Prenatal Diagnosis and Clinical Outcomes of Isolated Mega Cisterna Magna.

Objective: The study aimed to investigate the clinical outcomes of fetuses diagnosed with isolated mega cisterna magna in utero. Methods: A multicenter retrospective cohort study was conducted across 18 university hospitals from 2010 to 2019. Cases diagnosed with isolated mega cisterna magna, defined as a cisterna magna >10 mm with a normal cerebellar vermis and no cystic dilation of the fourth ventricle, were included. Cases with other central nervous system (CNS) anomalies, extra-central nervous system anomalies, chromosomal abnormalities, or congenital infections were excluded. Maternal demographics, prenatal findings, delivery outcomes, and postnatal outcomes were analyzed. Results: The mean gestational age at initial diagnosis was 28.6 ± 3.9 weeks, and the mean anteroposterior diameter of the cisterna magna was 12.5 ± 3.2 mm. Of the 71 cases initially assessed, 48 (67.6%) showed self-regression in utero. Postnatally, 13 cases (18.3%) had persistent isolated mega cisterna magna, whereas 10 cases (14.1%) were diagnosed with other central nervous system anomalies. Among the persistent isolated mega cisterna magna cases, one child exhibited delayed neurodevelopment. There was a higher incidence of isolated mega cisterna magna in male fetuses, which exhibited a significantly larger mean cisterna magna diameter compared with female fetuses (P = .045). Conclusion: Male fetuses exhibited a higher incidence of isolated mega cisterna magna compared with female fetuses and had larger anteroposterior diameters of the cisterna magna. The study demonstrated favorable neurodevelopmental outcomes associated with isolated mega cisterna magna, with self-regression observed in two-thirds of the cases. However, consecutive prenatal and postnatal evaluations for additional central nervous system or extra-central nervous system malformations need to be performed, considering the differences between prenatal and postnatal diagnoses.

Unveiling Cas12j Trans-Cleavage Activity for CRISPR Diagnostics: Application to miRNA Detection in Lung Cancer Diagnosis.

Cas12j, a hypercompact and efficient Cas protein, has potential for use in CRISPR diagnostics, but has not yet been used because the trans-cleavage activity of Cas12j is veiled. Here, the trans-cleavage behavior of Cas12j1, 2, and 3 variants and evaluate their suitability for nucleic acid detection is unveiled. The target preferences and mismatch specificities of the Cas12j variants are precisely investigated and the optimal Cas12j reaction conditions are determined. As a result, the EXP-J assay for miRNA detection by harnessing the robust trans-cleavage activity of Cas12j on short ssDNA is developed. The EXP-J method demonstrates exceptional detection capabilities for miRNAs, proving that Cas12j can be a pivotal component in molecular diagnostics. Furthermore, the translational potential of the EXP-J assay is validated by detecting oncogenic miRNAs in plasma samples from lung cancer patients. This investigation not only elucidates the trans-cleavage characteristics of Cas12j variants, but also advances the Cas12j-based diagnostic toolkit.

Tumor immunogenicity regulates host immune responses, and conventional dendritic cell type 2 uptakes the majority of tumor antigens in an orthotopic lung cancer model.

Human lung cancer carries high genetic alterations, expressing high tumor-specific neoantigens. Although orthotopic murine lung cancer models recapitulate many characteristics of human lung cancers, genetically engineered mouse models have fewer somatic mutations than human lung cancer, resulting in scarce immune cell infiltration and deficient immune responses. The endogenous mouse lung cancer model driven by Kras mutation and Trp53 deletion (KP model) has minimal immune infiltration because of a scarcity of neoantigens. Fine-tuning tumor antigenicity to trigger the appropriate level of antitumor immunity would be key to investigating immune responses against human lung cancer. We engineered the KP model to express antigens of OVA peptides (minOVA) as neoantigens along with ZsGreen, a traceable fluorescent conjugate. The KP model expressing minOVA exhibited stronger immunogenicity with higher immune cell infiltration comprised of CD8+ T cells and CD11c+ dendritic cells (DCs). Consequently, the KP model expressing minOVA exhibits suppressed tumor growth compared to its origin. We further analyzed tumor-infiltrated DCs. The majority of ZsGreen conjugated with minOVA was observed in the conventional type 2 DCs (cDC2), whereas cDC1 has minimal. These data indicate that tumor immunogenicity regulates host immune responses, and tumor neoantigen is mostly recognized by cDC2 cells, which may play a critical role in initiating antitumor immune responses in an orthotopic murine lung cancer model.

Three-dimensional computed tomography evaluation of the ulnocarpal joint under stress loading.

LEVEL OF EVIDENCE: IV.

Proteomic profiling of cerebrospinal fluid reveals TKT as a potential biomarker for medulloblastoma.

Cerebrospinal fluid (CSF) plays an important role in brain tumors, including medulloblastoma (MBL). Recent advancements in mass spectrometry systems and 'Omics' data analysis methods enable unbiased, high proteome depth research. We conducted proteomic profiling of the total CSF in MBL patients with the purpose of finding a potential diagnostic biomarker for MBL. We quantified 1112 proteins per CSF sample. Feature selection identified four elevated soluble proteins (SPTBN1, HSP90AA1, TKT, and NME1-NME2) in MBL CSF. Validation with ELISA confirmed that TKT was significantly elevated in MBL. Additionally, TKT-positive extracellular vesicles were significantly enriched in MBL CSF and correlated with the burden of leptomeningeal seeding. Our results provide insights into the proteomics data of the total CSF of MBL patients. Furthermore, we identified the significance of TKT within the total CSF and its presence within circulating EVs in the CSF. We suggest that TKT may serve as a biomarker for MBL.

Uncertainty Estimation for Dual View X-ray Mammographic Image Registration Using Deep Ensembles.

Techniques are developed for generating uncertainty estimates for convolutional neural network (CNN)-based methods for registering the locations of lesions between the craniocaudal (CC) and mediolateral oblique (MLO) mammographic X-ray image views. Multi-view lesion correspondence is an important task that clinicians perform for characterizing lesions during routine mammographic exams. Automated registration tools can aid in this task, yet if the tools also provide confidence estimates, they can be of greater value to clinicians, especially in cases involving dense tissue where lesions may be difficult to see. A set of deep ensemble-based techniques, which leverage a negative log-likelihood (NLL)-based cost function, are implemented for estimating uncertainties. The ensemble architectures involve significant modifications to an existing CNN dual-view lesion registration algorithm. Three architectural designs are evaluated, and different ensemble sizes are compared using various performance metrics. The techniques are tested on synthetic X-ray data, real 2D X-ray data, and slices from real 3D X-ray data. The ensembles generate covariance-based uncertainty ellipses that are correlated with registration accuracy, such that the ellipse sizes can give a clinician an indication of confidence in the mapping between the CC and MLO views. The results also show that the ellipse sizes can aid in improving computer-aided detection (CAD) results by matching CC/MLO lesion detects and reducing false alarms from both views, adding to clinical utility. The uncertainty estimation techniques show promise as a means for aiding clinicians in confidently establishing multi-view lesion correspondence, thereby improving diagnostic capability.

AI-Safe-C Score: Assessing Liver-Related Event Risks in Non-Cirrhotic Patients after Successful Direct-Acting Antiviral Treatment.

BACKGROUND & AIMS: Direct-acting antivirals (DAAs) have considerably improved chronic hepatitis C (HCV) treatment; however, post-sustained virological response (SVR) follow-up typically neglects the risk of liver-related events (LREs). This study introduces and validates artificial intelligence-safe score (AI-Safe-C score) to assess the risk of LREs in non-cirrhotic patients after successful DAA treatment. METHODS: The random survival forest model was trained to predict LREs in 913 non-cirrhotic HCV patients after SVR in Korea and was further tested in a combined cohort from Hong Kong and France (N = 1264). The model's performance was assessed using Harrell's C-index and the area under the time-dependent receiver operating characteristic curve (AUROC). RESULTS: The AI-Safe-C score, which incorporated liver stiffness measurement (LSM), age, sex, and six other biochemical tests-with LSM being ranked as the most important among 9 clinical features-demonstrated a C-index of 0.86 (95% confidence interval [CI]: 0.82-0.90) in predicting LREs in an external validation cohort. It achieved 3- and 5-year LRE AUROCs of 0.88 (95%CI, 0.84-0.92) and 0.79 (95%CI, 0.71-0.87), respectively, and for hepatocellular carcinoma, a C-index of 0.87 (95%CI, 0.81-0.92) with 3- and 5-year AUROCs of 0.88 (95%CI, 0.84-0.93) and 0.82 (95%CI, 0.75-0.90), respectively. Using a cut-off of 0.7, the 5-year LRE rate within a high-risk group was between 3.2% and 6.2%, mirroring the incidence observed in individuals with advanced fibrosis, in stark contrast to the significantly lower incidence of 0.2% to 0.6% in a low-risk group. CONCLUSION: AI-Safe-C score is a useful tool for identifying patients without cirrhosis who are at higher risk of developing LREs. The post-SVR LSM, as integrated within the AI-Safe-C score, plays a critical role in predicting future LREs. IMPACT AND IMPLICATIONS: The AI-Safe-C score introduces a paradigm shift in the management of non-cirrhotic patients post-DAA treatment, a cohort traditionally not included in routine surveillance protocols for LREs. By accurately identifying a subgroup at a comparably high risk of LREs, akin to those with advanced fibrosis, this predictive model facilitates a strategic reallocation of surveillance and clinical resources.

Ultrasound-Guided Percutaneous Biopsy With Needle Track Plugging in Patients With Focal Liver Lesions on an Outpatient Basis: A Randomized Controlled Trial.

OBJECTIVE: The increasing utilization of various molecular tests for diagnosing and selecting treatments for patients with malignancies has led to a rising trend in both the frequency of biopsies and the required tissue volume. We aimed to compare the safety of outpatient ultrasound (US)-guided percutaneous liver biopsy (PLB) between the coaxial method with needle track plugging (NTP) and the conventional method. MATERIALS AND METHODS: This single-center, prospective, randomized controlled study was conducted from October 2022 to May 2023. Patients referred for US-guided PLB with target liver lesions measuring ≥1 cm and requiring ≥3 tissue cores were enrolled. Patients with severe coagulopathy or a substantial volume of ascites were excluded. Patients were randomly assigned to undergo PLB using either the coaxial method with NTP or the conventional method, in a 1:1 ratio, and were subsequently discharged after 2 hours. The primary endpoint was the presence of a patent track sign, defined as a linear color flow along the biopsy track on Doppler US, as an indication of bleeding. The secondary endpoints included clinically significant bleeding, delayed bleeding after discharge, and diagnostic yield. The incidences of these endpoints were compared between the two methods. RESULTS: A total of 107 patients completed the study protocol. Patent track signs were observed significantly less frequently in the coaxial method with NTP group than in the conventional method group: 16.7% (9/54) vs. 35.8% (19/53; P = 0.042). Clinically significant bleeding and delayed bleeding did not occur in either group, and both methods achieved a high diagnostic yield: 94.4% (51/54) vs. 98.1% (52/53; P = 0.624). CONCLUSION: Compared with the conventional method, the coaxial method with NTP may potentially be safer, with a reduced risk of overall bleeding complications after PLB when retrieving ≥3 tissue cores. The coaxial method with NTP could be considered a viable option for acquiring multiple liver tissues on an outpatient basis.

Regional disparities in the risk of secondary fractures in patients with hip fractures.

PURPOSE: We aimed to examine the regional disparities in secondary fracture incidence among patients with hip fractures in South Korea. METHODS: This observational, retrospective, cohort study was conducted using data of 6,213 South Korean nationals from the National Health Insurance Service-National Sample Cohort (2004-2019). Secondary fractures included hip, wrist, humerus, spine, ankle, and pelvis fractures that occurred 6 months after hip fracture. The position value for relative composite index was used to identify medically vulnerable regions. Cox proportional hazards models were used for statistical analysis. RESULTS: Among the 6,213 (1,949 male, 4,264 female) patients with hip fracture, 981 lived in medically vulnerable areas and 5,232 in non-vulnerable areas. Patients residing in vulnerable areas had a higher risk of secondary fractures than did those residing in non-vulnerable areas (hazard ratio [HR]: 1.24, 95 % confidence interval [CI]: 1.05-1.47); the factors that increased their risk included female sex (HR: 1.30, 95 % CI: 1.08-1.57), age ≥71 years (HR: 1.23, 95 % CI: 1.01-1.44), and not receiving osteoporosis medication (HR: 1.47, 95 % CI: 1.14-1.89). Ten years after hip fracture surgery, the risk of secondary fracture more than tripled in the vulnerable areas than that in the non-vulnerable areas. CONCLUSION: Patients living in vulnerable regions had a higher risk of secondary fractures than that of those in non-vulnerable regions. Prevention and medication policies should thus be implemented to reduce regional healthcare disparities.

Actinomycetota Amycolatopsis nalaikhensis sp. nov. and Amycolatopsis carbonis sp. nov., two novel actinobacteria with antimicrobial activity isolated from a coal mining site in Mongolia.

Two-novel filamentous actinobacteria designated strains 2-2T and 2-15T were isolated from soil of a coal mining site in Mongolia, and their taxonomic positions were determined using a polyphasic approach. Phylogenetic analyses based on 16S rRNA gene sequences showed that each of the strains formed a distinct clade within the genus Amycolatopsis. The 16S rRNA gene sequence similarity analysis showed that both strains were mostly related to Amycolatopsis rhabdoformis NCIMB 14900T with 99.0 and 99.4% sequence similarity, respectively. The genome-based comparison indicated that strain 2-2T shared the highest digital DNA-DNA hybridization value of 35.6% and average nucleotide identity value of 86.9% with Amycolatopsis pretoriensis DSM 44654T, and strain 2-15T shared the corresponding values of 36.5 and 87.9% with A. rhabdoformis NCIMB 14900T, all of which being well below the thresholds for species delineation. The chemotaxonomic properties of both strains were typical of the genus Amycolatopsis. In silico prediction of chemotaxonomic markers was also carried out, and the results were consistent with the chemotaxonomic profiles of the genus. Genome mining for secondary metabolite production in strains 2-2T and 2-15T revealed the presence of 29 and 24 biosynthetic gene clusters involved in the production of polyketide synthase, non-ribosomal peptide synthetase, ribosomally synthesized and post-translationally modified peptides, lanthipeptide, terpenes, siderophore, and a number of other unknown type compounds. Both strains showed broad antifungal activity against several filamentous fungi and also antibacterial activity against methicillin-resistant Staphylococcus aureus and Acinetobacter baumannii. The phenotypic, biochemical, and chemotaxonomic properties indicated that both strains could be clearly distinguished from other species of Amycolatopsis, and thus the names Amycolatopsis nalaikhensis sp. nov. (type strain, 2-2T=KCTC 29695T=JCM 30462T) and Amycolatopsis carbonis (type strain, 2-15T=KCTC 39525T=JCM 30563T) are proposed accordingly.

Fructose 1,6-bisphosphate aldolase: A promising prognostic marker for oral cancer and its role in radiotherapy response.

Oral cancer remains a significant global health concern and its early detection plays a crucial role in improving patient outcomes. Identifying reliable prognostic markers is essential to guide treatment decisions and enhance survival rates. Fructose 1,6-bisphosphate aldolase (FBA), a glycolytic enzyme, has emerged as a promising candidate for prognostic assessment of oral cancer. This review highlights the role of FBA in tumorigenesis, its potential utility in predicting disease progression and patient survival, and its influence on response to radiotherapy. Recent studies have suggested that dysregulated metabolic pathways involving FBA may contribute to radiation resistance in oral cancer, emphasizing the need for further exploration of FBA-targeted therapeutic strategies. Understanding the role of FBA in oral cancer pathogenesis could pave the way for the development of personalized treatment strategies, including combined radiotherapy.

Gastric Cancer and Intestinal Metaplasia: Differential Metabolic Landscapes and New Pathways to Diagnosis.

Gastric cancer (GC) is the fifth most common cause of cancer-related death worldwide. Early detection is crucial for improving survival rates and treatment outcomes. However, accurate GC-specific biomarkers remain unknown. This study aimed to identify the metabolic differences between intestinal metaplasia (IM) and GC to determine the pathways involved in GC. A metabolic analysis of IM and tissue samples from 37 patients with GC was conducted using ultra-performance liquid chromatography with tandem mass spectrometry. Overall, 665 and 278 significant features were identified in the aqueous and 278 organic phases, respectively, using false discovery rate analysis, which controls the expected proportion of false positives among the significant results. sPLS-DA revealed a clear separation between IM and GC samples. Steroid hormone biosynthesis, tryptophan metabolism, purine metabolism, and arginine and proline metabolism were the most significantly altered pathways. The intensity of 11 metabolites, including N1, N2-diacetylspermine, creatine riboside, and N-formylkynurenine, showed significant elevation in more advanced GC. Based on pathway enrichment analysis and cancer stage-specific alterations, we identified six potential candidates as diagnostic biomarkers: aldosterone, N-formylkynurenine, guanosine triphosphate, arginine, S-adenosylmethioninamine, and creatine riboside. These metabolic differences between IM and GC provide valuable insights into gastric carcinogenesis. Further validation is needed to develop noninvasive diagnostic tools and targeted therapies to improve the outcomes of patients with GC.

Real-world safety and effectiveness of lenvatinib in unresectable hepatocellular carcinoma in Korea: post-marketing study.

Aim: This post-marketing surveillance study evaluated the safety and effectiveness of lenvatinib as first-line treatment for unresectable hepatocellular carcinoma in Korea.Materials & methods: Adverse drug reactions (ADRs) and other safety and effectiveness end points were assessed in patients who initiated lenvatinib according to the approved label in republic of Korea.Results: Among 658 lenvatinib-treated patients, ADRs were reported in 57.8%; ADRs grade ≥3 in 13.5%. The most common grade ≥3 ADRs were asthenia (1.2%) and hepatic encephalopathy (1.2%). Physician-reported tumor responses (n = 511) were complete (1.0%) or partial (12.9%) response and stable (45.2%) or progressive disease (40.9%); objective response rates were higher with longer lenvatinib treatment duration (p < 0.001).Conclusion: Lenvatinib was generally well tolerated and effective in real-world clinical practice in Korea.Clinical trial registration: ClinicalTrials.gov NCT05225207.

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The Impact of Pembrolizumab as a Salvage Therapy Based on HER2 Expression in Advanced Gastric Cancer.

Immune checkpoint inhibitors (ICIs) are used as salvage treatments for advanced gastric cancer (AGC) regardless of HER2 status. This study assessed the efficacy of ICIs based on HER2 expression in AGC patients who received pembrolizumab as salvage monotherapy at Samsung Medical Center from November 2017 to March 2023. HER2 status was determined via immunohistochemistry, and tumor response and survival outcomes were compared accordingly. Among the 113 patients analyzed, with a median age of 61 years and 64.6% being male, 12 patients (10.6%) were HER2-positive, and 101 patients (89.4%) were HER2-negative. Of 92 evaluable patients, none had a complete response. However, 50% of HER2-positive patients had a partial response, compared to 4.9% of HER2-negative patients (p < 0.001). The disease control rate was 70% in HER2-positive and 37.8% in HER2-negative patients (p = 0.086). Median progression-free survival was 5.53 months for HER2-positive patients versus 1.81 months for HER2-negative patients (p = 0.037). Pembrolizumab as a salvage chemotherapy for the treatment of AGC demonstrated superior effectiveness in HER2-positive patients compared with HER2-negative patients.

Suprasellar teratoma to germinoma recurrence: implications for diagnosis and follow-up.

Mature teratoma is a subtype of intracranial germ cell tumors (GCTs), distinguished from malignant GCTs by its benign nature and excellent prognosis. Typically, no adjuvant therapy is recommended following gross total resection (GTR). We report a case of a prepubertal girl with a suprasellar mature teratoma that recurred as a germinoma 6 months post-GTR. A 7-year-old girl presented with headache and polydipsia. Imaging revealed a suprasellar mass. The patient underwent GTR, and pathological diagnosis confirmed a mature teratoma without other GCT components. Six months later, MRI identified a newly developed suprasellar mass adjacent to the optic chiasm. A second surgery confirmed the mass as a germinoma. The patient subsequently underwent adjuvant chemotherapy combined with proton therapy, resulting in complete remission. The diagnosis of mature teratoma must be approached with caution, and thorough follow-up is imperative, particularly in cases involving female patients, prepubertal age, or non-pineal locations.

A machine learning model to predict liver-related outcomes after the functional cure of chronic hepatitis B.

BACKGROUND & AIMS: The risk of hepatocellular carcinoma (HCC) and hepatic decompensation persists after hepatitis B surface antigen (HBsAg) seroclearance. This study aimed to develop and validate a machine learning model to predict the risk of liver-related outcomes (LROs) following HBsAg seroclearance. METHODS: A total of 4,787 consecutive patients who achieved HBsAg seroclearance between 2000 and 2022 were enrolled from 6 centers in South Korea and a territory-wide database in Hong Kong, comprising the training (n=944), internal validation (n=1,102), and external validation (n=2,741) cohorts. Three machine learning-based models were developed and compared in each cohort. The primary outcome was the development of any LRO, including HCC, decompensation, and liver-related death. RESULTS: During a median follow-up of 55.2 (interquartile range=30.1-92.3) months, 123 LROs were confirmed (1.1%/person-year) in the Korean cohort. A model with the best predictive performance in the training cohort was selected as the final model (designated as PLAN-B-CURE), which was constructed using a gradient boosting algorithm and 7 variables (age, sex, diabetes, alcohol consumption, cirrhosis, albumin, and platelet count). Compared to previous HCC prediction models, PLAN-B-CURE showed significantly superior accuracy in the training cohort (c-index: 0.82 vs. 0.63-0.70, all P<0.001; area under the receiver operating characteristic curve: 0.86 vs. 0.62-0.72, all P<0.01; area under the precision-recall curve: 0.53 vs. 0.13-0.29, all P<0.01). PLAN-B-CURE showed a reliable calibration function (Hosmer-Lemeshow test P>0.05) and these results were reproduced in the internal and external validation cohorts. CONCLUSION: This novel machine learning model consisting of 7 variables provides reliable risk prediction of LRO after HBsAg seroclearance that can be used for personalized surveillance.

Orally Deliverable Iron-Ceria Nanotablets for Treatment of Inflammatory Bowel Disease.

Ceria-based nanoparticles are versatile in treating various inflammatory diseases, but their feasibility in clinical translation is undermined by safety concerns and a limited delivery system. Meanwhile, the idiopathic nature of inflammatory bowel disease (IBD) calls for a wider variety of therapeutics via moderation of the intestinal immune system. In this regard, the synthesis and oral formulation of iron-ceria nanoparticles (CF NPs) with enhanced nanozymic activity and lower toxicity risk than conventional ceria-based nanoparticles are reported. CF NPs are clustered in calcium phosphate (CaP) and coated with a pH-responsive polymer to provide the enteric formulation of iron-ceria nanotablets (CFNT). CFNT exhibits a marked alleviative efficacy in the dextran sodium sulfate (DSS)-induced enterocolitis model in vivo by modulating the pro-inflammatory behavior of innate immune cells including macrophages and neutrophils, promoting anti-inflammatory cytokine profiles, and downregulating key transcription factors of inflammatory pathways.

Deep-Transfer-Learning-Based Natural Language Processing of Serial Free-Text Computed Tomography Reports for Predicting Survival of Patients With Pancreatic Cancer.

PURPOSE: To explore the predictive potential of serial computed tomography (CT) radiology reports for pancreatic cancer survival using natural language processing (NLP). METHODS: Deep-transfer-learning-based NLP models were retrospectively trained and tested with serial, free-text CT reports, and survival information of consecutive patients diagnosed with pancreatic cancer in a Korean tertiary hospital was extracted. Randomly selected patients with pancreatic cancer and their serial CT reports from an independent tertiary hospital in the United States were included in the external testing data set. The concordance index (c-index) of predicted survival and actual survival, and area under the receiver operating characteristic curve (AUROC) for predicting 1-year survival were calculated. RESULTS: Between January 2004 and June 2021, 2,677 patients with 12,255 CT reports and 670 patients with 3,058 CT reports were allocated to training and internal testing data sets, respectively. ClinicalBERT (Bidirectional Encoder Representations from Transformers) model trained on the single, first CT reports showed a c-index of 0.653 and AUROC of 0.722 in predicting the overall survival of patients with pancreatic cancer. ClinicalBERT trained on up to 15 consecutive reports from the initial report showed an improved c-index of 0.811 and AUROC of 0.911. On the external testing set with 273 patients with 1,947 CT reports, the AUROC was 0.888, indicating the generalizability of our model. Further analyses showed our model's contextual interpretation beyond specific phrases. CONCLUSION: Deep-transfer-learning-based NLP model of serial CT reports can predict the survival of patients with pancreatic cancer. Clinical decisions can be supported by the developed model, with survival information extracted solely from serial radiology reports.

Longitudinal analysis of cranial growth using comprehensive craniometric measurements after fronto-orbital advancement in coronal craniosynostosis.

OBJECTIVE: The objective of this study was to investigate the longitudinal changes in cranial growth following fronto-orbital advancement (FOA) surgery in patients with unilateral and bilateral coronal craniosynostosis. METHODS: This retrospective review analyzed head circumference (HC) and CT data during preoperative (T0), immediate postoperative (T1), and final follow-up (T2) visits in 40 patients (23 female, 17 male) who underwent FOA using either the open approach or distraction osteogenesis (DO) between 1987 and 2018. The mean follow-up period was 90.62 months. The z-scores of HC, CT-based intracranial volume, anteroposterior diameter (APD), biparietal diameter (BPD), and cranial height (CH) were calculated using sex- and age-specific standards. Logistic regression analysis was performed. RESULTS: While the z-scores of HC, intracranial volume, and BPD remained within the normal range, the z-scores of APD fluctuated between -2 and -1, and the z-scores of CH were > 2, indicating a substantial elevation compared with norms from T0 to T2. Age at surgery significantly influenced the z-scores of HC, BPD, and CH at T2 (all p < 0.05). Delayed surgical timing was correlated with increased BPD and CH z-scores from T1 to T2 (p = 0.007 and 0.019, respectively). The DO for FOA resulted in elevated HC z-scores at T2 and increased APD from T0 to T1, followed by a significant APD relapse from T1 to T2. CONCLUSIONS: These findings suggest that delayed surgical timing may support better cranial growth, as indicated by increased HC at long-term follow-up. However, delayed timing is also associated with worsening abnormally elevated CH. Despite the immediate APD expansion and long-term HC increase with DO, potential relapse warrants caution. While intentional overcorrection of APD is recommended, careful consideration of surgical timing and planning is essential.

Real-Time Tunable Gas Sensing Platform Based on SnO2 Nanoparticles Activated by Blue Micro-Light-Emitting Diodes.

Micro-light-emitting diodes (µLEDs) have gained significant interest as an activation source for gas sensors owing to their advantages, including room temperature operation and low power consumption. However, despite these benefits, challenges still exist such as a limited range of detectable gases and slow response. In this study, we present a blue µLED-integrated light-activated gas sensor array based on SnO2 nanoparticles (NPs) that exhibit excellent sensitivity, tunable selectivity, and rapid detection with micro-watt level power consumption. The optimal power for µLED is observed at the highest gas response, supported by finite-difference time-domain simulation. Additionally, we first report the visible light-activated selective detection of reducing gases using noble metal-decorated SnO2 NPs. The noble metals induce catalytic interaction with reducing gases, clearly distinguishing NH3, H2, and C2H5OH. Real-time gas monitoring based on a fully hardware-implemented light-activated sensing array was demonstrated, opening up new avenues for advancements in light-activated electronic nose technologies.