Search Results (15,115)

Lipopolysaccharide (LPS), as the core active component of endotoxins from Gram-negative bacteria, serves as a mandatory quality control indicator in the biological safety evaluation of blood- and body fluid-contacting medical devices. Its rapid and accurate detection is of paramount importance for ensuring clinical patient safety and meeting global regulatory compliance requirements. Traditional endotoxin detection methods have inherent limitations, including poor anti-interference capability against medical device-specific matrices, limited automation capacity, and narrow regulatory applicability, which hinder their utility in meeting the practical demands of the modern medical device industry for high-throughput online quality control and on-site rapid screening. This review focuses on medical device-specific regulatory requirements, characteristics of extract matrices, and full-process quality control scenarios, and systematically summarizes the research progress in novel LPS-targeted biosensing detection technologies. By constructing a three-layer technical framework (biological recognition, interface engineering, and system integration), we provide a comparative assessment of four mainstream technologies—TLR4 biomimetic sensing, genetically engineered elements, EIS, and microfluidics—based on their matrix compatibility, automation potential, and regulatory compliance. It deeply analyzes the core role of microfluidic integration technology in driving the upgrading of detection systems towards automation, miniaturization and compliance, and objectively evaluates the applicability and limitations of various technologies in medical device scenarios. Unlike general reviews on LPS detection, this work specifically addresses endotoxin testing within the medical device quality control context. We systematically examine device-specific matrix interferences and regulatory landscapes, synthesizing cutting-edge research with critical analysis of industrialization bottlenecks. This review provides a theoretical foundation and technical roadmap for developing next-generation, pharmacopeial-compliant rapid automated endotoxin detection platforms—accelerating the advancement of medical device safety standards. Full article

Accurate monitoring of stress and workload in surgical environments is essential for improving performance and patient safety. Physiological signals, particularly heart rate variability (HRV), offer a promising approach for objective and continuous stress assessment. However, existing studies often rely on population-level models, limited temporal analysis, and evaluation strategies that may not reflect real-world generalisation. This study proposes an end-to-end pipeline for HRV-based classification of HRV-derived surrogate stress-like states in surgical settings, combining personalised feature extraction, surrogate label generation, and sequence-based deep learning. HRV data were collected from multiple surgeons during real colorectal procedures using wearable sensors and processed into minute-level feature representations. Stress labels were generated using subject-specific thresholds to account for individual physiological differences. Sequence-based models, including convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, were evaluated across multiple temporal window lengths and validation strategies. The results show that mean-based Standard Deviation of Normal-to-Normal intervals (SDNN) provided the most consistent separation of physiological states. The highest-performing models were most frequently associated with temporal windows of 10–20 min, while CNN and LSTM architectures achieved comparable performance. Notably, in this dataset, leave-one-subject-out (LOSO) validation produced performance that was comparable to, and in some configurations higher than, pooled random splits, highlighting the influence of evaluation strategy and the potential benefits of personalised labelling. Overall, this work suggests that personalised HRV-based modelling and temporal sequence analysis may provide a feasible approach for identifying HRV-derived stress-like physiological states in real surgical environments. The findings also emphasise the importance of rigorous evaluation design when developing physiological machine learning systems. Full article

Background: Next-generation sequencing (NGS)-detected ERBB2 amplification occurs in a subset of urothelial carcinomas, but its role as a treatment-selection marker for trastuzumab deruxtecan (T-DXd) remains uncertain. Methods: We retrospectively reviewed four patients with metastatic urothelial carcinoma treated with T-DXd in routine practice from 2024. Treatment selection was based on NGS-detected ERBB2 amplification because HER2 immunohistochemistry and in situ hybridization were unavailable. Results: Four men aged 65–76 years received T-DXd: one in the second line and three in the fourth or fifth line. The best radiological responses, abstracted from contemporaneous radiology reports and oncology medical records, were complete response in one patient, partial response in one, and stable disease in two. Three patients had previously received enfortumab vedotin. Documented adverse events included fatigue, anemia, diarrhea, rash, and leukopenia. No interstitial lung disease or pneumonitis was documented in the available records. Conclusions: These observations are descriptive and hypothesis-generating. They do not establish the efficacy or safety of T-DXd or validate ERBB2 amplification as a predictive biomarker, but they support prospective evaluation of genomic ERBB2 amplification when standard HER2 testing is unavailable. Full article

Additive manufacturing, also known as 3D printing (3DP), is intended to enable personalised medicine by producing drug products on demand at the Point of Care (PoC), with dose, drug-release profile, and geometry tailored to the individual patient. Despite its promise, widespread adoption is limited by the absence of ready-to-use quality control (QC) methods for printlets at the PoC. Process Analytical Technology (PAT) tools, particularly vibrational spectroscopic methods like Near-Infrared and Raman spectroscopy, can offer real-time monitoring to ensure the safety and consistency of printed dosage forms. Integrating these tools within a Quality-by-Design (QbD) framework can enhance process understanding, control variability, and minimise risk. Regulatory implementation and technological innovation remain essential for the broader clinical implementation of 3DP in pharmaceutical manufacturing. This review presents an overview of currently existing studies on PAT tools explored for non-destructive quality control across 3DP techniques, examines the correlation between Critical Process Parameters (CPPs), Critical Material Attributes (CMAs), and the Critical Quality Attributes (CQAs) of 3D-printed dosage forms within a QbD context, and outlines the current regulatory landscape alongside key limitations and future directions for the broader integration of 3DP into pharmaceutical development and manufacturing. Current evidence shows that PAT application remains uneven across printing technologies and is predominantly directed at final product quality control, rather than the real-time process monitoring required for a fully closed-loop QbD framework. Existing spectroscopic models are largely restricted to single formulations, printers, and APIs, and the absence of standardised validation reporting and transferability assessments represents a key barrier to routine implementation. Full article

Background/Objectives: Artificial intelligence (AI) is increasingly being evaluated for ophthalmic diagnosis, screening, and triage, yet its role in paediatric eye care remains less established than in adult ophthalmology. This systematic review aimed to synthesise evidence on AI-enabled tools for paediatric ophthalmic diagnosis, screening, triage, surveillance, and referral, with an emphasis on diagnostic performance, safety, workflow integration, equity, and implementation readiness in primary, community, and primary care-relevant settings. Methods: A PRISMA-guided systematic review was conducted using MEDLINE, Embase, Web of Science, Scopus, and IEEE Xplore from inception to 30 March 2026. Eligible studies evaluated AI or machine-learning tools for children and adolescents aged 0–18 years in relation to paediatric eye conditions. Study selection and data extraction were undertaken independently by reviewers, with disagreements resolved by consensus or third-reviewer adjudication. Methodological and reporting quality was evaluated using an author-adapted six-domain rubric informed by APPRAISE-AI. Diagnostic-accuracy studies were assessed using an author-adapted QUADAS-2 framework incorporating QUADAS-AI-informed AI-specific considerations, the prediction-model study was assessed using PROBAST+AI, and the non-randomised treatment-effect study was assessed using ROBINS-I. The public dataset descriptor was evaluated separately using an author-developed dataset-quality, representativeness, and applicability framework. Because of clinical and methodological heterogeneity, findings were synthesised thematically. Results: Twelve empirical studies and one public dataset descriptor were included, covering retinopathy of prematurity, retinoblastoma, amblyopia risk, myopia, congenital cataract, and visual-acuity assessment. AI systems frequently demonstrated promising diagnostic or screening performance, including sensitivity-first detection of treatment-requiring retinopathy of prematurity, high discrimination for retinoblastoma activity, and strong myopia prediction using fundus images. Several studies supported feasibility in neonatal, school, and community workflows using smartphone-based imaging, task-shifted operators, tele-referral, and human-in-the-loop review. However, external and temporal validation, calibration, patient-level reporting, subgroup and fairness assessment, and economic evaluation were limited. Conclusions: AI-enabled tools show promise for supporting selected paediatric ophthalmic screening, triage, and surveillance pathways, particularly when combined with image-quality control, explicit escalation, and human oversight. However, confidence in the reported performance is limited by single-centre studies and enriched samples, small numbers of clinically important cases, heterogeneous analytical units, potentially optimistic aggregation procedures, limited external or temporal validation, incomplete calibration, and absent fairness analyses. Routine autonomous implementation remains premature. Full article

Hyperpigmentation is a multifaceted process that involves the overproduction and uneven distribution of melanin. The number of patients with skin hyperpigmentation is on the rise, representing the most common complaint in dermatology clinics. Treatment focuses mainly on melanocyte reduction and stopping melanosome production due to their expected degradative effects. Kojic acid (KA), a widely known natural depigmenting agent of fungal origin, acts by inhibiting the action of tyrosinase, the enzyme that catalyzes melanin production. Although it has been used for many years in skin-lightening preparations, kojic acid suffers from many problems that reduce its efficacy, including poor chemical stability, hydrophilicity, and adverse effects. Many modern systems like polymeric, lipidic, and inorganic nanocarriers have been used to provide controlled release, improve the delivery of kojic acid to the target site of action, and provide protection during storage. Consequently, the aim of this narrative review is to present the current literature reports concerning the biological activity of kojic acid, with particular emphasis on recent advances in nanotechnology-based delivery systems, including lipidic, vesicular, polymeric, inorganic, and other emerging nanocarriers developed for pharmaceutical and cosmetic applications. This review also introduces prospective, next-generation delivery strategies that remain unaddressed in the current literature, which may optimize the therapeutic efficacy of kojic acid. It also reports the main challenges that face the use of nanoparticles for kojic acid delivery, namely, the lack of clinical validation, limited safety data, and large-scale production reproducibility, as well as regulatory constraints, thereby identifying key research gaps and future priorities that necessitate the prioritization of clinical evaluation of kojic acid delivery systems. Full article

Robotic-assisted minimally invasive esophagectomy (RAMIE) has emerged as an increasingly utilized approach for the surgical management of esophageal malignancies, offering potential advantages over conventional minimally invasive esophagectomy (MIE) and open esophagectomy (OE). Advances in robotic technology, enhanced visualization, instrument articulation, and surgeon ergonomics have facilitated wider adoption of RAMIE in thoracic surgical oncology. This review summarizes contemporary evidence regarding intraoperative, postoperative, oncologic, and patient-centered outcomes associated with RAMIE while highlighting emerging technologies and future directions in the field. Current literature, including randomized controlled trials, meta-analyses, propensity-matched studies, and international registry data, suggests that RAMIE is associated with reduced blood loss, improved lymph node harvest, and lower pulmonary morbidity compared with OE, while demonstrating outcomes comparable or favorable to conventional MIE. Oncologic outcomes, including R0 resection rates and overall survival, appear equivalent across approaches in most contemporary studies. In addition, robotic platforms may facilitate recurrent laryngeal nerve lymphadenectomy and complex mediastinal dissection. Despite these advantages, RAMIE is frequently associated with longer operative times and remains dependent on institutional expertise, surgeon experience, and resource availability. Current evidence is promising but remains limited by heterogeneity of surgical techniques, institutional expertise, and a relative scarcity of long-term randomized data. Emerging innovations including fluorescence-guided imaging, perfusion assessment technologies, artificial intelligence integration, augmented reality, and advanced robotic platforms may further enhance precision, safety, and personalization of esophageal cancer surgery. As robotic technology and perioperative systems continue to evolve, ongoing prospective investigation and long-term oncologic evaluation will remain essential to define the optimal role of RAMIE within multidisciplinary esophageal cancer care. Full article

Background: Modern hematology analyzers integrate multiparametric technologies and adaptive flagging algorithms to support rapid detection of abnormal leukocyte populations. The Sysmex XN-9100 employs the White Blood Cell Differential (WDF) channel for first-line screening and the White Precursor Cell (WPC) channel as a reflex test for improved detection of blasts and abnormal lymphocytes. Although widely implemented, the real-world diagnostic performance and workflow implications of this integrated strategy remain incompletely characterized. Objectives: To evaluate, in a large real-world cohort, the performance of the Sysmex XN-9100 WDF–WPC workflow, focusing on its diagnostic accuracy, its capability to identify pathological cases within the WDF-negative population, and its potential implications for blood smear review workload optimization. Methods: A retrospective analysis was performed on 4531 consecutive routine blood samples reviewed between February and June 2025. All samples were analyzed using the Sysmex XN-9100. WDF-positive cases (“Blasts/Abnormal lymphocytes?”) underwent reflex WPC testing (“Blasts?” and “Abnormal lymphocytes?”). Peripheral blood smear morphology, based on the evaluation of 200 leukocytes using the DI-60 digital imaging system, constituted the reference standard. Diagnostic performance metrics, including sensitivity, specificity, predictive values, likelihood ratios, accuracy, and ROC analysis, were calculated for WDF and WPC channels using both individual and aggregated flag evaluations. Results: The WDF-B/AL (White Blood Cell Differential Channel-“Blasts/Abnormal lymphocytes?”) flag demonstrated high sensitivity (88.24%) and negative predictive value (92.73%), supporting its role as an effective first-line screening tool, although specificity was limited (48.87%; AUC = 0.75). Unlike most previous studies, our workflow allowed evaluation of pathological cases occurring within the WDF-negative population, providing a realistic estimate of the false-negative burden. Disaggregated WPC analysis revealed complementary diagnostic profiles: WPC-B (White Precursor Cell Channel-“Blasts?”) showed higher specificity (77.71%) and overall discriminative performance (AUC = 0.81), whereas WPC-AL (White Precursor Cell Channel-“Abnormal lymphocytes?”) achieved higher sensitivity (92.18%) and negative predictive value (95.99%). Aggregated evaluation of WPC flags (logical OR) maximized sensitivity (92.68%) and reduced false-negative cases, supporting the role of the WPC channel as a second-level diagnostic safety net. Furthermore, within the integrated laboratory workflow, WPC-negative results may support the optimization of manual smear-review allocation when interpreted together with predefined institutional smear-review criteria, while maintaining diagnostic safety. Conclusions: The Sysmex XN-9100 WDF–WPC workflow constitutes a multilayered high-sensitivity screening strategy that prioritizes abnormality detection while optimizing laboratory efficiency. The complementary behavior of WPC-B and WPC-AL enhances overall workflow safety, whereas evaluation of WDF-negative pathological cases provides a more realistic assessment of screening performance than conventional reflex-based studies. Beyond analytical accuracy, the workflow may contribute to balancing diagnostic reliability, patient safety, and resource utilization in high-volume laboratory practice. Full article

Oncology care increasingly depends on heterogeneous sensing streams generated by computed tomography (CT), radiotherapy planning systems, wearable devices, home respiratory sensors, patient-reported outcomes, and clinical records. These data streams are often processed separately, limiting their value for longitudinal, context-aware review. This study proposes OncoSense-Agent, a reliability-aware agentic multimodal sensing architecture for CT-guided respiratory monitoring in oncology care. The architecture links CT-derived anatomical evidence with wearable physiology, respiratory symptoms, functional assessment, treatment context, and explainable human-in-the-loop review-priority generation. To move beyond a purely conceptual design, we implemented a lung-focused proof-of-concept with six bounded software agents: Imaging Reliability, Wearable Monitoring, Respiratory Review, Treatment Context, Multimodal Fusion, and Explainability. The prototype used real nnU-Net v2 3D lung segmentation metrics from 139 patients with complete bilateral lung CT data as the imaging anchor, while wearable, respiratory, symptom, and treatment-context channels were introduced as deterministic overlays for controlled validation. OncoSense-Agent changed review-priority assignment relative to CT-only assessment in 78/139 cases (56.1%), assigned 111/139 cases (79.9%) to high-priority or high-uncertainty tiers, and showed increasing Safety Gate activation as CT quality declined. Three illustrative cases demonstrate hidden respiratory deterioration, wearable data-quality uncertainty, and treatment-context risk not captured by CT-only assessment. The prototype does not establish clinical diagnostic accuracy, but demonstrates operational, auditable, reliability-aware multimodal review-priority generation for clinician-supervised oncology monitoring. Full article

Background: High-grade gliomas pose formidable challenges in neuro-oncology, with a median overall survival (OS) of 12–18 months. Laser interstitial thermal therapy (LITT) offers a minimally invasive cytoreductive option for deep-seated or recurrent tumors, achieving ablation rates of 85–98%. In parallel, artificial intelligence and machine learning are increasingly being applied to neuro-oncology to improve diagnosis, treatment planning, and outcome prediction, although these applications remain largely investigational. Methods: A literature search was conducted using the PubMed, MEDLINE, Embase, and ClinicalTrials.gov databases. The search terms included “laser interstitial thermotherapy,” “glioblastoma,” and “high-grade glioma”, “machine learning”, “artificial intelligence”. A total of 196 articles were identified. Inclusion criteria comprised primary studies, meta-analyses, and systematic reviews involving human data, with LITT used as a primary or secondary treatment modality. Sixty-nine studies were included in this review, while case reports and animal studies were excluded. Results: LITT represents a precision therapy for inoperable gliomas, achieving ablation rates of 85–98%. For primary glioblastoma, median overall survival (mOS) ranges from 11–16 months, and median progression-free survival (mPFS) from 4–9.5 months. In recurrent glioblastoma, LITT demonstrates a median overall survival ranging from 8.5 to 14.1 months and a median progression-free survival of 3–3.5 months with lower complication rates (5.7% vs. 13.8%) and shorter hospital stays (2.2 vs. 7 days). Overall complication rates range from 20–35%, predominantly due to cerebral edema, which is generally responsive to steroid therapy. Its value may be expanded by machine learning tools that integrate clinical, molecular, and imaging features to support patient selection and predict outcomes, though these remain at the proof-of-concept stage. In addition, LITT may serve as a platform for combination therapies, including immunotherapy, chemotherapy, targeted agents, and radiotherapy. Conclusions: Based on current evidence, LITT demonstrates outcomes that appear favorable in selected patient populations with high-grade gliomas and may be considered as a treatment option for primary tumors with challenging localization, near-spherical geometry, and volumes of approximately 30 cm³. It has a particularly important role in recurrent glioblastomas with similar characteristics, offering efficacy comparable to resection but with an improved safety profile in retrospective comparisons. LITT is evolving from a technically focused ablation method into a data-driven therapeutic platform. Integration with artificial intelligence may improve precision, safety, and personalization, helping define the role of LITT within modern neuro-oncology as higher-quality clinical evidence continues to accumulate. Full article

Background/Objectives: Ketamine has attracted interest in psychiatry due to its rapid antidepressant effects, particularly in patients with inadequate response to conventional treatments. This scoping review maps ketamine’s neuropharmacology, mechanisms of action, clinical applications, safety, and use in psychiatric disorders. Methods: This scoping review was conducted according to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. PubMed, Scopus, Web of Science, and Google Scholar were searched for English-language publications addressing ketamine pharmacology, clinical applications, and psychoactive effects. Included sources comprised randomized controlled trials, observational studies, systematic reviews, and relevant mechanistic studies, while non-English publications, editorials, commentaries, and studies without sufficient methodological information were excluded. Data were extracted using a structured data-charting form and synthesized narratively and thematically. Results: A total of 69 studies were included in the final synthesis. Ketamine demonstrated early improvements in depressive symptoms, especially in treatment-resistant depression (TRD), although the durability of benefits varied across studies. Intravenous racemic ketamine was the most extensively investigated administration route, while intranasal esketamine represents the primary approved formulation for TRD. Mechanistically, the drug acts through N-methyl-D-aspartate receptor antagonism and downstream modulation of glutamatergic signaling, synaptic plasticity and neural connectivity. Comparisons with conventional antidepressants and neuromodulatory interventions highlighted ketamine’s faster onset of action, although variability remained regarding long-term effects and treatment strategies. Conclusions: Ketamine represents an important rapid-acting treatment for TRD and severe depressive episodes associated with suicidal ideation. However, information regarding long-term efficacy and safety remains limited due to study heterogeneity, short follow-up periods, and variability in dosing protocols. Further research is needed to address gaps related to long-term outcomes, maintenance strategies, and optimal dosing approaches. Full article

Background/Objectives: Fecal microbiota transplantation (FMT) is an established treatment for recurrent or refractory Clostridioides difficile infection (rCDI) and is increasingly investigated for other gastrointestinal and neuropsychiatric conditions in children. However, pediatric safety data remains limited. This study aimed to evaluate the short-term safety of colonoscopy-delivered FMT in a heterogeneous pediatric cohort. Methods: We conducted a retrospective single-centre cohort study of all FMT procedures performed at Vilnius University Hospital Santaros Klinikos between 2017 and 2025. Fecal material from three screened healthy pediatric donors was delivered to the caecum via colonoscopy under general anesthesia. Adverse events (AEs) arising within 72 h of each procedure were identified from the clinical records and assigned a severity grade using version 5.0 of the Common Terminology Criteria for Adverse Events (CTCAE). AEs were analyzed on a per-procedure basis. Associations between sex, age, and underlying indication and AE occurrence were assessed using Fisher’s exact test and the Mann–Whitney U test. Results: A total of 108 FMT procedures were performed on 73 children aged 2 to 17 years. The predominant indication was autism spectrum disorder (ASD) and other developmental disorders (80.6%). AEs were reported after 11 procedures (10.2%); all were classified as CTCAE grade 1 or 2, and no serious AEs occurred. The most common AEs were diarrhoea (5.6%) and vomiting (2.8%). In an exploratory comparison, procedures performed for ASD were associated with a lower AE rate compared with other indications combined (6.9% vs. 23.8%; OR 0.24, 95% CI 0.06–0.87). Conclusions: Colonoscopy-delivered FMT was well tolerated in pediatric patients, with a favorable short-term safety profile consistent with published pediatric FMT literature. As follow-up was largely passive and the cohort was predominantly children with ASD, the observed rate should be regarded as a lower bound, and these findings warrant confirmation in prospective studies. Full article

Knee osteoarthritis (OA) is increasingly recognized as a whole-joint disorder involving periarticular soft tissues in addition to intra-articular structures. A recently published technical report described an ultrasound-guided posteromedial knee injection targeting a fascial–periarticular convergence region operationally termed the popliteal fascial retinaculum. In the present study, we evaluated preliminary longitudinal clinical outcomes after this procedure in patients with mild-to-moderate knee OA. Background/Objectives: Knee OA is a common cause of chronic pain, stiffness, and disability. In the present study, we evaluated preliminary 12-month WOMAC outcomes after a three-session ultrasound-guided posteromedial fascial–periarticular injection in patients with Kellgren–Lawrence grade 1–3 knee OA. Methods: This retrospective analysis of a prospectively maintained single-center clinical registry included 10 patients treated between October 2023 and October 2025. Each patient received three monthly ultrasound-guided posteromedial injections using 30 mL of 5% dextrose with 0.1% lidocaine (lignocaine). The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) was recorded at baseline and at 1, 3, 6, and 12 months after the final injection. Data are mean ± SD, median (IQR), and 95% CI. In exploratory inferential analyses, we used Friedman tests and Wilcoxon signed-rank tests with Bonferroni correction. Results: The mean WOMAC total score improved from 59.5 ± 4.33 at baseline to 38.6 ± 4.50 at 1 month, 34.3 ± 4.45 at 3 months, 30.6 ± 3.06 at 6 months, and 28.5 ± 2.51 at 12 months after the final injection, corresponding to a mean 12-month within-patient change of −31.0 points (95% CI −32.58 to −29.42; −52.1%). Mean pain improved from 12.6 ± 1.35 to 5.6 ± 0.70, stiffness from 4.7 ± 0.48 to 2.1 ± 0.32, and physical function from 42.2 ± 2.62 to 20.8 ± 2.15. All 10 patients had lower WOMAC total scores at 12 months than at baseline. Friedman tests were significant for all four WOMAC domains (all p ≤ 5.05 × 10⁻⁷); Wilcoxon signed-rank tests versus baseline reached the theoretical minimum p at n = 10 (Bonferroni-adjusted p = 7.81 × 10⁻³) at every follow-up timepoint. No serious adverse events were documented; mild transient post-procedural soreness occurred in three patients. Conclusions: In this small retrospective pilot cohort, ultrasound-guided posteromedial fascial–periarticular injection was associated with sustained improvement in WOMAC pain, stiffness, physical function, and total scores over 12 months. These findings are preliminary and hypothesis-generating; non-specific effects including placebo, regression to the mean, and natural symptomatic fluctuation cannot be excluded. Prospective controlled trials are required to establish safety, reproducibility, mechanism, and comparative effectiveness. Full article

Aim: This study aimed to develop a population pharmacokinetic (PK) model of intravenous fluconazole and, using model-based simulations, propose initial dosing recommendations that optimize efficacy while limiting toxicity. Methods: Therapeutic drug monitoring data from 116 adult patients (183 serum concentrations) treated with intravenous fluconazole between 2022 and 2025 at a single center were analyzed using nonlinear mixed-effects modeling. Monte Carlo simulations were applied to identify dosing strategies that maximize the probability of achieving the PK/PD efficacy target. Results: Estimated glomerular filtration rate (eGFR) was the strongest predictor of fluconazole clearance, and adjusted body weight (ABW) influenced the volume of distribution. For a patient with ABW of 75 kg and eGFR of 90 mL/min, the estimated volume of distribution and clearance were 41.6 L and 0.81 L/h, respectively. An eGFR-based dosing nomogram was developed, and simulations demonstrated that this approach outperformed standard dosing regimens in achieving the PK/PD target. Conclusions: These findings suggest an initial loading dose (2.8 times the maintenance dose) followed by individualized, eGFR-guided maintenance dosing to enhance the safety and efficacy of intravenous fluconazole therapy; however, prospective clinical validation is required before routine clinical implementation. Full article

Background/Objectives: Deficient mismatch repair (dMMR) and microsatellite instability-high (MSI-H) colorectal cancer (CRC) are highly sensitive to immune checkpoint blockade. We evaluated the efficacy, safety, and clinical maturity of neoadjuvant PD-1-based immunotherapy in localized disease. Methods: This PRISMA-compliant systematic review included prospective studies of neoadjuvant PD-1-based therapy in localized dMMR/MSI-H CRC. Proportions were pooled on the logit scale using inverse-variance random-effects models with the Paule–Mandel estimator. Pathologic complete response (pCR) was the primary outcome; major pathologic response (MPR), immune-related adverse events (irAEs), surgery, clinical complete response (cCR), organ preservation, and long-term outcomes were secondary outcomes. Results: Five prospective studies were included. Four studies, comprising 305 treated patients and 292 pathologically evaluable patients, contributed five treatment arms to the quantitative synthesis. The pooled pCR proportion was 0.65 (95% CI, 0.54–0.74), and the pooled MPR proportion was 0.89 (95% CI, 0.79–0.94). Exploratory subgroup analyses suggested higher response proportions with combination regimens, but clinical and methodological differences confounded these predominantly indirect comparisons. Any-grade irAEs occurred in 0.54 (95% CI, 0.36–0.71), whereas grade ≥3 irAEs occurred in 0.06 (95% CI, 0.04–0.10). The pooled surgery proportion was 0.96 (95% CI, 0.86–0.99), although this outcome largely reflected protocol-mandated surgery. cCR and organ preservation were promising in selected rectal-cancer cohorts. Survival and recurrence data were immature and unsuitable for quantitative pooling. Conclusions: Neoadjuvant PD-1-based immunotherapy is a highly promising investigational strategy for localized dMMR/MSI-H CRC. Nevertheless, predominantly early-phase evidence, indirect comparisons, heterogeneous endpoints, and limited follow-up preclude definitive conclusions regarding routine clinical adoption. Full article