and pathologies in rodents. The primary activity readout of VWR is aggregated wheel turns over a given time interval (most often, days). Given the typical running frequency of mice (∼4Hz) and the intermittency of voluntary running, aggregate wheel turn counts, therefore, provide minimal insight into the heterogeneity of voluntary activity. To overcome this limitation, we developed a six-layer convolutional neural network (CNN) to determine the hindlimb foot strike frequency of mice exposed to VWR. Aged female C57BL/6 mice (22months, n = 6) were first exposed to wireless angled running wheels for 2h/d, 5days/wk for 3weeks with all VWR activities recorded at 30 frames/s. To validate the CNN, we manually classified foot strikes within 4800 1-s videos (800 randomly chosen for each mouse) and converted those values to frequency. Upon iterative optimization of model architecture and training on a subset of classified videos (4400), the CNN model achieved an overall training set accuracy of 94%. Once trained, the CNN was validated on the remaining 400 videos (accuracy: 81%). We then applied transfer learning to the CNN to predict the foot strike frequency of young adult female C57BL6 mice (4months, n = 6) whose activity and gait differed from old mice during VWR (accuracy: 68%). In summary, we have developed a novel quantitative tool that non-invasively characterizes VWR activity at a much greater resolution than was previously accessible. This enhanced resolution holds potential to overcome a primary barrier to relating intermittent and heterogeneous VWR activity to induced physiological responses.

Evaluation of phthalic acid tri-ethylene diamine (TED) and folic acid-based carbon quantum dots for the detection of heavy metals in water resources using fibre-optic instrumentation

ABSTRACT Heavy metal pollution and toxicity from water resources have remained a great concern for the entire population. This research demonstrates the capability of carbon quantum dots (CQDs) for fluorescence-based heavy metal detection in different water resources using a fibre-optic spectrometer device. Two different types of CQDs phthalic acid and triethylenediamine (PT CQDs) and Folic acid (FCQDs) were synthesized using microwave irradiation and hydrothermal method, respectively. CQDs were characterized using several techniques such as TEM, EDX, XPS and FTIR. PTCQD and FCQDs both were tested for sensing capability in water reservoirs like household and river water. The results indicate that both CQDs were able to detect all six heavy metal ions (Pb2+, Co2+, Mn3+, Hg2+, Ni2+, Cr3+) tested in the study in the range of 0–100 µM. It was found that FCQDs show a three-fold higher sensitivity and greater resolution than PTCQDs for all the heavy metals samples. The CQDs’ sensing capability shows that they can achieve a limit of detection in the range of 0.15–3 µM along with 100% accuracy in terms of recovery with minimal error, these results indicate that both CQDs have a tremendous potential to be used as a sensor for the detection of heavy metals even in complex water matrices. FCQDs show more sensitivity for all metals compared to PTCQDs and used in future as a sensing tool for heavy metal detection with better sensitivity and accuracy with less response time.