Manual Protocol Research Articles

A Survey of Manual Therapy Techniques and Protocols Used to Prevent or Treat Dysphagia in Head and Neck Cancer Patients During and after Radiation Therapy.

Authoritative research demonstrating efficacy of traditional dysphagia therapy for Head & Neck Cancer (HNC) patients is limited. A 2019 survey reported speech-language-pathologists (SLPs) have started using Manual Therapy (MT) to prevent or rehabilitate dysphagia in HNC patients. This application of MT is supported theoretically but no research has established efficacy. Further, specific contents of MT protocols employed in this setting remain unknown. In the absence of HNC dysphagia specific MT protocols, this study aimed to better understand MT protocols employed by SLPs to prevent and treat dysphagia in HNC patients during and after Radiation Therapy (RT). An internet-based questionnaire for SLPs who use MT with HNC patients was developed and tested for face/content validity. It was sent to SLPs practicing in the USA, twice, through three national listservs (ASHA-SIG13, ASHA-SIG3, University of Iowa Voiceserv). Of 64 respondents, 44 completed the survey. Of the 44, 15(34%) provided proactive MT during RT, 37(84%) provided proactive MT after RT (to prevent dysphagia), and 44(100%) provided reactive MT after RT (to treat dysphagia). 40(91%) were trained in MT through a CE course and 25(57%) had HNC-specific MT training. The most common MT techniques were laryngeal manipulation (LM) and myofascial release (MFR). During RT, MT protocols are gentler and highly tailored, with simple home programs of mild intensity. After RT, protocols are more regimented and aggressive, but still highly customized, with more diverse home programs of at least moderate intensity. MT for HNC patients lacks a standard protocol or approach, but MFR and LM, or components of those techniques, are used most frequently. Given the frequency with which MFR and LM are employed to treat dysphagia during and post-RT, and the lack of empirical evidence supporting or refuting their use, a collaboratively designed RCT is warranted to establish the safety and efficacy of MT for HNC patients.

Rapid Analysis of Fentanyl and Fentanyl Analogues from Whole Blood Using SPME Coupled to the Microfluidic Open Interface.

Fentanyl and its analogues are potent opioids that pose a significant threat to society. Over the last several years, considerable focus has been on the concerning trend of increasing fentanyl usage among drug users. Fentanyl analogues are mainly synthesized to evade analytical detection or increase their potency; thus, very low concentrations are sufficient to achieve a therapeutic effect. In an effort to help combat the synthetic opioid epidemic, developing targeted mass spectrometric methods for quantifying fentanyl and its analogues at ultralow concentrations is incredibly important. Most methods used to analyze fentanyl and its analogues from whole blood require manual sample preparation protocols (solid-phase extraction or liquid-liquid extraction), followed by chromatographic separation and mass spectrometric detection. The main disadvantages of these methods are the tedious sample preparation workflows, resulting in lengthy analysis times. To mitigate these issues, we present a targeted method capable of analyzing 96 samples containing fentanyl, several fentanyl analogues, and a common fentanyl (analogue) precursor simultaneously in 2.4 min per sample. This is possible by using a high-throughput solid phase microextraction workflow on the Concept96 autosampler followed by manual coupling of solid-phase microextraction fibers to the microfluidic open interface for tandem mass spectrometry analysis. Our quantitative method is capable of extremely sensitive analysis, with limits of quantification ranging from 0.002 to 0.031 ng mL-1 and linearity ranging from 0.010 to 25.0 ng mL-1. The method shows very good reproducibility (1-18%), accuracy (81-100%) of calibration and validation points, and good interday reproducibility (6-15%).

Automated Protocol for Monitoring Droplets and Fomites on Surfaces

During the COVID-19 pandemic, extensive efforts focused on developing a better understanding of indirect transmission routes, environmental monitoring of fomites, and suitable surveillance strategies, providing new perspectives to also face other communicable diseases. Rapid methods for monitoring environmental contamination are strongly needed to support risk assessment, epidemiological surveillance and prevent infections from spreading. We optimized and automatized a protocol based on fomite detection by qPCR, using a microbial-signature approach based on marker genes belonging to the microbiota of droplets or different biological fluids. The procedure was implemented by exploiting the available tools developed for SARS-CoV-2 tracing, such as flocked swab sampling, real-time PCR equipment and automatic extraction of nucleic acids. This approach allowed scaling up, simplifying, and speeding up the extraction step of environmental swabs, processing at least 48 samples within 45 min vs. 90 min for about 24 samples by manual protocols. A comparison of microflora data by Next-Generation Sequencing (NGS) strongly supports the effectiveness of this semiautomated extraction procedure, providing good quality DNA with comparable representation of species as shown by biodiversity indexes. Today, equipment for qPCR is widely available and relatively inexpensive; therefore this approach may represent a promising tool for hospital hygiene in surveilling fomites associated with SARS-CoV-2 or other pathogen’s transmission.

Out‐of‐the box automated computation of cortical thickness of the medial perirhinal cortex does not replace segmentation by hand

AbstractBackgroundCortical thickness of the medial perirhinal cortex (mPRC) is a promising marker of early, potentially pre‐clinical Alzheimer’s disease (AD) because atrophy of this region is causally linked to intracellular neurofibrillary tangles. Neurofibrillary pathology, a major neuropathological characteristic of AD, typically starts in the mPRC, also referred to as the transentorhinal cortex. From there it spreads to the entorhinal cortex and eventually to the hippocampus. To date, no tools exist that automatically compute the cortical thickness of the mPRC, most likely because of the novelty and complexity of the manual segmentation protocol and the large variability of the morphology of the mPRC. Herein, we aimed to develop an automated segmentation algorithm for the mPRC.MethodAn experienced rater (SK) manually segmented the mPRC from two data sets (train: n = 103; test: n = 44) using the FreeSurfer segmentation tools. The train data set (mean age = 76.4 ± 7.0 years; normal controls and patients with AD) was used to train the native FreeSurfer segmentation algorithm with the custom region as well as a voxel‐based deep convolutional neural network based on nnUNet with minimal adaptations to the training protocol. In a next step, the trained models were applied to the test data set (mean age = 69.2 ± 10.4 years; normal controls, AD, major depression, and mild cognitive impairment or dementia due to other etiologies than AD) and cortical thickness values were extracted. Finally, cortical thickness values of both segmentations were compared individually to the manual segmentation.ResultsIntraclass correlation coefficients (ICCs) between FreeSurfer and the manual segmentation reached .768 for the left hemisphere (lh) and .835 for the right hemisphere (rh). The deep learning method compared to the manual segmentation achieved ICCs of .840 for lh and .896 for rh.ConclusionThe deep learning based procedure outperformed the native FreeSurfer segmentation in this complicated segmentation task. Nevertheless, it did not reach inter‐human reliability (SK vs. unexperienced rater (NAH): lh = .953 and rh = .986). Next steps are customization of the deep learning algorithm and validation of clinical usefulness.

The Pattern of Hippocampus and Entorhinal Cortex Subregion Atrophy in Early Alzheimer’s Disease

AbstractBackgroundAtrophy of the hippocampus and entorhinal cortex (EC) develops early in Alzheimer’s disease (AD). The nature of atrophy along the anterior‐posterior longitudinal axis of the hippocampus and EC in individuals with amnestic mild cognitive impairment (aMCI) with positive AD biomarkers (AD aMCI) has been less researched. We aimed to reveal a possible different pattern of atrophy in longitudinal axis of the hippocampus and EC between AD aMCI individuals and those with AD biomarker negative aMCI (non‐AD aMCI).MethodIn total, 100 older adults with AD aMCI (n = 26), non‐AD aMCI (n = 23), mild AD dementia (n = 22) and cognitively normal (CN; n = 29) from the Czech Brain Aging Study (CBAS) underwent clinical and cognitive testing, and brain MRI with the 3‐dimensional T1‐weighted high‐resolution magnetization‐prepared rapid gradient echo sequences. An automated processing pipeline using the Advanced Normalization Tools based on the CBAS population template and a manual segmentation protocol were used to measure left and right subregional hippocampus and EC volumes including hippocampus head (HH), body (HB) and tail (HT), and anterolateral (alEC) and posteromedial (pmEC) entorhinal cortex volumes, respectively. Volumes were normalized to estimated total intracranial volume.ResultCompared to the CN group, the AD aMCI group had lower subregional hippocampus and EC volumes (p<0.05) except for right and left HH volumes. Compared to the non‐AD aMCI group, the AD aMCI group had lower right HB (p<0.05), right and left HT (p<0.01), right alEC (p<0.05), and right (p<0.01) and left (p<0.05) pmEC volumes. The mild AD dementia group had lower all subregional hippocampus and EC volumes compared to the CN group (p<0.05).ConclusionThese results are in line with previous research that demonstrated atrophy of the hippocampus and EC in early AD and indicate that atrophy of the posterior hippocampus and EC subregions may reflect AD pathology in aMCI individuals. Volumetric differences along the anterior‐posterior axis of the hippocampus and EC could serve as a potential biomarker to identify the underlying pathology in different neurodegenerative diseases.

Automatic epicardial adipose tissue segmentation in pulmonary computed tomography venography using nnU-Net.

Epicardial adipose tissue (EAT) is a key aspect in the investigation of cardiac pathophysiology. We sought to develop a deep learning (DL) model for fully automatic extraction and quantification of EAT through pulmonary computed tomography venography (PCTV) images. In this retrospective study, we included 128 patients with atrial fibrillation and PCTV from 2 hospitals. A DL model for automated EAT segmentation was developed from a training set of 51 patients and a validation set of 13 patients from hospital A. The algorithm was further validated using an internal test set of 16 patients from hospital A and an external test set of 48 patients from hospital B. The consistency and measurement agreement of EAT quantification were compared between the DL model and the conventional manual protocol using the Dice score coefficient (DSC), Hausdorff distance (HD95), Pearson correlation coefficient, and Bland-Altman plot. In the internal and external test set, automated segmentation with DL was successful in all cases. The total analysis time was shorter for DL than for manual reconstruction (5.43±2.52 vs. 106.20±15.90 min; P<0.001). The EAT segmented with the DL model had good consistency with manual segmentation (the DSC of the internal and external test sets were 0.92±0.02 and 0.88±0.03, respectively). The quantification of EAT evaluated with the 2 methods showed excellent correlation (all correlation coefficients >0.9; all P values <0.001) and minimal measurement difference. The proposed DL model achieved fully automatic quantification of EAT from PCTV images. The yielded results were highly consistent with those of manual quantification.

B-020 Fully Automated and Scalable cfDNA Extraction Solution from up to 10 mL Samples

Abstract Background The use of circulating, cell-free DNA (cfDNA) is rapidly evolving in the clinical landscape, becoming one of the fastest growing areas in recent years. It offers tremendous clinical potential as a screening method for tumor, cancer, disease progression, treatment response, and more. Circulating DNA is found in low quantities and often requires large sample input volumes to isolate the less abundant cfDNA to sufficient amounts needed for downstream analysis. The existing methods for extraction are often silica spin column-based, which involve an extensive amount of hands-on work, and they require large volumes of binding buffers, making it unsuitable for extractions involving sample volumes as large as 10 mL. These existing workflows impose certain limitations in terms of the sample volume and number of samples that they can process. Methods To tackle this necessity, Omega Bio-tek has developed a fully automated solution using Mag-Bind® cfDNA Kit (M3298) to extract cfDNA from up to 10 mL volumes from 48 samples in 2.75 h when integrated on Hamilton’s Microlab® STAR™ platform. Results The system is scalable and can extract from sample volumes ranging from 1–10 mL without any hardware modification or additional, expensive accessories on the Hamilton workstation. Here, we elucidate the workings of this automated protocol using Omega Bio-tek’s Mag-Bind® cfDNA Kit and compare its performance to a manual extraction protocol from 4 mL of plasma processed using the same kit. We also present additional solutions using the Mag-Bind® cfDNA kit to showcase extraction of fragments as small as 50 bp with minimal genomic DNA contamination. Conclusion Omega Bio-tek’s custom workflows provides the customers with different protocols to fit their different application needs. Thus, this kit offers researchers and scientists the flexibility to use the same kit for not only large volume sample processing but also for recovering short cfDNA fragments.

Automated Sample Preparation Workflow for Tandem Mass Tag-Based Proteomics.

Although tandem mass tag (TMT)-based isobaric labeling has become a powerful approach for multiplexed protein quantitation, automating the workflow for this technique has not been easy to achieve for widespread adoption. This is because preparation of TMT-labeled peptide samples involves multiple steps ranging from protein extraction, denaturation, reduction, and alkylation to tryptic digestion, desalting, labeling, and cleanup, all of which require a high level of proficiency. The variability resulting from multiple processing steps is inherently problematic, especially with large-scale clinical studies that involve hundreds of samples where reproducibility is critical for quantitation. Here, we sought to compare the performance of a recently introduced platform, AccelerOme, for an automated proteomic workflow employing TMT labeling with the manual processing of samples. Cell pellets were prepared and subjected to a 16-plex experiment using an automated platform and a conventional manual protocol. Single-shot liquid chromatography with tandem mass spectrometry analysis revealed a higher number of proteins and peptides identified using the automated platform. Efficiency of tryptic digestion, alkylation, and TMT labeling were similar in both manual and automated processes. In addition, comparison of quantitation accuracy and precision showed similar performance in an automated workflow compared to manual sample preparation by an expert. Overall, we demonstrated that the automated platform performs at a level similar to a manual process performed by an expert for TMT-based proteomics. We anticipate that this automated workflow will increasingly replace manual pipelines and has the potential to be applied to large-scale TMT-based studies, providing robust results and high sample throughput.

FEP Protocol Builder: Optimization of Free Energy Perturbation Protocols Using Active Learning.

Significant improvements have been made in the past decade to methods that rapidly and accurately predict binding affinity through free energy perturbation (FEP) calculations. This has been driven by recent advances in small-molecule force fields and sampling algorithms combined with the availability of low-cost parallel computing. Predictive accuracies of ∼1 kcal mol-1 have been regularly achieved, which are sufficient to drive potency optimization in modern drug discovery campaigns. Despite the robustness of these FEP approaches across multiple target classes, there are invariably target systems that do not display expected performance with default FEP settings. Traditionally, these systems required labor-intensive manual protocol development to arrive at parameter settings that produce a predictive FEP model. Due to the (a) relatively large parameter space to be explored, (b) significant compute requirements, and (c) limited understanding of how combinations of parameters can affect FEP performance, manual FEP protocol optimization can take weeks to months to complete, and often does not involve rigorous train-test set splits, resulting in potential overfitting. These manual FEP protocol development timelines do not coincide with tight drug discovery project timelines, essentially preventing the use of FEP calculations for these target systems. Here, we describe an automated workflow termed FEP Protocol Builder (FEP-PB) to rapidly generate accurate FEP protocols for systems that do not perform well with default settings. FEP-PB uses an active-learning workflow to iteratively search the protocol parameter space to develop accurate FEP protocols. To validate this approach, we applied it to pharmaceutically relevant systems where default FEP settings could not produce predictive models. We demonstrate that FEP-PB can rapidly generate accurate FEP protocols for the previously challenging MCL1 system with limited human intervention. We also apply FEP-PB in a real-world drug discovery setting to generate an accurate FEP protocol for the p97 system. FEP-PB is able to generate a more accurate protocol than the expert user, rapidly validating p97 as amenable to free energy calculations. Additionally, through the active-learning workflow, we are able to gain insight into which parameters are most important for a given system. These results suggest that FEP-PB is a robust tool that can aid in rapidly developing accurate FEP protocols and increasing the number of targets that are amenable to the technology.

Establishing and testing a robot-based platform to enable the automated production of nanoparticles in a flexible and modular way

Robotic systems facilitate relatively simple human–robot interaction for non-robot experts, providing the flexibility to implement different processes. In this context, shorter process times, as well as an increased product and process quality could be achieved. Robots short time-consuming processes, take over ergonomically unfavorable tasks and work efficiently all the time. In addition, flexible production is possible while maintaining or even increasing safety. This study describes the successful development of a dual-arm robot-based modular infrastructure and the establishment of an automated process for the reproducible production of nanoparticles. As proof of concept, a manual synthesis protocol for silica nanoparticle preparation with a diameter of about 200 nm as building blocks for photonic crystals was translated into a fully automated process. All devices and components of the automated system were optimized and adapted according to the synthesis requirements. To demonstrate the benefit of the automated nanoparticle production, manual (synthesis done by lab technicians) and automated syntheses were benchmarked. To this end, different processing parameters (time of synthesis procedure, accuracy of dosage etc.) and the properties of the produced nanoparticles were compared. We demonstrate that the use of the robot not only increased the synthesis accuracy and reproducibility but reduced the personnel time and costs up to 75%.

Pragmatic Considerations When Extracting DNA for Metagenomics Analyses of Clinical Samples.

Microbiome analyses are essential for understanding microorganism composition and diversity, but interpretation is often challenging due to biological and technical variables. DNA extraction is a critical step that can significantly bias results, particularly in samples containing a high abundance of challenging-to-lyse microorganisms. Taking into consideration the distinctive microenvironments observed in different bodily locations, our study sought to assess the extent of bias introduced by suboptimal bead-beating during DNA extraction across diverse clinical sample types. The question was whether complex targeted extraction methods are always necessary for reliable taxonomic abundance estimation through amplicon sequencing or if simpler alternatives are effective for some sample types. Hence, for four different clinical sample types (stool, cervical swab, skin swab, and hospital surface swab samples), we compared the results achieved from extracting targeted manual protocols routinely used in our research lab for each sample type with automated protocols specifically not designed for that purpose. Unsurprisingly, we found that for the stool samples, manual extraction protocols with vigorous bead-beating were necessary in order to avoid erroneous taxa proportions on all investigated taxonomic levels and, in particular, false under- or overrepresentation of important genera such as Blautia, Faecalibacterium, and Parabacteroides. However, interestingly, we found that the skin and cervical swab samples had similar results with all tested protocols. Our results suggest that the level of practical automation largely depends on the expected microenvironment, with skin and cervical swabs being much easier to process than stool samples. Prudent consideration is necessary when extending the conclusions of this study to applications beyond rough estimations of taxonomic abundance.

Automatization of metabolite extraction for high-throughput metabolomics: case study on transgenic isoprene-emitting birch.

Metabolomics studies are becoming increasingly common for understanding how plant metabolism responds to changes in environmental conditions, genetic manipulations and treatments. Despite the recent advances in metabolomics workflow, the sample preparation process still limits the high-throughput analysis in large-scale studies. Here, we present a highly flexible robotic system that integrates liquid handling, sonication, centrifugation, solvent evaporation and sample transfer processed in 96-well plates to automatize the metabolite extraction from leaf samples. We transferred an established manual extraction protocol performed to a robotic system, and with this, we show the optimization steps required to improve reproducibility and obtain comparable results in terms of extraction efficiency and accuracy. We then tested the robotic system to analyze the metabolomes of wild-type and four transgenic silver birch (Betula pendula Roth) lines under unstressed conditions. Birch trees were engineered to overexpress the poplar (Populus × canescens) isoprene synthase and to emit various amounts of isoprene. By fitting the different isoprene emission capacities of the transgenic trees with their leaf metabolomes, we observed an isoprene-dependent upregulation of some flavonoids and other secondary metabolites as well as carbohydrates, amino acid and lipid metabolites. By contrast, the disaccharide sucrose was found to be strongly negatively correlated to isoprene emission. The presented study illustrates the power of integrating robotics to increase the sample throughput, reduce human errors and labor time, and to ensure a fully controlled, monitored and standardized sample preparation procedure. Due to its modular and flexible structure, the robotic system can be easily adapted to other extraction protocols for the analysis of various tissues or plant species to achieve high-throughput metabolomics in plant research.

Insight into Increased Recovery and Simplification of Genomic DNA Extraction Methods from Dried Blood Spots.

There is no consensus on how to perform the manual extraction of nucleic acids from dried blood spots (DBSs). Current methods typically involve agitation of the DBSs in a solution for varying amounts of time with or without heat, and then purification of the eluted nucleic acids with a purification protocol. We explored several characteristics of genomic DNA (gDNA) DBS extraction such as extraction efficiency, the role of red blood cells (RBCs) in extraction and critical kinetic factors to understand if these protocols can be simplified while maintaining sufficient gDNA recovery. We found that agitation in a RBC lysis buffer before performing a DBS gDNA extraction protocol increases yield 1.5 to 5-fold, depending upon the anticoagulant used. The use of an alkaline lysing agent along with either heat or agitation was sufficient to elute quantitative polymerase chain reaction (qPCR) amplifiable gDNA in 5 minutes. This work adds insight into the extraction of gDNA from DBSs with the intention of informing a simple, standardized manual protocol for extraction.

Temporo-basal sulcal connections: a manual annotation protocol and an investigation of sexual dimorphism and heritability.

The temporo-basal region of the human brain is composed of the collateral, the occipito-temporal, and the rhinal sulci. We manually rated (using a novel protocol) the connections between rhinal/collateral (RS-CS), collateral/occipito-temporal (CS-OTS) and rhinal/occipito-temporal (RS-OTS) sulci, using the MRI of nearly 3400 individuals including around 1000 twins. We reported both the associations between sulcal polymorphisms as well with a wide range of demographics (e.g. age, sex, handedness). Finally, we also estimated the heritability, and the genetic correlation between sulcal connections. We reported the frequency of the sulcal connections in the general population, which were hemisphere dependent. We found a sexual dimorphism of the connections, especially marked in the right hemisphere, with a CS-OTS connection more frequent in females (approximately 35-40% versus 20-25% in males) and an RS-CS connection more common in males (approximately 40-45% versus 25-30% in females). We confirmed associations between sulcal connections and characteristics of incomplete hippocampal inversion (IHI). We estimated the broad sense heritability to be 0.28-0.45 for RS-CS and CS-OTS connections, with hints of dominant contribution for the RS-CS connection. The connections appeared to share some of their genetic causing factors as indicated by strong genetic correlations. Heritability appeared much smaller for the (rarer) RS-OTS connection.

Osteopathic Manipulative Treatment of Chronic Pelvic Pain due to High-Tone Pelvic Floor Dysfunction

Context: Chronic pelvic pain syndrome (CPPS) is a complex pain syndrome that affects 15%–30% of people of childbearing age (~10–20 million, US). Etiologies range from musculoskeletal conditions and visceral disease to neurological and psychological disorders. The interplay of many systems and disorders can manifest into a complex pathophysiology that is difficult to diagnose and treat. Dysfunction of the musculoskeletal system is often involved in patients with CPPS, either as the cause of pain or the result of underlying disease or dysfunction. Hypertonicity of pelvic floor muscles, myofascial trigger points, and dysfunctional shortening of the levator ani group of muscles contribute to the structural and functional abnormalities involved in CPPS. Osteopathic physicians are in a unique position to directly address this somatic dysfunction with a nonpharmacologic, nonsurgical approach: osteopathic manipulative treatment (OMT).Objectives: The purpose of this article is to review the literature on manual treatment efficacy for high-tone pelvic floor dysfunction (HTPFD) and the standardization of diagnosis to provide rational, medically based treatments. The second purpose is to elucidate the steps that the medical, and specifically the osteopathic profession can take to standardize pelvic floor evaluation, diagnosis, and treatment in the primary care setting.&#x0D; Methods: A search was conducted on the US National Library of Medicine’s PubMed database for studies involving manual therapy treatment for HTPFD. The authors excluded studies that described manual therapy interventions aimed at increasing pelvic floor muscle tone in patients with urinary incontinence and/or pelvic organ prolapse.Results: For perspective, the initial search using the keywords “chronic pelvic pain syndrome” led to 2,281 publications since 1974; the addition of “osteopathic” led to 10 results since 2009. The search for “high-tone pelvic floor dysfunction” led to 30 publications since 1992; the addition of “osteopathic” yielded no results. To evaluate the efficacy of manual therapy for HTPFD, the search was expanded to include any manual therapy protocols. While the consensus in the literature is that manual treatment for chronic pelvic pain (CPP) is efficacious, the finding is limited by the lack of a comprehensive protocol to appropriately diagnose and treat the patient. The authors propose a system to standardize the assessment of a patient with CPP in the primary care setting by an appropriately trained physician so that pelvic floor dysfunction is recognized, properly diagnosed and treated, or referred to specialized care.Conclusion: The literature supports that manual therapy is an effective treatment for CPP, and as primary care providers, osteopathic physicians are uniquely placed to recognize and treat patients with HTPFD, providing an empathetic, patient-centered approach. Standardization of the diagnosis and manual treatment of HTPFD is required to assess and monitor patients systematically. Development of an advanced training program for clinicians to learn diagnostic approaches and OMTfor the pelvic floor should be required since the techniques addressing the pelvic floor musculature are often not included in traditional training.

Excellent Interrater Reliability for Manual Segmentation of the Medial Perirhinal Cortex.

Objective: Evaluation of interrater reliability for manual segmentation of brain structures that are affected first by neurofibrillary tau pathology in Alzheimer's disease. Method: Medial perirhinal cortex, lateral perirhinal cortex, and entorhinal cortex were manually segmented by two raters on structural magnetic resonance images of 44 adults (20 men; mean age = 69.2 ± 10.4 years). Intraclass correlation coefficients (ICC) of cortical thickness and volumes were calculated. Results: Very high ICC values of manual segmentation for the cortical thickness of all regions (0.953-0.986) and consistently lower ICC values for volume estimates of the medial and lateral perirhinal cortex (0.705-0.874). Conclusions: The applied manual segmentation protocol allows different raters to achieve remarkably similar cortical thickness estimates for regions of the parahippocampal gyrus. In addition, the results suggest a preference for cortical thickness over volume as a reliable measure of atrophy, especially for regions affected by collateral sulcus variability (i.e., medial and lateral perirhinal cortex). The results provide a basis for future automated segmentation and collection of normative data.

Effectiveness of a Manual Therapy Protocol in Women with Pelvic Pain Due to Endometriosis: A Randomized Clinical Trial.

A randomized controlled trial was carried out to assess the effectiveness of a manual therapy protocol in terms of the clinical characteristics, quality of life, and emotional condition of the women with endometriosis-related pelvic pain. Forty-one women (mean age of 36.10 (6.97) years) with pelvic pain due to endometriosis were randomly divided into (i) a manual therapy group (MTG) (n = 21) and (ii) a placebo group (PG) (n = 20). Both groups received an 8-week intervention. Pain, lumbar mobility, endometriosis health profile, quality of life, depression and anxiety levels, and the patient's perception of change were assessed before (T0) and after (T1) the intervention, as well as at a one-month follow-up (T2) and a six-month follow-up (T3). The MTG significantly improved pain intensity, powerlessness, lumbar mobility, and physical quality of life at T1 (p < 0.05). The results were maintained for pain intensity at T2 and T3. In addition, both the MTG and PG improved emotional wellbeing at T1 (p < 0.05). Neither group improved in terms of social support, self-image, and depression and anxiety levels after the intervention (p > 0.05). In conclusion, manual therapy may be an excellent complement to the gynecological treatment of endometriosis-related pelvic pain by alleviating pain and improving women's endometriosis health profile and physical quality of life.

Automated radiosynthesis of [89Zr]Zr-DFOSq-Durvalumab for imaging of PD-L1 expressing tumours in vivo

Objectives89Zr-labelled proteins are gaining importance in clinical research in a variety of diseases. To date, no clinical study has been reported that utilizes an automated approach for radiosynthesis of 89Zr-labelled radiopharmaceuticals. We aim to develop an automated method for the clinical production of 89Zr-labelled proteins and apply this method to Durvalumab, a monoclonal antibody targeting PD-L1 immune-checkpoint protein. PD-L1 expression is poorly understood and can be up-regulated over the course of chemo- and radiotherapy treatment. The ImmunoPET multicentre study aims to examine the dynamics of PD-L1 expression via 89Zr-Durvalumab PET imaging before, during, and after chemoradiotherapy. The developed automated technique will enable reproducible clinical production of [89Zr]Zr-DFOSq-Durvalumab for this study at three different sites. MethodsConjugation of Durvalumab to H3DFOSqOEt was optimized for optimal chelator-to-antibody ratio. Automated radiolabelling of H3DFOSq-Durvalumab with zirconium-89 was optimized on the disposable cassette based iPHASE technologies MultiSyn radiosynthesizer using a modified cassette. Activity losses were tracked using a dose calibrator and minimized by optimizing fluid transfers, reaction buffer, antibody formulation additives and pH. The biological profile of the radiolabelled antibody was confirmed in vivo in PD-L1+ (HCC827) and PD-L1- (A549) murine xenografts. Clinical process validation and quality control were performed at three separate study sites to satisfy clinical release criteria. ResultsH3DFOSq-Durvalumab with an average CAR of 3.02 was obtained. Radiolabelling kinetics in succinate (20 mM, pH 6) were significantly faster when compared to HEPES (0.5 M, pH 7.2) with >90 % conversion observed after 15 min. Residual radioactivity in the 89Zr isotope vial was reduced from 24 % to 0.44 % ± 0.18 % (n = 7) and losses in the reactor vial were reduced from 36 % ± 6 % (n = 4) to 0.82 % ± 0.75 % (n = 4) by including a surfactant in the reaction and formulation buffers. Overall process yield was 75 % ± 6 % (n = 5) and process time was 40 min. Typically, 165 MBq of [89Zr]Zr-DFOSq-Durvalumab with an apparent specific activity of 315 MBq/mg ± 34 MBq/mg (EOS) was obtained in a volume of 3.0 mL. At end-of-synthesis (EOS), radiochemical purity and protein integrity were always >99 % and >96 %, respectively, and dropped to 98 % and 65 % after incubation in human serum for 7 days at 37 °C. Immunoreactive fraction in HEK293/PD-L1 cells was 83.3 ± 9.0 (EOS). Preclinical in vivo data at 144 h p.i. showed excellent SUVmax in PD-L1+ tumour (8.32 ± 0.59) with a tumour-background ratio of 17.17 ± 3.96. [89Zr]Zr-DFOSq-Durvalumab passed all clinical release criteria at each study site and was deemed suitable for administration in a multicentre imaging trial. ConclusionFully automated production of [89Zr]Zr-DFOSq-Durvalumab for clinical use was achieved with minimal exposure to the operator. The cassette-based approach allows for consecutive productions on the same day and offers an alternative to currently used manual protocols. The method should be broadly applicable to other proteins and has the potential for clinical impact considering the growing number of clinical trials investigating 89Zr-labelled antibodies.

Dipeptidyl peptidase 4 (DPP4) in fecal samples: validation of the extraction methodology and stability in short-term storage conditions.

This study assesses the clinical relevance of dipeptidyl peptidase 4 (DPP4) membrane exopeptidase as a biomarker of inflammatory bowel disease (IBD). A spike-and-recovery approach of DPP4 in fecal samples was used to compare two different methods for protein extraction, followed by a stability assessment. Fecal samples of healthy volunteers spiked with known concentrations of recombinant DPP4 were processed using a standard manual extraction protocol and the CALEX® protocol. The two methods were compared by quantification of fecal DPP4 by ELISA, followed by Bland-Altman analysis. For the stability assays DPP4 was extracted from fecal samples and stored under different conditions of temperature and time after collection. In general, the levels of spiked DPP4 in stool samples were lower with the manual protocol than in those obtained with the CALEX® method; this trend was corroborated by Bland-Altman analysis. Nonetheless, variability was within the acceptable limits for both protocols. In the stability assessment, no statistically significant differences were found between the results obtained under the different storage conditions. Both manual and CALEX® protocols provided equal extraction ability of DPP4 from stool samples. In addition, DPP4 provided flexibility in terms of sample storage enabling the accurate assessment of samples delivered up to a week before analysis.

Automatic and manual segmentation of the piriform cortex: Method development and validation in patients with temporal lobe epilepsy and Alzheimer's disease

The piriform cortex (PC) is located at the junction of the temporal and frontal lobes. It is involved physiologically in olfaction as well as memory and plays an important role in epilepsy. Its study at scale is held back by the absence of automatic segmentation methods on MRI. We devised a manual segmentation protocol for PC volumes, integrated those manually derived images into the Hammers Atlas Database (n= 30) and used an extensively validated method (multi-atlas propagation with enhanced registration, MAPER) for automatic PC segmentation. We applied automated PC volumetry to patients with unilateral temporal lobe epilepsy with hippocampal sclerosis (TLE; n= 174 including n= 58 controls) and to the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; n= 151, of whom with mild cognitive impairment (MCI), n= 71; Alzheimer's disease (AD), n= 33; controls, n= 47). In controls, mean PC volume was 485 mm3 on the right and 461 mm3 on the left. Automatic and manual segmentations overlapped with a Jaccard coefficient (intersection/union) of ~0.5 and a mean absolute volume difference of ~22 mm3 in healthy controls, ~0.40/ ~28 mm3 in patients with TLE, and ~ 0.34/~29 mm3 in patients with AD. In patients with TLE, PC atrophy lateralised to the side of hippocampal sclerosis (p< .001). In patients with MCI and AD, PC volumes were lower than those of controls bilaterally (p< .001). Overall, we have validated automatic PC volumetry in healthy controls and two types of pathology. The novel finding of early atrophy of PC at the stage of MCI possibly adds a novel biomarker. PC volumetry can now be applied at scale.