Challenges and solutions to system-wide use of precision oncology as the standard of care paradigm.

The personalised oncology paradigm remains challenging to deliver despite technological advances in genomics-based identification of actionable variants combined with the increasing focus of drug development on these specific targets. To ensure we continue to build concerted momentum to improve outcomes across all cancer types, financial, technological and operational barriers need to be addressed. For example, complete integration and certification of the 'molecular tumour board' into 'standard of care' ensures a unified clinical decision pathway that both counteracts fragmentation and is the cornerstone of evidence-based delivery inside and outside of a research setting. Generally, integrated delivery has been restricted to specific (common) cancer types either within major cancer centres or small regional networks. Here, we focus on solutions in real-world integration of genomics, pathology, surgery, oncological treatments, data from clinical source systems and analysis of whole-body imaging as digital data that can facilitate cost-effectiveness analysis, clinical trial recruitment, and outcome assessment. This urgent imperative for cancer also extends across the early diagnosis and adjuvant treatment interventions, individualised cancer vaccines, immune cell therapies, personalised synthetic lethal therapeutics and cancer screening and prevention. Oncology care systems worldwide require proactive step-changes in solutions that include inter-operative digital working that can solve patient centred challenges to ensure inclusive, quality, sustainable, fair and cost-effective adoption and efficient delivery. Here we highlight workforce, technical, clinical, regulatory and economic challenges that prevent the implementation of precision oncology at scale, and offer a systematic roadmap of integrated solutions for standard of care based on minimal essential digital tools. These include unified decision support tools, quality control, data flows within an ethical and legal data framework, training and certification, monitoring and feedback. Bridging the technical, operational, regulatory and economic gaps demands the joint actions from public and industry stakeholders across national and global boundaries.

Enzyme-assisted high throughput sequencing of an expanded genetic alphabet at single base resolution.

With just four building blocks, low sequence information density, few functional groups, poor control over folding, and difficulties in forming compact folds, natural DNA and RNA have been disappointing platforms from which to evolve receptors, ligands, and catalysts. Accordingly, synthetic biology has created "artificially expanded genetic information systems" (AEGIS) to add nucleotides, functionality, and information density. With the expected improvements seen in AegisBodies and AegisZymes, the task for synthetic biologists shifts to developing for expanded DNA the same analytical tools available to natural DNA. Here we report one of these, an enzyme-assisted sequencing of expanded genetic alphabet (ESEGA) method to sequence six-letter AEGIS DNA. We show how ESEGA analyses this DNA at single base resolution, and applies it to optimized conditions for six-nucleotide PCR, assessing the fidelity of various DNA polymerases, and extending this to AEGIS components with functional groups. This supports the renewed exploitation of expanded DNA alphabets in biotechnology.

Sequential deep learning image enhancement models improve diagnostic confidence, lesion detectability, and image reconstruction time in PET.

BACKGROUND: Investigate the potential benefits of sequential deployment of two deep learning (DL) algorithms namely DL-Enhancement (DLE) and DL-based time-of-flight (ToF) (DLT). DLE aims to enhance the rapidly reconstructed ordered-subset-expectation-maximisation algorithm (OSEM) images towards block-sequential-regularised-expectation-maximisation (BSREM) images, whereas DLT aims to improve the quality of BSREM images reconstructed without ToF. As the algorithms differ in their purpose, sequential application may allow benefits from each to be combined. 20 FDG PET-CT scans were performed on a Discovery 710 (D710) and 20 on Discovery MI (DMI; both GE HealthCare). PET data was reconstructed using five combinations of algorithms:1. ToF-BSREM, 2. ToF-OSEM + DLE, 3. OSEM + DLE + DLT, 4. ToF-OSEM + DLE + DLT, 5. ToF-BSREM + DLT. To assess image noise, 30 mm-diameter spherical VOIs were drawn in both lung and liver to measure standard deviation of voxels within the volume. In a blind clinical reading, two experienced readers rated the images on a five-point Likert scale based on lesion detectability, diagnostic confidence, and image quality. RESULTS: Applying DLE + DLT reduced noise whilst improving lesion detectability, diagnostic confidence, and image reconstruction time. ToF-OSEM + DLE + DLT reconstructions demonstrated an increase in lesion SUVmax of 28 ± 14% (average ± standard deviation) and 11 ± 5% for data acquired on the D710 and DMI, respectively. The same reconstruction scored highest in clinical readings for both lesion detectability and diagnostic confidence for D710. CONCLUSIONS: The combination of DLE and DLT increased diagnostic confidence and lesion detectability compared to ToF-BSREM images. As DLE + DLT used input OSEM images, and because DL inferencing was fast, there was a significant decrease in overall reconstruction time. This could have applications to total body PET.

U.S. cereal rye winter cover crop growth database.

Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions, but they vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (Secale cereale) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001-2022 and encompasses a wide range of agronomic, soils, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha-1, a median of 2,458 kg ha-1, and a standard deviation of 3,163 kg ha-1. The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.

Rapid detection of West Nile and Dengue viruses from mosquito saliva by loop-mediated isothermal amplification and displaced probes.

Arthropod-borne viruses are major causes of human and animal disease, especially in endemic low- and middle-income countries. Mosquito-borne pathogen surveillance is essential for risk assessment and vector control responses. Sentinel chicken serosurveillance (antibody testing) and mosquito pool screening (by RT-qPCR or virus isolation) are currently used to monitor arbovirus transmission, however substantial time lags of seroconversion and/or laborious mosquito identification and RNA extraction steps sacrifice their early warning value. As a consequence, timely vector control responses are compromised. Here, we report on development of a rapid arbovirus detection system whereby adding sucrose to reagents of loop-mediated isothermal amplification with displaced probes (DP-LAMP) elicits infectious mosquitoes to feed directly upon the reagent mix and expectorate viruses into the reagents during feeding. We demonstrate that RNA from pathogenic arboviruses (West Nile and Dengue viruses) transmitted in the infectious mosquito saliva was detectable rapidly (within 45 minutes) without RNA extraction. Sucrose stabilized viral RNA at field temperatures for at least 48 hours, important for transition of this system to practical use. After thermal treatment, the DP-LAMP could be reliably visualized by a simple optical image sensor to distinguish between positive and negative samples based on fluorescence intensity. Field application of this technology could fundamentally change conventional arbovirus surveillance methods by eliminating laborious RNA extraction steps, permitting arbovirus monitoring from additional sites, and substantially reducing time needed to detect circulating pathogens.

The silver bullet that wasn't: Rapid agronomic weed adaptations to glyphosate in North America.

The rapid adoption of glyphosate-resistant crops at the end of the 20th century caused a simplification of weed management that relied heavily on glyphosate for weed control. However, the effectiveness of glyphosate has diminished. A greater understanding of trends related to glyphosate use will shed new light on weed adaptation to a product that transformed global agriculture. Objectives were to (1) quantify the change in weed control efficacy from postemergence (POST) glyphosate use on troublesome weeds in corn and soybean and (2) determine the extent to which glyphosate preceded by a preemergence (PRE) improved the efficacy and consistency of weed control compared to glyphosate alone. Herbicide evaluation trials from 24 institutions across the United States of America and Canada from 1996 to 2021 were compiled into a single database. Two subsets were created; one with glyphosate applied POST, and the other with a PRE herbicide followed by glyphosate applied POST. Within each subset, mean and variance of control ratings for seven problem weed species were regressed over time for nine US states and one Canadian province. Mean control with POST glyphosate alone decreased over time while variability in control increased. Glyphosate preceded by a labeled PRE herbicide showed little change in mean control or variability in control over time. These results illustrate the rapid adaptation of agronomically important weed species to the paradigm-shifting product glyphosate. Including more diversity in weed management systems is essential to slowing weed adaptation and prolonging the usefulness of existing and future technologies.

Efficacy of early PET-CT directed switch to carboplatin and paclitaxel based definitive chemoradiotherapy in patients with oesophageal cancer who have a poor early response to induction cisplatin and capecitabine in the UK: a multi-centre randomised controlled phase II trial.

Background: The utility of early metabolic response assessment to guide selection of the systemic component of definitive chemoradiotherapy (dCRT) for oesophageal cancer is uncertain. Methods: In this multi-centre, randomised, open-label, phase II substudy of the radiotherapy dose-escalation SCOPE2 trial we evaluated the role of 18F-Fluorodeoxyglucose positron emission tomography (PET) at day 14 of cycle 1 of three-weekly induction cis/cap (cisplatin (60 mg/m2)/capecitabine (625 mg/m2 days 1-21)) in patients with oesophageal squamous cell carcinoma (OSCC) or adenocarcinoma (OAC). Non-responders, who had a less than 35% reduction in maximum standardised uptake value (SUVmax) from pre-treatment baseline, were randomly assigned to continue cis/cap or switch to car/pac (carboplatin AUC 5/paclitaxel 175 mg/m2) for a further induction cycle, then concurrently with radiotherapy over 25 fractions. Responders continued cis/cap for the duration of treatment. All patients (including responders) were randomised to standard (50Gy) or high (60Gy) dose radiation as part of the main study. Primary endpoint for the substudy was treatment failure-free survival (TFFS) at week 24. The trial was registered with International Standard Randomized Controlled Trial Number 97125464 and ClinicalTrials.govNCT02741856. Findings: This substudy was closed on 1st August 2021 by the Independent Data Monitoring Committee on the grounds of futility and possible harm. To this point from 22nd November 2016, 103 patients from 16 UK centres had participated in the PET-CT substudy; 63 (61.2%; 52/83 OSCC, 11/20 OAC) of whom were non-responders. Of these, 31 were randomised to car/pac and 32 to remain on cis/cap. All patients were followed up until at least 24 weeks, at which point in OSCC both TFFS (25/27 (92.6%) vs 17/25 (68%); p = 0.028) and overall survival (42.5 vs. 20.4 months, adjusted HR 0.36; p = 0.018) favoured cis/cap over car/pac. There was a trend towards worse survival in OSCC + OAC cis/cap responders (33.6 months; 95%CI 23.1-nr) vs. non-responders (42.5 (95%CI 27.0-nr) months; HR = 1.43; 95%CI 0.67-3.08; p = 0.35). Interpretation: In OSCC, early metabolic response assessment is not prognostic for TFFS or overall survival and should not be used to personalise systemic therapy in patients receiving dCRT. Funding: Cancer Research UK.

Multiplex Surveillance Kit Using Sweetened Solid Support to Detect Arboviruses Isothermally in Mosquito Saliva from the Field.

Recently reported "displaceable probe" loop amplification (DP-LAMP) architecture has shown to amplify viral RNA from SARS-CoV-2 with little sample processing. The architecture allows signals indicating the presence of target nucleic acids to be spatially separated, and independent in sequence, from the complicated concatemer that LAMP processes create as part of their amplification process. This makes DP-LAMP an attractive molecular strategy to integrate with trap and sampling innovations to detect RNA from arboviruses carried by mosquitoes in the field. These innovations include (a) development of organically produced carbon dioxide with ethylene carbonate as a bait deployable in mosquito trap, avoiding the need for dry ice, propane tanks, or inorganic carbonates and (b) a process that induces mosquitoes to lay virus-infected saliva on a quaternary ammonium-functionalized paper (Q-paper) matrix, where (c) the matrix (i) inactivates the deposited viruses, (ii) releases their RNA, and (iii) captures viral RNA in a form that keeps it stable for days at ambient temperatures. We report this integration here, with a surprisingly simple workflow. DP-LAMP with a reverse transcriptase was found to amplify arboviral RNA directly from Q-paper, without requiring a separate elution step. This capture-amplification-detection architecture can be multiplexed, with the entire system integrated into a device that can support a campaign of surveillance, in the wild outdoors, that reports the prevalence of arboviruses from field-captured mosquitoes.

Reward insensitivity is associated with dopaminergic deficit in rapid eye movement sleep behaviour disorder.

Idiopathic rapid eye movement sleep behaviour disorder (iRBD) has now been established as an important marker of the prodromal stage of Parkinson's disease and related synucleinopathies. However, although dopamine transporter single photon emission computed tomography (SPECT) has been used to demonstrate the presence of nigro-striatal deficit in iRBD, quantifiable correlates of this are currently lacking. Sensitivity to rewarding stimuli is reduced in some people with Parkinson's disease, potentially contributing to aspects of the neuropsychiatric phenotype in these individuals. Furthermore, a role for dopaminergic degeneration is suggested by the fact that reward insensitivity can be improved by dopaminergic medications. Patients with iRBD present a unique opportunity to study the relationship between reward sensitivity and early dopaminergic deficit in the unmedicated state. Here, we investigate whether a non-invasive, objective measure of reward sensitivity might be a marker of dopaminergic status in prodromal Parkinson's disease by comparing with SPECT/CT measurement of dopaminergic loss in the basal ganglia. Striatal dopaminergic deficits in iRBD are associated with progression to Parkinsonian disorders. Therefore, identification of a clinically measurable correlate of this degenerative process might provide a basis for the development of novel risk stratification tools. Using a recently developed incentivized eye-tracking task, we quantified reward sensitivity in a cohort of 41 patients with iRBD and compared this with data from 40 patients with Parkinson's disease and 41 healthy controls. Patients with iRBD also underwent neuroimaging with dopamine transporter SPECT/CT. Overall, reward sensitivity, indexed by pupillary response to monetary incentives, was reduced in iRBD cases compared with controls and was not significantly different to that in patients with Parkinson's disease. However, in iRBD patients with normal dopamine transporter SPECT/CT imaging, reward sensitivity was not significantly different from healthy controls. Across all iRBD cases, a positive association was observed between reward sensitivity and dopaminergic SPECT/CT signal in the putamen. These findings demonstrate a direct relationship between dopaminergic deficit and reward sensitivity in patients with iRBD and suggest that measurement of pupillary responses could be of value in models of risk stratification and disease progression in these individuals.

Enzyme-Assisted High Throughput Sequencing of an Expanded Genetic Alphabet at Single Base Resolution.

Many efforts have sought to apply laboratory in vitro evolution (LIVE) to natural nucleic acid (NA) scaffolds to directly evolve functional molecules. However, synthetic biology can move beyond natural NA scaffolds to create molecular systems whose libraries are far richer reservoirs of functionality than natural NAs. For example, "artificially expanded genetic information systems" (AEGIS) add up to eight nucleotides to the four found in standard NA. Even in its simplest 6-letter versions, AEGIS adds functional groups, information density, and folding motifs that natural NA libraries lack. To complete this vision, however, tools are needed to sequence molecules that are created by AEGIS LIVE. Previous sequencing approaches, including approaches from our laboratories, exhibited limited performance and lost many sequences in diverse library mixtures. Here, we present a new approach that enzymatically transforms the target AEGIS DNA. With higher transliteration efficiency and fidelity, this Enzyme-Assisted Sequencing of Expanded Genetic Alphabet (ESEGA) approach produces substantially better sequences of 6-letter (AGCTZP) DNA than previous transliteration approaches. Therefore, ESEGA facilitates precise analysis of libraries, allowing 'next-generation deep sequencing' to accurately quantify the sequences of 6-letter DNA molecules at single base resolution. We then applied ESEGA to three tasks: (a) defining optimal conditions to perform 6-nucleotide PCR (b) evaluating the fidelity of 6-nucleotide PCR with various DNA polymerases, and (c) extending that evaluation to AEGIS components functionalized with alkynyl and aromatic groups. No other approach at present has this scope, allowing this work to be the next step towards exploiting the potential of expanded DNA alphabets in biotechnology.

In vitro evolution of ribonucleases from expanded genetic alphabets.

The ability of nucleic acids to catalyze reactions (as well as store and transmit information) is important for both basic and applied science, the first in the context of molecular evolution and the origin of life and the second for biomedical applications. However, the catalytic power of standard nucleic acids (NAs) assembled from just four nucleotide building blocks is limited when compared with that of proteins. Here, we assess the evolutionary potential of libraries of nucleic acids with six nucleotide building blocks as reservoirs for catalysis. We compare the outcomes of in vitro selection experiments toward RNA-cleavage activity of two nucleic acid libraries: one built from the standard four independently replicable nucleotides and the other from six, with the two added nucleotides coming from an artificially expanded genetic information system (AEGIS). Results from comparative experiments suggest that DNA libraries with increased chemical diversity, higher information density, and larger searchable sequence spaces are one order of magnitude richer reservoirs of molecules that catalyze the cleavage of a phosphodiester bond in RNA than DNA libraries built from a standard four-nucleotide alphabet. Evolved AEGISzymes with nitro-carrying nucleobase Z appear to exploit a general acid-base catalytic mechanism to cleave that bond, analogous to the mechanism of the ribonuclease A family of protein enzymes and heavily modified DNAzymes. The AEGISzyme described here represents a new type of catalysts evolved from libraries built from expanded genetic alphabets.

The impact of baseline 18F-FDG PET-CT on the management and outcome of patients with gastric cancer: a systematic review.

OBJECTIVE: CT and staging laparoscopy are routinely used to stage patients with gastric cancer, however the role of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with CT (PET-CT) is uncertain. This systematic review synthesised the evidence regarding the impact of baseline PET-CT staging on treatment decisions and patient outcomes. METHODS: Systematic database searches were performed without date restriction. Studies reporting data in patients with gastric adenocarcinoma who underwent radiological staging were included. One reviewer screened titles and abstracts for suitability and two reviewers extracted data from included articles. Primary outcome was the reported change in management after PET-CT. Secondary outcomes were the rates of recurrence and overall survival between patients staged with and without PET-CT. Risk of bias was assessed using the ROBINS-I tool. PROSPERO registration (CRD42022304314). RESULTS: Data from 11 studies recruiting 2101 patients between 2012 and 2021 were included. PET-CT was performed in 1422 patients. Change of management varied between 3% and 29% of cases. No studies compared recurrence or survival rates between patients staged with or without PET-CT. Adenocarcinoma of intestinal subtype tended to be more FDG-avid compared to diffuse or signet-ring subtypes. No randomised data existed, and studies were considered low quality with high risk of bias. CONCLUSION: Evidence for the additional value of PET-CT in the gastric cancer staging pathway is limited. All studies reported a positive impact by preventing those with undetected metastatic disease on CT undergoing futile surgery. Future national guidelines should consider routine staging PET-CT in gastric cancer. ADVANCES IN KNOWLEDGE: Studies indicated that FDG PET-CT added benefit in gastric cancer staging by detecting more distant metastases, but these studies were generally of low quality and at high risk of bias. Intestinal subtype of gastric adenocarcinoma tended to be more FDG-avid and therefore more distant metastases were subsequently detected.

Outcomes from a mechanistic biomarker multi-arm and randomised study of liposomal MTP-PE (Mifamurtide) in metastatic and/or recurrent osteosarcoma (EuroSarc-Memos trial).

The phase III clinical study of adjuvant liposomal muramyl tripeptide (MTP-PE) in resected high-grade osteosarcoma (OS) documented positive results that have been translated into regulatory approval, supporting initial promise for innate immune therapies in OS. There remains, however, no new approved treatment such as MTP-PE for either metastatic or recurrent OS. Whilst the addition of different agents, including liposomal MTP-PE, to surgery for metastatic or recurrent high-grade osteosarcoma has tried to improve response rates, a mechanistic hiatus exists in terms of a detailed understanding the therapeutic strategies required in advanced disease. Here we report a Bayesian designed multi-arm, multi-centre, open-label phase II study with randomisation in patients with metastatic and/or recurrent OS, designed to investigate how patients with OS might respond to liposomal MTP-PE, either given alone or in combination with ifosfamide. Despite the trial closing because of poor recruitment within the allocated funding period, with no objective responses in eight patients, we report the design and feasibility outcomes for patients registered into the trial. We demonstrate the feasibility of the Bayesian design, European collaboration, tissue collection with genomic analysis and serum cytokine characterisation. Further mechanistic investigation of liposomal MTP-PE alone and in combination with other agents remains warranted in metastatic OS.

Deep learning-based time-of-flight (ToF) image enhancement of non-ToF PET scans.

PURPOSE: To improve the quantitative accuracy and diagnostic confidence of PET images reconstructed without time-of-flight (ToF) using deep learning models trained for ToF image enhancement (DL-ToF). METHODS: A total of 273 [18F]-FDG PET scans were used, including data from 6 centres equipped with GE Discovery MI ToF scanners. PET data were reconstructed using the block-sequential-regularised-expectation-maximisation (BSREM) algorithm with and without ToF. The images were then split into training (n = 208), validation (n = 15), and testing (n = 50) sets. Three DL-ToF models were trained to transform non-ToF BSREM images to their target ToF images with different levels of DL-ToF strength (low, medium, high). The models were objectively evaluated using the testing set based on standardised uptake value (SUV) in 139 identified lesions, and in normal regions of liver and lungs. Three radiologists subjectively rated the models using testing sets based on lesion detectability, diagnostic confidence, and image noise/quality. RESULTS: The non-ToF, DL-ToF low, medium, and high methods resulted in - 28 ± 18, - 28 ± 19, - 8 ± 22, and 1.7 ± 24% differences (mean; SD) in the SUVmax for the lesions in testing set, compared to ToF-BSREM image. In background lung VOIs, the SUVmean differences were 7 ± 15, 0.6 ± 12, 1 ± 13, and 1 ± 11% respectively. In normal liver, SUVmean differences were 4 ± 5, 0.7 ± 4, 0.8 ± 4, and 0.1 ± 4%. Visual inspection showed that our DL-ToF improved feature sharpness and convergence towards ToF reconstruction. Blinded clinical readings of testing sets for diagnostic confidence (scale 0-5) showed that non-ToF, DL-ToF low, medium, and high, and ToF images scored 3.0, 3.0, 4.1, 3.8, and 3.5 respectively. For this set of images, DL-ToF medium therefore scored highest for diagnostic confidence. CONCLUSION: Deep learning-based image enhancement models may provide converged ToF-equivalent image quality without ToF reconstruction. In clinical scoring DL-ToF-enhanced non-ToF images (medium and high) on average scored as high as, or higher than, ToF images. The model is generalisable and hence, could be applied to non-ToF images from BGO-based PET/CT scanners.

Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise.

PURPOSE: To enhance the image quality of oncology [18F]-FDG PET scans acquired in shorter times and reconstructed by faster algorithms using deep neural networks. METHODS: List-mode data from 277 [18F]-FDG PET/CT scans, from six centres using GE Discovery PET/CT scanners, were split into ¾-, ½- and »-duration scans. Full-duration datasets were reconstructed using the convergent block sequential regularised expectation maximisation (BSREM) algorithm. Short-duration datasets were reconstructed with the faster OSEM algorithm. The 277 examinations were divided into training (n = 237), validation (n = 15) and testing (n = 25) sets. Three deep learning enhancement (DLE) models were trained to map full and partial-duration OSEM images into their target full-duration BSREM images. In addition to standardised uptake value (SUV) evaluations in lesions, liver and lungs, two experienced radiologists scored the quality of testing set images and BSREM in a blinded clinical reading (175 series). RESULTS: OSEM reconstructions demonstrated up to 22% difference in lesion SUVmax, for different scan durations, compared to full-duration BSREM. Application of the DLE models reduced this difference significantly for full-, ¾- and ½-duration scans, while simultaneously reducing the noise in the liver. The clinical reading showed that the standard DLE model with full- or ¾-duration scans provided an image quality substantially comparable to full-duration scans with BSREM reconstruction, yet in a shorter reconstruction time. CONCLUSION: Deep learning-based image enhancement models may allow a reduction in scan time (or injected activity) by up to 50%, and can decrease reconstruction time to a third, while maintaining image quality.

Diffusion of Protein Molecules through Microporous Nanofibrous Polyacrylonitrile Membranes.

Porous nanofibrous membranes have ultrahigh specific surface areas and could be broadly employed in protein purification, enzyme immobilization, and biosensors with enhanced selectivity, sensitivity, and efficiency. However, large biomolecules, such as proteins, have hindered diffusion behavior in the micro-porous media, significantly reducing the benefits provided by the nanofibrous membranes. The study of protein diffusion in polyacrylonitrile (PAN) nanofibrous membranes produced under varied humidity and polymer concentration of electrospinning revealed that heterogeneous structures of the nanofibrous membranes possess much smaller effective pore sizes than the measured pore sizes, which significantly affects the diffusion of large molecules through the system though sizes of proteins and pH conditions also have great impacts. Only when the measured membrane pore size is at least 1000 times higher than the protein size, the diffusion behavior of the protein is predictable in the system. The results provide insights into the design and applications of proper nanofibrous materials for improved applications in protein purification and immobilizations.

A DNA-damage immune response assay combined with PET biomarkers predicts response to neo-adjuvant chemotherapy and survival in oesophageal adenocarcinoma.

18F-fluorodeoxyglucose PET-CT may guide treatment decisions in patients with oesophageal adenocarcinoma (OAC). This study evaluated the added value of maximum standardised uptake value (SUVmax) to a novel DNA-damage immune response (DDIR) assay to improve pathological response prediction. The diagnostic accuracy of PET response and the prognostic significance of PET metrics for recurrence-free survival (RFS) and overall survival (OS) were assessed. This was a retrospective, single-centre study of OAC patients treated with neo-adjuvant chemotherapy from 2003 to 2014. SUVmax was recorded from baseline and repeat PET-CT after completion of pre-operative chemotherapy. Logistic regression models tested the additional predictive value of PET metrics combined with the DDIR assay for pathological response. Cox regression models tested the prognostic significance of PET metrics for RFS and OS. In total, 113 patients were included; 25 (22.1%) were DDIR positive and 88 (77.9%) were DDIR negative. 69 (61.1%) were PET responders (SUVmax reduction of 35%) and 44 (38.9%) were PET non-responders. After adding PET metrics to DDIR status, post-chemotherapy SUVmax (hazard ratio (HR) 0.75, p = 0.02), SUVmax change (HR 1.04, p = 0.003) and an optimum SUVmax reduction of 46.5% (HR 4.36, p = 0.021) showed additional value for predicting pathological response. The optimised SUVmax threshold was independently significant for RFS (HR 0.47, 95% CI 0.26-0.85, p = 0.012) and OS (HR 0.51, 95% CI 0.26-0.99, p = 0.047). This study demonstrated the additional value of PET metrics, when combined with a novel DDIR assay, to predict pathological response in OAC patients treated with neo-adjuvant chemotherapy. Furthermore, an optimised SUVmax reduction threshold for pathological response was calculated and was independently significant for RFS and OS.