Diversity matters: Cross-head mutual mean-teaching for semi-supervised medical image segmentation.

Semi-supervised medical image segmentation (SSMIS) has witnessed substantial advancements by leveraging limited labeled data and abundant unlabeled data. Nevertheless, existing state-of-the-art (SOTA) methods encounter challenges in accurately predicting labels for the unlabeled data, giving rise to disruptive noise during training and susceptibility to erroneous information overfitting. Moreover, applying perturbations to inaccurate predictions further impedes consistent learning. To address these concerns, we propose a novel cross-head mutual mean-teaching network (CMMT-Net) incorporated weak-strong data augmentations, thereby benefiting both co-training and consistency learning. More concretely, our CMMT-Net extends the cross-head co-training paradigm by introducing two auxiliary mean teacher models, which yield more accurate predictions and provide supplementary supervision. The predictions derived from weakly augmented samples generated by one mean teacher are leveraged to guide the training of another student with strongly augmented samples. Furthermore, two distinct yet synergistic data perturbations at the pixel and region levels are introduced. We propose mutual virtual adversarial training (MVAT) to smooth the decision boundary and enhance feature representations, and a cross-set CutMix strategy to generate more diverse training samples for capturing inherent structural data information. Notably, CMMT-Net simultaneously implements data, feature, and network perturbations, amplifying model diversity and generalization performance. Experimental results on three publicly available datasets indicate that our approach yields remarkable improvements over previous SOTA methods across various semi-supervised scenarios. The code is available at https://github.com/Leesoon1984/CMMT-Net.

Inositol 1,4,5-Trisphosphate Receptors Regulate Vascular Smooth Muscle Cell Proliferation and Neointima Formation in Mice.

BACKGROUND: Vascular smooth muscle cell (VSMC) proliferation is involved in many types of arterial diseases, including neointima hyperplasia, in which Ca2+ has been recognized as a key player. However, the physiological role of Ca2+ release via inositol 1,4,5-trisphosphate receptors (IP3Rs) from endoplasmic reticulum in regulating VSMC proliferation has not been well determined. METHODS AND RESULTS: Both in vitro cell culture models and in vivo mouse models were generated to investigate the role of IP3Rs in regulating VSMC proliferation. Expression of all 3 IP3R subtypes was increased in cultured VSMCs upon platelet-derived growth factor-BB and FBS stimulation as well as in the left carotid artery undergoing intimal thickening after vascular occlusion. Genetic ablation of all 3 IP3R subtypes abolished endoplasmic reticulum Ca2+ release in cultured VSMCs, significantly reduced cell proliferation induced by platelet-derived growth factor-BB and FBS stimulation, and also decreased cell migration of VSMCs. Furthermore, smooth muscle-specific deletion of all IP3R subtypes in adult mice dramatically attenuated neointima formation induced by left carotid artery ligation, accompanied by significant decreases in cell proliferation and matrix metalloproteinase-9 expression in injured vessels. Mechanistically, IP3R-mediated Ca2+ release may activate cAMP response element-binding protein, a key player in controlling VSMC proliferation, via Ca2+/calmodulin-dependent protein kinase II and Akt. Loss of IP3Rs suppressed cAMP response element-binding protein phosphorylation at Ser133 in both cultured VSMCs and injured vessels, whereas application of Ca2+ permeable ionophore, ionomycin, can reverse cAMP response element-binding protein phosphorylation in IP3R triple knockout VSMCs. CONCLUSIONS: Our results demonstrated an essential role of IP3R-mediated Ca2+ release from endoplasmic reticulum in regulating cAMP response element-binding protein activation, VSMC proliferation, and neointima formation in mouse arteries.

DIAS: A dataset and benchmark for intracranial artery segmentation in DSA sequences.

The automated segmentation of Intracranial Arteries (IA) in Digital Subtraction Angiography (DSA) plays a crucial role in the quantification of vascular morphology, significantly contributing to computer-assisted stroke research and clinical practice. Current research primarily focuses on the segmentation of single-frame DSA using proprietary datasets. However, these methods face challenges due to the inherent limitation of single-frame DSA, which only partially displays vascular contrast, thereby hindering accurate vascular structure representation. In this work, we introduce DIAS, a dataset specifically developed for IA segmentation in DSA sequences. We establish a comprehensive benchmark for evaluating DIAS, covering full, weak, and semi-supervised segmentation methods. Specifically, we propose the vessel sequence segmentation network, in which the sequence feature extraction module effectively captures spatiotemporal representations of intravascular contrast, achieving intracranial artery segmentation in 2D+Time DSA sequences. For weakly-supervised IA segmentation, we propose a novel scribble learning-based image segmentation framework, which, under the guidance of scribble labels, employs cross pseudo-supervision and consistency regularization to improve the performance of the segmentation network. Furthermore, we introduce the random patch-based self-training framework, aimed at alleviating the performance constraints encountered in IA segmentation due to the limited availability of annotated DSA data. Our extensive experiments on the DIAS dataset demonstrate the effectiveness of these methods as potential baselines for future research and clinical applications. The dataset and code are publicly available at https://doi.org/10.5281/zenodo.11401368 and https://github.com/lseventeen/DIAS.

Peripheral 5-HT Mediates Gonadotropin-Inhibitory Hormone-Induced Feeding Behavior and Energy Metabolism Disorder in Chickens via the 5-HT2C Receptor.

INTRODUCTION: Since the discovery of gonadotropin-inhibitory hormone (GnIH), it has been found to play a critical role in reproduction in vertebrates. Recently, a regulatory role of GnIH in appetite and energy metabolism has emerged, although its precise physiological mechanisms remain unknown. METHODS: Thus, the present study evaluated the effects of a single or long-term intraperitoneal GnIH treatment on the food intake, weight, and glucolipid metabolism of chickens, as well as investigating the possible neuroendocrinology factors and mechanisms involved in GnIH-induced obesity and glucolipid metabolism disorder. RESULTS: Our results show that the intraperitoneal administration of GnIH to chickens resulted in a marked body mass increase, hyperlipidemia, hyperglycemia, and glucose intolerance. Subsequently, the results of metabolomics studies and the pharmacological inhibition of the 5-HT2C receptor revealed that blocking the 5-HT2C receptor reinforced the effects of GnIH on food intake, body weight, and blood glucose and lipid levels, resulting in even worse cases of GnIH-induced hyperglycemia, hyperlipidemia, and hepatic lipid deposition. This suggests that, via the 5-HT2C receptor, peripheral 5-HT may act as a negative feedback regulator to interplay with GnIH and jointly control energy balance homeostasis in chickens. DISCUSSION: Our present study provides evidence of cross-talk between GnIH and 5-HT in food intake and energy metabolism at the in vivo pharmacological level, and it proposes a molecular basis for these interactions, suggesting that functional interactions between GnIH and 5-HT may open new avenues for understanding the mechanism of the neuroendocrine network involved in appetite and energy metabolism, as well as providing a new therapeutic strategy to prevent obesity, diabetes, and metabolic disorders.

Polycyclic aromatic hydrocarbons exposure and arterial stiffness-related plasma miRNAs: A panel study.

The underlying mechanisms between polycyclic aromatic hydrocarbons (PAHs) exposure and arterial stiffness are poorly understood. We carried out a panel study involving three repeated surveys to examine the associations of individual and mixture of PAHs exposure with arterial stiffness-related miRNAs among 123 community adults. In linear mixed-effect (LME) models, we found that urinary 9-hydroxyfluorene (9-OHFlu), 2-hydroxyphenanthrene (2-OHPh), 9-hydroxyphenanthrene (9-OHPh) at lag 0 day were positively linked to miR-146a and/or miR-222. The Bayesian kernel machine regression (BKMR) analyses revealed positive overall associations of PAHs mixture at lag 0 day with miR-146a and miR-222, and urinary 9-OHFlu contributed the most. In addition, an inter-quartile range (IQR) increase in urinary 9-OHFlu at lag 0 day was associated with elevated miR-146a and miR-222 by 0.16 (95% CI: 0.02, 0.30) to 0.34 (95% CI: 0.13, 0.54). Accordingly, exposure to PAHs, especially 9-OHFlu at lag 0 day, was related to elevated arterial stiffness-related plasma miRNAs.

Physical activity modified association of urinary metals mixture and fasting blood glucose in children: From two panel studies.

There is unclear evidence available on the associations between multiple metals and fasting blood glucose (FBG) in children, and whether they could be beneficial from physical activity. We included 283 children aged 4-12 years from two panel studies with 4-consecutive morning urinary 13 essential metals and 10 non-essential metals repeated across 3 seasons. We employed multiple informant model, linear mixed-effect model, and quantile g-computation to evaluate associations of single metal and their mixture with FBG and interactions with extra-school activity. The results showed that positive relations of multiple essential metals (aluminum, chromium, copper, iron, molybdenum (Mo), nickel, selenium (Se), strontium, zinc) and non-essential metals (arsenic (As), cadmium (Cd), rubidium, titanium (Ti), thallium) with FBG were the strongest at lag 0 (the health examination day), especially in overweight & obesity children (FDR <0.05). The strongest effect presented 1-fold increment in As was related to FBG increased 1.66% (95%CI: 0.84%, 2.48%) in overweight & obesity children. Notably, modification of extra-school activity showed significant, and the effects of multiple metals on FBG were attenuated in children taking total extra-school activity ≥1 h/day, and only one type of which, low or moderate & high intensity extra-school activity reached 20 min/day (Pint <0.05). For instance, each 1-fold increased As was associated with 1.41% increased FBG in overall children taking total extra-school activity <1 h/day, while that of 0.13% in those ≥1 h/day. Meanwhile, mixture of all, essential and non-essential metals were associated with increased FBG, a trend that decreased and became nonsignificant in children having certain extra-school activity, which were dominated by Mo, Se, Ti, Cd. And such relations were substantially beneficial from extra-school activity in overweight & obesity children. Accordingly, multiple essential and non-essential metals, both individual and in mixture, were positively related to FBG in children, which might be attenuated by regular physical activity.

ERNet: Edge Regularization Network for Cerebral Vessel Segmentation in Digital Subtraction Angiography Images.

Stroke is a leading cause of disability and fatality in the world, with ischemic stroke being the most common type. Digital Subtraction Angiography images, the gold standard in the operation process, can accurately show the contours and blood flow of cerebral vessels. The segmentation of cerebral vessels in DSA images can effectively help physicians assess the lesions. However, due to the disturbances in imaging parameters and changes in imaging scale, accurate cerebral vessel segmentation in DSA images is still a challenging task. In this paper, we propose a novel Edge Regularization Network (ERNet) to segment cerebral vessels in DSA images. Specifically, ERNet employs the erosion and dilation processes on the original binary vessel annotation to generate pseudo-ground truths of False Negative and False Positive, which serve as constraints to refine the coarse predictions based on their mapping relationship with the original vessels. In addition, we exploit a Hybrid Fusion Module based on convolution and transformers to extract local features and build long-range dependencies. Moreover, to support and advance the open research in the field of ischemic stroke, we introduce FPDSA, the first pixel-level semantic segmentation dataset for cerebral vessels. Extensive experiments on FPDSA illustrate the leading performance of our ERNet.

TBENet:A two-branch boundary enhancement Network for cerebrovascular segmentation.

Cerebrovascular segmentation in digital subtraction angiography (DSA) images is the gold standard for clinical diagnosis. However, owing to the complexity of cerebrovascular, automatic cerebrovascular segmentation in DSA images is a challenging task. In this paper, we propose a CNN-based Two-branch Boundary Enhancement Network (TBENet) for automatic segmentation of cerebrovascular in DSA images. The TBENet is inspired by U-Net and designed as an encoder-decoder architecture. We propose an additional boundary branch to segment the boundary of cerebrovascular and a Main and Boundary branches Fusion Module (MBFM) to integrate the boundary branch outcome with the main branch outcome to achieve better segmentation performance. The TBENet was evaluated on HMCDSA (an in-house DSA cerebrovascular dataset), and reaches 0.9611, 0.7486, 0.7152, 0.9860 and 0.9556 in Accuracy, F1 score, Sensitivity, Specificity, and AUC, respectively. Meanwhile, we tested our TBENet on the public vessel segmentation benchmark DRIVE, and the results show that our TBENet can be extended to diverse vessel segmentation tasks.

A feedback loop of PPP and PI3K/AKT signal pathway drives regorafenib-resistance in HCC.

BACKGROUND: Hepatocellular carcinoma (HCC) is a principal type of liver cancer with high incidence and mortality rates. Regorafenib is a novel oral multikinase inhibitor for second-line therapy for advanced HCC. However, resistance to regorafenib is gradually becoming a dilemma for HCC and the mechanism remains unclear. In this study, we aimed to reveal the metabolic profiles of regorafenib-resistant cells and the key role and mechanism of the most relevant metabolic pathway in regorafenib resistance. METHODS: Metabolomics was performed to detect the metabolic alteration between drug-sensitive and regorafenib-resistant cells. Colony formation assay, CCK-8 assay and flow cytometry were applied to observe cell colony formation, cell proliferation and apoptosis, respectively. The protein and mRNA levels were detected by western blot and RT-qPCR. Cell lines of Glucose-6-phosphate dehydrogenase(G6PD) knockdown in regorafenib-resistant cells or G6PD overexpression in HCC cell lines were stably established by lentivirus infection technique. G6PD activity, NADPH level, NADPH/NADP+ ratio, the ratio of ROS positive cells, GSH level, and GSH/GSSG ratio were detected to evaluate the anti-oxidative stress ability of cells. Phosphorylation levels of NADK were evaluated by immunoprecipitation. RESULTS: Metabonomics analysis revealed that pentose phosphate pathway (PPP) was the most relevant metabolic pathway in regorafenib resistance in HCC. Compared with drug-sensitive cells, G6PD enzyme activity, NADPH level and NADPH/NADP+ ratio were increased in regorafenib-resistant cells, but the ratio of ROS positive cells and the apoptosis rate under the conditions of oxidative stress were decreased. Furthermore, G6PD suppression using shRNA or an inhibitor, sensitized regorafenib-resistant cells to regorafenib. In contrast, G6PD overexpression blunted the effects of regorafenib to drug-sensitive cells. Mechanistically, G6PD, the rate-limiting enzyme of PPP, regulated the PI3K/AKT activation. Furthermore, PI3K/AKT inhibition decreased G6PD protein expression, G6PD enzymatic activity and the capacity of PPP to anti-oxidative stress possibly by inhibited the expression and phosphorylation of NADK. CONCLUSION: Taken together, a feedback loop of PPP and PI3K/AKT signal pathway drives regorafenib-resistance in HCC and targeting the feedback loop could be a promising approach to overcome drug resistance.

Elevated Intracranial Pressure Level Is a Risk Factor for Sepsis-associated Encephalopathy: A Prospective Cohort Study.

BACKGROUND/AIM: Cerebral edema is common in patients with sepsis-associated encephalopathy (SAE) and is a major cause of elevated intracranial pressure (ICP); however, the relationship between elevated ICP and SAE is unclear. The aim of this study was to investigate the association between optic nerve sheath diameter (ONSD), a surrogate of ICP, and the incidence of SAE. PATIENTS AND METHODS: A prospective observational study was performed in a medical-surgical adult intensive care unit (ICU). All patients in the ICU who were consecutively diagnosed with sepsis during the study period were evaluated for eligibility. Ultrasound measurements of ONSD were performed within 6 h of enrollment and every two days thereafter until the patient developed SAE. Clinical and blood test data were collected throughout this period. Patients underwent a daily conscious and cognitive assessment. SAE was diagnosed as delirium or Glasgow Coma Scale (GCS) <15 points. Multivariate modified Poisson regression analysis was performed to identify risk factors for SAE. RESULTS: A total of 123 patients with sepsis were included in the analysis. 58 patients (47.2%) developed SAE. The levels of ONSD0 (the first measured value) and ONSDmax (the maximum measured value) in the SAE group were significantly higher than those in the non-SAE group (5.23±0.52 mm vs. 5.85±0.54 mm for ONSD0 and 5.41±0.46 mm vs. 6.09±0.58 mm for ONSDmax, respectively; all p-values <0.001). The area under the curves (AUCs) for the ONSD0 and ONSDmax values in predicting SAE were 0.801 (95%CI=0.723-0.880, p<0.001) and 0.829 (95%CI=0.754-0.903, p<0.001), respectively. A higher ONSD0 level was significantly associated with an increased risk of SAE (adjusted risk ratio 3.241; 95%CI=1.686-6.230, p<0.001). CONCLUSION: The levels of ONSD correlate with risk of SAE, indicating that increased ICP level is an independent risk factor for the development of SAE. Dynamic monitoring of ONSD/ICP has a high predictive value for SAE. Measures to prevent increases in ICP are helpful to reduce the incidence of SAE in sepsis patients.

Short-term exposure to multiple metals mixture and mitochondrial DNA copy number among children: A panel study.

BACKGROUND: Little is known regarding the individual and overall associations of short-term co-exposure to metals mixture with mitochondrial DNA copy number (mtDNAcn) among healthy children. METHODS: We conducted a panel study across three seasons among 144 children aged 4 to 12 years in Guangzhou. For each season, we collected the first-morning urine for four consecutive days and fasting blood on the 4th day to detect 23 urinary metals and blood leukocyte mtDNAcn, respectively. Linear mixed-effect (LME) models and multiple informant models were used to examine the relations of individual metals with mtDNAcn over different lag days, and the least absolute shrinkage and selection operator (LASSO) regression was applied to determine the most important metal. We further employed weighted quantile sum (WQS) regression to investigate the overall association of metals mixture with mtDNAcn. RESULTS: Nickel (Ni), manganese (Mn) and antimony (Sb) were independently associated with mtDNAcn in a linear dose-response manner. Each 1-fold increase in Ni at lag 0 day, Mn and Sb at lag 2 day was associated with respective decrements of 8.74 %, 6.93 % and 3.98 % in mtDNAcn in multi-metal LME models. LASSO regression also selected Ni, Mn and Sb as the most significant metals at the corresponding lag day. WQS regression showed overall inverse associations between metals mixture and mtDNAcn both at lag 0 and lag 2 day, with mtDNAcn decreased by 2.75 % and 3.14 % in response to a quartile increase in the WQS index. Additionally, the associations of Ni and Mn with decreased mtDNAcn were stronger among children younger than 7 years, girls and those having less vegetables and fruit intake. CONCLUSION: We found an overall association between metals mixture and decreased mtDNAcn among healthy children, in which Ni, Mn and Sb were the major contributors. Younger children, girls and those with less vegetables and fruit intake were more susceptible.

Urinary phthalate metabolites and heart rate variability: A panel study.

Phthalates exposure is linked with cardiovascular disease. Decreased heart rate variability (HRV) is an early indicator of cardiac autonomic imbalance. We conducted a longitudinal panel study in 127 Chinese adults with 3 repeated visits to explore the associations of individual and mixtures of phthalates exposure with HRV. We quantified 10 urinary phthalate metabolites by gas chromatograph-tandem mass spectrometer (GC-MS/MS) and 6 HRV indices by 3-channel digital Holter monitors. Linear mixed-effect (LME) models and Bayesian kernel machine regression (BKMR) models were separately implemented to evaluate the associations. After multivariate adjustments, we found that urinary mono-ethyl phthalate (MEP), mono-iso-butyl phthalate (MiBP), and mono-n-butyl phthalate (MBP) at lag 0 day were inversely associated with low-frequency power (LF) or total power (TP) (all P-FDR <0.05). In mixture analysis, we observed negative overall associations of phthalate mixtures at lag 0 day with LF or TP, and MiBP was the major contributor. Moreover, stratified analysis suggested that the inverse relationships of MiBP at lag 0 day with LF and TP were more prominent in subjects aged >50 years (all Pinteraction < 0.01). Our findings revealed that exposure to individual and mixtures of phthalates, especially MiBP, were related to decreased HRV.

A highly efficient and accurate method of detecting and subtyping Influenza A pdm H1N1 and H3N2 viruses with newly emerging mutations in the matrix gene in Eastern Taiwan.

The rapid identification of Influenza A virus and its variants, which cause severe respiratory diseases, is imperative to providing timely treatment and improving patient outcomes. Conventionally, two separate assays (total test duration of up to 6 h) are required to initially differentiate Influenza A and B viruses and subsequently distinguish the pdm H1N1 and H3N2 serotypes of Influenza A virus. In this study, we developed a multiplex real-time RT-PCR method for simultaneously detecting Influenza A and B viruses and subtyping Influenza A virus, with a substantially reduced test duration. Clinical specimens from hospitalized patients and outpatients with influenza-like symptoms in Eastern Taiwan were collected between 2011 and 2015, transported to Hualien Tzu Chi Hospital, and analyzed. Conventional RT-PCR was used to subtype the isolated Influenza A viruses. Thereafter, for rapid identification, the multiplex real-time RT-PCR method was developed and applied to identify the conserved regions that aligned with the available primers and probes. Accordingly, a multiplex RT-PCR assay with three groups of primers and probes (MAF and MAR primers and MA probe; InfAF and InfAR primers and InfA probe; and MBF and MBR primers and MB probe) was established to distinguish these viruses in the same reaction. Thus, with this multiplex RT-PCR assay, Influenza B, Influenza A pdm H1N1, and Influenza A H3N2 viruses were accurately detected and differentiated within only 2.5 h. This multiplex RT-PCR assay showed similar analytical sensitivity to the conventional singleplex assay. Further, the phylogenetic analyses of our samples revealed that the characteristics of these viruses were different from those reported previously using samples collected during 2012-2013. In conclusion, we developed a multiplex real-time RT-PCR method for highly efficient and accurate detection and differentiation of Influenza A and B viruses and subtyping Influenza A virus with a substantially reduced test duration for diagnosis.

Associations of Urinary Phthalate Metabolites with Thyroid Function and the Mediated Role of Cytokines: A Panel Study of Healthy Children.

Evidence on joint association of a phthalate mixture with thyroid function among children and its underlying mechanism is largely unknown. We aimed to explore the associations of 10 urinary phthalate metabolites (mPAEs), either as individuals or as a mixture, with thyroid function indicators [free thyroxine, free triiodothyronine (FT3), and thyroid-stimulating hormone (TSH)] in 144 children aged 4-12 years with up to 3 repeated visits across 3 seasons. Significant and positive associations were observed for mono-(2-ethylhexyl) phthalate (MEHP), mono-iso-butyl phthalate (MiBP), and mono-n-butyl phthalate (MnBP) with TSH, as well as monobenzyl phthalate (MBzP) with FT3 in dose-response manners. The relationship between MEHP and TSH remained robust in multiple-phthalate models. Bayesian kernel machine regression (BKMR) models revealed overall linear associations of the 10 mPAE mixture with higher TSH and FT3 levels, and MEHP and MBzP were major contributors. Meanwhile, MEHP, MiBP, and MnBP were linked to the elevation of multiple cytokines including CCL 27, CCL3, CXCL1, and IL-16. Among them, IL-16 mediated the relationships of MEHP and MiBP with TSH, and the mediated proportions were 24.16% and 24.27%, respectively. Our findings suggested that mPAEs dominated by MEHP were dose-responsively associated with elevated TSH among healthy children and mediated by IL-16.

A Novel 3D Culture Scaffold to Shorten Development Time for Multicellular Tumor Spheroids.

Multicellular tumor spheroids and tumoroids are considered ideal in vitro models that reflect the features of the tumor microenvironment. Biomimetic components resembling the extracellular matrix form scaffolds to provide structure to 3-dimensional (3D) culture systems, supporting the growth of both spheroids and tumoroids. Although Matrigel has long been used to support 3D culture systems, batch variations, component complexity, and the use of components derived from tumors are complicating factors. To address these issues, we developed the ACD 3D culture system to provide better control and consistency. We evaluated spheroid and tumoroid formation using the ACD 3D culture system, including the assessment of cell viability and cancer marker expression. Under ACD 3D culture conditions, spheroids derived from cancer cell lines exhibited cancer stem cell characteristics, including a sphere-forming size and the expression of stem cell marker genes. The ACD 3D culture system was also able to support patient-derived primary cells and organoid cell cultures, displaying adequate cell growth, appropriate morphology, and resistance to oxaliplatin treatment. These spheroids could also be used for drug screening purposes. In conclusion, the ACD 3D culture system represents an efficient tool for basic cancer research and therapeutic development.

Individual and joint associations of co-exposure to multiple plasma metals with telomere length among middle-aged and older Chinese in the Dongfeng-Tongji cohort.

Studies on associations of metals with leucocyte telomere length (LTL) were mainly limited to several most common toxic metals and single-metal effect, but the impact of other common metals and especially the overall joint associations and interactions of metal mixture with LTL are largely unknown. We included 15 plasma metals and LTL among 4906 participants from Dongfeng-Tongji cohort. Multivariable linear regression was used to estimate associations of individual metals with LTL. We also applied Bayesian kernel machine regression (BKMR) and quantile g-computation regression (Q-g) to evaluate the overall association and interactions, and identified the major contributors as well as the potential modifications by major characteristics. Multivariable linear regression found vanadium, copper, arsenic, aluminum and nickel were negatively associated with LTL, and a 2-fold change was related to 1.9%-5.1% shorter LTL; while manganese and zinc showed 3.7% and 4.0% longer LTL (all P < 0.05) in multiple-metal models. BKMR confirmed above metals and revealed a linearly inverse joint association between 15 metals and LTL. Q-g regression further indicated each quantile increase in mixture was associated with 5.2% shorter LTL (95% CI: -8.1%, -2.3%). Furthermore, manganese counteracted against aluminum and vanadium respectively (Pint<0.05). In addition, associations of vanadium, aluminum and metal mixture with LTL were more prominent in overweight participants. Our results are among the first to provide a new comprehensive view of metal mixture exposure on LTL attrition in the general population, including identifying the major components, metals interactions and the overall effects.

[Investigation of intracranial pressure in intensive care unit patients with delirium assessed by bedside ultrasound].

OBJECTIVE: To explore the changes of intracranial pressure in intensive care unit (ICU) patients during the occurrence and evolution of delirium by using bedside ultrasound to measure the optic nerve sheath diameter (ONSD) to evaluate intracranial pressure. METHODS: A retrospective observational study was conducted. Adult patients who developed delirium during hospitalization in the general ICU of Beihai People's Hospital from October 2020 to November 2021 were enrolled, and patients who did not have ultrasonographic ONSD records within 24 hours after the diagnosis of delirium were excluded. The ONSD measured before delirium was recorded as ONSD0, the ONSD measured within 24 hours of the onset of delirium recorded as ONSD1, and the ONSD reexamined after ONSD1 recorded as ONSD2. Patients were divided into intracranial hypertension group (ONSD1 > 5 mm) and normal intracranial pressure group (ONSD1 ≤ 5 mm) according to the size of ONSD1. According to the outcome of delirium, the patients were divided into cured, improved, and non-improved groups. The reduction ratio of ONSD2 to ONSD1 in the three groups were calculated and compared. Pearson correlation test was used to analyze the correlation between fluid balance and ONSD changes after delirium. RESULTS: There were 43 patients, including 40 cases in the intracranial hypertension group (the incidence rate was 93.0%), 3 cases in the normal intracranial pressure group, 23 cases were cured, 13 cases were improved, and 7 cases were not improved. In the intracranial hypertension group, 11 cases had ONSD0 and ONSD1 records, and ONSD1 was significantly higher than ONSD0 [mm: 5.88±0.61 vs. 5.34±0.57, 95% confidence interval (95%CI) -0.85 to -0.23, P = 0.003]. The reduction ratio of ONSD2 to ONSD1 in the cured group was significantly higher than that in the improved group and the non-improved group [(12.04±6.20)% vs. (5.68±4.10)%, (0.17±3.96)%; 95%CI were 2.37 to 10.33, 6.41 to 17.31, P values were 0.003 and 0.000, respectively]. The correlation analysis showed that the reduction ratio of ONSD2 to ONSD1 was negatively correlated with fluid balance (r = -0.42, 95%CI was -0.66 to -0.10, P = 0.012). CONCLUSIONS: The incidence of intracranial hypertension in ICU delirium patients is high. A more pronounced decrease in intracranial pressure predicts a better delirium outcome. Dynamic ONSD measurement can provide valuable information for the prevention and treatment of delirium.

Full-Resolution Network and Dual-Threshold Iteration for Retinal Vessel and Coronary Angiograph Segmentation.

Vessel segmentation is critical for disease diagnosis and surgical planning. Recently, the vessel segmentation method based on deep learning has achieved outstanding performance. However, vessel segmentation remains challenging due to thin vessels with low contrast that easily lose spatial information in the traditional U-shaped segmentation network. To alleviate this problem, we propose a novel and straightforward full-resolution network (FR-UNet) that expands horizontally and vertically through a multiresolution convolution interactive mechanism while retaining full image resolution. In FR-UNet, the feature aggregation module integrates multiscale feature maps from adjacent stages to supplement high-level contextual information. The modified residual blocks continuously learn multiresolution representations to obtain a pixel-level accuracy prediction map. Moreover, we propose the dual-threshold iterative algorithm (DTI) to extract weak vessel pixels for improving vessel connectivity. The proposed method was evaluated on retinal vessel datasets (DRIVE, CHASE_DB1, and STARE) and coronary angiography datasets (DCA1 and CHUAC). The results demonstrate that FR-UNet outperforms state-of-the-art methods by achieving the highest Sen, AUC, F1, and IOU on most of the above-mentioned datasets with fewer parameters, and that DTI enhances vessel connectivity while greatly improving sensitivity. The code is available at: https://github.com/lseventeen/FR-UNet.