Ketogenic diet for human diseases: the underlying mechanisms and potential for clinical implementations

The ketogenic diet (KD) is a high-fat, adequate-protein, and very-low-carbohydrate diet regimen that mimics the metabolism of the fasting state to induce the production of ketone bodies. The KD has long been established as a remarkably successful dietary approach for the treatment of intractable epilepsy and has increasingly garnered research attention rapidly in the past decade, subject to emerging evidence of the promising therapeutic potential of the KD for various diseases, besides epilepsy, from obesity to malignancies. In this review, we summarize the experimental and/or clinical evidence of the efficacy and safety of the KD in different diseases, and discuss the possible mechanisms of action based on recent advances in understanding the influence of the KD at the cellular and molecular levels. We emphasize that the KD may function through multiple mechanisms, which remain to be further elucidated. The challenges and future directions for the clinical implementation of the KD in the treatment of a spectrum of diseases have been discussed. We suggest that, with encouraging evidence of therapeutic effects and increasing insights into the mechanisms of action, randomized controlled trials should be conducted to elucidate a foundation for the clinical use of the KD.

A randomized crossover study of functional electrical stimulation during walking in spastic cerebral palsy: the FES on participation (FESPa) trial

Background Spastic cerebral palsy is the most common cause of motor disability in children. It often leads to foot drop or equinus, interfering with walking. Ankle-foot orthoses (AFOs) are commonly used in these cases. However, AFOs can be too restrictive for mildly impaired patients. Functional electrical stimulation (FES) of the ankle-dorsiflexors is an alternative treatment as it could function as a dynamic functional orthosis. Despite previous research, high level evidence on the effects of FES on activities and participation in daily life is missing. The primary aim of this study is to evaluate whether FES improves the activity and participation level in daily life according to patients, and the secondary aim is to provide evidence of the effect of FES at the level of body functions and activities. Furthermore, we aim to collect relevant information for decisions on its clinical implementation. Methods A randomized crossover trial will be performed on 25 children with unilateral spastic cerebral palsy. Patients aged between 4 and 18 years, with Gross Motor Functioning Classification System level I or II and unilateral foot drop of central origin, currently treated with AFO or adapted shoes, will be included. All participants will undergo twelve weeks of conventional treatment (AFO/adapted shoes) and 12 weeks of FES treatment, separated by a six-week washout-phase. FES treatment consists of wearing the WalkAide® device, with surface electrodes stimulating the peroneal nerve during swing phase of gait. For the primary objective, the Goal Attainment Scale is used to test whether FES improves activities and participation in daily life. The secondary objective is to prove whether FES is effective at the level of body functions and structures, and activities, including ankle kinematics and kinetics measured during 3D-gait analysis and questionnaire-based frequency of falling. The tertiary objective is to collect relevant information for clinical implementation, including acceptability using the device log file and side effect registration, cost-effectiveness based on quality adjusted life years (QALYs) and clinical characteristics for patient selection. Discussion We anticipate that the results of this study will allow evidence-based use of FES during walking in children with unilateral spastic cerebral palsy. Trial registration ClinicalTrials.gov: NCT03440632.

212Pb: Production Approaches and Targeted Therapy Applications

Over the last decade, targeted alpha therapy has demonstrated its high effectiveness in treating various oncological diseases. Lead-212, with a convenient half-life of 10.64 h, and daughter alpha-emitter short-lived 212Bi (T1/2 = 1 h), provides the possibility for the synthesis and purification of complex radiopharmaceuticals with minimum loss of radioactivity during preparation. As a benefit for clinical implementation, it can be milked from a radionuclide generator in different ways. The main approaches applied for these purposes are considered and described in this review, including chromatographic, solution, and other techniques to isolate 212Pb from its parent radionuclide. Furthermore, molecules used for lead’s binding and radiochemical features of preparation and stability of compounds labeled with 212Pb are discussed. The results of preclinical studies with an estimation of therapeutic and tolerant doses as well as recently initiated clinical trials of targeted radiopharmaceuticals are presented.

Sumoylation of Cas9 at lysine 848 regulates protein stability and DNA binding

CRISPR/Cas9 is a popular genome editing technology. Although widely used, little is known about how this prokaryotic system behaves in humans. An unwanted consequence of eukaryotic Cas9 expression is off-target DNA binding leading to mutagenesis. Safer clinical implementation of CRISPR/Cas9 necessitates a finer understanding of the regulatory mechanisms governing Cas9 behavior in humans. Here, we report our discovery of Cas9 sumoylation and ubiquitylation, the first post-translational modifications to be described on this enzyme. We found that the major SUMO2/3 conjugation site on Cas9 is K848, a key positively charged residue in the HNH nuclease domain that is known to interact with target DNA and contribute to off-target DNA binding. Our results suggest that Cas9 ubiquitylation leads to decreased stability via proteasomal degradation. Preventing Cas9 sumoylation through conversion of K848 into arginine or pharmacologic inhibition of cellular sumoylation enhances the enzyme’s turnover and diminishes guide RNA-directed DNA binding efficacy, suggesting that sumoylation at this site regulates Cas9 stability and DNA binding. More research is needed to fully understand the implications of these modifications for Cas9 specificity.

Report on Webinar Series Cell and Gene Therapy: From Concept to Clinical Use

With the launch of the UK Academy of Pharmaceutical Sciences Advanced Therapy Medicinal Products Focus Group in late 2020, a webinar series reviewing the current and emerging trends in cell and gene therapy was held virtually in May 2021. This webinar series was timely given the recent withdrawal of the United Kingdom from the European Union and the global COVID-19 pandemic impacting all sectors of the pharmaceutical sciences research landscape globally and in the UK. Delegates from the academic, industry, regulatory and NHS sectors attended the session where challenges and opportunities in the development and clinical implementation of cell and gene therapies were discussed. Globally, the cell and gene therapy market has reached a value of 4.3 billion dollars in 2020, having increased at a compound annual growth rate of 25.5% since 2015. This webinar series captured all the major developments in this rapidly evolving area and highlighted emerging concepts warranting cross-sector efforts from across the community in the future.

Knowledge, Attitude, and Perceived Barriers of Newly Graduated Registered Nurses Undergoing Standardized Training in Intensive Care Unit Toward Early Mobilization of Mechanically Ventilated Patients: A Qualitative Study in Shanghai

Aim: To explore the knowledge and attitudes of newly graduated registered nurses, who have undergone standardized training in the intensive care unit, about the early mobilization of mechanically ventilated patients and identify perceived barriers to the application of early mobilization.Background: Early mobilization of mechanically ventilated patients has been gradually gaining attention, and its safety and effectiveness have also been verified. Nurses in intensive care units are the implementers of early mobilization, and the quality of their care is closely related to patient prognosis. However, the knowledge and attitude of newly graduated registered nurses undergoing standardized training, in intensive care units, on the early mobilization of mechanically ventilated patients and the obstacles they face in clinical implementation are still unclear.Methods: This qualitative study utilized the phenomenological method to explore the experiences of 15 newly graduated registered nurses undergoing standardized training in intensive care units in a 3rd hospital in Shanghai, China. Semi-structured face-to-face interviews were conducted in June 2020. The Colaizzi seven-step framework was used for data analysis.Findings: A total of 15 new nurses comprised the final sample after data saturation. Three main themes emerged from the analysis and seven subthemes: perceived importance, low implementation rate, and perceived barriers.Conclusions: Newly graduated registered nurses undergoing standardized training in intensive care units have a high level of awareness of the importance of early mobilization of mechanically ventilated patients and are willing to implement it. However, there is a lack of relevant knowledge and other obstacles that restrict clinical implementation. Early mobilization should be included in the standardized training of new nurses in intensive care units.

Spatial Metrics of Interaction between CD163-Positive Macrophages and Cancer Cells and Progression-Free Survival in Chemo-Treated Breast Cancer

Tumor-associated macrophages (TAMs) promote progression of breast cancer and other solid malignancies via immunosuppressive, pro-angiogenic and pro-metastatic effects. Tumor-promoting TAMs tend to express M2-like macrophage markers, including CD163. Histopathological assessments suggest that the density of CD163-positive TAMs within the tumor microenvironment is associated with reduced efficacy of chemotherapy and unfavorable prognosis. However, previous analyses have required research-oriented pathologists to visually enumerate CD163+ TAMs, which is both laborious and subjective and hampers clinical implementation. Objective, operator-independent image analysis methods to quantify TAM-associated information are needed. In addition, since M2-like TAMs exert local effects on cancer cells through direct juxtacrine cell-to-cell interactions, paracrine signaling, and metabolic factors, we hypothesized that spatial metrics of adjacency of M2-like TAMs to breast cancer cells will have further information value. Immunofluorescence histo-cytometry of CD163+ TAMs was performed retrospectively on tumor microarrays of 443 cases of invasive breast cancer from patients who subsequently received adjuvant chemotherapy. An objective and automated algorithm was developed to phenotype CD163+ TAMs and calculate their density within the tumor stroma and derive several spatial metrics of interaction with cancer cells. Shorter progression-free survival was associated with a high density of CD163+ TAMs, shorter median cancer-to-CD163+ nearest neighbor distance, and a high number of either directly adjacent CD163+ TAMs (within juxtacrine proximity <12 μm to cancer cells) or communicating CD163+ TAMs (within paracrine communication distance <250 μm to cancer cells) after multivariable adjustment for clinical and pathological risk factors and correction for optimistic bias due to dichotomization.

Inherently explainable deep neural network-based interpretation of electrocardiograms using variational auto-encoders

Background Deep neural networks (DNNs) show excellent performance in interpreting electrocardiograms (ECGs), both for conventional ECG interpretation and for novel applications such as detection of reduced ejection fraction and prediction of one-year mortality. Despite these promising developments, clinical implementation is severely hampered by the lack of trustworthy techniques to explain the decisions of the algorithm to clinicians. Especially, currently employed heatmap-based methods have shown to be inaccurate. Methods We present a novel approach that is inherently explainable and uses an unsupervised variational auto-encoder (VAE) to learn the underlying factors of variation of the ECG (the FactorECG) in a database with 1.1 million ECG recordings. These factors are subsequently used in a pipeline with common and interpretable statistical methods. As the ECG factors are explainable by generating and visualizing ECGs on both the model- and individual patient-level, the pipeline becomes fully explainable. The performance of the pipeline is compared to a state-of-the-art black box DNN in three tasks: conventional ECG interpretation with 35 diagnostic statements, detection of reduced ejection fraction and prediction of one-year mortality. Results The VAE was able to compress the ECG into 21 generative ECG factors, which are associated with physiologically valid underlying anatomical and (patho)physiological processes. When applying the novel pipeline to the three tasks, the explainable FactorECG pipeline performed similar to state-of-the-art black box DNNs in conventional ECG interpretation (AUROC 0.94 vs 0.96), detection of reduced ejection fraction (AUROC 0.90 vs 0.91) and prediction of one-year mortality (AUROC 0.76 vs 0.75). Contrary to state-of-the-art, our pipeline provided inherent explainability on which morphological ECG features were important for prediction or diagnosis. Conclusion Future studies should employ DNNs that are inherently explainable to facilitate clinical implementation by gaining confidence in artificial intelligence, and more importantly, making it possible to identify biased or inaccurate models.

A tool for translating polygenic scores onto the absolute scale using summary statistics

There is growing interest in the clinical application of polygenic scores as their predictive utility increases for a range of health-related phenotypes. However, providing polygenic score predictions on the absolute scale is an important step for their safe interpretation. We have developed a method to convert polygenic scores to the absolute scale for binary and normally distributed phenotypes. This method uses summary statistics, requiring only the area-under-the-ROC curve (AUC) or variance explained (R2) by the polygenic score, and the prevalence of binary phenotypes, or mean and standard deviation of normally distributed phenotypes. Polygenic scores are converted using normal distribution theory. We also evaluate methods for estimating polygenic score AUC/R2 from genome-wide association study (GWAS) summary statistics alone. We validate the absolute risk conversion and AUC/R2 estimation using data for eight binary and three continuous phenotypes in the UK Biobank sample. When the AUC/R2 of the polygenic score is known, the observed and estimated absolute values were highly concordant. Estimates of AUC/R2 from the lassosum pseudovalidation method were most similar to the observed AUC/R2 values, though estimated values deviated substantially from the observed for autoimmune disorders. This study enables accurate interpretation of polygenic scores using only summary statistics, providing a useful tool for educational and clinical purposes. Furthermore, we have created interactive webtools implementing the conversion to the absolute (https://opain.github.io/GenoPred/PRS_to_Abs_tool.html). Several further barriers must be addressed before clinical implementation of polygenic scores, such as ensuring target individuals are well represented by the GWAS sample.

Hyperspectral Imaging for Clinical Applications

Measuring morphological and biochemical features of tissue is crucial for disease diagnosis and surgical guidance, providing clinically significant information related to pathophysiology. Hyperspectral imaging (HSI) techniques obtain both spatial and spectral features of tissue without labeling molecules such as fluorescent dyes, which provides rich information for improved disease diagnosis and treatment. Recent advances in HSI systems have demonstrated its potential for clinical applications, especially in disease diagnosis and image-guided surgery. This review summarizes the basic principle of HSI and optical systems, deep-learning-based image analysis, and clinical applications of HSI to provide insight into this rapidly growing field of research. In addition, the challenges facing the clinical implementation of HSI techniques are discussed.