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To determine whether prophylactic ranibizumab prevents the development of neovascular age-related macular degeneration (nAMD) in eyes with intermediate age-related macular degeneration (AMD) for patients with preexisting nAMD in their contralateral eye.Multicenter randomized clinical trial.Adults aged 50 years and older with intermediate AMD (multiple intermediate drusen [≥63 μm and125 μm] or ≥1 large drusen [≥125 μm] and pigmentary changes) in the study eye and nAMD in the contralateral eye.Intravitreal ranibizumab injection (0.5 mg) or sham injection every 3 months for 24 months.Conversion to nAMD over 24 months (primary). Change in best-corrected visual acuity from baseline to 24 months (secondary).Among 108 enrolled participants (54 [50%] in each group), all except 2 were non-Hispanic Whites, 61 participants (56%) were female, and the mean age was 78 years. The mean baseline visual acuity was 77.7 letters (Snellen equivalent 20/32). Conversion to nAMD over 24 months occurred among 7 of 54 eyes (13%) in both groups (ranibizumab vs. sham hazard ratio = 0.91 [95% confidence interval (CI), 0.32-2.59]; P = 0.86). At 24 months, the cumulative incidence of nAMD adjusted for loss to follow-up was 14% (95% CI, 4%-23%) in the ranibizumab group and 15% (95% CI, 4%-25%) in the sham group. At 24 months, the mean change in visual acuity from baseline was -2.1 letters (standard deviation, 5.4 letters) with ranibizumab and -1.4 letters (standard deviation, 7.7 letters) with sham (adjusted difference = -0.8 letters [95% CI, -3.7 to 2.2 letters]; P = 0.62). The proportion of eyes that lost at least 10 letters of visual acuity from baseline at 24 months was 2 of 39 (5%) with ranibizumab and 4 of 40 (10%) with sham. There were no serious ocular adverse events in either group.Quarterly dosing of 0.5 mg ranibizumab in eyes with intermediate AMD did not reduce the incidence of nAMD compared with sham injections; however, the study was likely underpowered given the 95% CI, and a clinically meaningful effect cannot be excluded. There also was no effect on visual acuity at 24 months. Other strategies to reduce neovascular conversion in these vulnerable eyes are needed.

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory, and activity regulation. Here, we identify new components of the MB circuit inDrosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain., eLife digest Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons – compared to some 86 billion in humans – the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map – or connectome – the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

Understanding the structure and operation of any nervous system has been a subject of research for well over a century. A near-term opportunity in this quest is to understand the brain of a model species, the fruit fly Drosophila melanogaster. This is an enticing target given its relatively small size (roughly 200,000 neurons), coupled with the behavioral richness that this brain supports, and the wide variety of techniques now available to study both brain and behavior. It is clear that within a few years we will possess a connectome for D. melanogaster: an electron-microscopy-level description of all neurons and their chemical synaptic connections. Given what we will soon have, what we already know and the research that is currently underway, what more do we need to know to enable us to understand the fly's brain? Here, we itemize the data we will need to obtain, collate and organize in order to build an integrated model of the brain of D. melanogaster.

Anthracnose caused by the fungal pathogen C. sublineola is an economically important constraint on worldwide sorghum production. The most effective strategy to safeguard yield is through the introgression of resistance alleles. This requires elucidation of the genetic basis of the different resistance sources that have been identified. In this study, 223 recombinant inbred lines (RILs) derived from crossing anthracnose-differentials QL3 (96 RILs) and IS18760 (127 RILs) with the common susceptible parent PI609251 were evaluated at four field locations in the United States (Florida, Georgia, Texas, and Puerto Rico) for their anthracnose resistance response. Both RIL populations were highly susceptible to anthracnose in Florida and Georgia, while in Puerto Rico and Texas they were segregating for anthracnose resistance response. A genome scan using a composite linkage map of 982 single nucleotide polymorphisms (SNPs) detected two genomic regions of 4.31 and 0.85 Mb on chromosomes 4 and 8, respectively, that explained 10–27% of the phenotypic variation in Texas and Puerto Rico. In parallel, a subset of 43 RILs that contained 67% of the recombination events were evaluated against anthracnose pathotypes from Arkansas (2), Puerto Rico (2) and Texas (4) in the greenhouse. A genome scan showed that the 7.57 Mb region at the distal end of the short arm of chromosome 5 is associated with the resistance response against the pathotype AMP-048 from Arkansas. Comparative analysis identified the genomic region on chromosome 4 overlaps with an anthracnose resistance locus identified in another anthracnose-differential line, SC414-12E, indicating this genomic region is of interest for introgression in susceptible sorghum germplasm. Candidate gene analysis for the resistance locus on chromosome 5 identified an R-gene cluster that has high similarity to another R-gene cluster associated with anthracnose resistance on chromosome 9.

Ebola virus (EBOV) is one of the most lethal pathogens that can infect humans. The Ebola viral protein VP35 (EBOV VP35) inhibits host IFN-α/β production by interfering with host immune responses to viral invasion and is thus considered as a plausible drug target. The aim of this study was to identify potential novel lead compounds against EBOV VP35 using computational techniques in drug discovery. The 3D structure of the EBOV VP35 with PDB ID: 3FKE was used for molecular docking studies. An integrated library of 7675 African natural product was pre-filtered using ADMET risk, with a threshold of 7 and, as a result, 1470 ligands were obtained for the downstream molecular docking using AutoDock Vina, after an energy minimization of the protein via GROMACS. Five known inhibitors, namely, amodiaquine, chloroquine, gossypetin, taxifolin and EGCG were used as standard control compounds for this study. The area under the curve (AUC) value, evaluating the docking protocol obtained from the receiver operating characteristic (ROC) curve, generated was 0.72, which was considered to be acceptable. The four identified potential lead compounds of NANPDB4048, NANPDB2412, ZINC000095486250 and NANPDB2476 had binding affinities of −8.2, −8.2, −8.1 and −8.0 kcal/mol, respectively, and were predicted to possess desirable antiviral activity including the inhibition of RNA synthesis and membrane permeability, with the probable activity (Pa) being greater than the probable inactivity (Pi) values. The predicted anti-EBOV inhibition efficiency values (IC50), found using a random forest classifier, ranged from 3.35 to 11.99 μM, while the Ki values ranged from 0.97 to 1.37 μM. The compounds NANPDB4048 and NANPDB2412 had the lowest binding energy of −8.2 kcal/mol, implying a higher binding affinity to EBOV VP35 which was greater than those of the known inhibitors. The compounds were predicted to possess a low toxicity risk and to possess reasonably good pharmacological profiles. Molecular dynamics (MD) simulations of the protein–ligand complexes, lasting 50 ns, and molecular mechanisms Poisson-Boltzmann surface area (MM-PBSA) calculations corroborated the binding affinities of the identified compounds and identified novel critical interacting residues. The antiviral potential of the molecules could be confirmed experimentally, while the scaffolds could be optimized for the design of future novel anti-EBOV chemotherapeutics.

Purpose This work was to establish an uncomplicated tumor control probability (UTCP) model using hepatocellular carcinoma (HCC) stereotactic body radiation therapy (SBRT) clinical data in our institution. The model was then used to analyze the current dose prescription method and to seek the opportunity for improvement. Methods and Materials A tumor control probability (TCP) model was generated based on local clinical data using the maximum likelihood method. A UTCP model was then formed by combining the established TCP model with the normal tissue complication probability model based on the study by Dawson et al. The authors investigated the dependence of maximum achievable UTCP on planning target volume equivalent uniform dose (EUD) at various ratio between planning target volume EUD and normal liver EUD (T/N EUD ratios). A new term uncomplicated tumor control efficiency (UTCE) was also introduced to analyze the outcome. A UTCE value of 1 implied that the theoretical maximum UTCP for the corresponding T/N EUD ratio was achieved. Results The UTCE of the HCC SBRT patients based on the current dose prescription method was found to be 0.93 ± 0.05. It was found that the UTCE could be increased to 0.99 ± 0.03 by using a new dose prescription scheme, for which the UTCP could be maximized while keeping the normal tissue complication probability value smaller than 5%. Conclusions The dose prescription method of the current HCC SBRT in our institution was analyzed using a UTCP model established based on local clinical data. It was shown that there could be a potential to increase the prescription dose of HCC SBRT. A new dose prescription scheme was proposed to achieve better UTCP. Additional clinical trials would be required to validate the proposed dose prescription scheme in the future.

Aims: The aim of this study was to identify resistant accessions against pathogens, causing anthracnose and grain mold. Study Design: Study was laid out in a randomized complete block design with three replications. Data for anthracnose rating, grain mold severity, seed weight, and percent germination rate were analyzed using the command PROC GLM. Place and Duration of Study: The study was carried out at the Texas AgriLife Research Farm, Burleson County, Texas, in 2010, 2014, and 2015 growing seasons. Methodology: Forty-seven accessions were planted in 6 m rows 0.31 m spacing. Plants were inoculated by placing Colletotrichum sublineola colonized grain in the plant whorls 30 days after planting. Disease evaluation was initiated 30 days post-inoculation and thereafter on a weekly basis for three consecutive weeks. Grain mold experiment: Three treatments were used: 1) plants sprayed with A. alternata alone, 2) a mixture of A. alternata, F. thapsinum and C. lunata, 3) control plants sprayed with sterilized water and exposed to natural infection. At 50% bloom, three panicles per line within replication were inoculated for each treatment. Results: Eleven accessions, including PI641874, PI656070, PI656115, and PI534167 were consistently resistant when challenged with the anthracnose pathogen, C. sublineola. Accessions PI534047 and PI574455, exhibited resistance to moderately resistance grain mold response when challenged with the treatments. Seed weight, germination rate, and mycoflora analysis which are factors in determining grain mold resistance also were measured. Across the accessions, mean seed weight ranged from1.4 g to 4.3 g per 100 kernel and germination rate ranged from 26 to 87%. Conclusion: The resistant accessions identified in this study can be used in breeding programs to develop anthracnose and grain mold resistance lines.

The trigeminal ganglion with its three trigeminal nerve tracts consists mainly of clusters of sensory neurons with their peripheral and central processes. Most neurons are surrounded by satellite glial cells and the axons are wrapped by myelinating and non-myelinating Schwann cells. Trigeminal neurons express various neuropeptides, most notably, calcitonin gene-related peptide (CGRP), substance P, and pituitary adenylate cyclase-activating polypeptide (PACAP). Two types of CGRP receptors are expressed in neurons and satellite glia. A variety of other signal molecules like ATP, nitric oxide, cytokines, and neurotrophic factors are released from trigeminal ganglion neurons and signal to neighboring neurons or satellite glial cells, which can signal back to neurons with same or other mediators. This potential cross-talk of signals involves intracellular mechanisms, including gene expression, that can modulate mediators of sensory information, such as neuropeptides, receptors, and neurotrophic factors. From the ganglia cell bodies, which are outside the blood–brain barrier, the mediators are further distributed to peripheral sites and/or to the spinal trigeminal nucleus in the brainstem, where they can affect neural transmission. A major question is how the sensory neurons in the trigeminal ganglion differ from those in the dorsal root ganglion. Despite their functional overlap, there are distinct differences in their ontogeny, gene expression, signaling pathways, and responses to anti-migraine drugs. Consequently, drugs that modulate cross-talk in the trigeminal ganglion can modulate both peripheral and central sensitization, which may potentially be distinct from sensitization mediated in the dorsal root ganglion.

Mobilities has become a keyword in the agendas of policy makers and the decisions of individuals, including young people. Hong Kong as a city long defined as a hub of cross-border flows has...

The brain's synaptic networks endow an animal with powerfully adaptive biological behavior. Maps of such synaptic circuits densely reconstructed in those model brains that can be examined and manipulated by genetic means offer the best prospect for understanding the underlying biological bases of behavior. That prospect is now technologically feasible and a scientifically enabling possibility in neurobiology, much as genomics has been in molecular biology and genetics. In Drosophila, two major advances are in electron microscopic technology, using focused ion beam–scanning electron microscopy (FIB-SEM) milling to capture and align digital images, and in computer-aided reconstruction of neuron morphologies. The last decade has witnessed enormous progress in detailed knowledge of the actual synaptic circuits formed by real neurons. Advances in various brain regions that heralded identification of the motion-sensing circuits in the optic lobe are now extending to other brain regions, with the prospect of encompassing the fly's entire nervous system, both brain and ventral nerve cord.

Gene expression was analyzed at 0- and 24-h post-inoculation of two inbred sorghum cultivars known to differ in response to inoculation with Colletotrichum sublineola, the fungal pathogen that causes anthracnose. QL3 is reported to have quantitative resistance, while Theis is susceptible to most pathotypes of the pathogen; RNASeq identified over 3,000 specific genes in both cultivars as showing significant changes in expression following inoculation; in all but one gene, the changes in QL3 and Thies were in the same direction. Many other genes showed significant changes in only one of the two cultivars. Overall, more genes were downregulated than upregulated. Differences in changes in expression levels of a few genes suggested potential roles for the difference in disease response between QL3 and Theis, but did not identify known resistance genes. Gene ontology (GO) and pathway enrichment analysis identified upregulation of 23 transcription factor encoding genes as well as genes involved in the production of secondary metabolites, which are part of a typical host defense reaction.

Anthracnose disease of sorghum is caused by Colletotrichum sublineola, a filamentous fungus. The genetic basis of resistance to anthracnose in sorghum is largely unclear, especially in Senegalese sorghum germplasm. In this study, 163 Senegalese sorghum accessions were evaluated for response to C. sublineola, and a genome‐wide association study (GWAS) was performed to identify genetic variation associated with response to C. sublineola using 193,727 single nucleotide polymorphisms (SNPs) throughout the genome. Germplasm diversity analysis showed low genetic diversity and slow linkage disequilibrium (LD) decay among the Senegalese accessions. Phenotypic analysis resulted in relatively low differences to C. sublineola among the tested population. Genome‐wide association study did not identify any significant association based on a strict threshold for the number of SNPs available. However, individual analysis of the top eight SNPs associated with relative susceptibility and resistance identified candidate genes that have been shown to play important roles in plant stress tolerance in previous studies. This study identifies sorghum genes whose annotated properties have known roles in host defense and thus identify them as candidates for use in breeding for resistance to anthracnose.

Objective: To retrospectively analyze the clinical impact on stereotactic body radiation therapy (SBRT) for hepatocellular carcinoma (HCC) located at lung–liver boundary due to the use of Acuros XB algorithm (AXB) in replacement of anisotropic analytical algorithm (AAA). Methods: 23 SBRT volumetric modulated arc therapy (VMAT) plans for HCC located at lung–liver boundary were calculated using AAA and AXB respectively with the same treatment parameters. The dose–volume data of the planned target volumes (PTVs) were compared. A published tumour control probability (TCP) model was used to calculate the effect of dosimetric difference between AAA and AXB on tumour control probability. Results: For dose calculated by AXB (Dose to medium), the D95% and D98% of the PTV were on average 2.4 and 3.1% less than that calculated by AAA. For dose calculated by AXB (dose to water), the D95% and D98% of the PTV were on average 1.8%, and 2.7% less than that calculated by AAA. Up to 5% difference in D95% and 8% difference in D98% were observed in the worst cases. The significant decrease in D95% calculated by AXB compared to AAA could result in a % decrease in 2 year TCP up to 8% in the worst case (from 46.8 to 42.9%). Conclusion: The difference in dose calculated by AAA and AXB could lead to significant difference in TCP for HCC SBRT located at lung–liver boundary region. Advances in knowledge: The difference in calculated dose and tumour control probability for HCC SBRT between AAA and AXB algorithm at lung–liver boundary region was compared.

Purpose To report a case of a hemi-retinal vein occlusion (HRVO) in the setting of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Observations A 32-year-old healthy male presented with a paracentral scotoma, retinal hemorrhages, and dilated and tortuous retinal vessels inferiorly in the right eye. He was diagnosed with HRVO in the setting of recent SARS-CoV-2 infection. Conclusions and importance Venous thromboembolic complications and coagulation abnormalities have been widely reported in association with SARS-CoV-2 infection. We highlight this case to raise awareness that a retinal vein occlusion in an otherwise healthy, young patient may be a potential manifestation of the thromboinflammatory state associated with SARS-CoV-2 infection.