The characteristics of intratumoral microbial community reflect the development of lung adenocarcinoma.

Introduction: An increasing number of studies have demonstrated the pivotal role of microbiota changes in the onset, progression, diagnosis, treatment, and prognosis of lung adenocarcinoma (LUAD). However, a comprehensive analysis of intratumoral microbiome variation across distinct LUAD stages has not been performed. The aim of this study was to identify the microbial markers that significantly vary during tumor stage of LUAD. Methods: Here, we used the cancer genome atlas (TCGA) database to comprehensively compare and analyze the differences in microbial composition between 267 patients with early and 224 patients with advanced LUAD. In order to determine the best biomarkers, we used the random forest (RF) model and found that the microbial markers have a certain ability in predicting the stage of LUAD. Results: We found that there were certain differences in the microbiome of patients with LUAD at different stages, especially in the tumor tissues of patients with advanced LUAD, whose co-abundance network was significantly more complex. We also found that five bacterial biomarkers (Pseudoalteromonas, Luteibacter, Caldicellulosiruptor, Loktanella, and Serratia) were correlated with LUAD stage, among which Pseudoalteromonas, Luteibacter, Caldicellulosiruptor, and Serratia were significantly overexpressed in patients with advanced LUAD. In particular, after integrating the biomarkers of mRNA, we achieved an area under the curve (AUC) of 0.70. Discussion: Our study revealed the microbial profile of patients with LUAD and the intrinsic pathogenic mechanism between the microbiome and the disease, and established a multi-omics model to determine LUAD tumor stage.

Surface Reconstruction for Selective Oxidation of Tetrahydroisoquinoline.

Integration of hydrogen evolution with the oxidation of organic substances in one electrochemical system is highly desirable. However, achieving selective oxidation of organic substances in the integrated system is still highly challenging. In this study, a phosphorylated NiMoO4 nanoneedle-like array was designed as the catalytic active electrode for the integration of highly selective electrochemical dehydrogenation of tetrahydroisoquinolines (THIQs) with hydrogen production. The leaching of anions, including MoO42- and PO43-, facilitates the reconstruction of the catalyst. As a result, nickel oxyhydroxides with the doping of PO43- and richness of defects are in situ formed. In situ Raman and density functional theory calculations have shown that the high catalytic activity is attributed to the in situ formed PO43- involved NiOOH substance. In the dehydrogenation process, the involved C-H bond but not the N-H bond is first destroyed. A two-electrode system was then fabricated with the optimized electrode that shows a benchmark current density of 10 mA cm-2 at 1.783 V, providing a yield of 70% for dihydroisoquinolines. A robust stability was also shown for this integrated electrochemical system. The understanding of the reconstruction behavior and the achievement of selective dehydrogenation will provide some hints for electrochemical synthesis.

Logic-Based Strategy for Spatiotemporal Release of Dual Extracellular Vesicles in Osteoarthritis Treatment.

To effectively treat osteoarthritis (OA), the existing inflammation must be reduced before the cartilage damage can be repaired; this cannot be achieved with a single type of extracellular vesicles (EVs). Here, a hydrogel complex with logic-gates function is proposed that can spatiotemporally controlled release two types of EVs: interleukin 10 (IL-10)+ EVs to promote M2 polarization of macrophage, and SRY-box transcription factor 9 (SOX9)+ EVs to increase cartilage matrix synthesis. Following dose-of-action screening, the dual EVs are loaded into a matrix metalloporoteinase 13 (MMP13)-sensitive self-assembled peptide hydrogel (KM13E) and polyethylene glycol diacrylate/gelatin methacryloyl-hydrogel microspheres (PGE), respectively. These materials are mixed to form a "microspheres-in-gel" KM13E@PGE system. In vitro, KM13E@PGE abruptly released IL-10+ EVs after 3 days and slowly released SOX9+ EVs for more than 30 days. In vivo, KM13E@PGE increased the CD206+ M2 macrophage proportion in the synovial tissue and decreased the tumor necrosis factor-α and IL-1ß levels. The aggrecan and SOX9 expressions in the cartilage tissues are significantly elevated following inflammation subsidence. This performance is not achieved using anti-inflammatory or cartilage repair therapy alone. The present study provides an injectable, integrated delivery system with spatiotemporal control release of dual EVs, and may inspire logic-gates strategies for OA treatment.

Nanofiber-induced hierarchically-porous magnesium phosphate bone cements accelerate bone regeneration by inhibiting Notch signaling.

Magnesium phosphate bone cements (MPC) have been recognized as a viable alternative for bone defect repair due to their high mechanical strength and biodegradability. However, their poor porosity and permeability limit osteogenic cell ingrowth and vascularization, which is critical for bone regeneration. In the current study, we constructed a novel hierarchically-porous magnesium phosphate bone cement by incorporating extracellular matrix (ECM)-mimicking electrospun silk fibroin (SF) nanofibers. The SF-embedded MPC (SM) exhibited a heterogeneous and hierarchical structure, which effectively facilitated the rapid infiltration of oxygen and nutrients as well as cell ingrowth. Besides, the SF fibers improved the mechanical properties of MPC and neutralized the highly alkaline environment caused by excess magnesium oxide. Bone marrow stem cells (BMSCs) adhered excellently on SM, as illustrated by formation of more pseudopodia. CCK8 assay showed that SM promoted early proliferation of BMSCs. Our study also verified that SM increased the expression of OPN, RUNX2 and BMP2, suggesting enhanced osteogenic differentiation of BMSCs. We screened for osteogenesis-related pathways, including FAK signaing, Wnt signaling and Notch signaling, and found that SM aided in the process of bone regeneration by suppressing the Notch signaling pathway, proved by the downregulation of NICD1, Hes1 and Hey2. In addition, using a bone defect model of rat calvaria, the study revealed that SM exhibited enhanced osteogenesis, bone ingrowth and vascularization compared with MPC alone. No adverse effect was found after implantation of SM in vivo. Overall, our novel SM exhibited promising prospects for the treatment of critical-sized bone defects.

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis.

Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.

A microcosm evaluation of metal cycling in an urbanized contaminated estuary varying with oxic-hypoxic-anoxic-reoxic transition: Behavior, fluxes, and mechanism.

Water hypoxia and metal pollution are commonly co-existed in urbanized estuaries. This study focuses on the effect of an extended dissolved oxygen (DO) full-life dynamics (86 days) on metal behavior across the sediment-water interface through laboratory microcosms from two typical zones in Pearl River Estuary. Combining our time-series results of concentrations and fluxes, it showed that Co, Ni, and Zn consistently presented a release-precipitation-release trajectory with an oxic-hypoxic-anoxic-reoxic transition, characterized with highly variable behavior in the hypoxic-anoxic hotmoments. In parallel, changing DO dynamics significantly activated a repartitioning process of Co, Ni, and Zn among several species and elevated their risk in sediments, promoting the formation of more labile species in the 0-10 mm hotspots, where metals sensitively responded. Over DO transition, metal cycling was tightly co-related with Fe, Mn, and S elements. It was found that Mn was dominated in low oxygen-hypoxic period, but switched to S and Fe in anoxic stage, limiting sustained metal liberation to overlying water. Enlarging this experiment to practice, released Zn fluxes from sediments in hypoxic summer could contribute about ∼2.0% to their stocks in water column, while increase to 20% (1 m bottom water) in highly-stratified zones. This study has certain significance in understanding the long-term metal behavior and fate in estuarine regions, even lakes and reservoirs.

FOXF1 reverses lung fibroblasts transdifferentiation via inhibiting TGF-ß/SMAD2/3 pathway in silica-induced pulmonary fibrosis.

Silicosis is one of the most common and severe types of pneumoconiosis and is characterized by lung dysfunction, persistent lung inflammation, pulmonary nodule formation, and irreversible pulmonary fibrosis. The transdifferentiation of fibroblasts into myofibroblasts is one of the main reasons for the exacerbation of silicosis. However, the underlying mechanism of transcription factors regulating silicosis fibrosis has not been clarified. The aim of this study was to investigate the potential mechanism of transcription factor FOXF1 in fibroblast transdifferentiation in silica-induced pulmonary fibrosis. Therefore, a silicosis mouse model was established, and we found that FOXF1 expression level was significantly down-regulated in the silicosis group, and after overexpression of FOXF1 by adeno-associated virus (AAV), FOXF1 expression level was up-regulated, and silicosis fibrosis was alleviated. In order to further explore the specific regulatory mechanism of FOXF1 in silicosis, we established a fibroblasts transdifferentiation model induced by TGF-ß in vitro. In the model, the expression levels of SMAD2/3 and P-SMAD2/3 were up-regulated, but the expression levels of SMAD2/3 and P-SMAD2/3 were down-regulated, inhibiting transdifferentiation and accumulation of extracellular matrix after the overexpressed FOXF1 plasmid was constructed. However, after silencing FOXF1, the expression levels of SMAD2/3 and P-SMAD2/3 were further up-regulated, aggravating transdifferentiation and accumulation of extracellular matrix. These results indicate that the activation of FOXF1 in fibroblasts can slow down the progression of silicosis fibrosis by inhibiting TGF-ß/SMAD2/3 classical pathway, which provides a new idea for further exploration of silicosis treatment.

Green finance and high-pollution corporate compensation - Empirical evidence from green credit guidelines.

With the increasing focus on Environmental, Social, and Governance (ESG) and Corporate Social Responsibility (CSR) on a global scale, stakeholders expect businesses to transform and enhance social responsibility. Over time, ESG and CSR have developed into vital performance metrics for businesses. Businesses are actively putting improvement measures into place in response to this new paradigm in order to stay competitive in this changing environment. China's dual commitment to CSR and sustainable development is in line with wider objectives, such as resolving issues of pay inequality. In 2012, the China Banking Regulatory Commission (CBRC) unveiled the "Green Credit Guidelines" (GCG), which take corporate governance's environmental considerations into account. These regulations set standards and specifically target high-pollution corporations. Companies may need to restructure their corporate structures and create efficient governance mechanisms in order to comply with these regulations and reduce carbon emissions. This will have an impact on the compensation packages of executives and regular employees. The most important question is how the "GCG" will affect the wage disparity in highly polluting companies. This study examines the 2012 "GCG" and its potential to reduce internal wage disparities, viewing it as a critical element of green financial policy. The paper uses data from Chinese A-share listed companies from 2007 to 2020. Besides, it uses the Difference-in-Differences method to assess the impact of China's GCG, treating its implementation as a quasi-natural experiment and controlling for concurrent policy effects to precisely identify its net impact on corporate carbon emissions and internal wage disparities. The findings show that "GCG" considerably closed internal wage disparities. Furthermore, the "GCG" has a path of guidance, incentives, and punishments that reduce internal wage disparities and promote a more equitable wage distribution within businesses. According to heterogeneity analysis, policies have a greater impact on the wage gap in businesses that are highly dependent on outside funding and have political connection. In order to achieve a compensation balance and meet the objectives of social responsibility and corporate sustainable development, the government should strengthen the complementary effects of green financial policies. The compensation balance in highly polluting companies has important theoretical and practical ramifications. On the one hand, it represents the convergence of income equality, corporate governance, and environmental responsibility. It helps to expand knowledge of sustainable development, fair compensation, and environmental policies. On the other hand, the widening pay disparity between executives and average employees reflects the exacerbation of income inequality in China, which could potentially impact companies' long-term development. Conversely, a well-balanced pay plan can improve worker productivity and motivation while empowering stakeholders to make wise investment choices.

A Gnotobiotic Mouse Model with Divergent Equol-Producing Phenotypes: Potential for Determining Microbial-Driven Health Impacts of Soy Isoflavone Daidzein.

The implications of soy consumption on human health have been a subject of debate, largely due to the mixed evidence regarding its benefits and potential risks. The variability in responses to soy has been partly attributed to differences in the metabolism of soy isoflavones, compounds with structural similarities to estrogen. Approximately one-third of humans possess gut bacteria capable of converting soy isoflavone daidzein into equol, a metabolite produced exclusively by gut microbiota with significant estrogenic potency. In contrast, lab-raised rodents are efficient equol producers, except for those raised germ-free. This discrepancy raises concerns about the applicability of traditional rodent models to humans. Herein, we designed a gnotobiotic mouse model to differentiate between equol producers and non-producers by introducing synthetic bacterial communities with and without the equol-producing capacity into female and male germ-free mice. These gnotobiotic mice display equol-producing phenotypes consistent with the capacity of the gut microbiota received. Our findings confirm the model's efficacy in mimicking human equol production capacity, offering a promising tool for future studies to explore the relationship between endogenous equol production and health outcomes like cardiometabolic health and fertility. This approach aims to refine dietary guidelines by considering individual microbiome differences.

Understanding Heterogeneity in Individual Responses to Digital Lifestyle Intervention Through Self-Monitoring Adherence Trajectories in Adults With Overweight or Obesity: Secondary Analysis of a 6-Month Randomized Controlled Trial.

BACKGROUND: Achieving clinically significant weight loss through lifestyle interventions for obesity management is challenging for most individuals. Improving intervention effectiveness involves early identification of intervention nonresponders and providing them with timely, tailored interventions. Early and frequent self-monitoring (SM) adherence predicts later weight loss success, making it a potential indicator for identifying nonresponders in the initial phase. OBJECTIVE: This study aims to identify clinically meaningful participant subgroups based on longitudinal adherence to SM of diet, activity, and weight over 6 months as well as psychological predictors of participant subgroups from a self-determination theory (SDT) perspective. METHODS: This was a secondary data analysis of a 6-month digital lifestyle intervention for adults with overweight or obesity. The participants were instructed to perform daily SM on 3 targets: diet, activity, and weight. Data from 50 participants (mean age: 53.0, SD 12.6 y) were analyzed. Group-based multitrajectory modeling was performed to identify subgroups with distinct trajectories of SM adherence across the 3 SM targets. Differences between subgroups were examined for changes in clinical outcomes (ie, body weight, hemoglobin A1c) and SDT constructs (ie, eating-related autonomous motivation and perceived competence for diet) over 6 months using linear mixed models. RESULTS: Two distinct SM trajectory subgroups emerged: the Lower SM group (21/50, 42%), characterized by all-around low and rapidly declining SM, and the Higher SM group (29/50, 58%), characterized by moderate and declining diet and weight SM with high activity SM. Since week 2, participants in the Lower SM group exhibited significantly lower levels of diet (P=.003), activity (P=.002), and weight SM (P=.02) compared with the Higher SM group. In terms of clinical outcomes, the Higher SM group achieved a significant reduction in body weight (estimate: -6.06, SD 0.87 kg; P<.001) and hemoglobin A1c (estimate: -0.38, SD 0.11%; P=.02), whereas the Lower SM group exhibited no improvements. For SDT constructs, both groups maintained high levels of autonomous motivation for over 6 months. However, the Lower SM group experienced a significant decline in perceived competence (P=.005) compared with the Higher SM group, which maintained a high level of perceived competence throughout the intervention (P=.09). CONCLUSIONS: The presence of the Lower SM group highlights the value of using longitudinal SM adherence trajectories as an intervention response indicator. Future adaptive trials should identify nonresponders within the initial 2 weeks based on their SM adherence and integrate intervention strategies to enhance perceived competence in diet to benefit nonresponders. TRIAL REGISTRATION: ClinicalTrials.gov NCT05071287; https://clinicaltrials.gov/study/NCT05071287. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.cct.2022.106845.

Combination of S100A12/TLR2 signaling molecules and clinical indicators in a new predictive model for IVIG-resistant Kawasaki disease.

Although intravenous immunoglobulin (IVIG)-resistant Kawasaki disease (KD) presents with persistent inflammatory stimulation of the blood vessels and an increased risk of coronary artery dilatation. However, the pathogenesis of this disease is unclear, with no established biomarkers to predict its occurrence. This study intends to explore the utility of S100A12/TLR2-related signaling molecules and clinical indicators in the predictive modeling of IVIG-resistant KD. The subjects were classified according to IVIG treatment response: 206 patients in an IVIG-sensitive KD group and 49 in an IVIG-resistant KD group. Real-time PCR was used to measure the expression of S100A12, TLR2, MYD88, and NF-κB in peripheral blood mononuclear cells of patients, while collecting demographic characteristics, clinical manifestations, and laboratory test results of KD children. Multi-factor binary logistic regression analysis identified procalcitonin (PCT) level (≥ 0.845 ng/mL), Na level (≤ 136.55 mmol/L), and the relative expression level of S100A12 (≥ 10.224) as independent risk factors for IVIG-resistant KD and developed a new scoring model with good predictive ability to predict the occurrence of IVIG-resistant KD.

SIRT3 and SIRT4 double-genes remodeled the mitochondrial network to induce hepatocellular carcinoma cell line differentiation and suppress malignant phenotypes.

Tumor cells with damaged mitochondria undergo metabolic reprogramming, but gene therapy targeting mitochondria has not been comprehensively reported. In this study, plasmids targeting the normal hepatocyte cell line (L-O2) and hepatocellular carcinoma cell line were generated using three genes SIRT3, SIRT4, and SIRT5. These deacetylases play a variety of regulatory roles in cancer and are related to mitochondrial function. Compared with L-O2, SIRT3 and SIRT4 significantly ameliorated mitochondrial damage in HCCLM3, Hep3B and HepG2 cell lines and regulated mitochondrial biogenesis and mitophagy, respectively. We constructed double-gene plasmid for co-express SIRT3 and SIRT4 using the internal ribosome entry site (IRES). The results indicated that the double-gene plasmid effectively expressed SIRT3 and SIRT4, significantly improved mitochondrial quality and function, and reduced mtDNA level and oxidative stress in HCC cells. MitoTracker analysis revealed that the mitochondrial network was restored. The proliferation, migration capabilities of HCC cells were reduced, whereas their differentiation abilities were enhanced. This study demonstrated that the use of IRES-linked SIRT3 and SIRT4 double-gene vectors induced the differentiation of HCC cells and inhibited their development by ameliorating mitochondrial dysfunction. This intervention helped reverse metabolic reprogramming, and may provide a groundbreaking new framework for HCC treatment.

Realization of Fine-Tuning the Lattice Thermal Conductivity and Anharmonicity in Layered Semiconductors via Entropy Engineering.

Entropy engineering is widely proven to be effective in achieving ultra-low thermal conductivity for well-performed thermoelectric and heat management applications. However, no strong correlation between entropy and lattice thermal conductivity is found until now, and the fine-tuning of thermal conductivity continuously via entropy-engineering in a wide entropy range is still lacking. Here, a series of high-entropy layered semiconductors, Ni1- x(Fe0.25Co0.25Mn0.25Zn0.25)xPS3, where 0 ≤ x < 1, with low mass/size disorder is designed. High-purity samples with mixing configuration entropy of metal atomic site in a wide range of 0-1.61R are achieved. Umklapp phonon-phonon scattering is found to be the dominating phonon scattering mechanism, as revealed by the linear T-1 dependence of thermal conductivity. Meanwhile, fine tuning of the lattice thermal conductivity via continuous entropy engineering at metal atomic sites is achieved, in an almost linear dependence in middle-/high- entropy range. Moreover, the slope of the κ - T-1 curve reduces with the increase in entropy, and a linear response of the reduced Grüneisen parameter is revealed. This work provides an entropy engineering strategy by choosing multiple metal elements with low mass/size disorder to achieve the fine tuning of the lattice thermal conductivity and the anharmonic effect.

Microplastics are detected in human gallstones and have the ability to form large cholesterol-microplastic heteroaggregates.

Ubiquitous pollution due to microplastics through the food chain is a major cause of various deleterious effects on the human health. The aim of this study was to determine the existence of microplastics and the internal mechanism of microplastics as accelerators of cholelithiasis. Gallstones were collected from 16 patients after cholecystectomy, and microplastics in the gallstones were detected through laser direct infrared and pyrolysis gas chromatographymass spectrometry examinations. Mice model of gallstone were constructed with or without different diameters of microplastic (0.5, 5 and 50 µm). The affinity between microplastic and cholesterol or bilirubin was tested by co-culturing and qualified using molecular dynamics simulations. Finally, altered gut microbiota among the groups were identified using 16 s rRNA sequencing. The presence of microplastics in the gallstones of all the patients were confirmed. Microplastic content was significantly higher in younger chololithiasis patients (age<50 years). Mice fed a high-cholesterol diet with microplastic drinks showed more severe chololithiasis. In terms of the mechanism, microplastics showed a higher affinity for cholesterol than for bilirubin. Significant alterations in the gut microbiota have also been identified after microplastic intake in mice. Our study revealed the presence of microplastics in human gallstones, showcasing their potential to aggravate chololithiasis by forming large cholesterol-microplastic heteroaggregates and altering the gut microbiota.

Decoding Heterogeneity in Data-Driven Self-Monitoring Adherence Trajectories in Digital Lifestyle Interventions for Weight Loss: A Qualitative Study.

Background: Data-driven trajectory modeling is a promising approach for identifying meaningful participant subgroups with various self-monitoring (SM) responses in digital lifestyle interventions. However, there is limited research investigating factors that underlie different subgroups. This qualitative study aimed to investigate factors contributing to participant subgroups with distinct SM trajectory in a digital lifestyle intervention over 6 months. Methods: Data were collected from a subset of participants (n = 20) in a 6-month digital lifestyle intervention. Participants were classified into Lower SM Group (n = 10) or a Higher SM (n = 10) subgroup based on their SM adherence trajectories over 6 months. Qualitative data were obtained from semi-structured interviews conducted at 3 months. Data were thematically analyzed using a constant comparative approach. Results: Participants were middle-aged (52.9 ± 10.2 years), mostly female (65%), and of Hispanic ethnicity (55%). Four major themes with emerged from the thematic analysis: Acceptance towards SM Technologies, Perceived SM Benefits, Perceived SM Barriers, and Responses When Facing SM Barriers. Participants across both subgroups perceived SM as positive feedback, aiding in diet and physical activity behavior changes. Both groups cited individual and technical barriers to SM, including forgetfulness, the burdensome SM process, and inaccuracy. The Higher SM Group displayed positive problem-solving skills that helped them overcome the SM barriers. In contrast, some in the Lower SM Group felt discouraged from SM. Both subgroups found diet SM particularly challenging, especially due to technical issues such as the inaccurate food database, the time-consuming food entry process in the Fitbit app. Conclusions: This study complements findings from our previous quantitative research, which used data-drive trajectory modeling approach to identify distinct participant subgroups in a digital lifestyle based on individuals' 6-month SM adherence trajectories. Our results highlight the potential of enhancing action planning problem solving skills to improve SM adherence in the Lower SM Group. Our findings also emphasize the necessity of addressing the technical issues associated with current diet SM approaches. Overall, findings from our study may inform the development of practical SM improvement strategies in future digital lifestyle interventions. Trial registration: The study was pre-registered at ClinicalTrials.gov (NCT05071287) on April 30, 2022.

Three new griseofulvin derivatives from Aureobasidium pullulans.

Three new griseofulvin derivatives, griseofulvinoside A-C (1-3), were isolated from the ethyl acetate extract of the solid fermentation product of Aureobasidium pullulans. Their structures were elucidated based on extensive spectroscopic data analysis of MS, 1D and 2D NMR. The antifungal activities of new compounds were evaluated against four phytopathogenic fungi in vitro, and all test compounds demonstrated inhibitory effects. Among them, compound 2 exhibited the most potent activities against the four selected phytopathogenic fungi with inhibitory rates ranging from 40.2 to 75.8% at 0.2 mg/mL.

Fast Multichannel Inverse Design through Augmented Partial Factorization.

Computer-automated design and discovery have led to high-performance nanophotonic devices with diverse functionalities. However, massively multichannel systems such as metasurfaces controlling many incident angles and photonic-circuit components coupling many waveguide modes still present a challenge. Conventional methods require Min forward simulations and Min adjoint simulations-2Min simulations in total-to compute the objective function and its gradient for a design involving the response to Min input channels. Here, we develop a formalism that uses the recently proposed augmented partial factorization method to obtain both the objective function and its gradient for a massively multichannel system in a single or a few simulations, achieving over 2 orders of magnitude speedup and reduced memory usage. We use this method to inverse design a metasurface beam splitter that separates the incident light to the target diffraction orders for all incident angles of interest, a key component of the dot projector for 3D sensing. This formalism enables efficient inverse design for a wide range of multichannel optical systems.

Exploring the Osteogenic Potential of Zinc-Doped Magnesium Phosphate Cement (ZMPC): A Novel Material for Orthopedic Bone Defect Repair.

In orthopedics, the repair of bone defects remains challenging. In previous research reports, magnesium phosphate cements (MPCs) were widely used because of their excellent mechanical properties, which have been widely used in the field of orthopedic medicine. We built a new k-struvite (MPC) cement obtained from zinc oxide (ZnO) and assessed its osteogenic properties. Zinc-doped magnesium phosphate cement (ZMPC) is a novel material with good biocompatibility and degradability. This article summarizes the preparation method, physicochemical properties, and biological properties of ZMPC through research on this material. The results show that ZMPC has the same strength and toughness (25.3 ± 1.73 MPa to 20.18 ± 2.11 MPa), that meet the requirements of bone repair. Furthermore, the material can gradually degrade (12.27% ± 1.11% in 28 days) and promote osteogenic differentiation (relative protein expression level increased 2-3 times) of rat bone marrow mesenchymal stem cells (rBMSCs) in vitro. In addition, in vivo confirmation revealed increased bone regeneration in a rat calvarial defect model compared with MPC alone. Therefore, ZMPC has broad application prospects and is expected to be an important repair material in the field of orthopedic medicine.

Sonography-based multimodal information platform for identifying the surgical pathology of ductal carcinoma in situ.

BACKGROUND: The risk of ductal carcinoma in situ (DCIS) identified by biopsy often increases during surgery. Therefore, confirming the DCIS grade preoperatively is necessary for clinical decision-making. PURPOSE: To train a three-classification deep learning (DL) model based on ultrasound (US), combining clinical data, mammography (MG), US, and core needle biopsy (CNB) pathology to predict low-grade DCIS, intermediate-to-high-grade DCIS, and upstaged DCIS. MATERIALS AND METHODS: Data of 733 patients with 754 DCIS cases confirmed by biopsy were retrospectively collected from May 2013 to June 2022 (N1), and other data (N2) were confirmed by biopsy as low-grade DCIS. The lesions were randomly divided into training (n=471), validation (n=142), and test (n = 141) sets to establish the DCIS-Net. Information on the DCIS-Net, clinical (age and sign), US (size, calcifications, type, breast imaging reporting and data system [BI-RADS]), MG (microcalcifications, BI-RADS), and CNB pathology (nuclear grade, architectural features, and immunohistochemistry) were collected. Logistic regression and random forest analyses were conducted to develop Multimodal DCIS-Net to calculate the specificity, sensitivity, accuracy, receiver operating characteristic curve, and area under the curve (AUC). RESULTS: In the test set of N1, the accuracy and AUC of the multimodal DCIS-Net were 0.752-0.766 and 0.859-0.907 in the three-classification task, respectively. The accuracy and AUC for discriminating DCIS from upstaged DCIS were 0.751-0.780 and 0.829-0.861, respectively. In the test set of N2, the accuracy and AUC of discriminating low-grade DCIS from upstaged low-grade DCIS were 0.769-0.987 and 0.818-0.939, respectively. DL was ranked from one to five in the importance of features in the multimodal-DCIS-Net. CONCLUSION: By developing the DCIS-Net and integrating it with multimodal information, diagnosing low-grade DCIS, intermediate-to high-grade DCIS, and upstaged DCIS is possible. It can also be used to distinguish DCIS from upstaged DCIS and low-grade DCIS from upstaged low-grade DCIS, which could pave the way for the DCIS clinical workflow.