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Modern experimental technologies can assay large numbers of biological sequences, but engineered protein libraries rarely exceed the sequence diversity of natural protein families. Machine learning (ML) models trained directly on experimental data without biophysical modeling provide one route to accessing the full potential diversity of engineered proteins. Here we apply deep learning to design highly diverse adeno-associated virus 2 (AAV2) capsid protein variants that remain viable for packaging of a DNA payload. Focusing on a 28-amino acid segment, we generated 201,426 variants of the AAV2 wild-type (WT) sequence yielding 110,689 viable engineered capsids, 57,348 of which surpass the average diversity of natural AAV serotype sequences, with 12–29 mutations across this region. Even when trained on limited data, deep neural network models accurately predict capsid viability across diverse variants. This approach unlocks vast areas of functional but previously unreachable sequence space, with many potential applications for the generation of improved viral vectors and protein therapeutics. Viable AAV capsids are designed with a machine learning approach.

AIMWe aimed to document current clinical practice and needs in screening for visual perception problems after stroke to inform development of new screening tools.METHODSWe interviewed 25 health care professionals (12 occupational therapists, 13 orthoptists) from 16 organisations in England. Interviews were transcribed and coded in NVivo Software. Data were thematically analysed using the Value Proposition Canvas, a model which establishes what people want to achieve, the challenges they face and what facilitates their jobs.RESULTSParticipants’ understanding of visual perception varied and often included sensory and cognitive deficits. Occupational therapists commonly screened for visual field deficits and hemispatial neglect, while other aspects of visual cognition were rarely assessed. They decided on referrals to orthoptists for further assessment. Screening generally occurred during functional assessments and/or with in-house developed tools. Challenges to practice were: lack of time, lack of training, environmental and stroke survivor factors (e.g. aphasia), insufficient continuation of care, and test characteristics (e.g. not evidence-based). Facilitators to practice were: quick and practical tools, experienced staff or tools with minimal training requirements, a streamlined care pathway between a stroke unit and eye hospital supported by occupational therapists and orthoptists.CONCLUSIONScreening employs non-standardised assessments and rarely covers visual perceptual deficits in higher order perception. Our service evaluation demonstrates the need for a standardised visual perception screen, which should ideally be 15 minutes or less, be portable, and require minimal equipment. The screen should be suitable for bedside testing in noisy environments, inclusive for participants with aphasia and evidence-based.

Predicting the function of a protein from its amino acid sequence is a long-standing challenge in bioinformatics. Traditional approaches use sequence alignment to compare a query sequence either to thousands of models of protein families or to large databases of individual protein sequences. Here we instead employ deep convolutional neural networks to directly predict a variety of protein functions – EC numbers and GO terms – directly from an unaligned amino acid sequence. This approach provides precise predictions which complement alignment-based methods, and the computational efficiency of a single neural network permits novel and lightweight software interfaces, which we demonstrate with an in-browser graphical interface for protein function prediction in which all computation is performed on the user’s personal computer with no data uploaded to remote servers. Moreover, these models place full-length amino acid sequences into a generalised functional space, facilitating downstream analysis and interpretation. To read the interactive version of this paper, please visit https://google-research.github.io/proteinfer/Abstract FigureQR code for the interactive version of this preprint at https://google-research.github.io/proteinfer/

PURPOSE Visual perceptual deficits are frequently underdiagnosed in stroke survivors compared to sensory vision deficits or visual neglect. To better understand this imparity, we evaluated current practice for screening post-stroke visual perceptual deficits. METHODS We conducted a survey targeted at professionals working with stroke survivors involved in screening visual perceptual deficits across the United Kingdom and the Republic of Ireland. RESULTS Forty orthoptists and 174 occupational therapists responded to the survey. Visual perceptual deficit screening was primarily conducted by occupational therapists (94%), with 75∼100% of stroke survivors screened per month. Respondents lacked consensus on whether several common post-stroke visual deficits were perceptual or not. During the screening, respondents primarily relied on self-reports and observation (94%), while assessment batteries (58%) and screening tools were underutilised (56%) and selected inappropriately (66%). Respondents reported lack of training in visual perception screening (20%) and physical/cognitive condition of stroke survivors (19%) as extremely challenging during screening. CONCLUSIONS Visual perceptual deficits are screened post-stroke at a similar rate to sensory vision or visual neglect. Underdiagnosis of visual perceptual deficits may stem from both reliance on subjective and non-standardised screening approaches, and conflicting definitions of visual perception held among clinicians. We recommend increased training provision and use of brief performance-based screening tools.IMPLICATIONS FOR REHABILITATIONLack of agreement among clinicians on what constitutes as visual perceptual or sensory vision deficits may prove problematic, as precise and exact language is often required for clinical decision-making (e.g., referrals).Biases for more familiar visual (perceptual) deficits held among clinicians during the screening process may lead to other visual deficits being missed.To avoid problems being missed, clinicians should aim to use standardised assessments rather than stroke survivor self-report and observations of function when screening for visual perceptual difficulties.

Recent work demonstrated a large ensemble of convolutional neural networks (CNNs) outperforms industry-standard approaches at annotating protein sequences that are far from the training data. These results highlight the potential of deep learning to significantly advance protein sequence annotation, but this particular system is not a practical tool for many biologists because of the computational burden of making predictions using a large ensemble. In this work, we fine-tune a transformer model that is pre-trained on millions of unlabeled natural protein sequences in order to reduce the system's compute burden at prediction time and improve accuracy. By switching from a CNN to the pre-trained transformer, we lift performance from 73.6% to 90.5% using a single model on a challenging clustering-based train-test split, where the ensemble of 59 CNNs achieved 89.0%. Through extensive stratified analysis of model performance, we provide evidence that the new model's predictions are trustworthy, even in cases known to be challenging for prior methods. Finally, we provide a case study of the biological insight enabled by this approach.

BackgroundArthrospira platensis (commonly known as spirulina) is a promising new platform for low-cost manufacturing of biopharmaceuticals. However, full realization of the platform’s potential will depend on achieving both high growth rates of spirulina and high expression of therapeutic proteins.ObjectiveWe aimed to optimize culture conditions for the spirulina-based production of therapeutic proteins.MethodsWe used a machine learning approach called Bayesian black-box optimization to iteratively guide experiments in 96 photobioreactors that explored the relationship between production outcomes and 17 environmental variables such as pH, temperature, and light intensity.ResultsOver 16 rounds of experiments, we identified key variable adjustments that approximately doubled spirulina-based production of heterologous proteins, improving volumetric productivity between 70% to 100% in multiple bioreactor setting configurations.ConclusionAn adaptive, machine learning-based approach to optimize heterologous protein production can improve outcomes based on complex, multivariate experiments, identifying beneficial variable combinations and adjustments that might not otherwise be discoverable within high-dimensional data.

In many application domains, neural networks are highly accurate and have been deployed at large scale. However, users often do not have good tools for understanding how these models arrive at their predictions. This has hindered adoption in fields such as the life and medical sciences, where researchers require that models base their decisions on underlying biological phenomena rather than peculiarities of the dataset introduced. In response, we propose a set of methods for critiquing deep learning models and demonstrate their application for protein family classification, a task for which high-accuracy models have considerable potential impact. Our methods extend the sufficient input subsets technique, which we use to identify subsets of features (SIS) in each protein sequence that are alone sufficient for classification. Our suite of tools analyzes these subsets to shed light on the decision-making criteria employed by models trained on this task. These tools expose that while deep models may perform classification for biologically-relevant reasons, their behavior varies considerably across choice of network architecture and parameter initialization. While the techniques that we develop are specific to the protein sequence classification task, the approach taken generalizes to a broad set of scientific contexts in which model interpretability is essential.

It is important for foster caregivers to understand children's basic and psychological needs in order to provide better life experiences, and minimize the risk and vulnerability they previously experienced. Thus, this study is designed to understand clothing selection motivations and the meaning of possessions for foster tweens and how these are related to their life experiences in foster care group homes. We conducted qualitative in-depth focus group interviews with 18 tweens in a foster care group home in the Southwest region in the U.S. Thematic interpretation was used to analyze the interview data. Six themes emerged from the data including social acceptance, self-expression, family connection, independence, ownership, and respect. Participants expressed their individual character by the clothing they chose and expressed various needs of self-expression and social interaction. We also found that clothing and possessions play an important role in giving meanings to social interactions for tweens in the foster home. Furthermore, the findings of this study emphasize the need for proper education of foster care parents and tweens regarding ownership of property and respect in a foster care group home.

Data driven computational approaches to predicting protein-ligand binding are currently achieving unprecedented levels of accuracy on held-out test datasets. Up until now, however, this has not led to corresponding breakthroughs in our ability to design novel ligands for protein targets of interest. This review summarizes the current state of the art in this field, emphasizing the recent development of deep neural networks for predicting protein-ligand binding. We explain the major technical challenges that have caused difficulty with predicting novel ligands, including the problems of sampling noise and the challenge of using benchmark datasets that are sufficiently unbiased that they allow the model to extrapolate to new regimes.

Deep neural networks have achieved state-of-the-art accuracy at classifying molecules with respect to whether they bind to specific protein targets. A key breakthrough would occur if these models could reveal the fragment pharmacophores that are causally involved in binding. Extracting chemical details of binding from the networks could enable scientific discoveries about the mechanisms of drug actions. However, doing so requires shining light into the black box that is the trained neural network model, a task that has proved difficult across many domains. Here we show how the binding mechanism learned by deep neural network models can be interrogated, using a recently described attribution method. We first work with carefully constructed synthetic datasets, in which the molecular features responsible for “binding” are fully known. We find that networks that achieve perfect accuracy on held-out test datasets still learn spurious correlations, and we are able to exploit this nonrobustness to construct adversarial examples that fool the model. This makes these models unreliable for accurately revealing information about the mechanisms of protein–ligand binding. In light of our findings, we prescribe a test that checks whether a hypothesized mechanism can be learned. If the test fails, it indicates that the model must be simplified or regularized and/or that the training dataset requires augmentation.

The Kuiper Belt is a distant region of the Solar System. On 1 January 2019, the New Horizons spacecraft flew close to (486958) 2014 MU69, a Cold Classical Kuiper Belt Object, a class of objects that have never been heated by the Sun and are therefore well preserved since their formation. Here we describe initial results from these encounter observations. MU69 is a bi-lobed contact binary with a flattened shape, discrete geological units, and noticeable albedo heterogeneity. However, there is little surface color and compositional heterogeneity. No evidence for satellites, ring or dust structures, gas coma, or solar wind interactions was detected. By origin MU69 appears consistent with pebble cloud collapse followed by a low velocity merger of its two lobes., 43 pages, 8 figure

Understanding the relationship between amino acid sequence and protein function is a long-standing problem in molecular biology with far-reaching scientific implications. Despite six decades of progress, state-of-the-art techniques cannot annotate 1/3 of microbial protein sequences, hampering our ability to exploit sequences collected from diverse organisms. In this paper, we explore an alternative methodology based on deep learning that learns the relationship between unaligned amino acid sequences and their functional annotations across all 17929 families of the Pfam database. Using the Pfam seed sequences we establish rigorous benchmark assessments that use both random and clustered data splits to control for potentially confounding sequence similarities between train and test sequences. Using Pfam full, we report convolutional networks that are significantly more accurate and computationally efficient than BLASTp, while learning sequence features such as structural disorder and transmembrane helices. Our model co-locates sequences from unseen families in embedding space, allowing sequences from novel families to be accurately annotated. These results suggest deep learning models will be a core component of future protein function prediction tools.

Young children create spaces to claim as their own within their larger environments. Some spaces serve social and play functions, while others may offer a sense of security and safety, as suggested by prospect–refuge theory (Appleton, J. (1975). The experience of landscape. New York: John Wiley and Sons). Although we know that children create secret spaces for themselves, less is known about how children construct these spaces. This study used focus groups to learn what materials preschoolers would like to create spaces within their classrooms. Then, children were given the materials and provided time to create spaces. Results showed that children preferred flexible materials (e.g., blankets, bed sheets, cardboard tubes), worked collaboratively to create their spaces, and that the spaces provided refuge for the children. Implications for children's social development, classroom environment, and early childhood education are discussed.

Objectives: To examine the magnitude of impact of two nature-themed window murals on physiological processes, as measured by heart rate and blood pressure, of pediatric patients. Background: Many children and adolescents find at least one aspect of the hospitalization process frightening or anxiety provoking. One physical feature linked to stress reduction is access to positive distractions. Views of nature are one of the most common forms of positive distractions in healthcare environments. Patient room windows are the most common way patients are exposed to natural elements. Exposure to views of nature is linked to a number of positive impacts on physiological outcomes. Unfortunately, not every patient room will be able to provide a nature-filled window view. In situations where nature scenes do not occur, enhanced nature views may be utilized to replicate many of the same benefits as actual nature views. Methods: Pediatric patients were randomly assigned to one of the three room conditions: aquatic window mural, tree window mural, or control condition. The medical data of participants ( n = 90) who stayed in the rooms were gathered and evaluated for differences. Results: Data analysis supports the notion that patient stress is heightened at the time of admission. Patients in the rooms with murals were found to have improvements in heart rate and systolic blood pressure in comparison to patients in control rooms, suggesting that the murals had an impact on physiological processes. Data also suggest that subject matter played a role, as patients in tree murals rooms had the most health-related outcomes.

Few interventions have been shown to be successful in reducing child obesity, due in part to the challenges in reaching parents. Web-based nutrition intervention is becoming more feasible due to technology advancements and accessibility across income groups. However, studies on the effectiveness and acceptability of web-based interventions to teach parents about healthy behaviors are needed. The purpose of this study was to evaluate the Jump2Health™ Website intervention using qualitative interview methodology. A follow-up phone interview was conducted with 13 participants, approximately 1-to 2-month-postintervention. Participants reported making desired behavior changes in targeted areas and also considered the Website an effective learning method.

Background Hyperglycemia leading to increased oxidative stress is implicated in the increased risk for the development of macrovascular and microvascular complications in patients with type 1 diabetes mellitus. Methods and Results A random subcohort of 349 participants was selected from the DCCT / EDIC (Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications) cohort. This included 320 controls and 29 cardiovascular disease cases that were augmented with 98 additional known cases to yield a case cohort of 447 participants (320 controls, 127 cases). Biosamples from DCCT baseline, year 1, and closeout of DCCT , and 1 to 2 years post‐ DCCT ( EDIC years 1 and 2) were measured for markers of oxidative stress, including plasma myeloperoxidase, paraoxonase activity, urinary F 2α isoprostanes, and its metabolite, 2,3 dinor‐8 iso prostaglandin F 2α . Following adjustment for glycated hemoblobin and weighting the observations inversely proportional to the sampling selection probabilities, higher paraoxonase activity, reflective of antioxidant activity, and 2,3 dinor‐8 iso prostaglandin F 2α , an oxidative marker, were significantly associated with lower risk of cardiovascular disease (−4.5% risk for 10% higher paraoxonase, P iso prostaglandin F 2α , P =0.0092). In contrast, the oxidative markers myeloperoxidase and F 2α isoprostanes were not significantly associated with cardiovascular disease after adjustment for glycated hemoblobin. There were no significant differences between DCCT intensive and conventional treatment groups in the change in all biomarkers across time segments. Conclusions Heightened antioxidant activity (rather than diminished oxidative stress markers) is associated with lower cardiovascular disease risk in type 1 diabetes mellitus, but these biomarkers did not change over time with intensification of glycemic control. Clinical Trial Registration URL : https://www.clinicaltrials.gov . Unique identifiers: NCT 00360815 and NCT 00360893.

In this qualitative study, interviews about children's secret hiding places were conducted with 3–5-year-olds (n = 17) in a university sponsored preschool programme using art narratives. Since prior studies indicate that children understand the concept of a secret as early as five and that they associate secrets with hiding places, the purpose of this study was to look specifically at preschool children's experiences within their secret spaces. Analyses using interpretive phenomenology indicated that preschool children view secret hiding places with a sense of complexity, and they reserve certain areas as off limits to everyone, even in terms of the knowledge that these places exist. Consistent with a sociocultural framework, hiding places appear to serve individual, relational, and collaborative purposes, and children show heightened agency when deciding the function of a particular place. Children also relate secrets with secret hiding places and describe both with excitement, imagination, and intimacy....

Rapid determination of whether a candidate compound will bind to a particular target receptor remains a stumbling block in drug discovery. We use an approach inspired by random matrix theory to decompose the known ligand set of a target in terms of orthogonal "signals" of salient chemical features, and distinguish these from the much larger set of ligand chemical features that are not relevant for binding to that particular target receptor. After removing the noise caused by finite sampling, we show that the similarity of an unknown ligand to the remaining, cleaned chemical features is a robust predictor of ligand-target affinity, performing as well or better than any algorithm in the published literature. We interpret our algorithm as deriving a model for the binding energy between a target receptor and the set of known ligands, where the underlying binding energy model is related to the classic Ising model in statistical physics.

As clothing is a tool to express oneself and considered as an extended self to show one’s identity (Ahuvia, 2005), understanding the meaning of possessions related to clothing for children in the foster care homes can help us develop and provide necessary products or programs. Therefore, this study is designed to understand clothing selection motivations and the meaning of possessions for children in foster care homes.

Effects of an irritable bowel syndrome educational class on health-promoting behaviors and symptoms

PACECRAFT exposed to dynamic fluctuations in temperature, velocity, and gravity present significant challenges for a high-precision timekeeping system. En route to Mercury, the MESSENGER spacecraft has endured a total of six planetary flybys, considerable variation in proximity to the Sun, and large velocity gradients. The probe completed 15 solar revolutions during the heliocentric cruise phase, with a minimum perihelion distance of 0.302 AU and a maximum aphelion distance of 1.07 AU. Its environment changed once again when the spacecraft was captured in the gravity well of Mercury and the planetary orbital phase of the mission began. The accuracy goal of the timekeeping system is to maintain ground knowledge of the spacecraft clock to within 100 ms. This paper summarizes MESSENGER’s complex timekeeping system and the steps that have been taken to address the mission’s unique challenges. I. Introduction The MErcury, Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft, now in orbit about Mercury, uses two types of onboard oscillators: an oven-controlled crystal oscillator (OCXO) for precision timekeeping as well as an internal, coarse oscillator. Nominally, both oscillators run simultaneously, giving the mission operations team the option to select either. During certain operations, such as maneuvers that require the firing of thrusters, it is preferable to select the coarse oscillator. This precaution decreases the probability that spacecraft vibrations will trigger an anomaly with the OCXO that could potentially result in a reboot of the main processor (MP). For the majority of the mission, however, it is desirable to select the OCXO. The selected oscillator drives the clock that increments the mission elapsed time (MET), which provides a common frame of reference on which to base all events for the life of the mission. When commands are sequenced, they are executed at an assigned MET, and all information coming from the spacecraft is time-stamped with this MET. The unit of measurement for the MET is seconds, counted in terrestrial dynamical time (TDT). The formula for calculating TDT is expressed numerically as TDT = UTC + 32.184 s + (leap seconds).¹ For the ground-system component of MESSENGER’s timekeeping system, the mission operations team generates spacecraft clock data files called spacecraft clock (SCLK) kernels. One SCLK kernel is generated from each Deep Space Network support during which contact is established with the spacecraft. Telemetry and predictive ephemeris data are used to interpolate the clock drift rate and to create a linear formula to convert MET to TDT. This linear formula consists of a MET/TDT intercept and the drift rate of the oscillator (TDTRATE). These parameters are loaded to the spacecraft to support onboard calculations of TDT from MET. The spacecraft uses TDT knowledge to derive position from the onboard ephemerides. The guidance-and-control subsystem utilizes these position states to orient the spacecraft relative to Earth, the Sun, and other heavenly bodies. The SCLK kernels are also used to support ground system operations, converting time tags of telemetry data, supporting commandsequencing operations, and evaluating the performance of onboard TDT knowledge. While analyzing timekeeping data through the planetary flybys, the mission operations team observed unpredicted trends in the clock drift-rate data. These trends showed a divergence from the nominally expected drift rate. The unusual drift-rate behavior caused a greater-than-expected error in the onboard TDT knowledge, although the calculated error was still within the specified requirements. Analysis by the MESSENGER team determined that

The aims of this study were to investigate a group of patients with achalasia prospectively to determine (1) the relationship between changes in symptoms and esophageal motor function in response to pneumatic dilation and (2) the effects of the balloon size as well as the frequency and duration of inflation on the outcome of treatment. Fourteen patients with achalasia who were symptomatic for a median duration of 27 months participated in the study. The patients were randomized to one combination of the following pneumatic dilation conditions: a 30- or 35-mm balloon dilator, one or two balloon inflations, and 20, 40, or 60 seconds per balloon inflation. A comprehensive assessment of their symptoms and esophageal motility, transit, and diameter were performed before and 3 months after pneumatic dilation. Pneumatic dilation provided significant relief of dysphagia (P0.01), but other symptoms (heartburn, regurgitation, and chest pain) remained unchanged. Pneumatic dilation also caused a significant decrease in lower esophageal sphincter pressure and esophageal diameter and improved esophageal emptying of a solid bolus. Nevertheless, no significant association was detected between changes in the symptom score for dysphagia and changes in objective response measures as a result of pneumatic dilation. Changes in the symptom score for dysphagia or objective responses were similar regardless of the size of the dilator used or the frequency and duration of the balloon inflations.(ABSTRACT TRUNCATED AT 250 WORDS)

Objective: We aimed to determine whether psychiatric disorders and psychological symptoms are associated with the irritable bowel syndrome, and whether childhood sexual abuse is reported more often by patients with irritable bowel syndrome, as these issues continue to be controversial. Design: Prospectively, 32 symptomatic married outpatients with irritable bowel syndrome completed selected portions of the Structured Clinical Interview for DSM-III-R psychiatric diagnoses, a standardized interview for childhood abuse, and a series of self-report psychological symptom inventories. Controls comprised 20 currently symptomatic married outpatients who had undergone a partial colectomy or ileectomy for organic disease, the spouses of the patients with irritable bowel syndrome, and the spouses of the organic disease controls

In the past Science Planning for space missions has been comprised of using ad-hoc software toolscollected or reconstructed from previous missions, tools used by other groups who often speak a different 'technical' language or even 'the backs of envelopes'. In addition to the tools being rough, the work done with these tools often has had to be redone or at least re-entered when it came time to determine actual observations. Science Opportunity Analyzer (SOA), a Java-based application, has been built for scientists to enable them to identify/analyze observation opportunities and then, to create corresponding observation designs.

The Science Opportunity Analyzer, SOA, now in its third year of development, is intended to meet the need of adaptability to the various mission types at JPL and portability for the user community.

Union Gas, like many of the natural gas companies across Canada, has seen significant expansion of it’s compression and pipeline facilities in the past few years. Much of this expansion has been dedicated to the gas storage and transmission needs of the Eastern Canadian and American markets. With the capital costs of these facilities continually on the rise it is critical to ensure that each facility will yield maximum utility to the system for the proposed investment. Union Gas has a unique position within the Canadian gas industry as not only a major distribution company but also an operator of over 120 BCF of underground gas storage and a transmission pipeline system which is an integral part of the transCanadian gas supply infrastructure. Union’s transmission and storage system provides a vital link between the TransCanada PipeLines transmission system running through Northern Ontario and Central Michigan and several delivery points into the Northeastern United States and Eastern Canada. The diverse nature of Union’s operating facilities dictate a system with two distinctively different modes of compression during the winter operating season. These modes being storage withdrawal, which is typically a high head low flow operation and pipeline transmission which is a low head high flow operation. Each of these modes require specific compressor performance designs which do not typically display the flexibility to be utilized in either mode. With system demands consistently on the increase it can be very difficult to maintain adequate backup in the event of a compressor plant outage; this is particularly evident’ when considering the different operating requirements at various locations in the system. In an effort to maximize the operational flexibility of a new facility, Union Gas has implemented a new design consisting of a triple case compressor train driven off a single engine gas turbine package. With the external unit piping configured for both series and parallel operation this new design can effectively duplicate all possible modes of operation in Union’s present operating system, for both storage withdrawal and pipeline transmission. This paper will discuss the extent of operational flexibility this system can offer and the various design concerns associated with this type of compression plant facility.

An attempt was made to observe the phonon wave vector dependence of the 1-LO resonant Raman effect by comparing forward and back scattered intensities from CdS at room temperature. There was no intensity dependence on the scattering wave vector. We have also measured the absolute Raman efficiency and compared it with the result of a calculation assuming bound excitons as intermediate states.

Studies on the prevalence and etiology of splenomegaly were accomplished at three hamlets of a geographically remote village in South Vietnam. The percent of children and adolescents with enlarged spleen ranged from 70 to 90. Single or mixed malaria infections were demonstrated in 19 of 42 splenomegalic children. The results indicated that malaria infections were the primary cause for splenomegaly in those examined, although the beta-thalassemia trait was not excluded as a contributory factor.

The purpose of this study was to evalute the antimalarial action of a new tetracycline analogue, minocycline, which is more potent and has a broader antibacterial spectrum than tetracycline. The study was conducted in an area endemic for chloroquine-resistant falciparum malaria. Acutely ill residents infected with P. falciparum were alternately assigned to one of two treatment groups. Subjects in one group were given 540 mg of quinine base, thrice daily for 3 days followed by 100 mg of minocycline, twice daily for 7 days. Subjects in the other group were given a similar course of quinine followed by 250 mg of tetracycline, 4 times daily for 10 days. Presumptive radical cures were achieved in all 29 patients treated with quinine-tetracycline and in 27 of 28 treated with quinine-minocycline. No significant toxic side-effects were observed. Although both treatments were highly effective, further studies are warranted to determine the optimal duration and dosage of minocycline and its potential human toxicity.

This paper addresses the development of a practical method to predict fuel stability, which is faster and as reliable as existing methods. The new test applies a technique known as Pressure Differential Scanning Calorimetry (Pressure-DSC) and appears advantageous in several respects: 1. It relates reaction enthalpy, in a novel approach, to fuel stability. 2. The test can be completed within 24 hours. 3. Small amounts of fuel suffice for a complete test (less than or equal to100 mg). 4. It should be possible to develop a highly automated, micro-processor controlled tester.

Using a YAG laser operating at 2.1 µm, polarized Raman spectra of Ge(As) have been measured as a function of impurity concentration. The impurity concentration ranged from, 6.3 × 1015 cm−3 (semiconducting regime) to 5.5 × 1017 cm−3 (metallic regime). By fitting the lineshape of the valley-orbit Raman line, which changes markedly at the transition, semiconducting regions and metallic regions are shown to coexist. The scattering mechanism for single particle excitations in the metallic regime has been identified as intervalley fluctuations.

Serum immunoglobulin D concentrations were found to be elevated in Vietnamese and Montagnard but not in Cambodian residents of a Vietnam village which is highly endemic for malaria. Although a high frequency of positive malaria CF tests was demonstrated in all three groups, there was no significant correlation between the serum IgD levels and the malaria CF titres. Serum IgD levels in Vietnamese residents of a non-malarious community were similar to those of United States blood donors, however, in the former groups, a high frequency (i.e., 90%) of low titre CF reactions was observed, compared to a frequency of 8% low titre CF reactions in the U.S. donors.

Peripheral vascular disease is a devastating complication of diabetes mellitus. Post-operative vascular death rates are 10% or more following amputation for gangrene in diabetic patients, and three year mortality approaches 30%. An additional 20-30% of patients require subsequent amputation for diabetic gangrene. In view of these statistics, and because of the postulated role of the blood platelet in diabetic vascular disease, a collaborative study on antiplatelet agents was begun in 10 VA medical centers in 1977. In a double-blinded study, aspirin (325 mg tid) plus dipyridamole (75 mg tid) or placebos are given to adult diabetic males who had suffered a recent amputation for diabetic lower extremity vascular disease. End points are major vascular events after at least 3 years of follow-up.Recruitment of 231 subjects was completed by May, 1980. Baseline characteristics are well matched in both groups. Mean age is 59.6 years, duration of diabetes 12.7 years, smoking history 33.3 pack years, and treatment with insulin 68%. Previous myocardial infarction, congestive heart failure, and/or cerebrovascular disease is present in 17-18% and retinopathy is present in 40% at entry. About 43% have more than one vascular complication at baseline.Mean duration of follow-up is now 18 months. Major vascular events in separate patients are: 40 amputations, 31 deaths, 5 myocardial infarctions. Numerous less serious vascular events have also occurred, as have multiple events in single patients. Therapy has been stopped in 17% of patients, but rarely due to drug side effects. Compliance with therapy has been good.We conclude that this study will provide important new information on the natural history of lower extremity vascular disease in diabetes. It will also provide definitive data about the efficacy of antiplatelet agents in diabetic vascular disease.

Measurements of villus dimensions were made on jejunal mucosal biopsy specimens from 16 Vietnamese residents of the Mekong River delta of the Republic of Vietnam and from 13 North Americans who were asymptomatic and had no history of previous tropical exposure. There were marked differences between the two populations with respect to villus dimensions and histological characteristics of jejunal mucosa. Differences between the arithmetic means of all dimensions in the two groups were statistically highly significant.

Tetracycline hydrochloride was evaluated in asymptomatic and acutely ill subjects naturally infected with chloroquine resistant strains of Plasmodium falciparum . Sixteen asymptomatic subjects of whom eight had recently experienced chloroquine treatment failures received 250 mg of tetracycline hydrochloride, four times daily for ten days. A presumptive radical cure was demonstrated in 12. In the other four, treatment was discontinued within 72 hours because of symptomatic development. Acutely ill subjects were assigned to one of two treatment groups. One group received 640 mg of quinine sulfate, three times daily for three days, followed by 250 mg of tetracycline hydrochloride, four times daily for ten days. The other group received a similar course of quinine followed by a conventional course of chloroquine. A presumptive radical cure was demonstrated in 29 of 30 treated with the quinine-tetracycline regimen, and in 15 of 36 treated with the quinine-chloroquine regimen.