Medical Research Research Articles

Altering biomolecular condensates as a potential mechanism that mediates cannabidiol effect on glioblastoma.

Glioblastoma (GBM) is an extremely aggressive primary brain tumor with poor prognosis, short survival time post-diagnosis and high recurrence. Currently, no cure for GBM exists. The identification of an effective therapeutic modality for GBM remains a high priority amongst medical professionals and researches. In recent studies, inhalant cannabidiol (CBD) has demonstrated promise in effectively inhibiting GBM tumor growth. However, exactly how CBD treatment affects the physiology of these tumor cells remains unclear. Stress granules (SG) (a sub-class of biomolecular condensates (BMC)) are dynamic, membrane-less intracellular microstructures which contain proteins and nucleic acids. The formation and signaling of SGs and BMCs plays a significant role in regulating malignancies. This study investigates whether inhaled CBD may play an intervening role towards SGs in GBM tumor cells. Integrated bioinformatics approaches were preformed to gain further insights. This includes use of Immunohistochemistry and flow cytometry to measure SGs, as well as expression and phosphorylation of eukaryotic initiation factor-2α (eIF2α). The findings of this study reveal that CBD receptors (and co-regulated genes) have the potential to play an important biological role in the formation of BMCs within GBM. In this experiment, CBD treatment significantly increased the volume of TIAR-1. This increase directly correlated with elevation in both eIF2α expression and p-eIF2α in CBD treated tissues in comparison to the placebo group (p < 0.05). These results suggest that inhalant CBD significantly up-regulated SGs in GBM, and thus support a theory of targeting BMCs as a potential therapeutic substrate for treating GBM.

The Edifice of Vasculature-On-Chips: A Focused Review on the Key Elements and Assembly of Angiogenesis Models.

The conception of vascularized organ-on-a-chip models provides researchers with the ability to supply controlled biological and physical cues that simulate the in vivo dynamic microphysiological environment of native blood vessels. The intention of this niche research area is to improve our understanding of the role of the vasculature in health or disease progression in vitro by allowing researchers to monitor angiogenic responses and cell-cell or cell-matrix interactions in real time. This review offers a comprehensive overview of the essential elements, including cells, biomaterials, microenvironmental factors, microfluidic chip design, and standard validation procedures that currently govern angiogenesis-on-a-chip assemblies. In addition, we emphasize the importance of incorporating a microvasculature component into organ-on-chip devices in critical biomedical research areas, such as tissue engineering, drug discovery, and disease modeling. Ultimately, advances in this area of research could provide innovative solutions and a personalized approach to ongoing medical challenges.

Physiological paradigm for assessing reward prediction and extinction using cortical direct current potential responses in rats

Anticipating positive outcomes is a core cognitive function in the process of reward prediction. However, no neurophysiological method objectively assesses reward prediction in basic medical research. In the present study, we established a physiological paradigm using cortical direct current (DC) potential responses in rats to assess reward prediction. This paradigm consisted of five daily 1-h sessions with two tones, wherein the rewarded tone was followed by electrical stimulation of the medial forebrain bundle (MFB) scheduled at 1000 ms later, whereas the unrewarded tone was not. On day 1, both tones induced a negative DC shift immediately after auditory responses, persisting up to MFB stimulation. This negative shift progressively increased and peaked on day 4. Starting from day 3, the negative shift from 600 to 1000 ms was significantly larger following the rewarded tone than that following the unrewarded tone. This negative DC shift was particularly prominent in the frontal cortex, suggesting its crucial role in discriminative reward prediction. During the extinction sessions, the shift diminished significantly on extinction day 1. These findings suggest that cortical DC potential is related to reward prediction and could be a valuable tool for evaluating animal models of depression, providing a testing system for anhedonia.

ACcurate COnsensus Reporting Document (ACCORD) explanation and elaboration: Guidance and examples to support reporting consensus methods.

When research evidence is limited, inconsistent, or absent, healthcare decisions and policies need to be based on consensus among interested stakeholders. In these processes, the knowledge, experience, and expertise of health professionals, researchers, policymakers, and the public are systematically collected and synthesised to reach agreed clinical recommendations and/or priorities. However, despite the influence of consensus exercises, the methods used to achieve agreement are often poorly reported. The ACCORD (ACcurate COnsensus Reporting Document) guideline was developed to help report any consensus methods used in biomedical research, regardless of the health field, techniques used, or application. This explanatory document facilitates the use of the ACCORD checklist. This paper was built collaboratively based on classic and contemporary literature on consensus methods and publications reporting their use. For each ACCORD checklist item, this explanation and elaboration document unpacks the pieces of information that should be reported and provides a rationale on why it is essential to describe them in detail. Furthermore, this document offers a glossary of terms used in consensus exercises to clarify the meaning of common terms used across consensus methods, to promote uniformity, and to support understanding for consumers who read consensus statements, position statements, or clinical practice guidelines (CPGs). The items are followed by examples of reporting items from the ACCORD guideline, in text, tables, and figures. The ACCORD materials-including the reporting guideline and this explanation and elaboration document-can be used by anyone reporting a consensus exercise used in the context of health research. As a reporting guideline, ACCORD helps researchers to be transparent about the materials, resources (both human and financial), and procedures used in their investigations so readers can judge the trustworthiness and applicability of their results/recommendations.

Bacterial growth in patients with low back pain and Modic changes: protocol of a multicentre, case–control biopsy study

IntroductionBacterial infection and Modic changes (MCs) as causes of low back pain (LBP) are debated. Results diverged between two randomised controlled trials examining the effect of amoxicillin with and without...

Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures

The advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structures of biological macromolecules and their complexes significantly expedite biomedical research and drug discovery. However, automatically and accurately building atomic models from high-resolution cryo-EM density maps is still time-consuming and challenging when template-based models are unavailable. Artificial intelligence (AI) methods such as deep learning trained on limited amount of labeled cryo-EM density maps generate inaccurate atomic models. To address this issue, we created a dataset called Cryo2StructData consisting of 7,600 preprocessed cryo-EM density maps whose voxels are labelled according to their corresponding known atomic structures for training and testing AI methods to build atomic models from cryo-EM density maps. Cryo2StructData is larger than existing, publicly available datasets for training AI methods to build atomic protein structures from cryo-EM density maps. We trained and tested deep learning models on Cryo2StructData to validate its quality showing that it is ready for being used to train and test AI methods for building atomic models.

What do Australians affected by cancer think about oncology researchers sharing research data? A cross-sectional survey.

Previous research has shown patients and the public in Australia generally support medical researchers in making de-identified research data available to other scientists. However, this research has focussed on certain types of data and recipients. We surveyed Australians affected by cancer to characterize their attitudes toward the sharing of research data with multiple third parties, including the public. A short, anonymous online survey of Australians with a previous diagnosis of cancer was advertised between October 27, 2022, and February 27, 2023. Quantitative responses were analyzed with descriptive statistics. Free-text responses were coded deductively and summarised using content analysis. In total, 551 respondents contributed data to the survey. There was strong support for cancer researchers sharing non-human and de-identified human research data with clinicians (90% and 95%, respectively) and non-profit researchers (both 94%). However, fewer participants supported sharing data with for-profit researchers (both 64%) or publicly (both 61%). When asked if they would hypothetically consent to researchers at their treatment location using and sharing their de-identified data publicly, only half agreed. In contrast, after being shown a visual representation of the de-identified survey data, 80% of respondents supported sharing it publicly. Australians affected by cancer support the sharing of research data, particularly with clinicians and non-profit researchers. Our results also imply that visualization of the data to be shared may enhance support for making it publicly available. These results should help alleviate any concerns about research participants' attitudes toward data sharing, as well as boost researchers' motivation for sharing.

Peroperative administration of tranexamic acid in Roux-en-Y and one-anastomosis gastric bypass to reduce haemorrhage in patients with morbid obesity: protocol for randomised controlled trial (PATRY trial)

IntroductionBy implementation of Enhanced Recovery After Bariatric Surgery protocols and day-care surgery, early discharge poses a challenge if excessive bleeding occurs after bariatric surgery. Tranexamic acid (TXA) has demonstrated efficacy...

Improved Mass Calibration in MALDI MSI Using Neural Network-Based Recalibration.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a powerful imaging method for generating molecular maps of biological samples and has numerous applications in biomedical research. A key challenge in MALDI MSI is to reliably map observed mass peaks to theoretical masses, which can be difficult due to mass shifts that occur during the measurement process. In this paper, we propose MassShiftNet, a novel self-supervised learning framework for mass recalibration. We train a neural network on a data dependent and specifically augmented training data set to directly estimate and correct the mass shift in the observed spectra. In our evaluation, we show that this method is both able to reduce the absolute mass error and to increase the relative mass alignment between peptide MSI spectra acquired from FFPE-fixated tissue using a MALDI time-of-flight (TOF) instrument.

A Perspective on Protein Structure Prediction Using Quantum Computers.

Despite the recent advancements by deep learning methods such as AlphaFold2, in silico protein structure prediction remains a challenging problem in biomedical research. With the rapid evolution of quantum computing, it is natural to ask whether quantum computers can offer some meaningful benefits for approaching this problem. Yet, identifying specific problem instances amenable to quantum advantage and estimating the quantum resources required are equally challenging tasks. Here, we share our perspective on how to create a framework for systematically selecting protein structure prediction problems that are amenable for quantum advantage, and estimate quantum resources for such problems on a utility-scale quantum computer. As a proof-of-concept, we validate our problem selection framework by accurately predicting the structure of a catalytic loop of the Zika Virus NS3 Helicase, on quantum hardware.

Preparation of NIR-II Polymer Nanoprobe Through Twisted Intramolecular Charge Transfer and Förster Resonance Energy Transfer of NIR-I Dye.

Near-infrared-II (NIR-II) fluorescence imaging is pivotal in biomedical research. Organic probes exhibit high potential in clinical translation, due to advantages such as precise structure design, low toxicity, and post-modifications convenience. In related preparation, enhancement of NIR-II tail emission from NIR-I dyes is an efficient method. In particular, the promotion of twisted intramolecular charge transfer (TICT) of relevant NIR-I dyes is a convenient protocol. However, present TICT-type probes still show disadvantages in relatively low emission, large particle sizes, or limited choice of NIR-I dyes, etc. Herein, the synthesis of stable small-sized polymer NIR-II fluoroprobes (e.g., 7.2nm), integrating TICT and Förster resonance energy transfer process to synergistically enhance the NIR-II emission is reported. Strong enhanced emissions can be obtained from various NIR-I dyes and lanthanide elements (e.g., twelvefold at 1250nm from Nd-DTPA/IR-808 sample). The fluorophore provides high-resolution angiography, with high-contrast imaging on middle cerebral artery occlusion model mice for distinguishing occlusion. The fluorophore can be rapidly excreted from the kidney (urine ≈65% within 4h) in normal mice and exhibits long-term renal retention on acute kidney injury mice, showing potential applications in the prognosis of kidney diseases. This development provides an effective strategy to design and synthesize effective NIR-II fluoroprobes.

Human versus machine: identifying ChatGPT-generated abstracts in Gynecology and Urogynecology.

ChatGPT, a publicly available artificial intelligence (AI) large language model, has allowed for sophisticated AI technology on demand. Indeed, use of ChatGPT has already begun to make its way into medical research. However, the medical community has yet to understand the capabilities and ethical considerations of AI within this context, and unknowns exist regarding ChatGPT's writing abilities, accuracy, and implications for authorship. We hypothesize that human reviewers and AI detection software differ in their ability to correctly identify original published abstracts and AI-written abstracts in the subjects of Gynecology and Urogynecology. We additionally suspect that concrete differences in writing errors, readability, and perceived writing quality exist between original and AI-generated text. Twenty-five articles published in high impact medical journals and a collection of Gynecology and Urogynecology journals were selected. ChatGPT was prompted to write 25 corresponding AI-generated abstracts, providing the abstract title, journal-dictated abstract requirements, and select original results. The original and AI-generated abstracts were reviewed by blinded Gynecology and Urogynecology faculty and fellows to identify the writing as original or AI-generated. All abstracts were analyzed by publicly available AI detection software GPTZero, Originality, and Copyleaks and were assessed for writing errors and quality by AI writing assistant Grammarly. One hundred fifty-seven reviews of 25 original and 25 AI-generated abstracts were conducted by 26 faculty and 4 fellows. Fifty-seven percent of original abstracts and 42.3% of AI-generated abstracts were correctly identified for an average of 49.7% across all abstracts. All three AI detectors rated the original abstracts as less likely be AI-written than the ChatGPT-generated abstracts (GPTZero 5.8 vs 73.3%, p<0.001; Originality 10.9 vs 98.1%, p<0.001; Copyleaks 18.6 vs 58.2%, p<0.001). The performance of the three AI detection software differed when analyzing all abstracts (p=0.03), original abstracts (p<0.001), and AI-generated abstracts (p<0.001). Grammarly text analysis identified more writing issues and correctness errors in original than AI abstracts, including lower Grammarly score reflective of poorer writing quality (82.3 vs 88.1, p=0.006), more total writing issues (19.2 vs 12.8, p<0.001), critical issues (5.4 vs 1.3, p<0.001), confusing words (0.8 vs 0.1, p=0.006), misspelled words (1.7 vs 0.6, p=0.02), incorrect determiner use (1.2 vs 0.2, p=0.002), and comma misuse (0.3 vs 0.0, p=0.005). Human reviewers are unable to detect the subtle differences between human and ChatGPT-generated scientific writing due to AI's ability to generate tremendously realistic text. AI detection software improve identification of AI-generated writing but still lack complete accuracy and require programmatic improvements in order to achieve optimal detection. As reviewers and editors may be unable to reliably detect AI-generated pieces, clear guidelines for reporting AI use by authors and implementing AI detection software in the review process will need to be established as AI chatbots gain more widespread use.

Retrospective Assessment of Translational Pharmacokinetic-Pharmacodynamic Modeling Performance: A Case Study with Apitolisib, a Dual PI3K/mTOR Inhibitor.

Despite significant progress in biomedical research, the rate of success in oncology drug development remains inferior to that of other therapeutic fields. Mechanistic models provide comprehensive understanding of the therapeutic effects of drugs, which is crucial for designing effective clinical trials. This study was performed to acquire a better understanding of PI3K-AKT-TOR pathway modulation and preclinical to clinical translational bridging for a specific compound, apitolisib (PI3K/mTOR inhibitor), by developing integrated mechanistic models. Integrated pharmacokinetic (PK)-pharmacodynamic (PD)-efficacy models were developed for xenografts bearing human renal cell adenocarcinoma and for patients with solid tumors (phase 1 studies) to characterize relationships between exposure of apitolisib, modulation of the phosphorylated Akt (pAkt) biomarker triggered by inhibition of the PI3K-AKT-mTOR pathway, and tumor response. Both clinical and preclinical integrated models show a steep sigmoid curve linking pAkt inhibition to tumor growth inhibition and quantified that a minimum of 35-45% pAkt modulation is required for tumor shrinkage in patients, based on platelet-rich plasma surrogate matrix and in xenografts based on tumor tissue matrix. Based on this relationship between targeted pAkt modulation and tumor shrinkage rate, it appeared that a constant pAkt inhibition of 61% and 65%, respectively, would be necessary to achieve tumor stasis in xenografts and patients. These results help when it comes to evaluating the translatability of the preclinical analysis to the clinical target, and provide information that will enhance the value of future preclinical translational dose-finding and dose-optimization studies to accelerate clinical drug development. ClinicalTrials.gov NCT00854152 and NCT00854126.

Bioprinting of Stable Bionic Interfaces Using Piezoresistive Hydrogel Organoelectronics.

Bionic tissues offer an exciting frontier in biomedical research by integrating biological cells with artificial electronics, such as sensors. One critical hurdle is the development of artificial electronics that can mechanically harmonize with biological tissues, ensuring a robust interface for effective strain transfer and local deformation sensing. In this study, a highly tissue-integrative, soft mechanical sensor fabricated from a composite piezoresistive hydrogel. The composite not only exhibits exceptional mechanical properties, with elongation at the point of fracture reaching up to 680%, but also maintains excellent biocompatibility across multiple cell types. Furthermore, the material exhibits bioadhesive qualities, facilitating stable cell adhesion to its surface. A unique advantage of the formulation is the compatibility with 3D bioprinting, an essential technique for fabricating stable interfaces. A multimaterial sensorized 3D bionic construct is successfully bioprinted, and it is compared to structures produced via hydrogel casting. In contrast to cast constructs, the bioprinted ones display a high (87%) cell viability, preserve differentiation ability, and structural integrity of the sensor-tissue interface throughout the tissue development duration of 10 d. With easy fabrication and effective soft tissue integration, this composite holds significant promise for various biomedical applications, including implantable electronics and organ-on-a-chip technologies.

Severe cardiac and skeletal manifestations in DMD-edited microminipigs: an advanced surrogate for Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is an intractable X-linked muscular dystrophy caused by mutations in the DMD gene. While many animal models have been used to study the disease, translating findings to humans has been challenging. Microminipigs, with their pronounced physiological similarity to humans and notably compact size amongst pig models, could offer a more representative model for human diseases. Here, we accomplished precise DMD modification in microminipigs by co-injecting embryos with Cas9 protein and a single-guide RNA targeting exon 23 of DMD. The DMD-edited microminipigs exhibited pronounced clinical phenotypes, including perturbed locomotion and body-wide skeletal muscle weakness and atrophy, alongside augmented serum creatine kinase levels. Muscle weakness was observed as of one month of age, respiratory and cardiac dysfunctions emerged by the sixth month, and the maximum lifespan was 29.9 months. Histopathological evaluations confirmed dystrophin deficiency and pronounced dystrophic pathology in the skeletal and myocardial tissues, demonstrating that these animals are an unprecedented model for studying human DMD. The model stands as a distinct and crucial tool in biomedical research, offering deep understanding of disease progression and enhancing therapeutic assessments, with potential to influence forthcoming treatment approaches.

FPM-WSI: Fourier ptychographic whole slide imaging via feature-domain backdiffraction

Fourier ptychographic microscopy (FPM) theoretically provides a solution to the trade-off between spatial resolution and field of view (FOV), and has promising prospects in digital pathology. However, block reconstruction and then stitching has become an unavoidable procedure for reconstruction of large FOV due to vignetting artifacts. This introduces digital stitching artifacts, as the existing image-domain optimization algorithms are highly sensitive to systematic errors. Such obstacles significantly impede the advancement and practical implementation of FPM, explaining why, despite a decade of development, FPM has not gained widespread recognition in the field of biomedicine. We report a feature-domain FPM (FD-FPM) based on the structure-aware forward model to realize stitching-free, full-FOV reconstruction. The loss function is uniquely formulated in the feature domain of images, which bypasses the troublesome vignetting effect and algorithmic vulnerability via feature-domain backdiffraction. Through massive simulations and experiments, we show that FD-FPM effectively eliminates vignetting artifacts for full-FOV reconstruction, and still achieves impressive reconstructions despite the presence of various systematic errors. We also found it has great potential in recovering the data with a lower spectrum overlapping rate, and in realizing digital refocusing without a prior defocus distance. With FD-FPM, we achieved full-color and high-throughput imaging (4.7 mm diameter FOV, 336 nm resolution in the blue channel) free of blocking-and-stitching procedures on a self-developed Fourier ptychographic microscopy whole slide imaging platform. The reported FD-FPM shows the value of FPM for various experimental circumstances, and offers physical insights useful for the developments of models for other computational imaging techniques. The reported platform demonstrates high-quality, high-speed imaging and low cost, and could find applications in many fields of biomedical research, as well as in clinical applications.

The End of the Beginning? Temporality and Bioagency in Pandemic Research.

This paper deals with the ways in which the intellectual and political history of AIDS can assist in the chronological conceptualization of a pandemic such as COVID-19 as it is unfolding. It problematizes the idea of pandemic "beginnings" and "ends" to show that such definitions are shaped by the disciplinary location and thematic foci of relevant scholars. Central to this analysis is the notion that ethical and political contexts affect research on a pandemic in different ways at national and global levels at various points in its trajectory. The article develops this argument in relation to two main themes: firstly, with reference to the history of AIDS research in South Africa; secondly, with the philosophical concept of bioagency to understand the ways in which viruses and humans co-shape the course of epidemics over time. I first make the case for the development of historically informed, long-term ethnographic studies of COVID-19. Using bioagency as a point of departure to consider viruses as social actors, the essay then critiques the notion of bioinformationalism as catalyzing the widening accessibility of biomedical research. Instead, I discuss the biotechnology and pharmaceutical industries as protagonists in the operation of biocapital. I argue that the history of AIDS in South Africa can provide methodological and theoretical insights into how to interpret an unfolding epidemic, outlining an ambitious transdisciplinary research agenda for thinking about the temporality of a pandemic spanning the different, interconnected, scales of life.

Competitivity Issues Related to Biobank Activity

The recent development of biomedical research and greater attention to the use of human bio-material has led to an increase in the number of studies devoted to biobanks. In considering the question of whether a biobank can be subject to insolvency, the present article discusses multiple points of view related to the legal status of biobanks according to which they are perceived either as an object or subject of law. From an analysis of the various organizational forms of biobank activity, the author argues that biobanks should be considered as subjects of law. Here considerations include accessing financial support from government, municipal, and other sources, the possibility of carrying out income-generating activities, mechanisms for the protection of obtained bio-material, the monitoring requirement related to entities carrying out such activities, and the possibility of recognizing such entities as insolvent. Based on the results of this research (including an analysis of the experience of foreign countries), the permissible organizational-legal forms that biobanks are instantiated, namely, public corporations, public-law companies, institutions, and public benefit funds. Because of the sensitivities involved, it is argued that such organizations should be of a non-profit character. In the light of the research question, special attention is paid to the form of a consortium. Due to the impossibility of liquidating the assets of biobank organizations in order to meet the claims of creditors, it is argued that such organizations cannot be declared insolvent.

Bronchiectasis in Türkiye: Data from a Multicenter Registry (Turkish Adult Bronchiectasis Database).

Bronchiectasis is a chronic lung disease characterized by permanent bronchial wall dilatation. Although it has been known as an orphan disease, it has recently gained attention because of registry-based studies and drug research. We aimed to use a multicenter database to analyze and compare data regarding the etiology, associated comorbidities, microbiological characteristics, and preventive strategies of bronchiectasis in Türkiye to those of other countries. A multicenter prospective cohort study. The multicenter, prospective cohort study was conducted between March 2019 and January 2022 using the Turkish Adult Bronchiectasis Database, in which 25 centers in Türkiye participated. Patients aged > 18 years who presented with respiratory symptoms such as cough, sputum, and dyspnea and were diagnosed with non-cystic fibrosis bronchiectasis using computed tomography were included in the study. Demographic information, etiologies, comorbidities, pulmonary functions, and microbiological, radiological, and clinical data were collected from the patients. Of the 1,035 study participants, 518 (50%) were females. The mean age of the patients was 56.1 ± 16.1 years. The underlying etiology was detected in 565 (54.6%) patients. While postinfectious origin was the most common cause of bronchiectasis (39.5%), tuberculosis was identified in 11.3% of the patients. An additional comorbidity was detected in 688 (66.5%) patients. The most common comorbidity was cardiovascular disease, and chronic obstructive pulmonary disease (COPD) and bronchiectasis was identified in 19.5% of the patients. The most commonly detected microbiological agent was Pseudomonas aeruginosa (29.4%). Inhaled corticosteroids (ICS) were used in 70.1% of the patients, and the frequency of exacerbations in the last year was significantly higher in patients using ICS than in nonusers (p < 0.0001). Age [odds ratio (OR): 1.028; 95% confidence interval (CI): 1.005-1.051], cachexia (OR: 4.774; 95% CI: 2,054-11,097), high modified medical research council dyspnea scale score (OR: 1,952; 95% CI: 1,459-2,611), presence of chronic renal failure (OR: 4,172; 95% CI: 1,249-13,938) and use of inhaled steroids (OR: 2,587; 95% CI: 1,098-6,098) were significant risk factors for mortality. Mortality rates were higher in patients with COPD than in those with no COPD (21.7-9.1%, p = 0.016). Patients with bronchiectasis and COPD exhibited more frequent exacerbations, exacerbation-related hospitalizations, and hospitalization in the intensive care unit in the previous year than patients without COPD. This is the first multicenter study of bronchiectasis in Türkiye. The study results will provide important data that can guide the development of health policies in Türkiye on issues such as infection control, vaccination, and the unnecessary use of antibiotics and steroids.

Cubital Tunnel Syndrome Due to Intraneural Ganglion Cysts of the Ulnar Nerve With Joint-Cyst Connection at the Elbow

BACKGROUND AND OBJECTIVES: The unifying articular theory suggests that intraneural ganglion cysts in the cubital tunnel arise from the elbow joint and are connected to the ulnar nerve through an articular branch. This study aimed to report our clinical experience with these cysts and our surgical findings and outcomes. METHODS: We retrospectively analyzed 13 patients who underwent surgery for cubital tunnel syndrome caused by an intraneural ganglion cyst of the ulnar nerve. Clinical symptoms, physical examination findings, nerve conduction testing electromyography, plain radiography, and ultrasonography were evaluated before and after surgery. MRI was performed in 2 patients. Cyst decompression, disconnection of the articular branch, and ulnar nerve transposition were performed in all. RESULTS: The mean follow-up was 29 months. After surgery, local elbow pain and Tinel sign disappeared in all patients, and the average Numerical Rating Scale dropped from 3.7 (2-5) to 0 (0-0). Two-point discrimination testing was normal (&lt;5.0 mm) in 12 patients. Wartenberg sign and “claw hand” deformity became negative, and muscle function and motor nerve conduction velocity were improved in 12 patients. The Medical Research Council muscle strength grade was M4 or M5 in the flexor carpi ulnaris, flexor digitorum profundus of the 4th and 5th digits, and first dorsal interosseous muscle in 12 patients. Postoperative spontaneous potentials including fibrillation and sharp waves, and motor unit recruitment in the first dorsal interosseous muscle were obviously improved. A cystic articular branch was confirmed during surgery in all patients. No cyst recurred clinically or on follow-up ultrasonography. CONCLUSION: The unifying articular theory of intraneural ganglion cysts applies to those located in the ulnar nerve at the elbow. Surgical disconnection of the articular nerve branch from the ulnar nerve eliminated the pathway for cyst recurrence and achieved good long-term outcomes.