A Database of Wing Diversity in the Hawaiian Drosophila

Background. Within genus Drosophila, the endemic Hawaiian species offer some of the most dramatic examples of morphological and behavioral evolution. The advent of the Drosophila grimshawi genome sequence permits genes of interest to be readily cloned from any of the hundreds of species of Hawaiian Drosophila, offering a powerful comparative approach to defining molecular mechanisms of species evolution. A key step in this process is to survey the Hawaiian flies for characters whose variation can be associated with specific candidate genes. The wings provide an attractive target for such studies: Wings are essentially two dimensional, and genes controlling wing shape, vein specification, pigment production, and pigment pattern evolution have all been identified in Drosophila. Methodology/Principal Findings. We present a photographic database of over 180 mounted, adult wings from 73 species of Hawaiian Drosophila. The image collection, available at FlyBase.org, includes 53 of the 112 known species of picture wing\u27\u27 Drosophila, and several species from each of the other major Hawaiian groups, including the modified mouthparts, modified tarsus, antopocerus, and haleakalae (fungus feeder) groups. Direct image comparisons show that major wing shape changes can occur even between closely related species, and that pigment pattern elements can vary independently of each other. Among the 30 species closest to grimshawi, diverse visual effects are achieved by altering a basic pattern of seven wing spots. Finally, we document major pattern variations within species, which appear to result from reduced diffusion of pigment precursors through the wing blade. Conclusions/Significance. The database highlights the striking variation in size, shape, venation, and pigmentation in Hawaiian Drosophila, despite their generally low levels of DNA sequence divergence. In several independent lineages, highly complex patterns are derived from simple ones. These lineages offer a promising model system to study the evolution of complexity

Outcome measurement in functional neurological disorder: a systematic review and recommendations.

OBJECTIVES: We aimed to identify existing outcome measures for functional neurological disorder (FND), to inform the development of recommendations and to guide future research on FND outcomes. METHODS: A systematic review was conducted to identify existing FND-specific outcome measures and the most common measurement domains and measures in previous treatment studies. Searches of Embase, MEDLINE and PsycINFO were conducted between January 1965 and June 2019. The findings were discussed during two international meetings of the FND-Core Outcome Measures group. RESULTS: Five FND-specific measures were identified-three clinician-rated and two patient-rated-but their measurement properties have not been rigorously evaluated. No single measure was identified for use across the range of FND symptoms in adults. Across randomised controlled trials (k=40) and observational treatment studies (k=40), outcome measures most often assessed core FND symptom change. Other domains measured commonly were additional physical and psychological symptoms, life impact (ie, quality of life, disability and general functioning) and health economics/cost-utility (eg, healthcare resource use and quality-adjusted life years). CONCLUSIONS: There are few well-validated FND-specific outcome measures. Thus, at present, we recommend that existing outcome measures, known to be reliable, valid and responsive in FND or closely related populations, are used to capture key outcome domains. Increased consistency in outcome measurement will facilitate comparison of treatment effects across FND symptom types and treatment modalities. Future work needs to more rigorously validate outcome measures used in this population

Functional cognitive disorder: dementia's blind spot

An increasing proportion of cognitive difficulties are recognized to have a functional cause, the chief clinical indicator of which is internal inconsistency. When these symptoms are impairing or distressing, and not better explained by other disorders, this can be conceptualized as a cognitive variant of functional neurological disorder, termed functional cognitive disorder (FCD). FCD is likely very common in clinical practice but may be under-diagnosed. Clinicians in many settings make liberal use of the descriptive term mild cognitive impairment (MCI) for those with cognitive difficulties not impairing enough to qualify as dementia. However, MCI is an aetiology-neutral description, which therefore includes patients with a wide range of underlying causes. Consequently, a proportion of MCI cases are due to non-neurodegenerative processes, including FCD. Indeed, significant numbers of patients diagnosed with MCI do not 'convert' to dementia. The lack of diagnostic specificity for MCI 'non-progressors' is a weakness inherent in framing MCI primarily within a deterministic neurodegenerative pathway. It is recognized that depression, anxiety and behavioural changes can represent a prodrome to neurodegeneration; empirical data are required to explore whether the same might hold for subsets of individuals with FCD. Clinicians and researchers can improve study efficacy and patient outcomes by viewing MCI as a descriptive term with a wide differential diagnosis, including potentially reversible components such as FCD. We present a preliminary definition of functional neurological disorder-cognitive subtype, explain its position in relation to other cognitive diagnoses and emerging biomarkers, highlight clinical features that can lead to positive diagnosis (as opposed to a diagnosis of exclusion), and red flags that should prompt consideration of alternative diagnoses. In the research setting, positive identifiers of FCD will enhance our recognition of individuals who are not in a neurodegenerative prodrome, while greater use of this diagnosis in clinical practice will facilitate personalised interventions

Cognitive domains affected post-COVID-19; a systematic review and meta-analysis

\ua9 2024 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.Background and purpose: This review aims to characterize the pattern of post-COVID-19 cognitive impairment, allowing better prediction of impact on daily function to inform clinical management and rehabilitation. Methods: A systematic review and meta-analysis of neurocognitive sequelae following COVID-19 was conducted, following PRISMA-S guidelines. Studies were included if they reported domain-specific cognitive assessment in patients with COVID-19 at >4 weeks post-infection. Studies were deemed high-quality if they had >40 participants, utilized healthy controls, had low attrition rates and mitigated for confounders. Results: Five of the seven primary Diagnostic and Statistical Manual of Mental Disorders (DSM-5) cognitive domains were assessed by enough high-quality studies to facilitate meta-analysis. Medium effect sizes indicating impairment in patients post-COVID-19 versus controls were seen across executive function (standardised mean difference (SMD) −0.45), learning and memory (SMD −0.55), complex attention (SMD −0.54) and language (SMD −0.54), with perceptual motor function appearing to be impacted to a greater degree (SMD −0.70). A narrative synthesis of the 56 low-quality studies also suggested no obvious pattern of impairment. Conclusions: This review found moderate impairments across multiple domains of cognition in patients post-COVID-19, with no specific pattern. The reported literature was significantly heterogeneous, with a wide variety of cognitive tasks, small sample sizes and disparate initial disease severities limiting interpretability. The finding of consistent impairment across a range of cognitive tasks suggests broad, as opposed to domain-specific, brain dysfunction. Future studies should utilize a harmonized test battery to facilitate inter-study comparisons, whilst also accounting for the interactions between COVID-19, neurological sequelae and mental health, the interplay between which might explain cognitive impairment

UK-Wide Surveillance of Neurological and Neuropsychiatric Complications of COVID-19: The First 153 Patients

Background: Increasingly neurological complications of COVID-19 are identified, mostly in small series. Larger studies have been limited by both geography and specialty.Consequently, the breadth of complications is not represented. Comprehensive characterization of clinical syndromes is critical to rationally select and evaluate potential therapies.Methods: During the exponential pandemic phase, we developed coordinated online portals for rapid notification across the spectrum of major UK neuroscience bodies, representing neurology, stroke, psychiatry, and intensive care. Evidence of infection and clinical case definitions were applied prospectively. Cases were compared to overall Government Public Health COVID-19 reporting.Findings: Within three weeks, 153 cases were notified, both geographically and temporally representative of overall COVID-19 Public Health reports. Median (range) age was 71 (23-94) years. 77 (62%) had a cerebrovascular event: 57 (74%) ischemic strokes, nine (12%) intracerebral hemorrhages, and one CNS vasculitis.The second most common group were 39 (31%) who had altered mental status, including 16 (41%) with encephalopathy of whom seven (44%) had encephalitis. The remaining 23 (59%) had a psychiatric diagnosis of whom 21 (92%) were new diagnoses; including ten (43%) with psychosis, six (26%) neurocognitive (dementia-like) syndrome, and 4 (17%) an affective disorder. Cerebrovascular events predominated in older patients. Conversely, altered mental status, whilst present in all ages, had disproportionate representation in the young.Interpretation: This is the first nationwide, cross-specialty surveillance study of acute complications of COVID-19 in the nervous system. Alteration in mental status was common, reflecting encephalopathy/encephalitis and primary psychiatric diagnoses, often in young patients.These data provide valuable and timely information urgently needed by clinicians, researchers, and funders to inform immediate steps in COVID-19 neuroscience research and health policy throughout the areas of neurology and neuropsychiatry

Selection at the Y Chromosome of the African Buffalo Driven by Rainfall

Selection coefficients at the mammalian Y chromosome typically do not deviate strongly from neutrality. Here we show that strong balancing selection, maintaining intermediate frequencies of DNA sequence variants, acts on the Y chromosome in two populations of African buffalo (Syncerus caffer). Significant correlations exist between sequence variant frequencies and annual rainfall in the years before conception, with five- to eightfold frequency changes over short time periods. Annual rainfall variation drives the balancing of sequence variant frequencies, probably by affecting parental condition. We conclude that sequence variants confer improved male reproductive success after either dry or wet years, making the population composition and dynamics very sensitive to climate change. The mammalian Y chromosome, interacting with ecological processes, may affect male reproductive success much more strongly than previously thought

Phytochemicals as antibiotic alternatives to promote growth and enhance host health

There are heightened concerns globally on emerging drug-resistant superbugs and the lack of new antibiotics for treating human and animal diseases. For the agricultural industry, there is an urgent need to develop strategies to replace antibiotics for food-producing animals, especially poultry and livestock. The 2nd International Symposium on Alternatives to Antibiotics was held at the World Organization for Animal Health in Paris, France, December 12-15, 2016 to discuss recent scientific developments on strategic antibiotic-free management plans, to evaluate regional differences in policies regarding the reduction of antibiotics in animal agriculture and to develop antibiotic alternatives to combat the global increase in antibiotic resistance. More than 270 participants from academia, government research institutions, regulatory agencies, and private animal industries from >25 different countries came together to discuss recent research and promising novel technologies that could provide alternatives to antibiotics for use in animal health and production; assess challenges associated with their commercialization; and devise actionable strategies to facilitate the development of alternatives to antibiotic growth promoters (AGPs) without hampering animal production. The 3-day meeting consisted of four scientific sessions including vaccines, microbial products, phytochemicals, immune-related products, and innovative drugs, chemicals and enzymes, followed by the last session on regulation and funding. Each session was followed by an expert panel discussion that included industry representatives and session speakers. The session on phytochemicals included talks describing recent research achievements, with examples of successful agricultural use of various phytochemicals as antibiotic alternatives and their mode of action in major agricultural animals (poultry, swine and ruminants). Scientists from industry and academia and government research institutes shared their experience in developing and applying potential antibiotic-alternative phytochemicals commercially to reduce AGPs and to develop a sustainable animal production system in the absence of antibiotics.Fil: Lillehoj, Hyun. United States Department of Agriculture. Agricultural Research Service; ArgentinaFil: Liu, Yanhong. University of California; Estados UnidosFil: Calsamiglia, Sergio. Universitat Autònoma de Barcelona; EspañaFil: Fernandez Miyakawa, Mariano Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Patobiología; ArgentinaFil: Chi, Fang. Amlan International; Estados UnidosFil: Cravens, Ron L.. Amlan International; Estados UnidosFil: Oh, Sungtaek. United States Department of Agriculture. Agricultural Research Service; ArgentinaFil: Gay, Cyril G.. United States Department of Agriculture. Agricultural Research Service; Argentin

Time separation as a hidden variable to the Copenhagen school of quantum mechanics

The Bohr radius is a space-like separation between the proton and electron in the hydrogen atom. According to the Copenhagen school of quantum mechanics, the proton is sitting in the absolute Lorentz frame. If this hydrogen atom is observed from a different Lorentz frame, there is a time-like separation linearly mixed with the Bohr radius. Indeed, the time-separation is one of the essential variables in high-energy hadronic physics where the hadron is a bound state of the quarks, while thoroughly hidden in the present form of quantum mechanics. It will be concluded that this variable is hidden in Feynman's rest of the universe. It is noted first that Feynman's Lorentz-invariant differential equation for the bound-state quarks has a set of solutions which describe all essential features of hadronic physics. These solutions explicitly depend on the time separation between the quarks. This set also forms the mathematical basis for two-mode squeezed states in quantum optics, where both photons are observable, but one of them can be treated a variable hidden in the rest of the universe. The physics of this two-mode state can then be translated into the time-separation variable in the quark model. As in the case of the un-observed photon, the hidden time-separation variable manifests itself as an increase in entropy and uncertainty.Comment: LaTex 10 pages with 5 figure. Invited paper presented at the Conference on Advances in Quantum Theory (Vaxjo, Sweden, June 2010), to be published in one of the AIP Conference Proceedings serie

Pattern Recognition Software and Techniques for Biological Image Analysis

The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays

Quantitative Analysis of Peripheral Tissue Perfusion Using Spatiotemporal Molecular Dynamics

Background: Accurate measurement of peripheral tissue perfusion is challenging but necessary to diagnose peripheral vascular insufficiency. Because near infrared (NIR) radiation can penetrate relatively deep into tissue, significant attention has been given to intravital NIR fluorescence imaging. Methodology/Principal Findings: We developed a new optical imaging-based strategy for quantitative measurement of peripheral tissue perfusion by time-series analysis of local pharmacokinetics of the NIR fluorophore, indocyanine green (ICG). Time-series NIR fluorescence images were obtained after injecting ICG intravenously in a murine hindlimb ischemia model. Mathematical modeling and computational simulations were used for translating time-series ICG images into quantitative pixel perfusion rates and a perfusion map. We could successfully predict the prognosis of ischemic hindlimbs based on the perfusion profiles obtained immediately after surgery, which were dependent on the preexisting collaterals. This method also reflected increases in perfusion and improvements in prognosis of ischemic hindlimbs induced by treatment with vascular endothelial growth factor and COMP-angiopoietin-1. Conclusions/Significance: We propose that this novel NIR-imaging-based strategy is a powerful tool for biomedical studies related to the evaluation of therapeutic interventions directed at stimulating angiogenesis