AbDPP: Target-oriented antibody design with pretraining and prior biological structure knowledge.

Antibodies represent a crucial class of complex protein therapeutics and are essential in the treatment of a wide range of human diseases. Traditional antibody discovery methods, such as hybridoma and phage display technologies, suffer from limitations including inefficiency and a restricted exploration of the immense space of potential antibodies. To overcome these limitations, we propose a novel method for generating antibody sequences using deep learning algorithms called AbDPP (target-oriented antibody design with pretraining and prior biological knowledge). AbDPP integrates a pretrained model for antibodies with biological region information, enabling the effective use of vast antibody sequence data and intricate biological system understanding to generate sequences. To target specific antigens, AbDPP incorporates an antibody property evaluation model, which is further optimized based on evaluation results to generate more focused sequences. The efficacy of AbDPP was assessed through multiple experiments, evaluating its ability to generate amino acids, improve neutralization and binding, maintain sequence consistency, and improve sequence diversity. Results demonstrated that AbDPP outperformed other methods in terms of the performance and quality of generated sequences, showcasing its potential to enhance antibody design and screening efficiency. In summary, this study contributes to the field by offering an innovative deep learning-based method for antibody generation, addressing some limitations of traditional approaches, and underscoring the importance of integrating a specific antibody pretrained model and the biological properties of antibodies in generating novel sequences. The code and documentation underlying this article are freely available at https://github.com/zlfyj/AbDPP.

Evaluating the Persistence of Large Choroidal Hypertransmission Defects using SS-OCT Imaging.

In age-related macular degeneration (AMD), large choroidal hypertransmission defects (hyperTDs) are identified on en face optical coherence tomography (OCT) images as bright lesions measuring at least 250 µm in greatest linear dimension (GLD). These choroidal hyperTDs arise from focal attenuation or loss of the retinal pigment epithelium (RPE). We previously reported that once large hyperTDs formed, they were likely to persist compared with smaller lesions that were more likely to be transient. Due to their relative persistence, these large persistent choroidal hyperTDs are a point-of-no-return in the progression of intermediate AMD to the late stage of atrophic AMD. Moreover, the onset of these large choroidal hyperTDs can serve as a clinical trial endpoint when studying therapies that might slow disease progression from intermediate AMD to late atrophic AMD. To confirm the persistence of these large choroidal hyperTDs, we studied an independent dataset of AMD eyes enrolled in an ongoing prospective swept-source OCT (SS-OCT) natural history study to determine their overall persistence. We identified a total of 202 eyes with large choroidal hyperTDs containing 1725 hyperTDs followed for an average of 46.6 months. Of the 1725 large hyperTDs, we found that 1718 (99.6%) persisted while only 7 hyperTDs (0.4%) were non-persistent. Of the 7 non-persistent large hyperTDs in 6 eyes, their average GLD at baseline was 385 µm. Of the large hyperTDs ranging in size between 250-300 µm when first detected, only one was not persistent with a baseline GLD of 283 µm. In 6 of the non-persistent hyperTDs, the loss of a detectable large hyperTD was due to the accumulation of hyperreflective material along the retinal pigment epithelium (RPE) and in the retina over the area where the hyperTD was located. This hyperreflective material is thought to represent the migration and aggregation of RPE cells into this focal region where the choroidal hyperTD arose due to attenuated or lost RPE.

Correction: Flow and clogging of capillary droplets.

Correction for 'Flow and clogging of capillary droplets' by Yuxuan Cheng et al., Soft Matter, 2024, https://doi.org/10.1039/D4SM00752B.

Flow and clogging of capillary droplets.

Capillary droplets form due to surface tension when two immiscible fluids are mixed. We describe the motion of gravity-driven capillary droplets flowing through narrow constrictions and obstacle arrays in both simulations and experiments. Our new capillary deformable particle model recapitulates the shape and velocity of single oil droplets in water as they pass through narrow constrictions in microfluidic chambers. Using this experimentally validated model, we simulate the flow and clogging of single capillary droplets in narrow channels and obstacle arrays and find several important results. First, the capillary droplet speed profile is nonmonotonic as the droplet exits the narrow orifice, and we can tune the droplet properties so that the speed overshoots the terminal speed far from the constriction. Second, in obstacle arrays, we find that extremely deformable droplets can wrap around obstacles, which leads to decreased average droplet speed in the continuous flow regime and increased probability for clogging in the regime where permanent clogs form. Third, the wrapping mechanism causes the clogging probability in obstacle arrays to become nonmonotonic with surface tension Γ. At large Γ, the droplets are nearly rigid and the clogging probability is large since the droplets can not squeeze through the gaps between obstacles. With decreasing Γ, the clogging probability decreases as the droplets become more deformable. However, in the small-Γ limit, the clogging probability increases since the droplets are extremely deformable and wrap around the obstacles. The results from these studies are important for developing a predictive understanding of capillary droplet flows through complex and confined geometries.

Correlation between lipoprotein(a) and recurrent ischemic events post-cerebral vascular stent implantation.

BACKGROUND AND AIM: The association of Lipoprotein(a) (Lp[a]) with recurrent ischemic events in stented patients remains uncertain. So, this research aimed to investigate the impact of elevated Lp(a) levels on the occurrence of ischemic events in this specific patient population. METHODS: Totally 553 patients who underwent intracranial or extracranial artery stent implantation were included. Baseline data were collected and postoperative ischemic outcomes were followed up. Cox regression analysis was used to investigate the association between Lp(a) and outcomes, while accounting for confounding factors. Finally, we established prediction models based on nomogram. RESULTS: Of total 553 patients, a number of 107 (19.3%) experienced outcomes. These included 46 cases (25.4%) in group with elevated Lp(a) levels (>30 mg/dL) and 61 cases (16.4%) in non-elevated group (χ2=6.343, p=0.012). The group with elevated Lp(a) was 1.811 times more likely to experience ischemic events than the non-elevated group, each 1 mg/dL increase in Lp(a) resulted in a 1.008-fold increase in the recurrence rate of ischemic events. In addition, sex (male), previous history of coronary heart disease, decreased albumin, elevated very low density lipoprotein cholesterol and poorly controlled risk factors (including blood pressure and blood sugar) were also associated with a high risk of recurrent ischemic events after stent implantation. CONCLUSION: Lp(a) elevation was a significant risk factor for ischemic events in symptomatic patients who underwent intracranial or extracranial artery stenting.

Longitudinal quantification of choriocapillaris flow deficits in persistent placoid maculopathy: a case report.

BACKGROUND: Persistent placoid maculopathy (PPM) is a rare idiopathic chorioretinopathy characterized by choriocapillaris (CC) hypoperfusion. In a case of PPM, we quantified CC flow deficits (FDs) over time and observed an increase in CC perfusion as the visual acuity and outer photoreceptor anatomy improved. CASE PRESENTATION: A 58-year-old man was diagnosed with PPM in both eyes based on the patient's clinical presentation and imaging. He presented with sudden-onset central scotomas in both eyes for about two months. On referral, the best corrected visual acuity (BCVA) was 20/20 in the right eye and 20/100 in the left eye. Plaque-like yellowish macular lesions were observed bilaterally and autofluorescence imaging showed bilateral hyperautofluorescent lesions. Fluorescein angiography (FA) revealed early-phase hyper-fluorescent staining that intensified in the late phases, while indocyanine green angiography (ICGA) displayed persistent hypofluorescence in both eyes. Foveal centered swept source optical coherence tomography (SS-OCT) B-scans showed bilateral focal deposits on the level of retinal pigment epithelium (RPE) and disruption of outer photoreceptor bands. The CC FDs were quantified on SS-OCT angiography (SS-OCTA) images using a previously published algorithm that was validated. The CC FD% was 12.52% in the right eye and 14.64% in the left eye within a 5 mm circle centered on the fovea. After 5 months of steroid treatment, BCVA remained 20/20 in the right eye and improved to 20/25 in the left eye. On OCT imaging, the outer photoreceptor bands fully recovered in both eyes, while some focal deposits remained along the RPE in the left eye. The CC perfusion in both eyes improved, with CC FD% decreasing from 12.52% to 9.16% in the right eye and from 14.64% to 9.34% in the left eye. CONCLUSIONS: Significant impairment of macular CC perfusion was detected after the onset of PPM. Improvement in central macular CC perfusion corresponded with improvements in BCVA and outer retinal anatomy. Our findings suggest that imaging and quantification of CC FDs could serve as a valuable imaging strategy for diagnosing PPM and for following disease progression.

Identification of a ferroptosis-related gene pair biomarker with immune infiltration landscapes in ischemic stroke: a bioinformatics-based comprehensive study.

BACKGROUND: Ischemic stroke (IS) is a principal contributor to long-term disability in adults. A new cell death mediated by iron is ferroptosis, characterized by lethal aggregation of lipid peroxidation. However, a paucity of ferroptosis-related biomarkers early identify IS until now. This study investigated potential ferroptosis-related gene pair biomarkers in IS and explored their roles in immune infiltration. RESULTS: In total, we identified 6 differentially expressed ferroptosis-related genes (DEFRGs) in the metadata cohort. Of these genes, 4 DEFRGs were incorporated into the competitive endogenous RNA (ceRNA) network, including 78 lncRNA-miRNA and 16 miRNA-mRNA interactions. Based on relative expression values of DEFRGs, we constructed gene pairs. An integrated scheme consisting of machine learning algorithms, ceRNA network, and gene pair was proposed to screen the key DEFRG biomarkers. The receiver operating characteristic (ROC) curve witnessed that the diagnostic performance of DEFRG pair CDKN1A/JUN was superior to that of single gene. Moreover, the CIBERSORT algorithm exhibited immune infiltration landscapes: plasma cells, resting NK cells, and resting mast cells infiltrated less in IS samples than controls. Spearman correlation analysis confirmed a significant correlation between plasma cells and CDKN1A/JUN (CDKN1A: r = - 0.503, P < 0.001, JUN: r = - 0.330, P = 0.025). CONCLUSIONS: Our findings suggested that CDKN1A/JUN could be a robust and promising gene-pair diagnostic biomarker for IS, regulating ferroptosis during IS progression via C9orf106/C9orf139-miR-22-3p-CDKN1A and GAS5-miR-139-5p/miR-429-JUN axes. Meanwhile, plasma cells might exert a vital interplay in IS immune microenvironment, providing an innovative insight for IS therapeutic target.

Hopper flows of deformable particles.

Numerous experimental and computational studies show that continuous hopper flows of granular materials obey the Beverloo equation that relates the volume flow rate Q and the orifice width w: Q ∼ (w/σavg - k)ß, where σavg is the average particle diameter, kσavg is an offset where Q ∼ 0, the power-law scaling exponent ß = d - 1/2, and d is the spatial dimension. Recent studies of hopper flows of deformable particles in different background fluids suggest that the particle stiffness and dissipation mechanism can also strongly affect the power-law scaling exponent ß. We carry out computational studies of hopper flows of deformable particles with both kinetic friction and background fluid dissipation in two and three dimensions. We show that the exponent ß varies continuously with the ratio of the viscous drag to the kinetic friction coefficient, λ = ζ/µ. ß = d - 1/2 in the λ → 0 limit and d - 3/2 in the λ → ∞ limit, with a midpoint λc that depends on the hopper opening angle θw. We also characterize the spatial structure of the flows and associate changes in spatial structure of the hopper flows to changes in the exponent ß. The offset k increases with particle stiffness until k ∼ kmax in the hard-particle limit, where kmax ∼ 3.5 is larger for λ → ∞ compared to that for λ → 0. Finally, we show that the simulations of hopper flows of deformable particles in the λ → ∞ limit recapitulate the experimental results for quasi-2D hopper flows of oil droplets in water.

OCT-Based Angiography and Surface Topography in Burn-Damaged Skin.

BACKGROUND AND OBJECTIVES: There is a clinical need for an accurate, non-invasive imaging tool that can provide the objective assessment of burn wounds. The aims of this study are to demonstrate the potential of optical coherence tomography (OCT) in evaluating burn wound healing, as well as exploring the physiological basis of human wound healing. STUDY DESIGN/MATERIALS AND METHODS: This was a retrospective study. Seven patients with severe burn wounds who were admitted to Harborview Medical Center were imaged using an in-house-built, clinical-prototype OCT system. OCT imaging was carried out at multiple scan sites on the burned skin across two time points (imaging session #1 and #2) with a field of view of ~9 × 9 mm. Due to pathological differences among burn zones, scan sites were classified into red sites (zone of hyperemia), white sites (zone of coagulation), and mixed sites. In addition to obtaining qualitative en face vascular and surface topography maps, we quantified vascular area density and surface roughness for comparative purposes. RESULTS: En face vascular and surface topography maps demonstrated numerous morphological changes over both imaging sessions associated with burn injury, such as altered blood flow and loss of regular texture. Quantitative analyses revealed that during imaging session #1, vascular area density was significantly increased within the red sites compared with that of a healthy control (P = 0.0130), while vascular area density was significantly decreased within the white sites compared with that of a healthy control (P < 0.0001). During imaging session #2, vascular area density was significantly reduced to a more normal range within the red sites compared with imaging session #1 (P = 0.0215); however, vascular area density was still significantly lower within the white sites compared with that of a healthy control (P < 0.0001). Furthermore, vascular area density and surface roughness were significantly increased within the white sites during imaging session #2 compared with imaging session #1 (both P < 0.0001). CONCLUSIONS: OCT is clinically feasible to monitor vascular changes and alterations in skin surface roughness during the process of burn wound healing. Variations in vascular area density and roughness measurements within the burn wounds revealed by OCT offer some key insights into the underlying pathophysiological mechanisms responsible for wound healing, which may become critical biological indicators in future clinical evaluation and monitoring of wound healing. Lasers Surg. Med. © 2020 Wiley Periodicals LLC.

Application of OCT-Derived Attenuation Coefficient in Acute Burn-Damaged Skin.

BACKGROUND AND OBJECTIVES: There remains a need to objectively monitor burn wound healing within a clinical setting, and optical coherence tomography (OCT) is proving itself one of the ideal modalities for just such a use. The aim of this study is to utilize the noninvasive and multipurpose capabilities of OCT, along with its cellular-level resolution, to demonstrate the application of optical attenuation coefficient (OAC), as derived from OCT data, to facilitate the automatic digital segmentation of the epidermis from scan images and to work as an objective indicator for burn wound healing assessment. STUDY DESIGN/MATERIALS AND METHODS: A simple, yet efficient, method was used to estimate OAC from OCT images taken over multiple time points following acute burn injury. This method enhanced dermal-epidermal junction (DEJ) contrast, which facilitated the automatic segmentation of the epidermis for subsequent thickness measurements. In addition, we also measured and compared the average OAC of the dermis within said burns for correlative purposes. RESULTS: Compared with unaltered OCT maps, enhanced DEJ contrast was shown in OAC maps, both from single A-lines and completed B-frames. En face epidermal thickness and dermal OAC maps both demonstrated significant changes between imaging sessions following burn injury, such as a loss of epidermal texture and decreased OAC. Quantitative analysis also showed that OAC of acute burned skin decreased below that of healthy skin following injury. CONCLUSIONS: Our study has demonstrated that the OAC estimated from OCT data can be used to enhance imaging contrast to facilitate the automatic segmentation of the epidermal layer, as well as help elucidate our understanding of the pathological changes that occur in human skin when exposed to acute burn injury, which could serve as an objective indicator of skin injury and healing.

The prediction of asymptomatic carotid atherosclerosis with electronic health records: a comparative study of six machine learning models.

BACKGROUND: Screening carotid B-mode ultrasonography is a frequently used method to detect subjects with carotid atherosclerosis (CAS). Due to the asymptomatic progression of most CAS patients, early identification is challenging for clinicians, and it may trigger ischemic stroke. Recently, machine learning has shown a strong ability to classify data and a potential for prediction in the medical field. The combined use of machine learning and the electronic health records of patients could provide clinicians with a more convenient and precise method to identify asymptomatic CAS. METHODS: Retrospective cohort study using routine clinical data of medical check-up subjects from April 19, 2010 to November 15, 2019. Six machine learning models (logistic regression [LR], random forest [RF], decision tree [DT], eXtreme Gradient Boosting [XGB], Gaussian Naïve Bayes [GNB], and K-Nearest Neighbour [KNN]) were used to predict asymptomatic CAS and compared their predictability in terms of the area under the receiver operating characteristic curve (AUCROC), accuracy (ACC), and F1 score (F1). RESULTS: Of the 18,441 subjects, 6553 were diagnosed with asymptomatic CAS. Compared to DT (AUCROC 0.628, ACC 65.4%, and F1 52.5%), the other five models improved prediction: KNN + 7.6% (0.704, 68.8%, and 50.9%, respectively), GNB + 12.5% (0.753, 67.0%, and 46.8%, respectively), XGB + 16.0% (0.788, 73.4%, and 55.7%, respectively), RF + 16.6% (0.794, 74.5%, and 56.8%, respectively) and LR + 18.1% (0.809, 74.7%, and 59.9%, respectively). The highest achieving model, LR predicted 1045/1966 cases (sensitivity 53.2%) and 3088/3566 non-cases (specificity 86.6%). A tenfold cross-validation scheme further verified the predictive ability of the LR. CONCLUSIONS: Among machine learning models, LR showed optimal performance in predicting asymptomatic CAS. Our findings set the stage for an early automatic alarming system, allowing a more precise allocation of CAS prevention measures to individuals probably to benefit most.

Hybrid averaging offers high-flow contrast by cost apportionment among imaging time, axial, and lateral resolution in optical coherence tomography angiography.

The current temporal, wavelength, angular, and spatial averaging approaches trade imaging time and resolution for multiple independent measurements that improve the flow contrast in optical coherence tomography angiography (OCTA). We find that these averaging approaches are equivalent in principle, offering almost the same flow contrast enhancement as the number of averages increases. Based on this finding, we propose a hybrid averaging strategy for contrast enhancement by cost apportionment. We demonstrate that, compared with any individual approach, the hybrid averaging is able to offer a desired flow contrast without severe degradation of imaging time and resolution. Making use of the extended range of a VCSEL-based swept-source OCT, an angular averaging approach by path length encoding is also demonstrated for flow contrast enhancement.

Single-shot angular compounded optical coherence tomography angiography by splitting full-space B-scan modulation spectrum for flow contrast enhancement.

We proposed a single-shot spatial angular compounded optical coherence tomography angiography (AC-Angio-OCT) for blood flow contrast enhancement. By encoding incident angles in B-scan modulation frequencies and splitting the modulation spectrum in the spatial frequency domain, angle-resolved independent subangiograms were obtained and compounded to improve the flow contrast. A full space of the spatial frequency domain allows a wide modulation spectrum. To get access to the full space of the spatial frequency domain and avoid the complex-conjugate ambiguity of the modulation spectrum, a complex-valued OCT spectral interferogram was retrieved by removing one of the conjugate terms in the depth space. To validate the proposed concept, both flow phantom and live animal experiments were performed. The proposed AC-Angio-OCT offers a ∼50% decrease of misclassification errors, and an improved flow contrast and vessel connectivity, which contributes to the interpretation of OCT angiograms.

[Association of Insulin Resistance and ß Cell Function with Lipid Metabolism in Middle-aged and Elderly Hui and Han Populations].

OBJECTIVE: To explore the association of insulin resistance and ß cell function with lipid metabolism in middle-aged and elderly Hui and Han populations. METHODS: A total of 1000 subjects age over 40 years were recruited from five urban communities in Yinchuan and Wuzhong cities of Ningxia. The composition ratio between Hui and Han nationality was 1:2. A questionnaire-based survey was performed. Physical examinations were carried out to measure the height, body mass, waistline, and hipline. The levels of triglyceride (TG), total cholesterol (TC), blood uric acid (BUA), fasting blood glucose and insulin were measured. The boby mass index (BMI), waist-hip ratio (WHR), and secretion related index including insulin resistance index (IR), insulin sensitivity index (IAI), and beta cell function index (HBCI) were calculated. RESULTS: The BMI, WHR, IAI, HBCI, and the prevalence rate of diabetes in Hui nationality were significantly higher than those in Han nationality (P<0.01). The levels of BUA, fasting blood glucose, TC, and IR in Han nationality were significantly lower than those in Hui nationality (P<0.01). In Hui populations, TG, BMI, WHR, and BUA were positively correlated with IR (r=0.234, r=0.193, r=0.143, and r=0.129, respectively; P<0.01) and were negatively correlated with IAI (r=-0.234, r=-0.193, r=-0.143, r=-0.129, respectively; P<0.01), whereas TC was negatively correlated with HBCI (r=-0.169, P<0.01). In Han populations, TC, TG, BMI, WHR, and BUA were positively correlated with IR (r=0.140, r=0.257, r=0.288, r=0.163, r=0.104, P<0.01) and negatively correlated with IAI (r=-0.140, r=-0.257, r=-0.288, r=-0.163, and r=-0.104, P<0.01), whereas BMI was negatively correlated with HBCI (r=-0.111, P<0.01). After the influential factors such as gender, nationality, and age were adjusted, the TC, TG, BMI, WHR, BUA levels were positively correlated with IR (r=0.109, r=0.256, r=0.253, r=0.139, and r=0.142, P<0.01) and negatively correlated with IAI (r=-0.109, r=-0.256, r=-0.253, r=-0.139, and r=-0.142, P<0.01). TC and BMI were negatively correlated with HBCI (r=-0.113, r=-0.086, P<0.01). TG and BMI were independently associated with IR and IAI (r=0.218, r=0.182, r=-0.218, r=-0.182), while TC and BMI were independently associated with HBCI (r=-0.113, r=-0.086). CONCLUSIONS: The distributions of TC, TG, BMI, WHR, BUA, IR, IAI, and HBCI differ between Han and Hui populations. The development of insulin resistance is closely related with the increased levels of TC, TG, BMI, WHR, and BUA. However, the HBCI increases with the increased level of TC and BMI. TG and BMI may be related with insulin resistance. Also, TC and BMI may affect the secretion function of ß cells.

Robust Detection of Cracked Eggs Using a Multi-Domain Training Method for Practical Egg Production.

The presence of cracks reduces egg quality and safety, and can easily cause food safety hazards to consumers. Machine vision-based methods for cracked egg detection have achieved significant success on in-domain egg data. However, the performance of deep learning models usually decreases under practical industrial scenarios, such as the different egg varieties, origins, and environmental changes. Existing researches that rely on improving network structures or increasing training data volumes cannot effectively solve the problem of model performance decline on unknown egg testing data in practical egg production. To address these challenges, a novel and robust detection method is proposed to extract max domain-invariant features to enhance the model performance on unknown test egg data. Firstly, multi-domain egg data are built on different egg origins and acquisition devices. Then, a multi-domain trained strategy is established by using Maximum Mean Discrepancy with Normalized Squared Feature Estimation (NSFE-MMD) to obtain the optimal matching egg training domain. With the NSFE-MMD method, the original deep learning model can be applied without network structure improvements, which reduces the extremely complex tuning process and hyperparameter adjustments. Finally, robust cracked egg detection experiments are carried out on several unknown testing egg domains. The YOLOV5 (You Only Look Once v5) model trained by the proposed multi-domain training method with NSFE-MMD has a detection mAP of 86.6% on the unknown test Domain 4, and the YOLOV8 (You Only Look Once v8) model has a detection mAP of 88.8% on Domain 4, which is an increase of 8% and 4.4% compared to the best performance of models trained on a single domain, and an increase of 4.7% and 3.7% compared to models trained on all domains. In addition, the YOLOV5 model trained by the proposed multi-domain training method has a detection mAP of 87.9% on egg data of the unknown testing Domain 5. The experimental results demonstrate the robustness and effectiveness of the proposed multi-domain training method, which can be more suitable for the large quantity and variety of egg detection production.

Diameter-dependent classification of dermal vasculature using optical coherence tomography angiography.

Background: Dermal blood vessels beneath the epidermis play critical roles in epidermal homeostasis and are functionally divided into several types, such as capillaries. Optical coherence tomography angiography (OCTA) is a powerful tool for the non-invasive assessment of dermal vasculature. However, the classification of vessel types has been limited. To address this issue, we proposed an algorithm for diameter-dependent classification that preserves three-dimensional (3D) information using OCTA. Methods: OCTA data were acquired by a prototype swept-source-type optical coherence tomography (OCT) system, which was processed through several imaging filters: an optical microangiography (OMAG) imaging filter, a vesselness imaging filter, and a diameter map filter. All vessels were visually classified into three types based on their diameters, as micro-vessels, intermediate vessels, and thick vessels. Aging-related alterations and their association with the epidermis were investigated for each vessel type. The measurements were conducted on the cheeks of 124 female subjects aged 20-79 years. Results: The 3D vascular structure was visualized by applying our proposed post-processing filters. Based on visual assessment, the thresholds for the diameters of the micro, intermediate and thick vessels were set at 80 and 160 µm. It was found that micro-vessels were predominantly located in the upper layer of the dermis and thick vessels in the deeper layer. Analysis of vessel metrics revealed that the volume density of the micro-vessels decreased significantly with age (r=-0.36, P<0.001) and was positively correlated with epidermal thickness (r=0.50, P<0.001). In contrast, the volume density of thick vessels significantly increased with age (r=0.2, P<0.05) and was not significantly correlated with epidermal thickness (r=0.13, P≥0.05). Conclusions: In this study, we proposed a 3D quantification method using OCTA for dermal blood vessels and various vessel metrics, such as vessel volume density. This proposed classification will be beneficial for determining the function of the dermal vasculature and its diagnostic applications.

Longitudinal SS-OCT choroidal imaging following thrombosis of the superior ophthalmic vein.

Purpose: To report longitudinal changes in choroidal thickness and the choroidal vasculature using SS-OCT imaging in a patient with superior ophthalmic vein thrombosis (SOVT). Observations: In a 93-year-old woman with a left-sided SOVT, the choroid in the left eye was thickened and the choroidal vessels were dilated both superiorly and inferiorly, with greater changes evident in the inferotemporal region of the choroid. After the superior ophthalmic vein was decompressed, a decrease in the choroidal thickness and choroidal vessel dilatation was observed both superiorly and inferiorly. Conclusions and importance: In an eye with thrombosis of the superior ophthalmic vein, longitudinal SS-OCT choroidal imaging showed a greater increase in choroidal thickness and choroidal vessel dilation away from the obstructed quadrant, which improved after treatment. These observations associated with outflow obstruction may be applicable to other choroidal diseases characterized by venous overload.

Inorganic Pyrophosphate at Serum Concentration May Not Be Able to Inhibit Mineralization: A Study in Aqueous Solutions and Serum.

The constituent ions of calcium phosphate in body fluids are in the supersaturated state and tend to form minerals physiologically or pathologically. Inorganic pyrophosphate (PPi) has been considered as one of the most important inhibitors against the formation of calcium phosphate minerals. However, serum PPi concentrations in humans are maintained at a level of several µmol/L, and its effectiveness and mechanism for mineralization inhibition remain ambiguous. Therefore, this work studied the mineralization process in an aqueous solution, explored the effective inhibitory concentration of PPi by titration, and characterized the species during the reactions. We find that PPi at a normal serum concentration does not inhibit mineralization significantly. Such a conclusion was further confirmed in the PPi-added serum. This work indicates that PPi may not be a major direct inhibitor of mineralization in serum and possibly functions via alternative mechanisms.