Crystal Self-Assembly under Confinement: Bridging Nanomaterials to Integrated Devices.

ConspectusSelf-assembly, a spontaneous process that organizes disordered constituents into ordered structures, has revolutionized our fundamental understanding of living matter, nanotechnology, and molecular science. From the perspective of nanomaterials, self-assembly serves as a bottom-up method for creating long-range-ordered materials. This is accomplished by tailoring the geometry, chemistry, and interactions of the components, thereby facilitating the efficient fabrication of high-quality materials and high-performance functional devices. Over the past few decades, we have seen controllable organization and diverse phases in self-assembled materials, such as organic crystals, biomolecular structures, and colloidal nanoparticle supercrystals. However, most self-assembled ordered materials and their assembly mechanisms are derived from constituents in a liquid bulk medium, where the effects of boundaries and interfaces are negligible. In the context of nanostructure patterning, self-assembly occurs in confined spaces, with feature sizes ranging from a few to hundreds of nanometers. In such settings, ubiquitous boundaries and interfaces can trap the system in a kinetically favored but metastable state, devoid of long-range order. This makes it extremely difficult to achieve ordered structures in micro/nano-patterning techniques that rely on sessile microdroplets, such as inkjet printing, dip-pen lithography, and contact printing.In stark contrast to sessile droplets, capillary bridges─formed by liquids confined between two solid surfaces─provide unique opportunities for understanding the long-range-ordered self-assembly of crystalline materials under spatial confinement. Because capillary bridges are stabilized by Laplace pressure, which is inversely proportional to the feature size, the confinement and manipulation of solutions or suspensions of functional materials at the nanoscale become accessible through the rational design of surface chemistry and geometry. Although global thermodynamic equilibrium is unattainable in evaporative systems, ordered nucleation and packing of constituent components can be locally realized at the contact line of capillary bridges. This enables the unprecedented fabrication of long-range-ordered micro/nanostructures with deterministic patterns.In this Account, we review the advancements in long-range-ordered self-assembly of crystalline micro/nanostructures under confinement. First, we briefly introduce crystalline materials characterized by strong intramolecular interactions and relatively weak intermolecular forces, analyzing both the opportunities and challenges inherent to self-assembled nanomaterials. Next, we delve into the construction and manipulation of confined liquids, focusing especially on capillary bridges controlled by engineered chemistry and geometry to regulate Laplace pressure. Through this approach, we have achieved capillary bridges with thicknesses on the order of a few nanometers and wafer-scale homogeneity, facilitating the self-assembly of ordered structures. Supported by factors such as local free-volume entropy, electrostatic interactions, curvilinear geometry, directional microfluidics, and nanoconfinement, we have achieved long-range-ordered, deterministic patterning of organic semiconductors, metal-halide perovskites, and colloidal nanocrystal superlattices using this capillary-bridge platform. These long-range microstructures serve as a bridge between nanomaterials and integrated devices, enabling emergent functionalities like intrinsic stretchability, giant photoconductivity, propagating and interacting exciton polaritons, and spin-valley-locked lasing, which are otherwise unattainable in disordered materials. Finally, we discuss potential directions for both the fundamental understanding and practical applications of confined self-assembly.

Molecular Electronics: From Nanostructure Assembly to Device Integration.

Integrated electronics and optoelectronics based on organic semiconductors have attracted considerable interest in displays, photovoltaics, and biosensing owing to their designable electronic properties, solution processability, and flexibility. Miniaturization and integration of devices are growing trends in molecular electronics and optoelectronics for practical applications, which requires large-scale and versatile assembly strategies for patterning organic micro/nano-structures with simultaneously long-range order, pure orientation, and high resolution. Although various integration methods have been developed in past decades, molecular electronics still needs a versatile platform to avoid defects and disorders due to weak intermolecular interactions in organic materials. In this perspective, a roadmap of organic integration technologies in recent three decades is provided to review the history of molecular electronics. First, we highlight the importance of long-range-ordered molecular packing for achieving exotic electronic and photophysical properties. Second, we classify the strategies for large-scale integration of molecular electronics through the control of nucleation and crystallographic orientation, and evaluate them based on factors of resolution, crystallinity, orientation, scalability, and versatility. Third, we discuss the multifunctional devices and integrated circuits based on organic field-effect transistors (OFETs) and photodetectors. Finally, we explore future research directions and outlines the need for further development of molecular electronics, including assembly of doped organic semiconductors and heterostructures, biological interfaces in molecular electronics and integrated organic logics based on complementary FETs.

Development and Assessment of Multiple Illumination Color Fourier Ptychographic Microscopy for High Throughput Sample Digitization.

In this study, we proposed a multiplexed color illumination strategy to improve the data acquisition efficiency of Fourier ptychography microscopy (FPM). Instead of sequentially lighting up one single channel LED, our method turns on multiple white light LEDs for each image acquisition via a color camera. Thus, each raw image contains multiplexed spectral information. An FPM prototype was developed, which was equipped with a 4×/0.13 NA objective lens to achieve a spatial resolution equivalent to that of a 20×/0.4 NA objective lens. Both two- and four-LED illumination patterns were designed and applied during the experiments. A USAF 1951 resolution target was first imaged under these illumination conditions, based on which MTF curves were generated to assess the corresponding imaging performance. Next, H&E tissue samples and analyzable metaphase chromosome cells were used to evaluate the clinical utility of our strategy. The results show that the single and multiplexed (two- or four-LED) illumination results achieved comparable imaging performance on all the three channels of the MTF curves. Meanwhile, the reconstructed tissue or cell images successfully retain the definition of cell nuclei and cytoplasm and can better preserve the cell edges as compared to the results from the conventional microscopes. This study initially validates the feasibility of multiplexed color illumination for the future development of high-throughput FPM scanning systems.

Comparative study of instrumental measurement and sensory evaluation methods for the repairing effect of mildly damaged hair bundles.

OBJECTIVE: This study explores the applicability and scientific accuracy of instrument measurements in repairing hair products on slightly damaged hair bundles. MATERIALS AND METHOD: Sixty hair bundles mildly damaged with hydrogen peroxide and ammonia standards were divided into two groups: the treatment and control groups (30 hair bundles each). The treatment group used commercial hair care essential oil, whereas the control group used tap water to treat the damage. The two groups were measured using an instrument before and after the product application. The objective indicators included the gloss of hair, along with hair cuticle dynamic friction coefficient, and against hair cuticle dynamic friction coefficient. At the same time, two evaluators conducted sensory evaluations on the gloss and frizz levels of the hair bundles. Therefore, data comparison and verification were carried out together with instrumental measurement data. RESULTS: We verified that the instrumental measurement methods could obtain data trends that are consistent with sensory assessment methods; hence, they have the advantages of accuracy, convenience, and quantifiability. CONCLUSION: Thus, the instrumental measurement methods we verified can provide objective evidence for the efficacy of hair care products in repairing hair.

Evaluation of the antiwear-ability/scratch-resistance efficacy of makeup products by in vitro test method application.

OBJECTIVE: The objective of this study is to propose a method for assessing the antiwear-ability (AW) or surface scratch-resistance (SR) efficacy of makeup products through in vitro experiments. MATERIALS AND METHOD: The method primarily involves measuring the change in weight as a means of evaluating the overall effectiveness. AW/SR effects are evaluated by applying a fixed amount of makeup product on artificial fake skin and comparing the weight difference after simulated friction/scratch. RESULTS: The in vitro results indicate that this method is easy to operate and yields repeatable data. It consistently reflects differences between samples when compared to clinical studies. CONCLUSIONS: This method effectively compares the AW/SR effects of makeup products and demonstrates utility in evaluating product efficacy and difference. It holds great scientific and practical value.

Establishment and validation of visual assessment for the severity of lacrimal groove wrinkles in Chinese females.

OBJECTIVE: This study was undertaken to establish and validate a new wrinkle clinical assessment scale to measure Chinese Han women`s validated lacrimal groove. METHODS: Three clinical investigators asked to rate lacrimal groove wrinkles severity one each side for 30 photographic images from 15 subjects. Five-grade rating scale has been used in this clinical assessment. Scale definitions was standardized by 6 researchers in visual and descriptive formats. Assessments were conducted independently and were repeated after 1 week. RESULTS: For 30 photos from 15 subjects, test-retest of three investigators analyzed by Spearman's correlation were between 0.967 and 0.993 (p < 0.001), and by ICC Cronbach's α were between 0.989 and 0.997 (p < 0.001); intraobserver agreement of three investigators analyzed by Spearman's correlation were between 0.652 and 0.897 (p < 0.001), and by ICC Cronbach's α were between 0.840 and 0.959 (p < 0.001). CONCLUSION: This lacrimal groove wrinkles visual assessment scale is a valid and reliable instrument for quantitative assessment of China woman skin folds with inter- and intraobserver consistency. This assessment scale should prove a useful clinical tool by allowing objective and reproducible grading for assessing the effectiveness of lacrimal groove area.

Organic Single-Crystalline Microwire Arrays toward High-Performance Flexible Near-Infrared Phototransistors.

Flexible organic near-infrared (NIR) phototransistors hold promising prospects for potential applications such as noninvasive bioimaging, health monitoring, and biometric authentication. For integrated circuits of high-performance devices, organic single-crystalline micro-/nanostructures with precise positioning are prominently anticipated. However, the manufacturing of organic single-crystalline arrays remains a conundrum due to difficulties encountered in patterning arrays of dewetting processes at micron-scale confined space and modulating the dewetting dynamics. Herein, we utilize a capillary-bridge lithography strategy to fabricate organic 1D arrays with high quality, homogeneous size, and deterministic location toward high-performance flexible organic NIR phototransistors. Regular micro-liquid stripes and unidirectional dewetting are synchronously achieved by adapting micropillar templates with asymmetric wettability. As a result, high-throughput 1D arrays based organic field-effect transistors exhibit high electron mobility up to 9.82 cm2  V-1  s-1 . Impressively, flexible NIR phototransistors also show outstanding photoelectronic performances with a photosensitivity of 9.87 × 105 , a responsivity of 1.79 × 104  A W-1 , and a specific detectivity of 3.92 × 1014 Jones. This work paves a novel way to pattern high-throughput organic single-crystalline microarrays toward flexible NIR organic optoelectronics.

Chiral 2D-Perovskite Nanowires for Stokes Photodetectors.

Structural engineering in multiple scales permits the integration of exotic properties into a single material, which boosts the development of ultracompact multifunctional devices. Layered perovskites are capable of cross-linking efficient carrier transport originating from few-layer perovskite frameworks with extended functionalities contributed by designable bulky organic cations and nanostructures, thus providing a platform for multiscale material engineering. Herein, high-performance Stokes-parameter photodetectors for arbitrary polarized light detection are realized on the basis of solution-processed chiral-perovskite nanowire arrays. The chiral ammonium cations intercalated between the perovskite layers are responsive to circularly polarized light with a maximum anisotropy factor of 0.15, while the strictly aligned nanowires with the anisotropic dielectric function result in a large polarized ratio of 1.6 to linearly polarized light. Single crystallinity and pure crystallographic orientation permit efficient in-plane carrier transport along the nanowires, yielding a responsivity of 47.1 A W-1 and a detectivity of 1.24 × 1013 Jones. By synergy of linear- and circular-polarization response with high optoelectronic performance for providing sufficient photocurrent contrasts, Stokes-parameter photodetection is demonstrated on these nanowires. Our Stokes-parameter photodetectors with a small footprint and high performances present promising applications toward polarization imaging.

Scalable Single-Crystalline Organic 1D Arrays for Image Sensor.

Optoelectronic applications of organic semiconductors demand single-crystalline structures with long-range order and suppressed defects for sustaining efficient carrier transport and long photocarrier lifetime, which are pivotal in photodetection, photovoltaic, and light emission. For integrated devices, an additional requirement of precise patterning is imposed, whereas the patterning of single-crystalline organic microstructures is still challenging because the molecular stacking is easily perturbed by disordered fluids in microdroplets. Herein, a capillary-bridge lithography is developed for driving the directional transport of capillary flows to control the confined crystallization of organic 1D single-crystalline arrays with aligned positioning and pure orientation. Through tuning the concentration and pressure, the size of organic 1D arrays in three dimensions can be controlled with 2.9-5.8 µm in width and 1.2 µm to 110 nm in height. Organic 1D array photodetectors exhibit a stable performance with on/off ratio of 180 and responsivity of 4.99 mA W-1 . Based on the scalable fabrication of 1D array photodetectors, 20 × 20 multiplexed image sensors with high accuracy are demonstrated for capturing the light signals of capital letter "A," "B," and "C." This research will open opportunities for the large-scale fabrication of organic single-crystalline semiconductors toward the integrated optoelectronic modules.

Establishment of visual assessment for the severity of dark circles in Chinese Han women.

OBJECTIVE: To establish a visual assessment scale for the severity of dark circles' pigmented and vascular type in Chinese women. MATERIALS AND METHOD: A total of 269 healthy Chinese women from Shanghai with different degrees of dark circles', both pigmented and vascular types, were evaluated by visual assessment. Photographs of their dark circles were analyzed by image analysis. RESULTS: The visual assessment evaluation on classification and severity showed a favorable agreement between the successive measured results. Significant differences from very slight to severe dark circles for pigmented type and vascular type were observed. The severity level by visual assessment was significantly positively correlated with ΔE values while negatively correlated with ΔL values (P < .01) in both pigmented and vascular types. Besides, Δa values of vascular type were significantly positively correlated with the ΔE values for dark circles' vascular type. Values between ΔE and ΔL also showed a significant negative correlation (P < .01). CONCLUSION: The five-point visual assessment scale for dark circles of vascular and pigmented types was verified and proved to have good repeatability. The image analysis's objective result proved significant and consistent with the visual assessment and color parameters. This scale could be a useful and effective tool in diagnosing dark circles' severity.

Face-Sharing Archimedean Solids Stacking for the Construction of Mixed-Ligand Metal-Organic Frameworks.

Reticular chemistry has been an important guiding principle for the design of metal-organic frameworks (MOFs). This approach utilizes discrete building units (molecules and clusters) that are connected through strong bonds into extended networks assisted by topological considerations. Although the simple design principle of connecting points and lines has proved successful, new design strategies are still needed to further explore the structures and functions of MOFs. Herein, we report the design and synthesis of two mixed-ligand MOFs, [(CH3)2NH2]4[Zn4O]4[Zn(TCPP)]5[BTB]8/3 (PCN-137) and [Zr6(µ3-O)4(µ3-OH)4][TCPP][TBTB]8/3 (PCN-138) (BTB = 1,3,5-benzene(tris)benzoate, TBTB = 4,4',4″-(2,4,6-trimethylbenzene-1,3,5-triyl)tribenzoate, and TCPP = tetrakis(4-carboxyphenyl)porphyrin) by the stacking of face-sharing Archimedean solids. In these two MOFs, high-symmetrical metal clusters serve as vertices, and tritopic or tetratopic carboxylate ligands function as triangular and square faces, leading to the formation of two kinds of Archimedean solids (rhombicuboctahedron and cuboctahedron). Furthermore, the ordered accumulation of Archimedean solids successfully gives rise to 3D structures through face-sharing, highlighting the polyhedron-based approach for the design and preparation of MOFs. In addition, PCN-138 was utilized as a heterogeneous catalyst toward CO2 photoreduction under visible-light irradiation. This structure shows high photocatalytic activity, which can be attributed to the coexistence of photosensitizing porphyrin fragments and Zr-oxo centers within the PCN-138 scaffold.

Computer-aided classification of mammographic masses using visually sensitive image features.

PURPOSE: To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. METHODS: An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. RESULTS: Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. CONCLUSION: This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a "visual aid" interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features.

A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology.

PURPOSE: To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. METHODS: An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. RESULTS: The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. CONCLUSIONS: This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process.

Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome.

BACKGROUND: To investigate the feasibility of automated segmentation of visceral and subcutaneous fat areas from computed tomography (CT) images of ovarian cancer patients and applying the computed adiposity-related image features to predict chemotherapy outcome. METHODS: A computerized image processing scheme was developed to segment visceral and subcutaneous fat areas, and compute adiposity-related image features. Then, logistic regression models were applied to analyze association between the scheme-generated assessment scores and progression-free survival (PFS) of patients using a leave-one-case-out cross-validation method and a dataset involving 32 patients. RESULTS: The correlation coefficients between automated and radiologist's manual segmentation of visceral and subcutaneous fat areas were 0.76 and 0.89, respectively. The scheme-generated prediction scores using adiposity-related radiographic image features significantly associated with patients' PFS (p < 0.01). CONCLUSION: Using a computerized scheme enables to more efficiently and robustly segment visceral and subcutaneous fat areas. The computed adiposity-related image features also have potential to improve accuracy in predicting chemotherapy outcome.

Early prediction of clinical benefit of treating ovarian cancer using quantitative CT image feature analysis.

BACKGROUND: In current clinical trials of treating ovarian cancer patients, how to accurately predict patients' response to the chemotherapy at an early stage remains an important and unsolved challenge. PURPOSE: To investigate feasibility of applying a new quantitative image analysis method for predicting early response of ovarian cancer patients to chemotherapy in clinical trials. MATERIAL AND METHODS: A dataset of 30 patients was retrospectively selected in this study, among which 12 were responders with 6-month progression-free survival (PFS) and 18 were non-responders. A computer-aided detection scheme was developed to segment tumors depicted on two sets of CT images acquired pre-treatment and 4-6 weeks post treatment. The scheme computed changes of three image features related to the tumor volume, density, and density variance. We analyzed performance of using each image feature and applying a decision tree to predict patients' 6-month PFS. The prediction accuracy of using quantitative image features was also compared with the clinical record based on the Response Evaluation Criteria in Solid Tumors (RECIST) guideline. RESULTS: The areas under receiver operating characteristic curve (AUC) were 0.773 ± 0.086, 0.680 ± 0.109, and 0.668 ± 0.101, when using each of three features, respectively. AUC value increased to 0.831 ± 0.078 when combining these features together. The decision-tree classifier achieved a higher predicting accuracy (76.7%) than using RECIST guideline (60.0%). CONCLUSION: This study demonstrated the potential of using a quantitative image feature analysis method to improve accuracy of predicting early response of ovarian cancer patients to the chemotherapy in clinical trials.

Peanut leaf inspired multifunctional surfaces.

Nature has long served as a source of inspiration for scientists and engineers to design and construct multifunctional artificial materials. The lotus and the peanut are two typical plants living in the aquatic and the arid (or semiarid) habitats, respectively, which have evolved different optimized solutions to survive. For the lotus leaf, an air layer is formed between its surface and water, exhibiting a discontinuous three-phase contact line, which resulted in the low adhesive superhydrophobic self-cleaning effect to avoid the leaf decomposition. In contrast to the lotus leaf, the peanut leaf shows high-adhesive superhydrophobicity, arising from the formation of the quasi-continuous and discontinuous three-phase contact line at the microscale and nanoscale, respectively, which provides a new avenue for the fabrication of high adhesive superhydrophobic materials. Further, this high adhesive and superhydrophobic peanut leaf is proved to be efficient in fog capture. Inspired by the peanut leaf, multifunctional surfaces with structural similarity to the natural peanut leaf are prepared, exhibiting simultaneous superhydrophobicity and high adhesion towards water.

Experimental study of a canine model for a newly designed adjustable prefenestration aortic stent graft.

PURPOSE: When performing thoracic aortic endovascular repair (TEVAR) on lesions of the aortic arch, physician- modified fenestration or in situ fenestration is often used to maintain patent branches. We designed a new adjustable prefenestration aortic stent graft that can both isolate pathologies in the aortic arch and obtain patent branches simultaneously. In this study, we use this new type of stent to perform fenestrated TEVAR in a canine's aorta. This study aims to evaluate the safety and feasibility of the new device, which may provide preliminary data for potential human application. METHODS: Eight Labrador Retriever canines underwent fenestrated TEVAR using the new stent device. Digital subtract angiography (DSA) was performed before and after fenestrated TEVAR to evaluate the safety and feasibility of the procedure. For the device deployment, at the "large curvature" side in the endograft, there is a rectangular prefenestration area (2 × 5 cm) without the polytetrafluoroethylene membrane, and at both longer side edges of the fenestration, there are two slide rails. A moveable membrane that covers the same area as the prefenestration area is initially set at the prefenestration position. A stay line is connected from the distal site of the moveable membrane that controls it to the distal position along the slide rail, which releases the fenestration. After the positioning of the prefenestration is determined, the outer sheath of the delivery system is released, and the stay line at the end of the delivery system is pulled outside the body. The animals were divided into a 1-month group (n = 4) and a 3-month group (n = 4) after the fenestrated TEVAR. Computed tomography (CT) was performed before euthanasia, and video of the DSA during the procedures and CT angiography (CTA) images were then studied. RESULTS: The procedure success rate was 100%, but the total survival rate was only 87.5%. There were no aortic-related deaths during follow-up, and during the operation, there were no stent-graft-related accidents. In addition, no stent-graft migrations were observed in the CTA, and all branch arteries were kept patent by the adjustable fenestration. Finally, histological examination and electron microscope results showed no obvious vascular injury or inflammation. CONCLUSION: Based on the results of this study, we judge the safety and feasibility of the use of the newly designed adjustable prefenestration aortic stent graft in a fenestrated-TEVAR canine model to be acceptable. Our preliminary data may provide a first reference for evaluating the new stent's potential use in humans.

Utilizing a Pathomics Biomarker to Predict the Effectiveness of Bevacizumab in Ovarian Cancer Treatment.

The purpose of this investigation is to develop and initially assess a quantitative image analysis scheme that utilizes histopathological images to predict the treatment effectiveness of bevacizumab therapy in ovarian cancer patients. As a widely accessible diagnostic tool, histopathological slides contain copious information regarding underlying tumor progression that is associated with tumor prognosis. However, this information cannot be readily identified by conventional visual examination. This study utilizes novel pathomics technology to quantify this meaningful information for treatment effectiveness prediction. Accordingly, a total of 9828 features were extracted from segmented tumor tissue, cell nuclei, and cell cytoplasm, which were categorized into geometric, intensity, texture, and subcellular structure features. Next, the best performing features were selected as the input for SVM (support vector machine)-based prediction models. These models were evaluated on an open dataset containing a total of 78 patients and 288 whole slides images. The results indicated that the sufficiently optimized, best-performing model yielded an area under the receiver operating characteristic (ROC) curve of 0.8312. When examining the best model's confusion matrix, 37 and 25 cases were correctly predicted as responders and non-responders, respectively, achieving an overall accuracy of 0.7848. This investigation initially validated the feasibility of utilizing pathomics techniques to predict tumor responses to chemotherapy at an early stage.

Utilizing Pseudo Color Image to Improve the Performance of Deep Transfer Learning-Based Computer-Aided Diagnosis Schemes in Breast Mass Classification.

The purpose of this study is to investigate the impact of using morphological information in classifying suspicious breast lesions. The widespread use of deep transfer learning can significantly improve the performance of the mammogram based CADx schemes. However, digital mammograms are grayscale images, while deep learning models are typically optimized using the natural images containing three channels. Thus, it is needed to convert the grayscale mammograms into three channel images for the input of deep transfer models. This study aims to develop a novel pseudo color image generation method which utilizes the mass contour information to enhance the classification performance. Accordingly, a total of 830 breast cancer cases were retrospectively collected, which contains 310 benign and 520 malignant cases, respectively. For each case, a total of four regions of interest (ROI) are collected from the grayscale images captured for both the CC and MLO views of the two breasts. Meanwhile, a total of seven pseudo color image sets are generated as the input of the deep learning models, which are created through a combination of the original grayscale image, a histogram equalized image, a bilaterally filtered image, and a segmented mass. Accordingly, the output features from four identical pre-trained deep learning models are concatenated and then processed by a support vector machine-based classifier to generate the final benign/malignant labels. The performance of each image set was evaluated and compared. The results demonstrate that the pseudo color sets containing the manually segmented mass performed significantly better than all other pseudo color sets, which achieved an AUC (area under the ROC curve) up to 0.889 ± 0.012 and an overall accuracy up to 0.816 ± 0.020, respectively. At the same time, the performance improvement is also dependent on the accuracy of the mass segmentation. The results of this study support our hypothesis that adding accurately segmented mass contours can provide complementary information, thereby enhancing the performance of the deep transfer model in classifying suspicious breast lesions.

Roles of red mud-based biochar carriers in the recovery of anammox activity: characteristics and mechanisms.

Anaerobic ammonium oxidation (anammox) sludge is easily deactivated in the process of treating ammonia-laden wastewater. To investigate an effective recovery method, red mud-based biochar carriers (RMBC) were prepared and added to a deactivated anammox reactor; the operation of this reactor had been interrupted for 6 months with starvation and low temperature. The deactivated sludge with added RMBC was recovered rapidly after 31 days, with the specific anammox activity rapidly increasing to 0.84 g N/(g VSS∙day), and the recovery efficiency of nitrogen removal rate increased by four times compared to the unadded control. The granulation degree and extracellular polymeric substances secretion of the anammox sludge with the added RMBC were significantly higher than that of the control group. In addition, a large number of spherical anammox bacteria were observed moored at the porous channels of RMBC, and the copy numbers of functional genes of anammox bacteria were approximately twice that of the control group. Hence, RMBC is a potential sludge activator, and it can provide a "house" to protect anammox bacteria, enhance the metabolic activity and the agglomerative growth of anammox bacteria, and synergistically achieve rapid recovery of deactivated anammox sludge.