Robotic-assisted pedicle screw placement and full-endoscopic transforaminal lumbar interbody fusion (FE-TLIF) are established minimally invasive spine techniques. Their integration has the potential to combine navigation accuracy with the muscle-preserving advantages of uniportal endoscopy. This technical note describes a hybrid approach using the Mazor X Stealth edition robotic system to enhance workflow, safety, and efficiency during FE-TLIF. A 74-year-old patient with metabolic syndrome presented with severe back and radicular leg pain that was refractory to conservative treatment. Magnetic resonance imaging demonstrated bilateral lateral recess stenosis, disc height loss, and facet arthropathy at L4–5, with dynamic instability observed on flexion-extension radiographs. Preoperative computed tomography imaging was uploaded to the robotic system for trajectory planning. Following registration, the robotic arm guided percutaneous pedicle screw placement via Wiltse incisions. Uniportal endoscopic access enabled hemilaminotomy, facetectomy, discectomy, endplate preparation, and insertion of an expandable L4–5 interbody cage under direct visualization. Robotic guidance facilitated precise screw trajectory placement without repeated fluoroscopic localization, reduced intraoperative radiation exposure, and avoided muscle disruption associated with open approaches. Endoscopic visualization enabled controlled facet resection and preservation of neural elements during cage placement. Postoperative radiographs confirmed appropriate implant positioning. The combined workflow improved surgical ergonomics and minimized tissue trauma while maintaining fusion stability. Robotic-assisted FE-TLIF represents a safe and feasible hybrid minimally invasive surgery technique that enhances pedicle screw accuracy and complements endoscopic fusion. Despite a steep learning curve, this approach may reduce perioperative morbidity, improve procedural efficiency, and enhance postoperative recovery. Further comparative studies are required to evaluate long-term clinical and radiographic outcomes.

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.