Extracellular Water Ratio and Phase Angle as Predictors of Exacerbation in Chronic Obstructive Pulmonary Disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD), characterized by high-energy metabolism, often leads to malnutrition and is linked to exacerbations. This study investigates the association of malnutrition-related body composition and handgrip strength changes with exacerbation frequencies in COPD patients. METHODS: We analyzed 77 acute exacerbation COPD (AECOPD) patients and 82 stable COPD patients, categorized as frequent and infrequent exacerbators. Assessments included body composition, handgrip strength, nutritional risk, dyspnea scale, and COPD assessment. RESULTS: Among AECOPD patients, there were 22 infrequent and 55 frequent exacerbators. Infrequent exacerbators showed better muscle parameters, extracellular water ratio, phase angle, and handgrip strength. Significant differences in intracellular water, total cellular water, protein, and body cell mass were observed between groups. Logistic regression indicated that extracellular water ratio (OR = 1.086) and phase angle (OR = 0.396) were independently associated with exacerbation risk. Thresholds for exacerbation risk were identified as 0.393 for extracellular water ratio and 4.85° for phase angle. In stable COPD, 13 frequent and 69 infrequent exacerbators were compared, showing no significant differences in weight, muscle, and adipose parameters, but significant differences in extracellular water ratio, phase angle, and handgrip strength. CONCLUSIONS: These findings suggest that increased exacerbations in COPD patients correlate with higher extracellular water ratios and lower phase angles.

Breathable and wearable graphene/waterborne polyurethane coated regenerated polyethylene terephthalate fabrics for motion sensing and thermal therapy.

The functional utilization of recycled polymers has emerged as a current prominent and timely subject. Flexible wearable devices with high sensitivity to conductivity have garnered significant attention in the fields of human healthcare monitoring and personal heat management. One significant obstacle that needs to be addressed is the simultaneous maintenance of both sensing functionality and durability in composite fabrics. In this paper, a collection of durable, breathable, and flexible smart fabric was produced using the scratch coating method. The fabrics were created by utilizing a regenerated polyethylene terephthalate fabric as a base material, incorporating graphene microsheets (G) as a conductive agent, and applying a waterborne polyurethane layer as a surface protective coating. Furthermore, an investigation was conducted to assess their sensing performance and electrothermal performance. The composite fabric exhibits significant advantages in terms of high conductivity (592 S/m), wide strain range, high sensitivity (Gauge factor = 6.04) and fantabulous dynamic stability (2000 cycles) at a mass ratio of Graphene/WPU loading of 8:2. These sensors were successfully utilized to monitor various degrees of real-time human body movements, ranging from significant deformation bending of elbows to slight deformation swallowing. Furthermore, the sensors also exhibit a significant electric heating effect. Specifically, when a voltage of 10 V is applied, the sensors can reach a steady state temperature of 53.3 °C within a mere 30 s. This discovery holds potential for the development of wearable heaters that can be used for on-demand thermal therapy, functional protective clothing, and medical electric heating wearables.

Migraine Duration as a Potential Amplifier of Obesity.

Purpose: Migraine is a complex neurovascular disorder with obesity as a notable risk factor. This study aimed to investigate an under-researched area of the association between migraine duration and body composition. Patients and Methods: Patients with migraine from a neurology outpatient department were enrolled and were categorized into four groups based on illness duration: 1 year, 1-5 years, 5-10 years, and >10 years. Patient demographics, blood biochemistry, and body composition data were collected and analyzed statistically. Results: Patients with migraine were predominantly female, with lower education levels, significant work stress, poor sleep, and limited exercise. Longer migraine duration corresponded to increased obesity metrics. Notably, those patients with under 1 year of illness showed elevated blood lipid and liver function levels, whereas those with >10 years showed increased weight, waist circumference, body mass index, and fat content, despite higher physical activity. Significant positive correlation between obesity metrics and migraine duration was seen in patients who had migraine for >1 year. Conclusion: Our findings indicate that protracted episodes of migraine could amplify obesity tendencies, underscoring the imperative of weight regulation in migraine intervention to diminish ensuing adiposity-associated hazards.

Systematic review and meta-analysis of nutrient supplements for treating sarcopenia in people with chronic obstructive pulmonary disease.

Individuals with chronic obstructive pulmonary disease (COPD) are prone to malnutrition and sarcopenia as a result of nutritional deficiencies and increased energy metabolism. However, the effects of nutrient supplements (NS) on treating sarcopenia in patients with COPD are not well established from systematic evidence. This meta-analysis examined the effect of NS on sarcopenia in patients with COPD. A systematic search of multiple databases was conducted, and 29 randomized controlled trials involving 1625 participants (age, mean [SD] = 67.9 [7.8] years) were analyzed. NS demonstrated significant improvements in body weight (MD,1.33 kg; 95% CI, 0.60, 2.05 kg; P = 0.0003; I2 = 87%), fat-free mass index (MD, 0.74 kg/m2; 95% CI, 0.21, 1.27 kg/m2; P = 0.007; I2 = 75%), and 6-min walk test (MD, 19.43 m; 95% CI, 4.91, 33.94 m; P = 0.009; I2 = 81%) compared with control. However, NS had nonsignificant effects on handgrip strength (SMD, 0.36; 95% CI, - 0.15, 0.88; P = 0.16; I2 = 87%) and quadriceps muscle strength (SMD, 0.11; 95% CI, -  0.06, 0.27; P = 0.20; I2 = 25%) compared with the control. In conclusion, NS may be an effective treatment for improving body composition and physical performance in COPD. Future studies should explore the effects of intervention durations, specific NS types, or combined training in patients with COPD and sarcopenia.

Examining the molecular mechanisms of topiramate in alleviating insulin resistance: A study on C2C12 myocytes and 3T3L-1 adipocytes.

PURPOSE: Migraine, a severely debilitating condition, may be effectively managed with topiramate, known for its migraine prevention and weight loss properties due to changes in body muscle and fat composition and improved insulin sensitivity. However, the mechanism of topiramate in modulating insulin response in adipocytes and myocytes remains elusive. This study aims to elucidate these molecular mechanisms, offering insights into its role in weight management for migraine sufferers and underpinning its clinical application. METHODS: Insulin resistance improvements were evaluated through glucose uptake measurements in C2C12 muscle cells and 3T3L-1 adipocytes, with Oil red O staining conducted on adipocytes. RNA-seq transcriptome analysis was used to identify the regulatory target genes of topiramate in these cells. The involvement of key genes and pathways was further validated through western blot analysis. RESULTS: Topiramate effectively reduced insulin resistance in C2C12 and 3T3L-1 cells. In C2C12 cells, it significantly lowered SORBS1 gene and protein levels. In 3T3L-1 cells, topiramate upregulated CTGF and downregulated MAPK8 and KPNA1 genes. Changes were notable in nuclear cytoplasmic transport and circadian signaling pathways. Furthermore, it caused downregulation of MKK7, pJNK1/ JNK1, BMAL1, and CLOCK proteins compared to the insulin-resistant model. CONCLUSION: This study provides preliminary insights into the mechanisms through which topiramate modulates insulin resistance in C2C12 myocytes and 3T3L-1 adipocytes, enhancing our understanding of its therapeutic potential in managing weight and insulin sensitivity in migraine patients.

Formations of C6H from reactions C3 + C3H2 and C3H + C3H and of C8H from reactions C4 + C4H2 and C4H + C4H.

We interrogated C6H and C8H produced separately from the reactions C3 + C3H2/C3H + C3H/C3H2 + C3 → C6H + H and C4 + C4H2/C4H + C4H/C4H2 + C4 → C8H + H using product translational and photoionization spectroscopy. Individual contributions of the three reactions to the product C6H or C8H were evaluated with reactant concentrations. Translational-energy distributions, angular distributions, and photoionization efficiency curves of products C6H and C8H were unraveled. The product C6H (C8H) was recognized as the most stable linear isomer by comparing its photoionization efficiency curve with that of l-C6H (l-C8H), produced exclusively from the reaction C2 + C4H2 → l-C6H + H (C2 + C6H2 → l-C8H + H). The ionization threshold after deconvolution was determined to be 9.3 ± 0.1 eV for l-C6H and 8.9 ± 0.1 eV for l-C8H, which is in good agreement with theoretical values. Quantum-chemical calculations indicate that the reactions of C3 + C3H2 and C3H + C3H (C4 + C4H2 and C4H + C4H) incur no energy barriers that lie above the corresponding reactant and the most stable product l-C6H (l-C8H) with H on the lower-lying potential-energy surfaces. The theoretical calculation is in accord with the experimental observation. This work implies that the reactions of C3 + C3H2/C3H + C3H and C4 + C4H2/C4H + C4H need to be taken into account for the formation of interstellar C6H and C8H, respectively.

Study on Formation of Interstellar C7H from Reactions C4 + C3H2 and C4H + C3H.

We interrogated C7H produced from reactions C4 + C3H2/C4H + C3H → C7H + H using both translational and photoionization spectroscopy. Reactants C3H, C3H2, C4, and C4H were synthesized in two crossed beams of 1% C2H2/He ignited by pulsed high-voltage discharge. The individual contributions of reactions C4 + C3H2 and C4H + C3H to product C7H were evaluated as 17:83 from reactant concentrations in both molecular beams. The translational energy distribution, the angular distribution, and the photoionization efficiency curve of product C7H were unraveled. C7H was identified as the most stable linear isomer by its photoionization efficiency curve that features two ionization thresholds corresponding to separate transitions to singlet and triplet states of l-C7H+. The quantum-chemical calculations indicate that the associations of C4 with C3H2 and C4H with C3H incur no entrance barriers, and the most favorable exit channel leads to product l-C7H + H. It is the first time demonstrating that C7H is producible from reactions 1,3C4 + 1C3H2 and 2C4H + 2C3H on the lowest-lying singlet and triplet potential energy surfaces of 1,3C7H2. This work implies that the reactions of C4 + C3H2 and C4H + C3H might have contributions to interstellar C7H to some extent as compared with the C + C6H2 reaction commonly adopted in an astrochemical model.

Synergistic enhancement of modified sericite on rheological and foaming properties of poly (lactic acid).

Due to low melt strength and slow crystallization rate, poly (lactic acid) (PLA) foam materials are still not satisfactory. In order to improve the foaming performance of PLA, sericite (GA) was selected as the filler and modified by 3-Aminopropyltriethoxysilane (KH-550). Through melt blending with PLA, azodicarbonamide (ADC) foaming agent was selected for molding foaming, and PLA/GA composite foam was prepared. The addition of GA not only acts as a nucleating agent to improve the crystallization performance of the blend, but also improves its complex viscosity and storage modulus, and enhances its melt strength, so that the compressive strength and impact strength of the prepared composite foam are increased by 265.5 % and 224.0 %, respectively. Compared with PE foam, PLA/GA composite foam showed excellent thermal insulation performance through thermal infrared imaging test. Based on its mechanical and thermal insulation properties, this sample provides new materials for the field of wall insulation and foam packaging. This study provides an effective way to improve the melt strength and workability of PLA.

Is a soft tissue reinforcing mesh necessary in immediate prosthetic breast reconstruction for early breast cancer in patients with low-volume breast? A single-center, retrospective Chinese clinical study.

It is controversial as to whether soft tissue reinforcement mesh should be used for immediate prosthetic breast reconstruction after nipple-sparing mastectomy for low-volume breast early breast cancer (LVBEBC) in Chinese adult women. We collected data on 89 patients with LVBEBC who underwent such a surgery and divided them into two groups: 39 patients in the totally subpectoral prosthesis-only breast reconstruction group (simple group) and 50 patients in the prosthesis-combined titanium-coated polypropylene mesh (TCPM) group (or the so-called "dual plane" or "mesh-assisted partially subpectoral breast reconstruction group") (combined group). The results demonstrated no difference in operative time, intraoperative bleeding, and postoperative complications between the two groups; however, total drainage volume and extubation time were less and shorter, respectively, in the combined group. The median follow-up time was 18.6 months without local recurrence or distant metastasis in both groups. At 24 months after surgery, the excellent and good rates of breast reconstruction were higher in the combined group. However, patients' BMI, breast morphology, and breast volume of 300 mL or more had an effect on the shape of the reconstructed breast; in addition, in patients with higher BMI, conical breast morphology, and breast volume over 300 mL, the shape of the breast was more perfect with the prosthesis combined with TCPM reconstruction.Trial registration: This retrospective study was "retrospectively registered" in the Sixth Affiliated Hospital of South China University of Technology of China on March 15, 2022 (No. 2022018) and in the National Medical Research Registry filing system of China ( https://www.medicalresearch.org.cn ) (No. MR-44-22-003618).

Alleviative effects of α-lipoic acid on muscle atrophy via the modulation of TNF-α/JNK and PI3K/AKT pathways in high-fat diet and streptozotocin-induced type 2 diabetic rats.

Diabetes mellitus (DM) is often accompanied by clinical complications such as sarcopenia. Previous studies have indicated that oxidative stress and insulin resistance (IR) are highly associated with the pathogenesis of diabetic myopathy. α-lipoic acid (ALA), a potent biological antioxidant, exists abundantly in a variety of plants and vegetables. This study aimed to investigate the ameliorative effect of ALA on muscle atrophy in type 2 diabetic rats induced by high-fat diet feeding (HFD) plus streptozotocin (STZ) injection. The HFD/STZ-induced diabetic rats were orally administered 50, 100, or 200 mg/kg body weight ALA once a day for 13 weeks. The results showed that ALA at the tested concentrations significantly increased the soleus muscle mass and muscle fibers in diabetic rats. Proinflammatory cytokines, such as tumor necrosis factor (TNF)-α, were found to decrease in both the serum and muscle of ALA-treated diabetic rats. ALA significantly reduced the protein-expression levels of phosphorylated c-Jun N-terminal kinase (pJNK)/JNK, forkhead box O3 (FOXO3), and muscle ring-finger protein-1 (Murf1); whereas, it enhanced the protein-expression levels of phosphoinositide 3-kinase (PI3K), phosphorylated protein kinase B (pAKT)/AKT, myogenin determination gene D (MyoD), the mechanistic target of rapamycin (mTOR), and myosin heavy chain (MyHC) in the soleus muscle of diabetic rats. The results from this study suggested that ALA treatment may preserve soleus muscle mass, alleviate muscle atrophy by suppressing the TNF-α/JNK pathway, and ameliorate the PI3K/AKT pathway in HFD/STZ-induced type 2 diabetic rats.

Robust Face Alignment via Inherent Relation Learning and Uncertainty Estimation.

Human tends to locate the facial landmarks with heavy occlusion by their relative position to the easily identified landmarks. The clue is defined as the landmark inherent relation while it is ignored by most existing methods. In this paper, we present Dynamic Sparse Local Patch Transformer (DSLPT), a novel face alignment framework for the inherent relation learning and uncertainty estimation. Unlike most existing methods that regress facial landmarks directly from global features, the DSLPT first generates a rough representation of each landmark from a local patch cropped from the feature map and then adaptively aggregates them by a case dependent inherent relation. Finally, the DSLPT predicts the coordinate and uncertainty of each landmark by regressing their probability distribution from the output features. Moreover, we introduce a coarse-to-fine framework to incorporate with DSLPT for an improved result. In the framework, the position and size of each patch are determined by the probability distribution of the corresponding landmark predicted in the previous stage. The dynamic patches will ensure a fine-grained landmark representation for inherent relation learning so that a rough prediction result can gradually converge to the target facial landmarks. We integrate the coarse-to-fine model into an end-to-end training pipeline and carry out experiments on the mainstream benchmarks. The results demonstrate that the DSLPT achieves state-of-the-art performance with much less computational complexity. The codes and models are available at https://github.com/Jiahao-UTS/DSLPT.

Characterizing Macrophages Diversity in COVID-19 Patients Using Deep Learning.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent responsible for coronavirus disease 2019 (COVID-19), has affected the lives of billions and killed millions of infected people. This virus has been demonstrated to have different outcomes among individuals, with some of them presenting a mild infection, while others present severe symptoms or even death. The identification of the molecular states related to the severity of a COVID-19 infection has become of the utmost importance to understanding the differences in critical immune response. In this study, we computationally processed a set of publicly available single-cell RNA-Seq (scRNA-Seq) data of 12 Bronchoalveolar Lavage Fluid (BALF) samples diagnosed as having a mild, severe, or no infection, and generated a high-quality dataset that consists of 63,734 cells, each with 23,916 genes. We extended the cell-type and sub-type composition identification and our analysis showed significant differences in cell-type composition in mild and severe groups compared to the normal. Importantly, inflammatory responses were dramatically elevated in the severe group, which was evidenced by the significant increase in macrophages, from 10.56% in the normal group to 20.97% in the mild group and 34.15% in the severe group. As an indicator of immune defense, populations of T cells accounted for 24.76% in the mild group and decreased to 7.35% in the severe group. To verify these findings, we developed several artificial neural networks (ANNs) and graph convolutional neural network (GCNN) models. We showed that the GCNN models reach a prediction accuracy of the infection of 91.16% using data from subtypes of macrophages. Overall, our study indicates significant differences in the gene expression profiles of inflammatory response and immune cells of severely infected patients.

Formation of Para-H2O by Vacuum-UV Photolysis of O2 in Solid Hydrogen: Implication for Astrochemistry.

The observation that the ortho to para ratio (OPR) of interstellar H2O is smaller than 3 is an important yet unresolved subject in astronomy. We irradiated O2 embedded in solid H2 at 3 K with vacuum-ultraviolet (VUV) light and observed IR lines associated with para-H2O (denoted as pH2O) and nonrotating H2O-(oH2)n (where oH2 denotes ortho-H2) but no lines associated with ortho-H2O (denoted as oH2O). After maintaining the matrix in darkness for ∼30 h, the amount of pH2O decreased, accompanied by an increase in H2O-(oH2)n via diffusion of oH2. After that, the continuous nuclear-spin conversion from oH2 to para-H2 (denoted as pH2) in solid H2 over time resulted in the conversion of nonrotating H2O-(oH2)n to rotating pH2O in solid pH2. The observation of the formation and conversion of pH2O in our experiment suggests a plausible route in which VUV irradiation of O2 and H2 adsorbed on grain surfaces might be responsible for the smaller OPR of interstellar H2O.

Understanding the hydrolysis mechanism on segments and aggregate structures: Corrosion-tailored poly (lactic acid) deriving copolymers with δ-valerolactone.

Poly (L-lactic acid) (PLLA) based copolymers modified with δ-valerolactone (DVL) through random copolymerization (PVLA-R) and block copolymerization (PVLA-B) with various DVL content were prepared to investigate their degradation regulation and mechanism. Chemical structure, thermal properties, hydrophilicity, crystallization as well as the crystal defects of the obtained copolymers were respectively confirmed. Degradation regulation of both PVLA-R and PVLA-B, such molecular weight and pH value changes of PLLA based copolymers were investigated via vitro degradation method. In order to further explore the degradation principle of the two copolymers, their degradation residues at different stages were systematically studied. The addition and increasing content of DVL disturbs the regularity of original PLLA molecular structure, resulting in accelerating degradation of copolymers. Compared with amorphous region, the crystalline region of both two copolymers has better corrosion resistance, which could be confirmed by increased melting point and crystallinity of both PVLA-R and PVLA-B degradation residues. PVLA-B copolymers show relatively superior degradation resistance mainly due to their higher molecular weight, crystallinity and hydrophobic index than PVLA-R copolymers.

Simultaneous vessel segmentation and unenhanced prediction using self-supervised dual-task learning in 3D CTA (SVSUP).

BACKGROUND AND OBJECTIVE: The vessel segmentation in CT angiography (CTA) provides an important basis for automatic diagnosis and hemodynamics analysis. Virtual unenhanced (VU) CT images obtained by dual-energy CT can assist clinical diagnosis and reduce radiation dose by obviating true unenhanced imaging (UECT). However, accurate segmentation of all vessels in the head-neck CTA (HNCTA) remains a challenge, and VU images are currently not available from conventional single-energy CT imaging. METHODS: In this paper, we proposed a self-supervised dual-task deep learning strategy to fully automatically segment all vessels and predict unenhanced CT images from single-energy HNCTA based on a developed iterative residual-sharing scheme. The underlying idea was to use the correlation between the two tasks to improve task performance while avoiding manual annotation for model training. RESULTS: The feasibility of the strategy was verified using the data of 24 patients. For vessel segmentation task, the proposed model achieves a significantly higher average Dice coefficient (84.83%, P-values 10-3 in paired t-test) than the state-of-the-art segmentation model, vanilla VNet (78.94%), and several popular 3D vessel segmentation models, including Hessian-matrix based filter (62.59%), optically-oriented flux (66.33%), spherical flux model (66.91%), and deep vessel net (66.47%). For the unenhanced prediction task, the average ROI-based error compared to the UECT in the artery tissue is 6.1±4.5 HU, similar to previously reported 6.4±5.1 HU for VU reconstruction. CONCLUSIONS: Results show that the proposed dual-task framework can effectively improve the accuracy of vessel segmentation in HNCTA, and it is feasible to predict the unenhanced image from single-energy CTA, providing a potential new approach for radiation dose saving. Moreover, to our best knowledge, this is the first reported annotation-free deep learning-based full-image vessel segmentation for HNCTA.

Single-cell gene fusion detection by scFusion.

Gene fusions can play important roles in tumor initiation and progression. While fusion detection so far has been from bulk samples, full-length single-cell RNA sequencing (scRNA-seq) offers the possibility of detecting gene fusions at the single-cell level. However, scRNA-seq data have a high noise level and contain various technical artifacts that can lead to spurious fusion discoveries. Here, we present a computational tool, scFusion, for gene fusion detection based on scRNA-seq. We evaluate the performance of scFusion using simulated and five real scRNA-seq datasets and find that scFusion can efficiently and sensitively detect fusions with a low false discovery rate. In a T cell dataset, scFusion detects the invariant TCR gene recombinations in mucosal-associated invariant T cells that many methods developed for bulk data fail to detect; in a multiple myeloma dataset, scFusion detects the known recurrent fusion IgH-WHSC1, which is associated with overexpression of the WHSC1 oncogene. Our results demonstrate that scFusion can be used to investigate cellular heterogeneity of gene fusions and their transcriptional impact at the single-cell level.

Exploring the relationship between perceived social support and college students' autonomous fitness behavior: Chain mediating effect test.

Objective: This study aims to explore the effect of perceived social support on college students' autonomous fitness behavior, and the mediating role of mental toughness and exercise self-efficacy. Methodology: A survey participated by 985 college Students (average age, 19.55) was conducted by applying the following scales: The Perceived Social Support Scale, the Adolescent Self-Government Behavior Scale, the Mental Toughness Scale, and the Exercise Self-efficacy Scale (ESES). Results: (1) Perceived social support can directly and positively predict autonomous fitness behavior, mental toughness, and exercise self-efficacy; mental toughness can directly and positively predict exercise self-efficacy. Likewise, perceived social support, mental toughness, and exercise self-efficacy can positively predict autonomous fitness behavior. (2) The indirect effect of the path with mental toughness as the mediating variable is 0.078, the indirect effect of the path with exercise self-efficacy as the mediating variable is 0.122, and the indirect effect of the path with mental toughness and exercise self-efficacy as the mediating variable is 0.082. (3) The total of all indirect effects is 0.282, and the effects of the three indirect pathways account for 18.25, 28.62, and 19.37% of the total, respectively. Conclusion: The perceived social support can indirectly predict college students' autonomous fitness behavior through the independent mediating effect of mental toughness and self-efficacy, as well as the chain mediating effect of the two. The claim that mental toughness and exercise self-efficacy perform a chain-mediate role in the positive effect brought by perceived social support on autonomous fitness behavior has been supported. This study revealed the relationship and mechanism between perceived social support and college students' autonomous fitness behavior and further improved the research on the impact of perceived social support on college students' autonomous fitness behavior.

Formation and IR spectrum of monobridged Si2H4 isolated in solid argon.

The infrared (IR) spectrum of monobridged Si2H4 (denoted as mbr-Si2H4) isolated in solid Ar was recorded, and a set of lines (in the major matrix site) observed at 858.3 cm-1, 971.5 cm-1, 999.2 cm-1, 1572.7 cm-1, 2017.7 cm-1, 2150.4 cm-1, and 2158.4 cm-1 were characterized. The species was produced by the electron bombardment of an Ar matrix sample containing a small proportion of SiH4 during matrix deposition. Upon photolysis of the matrix samples using 365 nm and 160 nm light, the content of mbr-Si2H4 increased. The band positions, relative intensity ratios, and D-isotopic shift ratios of the observed IR features are generally in good agreement with those predicted by the B3LYP/aug-cc-pVTZ method. In addition, the photochemistry of the observed products was discussed.

A self-supervised strategy for fully automatic segmentation of renal dynamic contrast-enhanced magnetic resonance images.

PURPOSE: An automated accurate segmentation for dynamic contrast-enhanced magnetic resonance (DCE-MR) image sequences is essential for quantification of renal function. A self-supervised strategy is proposed for fully automatic segmentation of the renal DCE-MR images without using manually labeled data. METHODS: The proposed strategy employed both temporal and spatial information of the DCE-MR image sequences. First, the kidney area, the seed regions of the cortex, the medulla, and the pelvis were automatically detected in the spatial domain. Subsequently, all the pixels in the kidney were automatically labeled as the cortex, the medulla, or the pelvis based on their time-intensity signal and spatial position using a supervised classifier. The feasibility of the proposed strategy was verified on a dataset of renal DCE-MR images of 14 subjects without history of kidney diseases. Furthermore, the self-supervised strategy and the commonly used traditional unsupervised method were quantitatively compared with a reference manual segmentation by an experienced radiologist, using similarity indexes. RESULTS: The average Dice coefficient (ADC) for the segmentations of the proposed self-supervised method is 0.92 using a ransom walker model as the classifier or 0.86 using a K-nearest neighbor model as the classifier. The ADC of the Kmeans-based unsupervised methods with three and six clusters were 0.65 and 0.79, respectively. The Dice coefficients of the self-supervised method were remarkably higher than that of the unsupervised method (one-tailed paired-sample t-test, P-values <10-3 ). CONCLUSIONS: The results indicate that the proposed self-supervised approach yields a satisfactory similarity with the reference manual segmentation. Compared with the traditional unsupervised clustering method, the new strategy does not require manual intervention during the segmentation process and achieves better results for the segmentation of renal DCE-MR images.

Robust and Unobtrusive Display-to-Camera Communications via Blue Channel Embedding.

Due to the rapid advancement in processing power and camera quality of mobile devices, research on the display-to-camera (D2C) communication channel has recently received increasing attention. Unlike the traditional QR Code, the unobtrusive D2C communication scheme normally serves both the human eyes and the mobile camera in commercial advertisements. Thus, attention should be paid to both unobtrusiveness and reliability of the design of a D2C communication scheme. In this paper, 2D barcodes with unobtrusive embedding in the blue channel are proposed in image and video formats to yield the robust and unobtrusive (RU) code and video-based RU (vRU) code, respectively. The proposed RU code is featured with a modulation scheme in blue channel that leverages several important properties of the human visual system; such as insensitivity toward the yellow-blue chrominance component, the proximity principle, and the oblique effect. Both RU code and vRU code employ a low-density-parity-check code for intra-frame channel coding. In addition, vRU code adopts an erasure-correcting Reed-Solomon code for inter-frame channel coding. Under a high perceptual quality constraint (multiscale structural similarity (MS-SSIM) ≈ 0.95), RU code achieves a demodulation bit error probability of 3.84%, which is an order of magnitude smaller than that of the existing picture-embedding 2D barcodes. Meanwhile, under a similar perceptual quality requirement (MS-SSIM ≈ 0.95 for each video frame), the goodput of vRU code is reported to be as high as 34.33 kbps under practical settings, e.g., a display frame rate of 30 fps and a capture frame rate of 42 fps.