Sung, Jaeyun

Abstract Background Upper-airway and respiratory conditions impose a large and growing global burden, yet there is no standardized way to assess whether a nasal microbiome is “healthy”. Currently, monitoring remains reactive, beginning only after symptoms manifest. The nasal cavity is well suited to proactive monitoring: it shapes respiratory health and pathogen colonization resistance, and can be sampled non-invasively and repeatedly. To address this gap, we introduce the Nasal Microbiome Wellness Index (NMWI), a disease-agnostic, continuous score of nasal microbiome health derived from LASSO-penalized logistic regression. Rather than counting taxa, it learns which taxa (and in what balance) characterize a healthy nose and returns the predicted log-odds that a profile resembles a healthy state. The index was trained on 1654 nasal 16S rRNA gene amplicon sequencing samples (589 healthy, 1065 non-healthy) pooled from 27 publicly available studies, uniformly reprocessed through a single computational pipeline. Results The NMWI comprises an interpretable signature of 24 taxa whose combined relative abundances determine the health-associated log-odds. Health-associated genera such as Corynebacterium and Cutibacterium raised the score, while dysbiosis-associated genera such as Pseudomonas and Escherichia – Shigella lowered it. The NMWI substantially outperformed the Shannon, Simpson, and Chao1 diversity indices, which showed negligible, directionally inconsistent separation between healthy and non-healthy samples (|Cliff’s δ | = 0.01–0.20), whereas the NMWI produced large, consistent separation ( δ = 0.65). It achieved a balanced accuracy of 74.37% on the training data (resubstitution estimate), and 73.43% under repeated 10-times 10-fold cross-validation. Performance remained stable at mean balanced accuracy of 73.82% under a leave-one-study-out framework, reflecting cross-study generalizability. In independent external cohorts, the balanced accuracy was 71.49%, and leave-one-disease-out analysis (in which each disease condition was withheld from training) showed a mean balanced accuracy of 63.92% across unseen conditions, consistent with a disease-agnostic design. The index also generalized across heterogeneous datasets spanning multiple 16S rRNA gene hypervariable regions—to our knowledge the first demonstration of such cross-study, cross-region transferability for the nasal cavity. Conclusions The NMWI distills a complex nasal microbial profile into a single interpretable score computed directly from the 16S rRNA gene data that dominate existing nasal research, making it immediately applicable to published and future datasets without re-sequencing. By replacing descriptive, diversity-based comparison with a quantitative standard, it offers a reproducible, open-source foundation for cross-study benchmarking, individual-level phenotyping, and longitudinal respiratory wellness monitoring.

Background Lewy body disease (LBD) is a progressive neurodegenerative a-synucleinopathy, whereas isolated REM sleep behavior disorder (iRBD) is recognized as a prodromal stage of LBD. Although growing evidence implicates the gut–brain axis in neurodegeneration, the taxonomic and functional roles of the gut microbiome across the prodromal-to-symptomatic LBD continuum remain poorly defined. Methods Here, we performed shotgun metagenomic sequencing on stool samples from 25 patients with LBD (10 mild cognitive impairment due to LBD [MCI-LB] and 15 dementia with Lewy bodies [DLB]), 10 individuals with iRBD, and their household matched cohabitant controls to characterize disease-associated microbial alterations while minimizing environmental confounding. Results Despite no significant differences in global microbial diversity, we identified convergent shifts in microbial taxa, metabolic pathways, and gene families across disease stages. Both LBD and iRBD showed increased abundance of microbial taxa potentially associated with gut barrier disruption, as well as higher abundance of functional pathways related to lipopolysaccharide biosynthesis. LBD showed lower abundance of pathways related to complex carbohydrate fermentation, and both groups showed lower abundance of pathways associated with neurotransmitter-related metabolism. In particular, pathways and gene families associated with starch degradation were reduced in LBD, and those associated with histidine-to-glutamate/ GABA metabolism were reduced in both groups. Discussion These exploratory findings represent the first high-resolution, shotgun metagenomic characterization of gut microbiome alterations across the LBD continuum, highlighting functional patterns that may serve as candidate markers of disease progression in future longitudinal and mechanistic studies.

Abstract Objective. Modern stereotactic neurosurgery increasingly relies on bilateral and multi-trajectory workflows (e.g. deep brain stimulation (DBS), stereoelectroencephalography (sEEG)), which can exceed the reach and flexibility of conventional frame-based systems. Building on our skull-mounted Navinetics D1 platform, we present a stereotactic frame (Navinetics E1) intended to expand the reachable work envelope, enable independent bilateral targeting, and preserve mechanical accuracy and patient comfort. Approach. We designed the Navinetics E1 stereotactic frame using a center-of-arc architecture with five degrees of freedom per hemisphere ( X, Y, Z , Arc, Collar) and two operating modes: Double Arm (independent left/right arms for simultaneous bilateral targeting) and Single Arm (mechanically coupled arms). The system was designed in CAD and fabricated via carbon fiber-reinforced polylactic acid (PLA-CF) additive manufacturing. Collision-aware MATLAB simulations quantified work volume and admissible approach directions. Mechanical targeting accuracy was evaluated on a ground truth fixture (GTF) platform, with mixed-effects modeling to assess target- and trajectory-dependent effects. Operative feasibility was assessed through an intraoperative entry-point replication test relative to the D1 system. Main results. Compared to the D1, the E1 frame significantly expanded key geometric ranges, including, most notably, 0°–360° Collar rotation and posterior Y -axis reach, thereby increasing the work volume and trajectory range by factors of 3.39 and 8.42, respectively. Mean GTF targeting deviation was 0.78 ± 0.38 mm in Single Arm mode and 1.23 ± 0.36 mm (right) and 1.65 ± 0.47 mm (left) in Double Arm mode. Entry-point replication across 17 clinical cases achieved 76.5% success in overlapping the reference points, providing preliminary evidence of feasibility under real operative conditions. Significance. The E1 frame extends a compact skull-mounted platform to support broader stereotactic reach and trajectory while enabling independent bilateral workflows. These features may reduce intraoperative reconfiguration for complex DBS and sEEG cases. Future work will focus on increasing structural stiffness, improving angular readout/setting, and developing MRI-compatible implementations.

BACKGROUND AND OBJECTIVES: External ventricular drain (EVD) placement is the most commonly performed bedside emergent neurosurgical procedure. However, catheter misplacement occurs in approximately 25% of cases, potentially resulting in neurological injury or the need for repositioning, highlighting the need for safer and more accurate placement techniques. This review aims to (1) summarize technological innovations developed to enhance the accuracy and safety of bedside EVD placement, (2) evaluate their reported benefits and limitations, and (3) identify key barriers to their clinical implementation in critical care settings. METHODS: We conducted a systematic review of PubMed, Embase, and Scopus combining terms related to EVD placement and assistive technologies. All the studies evaluated EVD placement using simulations, phantoms, cadavers, and patient procedures conducted at the bedside and in the operating room. RESULTS: We identified 3898 records, and 76 studies met the inclusion criteria. Of these, 30 studies compared stereotactic systems, ultrasound guidance, frameless neuronavigation, and augmented or mixed reality technologies to the freehand technique. These studies consistently reported improved accuracy with advanced systems although complication rates and procedural times were variably reported. An additional 35 and 12 studies evaluated nonimmersive and immersive technologies, respectively, in noncomparative settings. Most of these demonstrated high first-pass success and mean tip deviations under 3 mm. Variability in the definitions of accuracy and procedural metrics limited data synthesis, but the overall findings suggest a promising trajectory for technology-assisted EVD placement. CONCLUSION: Assistive technologies for EVD placement show potential to improve accuracy and safety over the freehand technique. These early successes signal potential to improve bedside neurosurgical care. Realizing this promise will require future studies to standardize accuracy metrics, report time, and safety outcomes consistently and validate performance in real-world critical care settings.

OBJECTIVE Achieving submillimetric accuracy in stereotactic neurosurgery remains critical for safely targeting deep brain structures. Current workflows rely on intraoperative CT to register stereotactic frames to preoperative imaging, but this introduces additional radiation exposure, cost, and workflow complexity. Three-dimensional surface scanning (3DSS) potentially offers a fast radiation-free alternative capable of capturing detailed craniofacial anatomy and frame geometry. Therefore, the aim of this cadaveric study was to evaluate the feasibility, accuracy, and navigational compatibility of integrating 3DSS into stereotactic workflows as a potential replacement for intraoperative CT. METHODS A human cadaveric head was imaged with both thin-slice CT and structured-light 3DSS after mounting stereotactic frame components. CT, 3DSS, and computer-aided design (CAD) models were registered using a multistep point cloud alignment pipeline involving the fast point feature histogram, the random sample consensus method, and the iterative closest point algorithm. Accuracy was assessed using surface deviation error, root mean square error (RMSE), and fiducial registration error within a commercial neuronavigation platform. RESULTS Fusion of the 3D facial scan with CT provided a mean surface deviation error of approximately 0.4 mm. Registration of the 3DSS-derived N-bar localizer to its CAD reference model produced a frame alignment RMSE of 1.3 mm. Within the navigation system, the 3DSS-based workflow achieved a mean fiducial registration error of 0.14 mm (range 0.02–0.20 mm), outperforming the conventional CT-based method (mean error 0.20 mm, range 0.09–0.40 mm). CONCLUSIONS The 3DSS-based method enabled precise submillimetric stereotactic registration without the need for intraoperative CT, reducing radiation exposure and operative complexity. This workflow is fully compatible with existing navigation systems and could serve as a practical radiation-free alternative in stereotactic neurosurgery. Future work will focus on automating frame detection, incorporating artificial intelligence–driven fusion methods, and validating this approach in live surgical settings.

BACKGROUND: Pharmacological treatments for fibrocalcific aortic valve stenosis (FCAVS) have been elusive for >50 years. Here, we tested the hypothesis that reactivation of oxidized sGC (soluble guanylate cyclase), the primary receptor for nitric oxide, with ataciguat is a safe and efficacious strategy to slow progression of FCAVS. METHODS: We used quantitative real-time reverse transcription polymerase chain reaction, Western blotting, and immunohistochemistry to characterize sGC signaling and the biological effects of ataciguat on signaling cascades related to nitric oxide, calcification, and fibrosis in excised human aortic valve tissue, aortic valve interstitial cells, and mouse aortic valves. We then conducted randomized, placebo-controlled phase I (14-day safety/tolerance) and phase II (6-month efficacy) trials in patients with moderate aortic valve stenosis. RESULTS: In excised human tissue, we found robust losses in sGC signaling despite upregulation of sGC subunits. In vitro, ataciguat increased sGC signaling and reduced BMP2 (bone morphogenetic protein 2) signaling in aortic valve interstitial cells. In mice with established FCAVS, treatment with ataciguat attenuated BMP signaling and slowed progression of valve calcification and dysfunction. In a phase I, randomized, placebo-controlled trial, treatment with ataciguat for 2 weeks was safe and well tolerated in patients with moderate FCAVS ( https://www.clinicaltrials.gov ; Unique identifier: NCT02049203). In a separate phase II, randomized, placebo-controlled trial, treatment with ataciguat for 6 months slowed the progression of aortic valve calcification and tended to slow the progression of valvular and ventricular dysfunction in patients with moderate FCAVS ( https://www.clinicaltrials.gov ; Unique identifier: NCT02481258). CONCLUSIONS: Collectively, this study highlights the therapeutic potential of the targeted restoration of the diseased/inactive form of sGC for treatment of FCAVS. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02049203. URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02481258.

Recent advancements in translational gut microbiome research have revealed its crucial role in shaping predictive healthcare applications. Herein, we introduce the Gut Microbiome Wellness Index 2 (GMWI2), an enhanced version of our original GMWI prototype, designed as a standardized disease-agnostic health status indicator based on gut microbiome taxonomic profiles. Our analysis involves pooling existing 8069 stool shotgun metagenomes from 54 published studies across a global demographic landscape (spanning 26 countries and six continents) to identify gut taxonomic signals linked to disease presence or absence. GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence (i.e., outside the “reject option”). This performance exceeds that of the original GMWI model and traditional species-level α-diversity indices, indicating a more robust gut microbiome signature for differentiating between healthy and non-healthy phenotypes across multiple diseases. When assessed through inter-study validation and external validation cohorts, GMWI2 maintains an average accuracy of nearly 75%. Furthermore, by reevaluating previously published datasets, GMWI2 offers new insights into the effects of diet, antibiotic exposure, and fecal microbiota transplantation on gut health. Available as an open-source command-line tool, GMWI2 represents a timely, pivotal resource for evaluating health using an individual’s unique gut microbial composition.

Abstract Summary We recently introduced the Gut Microbiome Wellness Index (GMWI), a stool metagenome-based indicator for assessing health by determining the likelihood of disease given the state of one’s gut microbiome. The calculation of our wellness index depends on the relative abundances of health-prevalent and health-scarce species. Encouragingly, GMWI has already been utilized in various studies focusing on differences in the gut microbiome between cases and controls. Herein, we introduce the GMWI-webtool, a user-friendly browser application that computes GMWI, health-prevalent/-scarce species’ relative abundances, and α-diversities from stool shotgun metagenome taxonomic profiles. Users of our interactive online tool can visualize their results and compare them side-by-side with those from our pooled reference dataset of metagenomes, as well as export data in.csv format and high-resolution figures. Availability and implementation GMWI-webtool is freely available here: https://gmwi-webtool.github.io/. Supplementary information Supplementary data are available at Bioinformatics online.