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High boost switched capacitor based 13L CG transformerless inverter for cost effective grid integration

Minimally invasive surgery and neurophysiological monitoring for brainstem hemorrhage: Advancing predictive models with qEEG and TCD

Background Primary brainstem hemorrhage (PBSH) is a life-threatening neurological condition associated with high mortality and disability rates. Stereotactic hematoma aspiration surgery has been explored as a treatment option, and postoperative brainstem function monitoring is considered important for patient management. Objective This study aimed to evaluate the integration of minimally invasive stereotactic aspiration surgery with quantitative electroencephalography (qEEG) and transcranial Doppler (TCD) monitoring to assess brain function and improve predictive models for clinical outcomes in PBSH patients. Methods We conducted a retrospective analysis of 34 PBSH patients admitted between December 2022 and October 2023. After applying exclusion criteria, 25 eligible patients underwent stereotactic aspiration surgery within 24–48 hours of symptom onset. Both qEEG and TCD monitoring were performed preoperatively and within 24 hours postoperatively. Changes in qEEG parameters and TCD-derived hemodynamic indices were analyzed to assess surgical safety and efficacy. Results Stereotactic surgery was associated with higher rates of favorable outcomes at 90 days compared with the non-surgical group (68.75% vs. 11.11%, p = 0.01). Postoperative TCD parameters improved significantly, indicating better hemodynamic stability, though no correlation with mRS scores was found. qEEG analysis showed significant correlations between RBP δ% and mRS scores (ρ = 0.480, p = 0.015), and RBP α% (ρ = −0.456, p = 0.022). aEEG also correlated strongly with 90-day mRS scores (ρ = 0.544, p = 0.004). The combined model of hematoma volume, RBP α%, and aEEG showed the highest predictive accuracy (AUC = 0.865). Conclusion This study suggests the prognostic value of qEEG and explores the utility of combining neurophysiological monitoring with stereotactic aspiration surgery. The integration of these tools may assist in prognostic assessment for PBSH patients; however, validation in larger prospective studies is required before clinical adoption.

Multipartite EPR-steering and entanglement in a cavity magnomechanical system through coherent feedback

Decomposing drivers of air pollutant emissions in China: A hybrid LMDI and Geographically Weighted Regression approach

Air pollution control is an urgent problem in the field of environment, and it is crucial to accurately identify emission driving factors and collaborative emission reduction paths. In order to construct and analyze the driving mechanism of atmospheric pollutant emissions and explore the potential for regional collaborative emission reduction, an innovative three-stage progressive analysis framework was developed by combining Logarithmic Mean Divisia Index (LMDI) decomposition and Geographically Weighted Regression (GWR), which includes factor decomposition, spatial modeling, and collaborative optimization. Through empirical analysis, it was found that the energy intensity effect in Tangshan city reduces emissions by an average of −14.834 million tons per year, becoming the core driving force. The synergistic emission reduction ratio of SO2-PM2.5 in the Beijing Tianjin Hebei region reached 1: 0.38, with an average annual emission reduction of 297000 tons and a regional synergy index of 0.85 ( p  < 0.01), significantly better than other pollutant combinations. The adjusted R2 of the GWR model reached 0.86, the residual Moran’s I index was 0.07, and the proportion of significant variables reached 75%, which is 15.28% higher than other models. In addition, the Akaike information criterion corrected by the GWR model was reduced by an average of 12.78% compared to other models. The results indicated that the synergistic effect of multi factor decomposition and spatial heterogeneity analysis could significantly enhance the regional adaptability of emission reduction strategies, providing scientific support for cross regional collaborative governance.

Sexually dimorphic sail feathers in the Mandarin duck as a model for lifelong developmental modulation

Abstract Developmental processes extend beyond embryogenesis to support lifelong tissue adaptations. Avian feather follicles, with their resident stem cells and capacity for cyclic regeneration, provide a dynamic model for postnatal tissue remodeling. Here, we propose the Mandarin duck (Aix galericulata) as an ideal model to study lifelong developmental modulation, focusing on the sexually dimorphic “sail feather”—a secondary flight feather in males that undergoes seasonal transformation into a strikingly asymmetric, ornamented phenotype during the breeding season. We identified asymmetric morphogen expression in regenerating male sail feathers and used transcriptome and H3K27ac ChIP-seq to uncover male and female signaling pathways and regulatory elements. Comparative epigenomic profiling reveals enriched estrogen receptor binding motifs in females. Hormone profiling shows seasonal variation, with a marked rise in female estrogen levels preceding the mating season. These results imply Mandarin duck sail feathers integrate local morphogenetic programs, epigenetic regulation, and systemic hormonal cues to orchestrate sexually dimorphic and seasonally dynamic feather morphogenesis. This work establishes a framework for further mechanistic study of the interplay between regeneration, regional identity, and hormonal plasticity in a vertebrate integumentary system.

Preparation, characterization and in vitro evaluation of atorvastatin nanosuspensions

Poorly water-soluble drugs present a significant challenge for pharmaceutical development, particularly affecting the pharmacokinetics of orally administered drugs due to their poor dissolution. This study aimed to enhance the dissolution of a low water solubility drug atorvastatin using nanosuspension technology. Antisolvent technique was utilized to prepare atorvastatin calcium nanosuspensions. Different stabilizers were used including Cremophor, HPMC, pluronics (F127, F108, and F68), PEG400, PEG600, PEG 1k, PEG8k, PVA, PVP k30, PVP k10, PVP 44k, SLS, sodium alginate, Tween 20, and Tween 80. The prepared nanosuspensions were lyophilized using mannitol or trehalose as a lyoprotectant. Several optimum formulations were obtained. The selected best optimum formulation was 2% pluronic F127, 80 mg mannitol, and 2 min sonication time. It exhibited a mean particle size of 54.5 nm, a zeta potential of −0.809, and 0.141 PDI after reconstitution. The crystalline state of the nanoparticles was evaluated using differential scanning calorimetry (DSC) and X-ray diffraction (XRD). Fourier-transform infrared spectroscopy (FTIR) was used to assess interactions between the drug substance and the additives. In vitro drug release study was conducted for lyophilized nanosuspension in comparison to the innovator product Lipitor® in two different media, 0.05M potassium phosphate buffer pH 6.8 and 0.1N HCL. The XRD analyses indicated that the lyophilized nanosuspension was partially crystalline with some amorphization and this confirmed by DSC. FTIR results suggested that there was a physical interaction between atorvastatin and the additives. The polymer and lyoprotectant successfully preserved and coated the drug nanoparticles. The lyophilized nanosuspension exhibited superior dissolution in 0.1N HCl. However, the innovator was faster in 0.05 M phosphate buffer. In conclusion, successful preparation of lyophilized nanosuspension of atorvastatin calcium was achieved. The current findings revealed that excipient functionality in terms of stabilization, effect on solid state properties, and drug release were critical for development of stable and efficient nanosuspension.

Influence of oral health on smoking cessation intention in current smokers with insights from a nationally representative survey

Systemic nicotinamide mononucleotide administration to mitigate post-cardiac arrest brain injury in mice

Post-cardiac arrest brain injury (PCABI) is the leading cause of death and disability following cardiac arrest (CA). Nicotinamide adenine dinucleotide (NAD + ) depletion after CA contributes to neuronal injury, while nicotinamide mononucleotide (NMN) replenishes NAD + and may provide neuroprotection via sirtuin activation. This study aimed to investigate the effects of systemic NMN administration on neurological function, survival, and sirtuin-3 (SIRT3) levels in the brain post-CA. In adult male mice (C57BL/6NCrSlc, 10–15 weeks old), 10-min CA was induced by intravenous potassium chloride injection followed by cardiopulmonary resuscitation. NMN (60 mg/kg body weight) or normal saline (control) was randomly administered by intraperitoneal injection immediately after the return of spontaneous circulation (ROSC) and 24 and 48 h post-CA. Brain NAD + and adenosine triphosphate (ATP) levels, neurological function score (NFS), survival, histological neuronal injury, and brain gene expression and protein levels were measured. Brain NAD + levels decreased at 2 h post-ROSC and NMN significantly increased brain NAD + and ATP levels. At 48 h post-CA, surviving mice in the NMN group exhibited significantly higher NFS (control: 8 [IQR: 4–12] vs. NMN: 12 [IQR: 9–12], p = 0.03) and less severe hippocampal neuronal injury compared with controls. Moreover, the NMN group showed significantly higher 7-day survival rate (control: 22.2% [4/18] vs. NMN: 61.1% [11/18], p = 0.03) and brain SIRT3 levels (control: 17.7 ± 3.6 vs. NMN: 34.5 ± 4.4 pg/mg protein, p = 0.01). In conclusion, systemic NMN administration after ROSC attenuates PCABI. The increased brain ATP levels and SIRT3 upregulation may suggest the usefulness of NMN for improving mitochondrial function and contributing to neuroprotection. NAD + supplementation with NMN is a promising therapeutic approach against PCABI.

Integrative transcriptomic analysis identifies shared EndMT-related gene signatures in endometriosis and recurrent miscarriage

Beyond potency: A proposed lexicon for sensory differentiation of Cannabis sativa L. aroma

Aroma is a critical factor in consumer-perceived quality of Cannabis sativa L., yet standardized tools for describing the aromatic diversity of uncombusted Cannabis inflorescence are lacking. This study generated and evaluated a descriptive aroma lexicon for intact Cannabis inflorescence consisting of 25 terms with defined reference standards. A human panel evaluated 91 samples using a Check-All-That-Apply method. Multivariate analyses demonstrated the lexicon’s ability to differentiate samples based on orthonasal aroma. Type I and III Cannabis exhibited overlapping sensory profiles, though type I (high THC, low CBD) was more frequently described as skunky , musty , and animalic , whereas type III (low THC, high CBD) had higher frequencies of citrus , fruity , and candy -like aromas. Terpene profiling revealed clear chemical clusters, but terpene profiles alone poorly predicted sensory character. Terpinolene was the only compound consistently associated with sensory descriptors, specifically citrus and chemical . In type III samples, 43 volatile sulfur compounds were detected via gas chromatography with a pulsed flame photometric detector, including dimethyl sulfide, methional, and dimethyl trisulfide while others were tentatively identified or novel. However, neither terpene nor volatile sulfur compound profiles strongly predicted sensory perception. These results emphasize the limitations of chemical composition as a proxy for aroma quality. This work establishes a foundation for future research linking aroma, chemistry, and consumer preferences, and supports the development of quality metrics beyond delta-9-tetrahydrocannabinol potency.

Engineered polyaramides for extraction of bioamines from water

Classification of images of bee pollen according to their producers

The food industry is witnessing a growing interest in pollen due to its nutritional and energy composition. Consumers of bee pollen are increasingly eager to learn about the origins of the products they purchase. Establishing the geographical origin and the producer of pollen can enhance the product’s value and meet consumer demands for transparency in the supply chain. This article presents a novel approach for the classification of images of bee pollen according to their producers using digital images and machine learning. The study focuses on pollen collected from various beekeepers in the Boyacá region of Colombia. A standardized image acquisition process was employed to capture macroscopic images of the pollen samples. These images were then analyzed to extract color information, and machine learning models were trained to predict the producer of the pollen based on its color characteristics. The results demonstrate that the proposed approach can effectively determine the producer of pollen samples based on their color information. The model achieved an accuracy rate of 85% in associating pollen samples with their respective beekeepers. This outcome has significant implications for traceability and transparency in the bee pollen industry, offering a cost-effective and accessible method to verify the product’s origin.

Climate change drives the retreat of Aethionema spinosum (Brassicaceae) to high-elevation refugia

Quantitative analysis of proteomic changes in two monoclonal suspension MDCK cell lines infected with human influenza A virus (H1N1)

Suspension MDCK cells are a substrate for producing influenza A virus (IAV) and typically show very high virus yields compared to other animal cells. Due to the significant heterogeneity within cell populations, studying and comparing clonal cell lines with regard to specific properties, such as superior growth or higher productivity, could facilitate process optimization. In this study, we analyzed the expressed proteins of two clonal cell lines to identify intrinsic characteristics of effective IAV producers. We compared proteome changes in two human IAV PR8 (H1N1, A/PR/8/34) infected monoclonal suspension MDCK cell lines: C59, a low-yield IAV producer with fast cell growth and small cell diameter, and C113, a high-yield IAV producer with average cell growth and large cell diameter. We examined growth rate, size, metabolism and IAV production. A total of 5177 host cell proteins were detected in both cell lines using DIA-PASEF mode with a TimsTOFpro mass spectrometer. Analysis of the differentially expressed proteins revealed that fatty acid oxidation and branched-chain amino acid degradation were upregulated in highly productive cells. In contrast, steroid biosynthesis and DNA replication were more active in faster-growing cells. Following infection, 122 proteins were significantly upregulated (p < 0.05, log 2 -fold change ≥1) in the high-producing cell line. These proteins were associated with membrane trafficking, interactions with the IAV-NS1 protein and virus production. Additionally, 98 proteins associated with antiviral pathways such as the proto-oncogenic receptor tyrosine kinase MET and tumor necrosis factor (TNF) signaling were downregulated (p < 0.05, log 2 -fold change ≤1). In the cell line that produced lower IAV PR8 titers, 77 proteins were downregulated and 57 were upregulated after infection. RNA metabolism appeared to be downregulated, while the tricarboxylic acid (TCA) cycle and the stress response were both upregulated. In the high-yield C113 clone, only proteins associated with apoptosis and the target of rapamycin kinase (TOR) were expressed following infection. This may indicate a more effective release of virus particles. A comparison of intracellular IAV PR8 protein levels demonstrated that M1 and NA levels were 4-fold and 8-fold higher, respectively, for the high-yield C113 cell line. These findings again suggest an improved virus release.

SATU-net: a shadow adaptive tracing U-net for gastric cavity segmentation based on the principle of ultrasound imaging

Experimental study on soil impermeability based on chemical improvement method

To address the challenge of high permeability in coastal silty sand foundation pits, which is prone to seepage failure, this study investigated the improvement effects of three chemical stabilizers—sodium silicate, calcium lignosulfonate, and sodium polyacrylate—on the permeability characteristics of undisturbed silty sand using a self-designed seepage test system. The results demonstrated that the cumulative erosion mass of the untreated soil increased exponentially over time, with an erosion rate as high as 89.39 g/min. In contrast, the cumulative erosion mass of the silty sand treated with any of the three chemical stabilizers exhibited a trend of initial increase followed by stabilization, and the erosion rates were all reduced to below 30 g/min. Notably, under the conditions of 4% dosage and 6 hours of curing, sodium polyacrylate reduced the erosion rate to 3.98 g/min, limited the cumulative erosion mass to only 35 g, stabilized the permeability coefficient within the range of 10 ⁻ ⁶ to 10 ⁻ ⁷ cm/s, and shortened the permeability stabilization time to 6.3 minutes. Its improvement effect was superior to that of the other two stabilizers, meeting the anti-seepage requirements for high-standard cut-off walls. The research findings provide efficient and reliable chemical improvement solutions and a theoretical basis for anti-seepage engineering in foundation pits under complex coastal geological conditions.

Dynamic monitoring of dust transport effect on maritime visibility using multi source satellite data and advanced deep learning approach

Landslide susceptibility assessment via the information value-coupled machine learning models

Collapses and landslides are frequent in the southern mountainous areas of the economic zone on the northern slopes of the Tianshan Mountains in Xinjiang, and an accurate assessment of susceptibility can effectively avoid potential risks, which is crucial for the prevention and control of geological hazards. To obtain precise and reliable references for the prevention of landslide, a total of 10 landslide conditioning factors (e.g., elevation, slope degree, slope aspect, curvature, relief, engineering geological lithology, landform types, land use, distance to rivers, as well as distance to roads) were selected for the multicollinearity analysis. The evaluation index system was established in the present research to assess the landslide susceptibility with the combination of traditional statistical methods and machine learning models. Both the information value-maximum entropy coupled model (I-MaxEnt) and the information value-logistic regression coupled model (I-LR) were proposed to assess landslide susceptibility in the Tianshan northern slope economic belt after the detailed evaluation on the information value model (I), logistic regression model (LR), and maximum entropy model (MaxEnt). Comparative discussions on the receiver operating characteristic (ROC)curves revealed that the area under the curve(AUC) values of the I-MaxEnt and I-LR coupled models were 0.907 and 0.941, respectively, indicating the superior accuracy of the I-LR model. Furthermore, the results obtained from the I-LR model were more consistent with the actual situation as verified by field validation. That is, the I-LR model is much more suitable in assessing the landslide susceptibility in the given research region attributed to its high accuracy and reliability.The results of this research provide a reliable basis for disaster prevention and mitigation in this study area.

Effect of stratospheric aerosol injection on marine heatwave events off the coast of South Africa

PMA-qPCA: Accelerating the market release of high-quality Bradyrhizobium diazoefficiens inoculant

Traditional culture-based quantification of Bradyrhizobium diazoefficiens in inoculants presents significant limitations due to its labor-intensive and time-consuming nature. To address this limitation, we aimed to validate a propidium monoazide quantitative PCR (PMA-qPCR) assay as a rapid and reliable alternative for estimating Bradyrhizobium diazoefficiens counts in commercial inoculants. Key experiments optimized PMA concentration (50, 75 and 100 µM) to selectively inhibit DNA amplification from non-viable cells without interfering with viable cell signal. Assay´s efficiency, limit of detection and quantification, intra-assay repeatability and inter-assay reproducibility were determined. The assay demonstrated high efficiency (90–105%), a limit of detection (LOD) of 3.14 log CFU/mL, and a dynamic range from 8.74 to 3.14 log CFU/mL. Robust intra-assay repeatability (SD < 0.3) and inter-assay reproducibility (CV < 10%) were confirmed. The method successfully distinguished quarter-strength and 10-fold serial dilutions of viable bacteria, even in the presence of non-viable cells. Final validation against standard plate counting showed a strong linear correlation with an R² of 0.82. Crucially, this PMA-qPCR assay reduced processing time from 120 hours to just 5 hours, offering a significant improvement in turnaround time while maintaining strong agreement with the reference method. This study marks the first application of PMA-qPCR for Bradyrhizobium diazoefficiens quantification in inoculants, highlighting its potential as a high-throughput tool to enhance efficiency and precision for industrial batch-to-batch quality control.