Test Locations Research Articles

A progressive change in the virulence spectrum of Asian rice gall midge (<em>Orseolia oryzae</em>) biotype 2 after a decade in Coastal Karnataka, India

Virulence composition of traditionally designated biotype 2 field population of Asian rice gall midge, Orseolia oryzae (Wood- Mason) (Cecidomyiidae: Diptera) was conducted a decade after in 2019 and 2020 at coastal Karnataka, India using three standard differentials viz., W1263 (Gm1 gene for resistance), Phalguna (Gm2 gene for resistance) and TN1 (susceptible without any gene). The local population of gall midge was virulent against all 16 standard rice gene differentials representing four groups identified to characterize the prevailing rice gall midge biotypes in India. The local gall midge populations in the test locations expressed their virulence against all three rice gene differentials with varied female to male sex ratio of their F1 progenies. This confirms the prevalence of genetically heterogeneous population in coastal regions of Karnataka. Clearly, a progressive change in the virulence spectrum of local gall midge biotype 2 was noticed a decade after observations. In south coast, 73.33 to 87.27% population showed virulent attributes of traditional biotype 2 designated in 1989. Whereas in north coast, 79.69 to 86.36% population exhibited virulence attributes towards new biotype 3 for the first time in the state of Karnataka, India. These results suggested a progressive change in the traditionally designated population of biotype 2 capable of damaging resistant varieties in the region for over three decades. Further, the single female test for their F1 progenies in all endemic locations indicated an evolution of new biotype of rice gall midge in the region.

1366. Re-examining the Origins of Ebola virus Emergence

Abstract Background Ebola virus (EBOV) is one of four ebolaviruses known to cause Ebola virus disease (EVD). It is widely thought that EVD outbreaks originate from spillover of ebolaviruses from wildlife into humans. However, phylogenetic analysis of EBOV sequences from recent EVD cases reveal genetic similarity to EBOV from prior outbreaks. Therefore, it is likely that these recent EVD outbreaks originated through human-to-human transmission instead of wildlife spillover. The aim of this study is to re-examine the origins and contexts of EVD outbreaks given this new knowledge. Methods All known EVD outbreaks and EBOV emergence events from 1976-2021 were analyzed via literature review. The primary and index cases for each outbreak were compared based on demographics and suspected sources of transmission. The diagnostic testing and treatment locations for each EVD index case were also investigated. Phylogenetic and epidemiologic relationships were examined to characterize whether outbreaks likely originated from separate spillover events or human-to-human transmission. Results Overall, 22 outbreaks caused by EBOV were identified from 1976-2021 (Table). 5/22 (22.7%) of outbreaks were possibly linked to previous EVD outbreaks, including the four most recent outbreaks. Possible sources for these outbreaks included relapse and delayed sexual transmission from survivors. 12/22 (54.5%) of outbreaks were linked to suspected spillover sources, which included contact with duikers, chimpanzees, gorillas, monkeys, and bats. The locations of these Ebola virus emergence events are shown in the Figure. Conclusion Recent EVD outbreaks have changed our understanding of the emergence of EBOV in humans. Most recent outbreaks have originated from human-to-human transmission rather than spillover from wildlife. Multiple large EVD outbreaks have created the potential for future resurgence among humans. Therefore, increased surveillance among humans as well as awareness among healthcare workers and traditional healers, who are often the first to encounter index cases, will be critical to preventing the next epidemic. Clinicians and researchers will need to carefully evaluate the origins of EVD outbreaks through epidemiological and phylogenetic analyses while also preventing stigma among survivors. Disclosures All Authors: No reported disclosures.

Detection of Malpractice in Offline Examination Using Deep Learning

Exam proctoring is a hectic task i.e.; the monitoring of students' activities becomes difficult for supervisors in the examination rooms. It is a costly approach that requires much labor and difficult task for supervisors to keep an eye on all students at a time. Automatic exam activities recognition is therefore necessitating and a demanding field of research. In this research work, categorization of students' activities during the exam is performed using a deep learning approach. Adeep CNN architecture a kernel size of 7 * 7 and 64 different kernels all with a stride of size 2 givingus 1 layer. After that, the model is validated upon ImageNet. In this paper, we present amultimedia analytics system which performs automatic offline exam proctoring. The system hardwareincludes one webcam for the purpose of monitoring the visual environment of the testing location. Toevaluate our proposed system, we collect multimedia (visual) data from many exam centers performing various types of activities while taking exams. Extensive experimental results demonstratethe accuracy, robustness, and efficiency of our offline exam proctoring system.

Campus Managers’ Role in Innovation Implementation for Sustainability on Dutch University Campuses

Internationally, the ambition to achieve a sustainable built environment is becoming urgent. On the university campus, this vision, combined with unparalleled access to innovative technologies for sustainable development enables/urges universities to implement more innovative solutions more often. As a prime test location, the university campus is uniquely able to serve as a context for living labs, implementing and testing innovative technologies in a real-world environment. However, implementation of innovation on campus requires a clear vision, intentional action and transdisciplinary collaboration, while innovations themselves pose several challenges to the business-as-usual way of work. To explore the role of campus real estate managers in innovation implementation decisions on the university campus, a literature review and a qualitative study among campus managers of 13 Dutch universities were conducted. The research explored the innovation project types, risks, drivers and barriers and the real estate management responsibilities and decision criteria in innovation implementation projects. As one of the outputs of this research, a comprehensive categorization framework was developed. It clarifies campus managers’ decision-making dimensions for innovative sustainability project implementation on campus and highlights the sustainability objectives unique to universities. If implemented across universities, it could further strengthen the networked economy by identifying opportunities for cross-campus implementation of innovative projects for sustainability.

Diminutive Epibionts on Crinoid Stems from the Lower/Middle Devonian Boundary in the Barrandian, Czech Republic

Abstract Diminutive crinoid holdfasts and cemented tests of the foraminifers Psammosphaera and Tolypammina were observed on coarse bioclasts in weathered limestones of the Daleje-Třebotov Formation. Specimens were obtained in 1984 by washing so called “white beds” at a temporary locality in Praha- Barrandov. A few millimeter sized bioclasts with epibionts were freed from hard limestone beds of the Třebotov Limestone near the Lower/Middle Devonian boundary by long-term weathering. Many of the crinoid holdfasts attached to pluricolumnals provoked a stereomic response of the host crinoid. Also the growth orientation of the crinoid epibiont is not random and indicates some crinoid-epibiont to crinoidhost interaction. Reaction of host stereome and non-random stem orientation offer direct evidence of epibiont larval settlement and subsequent growth on the stem of a living crinoid host. The extensive growth of the host stereome ended by partial to total engulfing of the epibiont holdfast. This indicates advancing and finally successful defence of the host crinoid against the epibiont. The holdfast gives evidence that the small host crinoids offered a somewhat higher tier for even smaller epibiont crinoids. However, other observed holdfasts indicate fixation of larva and growth over loose bioclasts lying on a sea bed. Location of foraminifer test on bioclasts confims that foraminifers cemented and grew on loose echinodermal and brachiopod remains and preferred crevices and similar protected sites with concave profiles. This is clear evidence that diverse bioclasts (brachiopod shells, pelmatozoan ossicles) provided the hard substrate suitable for epibiont life on a sea bed.

Multidimensional Scaling of Cognitive Ability and Academic Achievement Scores.

Multidimensional scaling (MDS) was used as an alternate multivariate procedure for investigating intelligence and academic achievement test score correlations. Correlation coefficients among Wechsler Intelligence Scale for Children, Fifth Edition (WISC-5) and Wechsler Individual Achievement Test, Third Edition (WIAT-III) validity sample scores and among Kaufman Assessment Battery for Children, Second Edition (KABC-II) and Kaufman Test of Educational Achievement, Second Edition (KTEA-2) co-norming sample scores were analyzed using multidimensional scaling (MDS). Three-dimensional MDS configurations were the best fit for interpretation in both datasets. Subtests were more clearly organized by CHC ability and academic domain instead of complexity. Auditory-linguistic, figural-visual, reading-writing, and quantitative-numeric regions were visible in all models. Results were mostly similar across different grade levels. Additional analysis with WISC-V and WIAT-III tests showed that content (verbal, numeric, figural) and response process facets (verbal, manual, paper-pencil) were also useful in explaining test locations. Two implications from this study are that caution may be needed when interpreting fluency scores across academic areas, and MDS provides more empirically based validity evidence regarding content and response mode processes.

Efficient Use of a Hybrid Chamber for Radiated Susceptibility Tests

This letter describes the design and operation of a novel type of hybrid chamber used for radiated susceptibility tests. This is a semi-anechoic chamber with the possibility to install a vibrating intrinsic reverberation chamber inside. This testing environment can be used for the execution of the radiated susceptibility tests using both the deterministic and stochastic methodologies but without changing the test location, nor moving the device under test with its auxiliary equipment. This allows test engineers to combine the advantages of both reverberation and semi-anechoic chambers with a minimum effort, making it a very practical, cost- and time-efficient solution. The electric field into the reverberation chamber is monitored by eight electric field probes, permitting the closed-loop control of the electric field strength level and an efficient real-time analysis of the performance indicators discussed in this letter.

Monitoring European data with prospective space–time scan statistics: predicting and evaluating emerging clusters of COVID-19 in European countries

BackgroundCoronavirus disease 2019 (COVID-19) has become a pandemic infectious disease and become a serious public health crisis. As the COVID-19 pandemic continues to spread, it is of vital importance to detect COVID-19 clusters to better distribute resources and optimizing measures. This study helps the surveillance of the COVID-19 pandemic and discovers major space–time clusters of reported cases in European countries. Prospective space–time scan statistics are particularly valuable because it has detected active and emerging COVID-19 clusters. It can prompt public health decision makers when and where to improve targeted interventions, testing locations, and necessary isolation measures, and the allocation of medical resources to reduce further spread.MethodsUsing the daily case data of various countries provided by the European Centers for Disease Control and Prevention, we used SaTScan™ 9.6 to conduct a prospective space–time scan statistics analysis. We detected statistically significant space–time clusters of COVID-19 at the European country level between March 1st to October 2nd, 2020 and March 1st to October 2nd, 2021. Using ArcGIS to draw the spatial distribution map of COVID-19 in Europe, showing the emerging clusters that appeared at the end of our study period detected by Poisson prospective space–time scan statistics.ResultsThe results show that among the 49 countries studied, the regions with the largest number of reported cases of COVID-19 are Western Europe, Central Europe, and Eastern Europe. Among the 49 countries studied, the country with the largest cumulative number of reported cases is the United Kingdom, followed by Russia, Turkey, France, and Spain. The country (or region) with the lowest cumulative number of reported cases is the Faroe Islands. We discovered 9 emerging clusters, including 21 risky countries.ConclusionThis result can provide timely information to national public health decision makers. For example, a country needs to improve the allocation of medical resources and epidemic detection points, or a country needs to strengthen entry and exit testing, or a country needs to strengthen the implementation of protective isolation measures. As the data is updated daily, new data can be re-analyzed to achieve real-time monitoring of COVID-19 in Europe. This study uses Poisson prospective space–time scan statistics to monitor COVID-19 in Europe.

A deep investigation into the mechanisms and factors producing mud pumping of railway track

Ballast degradation and mud pumping are common issues facing all railroads in which slurry within the ballast pumps up around the surface of the track during train operations. This often corresponds to poor drainage, loss in track geometry, reduced ballast strength and stiffness, and, in the worst cases, can lead to derailment. Despite the prevalence of this problem, the mechanisms behind mud pumping and the factors influencing it have not been fully investigated, although past studies have determined that fines and water in the ballast, as well as repeated dynamic wheel loads, need to act together to produce mud pumping. Researchers at MxV Rail (formerly TTCI) have further investigated mud pumping situations from both the test track at the Facility for Accelerated Service Testing (FAST) and multiple revenue service track locations to further understand the underlying mechanisms of ballast mud pumping. These investigations have shown that some (and possibly most) ballast mud pumping situations are surficial problems, originating from the wet regions just around the ties (sleepers), which is the focus of this paper. However, other mud pumping situations include seasonal or perched water table below the bottom of the ties that causes moisture and fines to pump up to the surface from the underlying subgrade or lower degraded ballast and subballast layers.

Selection of High Yield and Stable Maize Hybrids in Mega-Environments of Java Island, Indonesia

Determination of grain yields of stable and high-yielding maize hybrids in a wide environment requires high accuracy. Many stability measurement methods have been used in multi-environment experiments. However, the relationships among the different methods are still difficult to understand. The objectives of this study were to 1. Identify the effect of growing season and location (Environments = E), hybrids (Genotypes = G), and their interactions (GEIs) on grain yields; 2. Select high-yielding and stable maize hybrids in a wide range of environments; 3. Determine the relationship between each stability estimation; and 4. Determine the mega-environment of maize hybrid and identify the best locations for testing. Field experiments were conducted at ten locations in Java Island, Indonesia, for two growing seasons using a randomized completed block design with three replications. The experimental results showed that the main effects of the growing season, location, hybrid, and GEIs, significantly affected maize hybrid yields. Stability estimations of TOP, S(3), S(6), NP(2), NP(3), KR, NP(4), CVi, and bi, belong to the concept of dynamic stability that can be used to select maize hybrids in favorable environments, while other estimations were classified as in the static stability. Three maize hybrids were successfully selected, with high and stable yields based on numerical and visual stability estimations, namely SC2, SC7, and SC9. The three hybrids can be used as candidates for sustainable maize development programs. The dry season, the rainy season, and the combination of two growing seasons produced three mega-environments. GJRS and KARS were the most discriminative environments. Both environments can be used as favorable environments for selecting the ideal maize hybrid.

Hybrid machine learning approach for landslide prediction, Uttarakhand, India

Natural disasters always have a damaging effect on our way of life. Landslides cause serious damage to both human and natural resources around the world. In this paper, the prediction accuracy of five hybrid models for landslide occurrence in the Uttarkashi, Uttarakhand (India) was evaluated and compared. In this approach, the Rough Set theory coupled with five different models namely Bayesian Network (HBNRS), Backpropagation Neural Network (HBPNNRS), Bagging (HBRS), XGBoost (HXGBRS), and Random Forest (HRFRS) were taken into account. The database for the models development was prepared using fifteen conditioning factors that had 373 landslide and 181 non-landslide locations that were then randomly divided into training and testing locations with a ratio of 75%:25%. The appropriateness and predictability of these conditioning factors were assessed using the multi-collinearity test and the least absolute shrinkage and selection operator approach. The accuracy, sensitivity, specificity, precision, and F-Measures, and the area under the curve (AUC)-receiver operating characteristics curve, were used to evaluate and compare the performance of the individual and hybrid created models. The findings indicate that the constructed hybrid model HXGBRS (AUC = 0.937, Precision = 0.946, F1-score = 0.926 and Accuracy = 89.92%) is the most accurate model for predicting landslides when compared to other models (HBPNNRS, HBNRS, HBRS, and HRFRS). Importantly, when the fusion is performed with the rough set method, the prediction capability of each model is improved. Simultaneously, the HXGBRS model proposed shows superior stability and can effectively avoid overfitting. After the core modules were developed, the user-friendly platform was designed as an integrated GIS environment using dynamic maps for effective landslide prediction in large prone areas. Users can predict the probability of landslide occurrence for selected region by changing the values of a conditioning factors. The created approach could be beneficial for predicting the impact of landslides on slopes and tracking landslides along national routes.

Experimental Study on Vibration Velocity of Piled Raft Supported Embankment and Foundation for Ballastless High Speed Railway

In recent years, the high development of high-speed railway lines cross through areas with poor geological conditions, such as soft soil, offshore and low-lying marsh areas, resulting geotechnical problems, such as large settlements and reduction of bearing capacity. As a new soil reinforcement method in high speed railway lines, the piled raft structure has been used to improve soil conditions and control excess settlement. In order to study the dynamic behavior of piled raft supported ballastless track system in soft soil, an experimental study on vibration velocities of piled raft supported embankment and foundations is presented in soft soil with different underground water levels. Vibration velocities at specified positions of the piled raft supported embankment and foundations are obtained and discussed. The vibration velocity curves on various testing locations of piled raft foundations are clearly visible and have sharp impulse and relaxation pattern, corresponding to loading from train wheels, bogies, and passages. Vibration velocity distribution in the horizontal direction at three train speeds clearly follows an exponential curves. Most of the power spectrums of vibration velocity at various locations are mainly concentrated at harmonic frequencies. The change in water level has slight impaction on the peak spectrum of vibration velocity at harmonic frequencies. The vibration power induced by train loads are transmitted, absorbed, and weakened to a certain extent through embankment and piled raft structure. The dynamic response character of embankments are affected by their self-vibration characteristics and the dynamic bearing capacity of the piled raft structure.

BayLUP: A Bayesian framework for conditional random field simulation of the liquefaction-induced settlement considering statistical uncertainty and model error

Assessing the spatial variability of the liquefaction-induced settlement at a site often involves spatial interpolation based on some stochastic models (e.g., random fields). Accuracy of the spatial interpolation results highly depends on the number of testing data and statistical model parameters. Statistical uncertainty in model parameters is inevitable due to a lack of sufficient testing data. Moreover, the liquefaction-induced settlement at testing locations can be estimated from site investigation data using semi-empirical models derived from previous testing data and observations, for which the model error is unavoidable. This paper develops a novel Bayesian framework, called BayLUP, based on Kriging-based conditional random field (CRF), which, simultaneously, accounts for spatial variability, statistical uncertainty, and model error into probabilistic characterization of the liquefaction-induced settlement. The proposed approach is comprised of three steps, i.e., learning step (L-step), updating step (U-step), and predicting step (P-step), which are formulated from a Bayesian perspective and are sequentially implemented using the ancestor sampling method. It is illustrated and validated using real and simulated data. Results show that the BayLUP framework provides reasonable spatial interpolation results of the liquefaction-induced settlement based on a limited number of testing data and prior knowledge. Under the BayLUP framework, the spatial variability, model error, and statistical uncertainty are taken into account in a quantifiable and rational way without compromising the computational efficiency of CRF simulation. Ignoring the statistical uncertainty and model error might lead to underestimation of the prediction uncertainty.

High Performance Convertible Coleopter Drones

This paper opens with an historical overview of efforts to develop micro-, mini-, and organic aerial vehicles (MAVs and OAVs) in the 1990’s. Although conceived during WWII, coleopters would not see serial production for 60 years. The paper continues with programmatic aspects of hovering coleopter development of the 1990’s and describes the technical motivations behind in-flight conversion from hover-mode to missile-mode flight and the record-setting XQ-138 family of convertible coleopters. As the first commercially successful family of such aircraft, the XQ-138 was taken from initial concept through configuration design, detailed design, patenting, prototyping, proof-of-concept, production, flight testing, qualification, and eventually high rate production, all with private funding. The paper lists basic engineering drivers, covers fundamental sizing methods, presents weight fraction data, and describes flight test procedures, locations, conditions, and results. High-speed flight test data show the stock aircraft achieving speeds in excess of 164 mph (263 kph) with endurances in excess of an hour at that speed with a special dash-optimized version reaching 288 mph (463 kph) for a few minutes. Videos from flight testing and live-fire exercises are shown at Redstone Arsenal, Eglin Air Force Base, and Fort Benning test ranges under extreme conditions. The paper concludes with an assessment of civil and military variants for a variety of military missions and commercial uses.

Tri-level Framework for Realistic Estimation of Concrete Strength Using Bayesian Data Fusion of UPV and Guided Coring

Identification of in situ concrete characteristic strength (CCS) of deteriorating RC structures directly affects their rehabilitation. Contemporary practices lack the ability to yield CCS or at most produce an unrealistic estimate, because: (i) core tests are few due to technical and economic constraints and their positioning is random, inducing bias in the strength estimate, (ii) non-destructive tests (NDT) are themselves not good estimators of project specific strength, (iii) tests are only local indicators and most practising engineers are unaware of how to process the spatial variability. This paper overcomes these limitations with a novel and implementable framework, for an asset manager to make scientific estimates of CCS. This is a tri-level framework: (1) NDT are performed to capture the spatial variability of the investigated concrete; (2) core extractions are guided by the prior NDT information, to avoid bias in test location selection; (3) NDT and coring results are fused via Bayesian NDT test calibration and updating of the probability distribution of the concrete strength. The proposed framework is successfully implemented for the assessment and rehabilitation of a critical hospital complex in India.

Deep Learning Estimation of 10-2 Visual Field Map Based on Circumpapillary Retinal Nerve Fiber Layer Thickness Measurements

To estimate central 10-degree visual field (VF) map from spectral-domain optical coherence tomography (SD-OCT) retinal nerve fiber layer thickness (RNFL) measurements in glaucoma with artificial intelligence. Artificial intelligence (convolutional neural networks) study. This study included 5352 SD-OCT scans and 10-2 VF pairs from 1365 eyes of 724 healthy patients, patients with suspected glaucoma, and patients with glaucoma. Convolutional neural networks (CNNs) were developed to estimate the 68 individual sensitivity thresholds of 10-2 VF map using all-sectors (CNNA) and temporal-sectors (CNNT) RNFL thickness information of the SD-OCT circle scan (768 thickness points). 10-2 indices including pointwise total deviation (TD) values, mean deviation (MD), and pattern standard deviation (PSD) were generated using the CNN-estimated sensitivity thresholds at individual test locations. Linear regression (LR) models with the same input were used for comparison. The CNNA model achieved an average pointwise mean absolute error of 4.04 dB (95% confidence interval [CI] 3.76-4.35) and correlation coefficient (r) of 0.59 (95% CI 0.52-0.64) over 10-2 map and the mean absolute error and r of 2.88 dB (95% CI 2.63-3.15) and 0.74 (95% CI 0.67-0.80) for MD, and 2.31 dB (95% CI 2.03-2.61) and 0.59 (95% CI 0.51-0.65) for PSD estimations, respectively, significantly outperforming the LRA model. The proposed CNNA model improved the estimation of 10-2 VF map based on circumpapillary SD-OCT RNFL thickness measurements. These artificial intelligence methods using SD-OCT structural data show promise to individualize the frequency of central VF assessment in patients with glaucoma and would enable the reallocation of resources from patients at lowest risk to those at highest risk of central VF damage.

Development of digital tools to enable remote ultrasonic inspection of fusion reactor in-vessel components

The feasibility of a new approach for pipe inspection has been explored using digital twins to enhance guided wave inspection. Guided wave inspection is well established in the oil & gas industry to remotely screen long lengths of predominately straight pipeline for corrosion. However, the inspection of complex pipe geometries remains a challenge. Nuclear fusion facilities are one such potential application. Fusion reactors have a network of many kilometres of service pipes with complex features, including multiple pipe bends. Some of these pipes could be used for actively cooling components such as the first wall and divertor. Guided ultrasonic wave inspection has the significant advantage of offering 100% coverage of the pipe wall over tens of metres of pipe from a remote test location. This is a highly attractive feature, particularly in the nuclear industry where it is important that human presence in high-risk areas is prohibited due to high radiation doses and temperatures. In this work, finite element wave propagation models have been investigated as digital twins of fusion reactor components. The models have been used to calculate bespoke excitation signals that will allow for full volumetric inspections of these complex pipes to be carried out from a remote location. For the first time, a digital twin technique has been developed that is predicted to successfully correct the distortion in guided wave signals caused by multiple pipe bends. The technique is predicted to yield an order of magnitude improvement in detection capability over conventional guided wave inspection. The digital twin technique presented here therefore shows significant promise for the future inspection of nuclear fusion power plant pipes.

Signature tracing of PCBs congeners in breastmilk of mothers living in selected urban centers of Pakistan

Polychlorinated biphenyls (PCBs) are banned toxic contaminants according to the Stockholm Convention of persistent pollutants (2001); however, they continue to be prevalent in the environment of Pakistan. The current study evaluates the risk to infants exposed to PCBs in breast milk from urban centers of Pakistan. The ∑14PCB concentrations ranged from ND to 118.36 ng/g lipid weight (l.w.) with a mean of 11.76. ± 4.88 ng/g l.w. These levels are greater than concentrations previously reported from Asia. The quantified PCB profile was also significantly (p < .05) related to the age of the mother while a negative correlation was observed with diet pattern (−0.26), fat content (−0.63), number of children (−0.185), and lactation (−0.19). There were significant differences among test locations with greater bioaccumulation observed in breast milk collected from urbanized Rawalpindi compared to less urbanized Jhang. The calculated estimated daily intakes of dioxin-like PCBs for infants were considerably higher than the recommended daily intake suggested by different organizations. The calculated hazard ratio (HR > 1) indicates health risks to infants in selected study regions.

Examining the effects of COVID-19 on pharmacy dispensing of naloxone and syringes sales across Massachusetts and New Hampshire

BackgroundCoronavirus disease 2019 (COVID-19) lockdowns disrupted access to harm reduction supplies and services known to be effective in overdose prevention and contributed to a worsening of the opioid crisis. However, because pharmacies can provide naloxone and sell over-the-counter (OTC) sterile syringes, their continued operation throughout the pandemic potentially reinforced a public health role as a distribution hub for safer use supplies. ObjectivesThe objective of this analysis was to examine patterns of naloxone and OTC syringe sale volume at 463 community pharmacies in 2 states with high overdose rates during the COVID-19 pandemic. MethodsWe analyzed weekly pharmacy-level dispensing data from January 5, 2020, to December 31, 2020, from one corporate community pharmacy chain in Massachusetts (n = 415 pharmacies) and New Hampshire (n = 48 pharmacies). Descriptive statistics and visualizations over the analytical period were generated as initial explorations of the outcome. Zero-inflated Poisson and negative binomial models were used to analyze distribution data along with county-level COVID-19 case rates and store-level COVID-19 testing location status during the same time. Interactions tested the effect of COVID-19 case rates on naloxone and OTC syringe sales. ResultsPharmacies that reported selling nonprescription syringes and dispensing naloxone during the study period averaged 210.13 OTC syringes sold and 0.53 naloxone prescriptions per week. Pharmacies in communities that experienced greater COVID-19 case burden also exhibited higher naloxone dispensing and OTC syringe sales during this period. The odds of selling OTC syringes increased over time but naloxone dispensing remained constant over the pandemic year. Pharmacies hosting COVID-19 testing tended to have lower OTC syringe sales and naloxone provision than nontesting sites. ConclusionDuring the COVID-19 pandemic, pharmacies provided harm reduction services and dispensed lifesaving medications by quickly adapting to fulfill community needs without disrupting co-located services for COVID-19 response.

Repeated measures of hypocretin-1 in Danish and Italian patients with narcolepsy and in controls

Study objectivesThe assay currently used worldwide to measure cerebrospinal fluid hypocretin-1 (CSF-hcrt-1) for diagnosing narcolepsy uses a competitive radioimmunoassay with polyclonal anti-hcrt-1 antibodies. This assay detects multiple hypocretin-1 immunoreactive species in the CSF that are all derived from full-length hcrt-1. We aimed to revalidate CSF-hcrt-1 cut-offs for narcolepsy type 1 (NT1) diagnosis and to evaluate temporal changes in CSF-hcrt-1 levels in patients suspected of having central hypersomnia. MethodWe carried out a repeat lumbar puncture with a mean follow-up of 4.0 years, to measure CSF-hcrt-1 in patients suspected of having central hypersomnia in a follow-up study. Data from CSF samples of patients with NT1 and of controls without known hypersomnia, from the Italian–Stanford and Danish populations, were examined using a receiver-operating characteristic analysis. ResultsThe optimal CSF-hcrt-1 cut-offs for identifying NT1 were 129 pg/ml and 179 pg/ml for the Italian-Stanford and Danish populations, respectively. The sensitivity was 0.93–0.99 and the specificity was 1.Follow-up lumbar puncture measurements of CSF-hcrt-1 were obtained from 73 patients. 30 of 32 patients with low CSF-hcrt-1 levels continued to be categorized as low, with an unaltered diagnosis; two patients showed a marked increase in CSF-hcrt-1, attaining normal values at follow-up. One of these patients relapsed to low CSF-hcrt-1 after follow-up. All 41 patients with normal CSF-hcrt-1 at baseline had normal CSF-hcrt-1 at follow-up. ConclusionCSF-hcrt-1 measurement can provide an accurate test for diagnosing NT1, although it is important to validate the CSF-hcrt-1 cut-off for specific testing locations. Stable CSF-hcrt-1 levels support the already established prognosis of narcolepsy as permanent once the disorder has fully developed.