Nanometric-Mapping and In Situ Quantification of Site-specific Photoredox Activities on 2D Nanoplates.

Defective layered bismuth oxychloride (BiOCl) exhibits excellent photocatalytic activities in water purification and environmental remediation. Herein, in situ single-molecule fluorescence microscopy is used to spatially resolve the photocatalytic heterogeneity and quantify the photoredox activities on individual structural features of BiOCl. The BiOCl nanoplates with respective dominant {001} and {010} facets (BOC-001 and BOC-010) are fabricated through tuning the pH of the solution. The corner position of BOC-001 exhibits the highest photo-oxidation turnover rate of 262.7 ± 30.8 s-1 µm-2, which is 2.1 and 65.7 times of those of edges and basal planes, respectively. A similar trend is also observed on BOC-010, which can be explained by the heterogeneous distribution of defects at each structure. Besides, BOC-001 shows a higher photoredox activity than BOC-010 at corners and edges. This can be attributed to the superior charge separation ability, active high-index facets of BOC-001, and its co-exposure of anisotropic facets steering the charge flow. Therefore, this work provides an effective strategy to understand the facet-dependent properties of single-crystalline materials at nanometer resolution. The quantification of site-specific photoredox activities on BiOCl nanoplates sheds more light on the design and optimization of 2D materials at the single-molecule level.

In Situ Quantitative Study of Single-Molecule Photoreduction Activities and Kinetics on 1D-1D Heterostructure.

Understanding the underlying catalytic mechanisms with nanometer resolution is of critical importance to the rational design of 1D heterogeneous catalysts. However, a fundamental investigation of photocatalytic activities and kinetics at their individual sites is still challenging. Herein, in situ single-molecule fluorescence microscopy is employed to study the site-specific catalytic activities and dynamics on 1D-1D heterostructure for the first time. For carbon nanotube (CNT)/CdS nanorod composites, it is found that the CdS end with heterojunction exhibits the highest catalytic conversion rate constant of resazurin photoreduction, which is 30%, 7%, and 19% higher than those of the middle segment and the bare end of CdS, and the CNT end with heterojunction, respectively. A similar trend of adsorption abilities is observed in these structures. Such phenomena can be attributed to the different content of defects in these structures. Regarding the dissociation behaviors, the dissociation rate constants of all structures exhibit an opposite trend to those of adsorption and conversion. The direct and indirect dissociation are found to be predominant on CdS and CNT, respectively. Such investigation provides a deep insight into the understanding of site-specific properties on 1D heterogeneous catalysts and helps construct the "structure-dynamics" correlations at the nanoscale.

Autologous Transplantation Tooth Guide Design Based on Deep Learning.

BACKGROUND: Autologous tooth transplantation requires precise surgical guide design, involving manual tracing of donor tooth contours based on patient cone-beam computed tomography (CBCT) scans. While manual corrections are time-consuming and prone to human errors, deep learning-based approaches show promise in reducing labor and time costs while minimizing errors. However, the application of deep learning techniques in this particular field is yet to be investigated. PURPOSE: We aimed to assess the feasibility of replacing the traditional design pipeline with a deep learning-enabled autologous tooth transplantation guide design pipeline. STUDY DESIGN, SETTING, SAMPLE: This retrospective cross-sectional study used 79 CBCT images collected at the Guangzhou Medical University Hospital between October 2022 and March 2023. Following preprocessing, a total of 5,070 region of interest images were extracted from 79 CBCT images. PREDICTOR VARIABLE: Autologous tooth transplantation guide design pipelines, either based on traditional manual design or deep learning-based design. MAIN OUTCOME VARIABLE: The main outcome variable was the error between the reconstructed model and the gold standard benchmark. We used the third molar extracted clinically as the gold standard and leveraged it as the benchmark for evaluating our reconstructed models from different design pipelines. Both trueness and accuracy were used to evaluate this error. Trueness was assessed using the root mean square (RMS), and accuracy was measured using the standard deviation. The secondary outcome variable was the pipeline efficiency, assessed based on the time cost. Time cost refers to the amount of time required to acquire the third molar model using the pipeline. ANALYSES: Data were analyzed using the Kruskal-Wallis test. Statistical significance was set at P < .05. RESULTS: In the surface matching comparison for different reconstructed models, the deep learning group achieved the lowest RMS value (0.335 ± 0.066 mm). There were no significant differences in RMS values between manual design by a senior doctor and deep learning-based design (P = .688), and the standard deviation values did not differ among the 3 groups (P = .103). The deep learning-based design pipeline (0.017 ± 0.001 minutes) provided a faster assessment compared to the manual design pipeline by both senior (19.676 ± 2.386 minutes) and junior doctors (30.613 ± 6.571 minutes) (P < .001). CONCLUSIONS AND RELEVANCE: The deep learning-based automatic pipeline exhibited similar performance in surgical guide design for autogenous tooth transplantation compared to manual design by senior doctors, and it minimized time costs.

Selective and Stable CO2 Electroreduction to CH4 via Electronic Metal-Support Interaction upon Decomposition/Redeposition of MOF.

The CO2 electroreduction to fuels is a feasible approach to provide renewable energy sources. Therefore, it is necessary to conduct experimental and theoretical investigations on various catalyst design strategies, such as electronic metal-support interaction, to improve the catalytic selectivity. Here a solvent-free synthesis method is reported to prepare a copper (Cu)-based metal-organic framework (MOF) as the precursor. Upon electrochemical CO2 reduction in aqueous electrolyte, it undergoes in situ decomposition/redeposition processes to form abundant interfaces between Cu nanoparticles and amorphous carbon supports. This Cu/C catalyst favors the selective and stable production of CH4 with a Faradaic efficiency of ≈55% at -1.4 V versus reversible hydrogen electrode (RHE) for 12.5 h. The density functional theory calculation reveals the crucial role of interfacial sites between Cu and amorphous carbon support in stabilizing the key intermediates for CO2 reduction to CH4 . The adsorption of COOH* and CHO* at the Cu/C interface is up to 0.86 eV stronger than that on Cu(111), thus promoting the formation of CH4 . Therefore, it is envisioned that the strategy of regulating electronic metal-support interaction can improve the selectivity and stability of catalyst toward a specific product upon electrochemical CO2 reduction.

Spectrally Resolved Single Particle Photoluminescence Microscopy Reveals Heterogeneous Photocorrosion Activity of Cuprous Oxide Microcrystals.

Photocorrosion of cuprous oxide (Cu2O) has notably limited its application as an efficient photocatalyst. We report a facile approach to visualize in situ formation of copper and oxygen vacancies on the Cu2O surface under ambient condition. By imaging photoexcited single Cu2O particles, the resultant photoluminescence generated at Cu2O surface enable effective localization of copper and oxygen vacancies. Single particle photoluminescence imaging showed substantial heterogeneity in the rate of defect formation at different facets with the truncated corners achieving the fastest initial rate of photooxidation before subsequently changing to the face and edge sites as the photocorrosion proceeds. The generation of copper or oxygen vacancy is proportional to the photoexcitation power, while pH-dependent studies rationalized alkaline conditions for the formation of copper vacancy. Reaction in an electron-hole scavenger system showed that photooxidation and photoreduction will simultaneously occur, yet heterogeneously on the surface of Cu2O, with rate of copper vacancy formation being fastest.

[Research progress on anti-tumor effects by traditional Chinese medicine based on "soothing" or "blockage" regulation of tumor vessels].

Regulation of tumor vessels has become one of the most common strategies for clinical anti-tumor therapy. In recent years, studies have found that the anti-tumor effect of limotherapy, which routinely inhibits tumor angiogenesis, is not ideal and may even deteriorate the tumor microenvironment, causing tumor resistance and distal metastasis and increasing the risk of tumor metastasis and recurrence. However, the proper use of anti-angiogenic drugs can promote the normalization of tumor vessels, improve the structure and function of tumor vessels, increase the number of functional vessels in the tumor, and reduce the number of ineffective vessels. It is beneficial to promote the penetration of anti-tumor drugs into the tumor, improve the microenvironment of tumor hypoxia and immunosuppression, and enhance the anti-tumor effect. Traditional Chinese medicine(TCM) has a long history of understanding the etiology and pathogenesis of tumors and has accumulated rich experience in tumor treatment, with significant clinical advantages and broad application prospects. In this study, from the perspective of bidirectional "soothing" or "blockage" regulation of tumor vessels, the commonly used molecular targets were sorted out, and the research status of anti-tumor regulation of tumor vessels by monomer-single herb-compound(herb pair) of TCM in recent years was summarized. The research on the anti-tumor effects of TCM compounds and active ingredients by regulating tumor vessels combined with other therapies was analyzed and sorted out, so as to provide ideas for the clinical application of TCM in regulating functions and anti-tumor effects of tumor vessels.

[Q-marker prediction of resin ethanol extract of Gegen Qinlian Decoction based on characteristic spectrum and network pharmacology].

The resin ethanol extract of Gegen Qinlian Decoction(GGQLD) has been found to significantly alleviate the intestinal toxicity caused by Irinotecan, but further research is needed to establish its overall quality and clinical medication standards. This study aimed to establish an HPLC characteristic fingerprint of the resin ethanol extract of GGQLD, predicted the targets and signaling pathways of its pharmacological effects based on network pharmacology, identified core compounds with pharmacological relevance, and analyzed potential quality markers(Q-markers) of the resin eluate of GGQLD for relieving Irinotecan-induced toxicity. By considering the uniqueness, measurability, and traceability of Q-markers based on the "five principles" of Q-markers and combining them with network pharmacology techniques, the overall efficacy of the resin ethanol extract of GGQLD can be characterized. Preliminary predictions suggested that the four components of puerarin, berberine, baicalin, and baicalein might serve as potential Q-markers for the resin etha-nol extract of GGQLD. This study provides a basis and references for the quality control and clinical mechanism of the resin ethanol extract of GGQLD.

[Equivalence of combined decoction and mixed single decoctions of Gegen Qinlian Decoction in alleviating chemotherapy-associated diarrhea].

This study compared the chemical profiles, component content, dry paste yield, and pharmacological effects of samples obtained from the mixed single decoctions and the combined decoction of Gegen Qinlian Decoction(GQD), aiming to provide an experimental foundation for evaluating the equivalence of the two decocting methods and the suitability of TCM formula granules in clinical application. The same decoction process was used to prepare the combined decoction and mixed single decoctions of GQD. Ultra-performance liquid chromatography coupled with Q-Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap MS) was employed to compare the chemical profiles between the two groups. High-performance liquid chromatography(HPLC) was used to compare the content of nine characteristic components between the two groups. Then, a delayed diarrhea mouse model induced by irinotecan was established to compare the pharmacological effects of the two groups on chemotherapy-induced diarrhea. The UPLC-Q-Exactive Orbitrap MS in ESI~+ and ESI~- modes identified 59 chemical components in the compound decoction and mixed single decoctions, which showed no obvious differences in component species. The content of baicalin and wogonoside was higher in the compound decoction, while that of puerarin, daidzein-8-C-apiosylglucoside, berberine, epiberberine, wogonin, glycyrrhizic acid, and daidzein was higher in the mixed single decoctions. Further statistical analysis revealed no significant difference in the content of the nine characteristic components between the compound decoction and the mixed single decoctions. The dry paste yield had no significant difference between the two groups. Compared with the model group, both compound decoction and mixed single decoctions alleviated the weight loss and reduced diarrhea index in mice. Both of them lowered the levels of tumor necrosis factor-α(TNF-α), interleukin-1ß(IL-1ß), cyclooxygenase-2(COX-2), intercellular adhesion molecule-1(ICAM-1), interleukin-10(IL-10), malondialdehyde(MDA), and nitric oxide(NO) in the colon tissue. Furthermore, they significantly increased the levels of glutathione peroxidase(GSH-Px) and superoxide dismutase(SOD). Hematoxylin-eosin(HE) staining showed that colon tissue cells were tightly arranged with clear nuclei in both groups without obvious difference. The compound decoction and mixed single decoctions showed no significant differences in chemical component species, content of nine characteristic components, dry paste yield, or the pharmacological effects on alleviating chemotherapy-induced diarrhea. The findings provide a reference for evaluating the flexibility and superiority of combined or single decocting method in the preparation of TCM decoctions or formula granules.

Cobaloxime-Integrated Covalent Organic Frameworks for Photocatalytic Hydrogen Evolution Coupled with Alcohol Oxidation.

We report an azide-functionalized cobaloxime proton-reduction catalyst covalently tethered into the Wurster-type covalent organic frameworks (COFs). The cobaloxime-modified COF photocatalysts exhibit enhanced photocatalytic activity for hydrogen evolution reaction (HER) in alcohol-containing solution with no presence of a typical sacrificial agent. The best performing cobaloxime-modified COF hybrid catalyzes hydrogen production with an average HER rate up to 38 µmol h-1 in ethanol/phosphate buffer solution under 4 h illumination. Ultrafast transient optical spectroscopy characterizations and charge carrier analysis reveal that the alcohol contents functioning as hole scavengers could be oxidized by the photogenerated holes of COFs to form aldehydes and protons. The consumption of the photogenerated holes thus suppresses exciton recombination of COFs and improves the ratio of free electrons that were effectively utilized to drive catalytic reaction for HER. This work demonstrates a great potential of COF-catalyzed HER using alcohol solvents as hole scavengers and provides an example toward realizing the accessibility to the scope of reaction conditions and a greener route for energy conversion.

Analytical validation of the Percepta genomic sequencing classifier; an RNA next generation sequencing assay for the assessment of Lung Cancer risk of suspicious pulmonary nodules.

BACKGROUND: Bronchoscopy is a common procedure used for evaluation of suspicious lung nodules, but the low diagnostic sensitivity of bronchoscopy often results in inconclusive results and delays in treatment. Percepta Genomic Sequencing Classifier (GSC) was developed to assist with patient management in cases where bronchoscopy is inconclusive. Studies have shown that exposure to tobacco smoke alters gene expression in airway epithelial cells in a way that indicates an increased risk of developing lung cancer. Percepta GSC leverages this idea of a molecular "field of injury" from smoking and was developed using RNA sequencing data generated from lung bronchial brushings of the upper airway. A Percepta GSC score is calculated from an ensemble of machine learning algorithms utilizing clinical and genomic features and is used to refine a patient's risk stratification. METHODS: The objective of the analysis described and reported here is to validate the analytical performance of Percepta GSC. Analytical performance studies characterized the sensitivity of Percepta GSC test results to input RNA quantity, the potentially interfering agents of blood and genomic DNA, and the reproducibility of test results within and between processing runs and between laboratories. RESULTS: Varying the amount of input RNA into the assay across a nominal range had no significant impact on Percepta GSC classifier results. Bronchial brushing RNA contaminated with up to 10% genomic DNA by nucleic acid mass also showed no significant difference on classifier results. The addition of blood RNA, a potential contaminant in the bronchial brushing sample, caused no change to classifier results at up to 11% contamination by RNA proportion. Percepta GSC scores were reproducible between runs, within runs, and between laboratories, varying within less than 4% of the total score range (standard deviation of 0.169 for scores on 4.57 scale). CONCLUSIONS: The analytical sensitivity, analytical specificity, and reproducibility of Percepta GSC laboratory results were successfully demonstrated under conditions of expected day to day variation in testing. Percepta GSC test results are analytically robust and suitable for routine clinical use.

Regorafenib-Attenuated, Bleomycin-Induced Pulmonary Fibrosis by Inhibiting the TGF-ß1 Signaling Pathway.

Idiopathic pulmonary fibrosis (IPF) is a fatal and age-related pulmonary disease. Nintedanib is a receptor tyrosine kinase inhibitor, and one of the only two listed drugs against IPF. Regorafenib is a novel, orally active, multi-kinase inhibitor that has similar targets to nintedanib and is applied to treat colorectal cancer and gastrointestinal stromal tumors in patients. In this study, we first identified that regorafenib could alleviate bleomycin-induced pulmonary fibrosis in mice. The in vivo experiments indicated that regorafenib suppresses collagen accumulation and myofibroblast activation. Further in vitro mechanism studies showed that regorafenib inhibits the activation and migration of myofibroblasts and extracellular matrix production, mainly through suppressing the transforming growth factor (TGF)-ß1/Smad and non-Smad signaling pathways. In vitro studies have also indicated that regorafenib could augment autophagy in myofibroblasts by suppressing TGF-ß1/mTOR (mechanistic target of rapamycin) signaling, and could promote apoptosis in myofibroblasts. In conclusion, regorafenib attenuates bleomycin-induced pulmonary fibrosis by suppressing the TGF-ß1 signaling pathway.

Rational Synthesis of Amorphous Iron-Nickel Phosphonates for Highly Efficient Photocatalytic Water Oxidation with Almost 100 % Yield.

A simple solvent ligation effect was successfully used to disrupt the growth of a model compound, Fe[(OH)(O3 P(CH2 )2 CO2 H)]⋅H2 O (MIL-37), into an extended 2D structure by replacing water with dimethylformamide (DMF) as the solvent during the synthesis. Owing to the lack of -OH group, which provides the corner-sharing (binding) oxygen atoms for the octahedra, an amorphous and porous structure is formed. When Fe3+ is partially replaced by Ni2+ , the amorphous structure remains and the resultant binary metal catalyst displays excellent photocatalytic oxygen evolution activity with almost 100 % yield achieved under visible light irradiation using [Ru(bpy)3 ]2+ as the photosensitizer. This study opens up new possibilities of using the simple solvent effect to synthesize high surface area metal phosphonates for catalytic and other applications.

A multi-faceted approach to characterizing user behavior and experience in a digital mental health intervention.

Digital interventions offer great promise for supporting health-related behavior change. However, there is much that we have yet to learn about how people respond to them. In this study, we present a novel mixed-methods approach to analysis of the complex and rich data that digital interventions collect. We perform secondary analysis of IntelliCare, an intervention in which participants are able to try 14 different mental health apps over the course of eight weeks. The goal of our analysis is to characterize users' app use behavior and experiences, and is rooted in theoretical conceptualizations of engagement as both usage and user experience. In the first aim, we employ cluster analysis to identify subgroups of participants that share similarities in terms of the frequency of their usage of particular apps, and then employ other engagement measures to compare the clusters. We identified four clusters with different app usage patterns: Low Usage, High Usage, Daily Feats Users, and Day to Day users. Each cluster was distinguished by its overall frequency of app use, or the main app that participants used. In the second aim, we developed a computer-assisted text analysis and visualization method - message highlighting - to facilitate comparison of the clusters. Last, we performed a qualitative analysis using participant messages to better understand the mechanisms of change and usability of salient apps from the cluster analysis. Our novel approach, integrating text and visual analytics with more traditional qualitative analysis techniques, can be used to generate insights concerning the behavior and experience of users in digital health contexts, for subsequent personalization and to identify areas for improvement of intervention technologies.

Amino-Assisted Anchoring of CsPbBr3 Perovskite Quantum Dots on Porous g-C3 N4 for Enhanced Photocatalytic CO2 Reduction.

Halide perovskite quantum dots (QDs) have great potential in photocatalytic applications if their low charge transportation efficiency and chemical instability can be overcome. To circumvent these obstacles, we anchored CsPbBr3 QDs (CPB) on NHx -rich porous g-C3 N4 nanosheets (PCN) to construct the composite photocatalysts via N-Br chemical bonding. The 20 CPB-PCN (20 wt % of QDs) photocatalyst exhibits good stability and an outstanding yield of 149 µmol h-1 g-1 in acetonitrile/water for photocatalytic reduction of CO2 to CO under visible light irradiation, which is around 15 times higher than that of CsPbBr3 QDs. This study opens up new possibilities of using halide perovskite QDs for photocatalytic application.

Viscoelastic deformation of lipid bilayer vesicles.

Lipid bilayers form the boundaries of the cell and its organelles. Many physiological processes, such as cell movement and division, involve bending and folding of the bilayer at high curvatures. Currently, bending of the bilayer is treated as an elastic deformation, such that its stress-strain response is independent of the rate at which bending strain is applied. We present here the first direct measurement of viscoelastic response in a lipid bilayer vesicle. We used a dual-beam optical trap (DBOT) to stretch 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) giant unilamellar vesicles (GUVs). Upon application of a step optical force, the vesicle membrane deforms in two regimes: a fast, instantaneous area increase, followed by a much slower stretching to an eventual plateau deformation. From measurements of dozens of GUVs, the average time constant of the slower stretching response was 0.225 ± 0.033 s (standard deviation, SD). Increasing the fluid viscosity did not affect the observed time constant. We performed a set of experiments to rule out heating by laser absorption as a cause of the transient behavior. Thus, we demonstrate here that the bending deformation of lipid bilayer membranes should be treated as viscoelastic.

Self-Amplified pH/ROS Dual-Responsive Co-Delivery Nano-System with Chemo-Photodynamic Combination Therapy in Hepatic Carcinoma Treatment.

Background: Chemo-photodynamic combination therapy has demonstrated significant potential in the treatment of cancer. Triptolide (TPL), a naturally derived anticancer agent, when combined with the photosensitizer Chlorin e6 (Ce6), has shown to provide enhanced anti-tumor benefits. However, the development of stimuli-responsive nanovehicles for the co-delivery of TPL and Ce6 could further enhance the efficacy of this combination therapy. Methods: In this study, we synthesized a pH/ROS dual-responsive mPEG-TK-PBAE copolymer, which contains a pH-sensitive PBAE moiety and a ROS-sensitive thioketal (TK) linkage. Through a self-assembly process, TPL and Ce6 were successfully co-loaded into mPEG-TK-PBAE nanoparticles, hereafter referred to as TPL/Ce6 NPs. We evaluated the pH- and ROS-sensitive drug release and particle size changes. Furthermore, we investigated both the in vitro suppression of cellular proliferation and induction of apoptosis in HepG2 cells, as well as the in vivo anti-tumor efficacy of TPL/Ce6 NPs in H22 xenograft nude mice. Results: The mPEG-TK-PBAE copolymer was synthesized through a one-pot Michael-addition reaction and successfully co-encapsulated both TPL and Ce6 by self-assembly. Upon exposure to acid pH values and high ROS levels, the payloads in TPL/Ce6 NPs were rapidly released. Notably, the abundant ROS generated by the released Ce6 under laser irradiation further accelerated the degradation of the nanosystem, thereby amplifying the tumor microenvironment-responsive drug release and enhancing anticancer efficacy. Consequently, TPL/Ce6 NPs significantly increased PDT-induced oxidative stress and augmented TPL-induced apoptosis in HepG2 cells, leading to synergistic anticancer effects in vitro. Moreover, administering TPL/Ce6 NPs (containing 0.3 mg/kg of TPL and 4 mg/kg of Ce6) seven times, accompanied by 650 nm laser irradiation, efficiently inhibited tumor growth in H22 tumor-bearing mice, while exhibiting lower systemic toxicity. Conclusion: Overall, we have developed a tumor microenvironment-responsive nanosystem for the co-delivery of TPL and Ce6, demonstrating amplified synergistic effects of chemo-photodynamic therapy (chemo-PDT) for hepatocellular carcinoma (HCC) treatment.

Pazopanib attenuated bleomycin-induced pulmonary fibrosis via suppressing TGF-ß1 signaling pathway.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease with a high mortality rate and limited treatment efficacy. Nintedanib, a tyrosine kinase inhibitor, is clinically used to treat pulmonary fibrosis. At present, only nintedanib is on the market for the treatment of pulmonary fibrosis. Pazopanib is a drug for the treatment of renal cell carcinoma and advanced soft tissue sarcoma. Methods: In this study, we explored whether pazopanib can attenuate bleomycin (BLM)-induced pulmonary fibrosis and explored its antifibrotic mechanism. In vivo and in vitro investigations were carried out to investigate the efficacy and mechanism of action of pazopanib in pulmonary fibrosis. Results: In vivo experiments showed that pazopanib can alleviate pulmonary fibrosis caused by BLM, reduce the degree of collagen deposition and improve lung function. In vitro experiments showed that pazopanib suppressed transforming growth factor-ß1 (TGF-ß1)-induced myofibroblast activation and promoted apoptosis and autophagy in myofibroblasts. Further mechanistic studies demonstrated that pazopanib inhibited the TGF-ß1/Smad and non-Smad signaling pathways during fibroblast activation. Conclusions: In conclusion, pazopanib attenuated BLM-induced pulmonary fibrosis by suppressing the TGF-ß1 signaling pathway. Pazopanib inhibits myofibroblast activation, migration, autophagy, apoptosis, and extracellular matrix (ECM) buildup by downregulating the TGF-ß1/Smad signal route and the TGF-ß1/non-Smad signal pathway. It has the same target as nintedanib and is a tyrosine kinase inhibitor.

A multicenter proof-of-concept study on deep learning-based intraoperative discrimination of primary central nervous system lymphoma.

Accurate intraoperative differentiation of primary central nervous system lymphoma (PCNSL) remains pivotal in guiding neurosurgical decisions. However, distinguishing PCNSL from other lesions, notably glioma, through frozen sections challenges pathologists. Here we sought to develop and validate a deep learning model capable of precisely distinguishing PCNSL from non-PCNSL lesions, especially glioma, using hematoxylin and eosin (H&E)-stained frozen whole-slide images. Also, we compared its performance against pathologists of varying expertise. Additionally, a human-machine fusion approach integrated both model and pathologic diagnostics. In external cohorts, LGNet achieved AUROCs of 0.965 and 0.972 in distinguishing PCNSL from glioma and AUROCs of 0.981 and 0.993 in differentiating PCNSL from non-PCNSL lesions. Outperforming several pathologists, LGNet significantly improved diagnostic performance, further augmented to some extent by fusion approach. LGNet's proficiency in frozen section analysis and its synergy with pathologists indicate its valuable role in intraoperative diagnosis, particularly in discriminating PCNSL from glioma, alongside other lesions.

An interpretable deep learning model for identifying the morphological characteristics of dMMR/MSI-H gastric cancer.

Accurate tumor diagnosis by pathologists relies on identifying specific morphological characteristics. However, summarizing these unique morphological features in tumor classifications can be challenging. Although deep learning models have been extensively studied for tumor classification, their indirect and subjective interpretation obstructs pathologists from comprehending the model and discerning the morphological features accountable for classifications. In this study, we introduce a new approach utilizing Style Generative Adversarial Networks, which enables a direct interpretation of deep learning models to detect significant morphological characteristics within datasets representing patients with deficient mismatch repair/microsatellite instability-high gastric cancer. Our approach effectively identifies distinct morphological features crucial for tumor classification, offering valuable insights for pathologists to enhance diagnostic accuracy and foster professional growth.

Quantitative single-molecule study reveals site-specific photo-oxidation activities and kinetics on 2D g-C3N4.

We report the utilization of single-molecule fluorescence microscopy to in situ quantify the photo-oxidation reaction kinetics on g-C3N4. The wrinkle structure shows the highest reactivity and direct dissociation rate. The basal plane exhibits the highest affinity to reactants and products and indirect dissociation rate constant, followed by edges and wrinkles.