Bioprocess monitoring applications of an innovative ATR-FTIR spectroscopy platform.

Pharmaceutical manufacturing is reliant upon bioprocessing approaches to generate the range of therapeutic products that are available today. The high cost of production, susceptibility to process failure, and requirement to achieve consistent, high-quality product means that process monitoring is paramount during manufacturing. Process analytic technologies (PAT) are key to ensuring high quality product is produced at all stages of development. Spectroscopy-based technologies are well suited as PAT approaches as they are non-destructive and require minimum sample preparation. This study explored the use of a novel attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy platform, which utilises disposable internal reflection elements (IREs), as a method of upstream bioprocess monitoring. The platform was used to characterise organism health and to quantify cellular metabolites in growth media using quantification models to predict glucose and lactic acid levels both singularly and combined. Separation of the healthy and nutrient deficient cells within PC space was clearly apparent, indicating this technique could be used to characterise these classes. For the metabolite quantification, the binary models yielded R 2 values of 0.969 for glucose, 0.976 for lactic acid. When quantifying the metabolites in tandem using a multi-output partial least squares model, the corresponding R 2 value was 0.980. This initial study highlights the suitability of the platform for bioprocess monitoring and paves the way for future in-line developments.

bbSelect - An Open-Source Tool for Performing a 3D Pharmacophore-Driven Diverse Selection of R-Groups.

The design of compounds during hit-to-lead often seeks to explore a vector from a core scaffold to form additional interactions with the target protein. A rational approach to this is to probe the region of a protein accessed by a vector with a systematic placement of pharmacophore features in 3D, particularly when bound structures are not available. Herein, we present bbSelect, an open-source tool built to map the placements of pharmacophore features in 3D Euclidean space from a library of R-groups, employing partitioning to drive a diverse and systematic selection to a user-defined size. An evaluation of bbSelect against established methods exemplified the superiority of bbSelect in its ability to perform diverse selections, achieving high levels of pharmacophore feature placement coverage with selection sizes of a fraction of the total set and without the introduction of excess complexity. bbSelect also reports visualizations and rationale to enable users to understand and interrogate results. This provides a tool for the drug discovery community to guide their hit-to-lead activities.

Toward a Behavioral Interpretation of English Grammar.

Behavior analysis is virtually alone among disciplines in assuming that the orderly arrangement of words in sentences, or grammar, arises from exposure to contingencies of reinforcement. In the face of the novelty, subtlety, complexity, and speed of acquisition of verbal behavior, this position will remain difficult to defend until the field can show that a representative range of grammatical phenomena is within reach of its interpretive tools. Using modern English as a case in point, this article points to the important role of automatic reinforcement in language acquisition and suggests that Skinner's concept of autoclitic frames (e.g., X is taller than Y) is central to a behavioral interpretation of grammatical phenomena. An enduring puzzle facing this interpretation is how stimulus control can shift from word to word in such frames as one speaks, for such permutations of verbal forms are often novel and rapidly emitted. A possible solution to the puzzle is offered by a consideration of contextual cues, prosodic cues, and the stimulus properties of the roles played by the content words that complete the frames. That these roles have discriminable stimulus properties is supported by considering that in Old English such roles directly controlled case inflections that correspond to positions in autoclitic frames. Continuing to develop behavioral interpretations of grammar is an important pursuit in its own right, whether or not it is sufficient to build bridges to other paradigms.

Structure-Guided Design of a Domain-Selective Bromodomain and Extra Terminal N-Terminal Bromodomain Chemical Probe.

Small-molecule-mediated disruption of the protein-protein interactions between acetylated histone tails and the tandem bromodomains of the bromodomain and extra-terminal (BET) family of proteins is an important mechanism of action for the potential modulation of immuno-inflammatory and oncology disease. High-quality chemical probes have proven invaluable in elucidating profound BET bromodomain biology, with seminal publications of both pan- and domain-selective BET family bromodomain inhibitors enabling academic and industrial research. To enrich the toolbox of structurally differentiated N-terminal bromodomain (BD1) BET family chemical probes, this work describes an analysis of the GSK BRD4 bromodomain data set through a lipophilic efficiency lens, which enabled identification of a BD1 domain-biased benzimidazole series. Structure-guided growth targeting a key Asp/His BD1/BD2 switch enabled delivery of GSK023, a high-quality chemical probe with 300-1000-fold BET BD1 domain selectivity and a phenotypic cellular fingerprint consistent with BET bromodomain inhibition.

Efficacy of dual intracerebroventricular and intravitreal CLN5 gene therapy in sheep prompts the first clinical trial to treat CLN5 Batten disease.

Mutations in the CLN5 gene cause the fatal, pediatric, neurodegenerative disease CLN5 neuronal ceroid lipofuscinosis. Affected children suffer progressive neuronal loss, visual failure and premature death. Presently there is no treatment. This study evaluated dual intracerebroventricular (ICV) and intravitreal (IVT) administration of a self-complementary adeno-associated viral vector encoding ovine CLN5 (scAAV9/oCLN5) into CLN5 affected sheep (CLN5-/-) at various disease stages. CLN5 disease progression was slowed in pre-symptomatic sheep who received a moderate dose of scAAV9/oCLN5, whilst a higher ICV dose treatment in early and advanced symptomatic animals delayed or halted disease progression. Intracranial (brain) volume loss was attenuated in all treatment cohorts, and visual function was also sustained in both the early and advanced symptomatic treated sheep over the 24-month duration of the study. Robust CLN5 protein expression was detected throughout the brain and spinal cord, and improvements in central nervous system and retinal disease correlates were observed. These findings hold translational promise for extending and improving the quality of life in both pre-symptomatic and symptomatic CLN5 patients, and prompted the initiation of the first in-human Phase I/II clinical trial testing ICV/IVT administration of scAAV9 encoding human CLN5 (https://clinicaltrials.gov/; NCT05228145).

A spectroscopic liquid biopsy for the earlier detection of multiple cancer types.

BACKGROUND: A rapid, low-cost blood test that can be applied to reliably detect multiple different cancer types would be transformational. METHODS: In this large-scale discovery study (n = 2092 patients) we applied the Dxcover® Cancer Liquid Biopsy to examine eight different cancers. The test uses Fourier transform infrared (FTIR) spectroscopy and machine-learning algorithms to detect cancer. RESULTS: Area under the receiver operating characteristic curve (ROC) values were calculated for eight cancer types versus symptomatic non-cancer controls: brain (0.90), breast (0.76), colorectal (0.91), kidney (0.91), lung (0.91), ovarian (0.86), pancreatic (0.84) and prostate (0.86). We assessed the test performance when all eight cancer types were pooled to classify 'any cancer' against non-cancer patients. The cancer versus asymptomatic non-cancer classification detected 64% of Stage I cancers when specificity was 99% (overall sensitivity 57%). When tuned for higher sensitivity, this model identified 99% of Stage I cancers (with specificity 59%). CONCLUSIONS: This spectroscopic blood test can effectively detect early-stage disease and can be fine-tuned to maximise either sensitivity or specificity depending on the requirements from different healthcare systems and cancer diagnostic pathways. This low-cost strategy could facilitate the requisite earlier diagnosis, when cancer treatment can be more effective, or less toxic. STATEMENT OF TRANSLATIONAL RELEVANCE: The earlier diagnosis of cancer is of paramount importance to improve patient survival. Current liquid biopsies are mainly focused on single tumour-derived biomarkers, which limits test sensitivity, especially for early-stage cancers that do not shed enough genetic material. This pan-omic liquid biopsy analyses the full complement of tumour and immune-derived markers present within blood derivatives and could facilitate the earlier detection of multiple cancer types. There is a low barrier to integrating this blood test into existing diagnostic pathways since the technology is rapid, simple to use, only minute sample volumes are required, and sample preparation is minimal. In addition, the spectroscopic liquid biopsy described in this study has the potential to be combined with other orthogonal tests, such as cell-free DNA, which could provide an efficient route to diagnosis. Cancer treatment can be more effective when given earlier, and this low-cost strategy has the potential to improve patient prognosis.

Long-term safety and dose escalation of intracerebroventricular CLN5 gene therapy in sheep supports clinical translation for CLN5 Batten disease.

CLN5 neuronal ceroid lipofuscinosis (NCL, Batten disease) is a rare, inherited fatal neurodegenerative disorder caused by mutations in the CLN5 gene. The disease is characterised by progressive neuronal loss, blindness, and premature death. There is no cure. This study evaluated the efficacy of intracerebroventricular (ICV) delivery of an adeno-associated viral vector encoding ovine CLN5 (scAAV9/oCLN5) in a naturally occurring sheep model of CLN5 disease. CLN5 affected (CLN5-/-) sheep received low, moderate, or high doses of scAAV9/oCLN5 at three disease stages. The treatment delayed disease progression, extended survival and slowed stereotypical brain atrophy in most animals. Of note, one high dose treated animal only developed mild disease symptomology and survived to 60.1 months of age, triple the natural life expectancy of an untreated CLN5-/- sheep. Eyesight was not preserved at any administration age or dosage. Histopathologic examination revealed that greater transduction efficiency was achieved through higher ICV doses, and this resulted in greater amelioration of disease pathology. Together with other pre-clinical data from CLN5-/- sheep, the safety and efficacy data from these investigational new drug (IND)-enabling studies supported the initiation of the first in-human CLN5 gene therapy clinical study using the ICV delivery route for the treatment of CLN5 NCL. Clinical Trial Registration: https://clinicaltrials.gov/, identifier NCT05228145.

Global serum profiling: an opportunity for earlier cancer detection.

The advances in cancer research achieved in the last 50 years have been remarkable and have provided a deeper knowledge of this disease in many of its conceptual and biochemical aspects. From viewing a tumor as a 'simple' aggregate of mutant cells and focusing on detecting key cell changes leading to the tumorigenesis, the understanding of cancer has broadened to consider it as a complex organ interacting with its close and far surroundings through tumor and non-tumor cells, metabolic mechanisms, and immune processes. Metabolism and the immune system have been linked to tumorigenesis and malignancy progression along with cancer-specific genetic mutations. However, most technologies developed to overcome the barriers to earlier detection are focused solely on genetic information. The concept of cancer as a complex organ has led to research on other analytical techniques, with the quest of finding a more sensitive and cost-effective comprehensive approach. Furthermore, artificial intelligence has gained broader consensus in the oncology community as a powerful tool with the potential to revolutionize cancer diagnosis for physicians. We herein explore the relevance of the concept of cancer as a complex organ interacting with the bodily surroundings, and focus on promising emerging technologies seeking to diagnose cancer earlier, such as liquid biopsies. We highlight the importance of a comprehensive approach to encompass all the tumor and non-tumor derived information salient to earlier cancer detection.

Augmentation of FTIR spectral datasets using Wasserstein generative adversarial networks for cancer liquid biopsies.

Over recent years, deep learning (DL) has become more widely used within the field of cancer diagnostics. However, DL often requires large training datasets to prevent overfitting, which can be difficult and expensive to acquire. Data augmentation is a method that can be used to generate new data points to train DL models. In this study, we use attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectra of patient dried serum samples and compare non-generative data augmentation methods to Wasserstein generative adversarial networks (WGANs) in their ability to improve the performance of a convolutional neural network (CNN) to differentiate between pancreatic cancer and non-cancer samples in a total cohort of 625 patients. The results show that WGAN augmented spectra improve CNN performance more than non-generative augmented spectra. When compared with a model that utilised no augmented spectra, adding WGAN augmented spectra to a CNN with the same architecture and same parameters, increased the area under the receiver operating characteristic curve (AUC) from 0.661 to 0.757, presenting a 15% increase in diagnostic performance. In a separate test on a colorectal cancer dataset, data augmentation using a WGAN led to an increase in AUC from 0.905 to 0.955. This demonstrates the impact data augmentation can have on DL performance for cancer diagnosis when the amount of real data available for model training is limited.

Intraparenchymal convection enhanced delivery of AAV in sheep to treat Mucopolysaccharidosis IIIC.

BACKGROUND: Mucopolysaccharidosis IIIC (MPSIIIC) is one of four Sanfilippo diseases sharing clinical symptoms of severe cognitive decline and shortened lifespan. The missing enzyme, heparan sulfate acetyl-CoA: α-glucosaminide-N-acetyltransferase (HGSNAT), is bound to the lysosomal membrane, therefore cannot cross the blood-brain barrier or diffuse between cells. We previously demonstrated disease correction in MPSIIIC mice using an Adeno-Associated Vector (AAV) delivering HGSNAT via intraparenchymal brain injections using an AAV2 derived AAV-truetype (AAV-TT) serotype with improved distribution over AAV9. METHODS: Here, intraparenchymal AAV was delivered in sheep using catheters or Hamilton syringes, placed using Brainlab cranial navigation for convection enhanced delivery, to reduce proximal vector expression and improve spread. RESULTS: Hamilton syringes gave improved AAV-GFP distribution, despite lower vector doses and titres. AAV-TT-GFP displayed moderately better transduction compared to AAV9-GFP but both serotypes almost exclusively transduced neurons. Functional HGSNAT enzyme was detected in 24-37% of a 140g gyrencephalic sheep brain using AAV9-HGSNAT with three injections in one hemisphere. CONCLUSIONS: Despite variabilities in volume and titre, catheter design may be critical for efficient brain delivery. These data help inform a clinical trial for MPSIIIC.

Outcomes of an Integrated Multidisciplinary Clinic for People with Functional Neurological Disorder.

Background: Functional neurological disorder (FND) is a disabling condition which has poor prognosis without treatment. This study aimed to evaluate the effectiveness of an outpatient integrated multidisciplinary intervention for the condition. Objectives: This study aimed to assess the outcomes of a pilot integrated multidisciplinary treatment clinic for FND with motor symptoms. Methods: Patients were seen simultaneously by a neurology doctor, a physiotherapist, a clinical psychologist, and sometimes a psychiatrist. The primary endpoint was change in quality of life measured by Short Form-36 (SF-36). Secondary outcomes were change in work and social participation measured by the Work and Social Adjustment Scale (WSAS), ability to participate in full-time or part-time employment, self-rated understanding of FND, and self-rated agreement with the diagnosis of FND. Over the year, 13 patients were recruited to the clinic, and 11 agreed to participate in the outcome study. Results: Statistically significant improvements in quality of life were seen across seven out of eight domains of the SF-36, with improvements in individual domains of between 23 and 39 points (of a possible 100). Mean Work and Social Adjustment Scale score halved from 26 to 13 (worst possible is 40). Of the 12 patients treated, one began to work again after complete unemployment, and two who had been working reduced hours due to disability resumed full time work. No patients had worsened occupational status. Conclusions: This intervention is associated with substantial improvements in quality of life and function, and may be more amenable to delivery at non-specialist centers than other described interventions for FND.

Phosphonate and α-fluorophosphonate analogs of d-glucose 6-phosphate as active-site probes of 1l-myo-inositol 1-phosphate synthase.

Phosphate ester analogs in which the bridging oxygen is replaced with a methylene or fluoromethylene group are well known non-hydrolyzable mimics of use as inhibitors and substrate analogs for reactions involving phosphate esters. Properties of the replaced oxygen are often best mimicked by a mono-fluoromethylene group, but such groups are challenging to synthesize and can exist as two stereoisomers. Here, we describe the protocol for our method of synthesizing the α-fluoromethylene analogs of d-glucose 6-phosphate (G6P), as well as the methylene and difluoromethylene analogs, and their application in the study of 1l-myo-inositol-1-phosphate synthase (mIPS). mIPS catalyzes the synthesis of 1l-myo-inositol 1-phosphate (mI1P) from G6P, in an NAD-dependent aldol cyclization. Its key role in myo-inositol metabolism makes it a putative target for the treatment of several health disorders. The design of these inhibitors allowed for the possibility of substrate-like behavior, reversible inhibition, or mechanism-based inactivation. In this chapter, the synthesis of these compounds, expression and purification of recombinant hexahistidine-tagged mIPS, the mIPS kinetic assay and methods for determining the behavior of the phosphate analogs in the presence of mIPS, and a docking approach to rationalizing the observed behavior are described.

Characterization of neuropathology in ovine CLN5 and CLN6 neuronal ceroid lipofuscinoses (Batten disease).

Sheep with naturally occurring CLN5 and CLN6 forms of neuronal ceroid lipofuscinoses (Batten disease) share the key clinical features of the human disease and represent an ideal model system in which the clinical efficacy of gene therapies is developed and test. However, it was first important to characterize the neuropathological changes that occur with disease progression in affected sheep. This study compared neurodegeneration, neuroinflammation, and lysosomal storage accumulation in CLN5 affected Borderdale, CLN6 affected South Hampshire, and Merino sheep brains from birth to end-stage disease at ≤24 months of age. Despite very different gene products, mutations, and subcellular localizations, the pathogenic cascade was remarkably similar for all three disease models. Glial activation was present at birth in affected sheep and preceded neuronal loss, with both spreading from the visual and parieto-occipital cortices most prominently associated with clinical symptoms to the entire cortical mantle by end-stage disease. In contrast, the subcortical regions were less involved, yet lysosomal storage followed a near-linear increase across the diseased sheep brain with age. Correlation of these neuropathological changes with published clinical data identified three potential therapeutic windows in affected sheep-presymptomatic (3 months), early symptomatic (6 months), and a later symptomatic disease stage (9 months of age)-beyond which the extensive depletion of neurons was likely to diminish any chance of therapeutic benefit. This comprehensive natural history of the neuropathological changes in ovine CLN5 and CLN6 disease will be integral in determining what impact treatment has at each of these disease stages.

Recurrent neural networks for time domain modelling of FTIR spectra: application to brain tumour detection.

Attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy alongside machine learning (ML) techniques is an emerging approach for the early detection of brain cancer in clinical practice. A crucial step in the acquisition of an IR spectrum is the transformation of the time domain signal from the biological sample to a frequency domain spectrum via a discrete Fourier transform. Further pre-processing of the spectrum is typically applied to reduce non-biological sample variance, and thus to improve subsequent analysis. However, the Fourier transformation is often assumed to be essential even though modelling of time domain data is common in other fields. We apply an inverse Fourier transform to frequency domain data to map these to the time domain. We use the transformed data to develop deep learning models utilising Recurrent Neural Networks (RNNs) to differentiate between brain cancer and control in a cohort of 1438 patients. The best performing model achieves a mean (cross-validated score) area under the receiver operating characteristic (ROC) curve (AUC) of 0.97 with sensitivity of 0.91 and specificity of 0.91. This is better than the optimal model trained on frequency domain data which achieves an AUC of 0.93 with sensitivity of 0.85 and specificity of 0.85. A dataset comprising 385 patient samples which were prospectively collected in the clinic is used to test a model defined with the best performing configuration and fit to the time domain. Its classification accuracy is found to be comparable to the gold-standard for this dataset demonstrating that RNNs can accurately classify disease states using spectroscopic data represented in the time domain.

Investigation of SARS-CoV-2 Transmission in The Tabernacle Choir at Temple Square in the Context of Prevention Protocols, Utah, September-November 2021.

Group singing and playing of wind instruments increase COVID-19 transmission risk. After a pause during the initial period of the COVID-19 pandemic, The Tabernacle Choir at Temple Square organization (hereinafter, Choir) resumed musical events in September 2021 with prevention protocols, including required vaccination and pre-event rapid antigen testing. We investigated potential SARS-CoV-2 transmission at Choir events during September 21-November 7, 2021. We interviewed COVID-19-positive members (hereinafter, case-members) and identified members exposed when a case-member attended a Choir event during his or her infectious period. We compared whole genome sequencing results to assess the genetic relatedness of available SARS-CoV-2 specimens obtained from case-members. We identified 30 case-members through pre-event testing (n = 10), self-reported positive test results (n = 18), and a review of Utah's disease surveillance system (n = 2). All 30 case-members reported symptoms; 21 (70%) were women and 23 (77%) received a positive test result by nucleic acid amplification test. No hospitalizations or deaths were reported. We identified 176 test-eligible exposed members from 14 instances of case-members attending events during their infectious periods. All were tested at least once 2 to 14 days after exposure: 74 (42%) by rapid antigen test only (all negative) and 102 (58%) by nucleic acid amplification test (4 positive, 97 negative, and 1 equivocal). Among viral sequences available from 15 case-members, the smallest single-nucleotide polymorphism distance between 2 sequences was 2, and the next-smallest distance was 10. The lack of disease detected in most exposed members suggests that minimal, if any, transmission occurred at Choir events. When community COVID-19 incidence is high, prevention protocols might help limit SARS-CoV-2 transmission during group musical activities.

Solvation entropy, enthalpy and free energy prediction using a multi-task deep learning functional in 1D-RISM.

Simultaneous calculation of entropies, enthalpies and free energies has been a long-standing challenge in computational chemistry, partly because of the difficulty in obtaining estimates of all three properties from a single consistent simulation methodology. This has been particularly true for methods from the Integral Equation Theory of Molecular Liquids such as the Reference Interaction Site Model which have traditionally given large errors in solvation thermodynamics. Recently, we presented pyRISM-CNN, a combination of the 1 Dimensional Reference Interaction Site Model (1D-RISM) solver, pyRISM, with a deep learning based free energy functional, as a method of predicting solvation free energy (SFE). With this approach, a 40-fold improvement in prediction accuracy was delivered for a multi-solvent, multi-temperature dataset when compared to the standard 1D-RISM theory [Fowles et al., Digital Discovery, 2023, 2, 177-188]. Here, we report three further developments to the pyRISM-CNN methodology. Firstly, solvation free energies have been introduced for organic molecular ions in methanol or water solvent systems at 298 K, with errors below 4 kcal mol-1 obtained without the need for corrections or additional descriptors. Secondly, the number of solvents in the training data has been expanded from carbon tetrachloride, water and chloroform to now also include methanol. For neutral solutes, prediction errors nearing or below 1 kcal mol-1 are obtained for each organic solvent system at 298 K and water solvent systems at 273-373 K. Lastly, pyRISM-CNN was successfully applied to the simultaneous prediction of solvation enthalpy, entropy and free energy through a multi-task learning approach, with errors of 1.04, 0.98 and 0.47 kcal mol-1, respectively, for water solvent systems at 298 K.

Liquid biopsies: the future of cancer early detection.

Cancer is a worldwide pandemic. The burden it imposes grows steadily on a global scale causing emotional, physical, and financial strains on individuals, families, and health care systems. Despite being the second leading cause of death worldwide, many cancers do not have screening programs and many people with a high risk of developing cancer fail to follow the advised medical screening regime due to the nature of the available screening tests and other challenges with compliance. Moreover, many liquid biopsy strategies being developed for early detection of cancer lack the sensitivity required to detect early-stage cancers. Early detection is key for improved quality of life, survival, and to reduce the financial burden of cancer treatments which are greater at later stage detection. This review examines the current liquid biopsy market, focusing in particular on the strengths and drawbacks of techniques in achieving early cancer detection. We explore the clinical utility of liquid biopsy technologies for the earlier detection of solid cancers, with a focus on how a combination of various spectroscopic and -omic methodologies may pave the way for more efficient cancer diagnostics.

Blinded Predictions and Post Hoc Analysis of the Second Solubility Challenge Data: Exploring Training Data and Feature Set Selection for Machine and Deep Learning Models.

Accurate methods to predict solubility from molecular structure are highly sought after in the chemical sciences. To assess the state of the art, the American Chemical Society organized a "Second Solubility Challenge" in 2019, in which competitors were invited to submit blinded predictions of the solubilities of 132 drug-like molecules. In the first part of this article, we describe the development of two models that were submitted to the Blind Challenge in 2019 but which have not previously been reported. These models were based on computationally inexpensive molecular descriptors and traditional machine learning algorithms and were trained on a relatively small data set of 300 molecules. In the second part of the article, to test the hypothesis that predictions would improve with more advanced algorithms and higher volumes of training data, we compare these original predictions with those made after the deadline using deep learning models trained on larger solubility data sets consisting of 2999 and 5697 molecules. The results show that there are several algorithms that are able to obtain near state-of-the-art performance on the solubility challenge data sets, with the best model, a graph convolutional neural network, resulting in an RMSE of 0.86 log units. Critical analysis of the models reveals systematic differences between the performance of models using certain feature sets and training data sets. The results suggest that careful selection of high quality training data from relevant regions of chemical space is critical for prediction accuracy but that other methodological issues remain problematic for machine learning solubility models, such as the difficulty in modeling complex chemical spaces from sparse training data sets.

Progressive MRI brain volume changes in ovine models of CLN5 and CLN6 neuronal ceroid lipofuscinosis.

Neuronal ceroid lipofuscinoses (Batten disease) are a group of inherited lysosomal storage disorders characterized by progressive neurodegeneration leading to motor and cognitive dysfunction, seizure activity and blindness. The disease can be caused by mutations in 1 of 13 ceroid lipofuscinosis neuronal (CLN) genes. Naturally occurring sheep models of the CLN5 and CLN6 neuronal ceroid lipofuscinoses recapitulate the clinical disease progression and post-mortem pathology of the human disease. We used longitudinal MRI to assess global and regional brain volume changes in CLN5 and CLN6 affected sheep compared to age-matched controls over 18 months. In both models, grey matter volume progressively decreased over time, while cerebrospinal fluid volume increased in affected sheep compared with controls. Total grey matter volume showed a strong positive correlation with clinical scores, while cerebrospinal fluid volume was negatively correlated with clinical scores. Cortical regions in affected animals showed significant atrophy at baseline (5 months of age) and progressively declined over the disease course. Subcortical regions were relatively spared with the exception of the caudate nucleus in CLN5 affected animals that degenerated rapidly at end-stage disease. Our results, which indicate selective vulnerability and provide a timeline of degeneration of specific brain regions in two sheep models of neuronal ceroid lipofuscinoses, will provide a clinically relevant benchmark for assessing therapeutic efficacy in subsequent trials of gene therapy for CLN5 and CLN6 disease.

A Type 1 Aldolase, NahE, Catalyzes a Stereoselective Nitro-Michael Reaction: Synthesis of ß-Aryl-γ-nitrobutyric Acids.

Michael addition reactions are highly useful in organic synthesis and are commonly accomplished using organocatalysts. However, the corresponding biocatalytic Michael additions are rare, typically lack synthetically useful substrate scope, and suffer from low stereoselectivity. Herein we report a biocatalytic nitro-Michael addition, catalyzed by NahE, that proceeds with low catalyst loading at room temperature in moderate to excellent enantioselectivity and high yields. A series of ß-nitrostyrenes reacted with pyruvate in the presence of NahE to give, after oxidative decarboxylation, ß-aryl-γ-nitrobutyric acids in up to 99 % yield without need for chromatography, providing a simple preparative-scale route to chiral GABA analogues. This reaction represents the first example of an aldolase displaying promiscuous Michaelase activity and opens the use of nitroalkenes in place of aldehydes as substrates for aldolases.