Discovery of TCP-(MP)-caffeic acid analogs as a new class of agents for treatment of osteoclastic bone loss.

Inhibition of LSD1 was proposed as promising and attractive therapies for treating osteoporosis. Here, we synthesized a series of novel TCP-(MP)-Caffeic acid analogs as potential LSD1 inhibitors to assess their inhibitory effects on osteoclastogenesis by using TRAP-staining assay and try to explore the preliminary SAR. Among them, TCP-MP-CA (11a) demonstrated osteoclastic bone loss both in vitro and in vivo, showing a significant improvement in the in vivo effects compared to the LSD1 inhibitor GSK-LSD1. Additionally, we elucidated a mechanism that 11a and its precursor that 11e directly bind to LSD1/CoREST complex through FAD to inhibit LSD1 demethylation activity and influence its downstream IκB/NF-κB signaling pathway, and thus regulate osteoclastic bone loss. These findings suggested 11a or 11e as potential novel candidates for treating osteoclastic bone loss, and a concept for further development of TCP-(MP)-Caffeic acid analogs for therapeutic use in osteoporosis clinics.

HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation.

Medical image segmentation has been significantly advanced with the rapid development of deep learning (DL) techniques. Existing DL-based segmentation models are typically discriminative; i.e., they aim to learn a mapping from the input image to segmentation masks. However, these discriminative methods neglect the underlying data distribution and intrinsic class characteristics, suffering from unstable feature space. In this work, we propose to complement discriminative segmentation methods with the knowledge of underlying data distribution from generative models. To that end, we propose a novel hybrid diffusion framework for medical image segmentation, termed HiDiff, which can synergize the strengths of existing discriminative segmentation models and new generative diffusion models. HiDiff comprises two key components: discriminative segmentor and diffusion refiner. First, we utilize any conventional trained segmentation models as discriminative segmentor, which can provide a segmentation mask prior for diffusion refiner. Second, we propose a novel binary Bernoulli diffusion model (BBDM) as the diffusion refiner, which can effectively, efficiently, and interactively refine the segmentation mask by modeling the underlying data distribution. Third, we train the segmentor and BBDM in an alternate-collaborative manner to mutually boost each other. Extensive experimental results on abdomen organ, brain tumor, polyps, and retinal vessels segmentation datasets, covering four widely-used modalities, demonstrate the superior performance of HiDiff over existing medical segmentation algorithms, including the state-of-the-art transformer- and diffusion-based ones. In addition, HiDiff excels at segmenting small objects and generalizing to new datasets. Source codes are made available at https://github.com/takimailto/HiDiff.

Donor-acceptor bulk-heterojunction sensitizer for efficient solid-state infrared-to-visible photon up-conversion.

Solid-state infrared-to-visible photon up-conversion is important for spectral-tailoring applications. However, existing up-conversion systems not only suffer from low efficiencies and a need for high excitation intensity, but also exhibit a limited selection of materials and complex fabrication processes. Herein, we propose a sensitizer with a bulk-heterojunction structure, comprising both an energy donor and an energy acceptor, for triplet-triplet annihilation up-conversion devices. The up-conversion occurs through charge separation at the donor-acceptor interface, followed by the formation of charge transfer state between the energy donor and annihilator following the spin statistics. The bulk-heterojunction sensitizer ensures efficient charge generation and low charge recombination. Hence, we achieve a highly efficient solid-state up-conversion device with 2.20% efficiency and low excitation intensity (10 mW cm-2) through a one-step solution method. We also demonstrate bright up-conversion devices on highly-flexible large-area substrates. This study introduces a simple and scalable platform strategy for fabricating efficient up-conversion devices.

Novel inhibitor N-cyclopropyl-4-((4-((4-(trifluoromethyl)phenyl)sulfonyl)piperazin-1-yl)methyl)benzamide attenuates RANKL-mediated osteoclast differentiation in vitro.

Both cyclopropyl amide and piperazine sulfonamide functional groups are known for their various biological properties used for drug development. Herein, we synthesized nine new derivatives with different substituent groups incorporating these moieties and screened them for their anti-osteoclast differentiation activity. After analyzing the structure-activity relationship (SAR), the inhibitory effect against osteoclastogenesis was determined to be dependent on the lipophilicity of the compound. Derivative 5b emerged as the most effective dose-dependent inhibitor after TRAP staining with an IC50 of 0.64 µM against RANKL-induced osteoclast cells. 5b was also able to suppress F-acting ring formation and bone resorption activity of osteoclasts in vitro. Finally, well-acknowledged gene and protein osteoclast-specific marker expression levels were decreased after 5b administration on primary murine osteoclast cells.

Quantitative Trait Loci Sequencing and Genetic Mapping Reveal Two Main Regulatory Genes for Stem Color in Wax Gourds.

Stem color is an important agronomic trait of wax gourds. However, its regulatory genes have not been identified. In this study, 105 inbred lines constructed from two parents (GX-71 and MY-1) were sequenced and quantitative trait loci sequencing was used to mine the genes that regulate stem color in wax gourds. The results identified two quantitative trait loci related to stem color, qSC5 and qSC12, located on Chr05 (11,134,567-16,459,268) and Chr12 (74,618,168-75,712,335), respectively. The qSC5 had a phenotypic variation rate of 36.9% and a maximum limit of detection of 16.9. And the qSC12 had a phenotypic variation rate of 20.9%, and a maximum limit of detection of 11.2. Bch05G003950 (named BchAPRR2) and Bch12G020400 were identified as candidate genes involved in stem color regulation in wax gourds. The chlorophyll content and expression of BchAPRR2 and Bch12G020400 were significantly higher in green-stemmed wax gourds than in white-stemmed ones. Therefore, BchAPRR2 and Bch12G020400 were considered the main and secondary regulatory genes for wax gourd stem color, respectively. Finally, InDel markers closely linked to BchAPRR2 were developed to validate the prediction of wax gourd stem color traits in 55 germplasm lines, with an accuracy of 81.8%. These findings lay the foundation for exploring the genetic regulation of wax gourd stem color and future research on wax gourd breeding.

Passivating Defects and Constructing Catalytic Sites on CsPbBr3 with ZnBr2 for Photocatalytic CO2 Reduction.

In recent years, halide perovskites have attracted considerable attention for photocatalytic CO2 reduction. However, the presence of surface defects and the lack of specific catalytic sites for CO2 reduction lead to low photocatalytic performance. In this study, we demonstrate a facile method that post-treats CsPbBr3 with ZnBr2 for photocatalytic CO2 reduction. Our experimental and characterization results show that ZnBr2 has a dual role: the Br- ions in ZnBr2 passivate Br vacancies (VBr) on the CsPbBr3 surface, while Zn2+ cations act as catalytic sites for CO2 reduction. The ZnBr2-CsPbBr3 achieves a photocatalytic CO evolution rate of 57 µmol g-1 h-1, which is nearly three times higher than that of the pristine CsPbBr3. The enhanced performance over ZnBr2-CsPbBr3 is mainly due to the decreased VBr and lower reaction energy barrier for CO2 reduction. This work presents an effective method to simultaneously passivate surface defects and introduce catalytic sites, providing useful guidance for the regulation of perovskite photoelectric properties and the design of efficient photocatalysts.

Influence of Different Ions on Pulse Electrodeposition of CaCO3 Scales in the Simulated Seawater.

In the circulating water system of coastal power plants, various kinds of ions have a great influence on the formation and growth of CaCO3 scales. This paper focuses on investigating the influence of existing ions on the pulse electrodeposition behaviors of CaCO3 scales. Different concentrations of ions, such as Fe3+, Mg2+, PO43- and SiO32-, are introduced to simulate the actual seawater environment, and their influence on the CaCO3 scale deposition behaviors is assessed by linear sweep voltammetry, chronoamperometry, and electrochemical impedance spectroscopy tests. The surface coverage of the CaCO3 scale layer is evaluated through the residual current density and polarization resistance values, while the crystal structure and surface compactness of the layer are confirmed by the scanning electron microscope and X-ray diffractometer tests. Results indicate that high concentrations of Mg2+, Fe3+, and PO43- ions have the most significant inhibitory effect on the pulse electrodeposition of CaCO3 scales, among which the inhibition effect of Mg2+ ions is mainly reflected in the change of crystal morphology of CaCO3, that is, the crystallization growth process is inhibited. The inhibition effect of PO43- ions is mainly reflected in the gradually reduced coverage and density of CaCO3 crystals on the electrode surface, suggesting that the crystallization nucleation process is inhibited, while Fe3+ ions have a certain inhibition effect on both the crystallization nucleation and growth processes. Furthermore, lower concentrations of SiO32- ions also display a significant inhibition effect on the crystallization nucleation and growth process, and the inhibition effect weakens with increased concentration. This study provides a theoretical basis for exploring the removal of ions in the industrial water softening field.

Chloride Ions-Responsive Intelligent Coatings for the Active Protection of Degradable Biomedical Mg Alloys.

In this work, the hydroxyapatite (HA) microspheres are utilized as carriers for 8-hydroxyquinoline (8-HQ) inhibitors with a sodium alginate-silver nitrate layer (Ag-SA) added to confer chloride-responsive properties. These 8-HQ@Ag-SA-HA microspheres are subsequently integrated into poly(lactic acid) (PLA) coatings to produce biocompatible coatings. The resulting 8-HQ@Ag-SA-HA microsphere exhibits a spherical structure with a diameter of 3.16 µm. Thermogravimetric analysis indicates that the encapsulated 8-HQ inhibitors are approximately 11.83 wt %. Furthermore, the incorporation of these microspheres fills the micropores within the PLA coating, leading to a denser coating surface, enhanced wettability (contact angle value = 88°), and improved adhesion strength, thereby reinforcing the physical barrier effect. Corrosion tests reveal that the coatings exhibit increased resistance to corrosion in simulated body fluid (SBF) solutions. The released 8-HQ inhibitors in response to chloride ions form a protective layer of Mg(HQ)2, providing the coatings with self-healing properties and ensuring their durability in the SBF environment. Additionally, the cell test demonstrates a significant presence of MG-63 cells, accompanied by a low hemolysis rate of 3.81%, confirming the exceptional biocompatibility of the coatings. These findings offer valuable insights into the development of stimuli-responsive biocompatible coatings for effectively protecting Mg alloys.

Engineering a targeted and safe bone anabolic gene therapy to treat osteoporosis in alveolar bone loss.

Alveolar bone loss in elderly populations is highly prevalent and increases the risk of tooth loss, gum disease susceptibility, and facial deformity. Unfortunately, there are very limited treatment options available. Here, we developed a bone-targeted gene therapy that reverses alveolar bone loss in patients with osteoporosis by targeting the adaptor protein Schnurri-3 (SHN3). SHN3 is a promising therapeutic target for alveolar bone regeneration, because SHN3 expression is elevated in the mandible tissues of humans and mice with osteoporosis while deletion of SHN3 in mice greatly increases alveolar bone and tooth dentin mass. We used a bone-targeted recombinant adeno-associated virus (rAAV) carrying an artificial microRNA (miRNA) that silences SHN3 expression to restore alveolar bone loss in mouse models of both postmenopausal and senile osteoporosis by enhancing WNT signaling and osteoblast function. In addition, rAAV-mediated silencing of SHN3 enhanced bone formation and collagen production of human skeletal organoids in xenograft mice. Finally, rAAV expression in the mandible was tightly controlled via liver- and heart-specific miRNA-mediated repression or via a vibration-inducible mechanism. Collectively, our results demonstrate that AAV-based bone anabolic gene therapy is a promising strategy to treat alveolar bone loss in osteoporosis.

Three-layered nanoplates and amorphous/crystalline interface synergism boost CO2 photoreduction on bismuth oxychloride nanospheres.

Structural features like 3D nano-size, ultrathin thickness and amorphous/crystalline interfaces play crucial roles in regulating charge separation and active sites of photocatalysts. However, their co-occurrence in a single catalyst and exploitation in photocatalytic CO2 reduction (PCR) remains challenging. Herein, nano-sized bismuth oxychloride spheres (BiOCl-NS) confining three-layered nanoplates (∼2.2 nm ultrathin) and an amorphous/crystalline interface are exclusively developed via intrinsic engineering for an enhanced sacrificial-reagent-free PCR system. The results uncover a unique synergism wherein the three-layered nanoplates accelerate electron-hole separation, and the amorphous/crystalline interface exposes electron-localized active sites (Bi-Ovac-Bi). Consequently, BiOCl-NS exhibit efficient CO2 adsorption and activation with the lowering of rate-determining-step energy barriers, leading to remarkable CO production (102.72 µmol g-1 h-1) with high selectivity (>99%), stability (>30 h), and apparent quantum efficiency (0.51%), outperforming conventional counterparts. Our work provides a facile structural engineering approach for boosting PCR and offers distinct synergism for advancing diverse materials.

Rapid and Convenient Potentiometric Method for Determining Fluorosulfate, a Byproduct of the Fumigant and Greenhouse Gas Sulfuryl Fluoride.

A fluorosulfate ion (FSO3-) is a hydrolysis product of sulfuryl fluoride (SO2F2), which is widely used to fumigate buildings, soil, construction materials, and postharvest commodities, and is a potent greenhouse gas. It is a potential marker for biological exposure to SO2F2 and for monitoring the progress of reactions used to scrub SO2F2 from fumigation vent gases. Here, we report a simple and inexpensive potentiometric method for determining FSO3- using a commercial nitrate-selective electrode and discuss its application. The method is suitable for solutions between 0.0025 mM and 660 mM FSO3- at initial pH between 5 and 9. Halide interference depends on its molar ratio to FSO3- and follows the sequence, F- < Cl- < Br- ≪ I-. Halide interference can be eliminated by adding silver sulfate. Interference by bicarbonate can be eliminated by H2SO4 pretreatment, and interference by phosphate or pyrophosphate by MgSO4 addition. Sulfate does not interfere, as it does in ion chromatography. Satisfactory method detection limits for FSO3- in spiked aqueous extracts of 11 fruits were obtained. The method accurately quantified the yield of FSO3- relative to that of F- in base hydrolysis of SO2F2. This study demonstrates that the developed method is highly selective, convenient, and sensitive and thus can be of great value in practice.

Size-dependent photoluminescence blinking mechanisms and volume scaling of biexciton Auger recombination in single CsPbI3 perovskite quantum dots.

Determining the correlation between the size of a single quantum dot (QD) and its photoluminescence (PL) properties is a challenging task. In the study, we determine the size of each QD by measuring its absorption cross section, which allows for accurate investigation of size-dependent PL blinking mechanisms and volume scaling of the biexciton Auger recombination at the single-particle level. A significant correlation between the blinking mechanism and QD size is observed under low excitation conditions. When the QD size is smaller than their Bohr diameter, single CsPbI3 perovskite QDs tend to exhibit BC-blinking, whereas they tend to exhibit Auger-blinking when the QD size exceeds their Bohr diameter. In addition, by extracting bright-state photons from the PL intensity trajectories, the effects of QD charging and surface defects on the biexcitons are effectively reduced. This allows for a more accurate measurement of the volume scaling of biexciton Auger recombination in weakly confined CsPbI3 perovskite QDs at the single-dot level, revealing a superlinear volume scaling (τXX,Auger ∝ σ1.96).

Rubidium Doped Cs2AgBiBr6 Hierarchical Microsphere for Enhanced Photocatalytic CO2 Reduction.

Halide perovskites have garnered significant attention for their unique optoelectronic properties in solar-to-fuel conversions. However, the efficiency of halide perovskites in the field of photocatalytic CO2 reduction is largely limited by serious charge recombination and a lack of efficient active sites. In this work, a rubidium (Rb) doped Cs2AgBiBr6 (Rb:CABB) hierarchical microsphere is developed for photocatalytic CO2 reduction. Experimental and theoretical analysis discloses that partially substituting Rb+ for Ag+ can effectively modulate the electronic structure of CABB, favoring charge separation and making adjacent Bi atoms an electron-rich active site. Further investigations indicated that Rb doping also reduces the energy barriers of the rate-determining step in CO2 reduction. As a result, Rb:CABB demonstrated an enhanced CO yield compared to its undoped counterpart. This work presents a promising approach to optimizing the electronic structures of photocatalysts and paving a new way for exploring halide perovskites for photocatalytic CO2 reduction.

Individualized survival prediction and surgery recommendation for patients with glioblastoma.

Background: There is a lack of individualized evidence on surgical choices for glioblastoma (GBM) patients. Aim: This study aimed to make individualized treatment recommendations for patients with GBM and to determine the importance of demographic and tumor characteristic variables in the selection of extent of resection. Methods: We proposed Balanced Decision Ensembles (BDE) to make survival predictions and individualized treatment recommendations. We developed several DL models to counterfactually predict the individual treatment effect (ITE) of patients with GBM. We divided the patients into the recommended (Rec.) and anti-recommended groups based on whether their actual treatment was consistent with the model recommendation. Results: The BDE achieved the best recommendation effects (difference in restricted mean survival time (dRMST): 5.90; 95% confidence interval (CI), 4.40-7.39; hazard ratio (HR): 0.71; 95% CI, 0.65-0.77), followed by BITES and DeepSurv. Inverse probability treatment weighting (IPTW)-adjusted HR, IPTW-adjusted OR, natural direct effect, and control direct effect demonstrated better survival outcomes of the Rec. group. Conclusion: The ITE calculation method is crucial, as it may result in better or worse recommendations. Furthermore, the significant protective effects of machine recommendations on survival time and mortality indicate the superiority of the model for application in patients with GBM. Overall, the model identifies patients with tumors located in the right and left frontal and middle temporal lobes, as well as those with larger tumor sizes, as optimal candidates for SpTR.

Boosting Photocatalytic CO2 Methanation through Interface Fusion over CdS Quantum Dot Aerogels.

In the field of photocatalytic CO2 reduction, quantum dot (QD) assemblies have emerged as promising candidate photocatalysts due to their superior light absorption and better substrate adsorption. However, the poor contacts within QD assemblies lead to low interfacial charge transfer efficiency, making QD assemblies suffer from unsatisfactory photocatalytic performance. Herein, a novel approach is presented involving the construction of strongly interfacial fused CdS QD assemblies (CdS QD gel) for CO2 reduction. The novel CdS QD gel demonstrates outstanding photocatalytic performance for CO2 methanation, achieving a CH4 generation rate of ≈296 µmol g-1 h-1, with a selectivity surpassing 76% and an apparent quantum yield (AQY) of 1.4%. Further investigations reveal that the robust interfacial fusion in these CdS QDs not only boosts their ability to absorb visible light but also significantly promotes charge separation. The present work paves the way for utilizing QD gel photocatalysts in realizing efficient CO2 reduction and highlights the critical role of interfacial engineering in photocatalysts.

AATCT-IDS: A benchmark Abdominal Adipose Tissue CT Image Dataset for image denoising, semantic segmentation, and radiomics evaluation.

BACKGROUND AND OBJECTIVE: The metabolic syndrome induced by obesity is closely associated with cardiovascular disease, and the prevalence is increasing globally, year by year. Obesity is a risk marker for detecting this disease. However, current research on computer-aided detection of adipose distribution is hampered by the lack of open-source large abdominal adipose datasets. METHODS: In this study, a benchmark Abdominal Adipose Tissue CT Image Dataset (AATCT-IDS) containing 300 subjects is prepared and published. AATCT-IDS publics 13,732 raw CT slices, and the researchers individually annotate the subcutaneous and visceral adipose tissue regions of 3213 of those slices that have the same slice distance to validate denoising methods, train semantic segmentation models, and study radiomics. For different tasks, this paper compares and analyzes the performance of various methods on AATCT-IDS by combining the visualization results and evaluation data. Thus, verify the research potential of this data set in the above three types of tasks. RESULTS: In the comparative study of image denoising, algorithms using a smoothing strategy suppress mixed noise at the expense of image details and obtain better evaluation data. Methods such as BM3D preserve the original image structure better, although the evaluation data are slightly lower. The results show significant differences among them. In the comparative study of semantic segmentation of abdominal adipose tissue, the segmentation results of adipose tissue by each model show different structural characteristics. Among them, BiSeNet obtains segmentation results only slightly inferior to U-Net with the shortest training time and effectively separates small and isolated adipose tissue. In addition, the radiomics study based on AATCT-IDS reveals three adipose distributions in the subject population. CONCLUSION: AATCT-IDS contains the ground truth of adipose tissue regions in abdominal CT slices. This open-source dataset can attract researchers to explore the multi-dimensional characteristics of abdominal adipose tissue and thus help physicians and patients in clinical practice. AATCT-IDS is freely published for non-commercial purpose at: https://figshare.com/articles/dataset/AATTCT-IDS/23807256.

Iterative feedback-based models for image and video polyp segmentation.

Accurate segmentation of polyps in colonoscopy images has gained significant attention in recent years, given its crucial role in automated colorectal cancer diagnosis. Many existing deep learning-based methods follow a one-stage processing pipeline, often involving feature fusion across different levels or utilizing boundary-related attention mechanisms. Drawing on the success of applying Iterative Feedback Units (IFU) in image polyp segmentation, this paper proposes FlowICBNet by extending the IFU to the domain of video polyp segmentation. By harnessing the unique capabilities of IFU to propagate and refine past segmentation results, our method proves effective in mitigating challenges linked to the inherent limitations of endoscopic imaging, notably the presence of frequent camera shake and frame defocusing. Furthermore, in FlowICBNet, we introduce two pivotal modules: Reference Frame Selection (RFS) and Flow Guided Warping (FGW). These modules play a crucial role in filtering and selecting the most suitable historical reference frames for the task at hand. The experimental results on a large video polyp segmentation dataset demonstrate that our method can significantly outperform state-of-the-art methods by notable margins achieving an average metrics improvement of 7.5% on SUN-SEG-Easy and 7.4% on SUN-SEG-Hard. Our code is available at https://github.com/eraserNut/ICBNet.

Improvement of nucleotide content of Cordyceps tenuipes by Schisandra chinensis: fermentation process optimization and application prospects.

Nucleotides are important components and the main indicators for judging Cordyceps quality. In this paper, the mixed fermentation process of Schisandra chinensis and Cordyceps tenuipes was systematically studied, and it was proposed that the fermentation products aqueous extract (S-ZAE) had antioxidant activity and anti-AChE ability. Herein, the results of a single factor showed that S. chinensis, yeast extract, inoculum amount, and pH had significant effects on nucleotide synthesis. The fermentation process optimization results were 3% glucose, 0.25% KH2PO4, 2.1% yeast extract, and S. chinensis 0.49% (m/v), the optimal fermentation conditions were 25℃, inoculum 5.8% (v/v), pH 3.8, 6 d. The yield of total nucleotides in the scale-up culture was 0.64 ± 0.027 mg/mL, which was 10.6 times higher than before optimization. S-ZAE has good antioxidant and anti-AChE activities (IC50 0.50 ± 0.050 mg/mL). This fermentation method has the advantage of industrialization, and its fermentation products have the potential to become good functional foods or natural therapeutic agents.

Development a high-sensitivity sandwich ELISA for determining antigen content of porcine circovirus type 2 vaccines.

Porcine circovirus type 2 (PCV2) is intensely prevalent in global pig farms. The PCV2 vaccine is an important means of preventing and controlling PCV2. The quality control of PCV2 vaccines is predominantly based on detection techniques such as animal testing and neutralizing antibody titration. Measuring the content of effective proteins in vaccines to measure vaccine efficacy is an excellent alternative to traditional methods, which can greatly accelerate the development speed and testing time of vaccines. In this study, we screened a monoclonal antibody (mAb) that can effectively recognize not only the exogenous expression of PCV2 Cap protein but also PCV2 virus. The double antibody sandwich ELISA (DAS-ELISA) was developed using this mAb that specifically recognize PCV2 Cap. The minimum protein content detected by this method is 3.5 ng/mL. This method can be used for the quality control of PCV2 inactivated vaccine and subunit vaccine, and the detection results are consistent with the results of mice animal experiments. This method has the advantages of simple operation, good sensitivity, high specificity and wide application. It can detect the effective antigen Cap protein content of various types of PCV2 vaccines, which not only shorten the vaccine inspection time but also save costs.