Mesophilic and Thermophilic Anaerobic Digestion of Wheat Straw in a CSTR System with 'Synthetic Manure': Impact of Nickel and Tungsten on Methane Yields, Cell Count, and Microbiome.

Lignocellulosic residues, such as straw, are currently considered as candidates for biogas production. Therefore, straw fermentations were performed to quantitatively estimate methane yields and cell counts, as well as to qualitatively determine the microbiome. Six fully automated, continuously stirred biogas reactors were used: three mesophilic (41 °C) and three thermophilic (58 °C). They were fed every 8 h with milled wheat straw suspension in a defined, buffered salt solution, called 'synthetic manure'. Total reflection X-ray fluorescence spectrometry analyses showed nickel and tungsten deficiency in the straw suspension. Supplementation of nickel and subsequently tungsten, or with an increasing combined dosage of both elements, resulted in a final concentration of approximately 0.1 mg/L active, dissolved tungsten ions, which caused an increase of the specific methane production, up to 63% under mesophilic and 31% under thermophilic conditions. That is the same optimal range for pure cultures of methanogens or bacteria found in literature. A simultaneous decrease of volatile fatty acids occurred. The Ni/W effect occurred with all three organic loading rates, being 4.5, 7.5, and 9.0 g volatile solids per litre and day, with a concomitant hydraulic retention time of 18, 10, or 8 days, respectively. A maximum specific methane production of 0.254 m3 CH4, under standard temperature and pressure per kg volatile solids (almost 90% degradation), was obtained. After the final supplementation of tungsten, the cell counts of methanogens increased by 300%, while the total microbial cell counts increased by only 3-62%. The mesophilic methanogenic microflora was shifted from the acetotrophic Methanosaeta to the hydrogenotrophic Methanoculleus (85%) by tungsten, whereas the H2-CO2-converter, Methanothermobacter, always dominated in the thermophilic fermenters.

Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases.

MOTIVATION: Gene expression data are commonly used at the intersection of cancer research and machine learning for better understanding of the molecular status of tumour tissue. Deep learning predictive models have been employed for gene expression data due to their ability to scale and remove the need for manual feature engineering. However, gene expression data are often very high dimensional, noisy and presented with a low number of samples. This poses significant problems for learning algorithms: models often overfit, learn noise and struggle to capture biologically relevant information. In this article, we utilize external biological knowledge embedded within structures of gene interaction graphs such as protein-protein interaction (PPI) networks to guide the construction of predictive models. RESULTS: We present Gene Interaction Network Constrained Construction (GINCCo), an unsupervised method for automated construction of computational graph models for gene expression data that are structurally constrained by prior knowledge of gene interaction networks. We employ this methodology in a case study on incorporating a PPI network in cancer phenotype prediction tasks. Our computational graphs are structurally constructed using topological clustering algorithms on the PPI networks which incorporate inductive biases stemming from network biology research on protein complex discovery. Each of the entities in the GINCCo computational graph represents biological entities such as genes, candidate protein complexes and phenotypes instead of arbitrary hidden nodes of a neural network. This provides a biologically relevant mechanism for model regularization yielding strong predictive performance while drastically reducing the number of model parameters and enabling guided post-hoc enrichment analyses of influential gene sets with respect to target phenotypes. Our experiments analysing a variety of cancer phenotypes show that GINCCo often outperforms support vector machine, Fully Connected Multi-layer Perceptrons (MLP) and Randomly Connected MLPs despite greatly reduced model complexity. AVAILABILITY AND IMPLEMENTATION: https://github.com/paulmorio/gincco contains the source code for our approach. We also release a library with algorithms for protein complex discovery within PPI networks at https://github.com/paulmorio/protclus. This repository contains implementations of the clustering algorithms used in this article. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice.

International initiatives such as the Molecular Taxonomy of Breast Cancer International Consortium are collecting multiple data sets at different genome-scales with the aim to identify novel cancer bio-markers and predict patient survival. To analyze such data, several machine learning, bioinformatics, and statistical methods have been applied, among them neural networks such as autoencoders. Although these models provide a good statistical learning framework to analyze multi-omic and/or clinical data, there is a distinct lack of work on how to integrate diverse patient data and identify the optimal design best suited to the available data.In this paper, we investigate several autoencoder architectures that integrate a variety of cancer patient data types (e.g., multi-omics and clinical data). We perform extensive analyses of these approaches and provide a clear methodological and computational framework for designing systems that enable clinicians to investigate cancer traits and translate the results into clinical applications. We demonstrate how these networks can be designed, built, and, in particular, applied to tasks of integrative analyses of heterogeneous breast cancer data. The results show that these approaches yield relevant data representations that, in turn, lead to accurate and stable diagnosis.

Metagenome, metatranscriptome, and metaproteome approaches unraveled compositions and functional relationships of microbial communities residing in biogas plants.

The production of biogas by anaerobic digestion (AD) of agricultural residues, organic wastes, animal excrements, municipal sludge, and energy crops has a firm place in sustainable energy production and bio-economy strategies. Focusing on the microbial community involved in biomass conversion offers the opportunity to control and engineer the biogas process with the objective to optimize its efficiency. Taxonomic profiling of biogas producing communities by means of high-throughput 16S rRNA gene amplicon sequencing provided high-resolution insights into bacterial and archaeal structures of AD assemblages and their linkages to fed substrates and process parameters. Commonly, the bacterial phyla Firmicutes and Bacteroidetes appeared to dominate biogas communities in varying abundances depending on the apparent process conditions. Regarding the community of methanogenic Archaea, their diversity was mainly affected by the nature and composition of the substrates, availability of nutrients and ammonium/ammonia contents, but not by the temperature. It also appeared that a high proportion of 16S rRNA sequences can only be classified on higher taxonomic ranks indicating that many community members and their participation in AD within functional networks are still unknown. Although cultivation-based approaches to isolate microorganisms from biogas fermentation samples yielded hundreds of novel species and strains, this approach intrinsically is limited to the cultivable fraction of the community. To obtain genome sequence information of non-cultivable biogas community members, metagenome sequencing including assembly and binning strategies was highly valuable. Corresponding research has led to the compilation of hundreds of metagenome-assembled genomes (MAGs) frequently representing novel taxa whose metabolism and lifestyle could be reconstructed based on nucleotide sequence information. In contrast to metagenome analyses revealing the genetic potential of microbial communities, metatranscriptome sequencing provided insights into the metabolically active community. Taking advantage of genome sequence information, transcriptional activities were evaluated considering the microorganism's genetic background. Metaproteome studies uncovered enzyme profiles expressed by biogas community members. Enzymes involved in cellulose and hemicellulose decomposition and utilization of other complex biopolymers were identified. Future studies on biogas functional microbial networks will increasingly involve integrated multi-omics analyses evaluating metagenome, transcriptome, proteome, and metabolome datasets.

TRPV1 is a physiological regulator of µ-opioid receptors.

Opioids are powerful analgesics, but also carry significant side effects and abuse potential. Here we describe a modulator of the µ-opioid receptor (MOR1), the transient receptor potential channel subfamily vanilloid member 1 (TRPV1). We show that TRPV1 binds MOR1 and blocks opioid-dependent phosphorylation of MOR1 while leaving G protein signaling intact. Phosphorylation of MOR1 initiates recruitment and activation of the ß-arrestin pathway, which is responsible for numerous opioid-induced adverse effects, including the development of tolerance and respiratory depression. Phosphorylation stands in contrast to G protein signaling, which is responsible for the analgesic effect of opioids. Calcium influx through TRPV1 causes a calcium/calmodulin-dependent translocation of G protein-coupled receptor kinase 5 (GRK5) away from the plasma membrane, thereby blocking its ability to phosphorylate MOR1. Using TRPV1 to block phosphorylation of MOR1 without affecting G protein signaling is a potential strategy to improve the therapeutic profile of opioids.

Genomics and prevalence of bacterial and archaeal isolates from biogas-producing microbiomes.

BACKGROUND: To elucidate biogas microbial communities and processes, the application of high-throughput DNA analysis approaches is becoming increasingly important. Unfortunately, generated data can only partialy be interpreted rudimentary since databases lack reference sequences. RESULTS: Novel cellulolytic, hydrolytic, and acidogenic/acetogenic Bacteria as well as methanogenic Archaea originating from different anaerobic digestion communities were analyzed on the genomic level to assess their role in biomass decomposition and biogas production. Some of the analyzed bacterial strains were recently described as new species and even genera, namely Herbinix hemicellulosilytica T3/55T, Herbinix luporum SD1DT, Clostridium bornimense M2/40T, Proteiniphilum saccharofermentans M3/6T, Fermentimonas caenicola ING2-E5BT, and Petrimonas mucosa ING2-E5AT. High-throughput genome sequencing of 22 anaerobic digestion isolates enabled functional genome interpretation, metabolic reconstruction, and prediction of microbial traits regarding their abilities to utilize complex bio-polymers and to perform specific fermentation pathways. To determine the prevalence of the isolates included in this study in different biogas systems, corresponding metagenome fragment mappings were done. Methanoculleus bourgensis was found to be abundant in three mesophilic biogas plants studied and slightly less abundant in a thermophilic biogas plant, whereas Defluviitoga tunisiensis was only prominent in the thermophilic system. Moreover, several of the analyzed species were clearly detectable in the mesophilic biogas plants, but appeared to be only moderately abundant. Among the species for which genome sequence information was publicly available prior to this study, only the species Amphibacillus xylanus, Clostridium clariflavum, and Lactobacillus acidophilus are of importance for the biogas microbiomes analyzed, but did not reach the level of abundance as determined for M. bourgensis and D. tunisiensis. CONCLUSIONS: Isolation of key anaerobic digestion microorganisms and their functional interpretation was achieved by application of elaborated cultivation techniques and subsequent genome analyses. New isolates and their genome information extend the repository covering anaerobic digestion community members.

Measuring G-protein-coupled Receptor Signaling via Radio-labeled GTP Binding.

G-Protein-Coupled Receptors (GPCRs) are a large family of transmembrane receptors that play critical roles in normal cellular physiology and constitute a major pharmacological target for multiple indications, including analgesia, blood pressure regulation, and the treatment of psychiatric disease. Upon ligand binding, GPCRs catalyze the activation of intracellular G-proteins by stimulating the incorporation of guanosine triphosphate (GTP). Activated G-proteins then stimulate signaling pathways that elicit cellular responses. GPCR signaling can be monitored by measuring the incorporation of a radiolabeled and non-hydrolyzable form of GTP, [35S]guanosine-5'-O-(3-thio)triphosphate ([35S]GTPγS), into G-proteins. Unlike other methods that assess more downstream signaling processes, [35S]GTPγS binding measures a proximal event in GPCR signaling and, importantly, can distinguish agonists, antagonists, and inverse agonists. The present protocol outlines a sensitive and specific method for studying GPCR signaling using crude membrane preparations of an archetypal GPCR, the µ-opioid receptor (MOR1). Although alternative approaches to fractionate cells and tissues exist, many are cost-prohibitive, tedious, and/or require non-standard laboratory equipment. The present method provides a simple procedure that enriches functional crude membranes. After isolating MOR1, various pharmacological properties of its agonist, [D-Ala, N-MePhe, Gly-ol]-enkephalin (DAMGO), and antagonist, naloxone, were determined.

Genome sequence of Methanobacterium congolense strain Buetzberg, a hydrogenotrophic, methanogenic archaeon, isolated from a mesophilic industrial-scale biogas plant utilizing bio-waste.

Methanogenic Archaea are of importance at the end of the anaerobic digestion (AD) chain for biomass conversion. They finally produce methane, the end-product of AD. Among this group of microorganisms, members of the genus Methanobacterium are ubiquitously present in anaerobic habitats, such as bioreactors. The genome of a novel methanogenic archaeon, namely Methanobacterium congolense Buetzberg, originally isolated from a mesophilic biogas plant, was completely sequenced to analyze putative adaptive genome features conferring competitiveness of this isolate within the biogas reactor environment. Sequencing and assembly of the M. congolense Buetzberg genome yielded a chromosome with a size of 2,451,457bp and a mean GC-content of 38.51%. Additionally, a plasmid with a size of 18,118bp, featuring a GC content of 36.05% was identified. The M. congolense Buetzberg plasmid showed no sequence similarities with the plasmids described previously suggesting that it represents a new plasmid type. Analysis of the M. congolense Buetzberg chromosome architecture revealed a high collinearity with the Methanobacterium paludis chromosome. Furthermore, annotation of the genome and functional predictions disclosed several genes involved in cell wall and membrane biogenesis. Compilation of specific genes among Methanobacterium strains originating from AD environments revealed 474 genetic determinants that could be crucial for adaptation of these strains to specific conditions prevailing in AD habitats.

Biphasic Study to Characterize Agricultural Biogas Plants by High-Throughput 16S rRNA Gene Amplicon Sequencing and Microscopic Analysis.

Process surveillance within agricultural biogas plants (BGPs) was concurrently studied by high-throughput 16S rRNA gene amplicon sequencing and an optimized quantitative microscopic fingerprinting (QMF) technique. In contrast to 16S rRNA gene amplicons, digitalized microscopy is a rapid and cost-effective method that facilitates enumeration and morphological differentiation of the most significant groups of methanogens regarding their shape and characteristic autofluorescent factor 420. Moreover, the fluorescence signal mirrors cell vitality. In this study, four different BGPs were investigated. The results indicated stable process performance in the mesophilic BGPs and in the thermophilic reactor. Bacterial subcommunity characterization revealed significant differences between the four BGPs. Most remarkably, the genera Defluviitoga and Halocella dominated the thermophilic bacterial subcommunity, whereas members of another taxon, Syntrophaceticus, were found to be abundant in the mesophilic BGP. The domain Archaea was dominated by the genus Methanoculleus in all four BGPs, followed by Methanosaeta in BGP1 and BGP3. In contrast, Methanothermobacter members were highly abundant in the thermophilic BGP4. Furthermore, a high consistency between the sequencing approach and the QMF method was shown, especially for the thermophilic BGP. The differences elucidated that using this biphasic approach for mesophilic BGPs provided novel insights regarding disaggregated single cells of Methanosarcina and Methanosaeta species. Both dominated the archaeal subcommunity and replaced coccoid Methanoculleus members belonging to the same group of Methanomicrobiales that have been frequently observed in similar BGPs. This work demonstrates that combining QMF and 16S rRNA gene amplicon sequencing is a complementary strategy to describe archaeal community structures within biogas processes.

Unraveling the microbiome of a thermophilic biogas plant by metagenome and metatranscriptome analysis complemented by characterization of bacterial and archaeal isolates.

BACKGROUND: One of the most promising technologies to sustainably produce energy and to mitigate greenhouse gas emissions from combustion of fossil energy carriers is the anaerobic digestion and biomethanation of organic raw material and waste towards biogas by highly diverse microbial consortia. In this context, the microbial systems ecology of thermophilic industrial-scale biogas plants is poorly understood. RESULTS: The microbial community structure of an exemplary thermophilic biogas plant was analyzed by a comprehensive approach comprising the analysis of the microbial metagenome and metatranscriptome complemented by the cultivation of hydrolytic and acido-/acetogenic Bacteria as well as methanogenic Archaea. Analysis of metagenome-derived 16S rRNA gene sequences revealed that the bacterial genera Defluviitoga (5.5 %), Halocella (3.5 %), Clostridium sensu stricto (1.9 %), Clostridium cluster III (1.5 %), and Tepidimicrobium (0.7 %) were most abundant. Among the Archaea, Methanoculleus (2.8 %) and Methanothermobacter (0.8 %) were predominant. As revealed by a metatranscriptomic 16S rRNA analysis, Defluviitoga (9.2 %), Clostridium cluster III (4.8 %), and Tepidanaerobacter (1.1 %) as well as Methanoculleus (5.7 %) mainly contributed to these sequence tags indicating their metabolic activity, whereas Hallocella (1.8 %), Tepidimicrobium (0.5 %), and Methanothermobacter (<0.1 %) were transcriptionally less active. By applying 11 different cultivation strategies, 52 taxonomically different microbial isolates representing the classes Clostridia, Bacilli, Thermotogae, Methanomicrobia and Methanobacteria were obtained. Genome analyses of isolates support the finding that, besides Clostridium thermocellum and Clostridium stercorarium, Defluviitoga tunisiensis participated in the hydrolysis of hemicellulose producing ethanol, acetate, and H2/CO2. The latter three metabolites are substrates for hydrogentrophic and acetoclastic archaeal methanogenesis. CONCLUSIONS: Obtained results showed that high abundance of microorganisms as deduced from metagenome analysis does not necessarily indicate high transcriptional or metabolic activity, and vice versa. Additionally, it appeared that the microbiome of the investigated thermophilic biogas plant comprised a huge number of up to now unknown and insufficiently characterized species.

Inositol hexakisphosphate (IP6) generated by IP5K mediates cullin-COP9 signalosome interactions and CRL function.

The family of cullin-RING E3 Ligases (CRLs) and the constitutive photomorphogenesis 9 (COP9) signalosome (CSN) form dynamic complexes that mediate ubiquitylation of 20% of the proteome, yet regulation of their assembly/disassembly remains poorly understood. Inositol polyphosphates are highly conserved signaling molecules implicated in diverse cellular processes. We now report that inositol hexakisphosphate (IP6) is a major physiologic determinant of the CRL-CSN interface, which includes a hitherto unidentified electrostatic interaction between the N-terminal acidic tail of CSN subunit 2 (CSN2) and a conserved basic canyon on cullins. IP6, with an EC50 of 20 nM, acts as an intermolecular "glue," increasing cullin-CSN2 binding affinity by 30-fold, thereby promoting assembly of the inactive CRL-CSN complexes. The IP6 synthase, Ins(1,3,4,5,6)P5 2-kinase (IPPK/IP5K) binds to cullins. Depleting IP5K increases the percentage of neddylated, active Cul1 and Cul4A, and decreases levels of the Cul1/4A substrates p27 and p21. Besides dysregulating CRL-mediated cell proliferation and UV-induced apoptosis, IP5K depletion potentiates by 28-fold the cytotoxic effect of the neddylation inhibitor MLN4924. Thus, IP5K and IP6 are evolutionarily conserved components of the CRL-CSN system and are potential targets for cancer therapy in conjunction with MLN4924.

Dual investigation of methanogenic processes by quantitative PCR and quantitative microscopic fingerprinting.

Monitoring of methanogenic communities in anaerobic digesters using molecular-based methods is very attractive but can be cost-intensive. A new and fast quantification method by microscopic image analysis was developed to accompany molecular-based methods. This digitalized method, called quantitative microscopic fingerprinting (QMF), enables quantification of active methanogenic cells (N mL(-1)) by their characteristic auto-fluorescence based on coenzyme F420 . QMF was applied to analyze the methanogenic communities in three biogas plant samples, and the results were compared with the relative proportion of gene copy numbers obtained with the quantitative PCR (qPCR). Analysis of QMF demonstrated dominance of Methanomicrobiales and Methanobacteriales in relation to the total methanogenic community in digesters operating at high ammonia concentrations, which corresponded to the results established by qPCR. Absolute microbial counts by QMF and the numbers obtained by qPCR were not always comparable. On the other hand, the restricted morphological analysis by QMF was enhanced by the capability of qPCR to identify microbes. Consequently, dual investigations of both methods are proposed to improve monitoring of anaerobic digesters. For a rough estimation of the methanogenic composition in anaerobic digesters, the QMF method seems to be a promising approach for the rapid detection of microbial changes.

Effect of shoe flexibility on plantar loading in children learning to walk.

BACKGROUND: In a previous pilot study of "cruisers" (nonindependent ambulation), "early walkers" (independent ambulation for 0-5 months), and "experienced walkers" (independent ambulation for 6-12 months), developmental age significantly affected the children's stability when walking and performing functional activities. We sought to examine how shoe structural characteristics affect plantar pressure distribution in early walkers. METHODS: Torsional flexibility was evaluated in four shoe designs (UltraFlex, MedFlex, LowFlex, and Stiff based on decreasing relative flexibility) with a structural testing machine. Plantar pressures were recorded in 25 early walkers while barefoot and shod at self-selected walking speeds. Peak pressure was calculated over ten masked regions for the barefoot and shod conditions. RESULTS: Torsional flexibility, the angular rotation divided by the applied moment about the long axis of the shoe, was different across the four shoe designs. As expected, UltraFlex was the most flexible and Stiff was the least flexible. As applied moment increased, torsional flexibility decreased in all footwear. When evaluating early walkers during gait, peak pressure was significantly different across shoe conditions for all of the masked regions. The stiffest shoe had the lowest peak pressures and the most flexible shoe had the highest. CONCLUSIONS: It is likely that increased shoe flexibility promoted greater plantar loading. Plantar pressures while wearing the most flexible shoe are similar to those while barefoot. This mechanical feedback may enhance proprioception, which is a desirable attribute for children learning to walk.

Potential impact of process parameters upon the bacterial diversity in the mesophilic anaerobic digestion of beet silage.

The impact of the process parameters hydraulic retention time (HRT), organic loading rate (OLR) and substrate upon bacterial diversity was analyzed. Therefore, a controlled anaerobic fermentation (1755 days) of beet silage, only initially inoculated with manure, was monitored by the amplified "ribosomal DNA" restriction analysis. More than 85% of detected operational taxonomic units (OTUs) could not be assigned to described Bacteria. In contrast to studies analyzing the digestion of energy crops in the presence of manure, Chloroflexi were detected, whereas Clostridia and Chloroflexi were identified as persistent groups. Both groups are known as potential hydrogen producers or users. Species distribution patterns for Firmicutes, Bacteroidetes, Synergistetes and Thermotogae were not clearly linked to process parameters. The presence of Planctomycetes, Actinobacteria and Alcaligenaceae was related to long HRTs and short OLRs, while Acidobacteria were governed by short HRTs and high OLRs, respectively. The impact of substrate variations on diversity was minute.

Neural and synaptic defects in slytherin, a zebrafish model for human congenital disorders of glycosylation.

Congenital disorder of glycosylation type IIc (CDG IIc) is characterized by mental retardation, slowed growth and severe immunodeficiency, attributed to the lack of fucosylated glycoproteins. While impaired Notch signaling has been implicated in some aspects of CDG IIc pathogenesis, the molecular and cellular mechanisms remain poorly understood. We have identified a zebrafish mutant slytherin (srn), which harbors a missense point mutation in GDP-mannose 4,6 dehydratase (GMDS), the rate-limiting enzyme in protein fucosylation, including that of Notch. Here we report that some of the mechanisms underlying the neural phenotypes in srn and in CGD IIc are Notch-dependent, while others are Notch-independent. We show, for the first time in a vertebrate in vivo, that defects in protein fucosylation leads to defects in neuronal differentiation, maintenance, axon branching, and synapse formation. Srn is thus a useful and important vertebrate model for human CDG IIc that has provided new insights into the neural phenotypes that are hallmarks of the human disorder and has also highlighted the role of protein fucosylation in neural development.

Mesophilic fermentation of renewable biomass: does hydraulic retention time regulate methanogen diversity?

The present long-term study (about 1,100 days) monitored the diversity of methanogens during the mesophilic, anaerobic digestion of beet silage. Six fermentor samples were analyzed by ribosomal RNA gene restriction analysis, fluorescence in situ hybridization, and fluorescence microscopy. Hydrogenotrophic methanogens dominated within the population in all samples analyzed. Multidimensional scaling revealed that a rapid decrease in hydraulic retention time resulted in increased species richness, which in turn led to slightly higher CH(4) yields.

Mechanisms underlying metabolic and neural defects in zebrafish and human multiple acyl-CoA dehydrogenase deficiency (MADD).

In humans, mutations in electron transfer flavoprotein (ETF) or electron transfer flavoprotein dehydrogenase (ETFDH) lead to MADD/glutaric aciduria type II, an autosomal recessively inherited disorder characterized by a broad spectrum of devastating neurological, systemic and metabolic symptoms. We show that a zebrafish mutant in ETFDH, xavier, and fibroblast cells from MADD patients demonstrate similar mitochondrial and metabolic abnormalities, including reduced oxidative phosphorylation, increased aerobic glycolysis, and upregulation of the PPARG-ERK pathway. This metabolic dysfunction is associated with aberrant neural proliferation in xav, in addition to other neural phenotypes and paralysis. Strikingly, a PPARG antagonist attenuates aberrant neural proliferation and alleviates paralysis in xav, while PPARG agonists increase neural proliferation in wild type embryos. These results show that mitochondrial dysfunction, leading to an increase in aerobic glycolysis, affects neurogenesis through the PPARG-ERK pathway, a potential target for therapeutic intervention.

Effect of functional foot orthoses on first metatarsophalangeal joint dorsiflexion in stance and gait.

Reduction in first metatarsophalangeal joint maximum degree of dorsiflexion with dorsiflexion of the first ray has been proposed to be the predominant cause of hallux abducto valgus and hallux rigidus. We sought to determine whether orthoses made from a cast with the first ray plantarflexed and a 4-mm medial skive could increase the maximum degree of dorsiflexion in patients with functional hallux limitus in stance and gait. Forty-eight feet of 27 subjects were casted for orthoses with the first ray plantarflexed and in the customary neutral rearfoot position with locked midtarsal joint. First metatarsophalangeal joint maximum dorsiflexion was measured with and without orthoses in stance, and subhallux pressure was measured with and without orthoses at heel-off. Changes in mean maximum dorsiflexion in stance and in mean maximum subhallux pressure in gait with orthoses were significant. We investigated the relationship between this increase in dorsiflexion and gender, shoe size, resting calcaneal stance position, and change in resting calcaneal stance position with the use of orthoses. These correlations were not statistically significant. The biomechanical implication of increasing limited first metatarsophalangeal joint dorsiflexion with orthoses is discussed and related to the clinical treatment of deformities, including hallux valgus and hallux rigidus. The use of orthoses to decrease subhallux pressure is also discussed.