Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium.

BACKGROUND: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection, foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates. METHODS: Twenty healthy older adults, 20 people with Parkinson's disease, 20 with multiple sclerosis, 19 with proximal femoral fracture, 17 with chronic obstructive pulmonary disease and 12 with congestive heart failure were monitored for 2.5 h in the real-world, using a single wearable device worn on the lower back. A reference system combining inertial modules with distance sensors and pressure insoles was used for comparison of DMOs from the single wearable device. We assessed and validated three algorithms for gait sequence detection, four for ICD, three for CAD and four for SL by concurrently comparing their performances (e.g., accuracy, specificity, sensitivity, absolute and relative errors). Additionally, the effects of walking bout (WB) speed and duration on algorithm performance were investigated. RESULTS: We identified two cohort-specific top performing algorithms for gait sequence detection and CAD, and a single best for ICD and SL. Best gait sequence detection algorithms showed good performances (sensitivity > 0.73, positive predictive values > 0.75, specificity > 0.95, accuracy > 0.94). ICD and CAD algorithms presented excellent results, with sensitivity > 0.79, positive predictive values > 0.89 and relative errors < 11% for ICD and < 8.5% for CAD. The best identified SL algorithm showed lower performances than other DMOs (absolute error < 0.21 m). Lower performances across all DMOs were found for the cohort with most severe gait impairments (proximal femoral fracture). Algorithms' performances were lower for short walking bouts; slower gait speeds (< 0.5 m/s) resulted in reduced performance of the CAD and SL algorithms. CONCLUSIONS: Overall, the identified algorithms enabled a robust estimation of key DMOs. Our findings showed that the choice of algorithm for estimation of gait sequence detection and CAD should be cohort-specific (e.g., slow walkers and with gait impairments). Short walking bout length and slow walking speed worsened algorithms' performances. Trial registration ISRCTN - 12246987.

Preclinical Characterization of the 177Lu-Labeled Prostate Stem Cell Antigen (PSCA)-Specific Monoclonal Antibody 7F5.

Prostate specific membrane antigen (PSMA) is an excellent target for imaging and treatment of prostate carcinoma (PCa). Unfortunately, not all PCa cells express PSMA. Therefore, alternative theranostic targets are required. The membrane protein prostate stem cell antigen (PSCA) is highly overexpressed in most primary prostate carcinoma (PCa) cells and in metastatic and hormone refractory tumor cells. Moreover, PSCA expression positively correlates with tumor progression. Therefore, it represents a potential alternative theranostic target suitable for imaging and/or radioimmunotherapy. In order to support this working hypothesis, we conjugated our previously described anti-PSCA monoclonal antibody (mAb) 7F5 with the bifunctional chelator CHX-A″-DTPA and subsequently radiolabeled it with the theranostic radionuclide 177Lu. The resulting radiolabeled mAb ([177Lu]Lu-CHX-A″-DTPA-7F5) was characterized both in vitro and in vivo. It showed a high radiochemical purity (>95%) and stability. The labelling did not affect its binding capability. Biodistribution studies showed a high specific tumor uptake compared to most non-targeted tissues in mice bearing PSCA-positive tumors. Accordingly, SPECT/CT images revealed a high tumor-to-background ratios from 16 h to 7 days after administration of [177Lu]Lu-CHX-A″-DTPA-7F5. Consequently, [177Lu]Lu-CHX-A″-DTPA-7F5 represents a promising candidate for imaging and in the future also for radioimmunotherapy.

Toward Personalized Medicine: One Chelator for Imaging and Therapy with Lutetium-177 and Actinium-225.

We report a nonadentate bispidine (3,7-diazabicyclo[3.3.1]nonane) that unveils the potential to bind theranostically relevant radionuclides, including indium-111, lutetium-177, and actinium-225 under mild labeling conditions. This radiopharmaceutical candidate allows the simultaneous application of imaging and treatment (radionuclide theranostics) without changing the type of the bioconjugate; that is, it allows the strong binding to an imaging and a therapeutic radionuclide by the same chelator. Since sophisticated coordination chemistry is required to achieve high thermodynamic and kinetic stability (inertness), it is not surprising that only a few chelators have been reported that are able to strongly bind several radionuclides to a satisfactory extent. Bispidine-derived ligands have proven to be ideal for di- and trivalent metal ions with generally fast complexation kinetics and high in vitro and in vivo stabilities. The presented (radio)complexes are formed under mild conditions (pH 6, <40 °C) and exhibit thermodynamic stability and inertness in human serum comparable to the corresponding DOTA complexes. The bispidine-based complexing agent was conjugated to a peptide, targeting somatostatin type 2 receptors (SSTR2), overexpressed on neuroendocrine tumors. The 177Lu- and 225Ac-labeled conjugates were investigated, considering their binding to two different SSTR2-positive cell lines, including the human pancreatic carcinoid tumor (BON-SSTR2+) and the murine pheochromocytoma cell line (MPC). The biodistribution and accumulation pattern in MPC tumor-bearing mice was also evaluated. The LuIII and AcIII complexes studied show how ligand structures can be optimized in general by extending the denticity and varying the donor set in order to allow for fast complex formation and medically relevant inertness.

Design and validation of a multi-task, multi-context protocol for real-world gait simulation.

BACKGROUND: Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a protocol for simulating real-world gait accounting for all these factors within a single set of observations, while ensuring minimisation of participant burden and safety. METHODS: The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants' strategy of walking. It was deployed in a convenience sample of 108 participants recruited from six cohorts that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson's disease (PD), multiple sclerosis (MS), proximal femoral fracture (PFF), chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks. RESULTS: The protocol proved to be safe and feasible (all participants could complete it and no adverse events were recorded) and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a representation of a variety of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life. CONCLUSIONS: The protocol allowed for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy. TRIAL REGISTRATION: ISRCTN-12246987.

Exploring Nitric Oxide (NO)-Releasing Celecoxib Derivatives as Modulators of Radioresponse in Pheochromocytoma Cells.

COX-2 can be considered as a clinically relevant molecular target for adjuvant, in particular radiosensitizing treatments. In this regard, using selective COX-2 inhibitors, e.g., in combination with radiotherapy or endoradiotherapy, represents an interesting treatment option. Based on our own findings that nitric oxide (NO)-releasing and celecoxib-derived COX-2 inhibitors (COXIBs) showed promising radiosensitizing effects in vitro, we herein present the development of a series of eight novel NO-COXIBs differing in the peripheral substitution pattern and their chemical and in vitro characterization. COX-1 and COX-2 inhibition potency was found to be comparable to the lead NO-COXIBs, and NO-releasing properties were demonstrated to be mainly influenced by the substituent in 4-position of the pyrazole (Cl vs. H). Introduction of the N-propionamide at the sulfamoyl residue as a potential prodrug strategy lowered lipophilicity markedly and abolished COX inhibition while NO-releasing properties were not markedly influenced. NO-COXIBs were tested in vitro for a combination with single-dose external X-ray irradiation as well as [177Lu]LuCl3 treatment in HIF2α-positive mouse pheochromocytoma (MPC-HIF2a) tumor spheroids. When applied directly before X-ray irradiation or 177Lu treatment, NO-COXIBs showed radioprotective effects, as did celecoxib, which was used as a control. Radiosensitizing effects were observed when applied shortly after X-ray irradiation. Overall, the NO-COXIBs were found to be more radioprotective compared with celecoxib, which does not warrant further preclinical studies with the NO-COXIBs for the treatment of pheochromocytoma. However, evaluation as radioprotective agents for healthy tissues could be considered for the NO-COXIBs developed here, especially when used directly before irradiation.

Men who stare at bone: multimodal monitoring of bone healing.

Knowledge of the physiological and pathological processes, taking place in bone during fracture healing or defect regeneration, is essential in order to develop strategies to enhance bone healing under normal and critical conditions. Preclinical testing allows a wide range of imaging modalities that may be applied both simultaneously and longitudinally, which will in turn lower the number of animals needed to allow a comprehensive assessment of the healing process. This work provides an up-to-date review on morphological, functional, optical, biochemical, and biophysical imaging techniques including their advantages, disadvantages and potential for combining them in a multimodal and multiscale manner. The focus lies on preclinical testing of biomaterials modified with artificial extracellular matrices in various animal models to enhance bone remodeling and regeneration.

Hidden Markov Model based stride segmentation on unsupervised free-living gait data in Parkinson's disease patients.

BACKGROUND: To objectively assess a patient's gait, a robust identification of stride borders is one of the first steps in inertial sensor-based mobile gait analysis pipelines. While many different methods for stride segmentation have been presented in the literature, an out-of-lab evaluation of respective algorithms on free-living gait is still missing. METHOD: To address this issue, we present a comprehensive free-living evaluation dataset, including 146.574 semi-automatic labeled strides of 28 Parkinson's Disease patients. This dataset was used to evaluate the segmentation performance of a new Hidden Markov Model (HMM) based stride segmentation approach compared to an available dynamic time warping (DTW) based method. RESULTS: The proposed HMM achieved a mean F1-score of 92.1% and outperformed the DTW approach significantly. Further analysis revealed a dependency of segmentation performance to the number of strides within respective walking bouts. Shorter bouts ([Formula: see text] strides) resulted in worse performance, which could be related to more heterogeneous gait and an increased diversity of different stride types in short free-living walking bouts. In contrast, the HMM reached F1-scores of more than 96.2% for longer bouts ([Formula: see text] strides). Furthermore, we showed that an HMM, which was trained on at-lab data only, could be transferred to a free-living context with a negligible decrease in performance. CONCLUSION: The generalizability of the proposed HMM is a promising feature, as fully labeled free-living training data might not be available for many applications. To the best of our knowledge, this is the first evaluation of stride segmentation performance on a large scale free-living dataset. Our proposed HMM-based approach was able to address the increased complexity of free-living gait data, and thus will help to enable a robust assessment of stride parameters in future free-living gait analysis applications.

Beta, gamma band, and high-frequency coherence of EMGs of vasti muscles caused by clustering of motor units.

The vasti muscles stabilize the knee joint during the running movement. This requires some motor units to synchronize. Test the hypothesis that EMGs from the vasti muscles (VM and VL) are coherent in four frequency bands, one below 30 Hz, the 40 Hz (30-45 Hz), the middle band up to 120 Hz, and the high-frequency band (135-280 Hz). Because the VM during one step and the VL during another step contain common EMG signal parts the inter-step coherence at low frequencies does not disappear when the coherence is computed between the EMGVM obtained from one step and the EMGVL of the previous step. Twelve participants ran on a treadmill at 2.9 m/s for 15 min. EMGs were recorded from the vasti muscles using bipolar current amplifiers. Ordinary coherence was computed between the EMGVM and EMGVL and for the inter-step-condition. Significant coherence was observed in all frequency bands. In the mid- and high-frequency range, coherence disappears for the inter-step condition, whereas the low-frequency coherence is still present. Four frequency bands must be considered. It was proposed that coherence at low frequencies reflects cortico-muscular interactions. However, the clustering of motor unit action potentials is sufficient to generate the low-frequency coherence as well. There is a low-frequency coherence resulting from EMGs of the vasti muscles that are similar in different steps. Therefore, at least these three effects must be considered to draw conclusions from the coherence of the vasti muscles at low frequencies that occur while running.

Comparison of Different Algorithms for Calculating Velocity and Stride Length in Running Using Inertial Measurement Units.

Running has a positive impact on human health and is an accessible sport for most people. There is high demand for tracking running performance and progress for amateurs and professionals alike. The parameters velocity and distance are thereby of main interest. In this work, we evaluate the accuracy of four algorithms, which calculate the stride velocity and stride length during running using data of an inertial measurement unit (IMU) placed in the midsole of a running shoe. The four algorithms are based on stride time, foot acceleration, foot trajectory estimation, and deep learning, respectively. They are compared using two studies: a laboratory-based study comprising 2377 strides from 27 subjects with 3D motion tracking as a reference and a field study comprising 12 subjects performing a 3.2-km run in a real-world setup. The results show that the foot trajectory estimation algorithm performs best, achieving a mean error of 0.032 ± 0.274 m/s for the velocity estimation and 0.022 ± 0.157 m for the stride length. An interesting alternative for systems with a low energy budget is the acceleration-based approach. Our results support the implementation decision for running velocity and distance tracking using IMUs embedded in the sole of a running shoe.

An orthotopic xenograft model for high-risk non-muscle invasive bladder cancer in mice: influence of mouse strain, tumor cell count, dwell time and bladder pretreatment.

BACKGROUND: Novel theranostic options for high-risk non-muscle invasive bladder cancer are urgently needed. This requires a thorough evaluation of experimental approaches in animal models best possibly reflecting human disease before entering clinical studies. Although several bladder cancer xenograft models were used in the literature, the establishment of an orthotopic bladder cancer model in mice remains challenging. METHODS: Luciferase-transduced UM-UC-3LUCK1 bladder cancer cells were instilled transurethrally via 24G permanent venous catheters into athymic NMRI and BALB/c nude mice as well as into SCID-beige mice. Besides the mouse strain, the pretreatment of the bladder wall (trypsin or poly-L-lysine), tumor cell count (0.5 × 106-5.0 × 106) and tumor cell dwell time in the murine bladder (30 min - 2 h) were varied. Tumors were morphologically and functionally visualized using bioluminescence imaging (BLI), magnetic resonance imaging (MRI), and positron emission tomography (PET). RESULTS: Immunodeficiency of the mouse strains was the most important factor influencing cancer cell engraftment, whereas modifying cell count and instillation time allowed fine-tuning of the BLI signal start and duration - both representing the possible treatment period for the evaluation of new therapeutics. Best orthotopic tumor growth was achieved by transurethral instillation of 1.0 × 106 UM-UC-3LUCK1 bladder cancer cells into SCID-beige mice for 2 h after bladder pretreatment with poly-L-lysine. A pilot PET experiment using 68Ga-cetuximab as transurethrally administered radiotracer revealed functional expression of epidermal growth factor receptor as representative molecular characteristic of engrafted cancer cells in the bladder. CONCLUSIONS: With the optimized protocol in SCID-beige mice an applicable and reliable model of high-risk non-muscle invasive bladder cancer for the development of novel theranostic approaches was established.

Improving susceptibility of neuroendocrine tumors to radionuclide therapies: personalized approaches towards complementary treatments.

Radionuclide therapies are an important tool for the management of patients with neuroendocrine neoplasms (NENs). Especially [131I]MIBG and [177Lu]Lu-DOTA-TATE are routinely used for the treatment of a subset of NENs, including pheochromocytomas, paragangliomas and gastroenteropancreatic tumors. Some patients suffering from other forms of NENs, such as medullary thyroid carcinoma or neuroblastoma, were shown to respond to radionuclide therapy; however, no general recommendations exist. Although [131I]MIBG and [177Lu]Lu-DOTA-TATE can delay disease progression and improve quality of life, complete remissions are achieved rarely. Hence, better individually tailored combination regimes are required. This review summarizes currently applied radionuclide therapies in the context of NENs and informs about recent advances in the development of theranostic agents that might enable targeting subgroups of NENs that previously did not respond to [131I]MIBG or [177Lu]Lu-DOTA-TATE. Moreover, molecular pathways involved in NEN tumorigenesis and progression that mediate features of radioresistance and are particularly related to the stemness of cancer cells are discussed. Pharmacological inhibition of such pathways might result in radiosensitization or general complementary antitumor effects in patients with certain genetic, transcriptomic, or metabolic characteristics. Finally, we provide an overview of approved targeted agents that might be beneficial in combination with radionuclide therapies in the context of a personalized molecular profiling approach.

Gaitmap-An Open Ecosystem for IMU-Based Human Gait Analysis and Algorithm Benchmarking.

Goal: Gait analysis using inertial measurement units (IMUs) has emerged as a promising method for monitoring movement disorders. However, the lack of public data and easy-to-use open-source algorithms hinders method comparison and clinical application development. To address these challenges, this publication introduces the gaitmap ecosystem, a comprehensive set of open source Python packages for gait analysis using foot-worn IMUs. Methods: This initial release includes over 20 state-of-the-art algorithms, enables easy access to seven datasets, and provides eight benchmark challenges with reference implementations. Together with its extensive documentation and tooling, it enables rapid development and validation of new algorithm and provides a foundation for novel clinical applications. Conclusion: The published software projects represent a pioneering effort to establish an open-source ecosystem for IMU-based gait analysis. We believe that this work can democratize the access to high-quality algorithm and serve as a driver for open and reproducible research in the field of human gait analysis and beyond.

Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

BACKGROUND: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies. OBJECTIVE: The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back-worn inertial sensors. METHODS: Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back-worn inertial sensors. RESULTS: The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids. CONCLUSIONS: Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health. TRIAL REGISTRATION: ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-050785.

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device.

This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and - 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application.Trial registration: ISRCTN - 12246987.

Remotely controlled diffusion from magnetic liposome microgels.

The reversible, temperature-dependent change in the permeability of a phospholipid bilayer has been used for controlling the diffusion rate of encapsulated molecular payload from liposomes. Liposomes were preloaded with a fluorescent dye and immobilized in calcium alginate hydrogel microparticles that also contained iron oxide nanoparticles. The composite microparticles were produced by a drop-on-demand inkjet method. The ability of iron oxide nanoparticles to locally dissipate heat upon exposure to a radio-frequency (RF) alternating magnetic field was used to control the local temperature and therefore diffusion from the liposomes in a contactless way using an RF coil. Several different release patterns were realized, including repeated on-demand release. The internal structure of the composite alginate-liposome-magnetite microparticles was investigated, and the influence of microparticle concentration on the heating rate was determined. In order to achieve a temperature rise required for the liposome membrane melting, the concentration of alginate beads should be at least 25% of their maximum packing density for the nanoparticle concentration and specific absorption rate used.

Design, Synthesis, and Biological Evaluation of Small-Molecule-Based Radioligands with Improved Pharmacokinetic Properties for Imaging of Programmed Death Ligand 1.

Small molecules offer some advantages for developing positron emission tomography (PET) tracers and are therefore a promising approach for imaging and therapy monitoring of programmed death ligand 1 (PD-L1) positive tumors. Here, we report six biphenyl PD-L1 radioligands using the NODA-GA-chelator for efficient copper-64 complexation. These radioligands contain varying numbers of sulfonic and/or phosphonic acid groups, serving as hydrophilizing units to lower the log D7.4 value down to -4.28. The binding affinities of compounds were evaluated using saturation binding and a real-time binding assay, with a highest binding affinity of 21 nM. Small-animal PET imaging revealed vastly different pharmacokinetic profiles depending on the quantity and type of hydrophilizing units. Of the investigated radioligands, [64Cu]Cu-3 showed the most favorable kinetics in vitro. This was also found in vivo, with a predominantly renal clearance and a specific uptake in the PD-L1-overexpressing tumor. With further modifications, this compound could be a promising candidate for the imaging of PD-L1 in the clinical setting.

Comparative Saturation Binding Analysis of 64Cu-Labeled Somatostatin Analogues Using Cell Homogenates and Intact Cells.

The development of novel ligands for G-protein-coupled receptors (GPCRs) typically entails the characterization of their binding affinity, which is often performed with radioligands in a competition or saturation binding assay format. Since GPCRs are transmembrane proteins, receptor samples for binding assays are prepared from tissue sections, cell membranes, cell homogenates, or intact cells. As part of our investigations on modulating the pharmacokinetics of radiolabeled peptides for improved theranostic targeting of neuroendocrine tumors with a high abundance of the somatostatin receptor sub-type 2 (SST2), we characterized a series of 64Cu-labeled [Tyr3]octreotate (TATE) derivatives in vitro in saturation binding assays. Herein, we report on the SST2 binding parameters measured toward intact mouse pheochromocytoma cells and corresponding cell homogenates and discuss the observed differences taking the physiology of SST2 and GPCRs in general into account. Furthermore, we point out method-specific advantages and limitations.

Automated assessment of foot elevation in adults with hereditary spastic paraplegia using inertial measurements and machine learning.

BACKGROUND: Hereditary spastic paraplegias (HSPs) cause characteristic gait impairment leading to an increased risk of stumbling or even falling. Biomechanically, gait deficits are characterized by reduced ranges of motion in lower body joints, limiting foot clearance and ankle range of motion. To date, there is no standardized approach to continuously and objectively track the degree of dysfunction in foot elevation since established clinical rating scales require an experienced investigator and are considered to be rather subjective. Therefore, digital disease-specific biomarkers for foot elevation are needed. METHODS: This study investigated the performance of machine learning classifiers for the automated detection and classification of reduced foot dorsiflexion and clearance using wearable sensors. Wearable inertial sensors were used to record gait patterns of 50 patients during standardized 4 [Formula: see text] 10 m walking tests at the hospital. Three movement disorder specialists independently annotated symptom severity. The majority vote of these annotations and the wearable sensor data were used to train and evaluate machine learning classifiers in a nested cross-validation scheme. RESULTS: The results showed that automated detection of reduced range of motion and foot clearance was possible with an accuracy of 87%. This accuracy is in the range of individual annotators, reaching an average accuracy of 88% compared to the ground truth majority vote. For classifying symptom severity, the algorithm reached an accuracy of 74%. CONCLUSION: Here, we show that the present wearable gait analysis system is able to objectively assess foot elevation patterns in HSP. Future studies will aim to improve the granularity for continuous tracking of disease severity and monitoring therapy response of HSP patients in a real-world environment.

Epigenetic drugs in somatostatin type 2 receptor radionuclide theranostics and radiation transcriptomics in mouse pheochromocytoma models.

Pheochromocytomas and paragangliomas (PCCs/PGLs) are catecholamine-producing tumors. In inoperable and metastatic cases, somatostatin type 2 receptor (SSTR2) expression allows for peptide receptor radionuclide therapy with [177Lu]Lu-DOTA-TATE. Insufficient receptor levels, however, limit treatment efficacy. This study evaluates whether the epigenetic drugs valproic acid (VPA) and 5-Aza-2'-deoxycytidine (DAC) modulate SSTR2 levels and sensitivity to [177Lu]Lu-DOTA-TATE in two mouse PCC models (MPC and MTT). Methods: Drug-effects on Sstr2/SSTR2 were investigated in terms of promoter methylation, mRNA and protein levels, and radiotracer binding. Radiotracer uptake was measured in subcutaneous allografts in mice using PET and SPECT imaging. Tumor growth and gene expression (RNAseq) were characterized after drug treatments. Results: DAC alone and in combination with VPA increased SSTR2 levels along with radiotracer uptake in vitro in MPC (high-SSTR2) and MTT cells (low-SSTR2). MTT but not MPC allografts responded to DAC and VPA combination with significantly elevated radiotracer uptake, although activity concentrations remained far below those in MPC tumors. In both models, combination of DAC, VPA and [177Lu]Lu-DOTA-TATE was associated with additive effects on tumor growth delay and specific transcriptional responses in gene sets involved in cancer and treatment resistance. Effects of epigenetic drugs were unrelated to CpG island methylation of the Sstr2 promoter. Conclusion: This study demonstrates that SSTR2 induction in mouse pheochromocytoma models has some therapeutic benefit that occurs via yet unknown mechanisms. Transcriptional changes in tumor allografts associated with epigenetic treatment and [177Lu]Lu-DOTA-TATE provide first insights into genetic responses of PCCs/PGLs, potentially useful for developing additional strategies to prevent tumor recurrence.