First report of Cryptostroma corticale causing sooty bark disease in California and first worldwide report of silver maple as a host.

In November 2022 and February 2023, CAL FIRE tree health experts examined four maples (Acer spp.) planted decades earlier in a residential setting in Elk Grove, Sacramento Co., California (USA). Three of the trees were silver maples (Acer saccharinum ) and one was a Norway maple (A. platanoides); both species are exotic to California. The trees were in an irreversible state of decline, with the canopy substantially thinned and browning. Extensive bark cankers elongating longitudinally along the stem were visible on all trees (Fig. S1). Cankers were filled by fungal stromata protruding through the bark and producing masses of elliptical dark brown conidia (Fig. S2), approximately 5.5 x 3.7 um in size, giving the cankers a sooty appearance. The cankered bark could be peeled off easily, revealing dark and discrete lesions in the phloem and xylem. Samples from the three trees were shipped to the U.C. Berkeley Forest Pathology and Mycology Laboratory and to the CDFA PPDC in Sacramento, CA. In the laboratories, small wood chips were taken from the margins of the lesions, surface sterilized by dipping them for 30 seconds in 70% Ethanol, rinsed for 30 seconds in sterile water and plated onto 2.5% Malt Extract Agar amended with 0.3g/L Streptomycin or onto one-half strength acidified potato dextrose agar (APDA). Two morphologically identical cultures were obtained, one (T2) from a silver maple and one (T6) from the Norway maple. Cultures were then grown in liquid 2.5% malt extract broth and, after one week, DNA was extracted using the Qiagen Plant DNeasy DNA extraction kit. The ITS sequences are diagnostic for this fungus (Li et al. 2021) and those of the two cultures (GB OR064033 and OR933565) were 100% homologous to GenBank sequences of Cryptostroma corticale ( e.g. GB OP474010-11). The RPB2 sequence of T2 ( GB OR992132) was 100% homologous to that of C. corticale (GB HG934116.1). The isolate obtained from silver maple was inoculated in four potted silver maples by removing a bark disk 50 mm in diameter with a cork borer in three spots staggered at different heights and sides on the stem, placing a colonized agar plug of C. corticale in contact with the phloem, replacing the bark disk and wrapping with parafilm. Two control trees were mock inoculated using sterile agar plugs. Trees were in 57 L pots, had an average stem caliper of 2.7 cm, an average height of 3.5 m and were kept in a lath house at average high temperatures of 18-24 degrees C. After ten weeks, average lesion length was 15.4 cm (SE= 4.6) and 4.3 cm (SE=2.3) in the fungus-inoculated and control trees, respectively. An ANOVA test, nesting lesions sizes within tree, determined lesions lengths were different between inoculated and mock trees (P= 0.04). The fungus was reisolated from all points in all inoculated trees but never from control trees. C. corticale was first described in the UK from sycamore maple (Acer pseudoplatanus) (Gregory et al. 1949) and is an emerging problem in Europe (Muller et al. 2023). In North America, it has been reported from A. negundo, A. campestre, A. macrophyllum and Cornus nuttallii (Worral 2020), and it appears to be present in the Pacific Northwest (Brooks et al. 2023, Goree 1969). Norway maple is included in the European Plant Protection Organization list of hosts for C. corticale (EPPO 2023), however our finding of C. corticale on silver maple is a first report of this host worldwide and of this pathogen in California. This report is noteworthy, given that C. corticale is also a human pathogen infecting the respiratory system (Braun et al. 2021).

Assembly and analysis of the genome of Notholithocarpus densiflorus.

Tanoak (Notholithocarpus densiflorus) is an evergreen tree in the Fagaceae family found in California and southern Oregon. Historically, tanoak acorns were an important food source for Native American tribes and the bark was used extensively in the leather tanning process. Long considered a disjunct relictual element of the Asian stone oaks (Lithocarpus spp.), phylogenetic analysis has determined that the tanoak is an example of convergent evolution. Tanoaks are deeply divergent from oaks (Quercus) of the Pacific Northwest and comprise a new genus with a single species. These trees are highly susceptible to 'sudden oak death' (SOD), a plant pathogen (Phytophthora ramorum) that has caused widespread mortality of tanoaks. Here, we set out to assemble the genome and perform comparative studies among a number of individuals that demonstrated varying levels of susceptibility to SOD. First, we sequenced and de novo assembled a draft reference genome of N. densiflorus using co-barcoded library processing methods and an MGI DNBSEQ-G400 sequencer. To increase the contiguity of the final assembly, we also sequenced Oxford Nanopore (ONT) long reads to 30X coverage. To our knowledge, the draft genome reported here is one of the more contiguous and complete genomes of a tree species published to date, with a contig N50 of ∼1.2 Mb, a scaffold N50 of ∼2.1 Mb, and a complete gene score of 95.5% through BUSCO analysis. In addition, we sequenced 11 genetically distinct individuals and mapped these onto the draft reference genome enabling the discovery of almost 25 million single nucleotide polymorphisms and ∼4.4 million small insertions and deletions. Finally, using co-barcoded data we were able to generate complete haplotype coverage of all 11 genomes.

A multi-stage transfer learning strategy for diagnosing a class of rare laryngeal movement disorders.

BACKGROUND: It remains hard to directly apply deep learning-based methods to assist diagnosing essential tremor of voice (ETV) and abductor and adductor spasmodic dysphonia (ABSD and ADSD). One of the main challenges is that, as a class of rare laryngeal movement disorders (LMDs), there are limited available databases to be investigated. Another worthy explored research question is which above sub-disorder benefits most from diagnosis based on sustained phonations. The question is from the fact that sustained phonations can help detect pathological voice from healthy voice. METHOD: A transfer learning strategy is developed for LMD diagnosis with limited data, which consists of three fundamental parts. (1) An extra vocally healthy database from the International Dialects of English Archive (IDEA) is employed to pre-train a convolutional autoencoder. (2) The transferred proportion of the pre-trained encoder is explored. And its impact on LMD diagnosis is also evaluated, yielding a two-stage transfer model. (3) A third stage is designed following the initial two stages to embed information of pathological sustained phonation into the model. This stage verifies the different effects of applying sustained phonation on diagnosing the three sub-disorders, and helps boost the final diagnostic performance. RESULTS: The analysis in this study is based on clinician-labeled LMD data obtained from the Vanderbilt University Medical Center (VUMC). We find that diagnosing ETV shows sensitivity to sustained phonation within the current database. Meanwhile, the results show that the proposed multi-stage transfer learning strategy can produce (1) accuracy of 65.3% on classifying normal and other three sub-disorders all at once, (2) accuracy of 85.3% in differentiating normal, ABSD, and ETV, and (3) accuracy of 77.7% for normal, ADSD and ETV. These findings demonstrate the effectiveness of the proposed approach.

Using Momentary Assessment and Machine Learning to Identify Barriers to Self-management in Type 1 Diabetes: Observational Study.

BACKGROUND: For adolescents living with type 1 diabetes (T1D), completion of multiple daily self-management tasks, such as monitoring blood glucose and administering insulin, can be challenging because of psychosocial and contextual barriers. These barriers are hard to assess accurately and specifically by using traditional retrospective recall. Ecological momentary assessment (EMA) uses mobile technologies to assess the contexts, subjective experiences, and psychosocial processes that surround self-management decision-making in daily life. However, the rich data generated via EMA have not been frequently examined in T1D or integrated with machine learning analytic approaches. OBJECTIVE: The goal of this study is to develop a machine learning algorithm to predict the risk of missed self-management in young adults with T1D. To achieve this goal, we train and compare a number of machine learning models through a learned filtering architecture to explore the extent to which EMA data were associated with the completion of two self-management behaviors: mealtime self-monitoring of blood glucose (SMBG) and insulin administration. METHODS: We analyzed data from a randomized controlled pilot study using machine learning-based filtering architecture to investigate whether novel information related to contextual, psychosocial, and time-related factors (ie, time of day) relate to self-management. We combined EMA-collected contextual and insulin variables via the MyDay mobile app with Bluetooth blood glucose data to construct machine learning classifiers that predicted the 2 self-management behaviors of interest. RESULTS: With 1231 day-level SMBG frequency counts for 45 participants, demographic variables and time-related variables were able to predict whether daily SMBG was below the clinical threshold of 4 times a day. Using the 1869 data points derived from app-based EMA data of 31 participants, our learned filtering architecture method was able to infer nonadherence events with high accuracy and precision. Although the recall score is low, there is high confidence that the nonadherence events identified by the model are truly nonadherent. CONCLUSIONS: Combining EMA data with machine learning methods showed promise in the relationship with risk for nonadherence. The next steps include collecting larger data sets that would more effectively power a classifier that can be deployed to infer individual behavior. Improvements in individual self-management insights, behavioral risk predictions, enhanced clinical decision-making, and just-in-time patient support in diabetes could result from this type of approach.

Prioritization of Features for Mobile Apps for Families in a Federal Nutrition Program for Low-Income Women, Infants, and Children: User-Centered Design Approach.

BACKGROUND: The Special Supplemental Nutrition Assistance Program for Women, Infants, and Children (WIC) is a federal nutrition program that provides nutritious food, education, and health care referrals to low-income women, infants, and children up to the age of 5 years. Although WIC is associated with positive health outcomes for each participant category, modernization and efficiency are needed at the clinic and shopping levels to increase program satisfaction and participation rates. New technologies, such as electronic benefits transfer (EBT), online nutrition education, and mobile apps, can provide opportunities to improve the WIC experience for participants. OBJECTIVE: This formative study applies user-centered design principles to inform the layout and prioritization of features in mobile apps for low-income families participating in the WIC program. METHODS: To identify and prioritize desirable app features, caregivers (N=22) of the children enrolled in WIC participated in individual semistructured interviews with a card sorting activity. Interviews were transcribed verbatim and analyzed using constant comparative analysis for themes. App features were ranked and placed into natural groupings by each participant. The sum and average of the rankings were calculated to understand which features were prioritized by the users. Natural groupings of features were labeled according to participant descriptions. RESULTS: Natural groupings focused on the following categories: clinics/appointments, shopping/stores, education/assessments, location, and recipes/food. Themes from the interviews triangulated the results from the ranking activity. The priority app features were balance checking, an item scanner, and appointment scheduling. Other app features discussed and ranked included appointment reminders, nutrition training and quizzes, shopping lists, clinic and store locators, recipe gallery, produce calculator, and dietary preferences/allergies. CONCLUSIONS: This study demonstrates how a user-centered design process can aid the development of an app for low-income families participating in WIC to inform the effective design of the app features and user interface.

Integrating multiple blockchains to support distributed personal health records.

Blockchain technologies have evolved in recent years, as have the use of personal health record (PHR) data. Initially, only the financial domain benefited from Blockchain technologies. Due to efficient distribution format and data integrity security, however, these technologies have demonstrated potential in other areas, such as PHR data in the healthcare domain. Applying Blockchain to PHR data faces different challenges than applying it to financial transactions via crypto-currency. To propose and discuss an architectural model of a Blockchain platform named "OmniPHR Multi-Blockchain" to address key challenges associated with geographical distribution of PHR data. We analyzed the current literature to identify critical barriers faced when applying Blockchain technologies to distribute PHR data. We propose an architecture model and describe a prototype developed to evaluate and address these challenges. The OmniPHR Multi-Blockchain architecture yielded promising results for scenarios involving distributed PHR data. The project demonstrated a viable and beneficial alternative for processing geographically distributed PHR data with performance comparable with conventional methods. Blockchain's implementation tools have evolved, but the domain of healthcare still faces many challenges concerning distribution and interoperability. This study empirically demonstrates an alternative architecture that enables the distributed processing of PHR data via Blockchain technologies.

First reports of Phytophthora ramorum clonal lineages NA1 and EU1 causing Sudden Oak Death on tanoaks in Del Norte County, California.

A year of forest health surveys has led to the first detection of Phytophthora ramorum in Del Norte County followed by the first wildland detection of the EU1 clonal lineage (Grunwald et al. 2009) of this pathogen in California. In July 2019, leaves were sampled from two tanoaks (Notholithocarpus densiflorus) and 16 California bay laurels (Umbellularia californica) in Jedediah Smith State Park in Del Norte County, the northernmost coastal County of California. Leaves displayed lesions normally associated with Sudden Oak Death (SOD) caused by P. ramorum and were discovered during the citizen science-based survey known as SOD Blitz (Meentemeyer et al. 2015). Samples were surface sterilized using 75% Ethanol and plated on PARPH-V8 agar (Jeffers and Martin 1986). After plating, DNA was extracted and amplified using two P. ramorum-specific assays (Hayden et al. 2006, Kroon et al. 2004). Leaves from two tanoaks exhibiting twig die-back had typical SOD lesions along the midvein, gave positive PCR results and yielded cultures with colony morphology, sporangia and chlamydospores typical of the NA1 lineage of P. ramorum originally isolated in California from tanoaks and coast live oaks (Quercus agrifolia) (Rizzo et al. 2002). The ITS locus and a portion of the Cox-1 locus were sequenced from DNA extracts of each culture using primers DC6-ITS4 (Bonants et al. 2004) and COXF4N-COXR4N (Kroon et al. 2004), respectively. ITS sequences (GB MN540639-40) were typical of P. ramorum and Cox-1 sequences (GB MN540142-3) perfectly matched the Cox-1 sequence of the NA1 lineage (GB DQ832718) (Kroon et al. 2004). Microsatellite alleles were generated as described in Croucher et al. (2013) for the two Del Norte cultures and for eight P. ramorum cultures, representative of the four main multilocus genotypes (MLGs) present in California, namely c1 (Santa Cruz/Commercial Nurseries), c3 (San Francisco Bay Area), c2 (Monterey County), and c4 (Humboldt County) (Croucher et al. 2013). The two Del Norte MLGs were identical to one another and most similar to MLG c1, with a single repeat difference at a single locus. SSR results suggest the inoculum source may not be from Humboldt County, neighboring to the South, but from a yet unidentified outbreak, possibly associated with ornamental plants. Jedediah Smith State Park was surveyed for 12 months following the initial detection, however the pathogen has yet to be re-isolated in that location. In July 2020, SOD symptomatic leaves from two tanoak trees exhibiting twig cankers were collected 8 Km north of Jedediah Smith State Park, where three additional tanoak trees displayed rapidly browned dead canopies consistent with late stage SOD. Leaves were processed as above. Colonies from these samples produced chlamydospores and sporangia typical of P. ramorum on PARPH-V8 agar, but displayed a growth rate faster than that of NA1 genotypes and were characterized by aerial hyphae, overall resembling the morphology of EU1 lineage colonies (Brasier 2003). The EU1 lineage was confirmed by the perfect match of the sequence of a portion of the Cox-1 gene (GB MW349116-7) with the Cox-1 sequence of EU1 genotypes (GB EU124926). The EU1 clonal lineage has been previously isolated from tanoaks in Oregon forests, approximately 55 Km to the North (Grünwald et al. 2016), but this is the first report for California wildlands and will require containment and government regulations. It is unknown whether the EU1 strains in Del Norte County originated from Oregon forests or elsewhere.

A mobile app identifies momentary psychosocial and contextual factors related to mealtime self-management in adolescents with type 1 diabetes.

Effective diabetes problem solving requires identification of risk factors for inadequate mealtime self-management. Ecological momentary assessment was used to enhance identification of factors hypothesized to impact self-management. Adolescents with type 1 diabetes participated in a feasibility trial for a mobile app called MyDay. Meals, mealtime insulin, self-monitored blood glucose, and psychosocial and contextual data were obtained for 30 days. Using 1472 assessments, mixed-effects between-subjects analyses showed that social context, location, and mealtime were associated with missed self-monitored blood glucose. Stress, energy, mood, and fatigue were associated with missed insulin. Within-subjects analyses indicated that all factors were associated with both self-management tasks. Intraclass correlations showed within-subjects accounted for the majority of variance. The ecological momentary assessment method provided specific targets for improving self-management problem solving, phenotyping, or integration within just-in-time adaptive interventions.

Decoding phonation with artificial intelligence (DeP AI): Proof of concept.

OBJECTIVE: Acoustic analysis of voice has the potential to expedite detection and diagnosis of voice disorders. Applying an image-based, neural-network approach to analyzing the acoustic signal may be an effective means for detecting and differentially diagnosing voice disorders. The purpose of this study is to provide a proof-of-concept that embedded data within human phonation can be accurately and efficiently decoded with deep learning neural network analysis to differentiate between normal and disordered voices. METHODS: Acoustic recordings from 10 vocally-healthy speakers, as well as 70 patients with one of seven voice disorders (n = 10 per diagnosis), were acquired from a clinical database. Acoustic signals were converted into spectrograms and used to train a convolutional neural network developed with the Keras library. The network architecture was trained separately for each of the seven diagnostic categories. Binary classification tasks (ie, to classify normal vs. disordered) were performed for each of the seven diagnostic categories. All models were validated using the 10-fold cross-validation technique. RESULTS: Binary classification averaged accuracies ranged from 58% to 90%. Models were most accurate in their classification of adductor spasmodic dysphonia, unilateral vocal fold paralysis, vocal fold polyp, polypoid corditis, and recurrent respiratory papillomatosis. Despite a small sample size, these findings are consistent with previously published data utilizing deep neural networks for classification of voice disorders. CONCLUSION: Promising preliminary results support further study of deep neural networks for clinical detection and diagnosis of human voice disorders. Current models should be optimized with a larger sample size. LEVELS OF EVIDENCE: Level III.

Analyzing the performance of a blockchain-based personal health record implementation.

BACKGROUND: The Personal Health Record (PHR) and Electronic Health Record (EHR) play a key role in more efficient access to health records by health professionals and patients. It is hard, however, to obtain a unified view of health data that is distributed across different health providers. In particular, health records are commonly scattered in multiple places and are not integrated. OBJECTIVE: This article presents the implementation and evaluation of a PHR model that integrates distributed health records using blockchain technology and the openEHR interoperability standard. We thus follow OmniPHR architecture model, which describes an infrastructure that supports the implementation of a distributed and interoperable PHR. METHODS: Our method involves implementing a prototype and then evaluating the integration and performance of medical records from different production databases. In addition to evaluating the unified view of records, our evaluation criteria also focused on non-functional performance requirements, such as response time, CPU usage, memory occupation, disk, and network usage. RESULTS: We evaluated our model implementation using the data set of more than 40 thousand adult patients anonymized from two hospital databases. We tested the distribution and reintegration of the data to compose a single view of health records. Moreover, we profiled the model by evaluating a scenario with 10 superpeers and thousands of competing sessions transacting operations on health records simultaneously, resulting in an average response time below 500 ms. The blockchain implemented in our prototype achieved 98% availability. CONCLUSION: Our performance results indicated that data distributed via a blockchain could be recovered with low average response time and high availability in the scenarios we tested. Our study also demonstrated how OmniPHR model implementation can integrate distributed data into a unified view of health records.

FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data.

Secure and scalable data sharing is essential for collaborative clinical decision making. Conventional clinical data efforts are often siloed, however, which creates barriers to efficient information exchange and impedes effective treatment decision made for patients. This paper provides four contributions to the study of applying blockchain technology to clinical data sharing in the context of technical requirements defined in the "Shared Nationwide Interoperability Roadmap" from the Office of the National Coordinator for Health Information Technology (ONC). First, we analyze the ONC requirements and their implications for blockchain-based systems. Second, we present FHIRChain, which is a blockchain-based architecture designed to meet ONC requirements by encapsulating the HL7 Fast Healthcare Interoperability Resources (FHIR) standard for shared clinical data. Third, we demonstrate a FHIRChain-based decentralized app using digital health identities to authenticate participants in a case study of collaborative decision making for remote cancer care. Fourth, we highlight key lessons learned from our case study.

Mobile Momentary Assessment and Biobehavioral Feedback for Adolescents with Type 1 Diabetes: Feasibility and Engagement Patterns.

BACKGROUND: Integration of momentary contextual and psychosocial factors within self-management feedback may provide more specific, engaging, and personalized targets for problem solving. METHODS: Forty-four youth ages 13-19 with type 1 diabetes (T1D) were provided a Bluetooth meter and completed the 30-day protocol. Participants were randomized to "app + meter" or "meter-only" groups. App + meter participants completed mealtime and bedtime assessment each day. Assessments focused on psychosocial and contextual information relevant for self-management. Graphical feedback integrated self-monitored blood glucose (SMBG), insulin, and Bluetooth-transmitted blood glucose data with the psychosocial and contextual data. App + meter participants completed an interview to identify data patterns. RESULTS: The median number of momentary assessments per participant was 80.0 (range 32-120) with 2.60 per day. By 2 weeks participants had an average of 40.77 (SD 12.23) assessments. Dose-response analyses indicated that the number of app assessments submitted were significantly related to higher mean daily SMBG (r = -0.44, P < 0.05) and to lower% missed mealtime SMBG (r = -0.47, P < 0.01). Number of feedback viewing sessions was also significantly related to a lower% missed mealtime SMBG (r = -0.44, P < 0.05). Controlling for baseline variables, mixed-effects analyses did not indicate group × time differences in mean daily SMBG. Engagement analyses resulted in three trajectory groups distinguished by assessment frequencies and rates of decline. Engagement group membership was significantly related to gender, mean daily SMBG, and HbA1c values. CONCLUSIONS: Momentary assessment combined with device data provided a feasible means to provide novel personalized biobehavioral feedback for adolescents with T1D. A 2-week protocol provided sufficient data for self-management problem identification. In addition to feedback, more intensive intervention may need to be integrated for those patients with the lowest self-management at baseline.

A Smartphone App for Families With Preschool-Aged Children in a Public Nutrition Program: Prototype Development and Beta-Testing.

BACKGROUND: The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) in the United States provides free supplemental food and nutrition education to low-income mothers and children under age 5 years. Childhood obesity prevalence is higher among preschool children in the WIC program compared to other children, and WIC improves dietary quality among low-income children. The Children Eating Well (CHEW) smartphone app was developed in English and Spanish for WIC-participating families with preschool-aged children as a home-based intervention to reinforce WIC nutrition education and help prevent childhood obesity. OBJECTIVE: This paper describes the development and beta-testing of the CHEW smartphone app. The objective of beta-testing was to test the CHEW app prototype with target users, focusing on usage, usability, and perceived barriers and benefits of the app. METHODS: The goals of the CHEW app were to make the WIC shopping experience easier, maximize WIC benefit redemption, and improve parent snack feeding practices. The CHEW app prototype consisted of WIC Shopping Tools, including a barcode scanner and calculator tools for the cash value voucher for purchasing fruits and vegetables, and nutrition education focused on healthy snacks and beverages, including a Yummy Snack Gallery and Healthy Snacking Tips. Mothers of 63 black and Hispanic WIC-participating children ages 2 to 4 years tested the CHEW app prototype for 3 months and completed follow-up interviews. RESULTS: Study participants testing the app for 3 months used the app on average once a week for approximately 4 and a half minutes per session, although substantial variation was observed. Usage of specific features averaged at 1 to 2 times per month for shopping-related activities and 2 to 4 times per month for the snack gallery. Mothers classified as users rated the app's WIC Shopping Tools relatively high on usability and benefits, although variation in scores and qualitative feedback highlighted several barriers that need to be addressed. The Yummy Snack Gallery and Healthy Snacking Tips scored higher on usability than benefits, suggesting that the nutrition education components may have been appealing but too limited in scope and exposure. Qualitative feedback from mothers classified as non-users pointed to several important barriers that could preclude some WIC participants from using the app at all. CONCLUSIONS: The prototype study successfully demonstrated the feasibility of using the CHEW app prototype with mothers of WIC-enrolled black and Hispanic preschool-aged children, with moderate levels of app usage and moderate to high usability and benefits. Future versions with enhanced shopping tools and expanded nutrition content should be implemented in WIC clinics to evaluate adoption and behavioral outcomes. This study adds to the growing body of research focused on the application of technology-based interventions in the WIC program to promote program retention and childhood obesity prevention.

Respiratory and sleep effects of remifentanil in volunteers with moderate obstructive sleep apnea.

BACKGROUND: There is concern that opioid-based analgesia will worsen sleep-related respiratory insufficiency in patients with obstructive sleep apnea (OSA), resulting in serious morbidity or mortality. However, there are no studies that directly address the merit of this concern. Consequently, the authors designed this study as the first prospective, double-blind, placebo-controlled investigation of opioid pharmacology in patients with documented OSA. METHODS: Patients (n = 19) with moderate OSA documented by polysomnography (sleep study) were randomized to undergo an additional sleep study while receiving either a saline infusion or a remifentanil infusion (0.075 microg x kg x h). Sleep stages, apneas, hypopneas, and arterial hemoglobin oxygen saturation were continually recorded during saline or remifentanil infusion, and were compared with values obtained during the patients' earlier sleep study. RESULTS: Saline infusion had no effect on sleep or respiratory variables. In contrast, remifentanil increased Stage 1 sleep, markedly decreased rapid eye movement sleep, increased arousals from sleep, and decreased sleep efficiency. Remifentanil actually decreased the number of obstructive apneas, but markedly increased the number of central apneas. Arterial hemoglobin oxygen saturation was also significantly lower in OSA patients receiving remifentanil. CONCLUSIONS: The decrease in obstructive apneas likely resulted from the marked decrease in rapid eye movement sleep caused by remifentanil. Despite fewer obstructions, OSA was worse during remifentanil infusion because of a marked increase in the number of central apneas. These data suggest that caution is warranted when administering opioids to subjects with moderate OSA, but that the primary risk may be central apnea, not obstructive apnea.

Mecanismos associados à tolerância ao alumínio em plantas / Associated mechanisms of aluminum tolerance in plants

A toxicidade do alumínio é um dos principais fatores limitantes do desenvolvimento das plantas emsolos ácidos. Pelo fato da utilização de corretivos da acidez do solo não ser a estratégia mais viável emmuitas situações com solos ácidos (por razões técnicas e econômicas), o desenvolvimento de genótipostolerantes ao Al tem sido o caminho mais focado, assim a investigação dos mecanismos de tolerânciabem como as bases genéticas da tolerância ao Al têm merecido atenção especial pela pesquisa científica.Nos últimos anos, foi gerado um significativo progresso no entendimento das bases dos mecanismos detolerância ao Al, assim como no desenvolvimento de cultivares mais adaptados as condições de solosácidos. Os mecanismos de tolerância ao Al conhecidos se resumem basicamente em duas classes: os queagem no sentido de expulsar o Al depois de absorvido ou de impedir sua entrada pela raiz e os mecanismosde desintoxicação, complexando o Al em organelas específicas da planta, principalmente nos vacúolos.Em inúmeras espécies, mecanismos fisiológicos tem sido reportados como responsáveis pela ativaçãode ácidos orgânicos (principalmente citrato e malato) que atuam como agentes quelantes do Al, porémmuitos processos ainda não são bem entendidos e esclarecidos. Atualmente, se começa a entendermelhor um segundo mecanismo de tolerância ao Al que envolve a desintoxicação interna do Al atravésda complexação por ácidos orgânicos e o seqüestro destes complexos pelos vacúolos. Outros mecanismospotenciais são alvo de especulações e discussões.

Aluminum toxicity is one of the major limiting factor regarding plant development in acid soils. The use of liming for correcting soil pH is not viable for some of acid soil areas (technique or economic reasons),making the development of Al tolerant genotypes the best alternative. Thus, the tolerance mechanisms as well as the genetic basis of Al tolerance has deserved special attention in the scientific community. In the last years, a significant progress has been achieved towards these goals, as well as in developing cultivars adapted to acid soils. The Al tolerance mechanisms are divided basically in two classes: the exclusion mechanisms that act after absorption or blocking its entry in the root system and those involved in detoxification, complexing the Al in specific organelles, mainly in the vacuoles. In man yspecies, physiological mechanisms have been reported as responsible for the activation of organic acids(mainly citrate and malate) that act as Al quelating agents, however many process are not yet understood and cleared. Currently, the basis for the internal detoxification is becoming clear through organic acid complexes and there sequestering by the vacuoles. Other potential mechanisms are the target for discussions

Application of biocatalysis to drug metabolism: preparation of mammalian metabolites of a biaryl-bis-sulfonamide AMPA (alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid) receptor potentiator using Actinoplanes missouriensis.

LY451395 (2-propanesulfonamide, N-[(2R)-2-[4'-[2-[methylsulfonyl)amino]ethyl][1,1'-biphenyl]-4-yl]propyl]-) is a potent and highly selective potentiator of the alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptors. It is a biaryl-bis-sulfonamide and is known to be highly metabolized in preclinical species. In those metabolism studies, the metabolite structures were proposed exclusively by the analysis of mass spectrometric data. Although mass spectrometry is clearly a technique of choice for rapid identification of drug metabolites, occasionally, nuclear magnetic resonance spectroscopy is required to unambiguously assign and characterize, particularly, the regio- and stereochemistry of metabolic changes. Nuclear magnetic resonance spectroscopy, in general, is less sensitive than other detection methods and demands several micrograms of material for the analysis. To support full structure characterization of metabolites by NMR, in this study we demonstrated the application of a microbial-based surrogate biocatalytic system to produce sufficient amounts of the mammalian metabolites of LY451395. The results revealed that incubation of LY451395 with Actinoplanes missouriensis NRRL B3342 generated several metabolites that were previously detected in the in vivo metabolism studies of the preclinical species. Subsequent large-scale bioconversion resulted in the isolation of seven mammalian metabolites in milligram quantities for structural characterization by nuclear magnetic resonance spectroscopy. Furthermore, a selected group of metabolites generated from the microbial conversion served as analytical standards to monitor and quantify drug metabolites during clinical investigations.

Heranca da resistência à ferrugem da folha da aveia (Puccinia coronata f. sp. avenae Fraser & Led.) em genótipos brasileiros de aveia branca / Inheritance of oat leaf rust (Puccinia coronata f. sp. avenae Fraser & Led.) resistance in white oat brazilian genotypes

A ferrugem da folha da aveia é a moléstia mais importante que ataca a cultura da aveia, ocorrendo em praticamente todas as áreas em que a aveia é cultivada. A forma mais indicada para o seu controle é a utilizacão de cultivares resistentes. Contudo, para que seja alcancada a resistência durável ao patógeno, é necessário que se conheca a genética da resistência à ferrugem da folha em aveia. O objetivo foi determinar a forma de heranca da resistência a três isolados de Puccinia coronata f. sp. avenae Fraser & Led., (coletados no sul do Brasil) em genótipos brasileiros de aveia branca. Para a determinacão da heranca da resistência a cada um dos três isolados, foram utilizadas populacões F2 geradas por meio de cruzamentos artificiais, entre genótipos resistentes (R) e suscetíveis (S) e entre genótipos resistentes (R). Desta forma, foram utilizadas populacões F2 dos cruzamentos artificiais entre: i) URPEL 15 (R) x UFRGS 7 (S), UPF 16 (R) x UFRGS 7 (S) e URPEL 15 (R) x UPF 16 (R), para a determinacão da heranca da resistência ao isolado um (1); ii) URPEL 15 (R) x UFRGS 7 (S), UPF 18 (R) x UFRGS 7 (S) e URPEL 15 (R) x UPF 18 (R), para a determinacão da heranca da resistência ao isolado dois (2); iii) URPEL 15 (R) x UFRGS 7 (S) e URPEL 15 (R) x UPF 18 (S), para a determinacão da heranca da resistência ao isolado três (3). Os resultados obtidos evidenciaram que o genótipo URPEL 15 apresenta genes dominantes de resistência aos três isolados de ferrugem da folha da aveia avaliados, que o cultivar UPF 16 apresenta um gene recessivo de resistência ao isolado 1 e o cultivar UPF 18 apresenta um gene recessivo de resistência ao isolado 2. E que os genes de resistência apresentados pelos genótipos URPEL 15, UPF 16 e UPF 18, segregam de forma independente.

Estimativas de correlações genotípicas e de ambiente em gerações com elevada freqüência de heterozigotos / Genotypic and enviromental correlation estimates with high heterozygous frequency

A correlação genotípica permite avaliar a magnitude e a direção da associação entre caracteres, sendo de grande utilidade por permitir a viabilidade do emprego da seleção indireta, que em alguns casos, pode levar a progressos genéticos mais rápidos e altamente expressivos em programas de melhoramento de aveia (Avena sativa L.). O objetivo deste trabalho foi avaliar a viabilidade da implementação de uma modificação na fórmula de PETR & FREY (1966), para a obtenção de estimativas de correlação genotípica, fenotípica e de ambiente, através da análise de quatro populações segregantes F2 de aveia: OR 2 x UPF 18, UPF 7 x CTC 5, OR 2 x UPF 7, UPF 18 x CTC 5. As estimativas de correlação genotípica indicam que a seleção de plantas de alta produtividade de grãos pode ser realizada indiretamente através dos caracteres número de panículas por planta, peso de panícula, número de grãos por panícula e peso médio de grãos. Entretanto, as diferenças em magnitude e direção das estimativas de correlações, entre os vários pares de caracteres, nas quatro populações estudadas, não permitem a generalização de uma estratégia de seleção, isto devido as limitações impostas pelas diferenças entre as constituições genéticas dos genitores e populações. Desta forma, é de fundamental importância a avaliação da capacidade combinatória das principais constituições genéticas utilizadas em cruzamentos artificiais, a fim de se estabelecer critérios mais efetivos a serem empregados na seleção de genótipos superiores.