Score-based generative model-assisted information compensation for high-quality limited-view reconstruction in photoacoustic tomography.

Photoacoustic tomography (PAT) regularly operates in limited-view cases owing to data acquisition limitations. The results using traditional methods in limited-view PAT exhibit distortions and numerous artifacts. Here, a novel limited-view PAT reconstruction strategy that combines model-based iteration with score-based generative model was proposed. By incrementally adding noise to the training samples, prior knowledge can be learned from the complex probability distribution. The acquired prior is then utilized as constraint in model-based iteration. The information of missing views can be gradually compensated by cyclic iteration to achieve high-quality reconstruction. The performance of the proposed method was evaluated with the circular phantom and in vivo experimental data. Experimental results demonstrate the outstanding effectiveness of the proposed method in limited-view cases. Notably, the proposed method exhibits excellent performance in limited-view case of 70° compared with traditional method. It achieves a remarkable improvement of 203% in PSNR and 48% in SSIM for the circular phantom experimental data, and an enhancement of 81% in PSNR and 65% in SSIM for in vivo experimental data, respectively. The proposed method has capability of reconstructing PAT images in extremely limited-view cases, which will further expand the application in clinical scenarios.

Unsupervised disentanglement strategy for mitigating artifact in photoacoustic tomography under extremely sparse view.

Traditional methods under sparse view for reconstruction of photoacoustic tomography (PAT) often result in significant artifacts. Here, a novel image to image transformation method based on unsupervised learning artifact disentanglement network (ADN), named PAT-ADN, was proposed to address the issue. This network is equipped with specialized encoders and decoders that are responsible for encoding and decoding the artifacts and content components of unpaired images, respectively. The performance of the proposed PAT-ADN was evaluated using circular phantom data and the animal in vivo experimental data. The results demonstrate that PAT-ADN exhibits excellent performance in effectively removing artifacts. In particular, under extremely sparse view (e.g., 16 projections), structural similarity index and peak signal-to-noise ratio are improved by ∼188 % and ∼85 % in in vivo experimental data using the proposed method compared to traditional reconstruction methods. PAT-ADN improves the imaging performance of PAT, opening up possibilities for its application in multiple domains.

High-resolution iterative reconstruction at extremely low sampling rate for Fourier single-pixel imaging via diffusion model.

The trade-off between imaging efficiency and imaging quality has always been encountered by Fourier single-pixel imaging (FSPI). To achieve high-resolution imaging, the increase in the number of measurements is necessitated, resulting in a reduction of imaging efficiency. Here, a novel high-quality reconstruction method for FSPI imaging via diffusion model was proposed. A score-based diffusion model is designed to learn prior information of the data distribution. The real-sampled low-frequency Fourier spectrum of the target is employed as a consistency term to iteratively constrain the model in conjunction with the learned prior information, achieving high-resolution reconstruction at extremely low sampling rates. The performance of the proposed method is evaluated by simulations and experiments. The results show that the proposed method has achieved superior quality compared with the traditional FSPI method and the U-Net method. Especially at the extremely low sampling rate (e.g., 1%), an approximately 241% improvement in edge intensity-based score was achieved by the proposed method for the coin experiment, compared with the traditional FSPI method. The method has the potential to achieve high-resolution imaging without compromising imaging speed, which will further expanding the application scope of FSPI in practical scenarios.

Accelerated model-based iterative reconstruction strategy for sparse-view photoacoustic tomography aided by multi-channel autoencoder priors.

Photoacoustic tomography (PAT) commonly works in sparse view due to data acquisition limitations. However, reconstruction suffers from serious deterioration (e.g., severe artifacts) using traditional algorithms under sparse view. Here, a novel accelerated model-based iterative reconstruction strategy for sparse-view PAT aided by multi-channel autoencoder priors was proposed. A multi-channel denoising autoencoder network was designed to learn prior information, which provides constraints for model-based iterative reconstruction. This integration accelerates the iteration process, leading to optimal reconstruction outcomes. The performance of the proposed method was evaluated using blood vessel simulation data and experimental data. The results show that the proposed method can achieve superior sparse-view reconstruction with a significant acceleration of iteration. Notably, the proposed method exhibits excellent performance under extremely sparse condition (e.g., 32 projections) compared with the U-Net method, with an improvement of 48% in PSNR and 12% in SSIM for in vivo experimental data.

Sparse-view reconstruction for photoacoustic tomography combining diffusion model with model-based iteration.

As a non-invasive hybrid biomedical imaging technology, photoacoustic tomography combines high contrast of optical imaging and high penetration of acoustic imaging. However, the conventional standard reconstruction under sparse view could result in low-quality image in photoacoustic tomography. Here, a novel model-based sparse reconstruction method for photoacoustic tomography via diffusion model was proposed. A score-based diffusion model is designed for learning the prior information of the data distribution. The learned prior information is utilized as a constraint for the data consistency term of an optimization problem based on the least-square method in the model-based iterative reconstruction, aiming to achieve the optimal solution. Blood vessels simulation data and the animal in vivo experimental data were used to evaluate the performance of the proposed method. The results demonstrate that the proposed method achieves higher-quality sparse reconstruction compared with conventional reconstruction methods and U-Net. In particular, under the extreme sparse projection (e.g., 32 projections), the proposed method achieves an improvement of ∼ 260 % in structural similarity and ∼ 30 % in peak signal-to-noise ratio for in vivo data, compared with the conventional delay-and-sum method. This method has the potential to reduce the acquisition time and cost of photoacoustic tomography, which will further expand the application range.

High-speed real 3D scene acquisition and 3D holographic reconstruction system based on ultrafast optical axial scanning.

The lack of three-dimensional (3D) content is one of the challenges that have been faced by holographic 3D display. Here, we proposed a real 3D scene acquisition and 3D holographic reconstruction system based on ultrafast optical axial scanning. An electrically tunable lens (ETL) was used for high-speed focus shift (up to 2.5 ms). A CCD camera was synchronized with the ETL to acquire multi-focused image sequence of real scene. Then, the focusing area of each multi-focused image was extracted by using Tenengrad operator, and the 3D image were obtained. Finally, 3D holographic reconstruction visible to the naked eye can be achieved by the layer-based diffraction algorithm. The feasibility and effectiveness of the proposed method have been demonstrated by simulation and experiment, and the experimental results agree well with the simulation results. This method will further expand the application of holographic 3D display in the field of education, advertising, entertainment, and other fields.

rhCNB Improves Cyclophosphamide-Induced Immunodeficiency in BALB/c Mice.

Background: This study aims to explore the immunomodulatory effect of rhCNB on mice with cyclophosphamide (CTX)-induced immunodeficiency through TLR4/MAPK pathway. Methods: BALB/c mice were randomly divided into three groups: a negative control group, an immunosuppression model group, and a rhCNB treatment group. Tail vein injection of cyclophosphamide (40 mg/kg) was used to establish a mouse immunosuppression model. Intraperitoneal injection of rhCNB (20 mg/kg) was administered to the treatment group, whereas equal quantities of normal saline were given to the control group and model group. Perform peripheral blood routine of CD4, CD8, and CD19 lymphocyte subsets and peripheral blood Th1/Th2 cell subsets 24 hours after the last administration. RT-PCR was used to detect mRNA levels of TLR4, P38, JNK, T-bet, and GATA3, the spleen immune organ index was measured, and the histopathological status of the spleen and thymus was observed. Results: The results showed that compared with the control group, WBC, PLT, LYM, NEU, immune organ index, CD4+/CD8+ and CD19+ subgroup ratio, and peripheral blood Th1/Th2 cell subgroups decreased in the model group. The mRNA levels of TLR4, P38, JNK, T-bet, and GATA3 decreased compared with the model group, while they increased in the treatment group. Conclusions: rhCNB has an immunomodulatory effect by regulating the expression of Th1/Th2 cytokine balance through the TLR4/MAPK signaling pathway and promoting the differentiation and proliferation of lymphocytes, thereby improving the immune function.

SIK2 Improving Mitochondrial Autophagy Restriction Induced by Cerebral Ischemia-Reperfusion in Rats.

Previous studies have shown that Salt-induced kinase-2(SIK2) is involved in the regulation of various energy-metabolism-related reactions, and it also can regulate angiogenesis after cerebral ischemia-reperfusion. However, it is unclear whether SIK2 can regulate energy metabolism in cerebral ischemia-reperfusion injury. As mitochondria plays an important role in energy metabolism, whether SIK2 regulates energy metabolism through affecting mitochondrial changes is also worth to be explored. In this study, rats were treated with adeno-associated virus-SIK2-Green fluorescent protein (AAV-SIK2-GFP) for the overexpression of SIK2 before middle cerebral artery occlusion (MCAO). We found that SIK2 overexpression could alleviate the neuronal damage, reduce the area of cerebral infarction, and increase the adenosine triphosphate (ATP) content, which could promote the expression of phosphorylated-mammalian target of rapamycin-1 (p-mTORC1), hypoxia-inducible factor-1α (HIF-1α), phosphatase and tensin homologue-induced putative kinase 1 (PINK1) and E3 ubiquitinligating enzyme (Parkin). Transmission electron microscopy revealed that SIK2 overexpression enhanced mitochondrial autophagy. It is concluded that SIK2 can ameliorate neuronal injury and promote the energy metabolism by regulating the mTOR pathway during cerebral ischemia-reperfusion, and this process is related to mitochondrial autophagy.

A T-cell-dependent antibody response (TDAR) method in BALB/c mice based on a cytometric bead array.

Most current methods to assess T-cell-dependent antibody responses (TDAR) are semi-quantitative and based on measures of antibody titer generated against a standard antigen like keyhole limpet hemocyanin (KLH). The precision, sensitivity, and convenience of TDAR assays might be improved by applying rapid, sensitive, specific cytometric bead assays (CBA). In the study here, KLH antigen was covalently coupled onto the surface of cytometric beads using immune microsphere technology, and IgM antibody capture spheres were prepared for use in pretreatment processing of samples. The working parameters associated with this novel TDAR-CBA system were optimized in orthogonal experiments. The optimal concentration of the KLH coating solution in this system was 160 µg/ml, that of the anti-KLH IgG capture spheres 6.0 × 105/ml, and the optimal dilution of fluorescein isothiocyanate (FITC)-conjugated Affini-Pure Goat Anti-Mouse IgG (H + L) was 60 µg/ml. Repeated tests indicated that this approach yielded good linearity (r2 = 0.9937) method, with a within-run precision of 3.1-4.9%, and a between-run precision of 4.4-4.9%. This new approach had a limit of detection of 113.43 ng/ml (linear range = 390.63-50 000), and an interference rate of just 0.04-3.51%. Based on these findings, it seems that a new mouse TDAR assay based on CBA can be developed that would appear to be more sensitive, accurate, and precise than the current TDAR assay approaches based on traditional ELISA.

A Novel Algorithm With Paired Predictive Indexes to Stratify the Risk Levels of Neonates With Invasive Bacterial Infections: A Multicenter Cohort Study.

BACKGROUND: Our aim was to develop a predictive model comprising clinical and laboratory parameters for early identification of full-term neonates with different risks of invasive bacterial infections (IBIs). METHODS: We conducted a retrospective study including 1053 neonates presenting in 9 tertiary hospitals in China from January 2010 to August 2019. An algorithm with paired predictive indexes (PPIs) for risk stratification of neonatal IBIs was developed. Predictive performance was validated using k-fold cross-validation. RESULTS: Overall, 166 neonates were diagnosed with IBIs (15.8%). White blood cell count, C-reactive protein level, procalcitonin level, neutrophil percentage, age at admission, neurologic signs, and ill-appearances showed independent associations with IBIs from stepwise regression analysis and combined into 23 PPIs. Using 10-fold cross-validation, a combination of 7 PPIs with the highest predictive performance was picked out to construct an algorithm. Finally, 58.1% (612/1053) patients were classified as low-risk cases. The sensitivity and negative predictive value of the algorithm were 95.3% (95% confidence interval: 91.7-98.3) and 98.7% (95% confidence interval: 97.8-99.6), respectively. An online calculator based on this algorithm was developed for clinical use. CONCLUSIONS: The new algorithm constructed for this study was a valuable tool to screen neonates with suspected infection. It stratified risk levels of IBIs and had an excellent predictive performance.

Antibiotic resistance in neonates in China 2012-2019: A multicenter study.

BACKGROUND: To investigate antibiotic resistance of pathogens responsible for neonatal invasive bacterial infections (IBIs) in China. METHODS: Cross-sectional study of neonates with IBI evaluated in nine hospitals in China (January 2012-August 2019). Antibiotic resistance patterns of pathogens responsible for neonatal IBIs were analyzed. RESULTS: Of 3770 full-term neonates who were subjected to lumbar puncture and a blood culture, IBIs were diagnosed in 460 neonates (12.2%). Escherichia coli and Group B Streptococcus (GBS) were the leading pathogens, followed by Enterococcus spp, and Staphylococcus aureus. E. coli expressed high resistance to ampicillin (72.0%) and third-generation cephalosporins (cefotaxime, 34.8%; ceftriaxone, 38.1%). The prevalence of extended spectrum beta-lactamase (ESBL)-producing E. coli was 34.1%. The proportions of E. spp resistant to penicillin and ampicillin were 60% and 54.1%. All S. aureus showed resistance to ampicillin and penicillin. The resistance rate of S. aureus to methicillin was 50%. Although all GBS were susceptible to penicillin and ampicillin, the proportions of GBS resistant to erythromycin and clindamycin were 75.9% and 77.3%. Antibiotic susceptibility appeared to improve in 2019. Susceptibility of E. coli to ampicillin, cefotaxime, and ceftriaxone improved to 42.9%, 76.9%, and 71.4% in 2019, compared with 12.5%, 37.5%, and 50% in 2012. The prevalence of ESBL-producing E. coli declined to 20% in 2019, lower than 100% in 2012. Susceptibility of GBS to erythromycin and clindamycin improved from 0% in 2012 to 28.6% and 25% in 2019. CONCLUSIONS: The prevalence of antibiotic resistance is high in neonates in China, although there is a favorable declining trend in recent years.

A sequential guide to identify neonates with low bacterial meningitis risk: a multicenter study.

OBJECTIVE: To derive and validate a predictive algorithm integrating clinical and laboratory parameters to stratify a full-term neonate's risk level of having bacterial meningitis (BM). METHODS: A multicentered dataset was categorized into derivation (689 full-term neonates aged ≤28 days with a lumbar puncture [LP]) and external validation (383 neonates) datasets. A sequential algorithm with risk stratification for neonatal BM was constructed. RESULTS: In the derivation dataset, 102 neonates had BM (14.8%). Using stepwise regression analysis, fever, infection source absence, neurological manifestation, C-reactive protein (CRP), and procalcitonin were selected as optimal predictive sets for neonatal BM and introduced to a sequential algorithm. Based on the algorithm, 96.1% of BM cases (98 of 102) were identified, and 50.7% of the neonates (349 of 689) were classified as low risk. The algorithm's sensitivity and negative predictive value (NPV) in identifying neonates at low risk of BM were 96.2% (95% CI 91.7%-98.9%) and 98.9% (95% CI 97.6%-99.6%), respectively. In the validation dataset, sensitivity and NPV were 95.9% (95% CI 91.0%-100%) and 98.8% (95% CI 97.7%-100%). INTERPRETATION: The sequential algorithm can risk stratify neonates for BM with excellent predictive performance and prove helpful to clinicians in LP-related decision-making.

The Role of Ceria in a Hybrid Catalyst toward Alkaline Water Oxidation.

Ceria-based catalysts for the oxygen evolution reaction (OER) have received keen interest in recent years owing to their potential excellent cost performance. However, despite a flurry of research activities, the mechanism on how ceria activates those hybrid catalysts is still puzzling. Herein, by controllably modifying the oxidation state of Ce in ceria, it was revealed that creating Ce3+ species, which are redox-coupled to Ce4+ under OER conditions, could enhance the conductivity and optimize the OH* binding, leading to greatly improved OER activity of the catalysts. More importantly, the ceria-based hybrid catalysts also exhibited excellent long-term stability even when operating at a high current density of 50 mA cm-2 in the strong alkaline electrolyte of 6 m KOH for more than 50 h. This work unveils the underlying role of ceria in improving the activity/stability of ceria-based catalysts and opens the way to design and fabricate ceria-based electrocatalysts for water splitting.

NaBH4 induces a high ratio of Ni3+/Ni2+ boosting OER activity of the NiFe LDH electrocatalyst.

Electrochemical water splitting is a promising way to produce hydrogen gas, but the sluggish kinetics of the oxygen evolution reaction (OER) extremely restrict the overall conversion efficiency of water splitting. Transition metal based LDHs (TM LDHs) are one of the most effective non-noble metal OER catalysts and have attracted wide interest, especially the nickel-iron LDH (NiFe LDH). The high valence Ni3+ species with a large coordination number play a vital role in OER catalysis. Herein, we report on a surprising discovery that reaction between NiFe LDH and NaBH4 with multi-hydrides induces vacancy formation around Fe3+ and enrichment in Ni3+, crucially activating the OER performance. The ratio of Ni3+/Ni2+ is found to be closely tied to the OER performance, nicely accounting for the leading role of Ni3+ ions in octahedral sites in electrocatalysis. Significantly, the NaBH4 treated NiFe LDH directly on nickel foam (NF), denoted as NaBH4-NiFe LDH@NF exhibited an outstanding OER performance with an overpotential of only 310 mV at 100 mA cm-2, and a Tafel slope of 47 mV dec-1. For the series of TM LDHs we studied with different metal combinations, the high valence metal ion is found to be positively related to OER performance.

Hybrid hollow spheres of carbon@CoxNi1-xMoO4 as advanced electrodes for high-performance asymmetric supercapacitors.

Combining pseudocapacitive materials with conductive substrates is an effective approach to enhance the overall performance of electrodes for supercapacitors. Herein, NiMoO4 nanosheets were grown on the surface of porous carbon nanospheres (PCNS) that were derived from cyclodextrin, resulting in PCNS@NiMoO4 hollow nanospheres. Co was further doped into NiMoO4 which gave rise to a composite PCNS@CoxNi1-xMoO4. The capacitive performance of these materials was systematically examined. Compared with pure NiMoO4 and PCNS@NiMoO4, PCNS@Co0.21Ni0.79MoO4 showed the highest specific capacitance of 954 F g-1 at 1 A g-1 and an extraordinary rate performance of 92.8% retention at 40 A g-1, which are significantly higher than those of PCNS@NiMoO4 and pure NiMoO4. This enhancement was due to the fact that PCNS provides high electrical conductivity, the hollow structure enables excellent contact and facile penetration of the electrolyte into the active material, and Co doping further improves the electrical conductivity and provides extra redox reaction sites. By using PCNS@Co0.21Ni0.79MoO4 as the positive electrode and activated carbon (AC) as the negative electrode, an asymmetric supercapacitor was fabricated. Such a device delivered an energy density of 36.7 W h kg-1 at a power density of 346.4 W kg-1, and an outstanding cycling stability with 90.2% retention of its initial capacitance after 5000 cycles of charge and discharge.

Factors related to retinal haemorrhage in infants born at high risk.

PURPOSE: This study aims to determine risk factors for retinal haemorrhage (RH) in high-risk infants. METHODS: A total of 3123 cases with high-risk pregnancy and/or neonatal asphyxia 72 hr after delivery were enrolled into this study. Fundus examinations were performed on newborns utilizing a wide-angle imaging system (RetCam III). Retinal haemorrhage (RH) was classified into three grades. Maternal, obstetric and neonatal parameters from high-risk infants with RH were compared with parameters from infants without RH. RESULTS: Retinal haemorrhage (RH) was found in 550 (18%) of 3123 high-risk infants. Retinal haemorrhage (RH) was classified as grade I (39%), grade II (24%) and grade III (37%). Monocular RH occurred in 37% of cases, while the remaining cases were binocular. Moreover, six cases had vitreous haemorrhage. The following parameters correlated (p < 0.05) with RH in this study: delivery mode (χ2  = 469), gestational age (χ2  = 35), birth weight (χ2  = 18), asphyxia (χ2  = 73), scalp hematoma (χ2  = 55), maternal age (χ2  = 8.9), precipitate labour (χ2  = 120) and delivery times (χ2  = 6.1). Logistic regression analysis indicated that delivery mode and asphyxia were risk factors for RH in high-risk infants, with odds ratios of 0.827 and 2.5, respectively. Gender, intracranial haemorrhage and foetal distress were not correlated with RH in high-risk infants. CONCLUSION: The incidence of RH in high-risk infants was 18%, and delivery mode, and neonatal asphyxia were major risk factors for RH in high-risk infants.