Silencing of SIRPα enhances the antitumor efficacy of CAR-M in solid tumors.

The potential of macrophage-mediated phagocytosis as a cancer treatment is promising. Blocking the CD47-SIRPα interaction with a CD47-specific antibody significantly enhances macrophage phagocytosis. However, concerns regarding their toxicity to nontumor cells remain substantial. Here, we engineered chimeric antigen receptor macrophages (CAR-Ms) by fusing a humanized single-chain variable fragment with FcγRIIa and integrating short hairpin RNA to silence SIRPα, thereby disrupting the CD47-SIRPα signaling pathway. These modified CAR-shSIRPα-M cells exhibited an M1-like phenotype, superior phagocytic function, substantial cytotoxic effects on HER2-positive tumor cells, and the ability to eliminate patient-derived organoids. In vivo, CAR-M cells significantly inhibited tumor growth and prolonged survival in tumor-bearing mice. Notably, CAR-shSIRPα-M cells enhanced cytotoxic T-cell infiltration into tumors, thereby enhancing the antitumor response in both the humanized immune system mouse model and immunocompetent mice. Mechanistically, SIRPα inhibition activated inflammatory pathways and the cGAS-STING signaling cascade in CAR-M cells, leading to increased production of proinflammatory cytokines, reactive oxygen species, and nitric oxide, thereby enhancing their antitumor effects. These findings underscore the potential of SIRPα inhibition as a novel strategy to increase the antitumor efficacy of CAR-M cells in cancer immunotherapy, particularly against solid tumors.

A comprehensive overview on antiviral effects of baicalein and its glucuronide derivative baicalin.

Natural product-based antiviral candidates have received significant attention. However, there is a lack of sufficient research in the field of antivirals to effectively combat patterns of drug resistance. Baicalein and its glucuronide derivative baicalin are two main components extracted from Scutellaria baicalensis Georgi. They have proven to be effective against a broad range of viruses by directly killing virus particles, protecting infected cells, and targeting viral antigens on their surface, among other mechanisms. As natural products, they both possess the advantage of lower toxicity, enhanced therapeutic efficacy, and even antagonistic effects against drug-resistant viral strains. Baicalein and baicalin exhibit promising potential as potent pharmacophore scaffolds, demonstrating their antiviral properties. However, to date, no review on the antiviral effects of baicalein and baicalin has been published. This review summarizes the recent research progress on antiviral effects of baicalein and baicalin against various types of viruses both in vitro and in vivo with a focus on the dosages and underlying mechanisms. The aim is to provide a basis for the rational development and utilization of baicalein and baicalin, as well as to promote antiviral drug research. Please cite this article as: Liu XY, Xie W, Zhou HY, Zhang HQ, Jin YS. A comprehensive overview on antiviral effects of baicalein and its glucuronide derivative baicalin. J Integr Med. 2024; Epub ahead of print.

Tuning metal-support interactions in nickel-zeolite catalysts leads to enhanced stability during dry reforming of methane.

Ni-based catalysts are highly reactive for dry reforming of methane (DRM) but they are prone to rapid deactivation due to sintering and/or coking. In this study, we present a straightforward approach for anchoring dispersed Ni sites with strengthened metal-support interactions, which leads to Ni active sites embedded in dealuminated Beta zeolite with superior stability and rates for DRM. The process involves solid-state grinding of dealuminated Beta zeolites and nickel nitrate, followed by calcination under finely controlled gas flow conditions. By combining in situ X-ray absorption spectroscopy and ab initio simulations, it is elucidated that the efficient removal of byproducts during catalyst synthesis is conducted to strengthen Ni-Si interactions that suppress coking and sintering after 100 h of time-on-stream. Transient isotopic kinetic experiments shed light on the differences in intrinsic turnover frequency of Ni species and explain performance trends. This work constructs a fundamental understanding regarding the implication of facile synthesis protocols on metal-support interaction in zeolite-supported Ni sites, and it lays the needed foundations on how these interactions can be tuned for outstanding DRM performance.

Brain Iron in signature regions relating to cognitive aging in older adults: the Taizhou Imaging Study.

BACKGROUND: Recent magnetic resonance imaging (MRI) studies have established that brain iron accumulation might accelerate cognitive decline in Alzheimer's disease (AD) patients. Both normal aging and AD are associated with cerebral atrophy in specific regions. However, no studies have investigated aging- and AD-selective iron deposition-related cognitive changes during normal aging. Here, we applied quantitative susceptibility mapping (QSM) to detect iron levels in cortical signature regions and assessed the relationships among iron, atrophy, and cognitive changes in older adults. METHODS: In this Taizhou Imaging Study, 770 older adults (mean age 62.0 ± 4.93 years, 57.5% women) underwent brain MRI to measure brain iron and atrophy, of whom 219 underwent neuropsychological tests nearly every 12 months for up to a mean follow-up of 2.68 years. Global cognition was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Domain-specific cognitive scores were obtained from MoCA subscore components. Regional analyses were performed for cortical regions and 2 signature regions where atrophy affected by aging and AD only: Aging (AG) -specific and AD signature meta-ROIs. The QSM and cortical morphometry means of the above ROIs were also computed. RESULTS: Significant associations were found between QSM levels and cognitive scores. In particular, after adjusting for cortical thickness of regions of interest (ROIs), participants in the upper tertile of the cortical and AG-specific signature QSM exhibited worse ZMMSE than did those in the lower tertile [ ß = -0.104, p = 0.026; ß = -0.118, p = 0.021, respectively]. Longitudinal analysis suggested that QSM values in all ROIs might predict decline in ZMoCA and key domains such as attention and visuospatial function (all p < 0.05). Furthermore, iron levels were negatively correlated with classic MRI markers of cortical atrophy (cortical thickness, gray matter volume, and local gyrification index) in total, AG-specific signature and AD signature regions (all p < 0.05). CONCLUSION: AG- and AD-selective iron deposition was associated with atrophy and cognitive decline in elderly people, highlighting its potential as a neuroimaging marker for cognitive aging.

Theoretical Design of Thorium Nitride MXenes.

Actinides with 5f6d7s valence orbitals feature special physicochemical properties different from those of the other elements. Actinide-based two-dimensional (2D) materials combine the distinctive physics of actinides with the quantum size effect of 2D materials, but relevant studies are scarce. Since Th has a valence electron configuration of 6d27s2 like Ti, and Ti-based MXenes show excellent stability and versatile applications, whether Th can form stable MXenes has become an intriguing question. Herein, we designed Th2N, Th3N2, and Th4N3 MXenes and investigated their physical properties, functionalization, and potential applications using density functional theory. Their stabilities are validated by global minimum search, phonon spectra, ab initio molecular dynamics, enthalpy of formation, and energy above the hull. All the Th-N MXenes exhibit metallic properties and are stabilized by the electrostatic interaction between Th and N ions, as well as the covalent bonding interaction between the Th 6d/5f and N 2p/2s orbitals. The H-, O-, and F-functionalization3N2 MXene improve its stability while preserving its metallicity, and the O-functionalized Th3N2 MXene shows promising catalytic activity for hydrogen evolution. The thorium nitride MXenes enrich the family of actinide-based 2D materials and extend our understanding of the structures and properties induced by actinide elements in low-dimensional materials.

Identification of an ionic mechanism for ERα-mediated rapid excitation in neurons.

The major female ovarian hormone, 17ß-estradiol (E2), can alter neuronal excitability within milliseconds to regulate a variety of physiological processes. Estrogen receptor-α (ERα), classically known as a nuclear receptor, exists as a membrane-bound receptor to mediate this rapid action of E2, but the ionic mechanisms remain unclear. Here, we show that a membrane channel protein, chloride intracellular channel protein-1 (Clic1), can physically interact with ERα with a preference to the membrane-bound ERα. Clic1-mediated currents can be enhanced by E2 and reduced by its depletion. In addition, Clic1 currents are required to mediate the E2-induced rapid excitations in multiple brain ERα populations. Further, genetic disruption of Clic1 in hypothalamic ERα neurons blunts the regulations of E2 on female body weight balance. In conclusion, we identified the Clic1 chloride channel as a key mediator for E2-induced rapid neuronal excitation, which may have a broad impact on multiple neurobiological processes regulated by E2.

Design, synthesis, and evaluation of novel oxyacanthine derivatives for anti-SARS-CoV-2 activity.

Here, we report the synthesis of a series of oxyacanthine derivatives and evaluation for their anti-SARS-CoV-2 activity in Vero E6 cells. In order to eliminate the potential metabolic activation caused by para-methylene phenol moiety in oxyacanthine, totally 29 derivatives were designed and synthesized, resulting in 23 compounds with antivirus IC50 below 5.00 µM and 9 compounds with antivirus IC50 below 1.00 µM. Among them, amides compound 4a and 4d exhibited potent anti-SARS-CoV-2 activity and the most favorable selectivity index (SI) in vitro with the SI values of 115 and 70, respectively. The pharmacokinetic properties of 4a and 4d were also assessed. Much more improved exposure in mice, longer half-life (T1/2), and increased oral bioavailability were observed for both compounds 4a and 4d compared with oxyacanthine.

Unlocking the potential of methionine: a dietary supplement for preventing colitis.

The incidence rate of colitis and conversion of colitis into colorectal cancer is increasing. However, the results of drug treatments are inconsistent with variable side effects; therefore, it is necessary to find alternative ways of treating colitis, e.g. through dietary supplements. One such dietary supplement could be sulfur-containing amino acids, which are known to have anti-inflammatory, antioxidant, and gut microbiota homeostasis effects. Therefore, the aim of the present study was to explore the effect of methionine supplementation in the diet of mice on experimental dextran sulfate sodium (DSS)-induced colitis. Here, 24 male C57BL/6J mice were split into three experimental treatment groups in such a way that each treatment group had four replicates and each replicate had two mice. The control group was colitis-free, while colitis was induced by the administration of DSS in the DSS groups. In the DSS and DSS plus methionine (DSS + Met) groups, DSS was provided in drinking water containing 3% DSS on days 1-5 and later provided with purified water on days 6-7. It was found that supplementing with methionine could activate pathways like Nrf2, and inhibit pathways like TLR4 and Nlrp3 to realize anti-inflammatory and antioxidant effects. Moreover, methionine could alter the microbiota of the gut in the experimental mice, whereby exploration of the gut microbiota demonstrated that methionine supplementation in the diet increased the abundance of parabacteroides and the production of propionate and butyrate. The current study shows that the dietary prophylactic supplementation of methionine has a beneficial effect on resisting colitis, providing new insights for the prevention of colitis.

Multimodal Data-Driven Segmentation of Bone Metastasis Lesions in SPECT Bone Scans Using Deep Learning.

BACKGROUND: Patients with malignant tumors often develop bone metastases. SPECT bone scintigraphy is an effective tool for surveying bone metastases due to its high sensitivity, low-cost equipment, and radiopharmaceutical. However, the low spatial resolution of SPECT scans significantly hinders manual analysis by nuclear medicine physicians. Deep learning, a promising technique for automated image analysis, can extract hierarchal patterns from images without human intervention. OBJECTIVE: To enhance the performance of deep learning-based segmentation models, we integrate textual data from diagnostic reports with SPECT bone scans, aiming to develop an automated analysis method that outperforms purely unimodal data-driven segmentation models. METHODS: We propose a dual-path segmentation framework to extract features from bone scan images and diagnostic reports separately. In the first path, an encoder-decoder network is employed to learn hierarchical representations of features from SPECT bone scan images. In the second path, the Chinese version of the MacBERT model is utilized to develop a text encoder for extracting features from diagnostic reports. The extracted textual features are then fused with image features during the decoding stage in the first path, enhancing the overall segmentation performance. RESULTS: Experimental evaluation conducted on real-world clinical data demonstrated the superior performance of the proposed segmentation model. Our model achieved a 0.0209 increase in the DSC (Dice Similarity Coefficient) score compared to the well-known U-Net model. CONCLUSIONS: The proposed multimodal data-driven method effectively identifies and isolates metastasis lesions in SPECT bone scans, outperforming existing classical deep learning models. This study demonstrates the value of incorporating textual data in the deep learning-based segmentation of lowresolution SPECT bone scans.

UTSRMorph: A Unified Transformer and Superresolution Network for Unsupervised Medical Image Registration.

Complicated image registration is a key issue in medical image analysis, and deep learning-based methods have achieved better results than traditional methods. The methods include ConvNet-based and Transformer-based methods. Although ConvNets can effectively utilize local information to reduce redundancy via small neighborhood convolution, the limited receptive field results in the inability to capture global dependencies. Transformers can establish long-distance dependencies via a self-attention mechanism; however, the intense calculation of the relationships among all tokens leads to high redundancy. We propose a novel unsupervised image registration method named the unified Transformer and superresolution (UTSRMorph) network, which can enhance feature representation learning in the encoder and generate detailed displacement fields in the decoder to overcome these problems. We first propose a fusion attention block to integrate the advantages of ConvNets and Transformers, which inserts a ConvNet-based channel attention module into a multihead self-attention module. The overlapping attention block, a novel cross-attention method, uses overlapping windows to obtain abundant correlations with match information of a pair of images. Then, the blocks are flexibly stacked into a new powerful encoder. The decoder generation process of a high-resolution deformation displacement field from low-resolution features is considered as a superresolution process. Specifically, the superresolution module was employed to replace interpolation upsampling, which can overcome feature degradation. UTSRMorph was compared to state-of-the-art registration methods in the 3D brain MR (OASIS, IXI) and MR-CT datasets (abdomen, craniomaxillofacial). The qualitative and quantitative results indicate that UTSRMorph achieves relatively better performance. The code and datasets used are publicly available at https://github.com/Runshi-Zhang/UTSRMorph.

Structures of Th4+ aqueous solutions: insights from AIMD and metadynamics simulations.

Solution chemistry of actinide ions is critical to understanding the solvation behaviors and hydrolysis process. Using tetravalent thorium ion Th4+ as a representative example, we investigate the local structures and dynamic behaviors of hydrated Th4+ ions by ab initio molecular dynamics (AIMD) simulations using the recently developed norm-conserving pseudopotentials and basis sets optimized for actinides (J.-B. Lu et al., J. Chem. Theory Comput. 2021, 17, 3360-3371). AIMD simulations reveal two distinct solvation shells, with the first shell comprising 9 water molecules at approximately rTh-O = 2.50 Å and exhibiting a tricapped trigonal prism geometry. These conclusions are confirmed through metadynamics simulations and further structural analysis. AIMD simulations also show the slight effect of temperature and counterions on the structure of the solution. The structured solvation shells of the highly charged Th4+ ion with the specific geometry, distinct from the structure of liquid water, lead to corresponding structural changes in the hydrogen bond network in water. Additionally, beyond the solvent-shared ion pair (SIP) state observed in the unbiased AIMD simulations, the metadynamics simulations reconstruct a two-dimensional free energy surface that clearly indicates the potential stability of the contact ion pair (CIP) state in the system with Cl- as a counterion. The findings in this work provide insights into the solution chemistry of actinides and serve as a reference for studying other actinide solution systems.

Multi-dimensional epidemiology and informatics data on COVID-19 wave at the end of zero COVID policy in China.

Background: China exited strict Zero-COVID policy with a surge in Omicron variant infections in December 2022. Given China's pandemic policy and population immunity, employing Baidu Index (BDI) to analyze the evolving disease landscape and estimate the nationwide pneumonia hospitalizations in the post Zero COVID period, validated by hospital data, holds informative potential for future outbreaks. Methods: Retrospective observational analyses were conducted at the conclusion of the Zero-COVID policy, integrating internet search data alongside offline records. Methodologies employed were multidimensional, encompassing lagged Spearman correlation analysis, growth rate assessments, independent sample T-tests, Granger causality examinations, and Bayesian structural time series (BSTS) models for comprehensive data scrutiny. Results: Various diseases exhibited a notable upsurge in the BDI after the policy change, consistent with the broader trajectory of the COVID-19 pandemic. Robust connections emerged between COVID-19 and diverse health conditions, predominantly impacting the respiratory, circulatory, ophthalmological, and neurological domains. Notably, 34 diseases displayed a relatively high correlation (r > 0.5) with COVID-19. Among these, 12 exhibited a growth rate exceeding 50% post-policy transition, with myocarditis escalating by 1,708% and pneumonia by 1,332%. In these 34 diseases, causal relationships have been confirmed for 23 of them, while 28 garnered validation from hospital-based evidence. Notably, 19 diseases obtained concurrent validation from both Granger causality and hospital-based data. Finally, the BSTS models approximated approximately 4,332,655 inpatients diagnosed with pneumonia nationwide during the 2 months subsequent to the policy relaxation. Conclusion: This investigation elucidated substantial associations between COVID-19 and respiratory, circulatory, ophthalmological, and neurological disorders. The outcomes from comprehensive multi-dimensional cross-over studies notably augmented the robustness of our comprehension of COVID-19's disease spectrum, advocating for the prospective utility of internet-derived data. Our research highlights the potential of Internet behavior in predicting pandemic-related syndromes, emphasizing its importance for public health strategies, resource allocation, and preparedness for future outbreaks.

Evaluation of grafts fixation techniques for temporomandibular joint reconstruction with medial femoral condyle flap: A numerical study.

Reconstruction for large-scale temporomandibular joint (TMJ) defects can be challenging. Previously, we utilized the medial femoral condyle (MFC) flap for TMJ reconstruction. However, the optimal fixation method remains uncertain. In this study, finite element analysis was used to study the effects of three different fixation types of bone graft: overlap type, bevel type, and flush type. Models of different fixation types of MFC flap were reconstructed from CT images. A standard internal fixation model for extracapsular condylar fracture was also included as a control. Displacement of bone graft, deformation of plates and screws, and stress distribution of plates, screws, and cortical and cancellous of the bone graft were analyzed by finite element analysis to investigate their biomechanical features. The displacement of the bone graft and deformation of plates and screws in three different fixation types showed no significant difference. The overlap type and flush type of fixation displayed the lowest and highest stress respectively. All three fixation types could satisfy the mechanical requirement and face no risk of breakage and the major displacement of the MFC bone graft. These results provide insights into the optimal fixation approach for MFC bone grafts, offering valuable guidance and reference for clinical application.

Impact of the hydrated functional zone on the adsorption of ciprofloxacin to microplastics under the influence of UV aging.

The inevitable UV aging of microplastics (MPs) is one of the key factors affecting their interaction with antibiotics. In this study, polyethylene (PE) and polystyrene (PS) MPs were aged with UV irradiation. The adsorption isotherms and kinetics of ciprofloxacin (CIP) to virgin and aged MPs were investigated through various models, and the effects of pH on the adsorption amount were explored. Characterization revealed that the surfaces of aged MPs became rougher, and the hydrophilicity increased. These aged MPs were still in the early stage of aging on the basis of their carbonyl index (CI) (<0.2) and O/C (<0.04) values. The adsorption isotherms indicated that the adsorption mechanism of aged PE was different from that of virgin PE. Compared with virgin PE, the adsorption amount of aged PE increased by 87.80-95.45%, and the adsorption rate decreased by 65.52-80.74%. However, aging did not significantly affect the equilibrium adsorption amount or adsorption rate of aged PS. The external diffusion rate (Kext) (about 2.29-0.36 h-1) was almost 30 times greater than the internal diffusion rate (Kint) in the film-pore mass transfer (FPMT) model, indicating that CIP adsorption rate was dominated by external diffusion. A hydrated functional zone is thought to form around aged MPs, thus changing the adsorption mechanism and adsorption amount of aged PE. Therefore, more attention should be given to alterations in the hydrated functional zone in the early stage of MPs aging.

Modulation of charge structure in Bi/Bi2O3-In2O3@C for efficient CO2 electroreduction to formate.

Electrocatalytic CO2 reduction reaction (ECO2RR) to value-added chemicals is of significant importance to control CO2 emission and reach carbon neutrality. Herein, Bi/Bi2O3-In2O3@C electrocatalyst with nanosheet arrays is successfully fabricated by a facile solvothermal with subsequent calcination process. It is found that the electron structure of Bi/Bi2O3-In2O3@C can be adjusted by the synergistic effects of Bi-In hetero-diatoms, which can significantly enhance its inherent catalytic activity. As expected, it requires a maximum HCOOH faradaic efficiency (FEHCOOH) of 97.6 % at -1.1 V vs. Reversible Hydrogen Electrode (RHE), which further delivers over 90 % at a wide potential range of -0.8 to -1.4 V vs. RHE, and exhibits high stability of 90.1 % over 60-h long-term test. In-situ Raman analysis is performed to explore the mechanism of its excellent stability. Meanwhile, in-situ attenuated total reflection-Fourier-transform infrared (ATR-FTIR) analysis combined with theoretical calculations reveal that the hetero-bridging absorption of *OCHO and d-d orbital coupling effect can regulate d-band center of Bi/Bi2O3-In2O3@C and improve its density of states around Ef, moderating free energy of intermediates, thereby the improved formate production performance can be seen.

Longitudinal changes of serum metabolomic profile after laparoscopic sleeve gastrectomy in obesity.

BACKGROUND: Bariatric surgery induces significant weight loss, increases insulin sensitivity and improves dyslipidemia. As one of the most widely performed bariatric surgeries, laparoscopic sleeve gastrectomy (LSG) is thought to improve metabolic profile along with weight loss. The objective of this study was to evaluate longitudinal changes in serum metabolite levels after LSG and elucidate the underlying mechanisms of metabolic improvement. METHODS: Clinical metabolic parameters and serum samples were collected preoperatively and at 1, 3, and 6 months postoperatively from nine patients with obesity undergoing LSG. Serum metabolites were measured using non-targeted metabolic liquid chromatography-mass spectrometry (LC-MS) method. RESULTS: During the 1, 3, and 6 months postoperative follow-up, the BMI, HOMA-IR, liver fat content showed a gradual descending trend. A total of 328 serum metabolites were detected and 38 were differentially expressed. The up-regulated metabolites were mainly enriched in ketone body metabolism, alpha linolenic acid and linoleic acid metabolism, pantothenate and CoA biosynthesis, glycerolipid metabolism, fructose and mannose degradation, while the down-regulated metabolites were closely related to caffeine metabolism, oxidation of branched chain fatty acids, glutamate metabolism, and homocysteine degradation. Notably, nine metabolites (oxoglutarate, 2-ketobutyric acid, succinic acid semialdehyde, phthalic acid, pantetheine, eicosapentaenoate, 3-hydroxybutanoate, oxamic acid, and dihydroxyfumarate) showed persistent differential expression at 1, 3, and 6 months follow-up. Some were found to be significantly associated with weight loss, insulin resistance improvement and liver fat content reduction. CONCLUSIONS: This finding may provide a new perspective for revealing novel biomarkers and mechanisms of metabolic improvement in obesity and related comorbidities.

A harsh environmental resistant and long-term stable ionic conductive hydrogel by one-step preparation for wireless health activity and physiological state detection.

Benefiting from the good electromechanical performance, ionic conductive hydrogel can easily convert the deformation into electrical signals, showing great potential in wearable electronic devices. However, due to the high water content, icing and water evaporation problems seriously limit their development. Although additives can ease these disadvantages, the accompanying performance degradation and complex preparation processes couldn't meet application needs. In this work, a convenient method was provided to prepare ionic conductive hydrogels with sensitive electromechanical performance, harsh environmental tolerance, and long-term stability without additives. Based on the hydratability between metal ions and water molecules resulting in spatial condensation of the hydrogel framework, the hydrogel exhibits good flexibility and ionic conductivity (70.3 mS/cm). Furthermore, the metal salt can bind with water molecules to reduce the vapor pressure, thus endowing the hydrogel with good freezing resistance (-40 °C) and long-term stability over a wide temperature range (-20 °C-50 °C). Based on these unique advantages, the hydrogel shows good sensitivity. Even in a harsh environment, it still maintained excellent stability (-20 °C-50 °C, GF = 2.2, R2 > 0.99). Assembled with a Wi-Fi device, the hydrogel sensor demonstrates good health activity and physiological state detection performance, demonstrating great potential for wearable medical devices.

Prevention of medication-related osteonecrosis of the jaw in mice by adipose-derived stem cells associated with activated autophagic flux.

Background/purpose: Medication-related osteonecrosis of the jaw (MRONJ) represents a rare yet serious adverse reaction associated with the prolonged use of anti-bone resorptive or anti-angiogenic agents. This study aimed to investigate the impact and underlying mechanisms of adipose-derived stem cells (ADSCs) in preventing MRONJ in a mouse model. Materials and methods: Following tooth extraction in MRONJ mice, ADSCs or PBS were administered via the tail vein. The healing progress of gingival epithelium and the extraction socket was assessed using a stereoscopic microscope and histological analysis. Immunofluorescence was employed to examine markers associated with autophagy (LC3 and SQSTM1) and apoptosis (Cleaved-CASP 3). Statistical analysis involved unpaired Student's t-test and ANOVA on ABI Prism 7500, with P-values below 0.05 deemed statistically significant. Results: ADSCs enhanced gingival epithelium migration and facilitated new bone formation. In the MRONJ group, the expressions of autophagy-related protein LC3 and SQSTM1 in gingival epithelium were concurrently elevated, which indicated autophagic flux was impaired. Conversely, when treated with ADSCs, the expression of LC3 and SQSTM1 were downregulated, similarly to the Control group. Mechanically, zoledronate induced a deficiency of autophagosome-lysosome fusion in epithelial cells, while ADSCs supernatant could promote the autolysosomes formation. Furthermore, ADSCs rescued the number of autophagy-related apoptotic cells in the gingival epithelium of MRONJ. Conclusion: ADSCs could effectively prevent the occurrence of MRONJ, likely through the activation of autophagic flux and the inhibition of autophagy-related apoptosis in gingival epithelium. These findings enhanced the understanding of MRONJ pathogenesis and propose a potential therapeutic target for this disease.

Recent Advances and Insights in Designing ZnxCd1-xS-Based Photocatalysts for Hydrogen Production and Synergistic Selective Oxidation to Value-Added Chemical Production.

Combining the hydrogen (H2) extraction process and organic oxidation synthesis in photooxidation-reduction reactions mediated by semiconductors is a desirable strategy because rich chemicals are evolved as byproducts along with hydrogen in trifling conditions upon irradiation, which is the only effort. The bifunctional photocatalytic strategy facilitates the feasible formation of a C═O/C─C bond from a large number of compounds containing a X-H (X = C, O) bond; therefore, the production of H2 can be easily realized without support from third agents like chemical substances, thus providing an eco-friendly and appealing organic synthesis strategy. Among the widely studied semiconductor nanomaterials, ZnxCd1-xS has been continuously studied and explored by researchers over the years, and it has attracted much consideration owing to its unique advantages such as adjustable band edge position, rich elemental composition, excellent photoelectric properties, and ability to respond to visible light. Therefore, nanostructures based on ZnxCd1-xS have been widely studied as a feasible way to efficiently prepare hydrogen energy and selectively oxidize it into high-value fine chemicals. In this Review, first, the crystal and energy band structures of ZnxCd1-xS, the model of twin nanocrystals, the photogenerated charge separation mechanism of the ZB-WZ-ZB homojunction with crisscross bands, and the Volmer-Weber growth mechanism of ZnxCd1-xS are described. Second, the morphology, structure, modification, synthesis, and vacancy engineering of ZnxCd1-xS are surveyed, summarized, and discussed. Then, the research progress in ZnxCd1-xS-based photocatalysis in photocatalytic hydrogen extraction (PHE) technology, the mechanism of PHE, organic substance (benzyl alcohol, methanol, etc.) dehydrogenation, the factors affecting the efficiency of photocatalytic discerning oxidation of organic derivatives, and selective C-H activation and C-C coupling for synergistic efficient dehydrogenation of photocatalysts are described. Conclusively, the challenges in the applicability of ZnxCd1-xS-based photocatalysts are addressed for further research development along this line.

Ion Leakage Current Control for Polycrystalline Metal Halide Perovskite Direct X-ray Detectors.

Metal halide perovskites have emerged as promising materials for X-ray detection due to their high X-ray attenuation coefficients, defect tolerance, and suitability for large-area, low-temperature fabrication. However, the intrinsic high ion conductivity of these materials presents challenges, such as high dark current density and current drift, which impair the stability and sensitivity of perovskite X-ray detectors. This study introduces an approach to mitigating these issues by incorporating 2,2,3,3,3-pentafluoropropylamine hydrochloride (PFH) into polycrystalline MAPbI3-xClx films using a one-step blade-coating method. PFH aggregates at grain boundaries, raising local vacuum energy levels and passivating surface defects, thereby reducing ion conductivity without affecting electron conductivity. As a result, this approach significantly reduces the dark current and enhances sensitivity, achieving a low detection limit of 14.7 nGyair/s. Additionally, it improves signal stability, consistency, and response speed of the detector. These findings suggest that PFH is a promising additive for advancing the performance and practical application of polycrystalline metal halide perovskite-based X-ray detectors.