Multi-omic analysis of mandibuloacral dysplasia type A patient iPSC-derived MSC senescence reveals miR-311 as a novel biomarker for MSC senescence.

Mandibuloacral dysplasia type A (MADA) is a rare genetic progeroid syndrome associated with lamin A/C (LMNA) mutations. Pathogenic mutations of LMNA result in nuclear structural abnormalities, mesenchymal tissue damage and progeria phenotypes. However, it remains elusive how LMNA mutations cause mesenchymal-derived cell senescence and disease development. Here, we established an in vitro senescence model using induced pluripotent stem cell-derived mesenchymal stem cells (iMSCs) from MADA patients with homozygous LMNA p.R527C mutation. When expanded to passage 13 in vitro, R527C iMSCs exhibited marked senescence and attenuation of stemness potential, accompanied by immunophenotypic changes. Transcriptome and proteome analysis revealed that cell cycle, DNA replication, cell adhesion and inflammation might play important roles in senescence. In-depth evaluation of changes in extracellular vesicle (EV) derived iMSCs during senescence revealed that R527C iMSC-EVs could promote surrounding cell senescence by carrying pro-senescence microRNAs (miRNAs), including a novel miRNA called miR-311, which can serve as a new indicator for detecting chronic and acute mesenchymal stem cell (MSC) senescence and play a role in promoting senescence. Overall, this study advanced our understanding of the impact of LMNA mutations on MSC senescence and provided novel insights into MADA therapy as well as the link between chronic inflammation and aging development.

Morphology-based deep learning enables accurate detection of senescence in mesenchymal stem cell cultures.

BACKGROUND: Cell senescence is a sign of aging and plays a significant role in the pathogenesis of age-related disorders. For cell therapy, senescence may compromise the quality and efficacy of cells, posing potential safety risks. Mesenchymal stem cells (MSCs) are currently undergoing extensive research for cell therapy, thus necessitating the development of effective methods to evaluate senescence. Senescent MSCs exhibit distinctive morphology that can be used for detection. However, morphological assessment during MSC production is often subjective and uncertain. New tools are required for the reliable evaluation of senescent single cells on a large scale in live imaging of MSCs. RESULTS: We have developed a successful morphology-based Cascade region-based convolution neural network (Cascade R-CNN) system for detecting senescent MSCs, which can automatically locate single cells of different sizes and shapes in multicellular images and assess their senescence state. Additionally, we tested the applicability of the Cascade R-CNN system for MSC senescence and examined the correlation between morphological changes with other senescence indicators. CONCLUSIONS: This deep learning has been applied for the first time to detect senescent MSCs, showing promising performance in both chronic and acute MSC senescence. The system can be a labor-saving and cost-effective option for screening MSC culture conditions and anti-aging drugs, as well as providing a powerful tool for non-invasive and real-time morphological image analysis integrated into cell production.

An aging-related immune landscape in the hematopoietic immune system.

BACKGROUND: Aging is a holistic change that has a major impact on the immune system, and immunosenescence contributes to the overall progression of aging. The bone marrow is the most important hematopoietic immune organ, while the spleen, as the most important extramedullary hematopoietic immune organ, maintains homeostasis of the human hematopoietic immune system (HIS) in cooperation with the bone marrow. However, the overall changes in the HIS during aging have not been described. Here, we describe a hematopoietic immune map of the spleen and bone marrow of young and old mice using single-cell sequencing and flow cytometry techniques. RESULTS: We observed extensive, complex changes in the HIS during aging. Compared with young mice, the immune cells of aged mice showed a marked tendency toward myeloid differentiation, with the neutrophil population accounting for a significant proportion of this response. In this change, hypoxia-inducible factor 1-alpha (Hif1α) was significantly overexpressed, and this enhanced the immune efficacy and inflammatory response of neutrophils. Our research revealed that during the aging process, hematopoietic stem cells undergo significant changes in function and composition, and their polymorphism and differentiation abilities are downregulated. Moreover, we found that the highly responsive CD62L + HSCs were obviously downregulated in aging, suggesting that they may play an important role in the aging process. CONCLUSIONS: Overall, aging extensively alters the cellular composition and function of the HIS. These findings could potentially give high-dimensional insights and enable more accurate functional and developmental analyses as well as immune monitoring in HIS aging.

The c-di-GMP Phosphodiesterase PipA (PA0285) Regulates Autoaggregation and Pf4 Bacteriophage Production in Pseudomonas aeruginosa PAO1.

In Pseudomonas aeruginosa PAO1, 41 genes encode proteins predicted to be involved in the production or degradation of c-di-GMP, a ubiquitous secondary messenger that regulates a variety of physiological behaviors closely related to biofilm and aggregate formation. Despite extensive effort, the entire picture of this important signaling network is still unclear, with one-third of these proteins remaining uncharacterized. Here, we show that the deletion of pipA, which produces a protein containing two PAS domains upstream of a GGDEF-EAL tandem, significantly increased the intracellular c-di-GMP level and promoted the formation of aggregates both on surfaces and in planktonic cultures. However, this regulatory effect was not contributed by either of the two classic pathways modulating biofilm formation, exopolysaccharide (EPS) overproduction or motility inhibition. Transcriptome sequencing (RNA-Seq) data revealed that the expression levels of 361 genes were significantly altered in a ΔpipA mutant strain compared to the wild type (WT), indicating the critical role of PipA in PAO1. The most remarkably downregulated genes were located on the Pf4 bacteriophage gene cluster, which corresponded to a 2-log reduction in the Pf4 phage production in the ΔpipA mutant. The sizes of aggregates in ΔpipA cultures were affected by exogenously added Pf4 phage in a concentration-dependent manner, suggesting the quantity of phage plays a part in regulating the formation of aggregates. Further analysis demonstrated that PipA is highly conserved across 83 P. aeruginosa strains. Our work therefore for the first time showed that a c-di-GMP phosphodiesterase can regulate bacteriophage production and provided new insights into the relationship between bacteriophage and bacterial aggregation. IMPORTANCE The c-di-GMP signaling pathways in P. aeruginosa are highly organized and well coordinated, with different diguanylate cyclases and phosphodiesterases playing distinct roles in a complex network. Understanding the function of each enzyme and the underlying regulatory mechanisms not only is crucial for revealing how bacteria decide the transition between motile and sessile lifestyles, but also greatly facilitates the development of new antibiofilm strategies. This work identified bacteriophage production as a novel phenotypic output controlled transcriptionally by a phosphodiesterase, PipA. Further analysis suggested that the quantity of phage may be important in regulating autoaggregation, as either a lack of phage or overproduction was associated with higher levels of aggregation. Our study therefore extended the scope of c-di-GMP-controlled phenotypes and discovered a potential signaling circuit that can be target for biofilm treatment.

Highly Stable Inorganic Lead Halide Perovskite toward Efficient Photovoltaics.

ConspectusOwing to the remarkable progress achieved over the past decade with research efforts from the perspectives of material synthesis, device configuration, and theoretical investigation, metal halide perovskites have emerged as a revolutionary class of light-absorbing semiconductors. The perovskite photovoltaic devices have demonstrated an impressive increase in power conversion efficiency. For single-junction perovskite solar cells, the value has risen from the initial one-digit maximum to the state-of-art record of 25.5%. Among various chemical and structural variations of perovskites, inorganic lead halides possess a more favorable operational stability and hold greater potential for perovskite/silicon tandem photovoltaics' top cells. At the initial stage of exploring all-inorganic perovskites for optoelectronic applications, many concepts, technical routes, and modification strategies were directly adopted from research on the more-developed field of organic-inorganic hybrid perovskite (OIHP). However, as understandings on inorganic perovskite deepen with research experience gained from both experimental and theoretical progression, it has been found that the difference between the asymmetric, volatile organic cations and the spherical, stable inorganic cations can lead to drastic changes on overall material properties and the subsequent device performances. In detail, the disparities reflect the crystalline and phase profiles of the material, the fabrication and passivation rationales of perovskite thin films, and the photophysics in the assembled optoelectronic devices. Therefore, the discussions of all-inorganic perovskites have their own exclusivity and are worthy of a specialized scrutinization.Here in this Account, the latest progress on the stabilization of inorganic lead halide perovskites for efficient photovoltaic applications is highlighted. A library of chemical compositions will be discussed with a focus on notable works about CsPbI3, which possesses a more favorable bandgap as a tandem to commercialized silicon solar cells. To underscore the influence of the crystal phase on the stability of inorganic perovskites, fundamental investigations regarding the chemical and physical properties, including experimental and theoretical studies, will be summarized as a means of phase control. The stability of inorganic lead halide perovskites can also be improved by the strategic introduction of external components to the light-absorbing layer, such as the incorporation of inorganic halides, organic cations, OIHPs with low dimension, etc. These strategies can synergistically improve the stability and efficiency of the fabricated devices from the perspectives of compositional tuning, dimensional engineering, surface termination, and low-dimension capping. On the basis of a careful examination and an analysis of works achieved in these categories from our group and others, we will then discuss some promising approaches toward achieving more stable and efficient photovoltaics using inorganic lead halide perovskites.

High-intensity focused ultrasound (HIFU) ablation versus surgical interventions for the treatment of symptomatic uterine fibroids: a meta-analysis.

OBJECTIVES: To compare the treatment success and safety of ultrasound- and MR-guided high-intensity focused ultrasound (HIFU) with surgery for treating symptomatic uterine fibroids. METHODS: We searched studies comparing HIFU with surgery for fibroids in different databases from January 2000 to July 2020. The mean difference (MD) or relative risk (RR) with 95% confidence interval (CI) for different outcome parameters was synthesized. RESULTS: We included 10 studies involving 4450 women. Compared with the surgery group, the decrease in uterine fibroid severity score at 6- and 12-month follow-up was higher in the HIFU group (MD - 4.16, 95% CI - 7.39 to - 0.94, and MD - 2.44, 95% CI - 3.67 to - 1.20, p < 0.05). The increase in quality-of-life (QoL) score at 6- and 12-month follow-up was higher in the HIFU group (MD 2.13, 95% CI 0.86 to 3.14, and MD 2.34, 95% CI 0.82 to 3.85, p < 0.05). The duration of hospital stay and the time to return to work was shorter in the HIFU group (MD - 3.41 days, 95% CI - 5.11 to - 1.70, and MD - 11.61 days, 95% CI - 19.73 to - 3.50, p < 0.05). The incidence of significant complications was lower in the HIFU group (RR 0.33, 95% CI 0.13 to 0.81, p < 0.05). The differences in the outcomes of adverse events, symptom recurrence, re-intervention, and pregnancy were not statistically significant (p > 0.05). CONCLUSIONS: HIFU is superior to surgery in terms of symptomatic relief, improvement in QoL, recovery, and significant complications. However, HIFU showed comparable effects to surgery regarding the incidence of adverse events, symptom recurrence, re-intervention, and pregnancy. KEY POINTS: • HIFU ablation is superior to surgery in terms of symptomatic relief, improvement in QoL, recovery, and significant complications. • HIFU has comparable effects to surgery in terms of symptom recurrence rate, re-intervention rate, and pregnancy rate, indicating that HIFU is a promising non-invasive therapy that seems not to raise the risk of recurrence and re-intervention or deteriorate fertility compared to surgical approaches in women with fibroids. • There is still a lack of good-quality comparative data and further randomized studies are necessary to provide sufficient and reliable data, especially on re-intervention rate and pregnancy outcome.

Electrochemical Reactors for Continuous Decentralized H2 O2 Production.

The global utilization of H2 O2 is currently around 4 million tons per year and is expected to continue to increase in the future. H2 O2 is mainly produced by the anthraquinone process, which involves multiple steps in terms of alkylanthraquinone hydrogenation/oxidation in organic solvents and liquid-liquid extraction of H2 O2 . The energy-intensive and environmentally unfriendly anthraquinone process does not meet the requirements of sustainable and low-carbon development. The electrocatalytic two-electron (2 e- ) oxygen reduction reaction (ORR) driven by renewable energy (e.g. solar and wind power) offers a more economical, low-carbon, and greener route to produce H2 O2 . However, continuous and decentralized H2 O2 electrosynthesis still poses many challenges. This Minireview first summarizes the development of devices for H2 O2 electrosynthesis, and then introduces each component, the assembly process, and some optimization strategies.

Alzheimer's disease diagnosis framework from incomplete multimodal data using convolutional neural networks.

Alzheimer's disease (AD) is a severe irreversible neurodegenerative disease that has great sufferings on patients and eventually leads to death. Early detection of AD and its prodromal stage, mild cognitive impairment (MCI) which can be either stable (sMCI) or progressive (pMCI), is highly desirable for effective treatment planning and tailoring therapy. Recent studies recommended using multimodal data fusion of genetic (single nucleotide polymorphisms, SNPs) and neuroimaging data (magnetic resonance imaging (MRI) and positron emission tomography (PET)) to discriminate AD/MCI from normal control (NC) subjects. However, missing multimodal data in the cohort under study is inevitable. In addition, data heterogeneity between phenotypes and genotypes biomarkers makes learning capability of the models more challenging. Also, the current studies mainly focus on identifying brain disease classification and ignoring the regression task. Furthermore, they utilize multistage for predicting the brain disease progression. To address these issues, we propose a novel multimodal neuroimaging and genetic data fusion for joint classification and clinical score regression tasks using the maximum number of available samples in one unified framework using convolutional neural network (CNN). Specifically, we initially perform a technique based on linear interpolation to fill the missing features for each incomplete sample. Then, we learn the neuroimaging features from MRI, PET, and SNPs using CNN to alleviate the heterogeneity among genotype and phenotype data. Meanwhile, the high learned features from each modality are combined for jointly identifying brain diseases and predicting clinical scores. To validate the performance of the proposed method, we test our method on 805 subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Also, we verify the similarity between the synthetic and real data using statistical analysis. Moreover, the experimental results demonstrate that the proposed method can yield better performance in both classification and regression tasks. Specifically, our proposed method achieves accuracy of 98.22%, 93.11%, and 97.35% for NC vs. AD, NC vs. sMCI, and NC vs. pMCI, respectively. On the other hand, our method attains the lowest root mean square error and the highest correlation coefficient for different clinical scores regression tasks compared with the state-of-the-art methods.

Image-guided thermal ablation in the management of symptomatic adenomyosis: a systematic review and meta-analysis.

OBJECTIVE: To evaluate the clinical effects of image-guided thermal ablation for the treatment of symptomatic adenomyosis (AD). DATA SOURCES: We searched PubMed, Web of Science, Cochrane Library, EMBASE, ClinicalTrials.gov and Google Scholar for literature from January 2000 to September 2020. METHODS OF STUDY SELECTION: We included all studies reporting clinical outcomes of image-guided thermal ablation for AD, involving high-intensity focused ultrasound (HIFU), percutaneous microwave ablation (PMWA) and radiofrequency ablation (RFA). Two independent researchers performed study selection according to the screening criteria. RESULTS: A total of 38 studies representing 15,908 women were included. Compared with those at baseline, the visual analog scale scores, the symptom severity scores and the menorrhagia severity scores decreased significantly after these thermal ablation therapies. The mean ablation time was 92.18 min, 24.15 min and 31.93 min during HIFU, PMWA and RFA, respectively. The non-perfused volume ratio of AD was 68.3% for HIFU, 82.5% for PMWA and 79.2% for RFA. The reduction rates of uterine volume were 33.6% (HIFU), 46.8% (PMWA) and 44.0% (RFA). The reduction rates of AD volume were 45.1% (HIFU), 74.9% (PMWA) and 61.3% (RFA). The relief rates of dysmenorrhea were 84.2% (HIFU), 89.7% (PMWA) and 89.2% (RFA). The incidence of minor adverse events was 39.0% (HIFU), 51.3% (PMWA) and 3.6% (RFA). The re-intervention rates were 4.0% (HIFU) and 28.7% (RFA). The recurrence rate was 10.2% after HIFU. The pregnancy rates were 16.7% (HIFU), 4.93% (PMWA) and 35.8% (RFA). CONCLUSION: Image-guided HIFU, PMWA and RFA may be effective and safe minimally invasive therapies for symptomatic AD.

Correlation Analysis of Histopathology and Proteogenomics Data for Breast Cancer.

Tumors are heterogeneous tissues with different types of cells such as cancer cells, fibroblasts, and lymphocytes. Although the morphological features of tumors are critical for cancer diagnosis and prognosis, the underlying molecular events and genes for tumor morphology are far from being clear. With the advancement in computational pathology and accumulation of large amount of cancer samples with matched molecular and histopathology data, researchers can carry out integrative analysis to investigate this issue. In this study, we systematically examine the relationships between morphological features and various molecular data in breast cancers. Specifically, we identified 73 breast cancer patients from the TCGA and CPTAC projects matched whole slide images, RNA-seq, and proteomic data. By calculating 100 different morphological features and correlating them with the transcriptomic and proteomic data, we inferred four major biological processes associated with various interpretable morphological features. These processes include metabolism, cell cycle, immune response, and extracellular matrix development, which are all hallmarks of cancers and the associated morphological features are related to area, density, and shapes of epithelial cells, fibroblasts, and lymphocytes. In addition, protein specific biological processes were inferred solely from proteomic data, suggesting the importance of proteomic data in obtaining a holistic understanding of the molecular basis for tumor tissue morphology. Furthermore, survival analysis yielded specific morphological features related to patient prognosis, which have a strong association with important molecular events based on our analysis. Overall, our study demonstrated the power for integrating multiple types of biological data for cancer samples in generating new hypothesis as well as identifying potential biomarkers predicting patient outcome. Future work includes causal analysis to identify key regulators for cancer tissue development and validating the findings using more independent data sets.

Ultrasound-guided Microwave Ablation in the Management of Symptomatic Uterine Myomas: A Systematic Review and Meta-analysis.

OBJECTIVE: This systematic review and meta-analysis aimed to evaluate the clinical effects and safety of ultrasound-guided microwave ablation (MWA) for the treatment of symptomatic uterine myomas. DATA SOURCES: We searched PubMed, Web of Science Core Collection, Cochrane Library, Embase, Scopus, and Google Scholar for studies from January 2000 to January 2021. METHODS OF STUDY SELECTION: We included all studies that reported the clinical outcomes of ultrasound-guided MWA in women with symptomatic uterine myomas. Two researchers conducted the study selection according to the screening criteria. TABULATION, INTEGRATION, AND RESULTS: We evaluated the risk of bias and evidence quality using the Newcastle-Ottawa scale. Two researchers independently extracted information from the included studies. We extracted the standardized mean difference (SMD) and pooled proportion with a 95% confidence interval (CI) for the outcome measures of interest. A total of 10 studies representing 671 patients were included. The Uterine Fibroid Symptom and Quality of Life (UFS-QoL) questionnaire was used to assess the clinical effects. Compared with baseline, the UFS scores decreased significantly (SMD 3.37; 95% CI, 2.27-4.47; p <.001; reduction rate 65.9%), QoL scores increased significantly (SMD -3.12; 95% CI, -3.93 to -2.30; p <.001; rate of increase 72.0%), and hemoglobin concentration increased significantly (SMD -2.13; 95% CI, -3.44 to -0.81; p = .002; rate of increase 30.3%) at follow-up. The mean operation time was 34.48 minutes (95% CI, 22.82-46.13; p <.001). The rate of reduction in myoma volume after MWA was 85.3% (95% CI, 82.7%-88.0%, p <.001). No major adverse event was reported, and the incidence of minor adverse events was 21.1% (95% CI, 15.1%-27.0%, p <.001). CONCLUSION: Ultrasound-guided MWA is an effective and safe minimally invasive therapy for symptomatic uterine myomas.

Uterine Artery Embolization Compared with High-intensity Focused Ultrasound Ablation for the Treatment of Symptomatic Uterine Myomas: A Systematic Review and Meta-analysis.

OBJECTIVE: This study aimed to compare the clinical effects of uterine artery embolization (UAE) with those of high-intensity focused ultrasound (HIFU) ablation for the treatment of symptomatic uterine myomas. DATA SOURCES: We searched PubMed, EMBASE, Web of Science, Cochrane Library, Google Scholar, and ClinicalTrials.gov for studies from January 2000 to August 2020. Related articles and relevant references of the included studies were also searched. METHODS OF STUDY SELECTION: Two researchers independently performed the data selection. We included comparative studies that compared the clinical outcomes of UAE with those of HIFU ablation in women with myomas. TABULATION, INTEGRATION, AND RESULTS: We assessed the study quality using the Cochrane Handbook for Systematic Reviews of Interventions for evaluating the risk of bias. Two independent researchers performed the article selection according to the screening criteria and rated the quality of evidence for each article. We calculated pooled mean difference with 95% confidence interval (CI) for continuous data and relative risk (RR) with 95% CI for dichotomous data. The systematic review registration number is CRD42020199630 on the International Prospective Register of Systematic Reviews. A total of 7 articles (5 trials), involving 4592 women with symptomatic uterine myomas, were included in the meta-analysis. Compared with the HIFU ablation group, the decrease in "uterine fibroid symptom" scores as well as the increase in quality-of-life scores at the time of follow-up were higher in the UAE group, with overall mean difference 19.54 (95% CI, 15.21-23.87; p <.001) and 15.72 (95% CI, 8.30-23.13; p <.001), respectively. The women in the UAE group had a significantly lower reintervention rate (RR 0.25; 95% CI, 0.15-0.42; p <.001). The women undergoing UAE had a significantly lower pregnancy rate than those undergoing HIFU ablation (RR 0.06; 95% CI, 0.01-0.45; p = .006). The difference in the incidence of adverse events between the 2 groups was not statistically significant (p = .53). CONCLUSION: Compared with HIFU ablation, UAE provided more significant alleviation of symptoms and improvement in quality of life, lower postoperative reintervention rate, and lower pregnancy rate for women with uterine myomas. However, we cannot conclude that HIFU ablation is more favorable for desired pregnancy than UAE because of the confounding factors.

Dose-Related Structural Effects of Photodynamic Therapy on Rabbit Choroidal Structure.

INTRODUCTION: Photodynamic therapy with verteporfin (vPDT) has been shown to be effective against central serous chorioretinopathy (CSC) and was the preferred therapeutic for CSC treatment. However, alterations in choroidal structure after PDT were reported, and these effects were dose-dependent. This study aimed to compare the changes in choroidal structure after PDT with different doses of verteporfin in rabbits and may provide individualized therapeutic guidance for patients who failed to respond to initial half-dose vPDT. METHODS: The full dose of verteporfin used in CSC was 6 mg/m2, which was used in patients with neovascular age-related macular degeneration. Laser fluence was 50 J/cm2 (irradiance, 600 mW/cm2, 83 s). There were 4 different dose groups in this study (100%, 70%, 50%, and 30%). The alterations were examined at 1 day, 1 week, and 1 month after vPDT using color fundus imaging, indocyanine green angiography, and histopathology analysis. RESULTS: Various degrees of choroidal alterations were demonstrated at different dose groups. Examinations on day 1 showed that gradually reduced verteporfin dose tended to decrease photochemical reactions to the choroid in terms of the number of occlusion vessels and area of the lesion. After 1 month, choroid vessel alteration persisted in high-dose groups (100% and 70%); nevertheless, alterations of low-dose groups (50% and 30%) returned to normal. CONCLUSIONS: vPDT can induce photochemical reactions of the choroid, high dose causes permanent change, and low dose causes recoverable change. The dose-dependent alterations need to be considered for the individual therapeutic plan according to the situation of a patient with CSC.

Augmented Multicenter Graph Convolutional Network for COVID-19 Diagnosis.

Chest computed tomography (CT) scans of coronavirus 2019 (COVID-19) disease usually come from multiple datasets gathered from different medical centers, and these images are sampled using different acquisition protocols. While integrating multicenter datasets increases sample size, it suffers from inter-center heterogeneity. To address this issue, we propose an augmented multicenter graph convolutional network (AM-GCN) to diagnose COVID-19 with steps as follows. First, we use a 3-D convolutional neural network to extract features from the initial CT scans, where a ghost module and a multitask framework are integrated to improve the network's performance. Second, we exploit the extracted features to construct a multicenter graph, which considers the intercenter heterogeneity and the disease status of training samples. Third, we propose an augmentation mechanism to augment training samples which forms an augmented multicenter graph. Finally, the diagnosis results are obtained by inputting the augmented multi-center graph into GCN. Based on 2223 COVID-19 subjects and 2221 normal controls from seven medical centers, our method has achieved a mean accuracy of 97.76%. The code for our model is made publicly.1.

Oriented boronate affinity-imprinted inverse opal hydrogel for glycoprotein assay via colorimetry.

A biomimetic antibody is described for colorimetric determination of glycoprotein, and horseradish peroxidase (HRP) is used as model analyte. Use is made of oriented surface imprinted inverse opal hydrogel particles functionalized with phenylboronic acid. The inverse opal hydrogel particles were negatively replicated from silica colloidal crystal beads (SCCBs), so that they were endowed with larger specific surface area than the bulk structure. Benefit from that, there were abundant surface molecularly imprinting sites in the hydrogel particles. Because the imprinting sites match the structure of the template molecules, they can recognize HRP with high selectivity and sensitivity. The recognized glycoprotein was bonded with the phenylboronic acid within the sites. The bonded HRP was determined by colorimetry of 3, 3', 5, 5'-tetramethylbenzidine (TMB) single-component solution at 450 nm, and it shows a 16.03 imprinting factor under optimized conditions. Alpha-fetoprotein (AFP) was also investigated and demostrated the value of this strategy in practical applications. The results show that the absorbance increases linearly in the 1-50 ng mL-1 AFP concentration range and has a 1.32 ng mL-1 detection limit. The assay of human serum was realized by the standard addition method. This strategy is promising to open new horizons for glycoprotein assay. Graphical abstract Schematic representation of the preparation of oriented boronate affinity-imprinted inverse opal hydrogel particles for glycoprotein assay.

Breast Cancer Detection and Diagnosis Using Mammographic Data: Systematic Review.

BACKGROUND: Machine learning (ML) has become a vital part of medical imaging research. ML methods have evolved over the years from manual seeded inputs to automatic initializations. The advancements in the field of ML have led to more intelligent and self-reliant computer-aided diagnosis (CAD) systems, as the learning ability of ML methods has been constantly improving. More and more automated methods are emerging with deep feature learning and representations. Recent advancements of ML with deeper and extensive representation approaches, commonly known as deep learning (DL) approaches, have made a very significant impact on improving the diagnostics capabilities of the CAD systems. OBJECTIVE: This review aimed to survey both traditional ML and DL literature with particular application for breast cancer diagnosis. The review also provided a brief insight into some well-known DL networks. METHODS: In this paper, we present an overview of ML and DL techniques with particular application for breast cancer. Specifically, we search the PubMed, Google Scholar, MEDLINE, ScienceDirect, Springer, and Web of Science databases and retrieve the studies in DL for the past 5 years that have used multiview mammogram datasets. RESULTS: The analysis of traditional ML reveals the limited usage of the methods, whereas the DL methods have great potential for implementation in clinical analysis and improve the diagnostic capability of existing CAD systems. CONCLUSIONS: From the literature, it can be found that heterogeneous breast densities make masses more challenging to detect and classify compared with calcifications. The traditional ML methods present confined approaches limited to either particular density type or datasets. Although the DL methods show promising improvements in breast cancer diagnosis, there are still issues of data scarcity and computational cost, which have been overcome to a significant extent by applying data augmentation and improved computational power of DL algorithms.

Intelligent Metal Carbonyl Metal-Organic Framework Nanocomplex for Fluorescent Traceable H2 O2 -Triggered CO Delivery.

The recognized therapeutic benefits from carbon monoxide (CO) have caused booming attention to develop a CO therapy for various major diseases, such as cancer. However, the controlled release of CO gas and the monitoring of the CO release are vitally important to the on-demand CO administration for a safe and efficient therapy, but greatly challenging. In this work, a new CO-releasing nanocomplex was constructed by the adsorption and coordination of manganese carbonyl ([MnBr(CO)5 ], abbreviated as MnCO) with a Ti-based metal-organic framework (Ti-MOF) to realize an intratumoral H2 O2 -triggered CO release and real-time CO release monitoring by fluorescence imaging. A high CO prodrug loading capacity (0.532 g MnCO per gram Ti-MOF) is achieved due to the high surface area of Ti-MOF, and the intracellular H2 O2 -triggered CO release from the MnCO@Ti-MOF is realized to enable the nanocomplex selectively release CO in tumor cells and kill tumor cells rather than normal cells. Particularly significant is that the real-time fluorescence imaging monitoring of the CO release is realized based on an annihilation effect of the fluorescence after MnCO loading into Ti-MOF and an activation effect of the fluorescence after CO release from Ti-MOF. The quantitative relationship between the fluorescence intensity and the released CO amount is established in great favor of guiding on-demand CO administration. The results demonstrate the advantage of versatile MOFs for high efficient CO delivery and monitoring, which is critical for the improvement of the effectiveness of future therapeutic application.

Noninvasive assessment of age-related stiffness of crystalline lenses in a rabbit model using ultrasound elastography.

BACKGROUND: The pathological or physiological changes of a crystalline lens directly affect the eye accommodation and transmittance, and then they increase the risk of presbyopia and cataracts for people in the middle and old age groups. There is no universally accepted quantitative method to measure the lens' mechanical properties in vivo so far. This study aims to investigate the possibility of assessing the age-related stiffness change of crystalline lens by acoustic-radiation-force-based ultrasound elastography (ARF-USE) in a rabbit model in vivo. METHODS: There were 13 New Zealand white rabbits that were divided into four groups and fed normally until they were 60 (n = 4), 90 (n = 2), 120 (n = 4), and 150 (n = 3) days old, respectively. An ARF-USE platform was built based on the Verasonics™ Vantage 256 system. The shear waves were excited and traced in the lens by a linear ultrasound probe after a rabbit was anaesthetized. RESULTS: The average group velocities were 1.38 ± 0.2 m/s, 2.06 ± 0.3 m/s, 2.07 ± 0.29 m/s, and 2.30 ± 0.28 m/s, respectively, for the four groups of rabbits. The results shows that the group velocity has a strong correlation with the day age (r = 0.84, p < 1 × 10-7) and the weight (r = 0.83, p < 1×10-7) of the rabbits while the maximum displacement has no correlations with the day age (r = 0.27, p > 0.1) and the weight (r = 0.32, p > 0.1). CONCLUSION: This study demonstrated that the group velocity measured by ARF-USE had a strong correlation with age-related stiffness in a rabbit model, suggesting that group velocity is a good biomarker to characterize the stiffness of a crystalline lens. This study also demonstrated the feasibility of using this USE technique to assess the mechanical properties of the lens in vivo for clinical or research purposes.

[A review of automatic liver tumor segmentation based on computed tomography].

Liver cancer is a common type of malignant tumor in digestive system. At present, computed tomography (CT) plays an important role in the diagnosis and treatment of liver cancer. Segmentation of tumor lesions based on CT is thus critical in clinical diagnosis and treatment. Due to the limitations of manual segmentation, such as inefficiency and subjectivity, the automatic and accurate segmentation based on advanced computational techniques is becoming more and more popular. In this review, we summarize the research progress of automatic segmentation of liver cancer lesions based on CT scans. By comparing and analyzing the results of experiments, this review evaluate various methods objectively, so that researchers in related fields can better understand the current research progress of liver cancer segmentation based on CT scans.

[Research progress of computer-aided diagnosis in cancer based on deep learning and medical imaging].

The dramatically increasing high-resolution medical images provide a great deal of useful information for cancer diagnosis, and play an essential role in assisting radiologists by offering more objective decisions. In order to utilize the information accurately and efficiently, researchers are focusing on computer-aided diagnosis (CAD) in cancer imaging. In recent years, deep learning as a state-of-the-art machine learning technique has contributed to a great progress in this field. This review covers the reports about deep learning based CAD systems in cancer imaging. We found that deep learning has outperformed conventional machine learning techniques in both tumor segmentation and classification, and that the technique may bring about a breakthrough in CAD of cancer with great prospect in the future clinical practice.