Using machine learning to enhance prediction of atrial fibrillation recurrence after catheter ablation.

Background: Traditional risk scores for recurrent atrial fibrillation (AF) following catheter ablation utilize readily available clinical and echocardiographic variables and yet have limited discriminatory capacity. Use of data from cardiac imaging and deep learning may help improve accuracy and prediction of recurrent AF after ablation. Methods: We evaluated patients with symptomatic, drug-refractory AF undergoing catheter ablation. All patients underwent pre-ablation cardiac computed tomography (cCT). LAVi was computed using a deep-learning algorithm. In a two-step analysis, random survival forest (RSF) was used to generate prognostic models with variables of highest importance, followed by Cox proportional hazard regression analysis of the selected variables. Events of interest included early and late recurrence. Results: Among 653 patients undergoing AF ablation, the most important factors associated with late recurrence by RSF analysis at 24 (+/-18) months follow-up included LAVi and early recurrence. In total, 5 covariates were identified as independent predictors of late recurrence: LAVi (HR per mL/m2 1.01 [1.01-1.02]; p < .001), early recurrence (HR 2.42 [1.90-3.09]; p < .001), statin use (HR 1.38 [1.09-1.75]; p = .007), beta-blocker use (HR 1.29 [1.01-1.65]; p = .043), and adjunctive cavotricuspid isthmus ablation [HR 0.74 (0.57-0.96); p = .02]. Survival analysis demonstrated that patients with both LAVi >66.7 mL/m2 and early recurrence had the highest risk of late recurrence risk compared with those with LAVi <66.7 mL/m2 and no early recurrence (HR 4.52 [3.36-6.08], p < .001). Conclusions: Machine learning-derived, full volumetric LAVi from cCT is the most important pre-procedural risk factor for late AF recurrence following catheter ablation. The combination of increased LAVi and early recurrence confers more than a four-fold increased risk of late recurrence.

Long-term evaluation of pulmonary function and survival of patients with interstitial pneumonia with autoimmune features.

OBJECTIVES: Interstitial pneumonia with autoimmune features (IPAF) includes patients with interstitial lung disease with autoimmune features who do not meet criteria for a connective tissue disease (CTD). Previous studies showed a wide variation in the radiologic pattern, pulmonary function and prognosis but there is still limited data on longitudinal outcomes. We aim to describe the long-term pulmonary function, radiological patterns, and survival of IPAF patients and explore a classification based on CTD-like subgroups by using clinical/serologic data. METHODS: Retrospective analysis of IPAF patients who were sub-classified into six CTD-(like) subgroups: systemic lupus erythematosus-like, rheumatoid arthritis-like, Sjögren's syndrome-like, scleroderma, myositis-like, and unclassifiable. Linear mixed-effect models were used to compare the change in percent-predicted forced vital capacity (FVC%), percent-predicted diffusion capacity (DLCO%), and six-minute walk distance (SMWD) over time; and survival in the entire cohort and according to CTD-like subgroups and radiological patterns. RESULTS: Fifty-nine patients fulfilled IPAF criteria. FVC%, DLCO%, and SMWD remained stable over time. There was no difference between usual interstitial pneumonia (UIP) versus non-UIP radiologic patterns. Thirty-five patients were sub-classified into CTD-like subgroups. Survival decreased from 79% at 60 months to 53% at 120 months in the entire cohort but was similar among CTD-like subgroups and radiological patterns. CONCLUSIONS: Long-term pulmonary function and six-minute walk test remained stable over 36 months in our IPAF cohort. Prognosis and pulmonary function in UIP had similar outcomes compared to non-UIP. Although 40% of IPAF patients could not be sub-classified, our exploratory subclassification stratified 60% of patients into a CTD-like subgroup.

Remarkable Intracranial Response to Sotorasib in a Patient With KRAS G12C-Mutated Lung Adenocarcinoma and Untreated Brain Metastases: A Case Report.

Sotorasib is a KRAS G12C inhibitor that recently received approval for use in locally advanced or metastatic KRAS G12C-mutated NSCLC. CodeBreaK100, the phase 2 clinical trial leading to the approval of sotorasib, excluded patients with untreated brain metastases; there have been no reports describing efficacy of sotorasib on untreated brain metastases. We present a case of a patient with active untreated brain metastases with resulting disorientation and weakness who has radiographic response and complete resolution of neurologic symptoms with sotorasib. Our case illustrates the intracranial activity of sotorasib, but additional studies are needed to characterize the intracranial response rate and duration of response in these patients.

Generalizable Framework for Atrial Volume Estimation for Cardiac CT Images Using Deep Learning With Quality Control Assessment.

OBJECTIVES: Cardiac computed tomography (CCT) is a common pre-operative imaging modality to evaluate pulmonary vein anatomy and left atrial appendage thrombus in patients undergoing catheter ablation (CA) for atrial fibrillation (AF). These images also allow for full volumetric left atrium (LA) measurement for recurrence risk stratification, as larger LA volume (LAV) is associated with higher recurrence rates. Our objective is to apply deep learning (DL) techniques to fully automate the computation of LAV and assess the quality of the computed LAV values. METHODS: Using a dataset of 85,477 CCT images from 337 patients, we proposed a framework that consists of several processes that perform a combination of tasks including the selection of images with LA from all other images using a ResNet50 classification model, the segmentation of images with LA using a UNet image segmentation model, the assessment of the quality of the image segmentation task, the estimation of LAV, and quality control (QC) assessment. RESULTS: Overall, the proposed LAV estimation framework achieved accuracies of 98% (precision, recall, and F1 score metrics) in the image classification task, 88.5% (mean dice score) in the image segmentation task, 82% (mean dice score) in the segmentation quality prediction task, and R 2 (the coefficient of determination) value of 0.968 in the volume estimation task. It correctly identified 9 out of 10 poor LAV estimations from a total of 337 patients as poor-quality estimates. CONCLUSIONS: We proposed a generalizable framework that consists of DL models and computational methods for LAV estimation. The framework provides an efficient and robust strategy for QC assessment of the accuracy for DL-based image segmentation and volume estimation tasks, allowing high-throughput extraction of reproducible LAV measurements to be possible.

Quantification of Epicardial Adipose Tissue Volume and Attenuation for Cardiac CT Scans Using Deep Learning in a Single Multi-Task Framework.

Background: Recent studies have shown that epicardial adipose tissue (EAT) is an independent atrial fibrillation (AF) prognostic marker and has influence on the myocardial function. In computed tomography (CT), EAT volume (EATv) and density (EATd) are parameters that are often used to quantify EAT. While increased EATv has been found to correlate with the prevalence and the recurrence of AF after ablation therapy, higher EATd correlates with inflammation due to arrest of lipid maturation and with high risk of plaque presence and plaque progression. Automation of the quantification task diminishes the variability in readings introduced by different observers in manual quantification and results in high reproducibility of studies and less time-consuming analysis. Our objective is to develop a fully automated quantification of EATv and EATd using a deep learning (DL) framework. Methods: We proposed a framework that consists of image classification and segmentation DL models and performs the task of selecting images with EAT from all the CT images acquired for a patient, and the task of segmenting the EAT from the output images of the preceding task. EATv and EATd are estimated using the segmentation masks to define the region of interest. For our experiments, a 300-patient dataset was divided into two subsets, each consisting of 150 patients: Dataset 1 (41,979 CT slices) for training the DL models, and Dataset 2 (36,428 CT slices) for evaluating the quantification of EATv and EATd. Results: The classification model achieved accuracies of 98% for precision, recall and F 1 scores, and the segmentation model achieved accuracies in terms of mean ( ± std.) and median dice similarity coefficient scores of 0.844 ( ± 0.19) and 0.84, respectively. Using the evaluation set (Dataset 2), our approach resulted in a Pearson correlation coefficient of 0.971 ( R 2 = 0.943) between the label and predicted EATv, and the correlation coefficient of 0.972 ( R 2 = 0.945) between the label and predicted EATd. Conclusions: We proposed a framework that provides a fast and robust strategy for accurate EAT segmentation, and volume (EATv) and attenuation (EATd) quantification tasks. The framework will be useful to clinicians and other practitioners for carrying out reproducible EAT quantification at patient level or for large cohorts and high-throughput projects.

Universal Enzyme-Based Field Workflow for Rapid and Sensitive Quantification of Water Pathogens.

A universal filtration and enzyme-based workflow has been established to allow for the rapid and sensitive quantification of leading pathogens Cryptosporidium parvum, Giardia gamblia, Campylobacter jejuni, and Escherichia coli from tap water samples with volumes up to 100 mL, and the potential to scale up to larger volumes. qPCR limits of quantification as low as four oocysts for Cryptosporidium, twelve cysts for Giardia, two cells for C. jejuni, and nineteen cells for E. coli per reaction were achieved. A polycarbonate filter-based sampling method coupled with the prepGEM enzyme-based DNA extraction system created a single-step transfer workflow that required as little as 20 min of incubation time and a 100 µL reaction mix. The quantification via qPCR was performed directly on the prepGEM extract, bypassing time-consuming, labour-intensive conventional culture-based methods. The tap water samples were shown to contain insoluble particles that inhibited detection by reducing the quantification efficiency of a representative pathogen (C. jejuni) to 30-60%. This sample inhibition was effectively removed by an on-filter treatment of 20% (v/v) phosphoric acid wash. Overall, the established workflow was able to achieve quantification efficiencies of 92% and higher for all four leading water pathogens, forming the basis of a rapid, portable, and low-cost solution to water monitoring.

Interobserver Reliability of the Coronary Artery Disease Reporting and Data System in Clinical Practice.

PURPOSE: This study aimed to evaluate interobserver reproducibility between cardiothoracic radiologists applying the Coronary Artery Disease Reporting and Data System (CAD-RADS) to describe atherosclerotic burden on coronary computed tomography angiography. METHODS: Forty clinical computed tomography angiography cases were retrospectively and independently evaluated by 3 attending and 2 fellowship-trained cardiothoracic radiologists using the CAD-RADS lexicon. Radiologists were blinded to patient history and underwent initial training using a practice set of 10 subjects. Interobserver reproducibility was assessed using an intraclass correlation (ICC) on the basis of single-observer scores, absolute agreement, and a 2-way random-effects model. Nondiagnostic studies were excluded. ICC was also performed for CAD-RADS scores grouped by management recommendations for absent (0), nonobstructive (1 to 2), and potentially obstructive (3 to 5) CAD. RESULTS: Interobserver reproducibility was moderate to good (ICC: 0.748, 95% confidence interval [CI]: 0.639-0.842, P<0.0001), with higher agreement among cardiothoracic radiology fellows (ICC: 0.853, 95% CI: 0.730-0.922, P<0.0001) than attending radiologists (ICC: 0.711, 95% CI: 0.568-0.824, P<0.0001). Interobserver reproducibility for clinical management categories was marginally decreased (ICC: 0.692, 95% CI: 0.570-0.802, P<0.0001). The average percent agreement between pairs of radiologists was 84.74%. Percent observer agreement was significantly reduced in the presence (M=62.22%, SD=15.17%) versus the absence (M=80.91%, SD=17.97%) of modifiers, t(37.95)=3.566, P=0.001. CONCLUSIONS: Interobserver reliability and agreement with the CAD-RADS terminology are moderate to good in clinical practice. However, further investigations are needed to characterize the causes of interobserver disagreement that may lead to differences in management recommendations.

Smartphone technology facilitates point-of-care nucleic acid diagnosis: a beginner's guide.

The reliable detection of nucleic acids at low concentrations in clinical samples like blood, urine and saliva, and in food can be achieved by nucleic acid amplification methods. Several portable and hand-held devices have been developed to translate these laboratory-based methods to point-of-care (POC) settings. POC diagnostic devices could potentially play an important role in environmental monitoring, health, and food safety. Use of a smartphone for nucleic acid testing has shown promising progress in endpoint as well as real-time analysis of various disease conditions. The emergence of smartphone-based POC devices together with paper-based sensors, microfluidic chips and digital droplet assays are used currently in many situations to provide quantitative detection of nucleic acid targets. State-of-the-art portable devices are commercially available and rapidly emerging smartphone-based POC devices that allow the performance of laboratory-quality colorimetric, fluorescent and electrochemical detection are described in this review. We present a comprehensive review of smartphone-based POC sensing applications, specifically on microbial diagnostics, assess their performance and propose recommendations for the future.

A Prospective Study of Early Radiation Associated Cardiac Toxicity Following Neoadjuvant Chemoradiation for Distal Esophageal Cancer.

Purpose: This study aimed to prospectively evaluate the early effects of radiation on cardiac structure and function following neoadjuvant chemoradiation for distal esophageal cancer. Methods and Materials: Patients with non-metastatic esophageal cancer who were suitable for tri-modality therapy with concurrent chemoradiotherapy followed by esophagectomy were enrolled. Cardiac magnetic resonance imaging (CMR) was obtained at baseline and 3-5 months following completion of chemoradiation. Standardized myocardial segmentation was used to identify regions on post-treatment CMR with new T2 signal or late gadolinium enhancement (LGE). Pre and post-treatment cardiac function was assessed with quantitative end points including left ventricle end-systolic volume (LSESV). Serum biomarkers of cardiac damage including troponin I, CRP, and BNP were collected at baseline and time of follow-up CMR. Results: A total of 11 patients were enrolled from 2016 to 2018. Patients had clinical stage T2 (18%) and T3 (82%) disease with clinical N0 (27%) and N1 (73%) nodal stage. All patients completed baseline CMR and completed chemoradiotherapy. One patient did not complete follow-up CMR or serum biomarkers and was excluded from the analysis. The median time from completion of chemoradiation to follow-up CMR was 3.9 months. Three out of 10 patients (30%) developed new structural findings of myocardial fibrosis and/or reversible ischemia involving the basal and mid-inferior and inferoseptal walls. In these three patients, the LVESV was significantly increased from baseline following radiation. There were no differences in other quantitative end points or serum biomarkers between the patients with myocardial damage and those without. Conclusions: Our study is the first to our knowledge to prospectively demonstrate radiation associated structural and functional heart damage as early as 3 months following neoadjuvant chemoradiation for distal esophageal cancer. Given the early onset of this subclinical heart damage, strategies should be developed to identify patients at risk for future clinically significant heart toxicity.

A novel framework for the cell-free enzymatic production of glucaric acid.

Glucaric acid (GlucA) is a valuable glucose-derived chemical with promising applications as a biodegradable and biocompatible chemical in the manufacturing of plastics, detergents and drugs. Recently, there has been a significant focus on producing GlucA microbially (in vivo) from renewable materials such as glucose, sucrose and myo-inositol. However, these in vivo GlucA production processes generally lack efficiency due to toxicity problems, metabolite competition and suboptimal enzyme ratios. Synthetic biology and accompanying cell-free biocatalysis have been proposed as a viable approach to overcome many of these limitations. However, cell-free biocatalysis faces its own limitations for industrial applications due to high enzyme costs and cofactor consumption. We have constructed a cell-free GlucA pathway and demonstrated a novel framework to overcome limitations of cell-free biocatalysis by i) the combination of both thermostable and mesophilic enzymes, ii) incorporation of a cofactor regeneration system and iii) immobilisation and recycling of the pathway enzymes. The cell-free production of GlucA was achieved from glucose-1-phosphate with a titre of 14.1 ±â€¯0.9 mM (3.0 ±â€¯0.2 g l-1) and a molar yield of 35.2 ±â€¯2.3% using non-immobilised enzymes, and a titre of 8.1 ±â€¯0.2 mM (1.70 ±â€¯0.04 g l-1) and a molar yield of 20.2 ±â€¯0.5% using immobilised enzymes with a total reaction time of 10 h. The resulting productivities (0.30 ±â€¯0.02 g/h/l for free enzymes and 0.170 ±â€¯0.004 g/h/l for immobilised enzymes) are the highest productivities so far reported for glucaric acid production using a synthetic enzyme pathway.

Multimodality Imaging in the Evaluation of Intracardiac Masses.

Intracardiac masses are classified as neoplastic or non-neoplastic. Prognosis varies based on the diagnosis of the mass since treatment options differ greatly. As novel imaging techniques emerge, a multimodality approach to the evaluation of intracardiac masses becomes an important part of non-invasive evaluation prior to potential surgical planning or oncological treatment. The purpose of this article is to compare the available imaging modalities-echocardiography, cardiovascular magnetic resonance, cardiac computed tomography, nuclear imaging, and emerging novel hybrid imaging techniques for future clinical applications-and to review the characteristic features seen on those modalities for the most common intracardiac masses.

A portable nucleic acid detection system using natural convection combined with a smartphone.

The development of portable nucleic acid diagnostic devices has the potential to expand the availability of molecular diagnostics into low-resource settings. One of the promising solutions for rapid and simple DNA amplification is the use of Rayleigh-Bernard natural convection which is caused by a buoyancy-driven thermal gradient of liquid when heated from below. This natural convection avoids the use of the complex and sophisticated hardware that is required for precise maintenance of temperature cycles in conventional PCR. We have developed a stand-alone convective PCR (cPCR) device linked to a smartphone for rapid detection of nucleic acids using natural convection heating. The device amplifies multiple DNA samples simultaneously using a custom-made heat block controlled by Bluetooth wireless communication. The entire device is highly portable, user-friendly, battery-operated and can provide target DNA amplification in less than 30 min. A detection limit of 2.8 × 103 copies of a segment of lambda DNA was obtained when the two different fluorescently-tagged amplicons were collected magnetically and detected using the smartphone fluorescence reader. Thus, the combination of cPCR and multiplex fluorescence-based detection on a smartphone provides new opportunities for the development of affordable and portable molecular diagnostic devices for point-of-care situations or remote clinical settings.

Intracavitary Coronary Artery: An Unusual Coronary Anomaly.

PURPOSE: A few case reports of intracavitary coronary arteries (ICCA) have been reported and only a single case series on the coronary computed tomography angiography (CCTA) prevalence rate of ICCA of the right coronary artery (RCA). We describe several cases of ICCA that were noted incidentally and also determine the overall prevalence rate of anomalous ICCA. MATERIALS AND METHODS: A retrospective analysis of ICCA was performed consisting of consecutive CCTA cases as well as a group of ICCA from teaching files. To establish a prevalence rate, we reviewed 464 consecutive CCTA referred to our center for transcatheter aortic valve replacement. The presence of ICCA and several imaging features were evaluated. RESULTS: Our cohort comprises a total of 12 patients with ICCA, with 1 patient containing 2 anomalous ICCA. 83.3% of affected patients were adult males, with an average age of 69.8 years. The RCA was the most commonly affected vessel (53.8%). The mean length of the intracavitary segment was 33.4 mm for the RCA and 27 mm for the LAD. No cases involved the left circumflex coronary artery. Six of the cases were identified routinely as part of clinical practice and therefore not included in the prevalence analysis. On review of our transcatheter aortic valve replacement database, there was a 1.3% prevalence rate of ICCA. RCA had a prevalence of 0.4%, whereas LAD had a prevalence of 0.9%. CONCLUSIONS: Although rare, our study suggests that ICCA may be more common than previously described. Its presence is important to communicate to clinicians prior to invasive cardiac procedures to prevent potentially catastrophic outcomes.

Mixed-mode liquid chromatography for the rapid analysis of biocatalytic glucaric acid reaction pathways.

Glucaric acid (GlucA) has been identified as one of the top 10 potential bio-based chemicals for replacement of oil-based chemicals. Several synthetic enzyme pathways have been engineered in bacteria and yeast to produce GlucA from glucose and myo-inositol. However, the yields and titres achieved with these systems remain too low for the requirements of a bio-based GlucA industry. A major limitation for the optimisation of GlucA production via synthetic enzymatic pathways are the laborious analytical procedures required to detect the final product (GlucA) and pathway intermediates. We have developed a novel method for the simple and simultaneous analysis of GlucA and pathway intermediates to address this limitation using mixed mode (MM) HILIC and weak anion exchange chromatography (WAX), referred to as MM HILIC/WAX, coupled with RID. Isocratic mobile phase conditions and the sample solvent were optimised for the separation of GlucA, glucose-1-phosphate (G1P), glucose-6-phosphate (G6P), inositol-1-phosphate (I1P), myo-inositol and glucuronic acid (GA). The method showed good repeatability, precision and excellent accuracy with detection and quantitation limits (LOD and LOQ) of 1.5-2 and 577 mM, respectively. The method developed was used for monitoring the enzymatic synthesis of the final step in the GlucA pathway, and showed that GlucA was produced from GA with near 100% conversion and a titre of 9.2 g L-1.

Tools and strategies for constructing cell-free enzyme pathways.

Single enzyme systems or engineered microbial hosts have been used for decades but the notion of assembling multiple enzymes into cell-free synthetic pathways is a relatively new development. The extensive possibilities that stem from this synthetic concept makes it a fast growing and potentially high impact field for biomanufacturing fine and platform chemicals, pharmaceuticals and biofuels. However, the translation of individual single enzymatic reactions into cell-free multi-enzyme pathways is not trivial. In reality, the kinetics of an enzyme pathway can be very inadequate and the production of multiple enzymes can impose a great burden on the economics of the process. We examine here strategies for designing synthetic pathways and draw attention to the requirements of substrates, enzymes and cofactor regeneration systems for improving the effectiveness and sustainability of cell-free biocatalysis. In addition, we comment on methods for the immobilisation of members of a multi-enzyme pathway to enhance the viability of the system. Finally, we focus on the recent development of integrative tools such as in silico pathway modelling and high throughput flux analysis with the aim of reinforcing their indispensable role in the future of cell-free biocatalytic pathways for biomanufacturing.

Making a Bacterial Thermophilic Enzyme in a Fungal Expression System.

This unit describes production of a bacterial thermophilic xylanase enzyme in an industrially exploited filamentous fungus, Trichoderma reesei. Successful expression of a gene of interest in a heterologous host involves front-end design of the expression constructs using bioinformatics tools, making the constructs in the laboratory, and introducing them into the expression host. This is followed by synthesis and characterization of the gene product on a laboratory scale and optimization of the cultivation parameters in a controlled, scaled-up fermentation. The thermophilic xylanase B (XynB) enzyme from the bacterium Dictyoglomus thermophilum discussed here can be easily purified by heat-precipitation from the culture supernatant of the mesophilic host. A functional XynB can also be produced in Escherichia coli, but at a lower yield compared to that obtained in T. reesei. The protocol provided here can be adapted to various other proteins and filamentous fungal hosts. © 2018 by John Wiley & Sons, Inc.

Solid-Binding Peptides in Biomedicine.

Some peptides are able to bind to inorganic materials such as silica and gold. Over the past decade, Solid-binding peptides (SBPs) have been used increasingly as molecular building blocks in nanobiotechnology. These peptides show selectivity and bind with high affinity to a diverse range of inorganic surfaces e.g. metals, metal oxides, metal compounds, magnetic materials, semiconductors, carbon materials, polymers and minerals. They can be used in applications such as protein purification and synthesis, assembly and the functionalization of nanomaterials. They offer simple and versatile bioconjugation methods that can increase biocompatibility and also direct the immobilization and orientation of nanoscale entities onto solid supports without impeding their functionality. SBPs have been employed in numerous nanobiotechnological applications such as the controlled synthesis of nanomaterials and nanostructures, formation of hybrid biomaterials, immobilization of functional proteins and improved nanomaterial biocompatibility. With advances in nanotechnology, a multitude of novel nanomaterials have been designed and synthesized for diagnostic and therapeutic applications. New approaches have been developed recently to exert a greater control over bioconjugation and eventually, over the optimal and functional display of biomolecules on the surfaces of many types of solid materials. In this chapter we describe SBPs and highlight some selected examples of their potential applications in biomedicine.

Cardiac Applications of PET-MR.

PURPOSE OF REVIEW: The purpose of this study was to provide an overview of the clinical applications of PET-MR in the setting of cardiac imaging with emphasis on specific scenarios where both techniques together provided added information. RECENT FINDINGS: Synergy of cardiac PET and MR fusion may hold similar promise eliminating ionizing radiation and improving tissue contrast. Future development of new hybrid scanners, use of new imaging tracers, and clinical applications are significant factors which will influence its use. Both positron emission tomography (PET) and cardiac magnetic resonance imaging (CMR) provide important anatomic and physiologic information with regard to the heart. Being able to combine the data from these two examinations in a hybrid technique allows for a more complete evaluation of cardiac pathology. While hybrid PET-CT has already established the utility of a combined imaging approach, the use of CMR in lieu of CT allows for elimination of ionizing radiation and for improved tissue contrast.

Solid-binding peptides for immobilisation of thermostable enzymes to hydrolyse biomass polysaccharides.

BACKGROUND: Solid-binding peptides (SBPs) bind strongly to a diverse range of solid materials without the need for any chemical reactions. They have been used mainly for the functionalisation of nanomaterials but little is known about their use for the immobilisation of thermostable enzymes and their feasibility in industrial-scale biocatalysis. RESULTS: A silica-binding SBP sequence was fused genetically to three thermostable hemicellulases. The resulting enzymes were active after fusion and exhibited identical pH and temperature optima but differing thermostabilities when compared to their corresponding unmodified enzymes. The silica-binding peptide mediated the efficient immobilisation of each enzyme onto zeolite, demonstrating the construction of single enzyme biocatalytic modules. Cross-linked enzyme aggregates (CLEAs) of enzyme preparations either with or without zeolite immobilisation displayed greater activity retention during enzyme recycling than those of free enzymes (without silica-binding peptide) or zeolite-bound enzymes without any crosslinking. CLEA preparations comprising all three enzymes simultaneously immobilised onto zeolite enabled the formation of multiple enzyme biocatalytic modules which were shown to degrade several hemicellulosic substrates. CONCLUSIONS: The current work introduced the construction of functional biocatalytic modules for the hydrolysis of simple and complex polysaccharides. This technology exploited a silica-binding SBP to mediate effectively the rapid and simple immobilisation of thermostable enzymes onto readily-available and inexpensive silica-based matrices. A conceptual application of biocatalytic modules consisting of single or multiple enzymes was validated by hydrolysing various hemicellulosic polysaccharides.