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Ultrathin two-dimensional (2D) metal oxyhalides exhibit outstanding photocatalytic properties with unique electronic and interfacial structures. Compared with monometallic oxyhalides, bimetallic oxyhalides are less explored. In this work, we have developed a novel top-down wet-chemistry desalination approach to remove the alkali-halide salt layer within the complicated precursor bulk structural matrix Pb 0.6 Bi 1.4 Cs 0.6 O 2 Cl 2 , and successfully fabricate a new 2D ultrathin bimetallic oxyhalide Pb 0.6 Bi 1.4 O 2 Cl 1.4 . The unlocked larger surface area, rich bimetallic active sites, and faster carrier dynamics within Pb 0.6 Bi 1.4 O 2 Cl 1.4 layers significantly enhance the photocatalytic efficiency for atmospheric CO 2 reduction. It outperforms the corresponding parental matrix phase and other state-of-the-art bismuth-based monometallic oxyhalides photocatalysts. This work reports a top-down desalination strategy to engineering ultrathin bimetallic 2D material for photocatalytic atmospheric CO 2 reduction, which sheds light on further constructing other ultrathin 2D catalysts for environmental and energy applications from similar complicate structure matrixes. Ultrathin two-dimensional metal oxyhalides show excellent photocatalytic properties with unique electronic and interfacial structures. Here, the authors develop a top-down desalination strategy to engineer ultrathin bimetallic two-dimensional material for photocatalytic atmospheric carbon dioxide reduction.

A stable and efficient Fe 2 O 3 /expanded perlite (Fe 2 O 3 -Ep) composite catalyst was synthesized by a simple hydrothermal method for degradation of refractory contaminants in heterogeneous photo-Fenton system. X-ray diffraction and FT-IR analyses confirmed the presence of the Fe 2 O 3 in the synthesized catalyst. The catalytic activity of the Fe 2 O 3 -Ep catalyst was evaluated by the degradation of rhodamine B (RhB, 5 mg/L) and metronidazole (MET, 5 mg/L) in the presence of H 2 O 2 under visible light irradiation. The Fe 2 O 3 -Ep catalyst exhibited high efficiency for degradation of RhB at a wide pH range from 2 to 10 and showed excellent catalytic property for decomposition of MET as well. The degradation ratio of RhB was achieved 99%, and the removal ratio of COD was 62% within 90 min at the best experimental conditions (0.5 g/L of Fe 2 O 3 -Ep catalyst, 2 mL/L of H 2 O 2 ). Furthermore, iron leaching of the Fe 2 O 3 -Ep catalyst during the catalytic degradation reaction was negligible and the catalyst still exhibited high catalytic activity and stability after five cycles. These results show that the catalyst can be used as a highly efficient heterogeneous photo-Fenton catalyst for the degradation of non-biodegradable refractory pollutants in water.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, characterized by profound therapeutic resistance and a 5-year survival rate below 10%. This prognosis is largely driven by a highly immunosuppressive tumor microenvironment (TME), in which tumor-associated neutrophils (TANs) serve as pivotal regulators. Upon recruitment to the TME, neutrophils undergo functional polarization into distinct phenotypes that either antagonize or facilitate tumor progression. This review synthesizes recent advances in PDAC research, delineating the ontogeny, subpopulation heterogeneity, and molecular mechanisms governing the pro- or anti-tumorigenic effects of TANs. We emphasize the regulatory crosstalk between TANs and the immune microenvironment, highlighting key signaling axes such as TGF-β and C-X-C chemokine receptor 2 (CXCR2) pathways. Furthermore, we evaluate TAN-targeted therapeutic strategies, categorizing them into recruitment inhibition, functional reprogramming, and immunosuppression disruption. Finally, we discuss translational challenges, including biomarker development and the shift from neutrophil depletion to functional reprogramming, offering perspectives for overcoming therapeutic resistance in PDAC.

The COVID-19 pandemic has highlighted the importance of studying the course of infectious progression. Similar needs exist for time series of other origins. While models are commonly devised and fitted to the observed data, we recently demonstrated the feasibility to directly evaluate the noisy non-linear time series that characterize the occurrence. However, for practical utility, analytics alone has limited value. The requirement of forecasting - at least in the short term - needs to be met. We initially utilized normalized new infections per day (7-day moving average for cases per million inhabitants) from Our World in Data. We then validated our method in unrelated non-linear time series of stock markets and blowfly populations. We studied a novel model-independent time series approach, time lagged analyses, and feature-space plots incorporating the time-lagged data. 1) Machine learning on the basis of correlation coefficient, utilizing about 80% of the time series as training sets, was able to generate excellent predictions for progression. 2) Feature-space plots of normalized new cases versus autocorrelation and average mutual information required a form of dynamic calibration to correct for differences in scale among the axes. With that adjustment, the maximum local Lyapunov exponent displayed sharp spikes concomitantly with peaks of infectious spread. 3) The average mutual information over various time lags and wave lengths displayed divergence and sums of absolute values that were anticipatory to peaks in new infections. The study of non-linear time series with available techniques for observed complex data can extract characteristics that enable short-range forecasting without the need for model-building. Time-lagged analysis provides one suitable foundation. Among various approaches, machine learning achieved the best prognosticative results.

Developing a feasible and low-cost strategy for the recovery of calcium fluoride efficiently from fluoride-containing wastewater is very essential for the recycle of fluoride resources. Herein, a modified lime precipitation method was employed to recover CaF2 from fluorinated wastewater using a special icy lime solution. Intriguingly, the highest F– removal was greater than 95% under the optimal condition, leaving a fluoride concentration from 200 to 8.64 mg/L, while the lime dosage was much lower than that of industry. Importantly, spherical-shaped CaF2 particles with a 93.47% purity and size smaller than 600 nm were recovered, which has a high potential for the production of hydrofluoric acid. Besides, the precipitation was significantly affected by Ca/F molar ratio, stirring time, temperature, and solution pH. Furthermore, the thermodynamics and kinetics were investigated in detail to reveal the crystallization process. As a result, the defluorination reaction followed the pseudo-second order reaction kinetics model. Also, CO2 in the air adversely influenced the CaF2 purity. Based on this facile method, a high lime utilization efficiency was applied to defluorination, which contributed to protecting the environment and saving costs. This study, therefore, provides a feasible approach for the green recovery of fluorine resources and has significance for related research.

Background Many observational studies have reported correlations between postoperative complications and prognosis after radical gastrectomy but the results are controversial. This meta-analysis was performed to investigate whether there is a correlation between postoperative complications and prognosis after radical gastrectomy. Methods Literature searches were performed in PubMed, EMBASE, and the Cochrane Library. Studies that investigated the correlations between any postoperative complications and prognosis after radical gastrectomy were included. The pooled hazard ratio (HR) with 95% confidence interval (CI) for postoperative complications regarding overall survival (OS) or recurrence-free survival (RFS) was calculated by using RevMan 5.3.5. Subgroup analyses were performed within pathological stages I, II, and III. Results Sixteen retrospective studies comprising 12,065 patients were included. The pooled HR (95% CI) for complications regarding OS was 1.79 (1.39, 2.30) and was 1.40 (1.06, 1.84) after excluding in-hospital mortality; the pooled HR (95% CI) for complications regarding RFS was 1.28 (1.10, 1.49). The pooled HR (95% CI) for infectious complications and leakage regarding OS was 1.86 (1.22, 2.83) and 2.02 (1.02, 4.00), respectively. The pooled HR (95% CI) for any reported postoperative complications regarding OS for stage I, II, and III diseases was 2.39 (0.77, 7.46), 4.35 (2.58, 7.35), and 2.84 (1.77, 4.56), respectively. Conclusions Postoperative complications correlate with poor prognosis after radical gastrectomy. Such correlations are found in stage II and III gastric cancer patients but remain to be determined in stage I gastric cancer patients.

Soil Moisture Content (SMC) is crucial for sustaining agricultural productivity, ecosystem health, and climate feedback processes. This study investigates the spatiotemporal variation of SMC during two key maize growth stages using a combined physically-based and data-driven approach, which synergizes Water Cloud vegetation correction, Dubois–Dobson dielectric retrieval. The developed SMC inversion method achieving high accuracy with determination coefficients (R 2 ) of 0.75 in the maturity stage and 0.78 in the filling stage, yielding high-resolution SMC product. Machine learning methods, enhanced by Shapley Additive Explanations (SHAP), were employed to analyze the impacts of environmental factors on SMC based on the high-resolution SMC product. Land surface temperature (LST) was identified as the primary driver of spatial variation during maturity, while elevation dominated during the filling stage. The different levels of SMC in two stages were largely dictated by meteorological factors, but the role of maize was deemed inconsequential on SMC’s temporal variation. Furthermore, the relationships between SMC and environmental factors were quantified. SMC exhibits a gradual decrease trend with rising LST, yet this trend escalates sharply when LST surpasses 15 °C. An optimal range of Normalized difference vegetation index (NDVI) value, between 0.2 and 0.5, was discovered to be most effective for preserving SMC. This research offers a comprehensive perspective on the drivers of SMC variation, which is pivotal for informed agricultural practices and the enhancement of climate models.

Unraveling atomic‐level active sites of layered photocatalyst towards low‐concentration CO2 conversion is still challenging. Herein, the yield and selectivity of photocatalytic CO2 reduction of the Aurivillius‐related oxide semiconductor Bi2O2SiO3 nanosheet (BOSO) were largely improved using a surface sulfidation strategy. The experiment and theoretical calculation confirmed that surface sulfidation of the Bi2O2SiO3 nanosheet (S‐BOSO, 6.28 nm) redistributed the charge‐enriched Bi sites, extended the solar spectrum absorption to the whole visible range, and considerably enhanced the charge separation, in addition to creating new reaction active sites, as compared to pristine BOSO. Subsequently, surface sulfidation played a switchable role, wherein S‐BOSO showed a very high CH3OH generation rate (12.78 µmol g−1 for 4 h, 78.6% selectivity) from low‐concentration CO2 (1000 ppm) under visible light irradiation, which outperforms most of the state‐of‐the‐art photocatalysts under similar conditions. This study presents an atomic‐level modification protocol for engineering reactive sites and charge behaviors to promote solar‐to‐energy conversion. A desirable atomic‐level sulfidation strategy over an Aurivillius‐related layer‐structured photocatalyst Bi2O2SiO3 is demonstrated. Sulfidation‐induced reactive sites facilitate local charge separation, contributing to enhanced low‐concentration CO2 photoreduction. The system also shows feasibility in diluted CO2 conditions, typically hindered by the deficient reactive sites in conventional systems.

Osteoporosis is driven in part by excessive osteoclast-mediated bone resorption, yet osteoblast-derived extracellular cues that restrain osteoclast bioenergetics remain incompletely defined. Here we identify osteomodulin (OMD), a matrix-associated osteoblast-derived protein that is reduced in the bone tissue and serum of postmenopausal patients with osteoporosis. Inducible global or osteoblast-specific Omd deletion exacerbates bone loss and increases osteoclast activity, whereas osteoclast precursor-specific deletion produces no overt skeletal phenotype. Mechanistically, OMD engages integrin β8 on osteoclast precursors, suppresses RhoA activity and enhances YAP phosphorylation, thereby reducing YAP/TEAD occupancy at the ribonucleotide reductase M2 (RRM2) promoter and repressing Rrm2 transcription. Consistent with RRM2’s role in maintaining the dNTP pools required for mitochondrial DNA replication, OMD decreases mtDNA copy number and the abundance of electron transport chain proteins, leading to reduced mitochondrial respiration and ATP production, with only limited glycolytic compensation. Finally, recombinant OMD supplementation or pharmacologic RRM2 inhibition mitigates ovariectomy and lipopolysaccharide-induced bone loss. Together, our findings identify an OMD-integrin β8-RhoA-YAP/TEAD-RRM2 axis that links extracellular matrix signaling to mitochondrial respiration and mitochondrial ATP production during osteoclastogenesis. Osteomodulin links bone loss to mitochondrial function Osteoporosis is a condition characterized by reduced bone strength, increasing the risk of fractures, particularly in older adults and postmenopausal women. This study explores a protein called osteomodulin (OMD) and its role in bone health. Researchers found that OMD levels are lower in people with osteoporosis. They used mice to study how OMD affects bone cells. By removing OMD in mice, they observed increased bone loss and more active bone-resorbing cells called osteoclasts. They also discovered that OMD interacts with a receptor called ITGB8 on osteoclast precursors, reducing their activity by affecting energy production in the cells. The study suggests that OMD helps maintain bone health by regulating osteoclast activity. The researchers propose that increasing OMD levels or targeting related pathways could be a new way to treat osteoporosis. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

BackgroundPlant endogenous hormones play crucial roles in seed germination. Among them, abscisic acid (ABA) and gibberellin (GA), two antagonistic hormones, are central regulators. However, their precise mechanisms in quinoa seed germination remain incompletely understood.MethodsThus, by combining physiological and transcriptome analyses, this study provides insights into the ABA/GA3-mediated regulatory mechanisms during seed germination in quinoa. employs quinoa seed germination as a model to simulate PHS, with a primary focus on analyzing the alterations in starch, protein, soluble sugar, and endogenous ABA and GA3 content in quinoa seeds pre- and post-germination. Additionally, the study investigates the enzymatic activities associated with these two hormones. Also, the transcriptome data analysis before and after seed germination elucidate the mechanisms by which endogenous ABA and GA3 regulate quinoa seed germination.Results and discussionThe germination leads to an increase in the concentrations of soluble sugars, proteins, maltose, and glucose. Quinoa seeds exhibit insensitivity to ABA, while GA3 plays a significant role in promoting seed germination. Transcriptome revealed upregulation of starch and sucrose metabolism and the EMP pathway and TCA cycle were enhanced during seed germination. Fifteen crucial genes related to ABA, GA3, starch/sucrose metabolism, and EMP pathway in quinoa germination were identified. Notably, unlike most crops, the elevated endogenous ABA levels are inadequate to impede the germination of quinoa seeds or quinoa seeds exhibit insensitivity to ABA. The analysis of transcriptome data demonstrated an upregulation of the starch and sucrose metabolism pathways, as well as glycolysis and the tricarboxylic acid cycle, during the germination process of quinoa seeds. These findings provide a foundational theoretical framework for elucidating the intrinsic mechanisms underlying quinoa germination and preharvest sprouting.