Investigating the effects of synbiotic supplementation on functional movement, strength and muscle health in older Australians: a study protocol for a double-blind, randomized, placebo-controlled trial

BACKGROUND

Aging has been associated with a progressive loss of skeletal muscle quality, quantity and strength, which may result in a condition known as sarcopenia, leading to a decline in physical performance, loss of independence and reduced quality of life. While the cause of impaired physical functioning observed in elderly populations appears to be multifactorial, recent evidence suggests that age-associated alterations in gut microbiota could be a contributing factor. The primary objective will be to assess the effects of a dietary synbiotic formulation on sarcopenia-related functional outcomes such as handgrip strength, gait speed and physical performance within older individuals living independently. The secondary objective will be to examine associations between changes in gut microbiota composition, functional performance and lean muscle mass.

METHODS

Seventy-four elderly (60-85 years) participants will be randomized in a double-blind, placebo-controlled fashion to either an intervention or control group. The intervention group (n = 37) will receive oral synbiotic formulation daily for 16 weeks. The control group (n = 37) will receive placebo. Assessments of physical performance (including Short Physical Performance Battery, handgrip strength and timed up-and-go tests) and muscle ultrasonography will be performed at 4 time points (baseline and weeks 8, 16 and 20). Likewise, body composition via bioelectric impedance analysis and blood and stool samples will be collected at each time point. Dual-energy X-ray absorptiometry will be performed at baseline and week 16. The primary outcomes will be between-group changes in physical performance from baseline to 16 weeks. Secondary outcomes include changes in body composition, muscle mass and architecture, fecal microbiota composition and diversity, and fecal and plasma metabolomics.

DISCUSSION

Gut-modulating supplements appear to be effective in modifying gut microbiota composition in healthy older adults. However, it is unclear whether these changes translate into functional and/or health improvements. In the present study, we will investigate the effects of a synbiotic formulation on measures of physical performance, strength and muscle health in healthy older populations.

TRIAL REGISTRATION

This study was prospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12622000652774) in May 2022.

Automated staging of zebrafish embryos with deep learning

The zebrafish (Danio rerio) is an important biomedical model organism used in many disciplines. The phenomenon of developmental delay in zebrafish embryos has been widely reported as part of a mutant or treatment-induced phenotype. However, the detection and quantification of these delays is often achieved through manual observation, which is both time-consuming and subjective. We present KimmelNet, a deep learning model trained to predict embryo age (hours post fertilisation) from 2D brightfield images. KimmelNet's predictions agree closely with established staging methods and can detect developmental delays between populations with high confidence using as few as 100 images. Moreover, KimmelNet generalises to previously unseen data, with transfer learning enhancing its performance. With the ability to analyse tens of thousands of standard brightfield microscopy images on a timescale of minutes, we envisage that KimmelNet will be a valuable resource for the developmental biology community. Furthermore, the approach we have used could easily be adapted to generate models for other organisms.

Bridging imaging users to imaging analysis - A community survey

The 'Bridging Imaging Users to Imaging Analysis' survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), BioImaging North America (BINA) and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multichoice and open-ended questions, the survey inquired about demographics, image analysis experiences, future needs and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross-community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user-friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarise themselves with the fundamentals of image analysis, provide constant feedback and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for 'written tutorials' to acquire knowledge on image analysis. We also observed that the interest in having 'office hours' to get an expert opinion on their image analysis methods has increased over the years. The results also showed less-than-expected usage of online discussion forums in the imaging community for solving image analysis problems. Surprisingly, we also observed a decreased interest among the survey respondents in deep/machine learning despite the increasing adoption of artificial intelligence in biology. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

Bridging Imaging Users to Imaging Analysis - A community survey

The "Bridging Imaging Users to Imaging Analysis" survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), Bioimaging North America (BINA), and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multi-choice and open-ended questions, the survey inquired about demographics, image analysis experiences, future needs, and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross-community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user-friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarize themselves with the fundamentals of image analysis, provide constant feedback, and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for 'written tutorials' to acquire knowledge on image analysis. We also observed that the interest in having 'office hours' to get an expert opinion on their image analysis methods has increased over the years. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

Automated staging of zebrafish embryos using machine learning

The zebrafish ( Danio rerio), is an important biomedical model organism used in many disciplines, including development, disease modeling and toxicology, to better understand vertebrate biology. The phenomenon of developmental delay in zebrafish embryos has been widely reported as part of a mutant or treatment-induced phenotype, and accurate characterization of such delays is imperative. Despite this, the only way at present to identify and quantify these delays is through manual observation, which is both time-consuming and subjective. Machine learning approaches in biology are rapidly becoming part of the toolkit used by researchers to address complex questions. In this work, we introduce a machine learning-based classifier that has been trained to detect temporal developmental differences across groups of zebrafish embryos. Our classifier is capable of rapidly analyzing thousands of images, allowing comparisons of developmental temporal rates to be assessed across and between experimental groups of embryos. Finally, as our classifier uses images obtained from a standard live-imaging widefield microscope and camera set-up, we envisage it will be readily accessible to the zebrafish community, and prove to be a valuable resource.

Automated staging of zebrafish embryos using machine learning

The zebrafish ( Danio rerio), is an important biomedical model organism used in many disciplines, including development, disease modeling and toxicology, to better understand vertebrate biology. The phenomenon of developmental delay in zebrafish embryos has been widely reported as part of a mutant or treatment-induced phenotype, and accurate characterization of such delays is imperative. Despite this, the only way at present to identify and quantify these delays is through manual observation, which is both time-consuming and subjective. Machine learning approaches in biology are rapidly becoming part of the toolkit used by researchers to address complex questions. In this work, we introduce a machine learning-based classifier that has been trained to detect temporal developmental differences across groups of zebrafish embryos. Our classifier is capable of rapidly analyzing thousands of images, allowing comparisons of developmental temporal rates to be assessed across and between experimental groups of embryos. Finally, as our classifier uses images obtained from a standard live-imaging widefield microscope and camera set-up, we envisage it will be readily accessible to the zebrafish community, and prove to be a valuable resource.

Automated staging of zebrafish embryos using machine learning

The zebrafish (Danio rerio), is an important biomedical model organism used in many disciplines, including development, disease modeling and toxicology, to better understand vertebrate biology. The phenomenon of developmental delay in zebrafish embryos has been widely reported as part of a mutant or treatment-induced phenotype, and accurate characterization of such delays is imperative. Despite this, the only way at present to identify and quantify these delays is through manual observation, which is both time-consuming and subjective. Machine learning approaches in biology are rapidly becoming part of the toolkit used by researchers to address complex questions. In this work, we introduce a machine learning-based classifier that has been trained to detect temporal developmental differences across groups of zebrafish embryos. Our classifier is capable of rapidly analyzing thousands of images, allowing comparisons of developmental temporal rates to be assessed across and between experimental groups of embryos. Finally, as our classifier uses images obtained from a standard live-imaging widefield microscope and camera set-up, we envisage it will be readily accessible to the zebrafish community, and prove to be a valuable resource.

GIANI: open-source software for automated analysis of 3D microscopy images

The study of cellular and developmental processes in physiologically relevant three-dimensional (3D) systems facilitates an understanding of mechanisms underlying cell fate, disease and injury. While cutting-edge microscopy technologies permit the routine acquisition of 3D datasets, there is currently a limited number of open-source software packages to analyse such images. Here, we describe General Image Analysis of Nuclei-based Images (GIANI; https://djpbarry.github.io/Giani), new software for the analysis of 3D images. The design primarily facilitates segmentation of nuclei and cells, followed by quantification of morphology and protein expression. GIANI enables routine and reproducible batch-processing of large numbers of images, and comes with scripting and command line tools. We demonstrate the utility of GIANI by quantifying cell morphology and protein expression in confocal images of mouse early embryos and by segmenting nuclei from light-sheet microscopy images of the flour beetle embryo. We also validate the performance of the software using simulated data. More generally, we anticipate that GIANI will be a useful tool for researchers in a variety of biomedical fields.

Summary: General Image Analysis of Nuclei-based Images (GIANI) is a new plugin for the popular FIJI platform, designed for the automated analysis of 3D microscopy images of a wide range of sample types.

RASSF8-mediated transport of Echinoid via the exocyst promotes Drosophila wing elongation and epithelial ordering

Cell-cell junctions are dynamic structures that maintain cell cohesion and shape in epithelial tissues. During development, junctions undergo extensive rearrangements to drive the epithelial remodelling required for morphogenesis. This is particularly evident during axis elongation, where neighbour exchanges, cell-cell rearrangements and oriented cell divisions lead to large-scale alterations in tissue shape. Polarised vesicle trafficking of junctional components by the exocyst complex has been proposed to promote junctional rearrangements during epithelial remodelling, but the receptors that allow exocyst docking to the target membranes remain poorly understood. Here, we show that the adherens junction component Ras Association domain family 8 (RASSF8) is required for the epithelial re-ordering that occurs during Drosophila pupal wing proximo-distal elongation. We identify the exocyst component Sec15 as a RASSF8 interactor. Loss of RASSF8 elicits cytoplasmic accumulation of Sec15 and Rab11-containing vesicles. These vesicles also contain the nectin-like homophilic adhesion molecule Echinoid, the depletion of which phenocopies the wing elongation and epithelial packing defects observed in RASSF8 mutants. Thus, our results suggest that RASSF8 promotes exocyst-dependent docking of Echinoid-containing vesicles during morphogenesis.

MICAL2 enhances branched actin network disassembly by oxidizing Arp3B-containing Arp2/3 complexes

The mechanisms regulating the disassembly of branched actin networks formed by the Arp2/3 complex still remain to be fully elucidated. In addition, the impact of Arp3 isoforms on the properties of Arp2/3 are also unexplored. We now demonstrate that Arp3 and Arp3B isocomplexes promote actin assembly equally efficiently but generate branched actin networks with different disassembly rates. Arp3B dissociates significantly faster than Arp3 from the network, and its depletion increases actin stability. This difference is due to the oxidation of Arp3B, but not Arp3, by the methionine monooxygenase MICAL2, which is recruited to the actin network by coronin 1C. Substitution of Arp3B Met293 by threonine, the corresponding residue in Arp3, increases actin network stability. Conversely, replacing Arp3 Thr293 with glutamine to mimic Met oxidation promotes disassembly. The ability of MICAL2 to enhance network disassembly also depends on cortactin. Our observations demonstrate that coronin 1C, cortactin, and MICAL2 act together to promote disassembly of branched actin networks by oxidizing Arp3B-containing Arp2/3 complexes.

A FIJI macro for quantifying pattern in extracellular matrix

Diverse extracellular matrix patterns are observed in both normal and pathological tissue. However, most current tools for quantitative analysis focus on a single aspect of matrix patterning. Thus, an automated pipeline that simultaneously quantifies a broad range of metrics and enables a comprehensive description of varied matrix patterns is needed. To this end, we have developed an ImageJ plugin called TWOMBLI, which stands for The Workflow Of Matrix BioLogy Informatics. This pipeline includes metrics of matrix alignment, length, branching, end points, gaps, fractal dimension, curvature, and the distribution of fibre thickness. TWOMBLI is designed to be quick, versatile and easy-to-use particularly for non-computational scientists. TWOMBLI can be downloaded from https://github.com/wershofe/TWOMBLI together with detailed documentation and tutorial video. Although developed with the extracellular matrix in mind, TWOMBLI is versatile and can be applied to vascular and cytoskeletal networks. Here we present an overview of the pipeline together with examples from a wide range of contexts where matrix patterns are generated.

Fission yeast condensin contributes to interphase chromatin organization and prevents transcription-coupled DNA damage

BACKGROUND

Structural maintenance of chromosomes (SMC) complexes are central organizers of chromatin architecture throughout the cell cycle. The SMC family member condensin is best known for establishing long-range chromatin interactions in mitosis. These compact chromatin and create mechanically stable chromosomes. How condensin contributes to chromatin organization in interphase is less well understood.

RESULTS

Here, we use efficient conditional depletion of fission yeast condensin to determine its contribution to interphase chromatin organization. We deplete condensin in G2-arrested cells to preempt confounding effects from cell cycle progression without condensin. Genome-wide chromatin interaction mapping, using Hi-C, reveals condensin-mediated chromatin interactions in interphase that are qualitatively similar to those observed in mitosis, but quantitatively far less prevalent. Despite their low abundance, chromatin mobility tracking shows that condensin markedly confines interphase chromatin movements. Without condensin, chromatin behaves as an unconstrained Rouse polymer with excluded volume, while condensin constrains its mobility. Unexpectedly, we find that condensin is required during interphase to prevent ongoing transcription from eliciting a DNA damage response.

CONCLUSIONS

In addition to establishing mitotic chromosome architecture, condensin-mediated long-range chromatin interactions contribute to shaping chromatin organization in interphase. The resulting structure confines chromatin mobility and protects the genome from transcription-induced DNA damage. This adds to the important roles of condensin in maintaining chromosome stability.

Matrix feedback enables diverse higher-order patterning of the extracellular matrix

The higher-order patterning of extra-cellular matrix in normal and pathological tissues has profound consequences on tissue function. Whilst studies have documented both how fibroblasts create and maintain individual matrix fibers and how cell migration is altered by the fibers they interact with, a model unifying these two aspects of tissue organization is lacking. Here we use computational modelling to understand the effect of this interconnectivity between fibroblasts and matrix at the mesoscale level. We created a unique adaptation to the Vicsek flocking model to include feedback from a second layer representing the matrix, and use experimentation to parameterize our model and validate model-driven hypotheses. Our two-layer model demonstrates that feedback between fibroblasts and matrix increases matrix diversity creating higher-order patterns. The model can quantitatively recapitulate matrix patterns of tissues in vivo. Cells follow matrix fibers irrespective of when the matrix fibers were deposited, resulting in feedback with the matrix acting as temporal 'memory' to collective behaviour, which creates diversity in topology. We also establish conditions under which matrix can be remodelled from one pattern to another. Our model elucidates how simple rules defining fibroblast-matrix interactions are sufficient to generate complex tissue patterns.

Murine leukemia virus p12 tethers the capsid-containing pre-integration complex to chromatin by binding directly to host nucleosomes in mitosis

The murine leukaemia virus (MLV) Gag cleavage product, p12, is essential for both early and late steps in viral replication. The N-terminal domain of p12 binds directly to capsid (CA) and stabilises the mature viral core, whereas defects in the C-terminal domain (CTD) of p12 can be rescued by addition of heterologous chromatin binding sequences (CBSs). We and others hypothesised that p12 tethers the pre-integration complex (PIC) to host chromatin ready for integration. Using confocal microscopy, we have observed for the first time that CA localises to mitotic chromatin in infected cells in a p12-dependent manner. GST-tagged p12 alone, however, did not localise to chromatin and mass-spectrometry analysis of its interactions identified only proteins known to bind the p12 region of Gag. Surprisingly, the ability to interact with chromatin was conferred by a single amino acid change, M63I, in the p12 CTD. Interestingly, GST-p12_M63I showed increased phosphorylation in mitosis relative to interphase, which correlated with an increased interaction with mitotic chromatin. Mass-spectrometry analysis of GST-p12_M63I revealed nucleosomal histones as primary interactants. Direct binding of MLV p12_M63I peptides to histones was confirmed by biolayer-interferometry (BLI) assays using highly-avid recombinant poly-nucleosomal arrays. Excitingly, using this method, we also observed binding between MLV p12_WT and nucleosomes. Nucleosome binding was additionally detected with p12 orthologs from feline and gibbon ape leukemia viruses using both pull-down and BLI assays, indicating that this a common feature of gammaretroviral p12 proteins. Importantly, p12 peptides were able to block the binding of the prototypic foamy virus CBS to nucleosomes and vice versa, implying that their docking sites overlap and suggesting a conserved mode of chromatin tethering for different retroviral genera. We propose that p12 is acting in a similar capacity to CPSF6 in HIV-1 infection by facilitating initial chromatin targeting of CA-containing PICs prior to integration.

APC/C Dysfunction Limits Excessive Cancer Chromosomal Instability

Intercellular heterogeneity, exacerbated by chromosomal instability (CIN), fosters tumor heterogeneity and drug resistance. However, extreme CIN correlates with improved cancer outcome, suggesting that karyotypic diversity required to adapt to selection pressures might be balanced in tumors against the risk of excessive instability. Here, we used a functional genomics screen, genome editing, and pharmacologic approaches to identify CIN-survival factors in diploid cells. We find partial anaphase-promoting complex/cyclosome (APC/C) dysfunction lengthens mitosis, suppresses pharmacologically induced chromosome segregation errors, and reduces naturally occurring lagging chromosomes in cancer cell lines or following tetraploidization. APC/C impairment caused adaptation to MPS1 inhibitors, revealing a likely resistance mechanism to therapies targeting the spindle assembly checkpoint. Finally, CRISPR-mediated introduction of cancer somatic mutations in the APC/C subunit cancer driver gene CDC27 reduces chromosome segregation errors, whereas reversal of an APC/C subunit nonsense mutation increases CIN. Subtle variations in mitotic duration, determined by APC/C activity, influence the extent of CIN, allowing cancer cells to dynamically optimize fitness during tumor evolution.

SIGNIFICANCE

We report a mechanism whereby cancers balance the evolutionary advantages associated with CIN against the fitness costs caused by excessive genome instability, providing insight into the consequence of CDC27 APC/C subunit driver mutations in cancer. Lengthening of mitosis through APC/C modulation may be a common mechanism of resistance to cancer therapeutics that increase chromosome segregation errors. Cancer Discov; 7(2); 218-33. ©2017 AACR.See related commentary by Burkard and Weaver, p. 134This article is highlighted in the In This Issue feature, p. 115.

Isoform diversity in the Arp2/3 complex determines actin filament dynamics

The Arp2/3 complex consists of seven evolutionarily conserved subunits (Arp2, Arp3 and ARPC1-5) and plays an essential role in generating branched actin filament networks during many different cellular processes. In mammals, however, the ARPC1 and ARPC5 subunits are each encoded by two isoforms that are 67% identical. This raises the possibility that Arp2/3 complexes with different properties may exist.  We found that Arp2/3 complexes containing ARPC1B and ARPC5L are significantly better at promoting actin assembly than those with ARPC1A and ARPC5, both in cells and in vitro. Branched actin networks induced by complexes containing ARPC1B or ARPC5L are also disassembled ∼2-fold slower than those formed by their counterparts. This difference reflects the ability of cortactin to stabilize ARPC1B- and ARPC5L- but not ARPC1A- and ARPC5-containing complexes against coronin-mediated disassembly. Our observations demonstrate that the Arp2/3 complex in higher eukaryotes is actually a family of complexes with different properties.

Automated analysis of filamentous microbial morphology with AnaMorf

The morphological quantification of filamentous microbes represents an important analytical technique in the optimization of bioprocesses involving such organisms, given the demonstrated links between morphology and metabolite yield. However, in many studies, much of this quantification has required some degree of manual intervention, if it has been conducted at all, burdening biotechnologists with a time-consuming process and potentially introducing bias into analyses. Here, software for the automated quantification of filamentous microbes is presented, implemented as a plug-in for the widely used, freely available image analysis package, ImageJ. The software, together with all related source code, documentation and test data, is freely available to the community via an online repository.

Open source software for quantification of cell migration, protrusions, and fluorescence intensities

ADAPT is an ImageJ plug-in that can be used for rapid whole-cell analysis of time-lapse videos, thereby providing data on cell morphology, membrane velocity, and temporal changes in any fluorescent protein of interest at the cell periphery, as exemplified by the morphological characterization of cellular blebs.

Cell migration is frequently accompanied by changes in cell morphology (morphodynamics) on a range of spatial and temporal scales. Despite recent advances in imaging techniques, the application of unbiased computational image analysis methods for morphodynamic quantification is rare. For example, manual analysis using kymographs is still commonplace, often caused by lack of access to user-friendly, automated tools. We now describe software designed for the automated quantification of cell migration and morphodynamics. Implemented as a plug-in for the open-source platform, ImageJ, ADAPT is capable of rapid, automated analysis of migration and membrane protrusions, together with associated fluorescently labeled proteins, across multiple cells. We demonstrate the ability of the software by quantifying variations in cell population migration rates on different extracellular matrices. We also show that ADAPT can detect and morphologically profile filopodia. Finally, we have used ADAPT to compile an unbiased description of a “typical” bleb formed at the plasma membrane and quantify the effect of Arp2/3 complex inhibition on bleb retraction.

The Escherichia coli effector EspJ blocks Src kinase activity via amidation and ADP ribosylation

The hallmark of enteropathogenic Escherichia coli (EPEC) infection is the formation of actin-rich pedestal-like structures, which are generated following phosphorylation of the bacterial effector Tir by cellular Src and Abl family tyrosine kinases. This leads to recruitment of the Nck-WIP-N-WASP complex that triggers Arp2/3-dependent actin polymerization in the host cell. The same phosphorylation-mediated signalling network is also assembled downstream of the Vaccinia virus protein A36 and the phagocytic Fc-gamma receptor FcγRIIa. Here we report that the EPEC type-III secretion system effector EspJ inhibits autophosphorylation of Src and phosphorylation of the Src substrates Tir and FcγRIIa. Consistent with this, EspJ inhibits actin polymerization downstream of EPEC, Vaccinia virus and opsonized red blood cells. We identify EspJ as a unique adenosine diphosphate (ADP) ribosyltransferase that directly inhibits Src kinase by simultaneous amidation and ADP ribosylation of the conserved kinase-domain residue, Src E310, resulting in glutamine-ADP ribose.

Ena/VASP proteins cooperate with the WAVE complex to regulate the actin cytoskeleton

Ena/VASP proteins and the WAVE regulatory complex (WRC) regulate cell motility by virtue of their ability to independently promote actin polymerization. We demonstrate that Ena/VASP and the WRC control actin polymerization in a cooperative manner through the interaction of the Ena/VASP EVH1 domain with an extended proline rich motif in Abi. This interaction increases cell migration and enables VASP to cooperatively enhance WRC stimulation of Arp2/3 complex-mediated actin assembly in vitro in the presence of Rac. Loss of this interaction in Drosophila macrophages results in defects in lamellipodia formation, cell spreading, and redistribution of Ena to the tips of filopodia-like extensions. Rescue experiments of abi mutants also reveals a physiological requirement for the Abi:Ena interaction in photoreceptor axon targeting and oogenesis. Our data demonstrate that the activities of Ena/VASP and the WRC are intimately linked to ensure optimal control of actin polymerization during cell migration and development.

Clathrin potentiates vaccinia-induced actin polymerization to facilitate viral spread

During their egress, newly assembled vaccinia virus particles fuse with the plasma membrane and enhance their spread by inducing Arp2/3-dependent actin polymerization. Investigating the events surrounding vaccinia virus fusion, we discovered that vaccinia transiently recruits clathrin in a manner dependent on the clathrin adaptor AP-2. The recruitment of clathrin to vaccinia dramatically enhances the ability of the virus to induce actin-based motility. We demonstrate that clathrin promotes clustering of the virus actin tail nucleator A36 and host N-WASP, which activates actin nucleation through the Arp2/3 complex. Increased clustering enhances N-WASP stability, leading to more efficient actin tail initiation and sustained actin polymerization. Our observations uncover an unexpected role for clathrin during virus spread and have important implications for the regulation of actin polymerization.

Morphological quantification of filamentous fungal development using membrane immobilization and automatic image analysis

Mycelial morphology is a critically important process property in industrial fermentations of filamentous micro-organisms, as particular phenotypes are associated with maximum productivity. However, the accurate quantification of complex morphologies still represents a significant challenge in elucidating this relationship. A system has been developed for high-resolution characterisation of filamentous fungal growth on a solid substrate, using membrane immobilization and fully-automatic plug-ins developed for the public domain, Java-based, image-processing software, ImageJ. The system has been used to quantify the microscopic development of Aspergillus oryzae on malt agar, by measuring spore projected area and circularity, the total length of a hyphal element, the number of tips per element, and the hyphal growth unit. Two different stages of growth are described, from the swelling of a population of conidiospores up to fully developed, branched hyphae 24 h after inoculation. Spore swelling expressed as an increase in mean equivalent spore diameter was found to be approximately linear with time. Widespread germination of spores was observed by 8 h after inoculation. From approximately 12 h, the number of tips was found to increase exponentially. The specific growth rate of a population of hyphae was calculated as approximately 0.24-0.27 h(-1). A wide variation in growth kinetics was found within the population. The robustness of the image-analysis system was verified by testing the effect of small variations in the input data.

Treatment outcomes in an integrated civilian and prison MDR-TB treatment program in Russia

SETTING

Multidrug-resistant tuberculosis (MDR-TB) is a major problem in countries of the former Soviet Union in both the civilian and prison sectors.

OBJECTIVE

To evaluate outcomes of the MDR-TB treatment program (DOTS-Plus) in Tomsk, Russia.

DESIGN

Retrospective case series of all patients enrolled in this program between 10 September 2000 and 10 September 2002. The program involves both the civilian and penitentiary TB services in Tomsk. Poor treatment outcome was defined as death, default and treatment failure.

RESULTS

Among the 244 patients who received treatment, 77% were cured, 5% died, 7% failed, and 12% defaulted. In a multivariable analysis, alcohol consumption during treatment and the presence of both cavitary and bilateral disease were found to be the strongest predictors of poor treatment outcome.

CONCLUSIONS

The integration of civilian and penitentiary TB services in the Tomsk MDR-TB treatment program has resulted in high cure rates and low rates of default. However, alcohol use among patients with MDR-TB is associated with poor treatment outcomes. Better understanding and programmatic alcohol interventions are needed if large-scale treatment of MDR-TB is to be successful in areas with high rates of alcohol use disorders.

An algorithm for the treatment of schizophrenia in the correctional setting: the Forensic Algorithm Project

The Forensic Algorithm Project (FAP) was born of the need for a holistic approach in the treatment of the inmate with schizophrenia. Schizophrenia was chosen as the first entity to be addressed by the algorithm because of its refractory nature and high rate of recidivism in the correctional setting. Schizophrenia is regarded as a spectrum disorder, with symptom clusters and behaviors ranging from positive to negative symptoms to neurocognitive dysfunction and affective instability. Furthermore, the clinical picture is clouded by Axis II symptomatology (particularly prominent in the inmate population), comorbid Axis I disorders, and organicity. Four subgroups of schizophrenia were created to coincide with common clinical presentations in the forensic inpatient facility and also to parallel 4 tracks of intervention, consisting of pharmacologic management and programming recommendations. The algorithm begins with any antipsychotic medication and proceeds to atypical neuroleptic usage, augmentation with other psychotropic agents, and, finally, the use of clozapine as the common pathway for refractory schizophrenia. Outcome measurement of pharmacologic intervention is assessed every 6 weeks through the use of a 4-item subscale, specific for each forensic subgroup. A "floating threshold" of 40% symptom severity reduction on Positive and Negative Syndrome Scale and Brief Psychiatric Rating Scale items over a 6-week period is considered an indication for neuroleptic continuation. The forensic algorithm differs from other clinical practice guidelines in that specific programming in certain prison environments is stipulated. Finally, a social commentary on the importance of state-of-the-art psychiatric treatment for all members of society is woven into the clinical tapestry of this article.