Dynamics of peripheral blood inflammatory index predict tumor pathological response and survival among patients with locally advanced non-small cell lung cancer who underwent neoadjuvant immunochemotherapy: a multi-cohort retrospective study.

Background: Static tumor features before initiating anti-tumor treatment were insufficient to distinguish responding from non-responding tumors under the selective pressure of immuno-therapy. Herein we investigated the longitudinal dynamics of peripheral blood inflammatory indexes (dPBI) and its value in predicting major pathological response (MPR) in non-small cell lung cancer (NSCLC). Methods: A total of 147 patients with NSCLC who underwent neoadjuvant immunochemotherapy were retrospectively reviewed as training cohort, and 26 NSCLC patients from a phase II trial were included as validation cohort. Peripheral blood inflammatory indexes were collected at baseline and as posttreatment status; their dynamics were calculated as their posttreatment values minus their baseline level. Least absolute shrinkage and selection operator algorithm was utilized to screen out predictors for MPR, and a MPR score was integrated. We constructed a model incorporating this MPR score and clinical predictors for predicting MPR and evaluated its predictive capacity via the area under the curve (AUC) of the receiver operating characteristic and calibration curves. Furthermore, we sought to interpret this MPR score in the context of micro-RNA transcriptomic analysis in plasma exosomes for 12 paired samples (baseline and posttreatment) obtained from the training cohort. Results: Longitudinal dynamics of monocyte-lymphocyte ratio, platelet-to-lymphocyte ratio, platelet-to-albumin ratio, and prognostic nutritional index were screened out as significant indicators for MPR and a MPR score was integrated, which was further identified as an independent predictor of MPR. Then, we constructed a predictive model incorporating MPR score, histology, and differentiated degree, which discriminated MPR and non-MPR patients well in both the training and validation cohorts with an AUC value of 0.803 and 0.817, respectively. Furthermore, micro-RNA transcriptomic analysis revealed the association between our MPR score and immune regulation pathways. A significantly better event-free survival was seen in subpopulations with a high MPR score. Conclusion: Our findings suggested that dPBI reflected responses to neoadjuvant immuno-chemotherapy for NSCLC. The MPR score, a non-invasive biomarker integrating their dynamics, captured the miRNA transcriptomic pattern in the tumor microenvironment and distinguished MPR from non-MPR for neoadjuvant immunochemotherapy, which could support the clinical decisions on the utilization of immune checkpoint inhibitor-based treatments in NSCLC patients.

The Role of Phosphorus on Alkaline Hydrogen Oxidation Electrocatalysis for Ruthenium Phosphides.

Transition metal/p-block compounds are regarded as the most essential materials for electrochemical energy converting systems involving various electrocatalysis. Understanding the role of p-block element on the interaction of key intermediates and interfacial water molecule orientation at the polarized catalyst-electrolyte interface during the electrocatalysis is important for rational designing advanced p-block modified metal electrocatalysts. Herein, taking a sequence of ruthenium phosphides (including Ru2P, RuP and RuP2) as model catalysts, we establish a volcanic-relation between P-proportion and alkaline hydrogen oxidation reaction (HOR) activity. The dominant role of P for regulating hydroxyl binding energy is validated by active sites poisoning experiments, pH-dependent infection-point behavior, in situ surface enhanced absorption spectroscopy, and density functional theory calculations, in which P could tailor the d-band structure of Ru, optimize the hydroxyl adsorption sites across the Ru-P moieties, thereby leading to improved proportion of strongly hydrogen-bonded water and facilitated proton-coupled electron transfer process, which are responsible for the enhanced alkaline HOR performance.

Augmentation of hepatocellular carcinoma malignancy by annexin A5 through modulation of invasion and angiogenesis.

BACKGROUND: Hepatocellular carcinoma (HCC) continues to play a substantial role in cancer-related morbidity and mortality, largely owing to its pronounced tumor heterogeneity and propensity for recurrence. This underscores the pressing need for in-depth examination of its highly malignant mechanisms. Annexin A5 (ANXA5), recognized as a hallmark tumor protein, has emerged as a focal point of interest because of its ambiguous function and mechanism in HCC prognosis. This study aimed to provide a comprehensive understanding of the role of ANXA5 in the malignant progression of human HCC cells by employing an integrative approach that combines conventional experimental methods with RNA sequencing. METHODS: Differences in ANXA5 expression between HCC tissues and corresponding nontumor tissues were evaluated using immunofluorescence (n = 25). Correlation analysis was subsequently performed to assess the association between ANXA5 expression and clinicopathological features (n = 65). The role of ANXA5 in human HCC cell lines with ANXA5 gene knockout and overexpression was explored in vitro using migration and invasion assays and Ki-67 indices and in vivo based on node mice xenograft model. A tube formation assay using human umbilical vein endothelial cells (HUVECs) was conducted to demonstrate the angiogenic effects of ANXA5 in HCC. Single-cell and bulk RNA sequencing was used to further investigate the underlying mechanisms involved. RESULTS: This study revealed that ANXA5 is highly expressed in patients with HCC and correlates with poor prognosis. Assays for migration, invasion, and proliferation based on ANXA5 gene knockout and overexpression systems in human HCC cell lines have demonstrated that ANXA5 enhances HCC malignancy in vitro and in vivo. Tube formation assays of HUVECs indicated that ANXA5 facilitates angiogenesis and recruits endothelial cells to HCC cells. Single-cell and bulk RNA sequencing data analysis further confirmed that ANXA5 expression in HCC is associated with hepatocyte metabolism, immune response activation, and various oncogenic signaling pathways. CONCLUSIONS: This study revealed a meaningful association between elevated ANXA5 expression in tumor tissues and an unfavorable prognosis in patients with HCC. In addition, ANXA5 promotes HCC malignancy by promoting invasion and angiogenesis. Thus, ANXA5 has emerged as a promising therapeutic target for HCC and has the potential to improve patient outcomes.

A frogspawn inspired twin Mo2C/Ni composite with a conductive fibrous network as a robust bifunctional catalyst for advanced anion exchange membrane electrolyzers.

Anion exchange membrane water electrolysis (AEMWE) is considered one of the most cost-effective methods for producing green hydrogen. However, the performance of AEMWE is still restrained by the slow reaction kinetics and poor ion/electron transport of catalysts. Herein, inspired by frogspawn, Mo2C nanoparticles coupled with Ni were in situ embedded into a N-doped porous carbon nanofiber network (Mo2C/NCNTs@Ni) by chemical crosslinking electrospinning combined with carbonization. The unique bionic structure can guarantee favorable overall structural flexibility and fast ion/electron transport kinetics. As a result of the robust hydrogen binding energy of Mo2C, as well as the synergistic impact between Ni and Mo2C nanoparticles and the conductive network resembling frogspawn, the catalyst developed demonstrates excellent performance in both the HER and OER. When employed as a bifunctional catalyst in water electrolysis, Mo2C/NCNTs@Ni delivers overpotentials of 155 mV and 320 mV at 10 mA cm-2 for the HER and OER, respectively. In addition, the Mo2C/NCNTs@Ni also displays excellent long-term durability during a continuous operation test under different currents for 50 h. The assembled AEMWE electrolyzers with Mo2C/NCNTs@Ni as both the anode and cathode can achieve a current density of 82.5 mA cm-2 at 1.99 V, indicating great potential for industrial water splitting. These results give an insight for the development of advanced bifunctional electrocatalysts for the next generation of green and efficient H2 production by water electrolysis.

Deep learning segmentation of the tear fluid reservoir under the sclera lens in optical coherence tomography images.

The tear fluid reservoir (TFR) under the sclera lens is a unique characteristic providing optical neutralization of any aberrations from corneal irregularities. Anterior segment optical coherence tomography (AS-OCT) has become an important imaging modality for sclera lens fitting and visual rehabilitation therapy in both optometry and ophthalmology. Herein, we aimed to investigate whether deep learning can be used to segment the TFR from healthy and keratoconus eyes, with irregular corneal surfaces, in OCT images. Using AS-OCT, a dataset of 31850 images from 52 healthy and 46 keratoconus eyes, during sclera lens wear, was obtained and labeled with our previously developed algorithm of semi-automatic segmentation. A custom-improved U-shape network architecture with a full-range multi-scale feature-enhanced module (FMFE-Unet) was designed and trained. A hybrid loss function was designed to focus training on the TFR, to tackle the class imbalance problem. The experiments on our database showed an IoU, precision, specificity, and recall of 0.9426, 0.9678, 0.9965, and 0.9731, respectively. Furthermore, FMFE-Unet was found to outperform the other two state-of-the-art methods and ablation models, suggesting its strength in segmenting the TFR under the sclera lens depicted on OCT images. The application of deep learning for TFR segmentation in OCT images provides a powerful tool to assess changes in the dynamic tear film under the sclera lens, improving the efficiency and accuracy of lens fitting, and thus supporting the promotion of sclera lenses in clinical practice.

CMS-NET: deep learning algorithm to segment and quantify the ciliary muscle in swept-source optical coherence tomography images.

Background: The ciliary muscle plays a role in changing the shape of the crystalline lens to maintain the clear retinal image during near work. Studying the dynamic changes of the ciliary muscle during accommodation is necessary for understanding the mechanism of presbyopia. Optical coherence tomography (OCT) has been frequently used to image the ciliary muscle and its changes during accommodation in vivo. However, the segmentation process is cumbersome and time-consuming due to the large image data sets and the impact of low imaging quality. Objectives: This study aimed to establish a fully automatic method for segmenting and quantifying the ciliary muscle on the basis of optical coherence tomography (OCT) images. Design: A perspective cross-sectional study. Methods: In this study, 3500 signed images were used to develop a deep learning system. A novel deep learning algorithm was created from the widely used U-net and a full-resolution residual network to realize automatic segmentation and quantification of the ciliary muscle. Finally, the algorithm-predicted results and manual annotation were compared. Results: For segmentation performed by the system, the total mean pixel value difference (PVD) was 1.12, and the Dice coefficient, intersection over union (IoU), and sensitivity values were 93.8%, 88.7%, and 93.9%, respectively. The performance of the system was comparable with that of experienced specialists. The system could also successfully segment ciliary muscle images and quantify ciliary muscle thickness changes during accommodation. Conclusion: We developed an automatic segmentation framework for the ciliary muscle that can be used to analyze the morphological parameters of the ciliary muscle and its dynamic changes during accommodation.

Recent Progress in Silicon-Based Materials for Performance-Enhanced Lithium-Ion Batteries.

Silicon (Si) has been considered to be one of the most promising anode materials for high energy density lithium-ion batteries (LIBs) due to its high theoretical capacity, low discharge platform, abundant raw materials and environmental friendliness. However, the large volume changes, unstable solid electrolyte interphase (SEI) formation during cycling and intrinsic low conductivity of Si hinder its practical applications. Various modification strategies have been widely developed to enhance the lithium storage properties of Si-based anodes, including cycling stability and rate capabilities. In this review, recent modification methods to suppress structural collapse and electric conductivity are summarized in terms of structural design, oxide complexing and Si alloys, etc. Moreover, other performance enhancement factors, such as pre-lithiation, surface engineering and binders are briefly discussed. The mechanisms behind the performance enhancement of various Si-based composites characterized by in/ex situ techniques are also reviewed. Finally, we briefly highlight the existing challenges and future development prospects of Si-based anode materials.

Enhanced anaerobic hydrogen production from cotton straws assisted by copper molybdate.

Hydrogen production from dark fermentation has potential application due to its environmental friendliness, low production cost, and sustainability. However, there is still an obstacle to improving the efficiency of bioH2 production to meet the requirements in practical applications. In this research, copper molybdates are synthesized under different pH conditions as additives to study their different influence processes during anaerobic hydrogen production from cotton straws with the pure cultural system. A series of results indicate that CuMoO4 with appropriate experimental conditions has the highest H2 yield at 191.3 mL/g straws at 37 °C, which is 236% higher than the control group. It can be shown that O. ethanolica 8KG-4 has an obvious accompanying with high stability and low cytotoxicity for this clean energy production system as well as the improvement of metabolic pathway. These results extend new thinking of obtaining higher H2 yield as a biofuel in future production.

Effects of a heavy metal (cadmium) on the responses of subtropical coastal tree species to drought stress.

With global climate change and increased industrialization, drought and heavy metals have become common abiotic stress factors for coastal vegetation. In this study, we investigated the ecophysiological responses of the seedlings of three subtropical coastal tree species (Barringtonia racemosa, Hibiscus tiliaceus, and Terminalia neotaliala) to drought stress (D), cadmium addition (Cd), and their combined effects (Cd + D). The results showed that, for all three plant species, treatment D significantly decreased Amax, Y(II), qP, and ETR; increased the concentrations of PRO, soluble sugars, ABA, MDA, and O2-; and increased the activity of Rubisco. The concentrations of soluble sugars, MDA, and O2- were similar for treatments D and Cd; the only difference was that qP, Amax, and ETR values of B. racemosa and the Amax value of H. tiliaceus were significantly lower in treatment Cd than in control. The concentrations of PRO, soluble sugars, ABA, and MDA were significantly lower for treatment Cd + D than for treatment D. The O2- concentration was positively correlated with the concentrations of soluble sugars and PRO, indicating that osmoregulation was important for the responses of the plants to oxidative stress. ABA was positively correlated with MDA, indicating that ABA was involved in the response to oxidative stress. These results, which show that Cd may weaken the physiological responses of coastal plants to drought stress by increasing ABA accumulation, may provide guidance for coastal ecosystem management in South China.

Network Pharmacology and Transcriptomics Reveal the Mechanism of GuaLouQuMaiWan in Treatment of Type 2 Diabetes and Its Active Small Molecular Compound.

The main pathophysiological abnormalities in type 2 diabetes (T2D) include pancreatic ß-cell dysfunction and insulin resistance. Due to hyperglycemia, patients receive long-term treatment. However, side effects and drug tolerance usually lead to treatment failure. GuaLouQuMaiWan (GLQMW), a common traditional Chinese medicine (TCM) prescription, has positive effects on controlling blood sugar and improving quality of life, but the mechanism is still unclear. To decipher their molecular mechanisms, we used a novel computational systems pharmacology-based approach consisting of bioinformatics analysis, network pharmacology, and drug similarity comparison. We divided the participants into nondisease (ND), impaired glucose tolerance (IGT), and type 2 diabetes groups according to the WHO's recommendations for diabetes. By analyzing the gene expression profile of the ND-IGT-T2D (ND to IGT to T2D) process, we found that the function of downregulated genes in the whole process was mainly related to insulin secretion, while the upregulated genes were related to inflammation. Furthermore, other genes in the ND-IGT (ND to IGT) process are mainly related to inflammation and lipid metabolic disorders. We speculate that 17 genes with a consistent trend may play a key role in the process of ND-IGT-T2D. We further performed target prediction for 50 compounds in GLQMW that met the screening criteria and intersected the differentially expressed genes of the T2D process with the compounds of GLQMW; a total of 18 proteins proved potential targets for GLQMW. Among these, RBP4 is considerably related to insulin resistance. GO/KEGG enrichment analyses of the target genes of GLQMW showed enrichment in inflammation- and T2D therapy-related pathways. Based on the RDKit tool and the DrugBank database, we speculate that (-)-taxifolin, dialoside A_qt, spinasterol, isofucosterol, and 11,14-eicosadienoic acid can be used as potential drugs for T2D via molecular docking and drug similarity comparison.

Innovative Materials for Energy Storage and Conversion.

The metal chalcogenides (MCs) for sodium-ion batteries (SIBs) have gained increasing attention owing to their low cost and high theoretical capacity. However, the poor electrochemical stability and slow kinetic behaviors hinder its practical application as anodes for SIBs. Hence, various strategies have been used to solve the above problems, such as dimensions reduction, composition formation, doping functionalization, morphology control, coating encapsulation, electrolyte modification, etc. In this work, the recent progress of MCs as electrodes for SIBs has been comprehensively reviewed. Moreover, the summarization of metal chalcogenides contains the synthesis methods, modification strategies and corresponding basic reaction mechanisms of MCs with layered and non-layered structures. Finally, the challenges, potential solutions and future prospects of metal chalcogenides as SIBs anode materials are also proposed.

Compact Integration of Hydrogen-Resistant a-InGaZnO and Poly-Si Thin-Film Transistors.

The low-temperature poly-Si oxide (LTPO) backplane is realized by monolithically integrating low-temperature poly-Si (LTPS) and amorphous oxide semiconductor (AOS) thin-film transistors (TFTs) in the same display backplane. The LTPO-enabled dynamic refreshing rate can significantly reduce the display's power consumption. However, the essential hydrogenation of LTPS would seriously deteriorate AOS TFTs by increasing the population of channel defects and carriers. Hydrogen (H) diffusion barriers were comparatively investigated to reduce the H content in amorphous indium-gallium-zinc oxide (a-IGZO). Moreover, the intrinsic H-resistance of a-IGZO was impressively enhanced by plasma treatments, such as fluorine and nitrous oxide. Enabled by the suppressed H conflict, a novel AOS/LTPS integration structure was tested by directly stacking the H-resistant a-IGZO on poly-Si TFT, dubbed metal-oxide-on-Si (MOOS). The noticeably shrunken layout footprint could support much higher resolution and pixel density for next-generation displays, especially AR and VR displays. Compared to the conventional LTPO circuits, the more compact MOOS circuits exhibited similar characteristics.

Inorganic Nitrogen Enhances the Drought Tolerance of Evergreen Broad-Leaved Tree Species in the Short-Term, but May Aggravate Their Water Shortage in the Mid-Term.

With global climate change, atmospheric nitrogen (N) deposition and drought have been well documented to cause substantial challenges for tropical and subtropical evergreen broad-leaved forests. Here, we conducted an experiment that measured the physiological responses of the seedlings of three dominant tree species (Tabebuia chrysantha, Elaeocarpus sylvestris, and Bischofia javanica) of the evergreen broad-leaved forests in South China under control (CT), drought stress (D), N addition (N), and drought stress plus N addition (N+D). We found that N addition significantly decreased malondialdehyde (MDA) content, abscisic acid (ABA) content, total antioxidant capacity (T-AOC), but significantly increased the content of proline (PRO), and the activities of ribulose-1, 5-bisphosphate carboxylase/oxygenase (Rubisco), nitrate reductase (NR), nitrite reductase (NiR), and glutamine synthetase (GS) in the three species under D. Meanwhile, we also found that under drought conditions, N addition promoted the leaf transpiration rate (E), stomatal conductance (g s ), and light-saturated net photosynthetic rate (A max ) of the three species. These results indicate that N addition can enhance the drought tolerance of the three species by osmotic adjustment and protecting the photosystem. However, the enhancement in A max and E will cause plants to face more severe drought conditions, especially B. javanica (large tree species). This study helps to explain why the evergreen broad-leaved forests in South China are gradually degrading to shrublands in recent decades.

Enzyme Activity of Natural Products on Cytochrome P450.

Drug-metabolizing enzymes, particularly the cytochrome P450 (CYP450) monooxygenases, play a pivotal role in pharmacokinetics. CYP450 enzymes can be affected by various xenobiotic substrates, which will eventually be responsible for most metabolism-based herb-herb or herb-drug interactions, usually involving competition with another drug for the same enzyme binding site. Compounds from herbal or natural products are involved in many scenarios in the context of such interactions. These interactions are decisive both in drug discovery regarding the synergistic effects, and drug application regarding unwanted side effects. Herein, this review was conducted as a comprehensive compilation of the effects of herbal ingredients on CYP450 enzymes. Nearly 500 publications reporting botanicals' effects on CYP450s were collected and analyzed. The countries focusing on this topic were summarized, the identified herbal ingredients affecting enzyme activity of CYP450s, as well as methods identifying the inhibitory/inducing effects were reviewed. Inhibitory effects of botanicals on CYP450 enzymes may contribute to synergistic effects, such as herbal formulae/prescriptions, or lead to therapeutic failure, or even increase concentrations of conventional medicines causing serious adverse events. Conducting this review may help in metabolism-based drug combination discovery, and in the evaluation of the safety profile of natural products used therapeutically.

The Location Consistency Index Helps to Distinguish Eyes With Subclinical Keratoconus From Normal Eyes.

PURPOSE: To develop a novel index that combines the locations and magnitudes of corneal alterations to improve discrimination of eyes with subclinical keratoconus from normal eyes. METHODS: A Scheimpflug-based tomography system was used to image 252 eyes (normal: 78 eyes, subclinical keratoconus: 71 eyes, and keratoconus: 103 eyes) of 252 patients from two clinical centers. Coordinates and magnitudes of the maximum corneal protrusion alterations were extracted from curvature, elevation, and pachymetry maps. A location consistency index (LCI) was calculated from the Euclidean distances among these locations. A logistic regression model, named the location consistency enhanced score (LCES), which combined the LCI and the magnitudes of these maximum alterations, was trained and tested in two different datasets. RESULTS: The LCI in eyes with subclinical keratoconus was 7.8 ± 2.6 µm, which was significantly different from that in normal eyes (11.8 ± 3.9 µm) and eyes with keratoconus (5.8 ± 2.4 µm) (all P < .001). The LCI could differentiate eyes with subclinical keratoconus from normal eyes with a sensitivity of 67.6%, specificity of 83.3%, and area under the receiver operating characteristic curve (AUC) of 0.81. Combining the magnitudes of these maximum alterations with the LCI for the LCES yielded a sensitivity of 90.0% and a specificity of 74.4% for differentiating eyes with subclinical keratoconus from normal eyes (AUC: 0.91). CONCLUSIONS: The LCI can assist in differentiating eyes with subclinical keratoconus from normal eyes. The LCES is a potential new index to assist in a confirmatory test of eyes with subclinical keratoconus. [J Refract Surg. 2022;38(1):35-42.].

A novel diagnostic model for predicting immune microenvironment subclass based on costimulatory molecules in lung squamous carcinoma.

There is still no ideal predictive biomarker for immunotherapy response among patients with non-small cell lung cancer. Costimulatory molecules play a role in anti-tumor immune response. Hence, they can be a potential biomarker for immunotherapy response. The current study comprehensively investigated the expression of costimulatory molecules in lung squamous carcinoma (LUSC) and identified diagnostic biomarkers for immunotherapy response. The costimulatory molecule gene expression profiles of 627 patients were obtained from the The Cancer Genome Atlas, GSE73403, and GSE37745 datasets. Patients were divided into different clusters using the k-means clustering method and were further classified into two discrepant tumor microenvironment (TIME) subclasses (hot and cold tumors) according to the immune score of the ESTIMATE algorithm. A high proportion of activated immune cells, including activated memory CD4 T cells, CD8 T cells, and M1 macrophages. Five CMGs (FAS, TNFRSF14, TNFRSF17, TNFRSF1B, and TNFSF13B) were considered as diagnostic markers using the Least Absolute Shrinkage and Selection Operator and the Support Vector Machine-Recursive Feature Elimination machine learning algorithms. Based on the five CMGs, a diagnostic nomogram for predicting individual tumor immune microenvironment subclasses in the TCGA dataset was developed, and its predictive performance was validated using GSE73403 and GSE37745 datasets. The predictive accuracy of the diagnostic nomogram was satisfactory in all three datasets. Therefore, it can be used to identify patients who may benefit more from immunotherapy.

The Regulatory Role of GBF1 on Osteoclast Activation Through EIF2a Mediated ER Stress and Novel Marker FAM129A Induction.

Bone-resorbing activities of osteoclasts (OCs) are highly dependent on actin cytoskeleton remodeling, plasma membrane reorganization, and vesicle trafficking pathways, which are partially regulated by ARF-GTPases. In the present study, the functional roles of Golgi brefeldin A resistance factor 1 (GBF1) are proposed. GBF1 is responsible for the activation of the ARFs family and vesicular transport at the endoplasmic reticulum-Golgi interface in different stages of OCs differentiation. In the early stage, GBF1 deficiency impaired OCs differentiation and was accompanied with OCs swelling and reduced formation of mature OCs, indicating that GBF1 participates in osteoclastogenesis. Using siRNA and the specific inhibitor GCA for GBF1 knockdown upregulated endoplasmic reticulum stress-associated signaling molecules, including BiP, p-PERK, p-EIF2α, and FAM129A, and promoted autophagic Beclin1, Atg7, p62, and LC3 axis, leading to apoptosis of OCs. The present data suggest that, by blocking COPI-mediated vesicular trafficking, GBF1 inhibition caused intense stress to the endoplasmic reticulum and excessive autophagy, eventually resulting in the apoptosis of mature OCs and impaired bone resorption function.

Automated delineation of corneal layers on OCT images using a boundary-guided CNN.

Accurate segmentation of corneal layers depicted on optical coherence tomography (OCT) images is very helpful for quantitatively assessing and diagnosing corneal diseases (e.g., keratoconus and dry eye). In this study, we presented a novel boundary-guided convolutional neural network (CNN) architecture (BG-CNN) to simultaneously extract different corneal layers and delineate their boundaries. The developed BG-CNN architecture used three convolutional blocks to construct two network modules on the basis of the classical U-Net network. We trained and validated the network on a dataset consisting of 1,712 OCT images acquired on 121 subjects using a 10-fold cross-validation method. Our experiments showed an average dice similarity coefficient (DSC) of 0.9691, an intersection over union (IOU) of 0.9411, and a Hausdorff distance (HD) of 7.4423 pixels. Compared with several other classical networks, namely U-Net, Attention U-Net, Asymmetric U-Net, BiO-Net, CE-Net, CPFnte, M-Net, and Deeplabv3, on the same dataset, the developed network demonstrated a promising performance, suggesting its unique strength in segmenting corneal layers depicted on OCT images.

In vivo non-contact measurement of human iris elasticity by optical coherence elastography.

Quantifying the mechanical properties of the iris can offer valuable insights into the pathophysiology of primary angle closure glaucoma. However, current techniques for iris elastography remain ex vivo with limited clinical applications. This article describes a proposition for a non-contact and non-invasive air-puff optical coherence elastography (OCE) system that can evaluate iris elasticity in vivo. Ten eyes recruited from seven subjects underwent OCE imaging acquisition under three different illumination conditions. The Young's modulus of each eye was detected and shown to be inversely proportional to the iris length, indicating a relationship between mechanical properties and morphology of the iris. With its noninvasive and high-resolution features, this air-puff system shows great potential for applications in clinical ophthalmology.

Implementation of a Skull-Conformal Phased Array for Transcranial Focused Ultrasound Therapy.

OBJECTIVE: To implement a skull-conformal phased array for ultrasound-guided transcranial focused ultrasound therapy with improved patient comfort. METHODS: Using patient-specific computed tomography and MRI neuroimaging data, tightly-conforming helmet scaffolds were designed computationally. The helmet scaffolds were designed to hold reusable transducer modules at near-normal incidence in an optimal configuration for the treatment location(s) of interest. Numerical simulations of trans-skull ultrasound propagation were performed to evaluate different conformal array designs and to compare with hemispherical arrays similar to those employed clinically. A 4096-element phased array was constructed by 3D printing a helmet scaffold optimised for an ex vivo human skullcap, and its performance was evaluated via benchtop and in vivo experiments. RESULTS: Acoustic field measurements confirmed the system's ability to focus through human skull bone using simulation-based transcranial aberration corrections. Preliminary in vivo testing demonstrated safe trans-human skull blood-brain barrier (BBB) opening in rodents. CONCLUSION: Patient-specific conformal ultrasound phased arrays appear to be a feasible and safe approach for conducting transcranial BBB opening procedures. SIGNIFICANCE: Skull-conformal phased arrays stand to improve patient comfort and have the potential to accelerate the adoption of transcranial FUS therapy by improving access to the technology.